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Design patterns have gained popularity as they provide strategies for solving specific problems. This paper explores two common design patterns in iOS development field: Model View Controller (MVC) and Model View ViewModel (MVVM) design patterns. The paper investigates the problems with MVC design pattern. Then, it introduces a validation model that detects MVC problems, and helps programmers make the decision to switch between MVC and MVVM design pattern. The proposed validation model consists of two phases: phase one is to detect MVC problems, and phase two is to validate the relation between MVVM objects. The model was then applied to a Cloudy app as a case study. As a result, the model was able to detect MVC problems. The relation between MVVM objects was also validated. Further, this research provided some recommended solutions to satisfy the relations between MVVM objects in the project. [ABSTRACT FROM AUTHOR]

The problem of the longest common subsequence is a classical distance measure for strings. There have been several attempts to accommodate longest common subsequences along with some other distance measures. There are a large number of different variants of the problem. In this paper, we consider the constrained longest common subsequence problem for two strings and arbitrary number of constraints. In particular, we consider an explicit reduction from the problem to the satisfiability problem and present experimental results for different satisfiability algorithms. It should be noted that different regularities in experimentally obtained data reveal important information about the underlying physical system. In this paper, we consider the problem of systematic monitoring of passenger flows. In particular, we use constrained longest common subsequences for tracking the image features. [ABSTRACT FROM AUTHOR]

This paper presents a linear space algorithm for finding a longest common increasing subsequence of two given input sequences in a very succinct way. The simple linear space algorithm based on a new formula can find a longest common increasing subsequence of sizes n and m respectively, in time O(nm) using O(n + m) space. [ABSTRACT FROM AUTHOR]

High performance computing is facing a major challenge due to its increasing failure rate. Fault tolerance needs to be used to ensure the efficient progress and correct termination of its applications when failures occur. In this paper, the divisible load fault-tolerant scheduling problem on the homogeneous distributed system is addressed, where communication is in the non-blocking message receiving mode, and both processors and communication links have the same speed and start-up overhead. First, the workload for each processor has been derived with the fault checkout overhead and checkout time consumption taken into account. Second, a checkout strategy which works better for divisible loads has been employed to reduce time consumption and checkout overhead. Third, an efficient algorithm for fault workload redistribution has been proposed. Finally, some simulation experiments have been conducted. The result shows that the proposed algorithm is effective. It can minimize the expected execution time and reduce the time consumed by fault-tolerance. [ABSTRACT FROM AUTHOR]

In this paper, the adaptive synchronization of fractional-order muscular blood vessel (MBV) model subject to input nonlinearity is investigated. The parameters of controlled systems are assumed to be unknown in advance, moreover, the effects of model uncertainties and external disturbances are fully taken into account. On the basis of frequency distributed fractional integrator model and Lyapunov stability theory, a robust control law and fractional-order type parametric update laws are designed to ensure the synchronization. Simulation results demonstrate that the proposed control scheme can steer the abnormal muscular vessel into normal orbit with good robustness. [ABSTRACT FROM AUTHOR]

Hand posture segmentation is an important step in hand posture recognition process, which aims to eliminate the interference from other elements in an image, and get the hand posture region precisely. In this paper, we propose a hand segmentation method based on saliency and skin colour detection. This method mainly consists of a pixel-level hand detection method, a region-level hand detection method, and a multiple saliency maps fusion framework, thereby achieving the deep integration of the bottom-up saliency information and top-down skin colour information. Experimental results show that the proposed method has excellent performance, and is reliable against cluttered backgrounds. Moreover, evaluations based on comparisons with other approaches of the literature have demonstrated its effectiveness. [ABSTRACT FROM AUTHOR]

Real-time deferrable server (RTDS) scheduler is an experimental CPU scheduler for Xen virtualization systems since version 4.5. Under RTDS, each virtual CPU (VCPU) is guaranteed to have a predefined amount of physical CPU (PCPU) capacity so that the performance can be better predicted. However, the guaranteed capacity might not fit the requirement of a VCPU at the run-time because it is defined offline. Therefore, the performance of virtual machines (VMs) might be deteriorated at the run-time. In this paper, an RTDSbased CPU scheduler is proposed, called enhanced real-time deferrable server (ERTDS), to provide an additional amount of PCPU capacity to a VCPU when its run-time requirement is higher than expected. We have implemented ERTDS in Xen version 4.7 and a series of experiments has been conducted for which we have some encouraging results. [ABSTRACT FROM AUTHOR]

