Transformation Method CIM to PIM: From Business Processes Models Defined in BPMN to Use Case and Class Models Defined in UML

This paper proposes a method to automatic transformation of CIM level to PIM level respecting the MDA approach. Our proposal is based on creating a good CIM level through well-defined rules allowing as achieving rich models that contain relevant information to facilitate the task of the transformation to the PIM level. We define, thereafter, an appropriate PIM level through various UML diagram. Next, we propose set rules to move from CIM to PIM. Our method follows the MDA approach by considering the business dimension in the CIM level through the use BPMN, standard modeling business of OMG, and the use of UML in PIM advocated by MDA in this level.

Service-Based Application Adaptation Strategies: A Survey

Service Oriented Architecture (SOA) allows modeling of dynamic interaction between incongruous providers, which enables governing the development of complex applications. However, implementation of SOA comes with some challenges, including its adaptability and robustness. Dynamism is inherent to the nature of service based applications and of their running environment. These factors lead to necessity for dynamic adaptation. In this paper we try to describe basics and main structure of SOA adaptation process with a conceptual view to this issue. In this survey we will review the relevant adaptation approaches. This paper allows studying how different approaches deal with service oriented architecture adaptation life-cycle and provides basic guidelines for their analysis, evaluation and comparison.

Research and Development of Net-Centric Information Sharing Platform

Compared with traditional distributed environment, the net-centric environment brings on more demanding challenges for information sharing with the characteristics of ultra-large scale and strong distribution, dynamic, autonomy, heterogeneity, redundancy. This paper realizes an information sharing model and a series of core services, through which provides an open, flexible and scalable information sharing platform.

The Customization of 3D Last Form Design Based On Weighted Blending

When it comes to last, it is regarded as the critical foundation of shoe design and development. Not only the last relates to the comfort of shoes wearing but also it aids the production of shoe styling and manufacturing. In order to enhance the efficiency and application of last development, a computer aided methodology for customized last form designs is proposed in this study. The reverse engineering is mainly applied to the process of scanning for the last form. Then the minimum energy is used for the revision of surface continuity, the surface of the last is reconstructed with the feature curves of the scanned last. When the surface of a last is reconstructed, based on the foundation of the proposed last form reconstruction module, the weighted arithmetic mean method is applied to the calculation on the shape morphing which differs from the grading for the control mesh of last, and the algorithm of subdivision is used to create the surface of last mesh, thus the feet-fitting 3D last form of different sizes is generated from its original form feature with functions remained. Finally, the practicability of the proposed methodology is verified through later case studies.

Grid Artifacts Suppression in Computed Radiographic Images

Anti-scatter grids used in radiographic imaging for the contrast enhancement leave specific artifacts. Those artifacts may be visible or may cause Moiré effect when digital image is resized on a diagnostic monitor. In this paper we propose an automated grid artifactsdetection and suppression algorithm which is still an actual problem. Grid artifacts detection is based on statistical approach in spatial domain. Grid artifacts suppression is based on Kaiser bandstop filter transfer function design and application avoiding ringing artifacts. Experimental results are discussed and concluded with description of advantages over existing approaches.

Determination of the Concentrated State Using Multiple EEG Channels

Analysis of EEG brainwave provides information on mental or emotional states. One of the particular states that can have various applications in human machine interface (HMI) is concentration. 8-channel EEG signals were measured and analyzed. The concentration index was compared during resting and concentrating periods. Among eight channels, locations the frontal lobe (Fp1 and Fp2) showed a clear increase of the concentration index during concentration regardless of subjects. The rest six channels produced conflicting observations depending on subjects. At this time, it is not clear whether individual difference or how to concentrate made these results for the rest six channels. Nevertheless, it is expected that Fp1 and Fp2 are promising locations for extracting control signal for HMI applications.

Intelligent Assistive Methods for Diagnosis of Rheumatoid Arthritis Using Histogram Smoothing and Feature Extraction of Bone Images

Advances in the field of image processing envision a new era of evaluation techniques and application of procedures in various different fields. One such field being considered is the biomedical field for prognosis as well as diagnosis of diseases. This plethora of methods though provides a wide range of options to select from, it also proves confusion in selecting the apt process and also in finding which one is more suitable. Our objective is to use a series of techniques on bone scans, so as to detect the occurrence of rheumatoid arthritis (RA) as accurately as possible. Amongst other techniques existing in the field our proposed system tends to be more effective as it depends on new methodologies that have been proved to be better and more consistent than others. Computer aided diagnosis will provide more accurate and infallible rate of consistency that will help to improve the efficiency of the system. The image first undergoes histogram smoothing and specification, morphing operation, boundary detection by edge following algorithm and finally image subtraction to determine the presence of rheumatoid arthritis in a more efficient and effective way. Using preprocessing noises are removed from images and using segmentation, region of interest is found and Histogram smoothing is applied for a specific portion of the images. Gray level co-occurrence matrix (GLCM) features like Mean, Median, Energy, Correlation, Bone Mineral Density (BMD) and etc. After finding all the features it stores in the database. This dataset is trained with inflamed and noninflamed values and with the help of neural network all the new images are checked properly for their status and Rough set is implemented for further reduction.