Flower pollination algorithm (FPA) is a new swarm intelligence optimization algorithm which simulates flower pollination. For all intelligent optimization algorithms, the performance analysis of parameters can affect the convergence speed, convergence precision and global optimization ability. In this paper, an enhanced variation of flower pollination algorithm (MFPA) was proposed. The convergence speed and algorithm searching precision are determined by the switching probability andƛin Levy flight. The simulation experiments are carried out by using the six typical test functions to discuss this influence. The simulation results show that the switching probability is less sensitive to the MPFA algorithm. With reasonable setting of MFPA parameters, the search precision and convergence speed can be improved effectively. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method for enhancing of speech corrupted by broadband noise. The method is based on the spectral subtraction technique. Performance of spectral subtraction, its limitations, artifacts introduced by it, and spectral subtraction modifications for eliminating these artifacts are discussed in the paper in details. To eliminate the musical noise, one of the artifacts introduced by conventional spectral subtraction, we propose to implement reduced varying scaling factor of spectral subtraction, with a following application of weighted function. Weighting function, used in the proposed algorithm, attenuates frequency spectrum components lying outside identified formants regions. The algorithm effects a substantial reduction of the musical noise without significantly distorting the speech. Listening tests were performed to determinate the subjective quality and intelligibility of speech enhanced by our method. Proposed noise reduction algorithm is compared to conventional spectral subtraction based on SNR improvement introduced by them. Spectrograms of speech, enhanced by the proposed algorithm and other modified spectral subtraction algorithms, which show the algorithms performance and degree of speech distortion, are also presented in the paper. [ABSTRACT FROM AUTHOR]

This paper discusses the positive impact of soft vector quantization on the performance of machine-learning systems that include one or more vector quantization modules. The most impactful gains here are avoiding over-fitting and boosting the robustness of such systems in the presence of considerable parasitic variance; e.g. noise, in the runtime inputs. The paper then introduces a soft vector quantization scheme with inverse power-function distributions, and analytically derives an upper bound of its relative quantization noise energy to that of typical (hard-deciding) vector quantization. This relative noise is expressed as a closed-form function of the power in order to allow the selection of its optimal values of that compromise both a soft enough vector quantization with a stable performance via small enough relative quantization noise. Finally, we present empirical evidence obtained via experimenting with two versions of the best reported OCR system for cursive scripts - that happened to deploy discrete HMMs - one version with hard vector quantization and the other with our herein presented soft quantization. Test samples of real-life scanned Arabic text pages are used to challenge both versions; hence the recognition error margins are compared. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the bounds of the fixed common step-size parameter μGMDF for the generalized multidelay adaptive filter (GMDF). Frequency domain adaptive filters are attractive in applications requiring a large number of coefficients such as acoustic echo cancellation (AEC). However, the very restrictive convergence bound for block LMS has limited its usefulness. Derivations on step-size bounds for the partitioned frequency-domain block LMS have been reported recently, but are not consistent with each other. Contrary to other researchers' work, this paper derives a not-so-restrictive step-size bound that supports a stable GMDF. We also derive relations of step-size parameters for NLMS and GMDF to have similar convergence properties. The results of extensive simulation experiments are included in the paper. These results show the bounds and the convergence behavior predicted by the analysis is in very good agreement with the experimental results. [ABSTRACT FROM AUTHOR]

This paper presents the importance of formulating general discrete-time model representations for current pathway deterministic modeling study. Discrete-time models can be considered as a link between continuous-time kinetic reactions and discrete-time experimentation as well as computer based simulation and analysis. In the paper, different discretization techniques are investigated according to different sorts of ODE model structures. Two discretization strategies are mainly focused, that are one-step Taylor/Lie series based method and multi-step Runge-Kutta method. A new discretization approach based on Taylor expansion and Carleman linearization is proposed for bilinear in states pathway models. Finally, the superiority of using Runge-Kutta based approach as general discrete-time model representations are concluded. [ABSTRACT FROM AUTHOR]

This paper is to clarify ontologies in knowledge base compare with object models in object oriented software engineering. Ontology itself has the concept which is the foundation of knowledge base; on the other hand The object model is the center of object oriented software engineering. Because ontologies are closely related to modern object-oriented software design, it is natural to adapt existing object-oriented software development methodologies for the task of ontology development. Selected approaches originate from research in artificial intelligence; knowledge representation and object modeling are presented in this paper. Some issues mentioned in this paper are related with their connection; some are addressed directly into the similarities or differences point of view of both. This paper also presents the available tools, methods, procedures which show the corporation with object modeling and ontologies. [ABSTRACT FROM AUTHOR]

Understanding the characteristics of workloads is extremely important in the hardware and software design of computer systems. Better metrics and methods for evaluating workloads are continually needed. Here we propose a quantitative metric, namely RDCC (Ratio of Dynamic Computation to Control operations), for evaluating workloads. The RDCC values of a great many benchmarks are measured in various conditions. The evaluation results indicate that the intrinsic properties of the application can be marked with the RDCC value. The applications with lower RDCC values contain more control operations and less computational operations. In contrast, the applications with higher RDCC values consist of less control operations and more computational operations. In addition, the RDCC value of one application is relatively stable with different compiler optimizations and inputs. Furthermore, this paper presents a quantitative approach for identifying computation-intensive and control-intensive applications by RDCC values, and provides five levels of classification based on the K-means clustering of RDCC values. The feasibility is verified by many evaluation results. Therefore, RDCC can be used as a metric to identify and evaluate the characteristics of applications and is much helpful for the design of high-efficiency processor architecture and software optimization. [ABSTRACT FROM AUTHOR]

A large number of landmarks selection techniques has been proposed. However, finding optimal solutions requires to solve some hard problems. In this paper, we consider the ρ- minimum overlapping region decomposition problem that was proposed for landmarks selection. This problem is NP-complete. We describe an approach to solve the problem optimally. This approach is based on an explicit reduction from the problem to the satisfiability problem. Also, we consider some greedy algorithms for solution of the problem. [ABSTRACT FROM AUTHOR]

Arc-annotated sequences are useful in representing the structural information of RNA and protein sequences. In particular, arc-annotated sequences are useful in describing the secondary and tertiary structures of RNA and protein sequences. Structure comparison for RNA and for protein sequences has become a central computational problem bearing many challenging computer science questions. The longest arcpreserving common subsequence problem has been introduced as a framework for studying the similarity of arc-annotated sequences. It is a sound and meaningful mathematical formalization of comparing the secondary structures of molecular sequences. In this paper, we consider two special cases of the longest arc-preserving common subsequence problem, c- fragment LAPCS (unlimited, plain), c-fragment LAPCS (unlimited, unlimited). In particular, we consider a parameterized version of the 1-fragment LAPCS (unlimited, plain) problem, parameterized by the length l of the desired subsequence. We show W[1]-completeness of the problem. Also, we describe an approach to solve c-fragment LAPCS (unlimited, unlimited). This approach is based on constructing logical models for the problem. [ABSTRACT FROM AUTHOR]

In this paper, a new fast and efficient algorithm capable in removing Gaussian noise with less computational complexity is presented. The algorithm initially estimates the amount of noise corruption from the noise corrupted image. In the second stage, the center pixel is replaced by the mean value of the some of the surrounding pixels based on a threshold value. Noise removing with edge preservation and computational complexity are two conflicting parameters. The proposed method is an optimum solution for these requirements. The performance of the algorithm is tested and compared with standard mean filter, wiener filter, alpha trimmed mean filter K- means filter, bilateral filter and recently proposed trilateral filter. Experimental results show the superior performance of the proposed filtering algorithm compared to the other standard algorithms in terms of both subjective and objective evaluations. The proposed method removes Gaussian noise and the edges are better preserved with less computational complexity and this aspect makes it easy to implement in hardware. [ABSTRACT FROM AUTHOR]

A number of successful implementation of Multiple-Valued Logic (MVL) circuits using Very Large Scale Integration (VLSI) technology has been reported in the literature. The Ant Colony (ACO) optimization algorithm is a meta-heuristic that mimics the ants' behavior in finding the shortest path to reach food sources. We have previously introduced ACO-based heuristic for synthesis of two-level MVL functions. In this paper, we introduce a hybrid ACO-Direct Cover (DC) technique for synthesis of multi-level MVL functions. In this technique, we use ants to decompose the given MVL function into a number of levels and synthesize each sub-function using a DC-based technique. A benchmark set consisting of 50000 randomly generated 2-varaible 4-valued functions is used to compare the results obtained using the proposed approach with those obtained using existing techniques. It is shown that on average the proposed hybrid technique produces more efficient realizations in terms of the chip area consumed in synthesizing a given MVL function. [ABSTRACT FROM AUTHOR]

FinFET, which is a double-gate field effect transistor (DGFET), is more versatile than traditional single-gate field effect transistors because it has two gates that can be controlled independently. Usually, the second gate of FinFETs is used to dynamically control the threshold voltage of the first gate in order to improve circuit performance and reduce leakage power. However, we can also utilize the second gate to implement circuits with fewer transistors. This is important since area efficiency is one of the main concerns in modern circuit design. In this paper, a methodology for effectively synthesizing logic circuits using both gates of FinFETs as inputs is presented. Simulation results show that independent-gate FinFET circuit implementation has significant advantages over single-gate FinFET circuit implementation in terms of power consumption and cell area. [ABSTRACT FROM AUTHOR]

In large parking areas such as those at mega shopping malls or stadiums, drivers always have difficulty to find vacant carpark lots especially during peak periods or when the parking lots are almost full. A solution to reduce the drivers' searching time for vacant car-park lots will greatly save time, reduce cost and improve the traffic flow in the car park areas. In this paper, a research project which was developed to acquire car-park occupancy information using integrated approach of image processing algorithms is presented. Motivation for developing this system came from the fact that minimum cost is involved because image processing technique is used rather than sensor-based techniques. Security surveillance cameras which are readily available in most car parks can be used to acquire the images of the car park. This solution is much cost effective than installing sensor on each parking lot. This project is called as Car-Park Occupancy Information System (COINS), and it was tested using simulation model and also in real-case scenarios. [ABSTRACT FROM AUTHOR]

In this paper, we cast the segmentation problem as the maximization of cognate information between the row and column pairs of the neighborhood. For this, the maximum and minimum gradient on pairs of row and column of the local neighborhood are calculated and applied on the original image. The maximum and minimum row and column pair of the local neighborhood forms the contribution of primitive morphological operations, dilation and erosion respectively. For extracting strong edges edge increase and edge decrease are applied on local neighborhood. The final segmentation is obtained after applying the above preprocessing steps by using a new approach of cognate neighborhood. To test the above process of segmentation the method is applied on brodatz textures, leena and brain MRI images, which resulted a good segmentation. [ABSTRACT FROM AUTHOR]

Embedded zero-tree coding in wavelet domain has drawn a lot of attention to the image compression applications. Among noteworthy zero-tree algorithms is the SPIHT algorithm. For images with textures, high frequency wavelet coefficients are likely to become significant after few scan passes of SPIHT, and therefore the coding results are often insufficient. It is desirable that the low frequency and high frequency components of an image are coded using different strategies. In this paper, we propose a hybrid algorithm using SPIHT and EBC (embedded block coding) to code low frequency and high frequency wavelet coefficients, respectively; the intermediate coding results of low frequency coefficients are used to facilitate the coding operation of high frequency coefficients. Experimental results show that the coding performance can be significantly improved by the hybrid SPIHT-EBC algorithm. [ABSTRACT FROM AUTHOR]

This paper describes XML externalization built into compiler front-ends and its application to quick reverse engineering tool development. A parser generator MoJay was developed to build XML externalization functionality into compiler front-ends. After replacing the original parser generator with MoJay, generating a parser using it, and modifying a few lines of source code in the compiler, we were able to obtain a special compiler that externalizes three types of information in the form of XML documents, namely, lexical information, syntactic information, and parse tree. The syntactic information was applied to develop a reverse engineering tool for C#. The tool shows a performance penalty from the viewpoint of the generated XML document size. However, even with a storage penalty, the quick development is far superior option. [ABSTRACT FROM AUTHOR]

The research community and the IT industry have invested significant effort in fighting spam emails. There are many different approaches, ranging from white listing, black listing, reputation ranking, postage, legislation, and content scanning etc. Until every ISP obeys the same rules, content scanning based spam email filters still have a significant role to play in fighting spam emails. There are many content scanning based spam email filters available and also in operation. Yet we are still inundated with spam emails everyday. This is not because the filters are not powerful enough, but because the filtering systems are not flexible enough to adapt the new development of spam techniques, such as HTML tagging, image based spam, and keyword obfuscating etc. In this paper, we propose to use dynamic multiple normalizers as the preprocessors for spam filters. The normalizers convert an email to its plain text format, called normalization. With the help of the normalizers, spam filters only need to deal with plain text format, which is what the filters are good at. The flexibility of the proposed architecture does not only make the adoption to the new creations of spammers easier but also makes the integration to the other spam fighting technologies easier. [ABSTRACT FROM AUTHOR]

We had previously proposed an outstanding evolutionary method, Automatically Defined Groups (ADG), for generating heterogeneous cooperative agents, and then we had developed a rule extraction algorithm from computer log files using ADG. In this algorithm, agents search multiple errordetection rules cooperatively based on the difference between normal state log files and abnormal state log files. The more frequent applicable and the more accurate the error-detection rule is, the more agents are allocated for searching the rule. Therefore, the number of agents allocated for each rule can represent the important degree of the rule. However, when the rule extraction method was applied to the large scale log files, which may have a number of latent rules, a problematic situation on the number of agents could be observed. In the previous proposed method, the number of agents is not adaptive, therefore the number of agents may be lack for evaluating the each rule's importance minutely. In this paper, we propose an improved method, where the number of agents is adaptively increased depending on the discovered rules. As a result, the importance of respective rules could be evaluated minutely by increasing the number of agents. In addition, the proposed method could acquire more rules than those by the method with the fixed number of agents. [ABSTRACT FROM AUTHOR]

Routing in wireless sensor networks is a demanding task. This demand has led to a number of routing protocols which efficiently utilize the limited resources available at the sensor nodes. All these protocols typically find the minimum energy path. In this paper we take a view that, always using the minimum energy path deprives the nodes energy quickly and the time taken to determine an alternate path increases. Multipath routing schemes distribute traffic among multiple paths instead of routing all the traffic along a single path. Two key questions that arise in multipath routing are how many paths are needed and how to select these paths. Clearly, the number and the quality of the paths selected dictate the performance of a multipath routing scheme. We propose an energy efficient adaptive multipath routing technique which utilizes multiple paths between source and the sink, adaptive because they have low routing overhead. This protocol is intended to provide a reliable transmission environment with low energy consumption, by efficiently utilizing the energy availability and the received signal strength of the nodes to identify multiple routes to the destination. Simulation results show that the energy efficient adaptive multipath routing scheme achieves much higher performance than the classical routing protocols, even in the presence of high node density and overcomes simultaneous packet forwarding. [ABSTRACT FROM AUTHOR]

Communication protocol conformance testing has become more complex as protocols have grown larger. The study of design for testability (DFT) is a research area to help overcoming the ever increasing complexity of testing distributed systems. In the previous research, we introduced a new metric for testability of communication protocols, demonstrated the usefulness of the metric for identifying faults that are more difficult to detect, and also presented the approach for improved testability without modifying the protocol structure by means of unique input/output (UIO) sequences. Since a UIO sequence may not exist for every state of some protocol specification finite state machines (FSMs), in this paper, we extend UIO sequence to a new general concept called narrow input/output (NIO) sequence. We demonstrate the effectiveness of NIO sequence application on the improvement of protocol testability. [ABSTRACT FROM AUTHOR]

This paper proposes an authentication approach to support multi-clients in using a multi-application based environment. The approach is primarily based on the public key infrastructure (PKI) authentication scheme and the multi-agent technique. A key pair and a certificate issued by the Certification Authority (CA) are normally kept in a smart card or a token in order to enforce two-factor authentication. Both key pair and certificate are deployed to encrypt/decrypt electronic data or transaction, or sign/authenticate the sender and the recipient. We apply the Single Sign-On (SSO) and the Multi-Agent System (MAS) concepts to facilitate the authentication and the authorization process in order to work with multi-applications and multi-clients more dynamically and efficiently. The agent system functions when each client requests to sign on and it is responsible for validating a client certificate, granting an access role to the client, and controlling a concurrent use of applications. [ABSTRACT FROM AUTHOR]