Human Tracking across Heterogeneous Systems Based On Mobile Agent Technologies

In a human tracking system, expanding a monitoring range of one system is complicating the management of devices and increasing its cost. Therefore, we propose a method to realize a wide-range human tracking by connecting small systems. In this paper, we examined an agent deploy method and information contents across the heterogeneous human tracking systems. By implementing the proposed method, we can construct a human tracking system across heterogeneous systems, and the system can track a target continuously between systems.

Enhanced Traffic Light Detection Method Using Geometry Information

In this paper, we propose a method that allows faster and more accurate detection of traffic lights by a vision sensor during driving, DGPS is used to obtain physical location of a traffic light, extract from the image information of the vision sensor only the traffic light area at this location and ascertain if the sign is in operation and determine its form. This method can solve the problem in existing research where low visibility at night or reflection under bright light makes it difficult to recognize the form of traffic light, thus making driving unstable. We compared our success rate of traffic light recognition in day and night road environments. Compared to previous researches, it showed similar performance during the day but 50% improvement at night.

Weighted Data Replication Strategy for Data Grid Considering Economic Approach

Data Grid is a geographically distributed environment that deals with data intensive application in scientific and enterprise computing. Data replication is a common method used to achieve efficient and fault-tolerant data access in Grids. In this paper, a dynamic data replication strategy, called Enhanced Latest Access Largest Weight (ELALW) is proposed. This strategy is an enhanced version of Latest Access Largest Weight strategy. However, replication should be used wisely because the storage capacity of each Grid site is limited. Thus, it is important to design an effective strategy for the replication replacement task. ELALW replaces replicas based on the number of requests in future, the size of the replica, and the number of copies of the file. It also improves access latency by selecting the best replica when various sites hold replicas. The proposed replica selection selects the best replica location from among the many replicas based on response time that can be determined by considering the data transfer time, the storage access latency, the replica requests that waiting in the storage queue and the distance between nodes. Simulation results utilizing the OptorSim show our replication strategy achieve better performance overall than other strategies in terms of job execution time, effective network usage and storage resource usage.

An Enhanced SAR-Based Tsunami Detection System

Tsunami early detection and warning systems have proved to be of ultimate importance, especially after the destructive tsunami that hit Japan in March 2012. Such systems are crucial to inform the authorities of any risk of a tsunami and of the degree of its danger in order to make the right decision and notify the public of the actions they need to take to save their lives. The purpose of this research is to enhance existing tsunami detection and warning systems. We first propose an automated and miniaturized model of an early tsunami detection and warning system. The model for the operation of a tsunami warning system is simulated using the data acquisition toolbox of Matlab and measurements acquired from specified internet pages due to the lack of the required real-life sensors, both seismic and hydrologic, and building a graphical user interface for the system. In the second phase of this work, we implement various satellite image filtering schemes to enhance the acquired synthetic aperture radar images of the tsunami affected region that are masked by speckle noise. This enables us to conduct a post-tsunami damage extent study and calculate the percentage damage. We conclude by proposing improvements to the existing telecommunication infrastructure of existing warning tsunami systems using a migration to IP-based networks and fiber optics links.

Loudspeaker Parameters Inverse Problem for Improving Sound Frequency Response Simulation

The sound pressure level (SPL) of the moving-coil loudspeaker (MCL) is often simulated and analyzed using the lumped parameter model. However, the SPL of a MCL cannot be simulated precisely in the high frequency region, because the value of cone effective area is changed due to the geometry variation in different mode shapes, it is also related to affect the acoustic radiation mass and resistance. Herein, the paper presents the inverse method which has a high ability to measure the value of cone effective area in various frequency points, also can estimate the MCL electroacoustic parameters simultaneously. The proposed inverse method comprises the direct problem, adjoint problem, and sensitivity problem in collaboration with nonlinear conjugate gradient method. Estimated values from the inverse method are validated experimentally which compared with the measured SPL curve result. Results presented in this paper not only improve the accuracy of lumped parameter model but also provide the valuable information on loudspeaker cone design.

Spatial Audio Player Using Musical Genre Classification

In this paper, we propose a smart music player that combines the musical genre classification and the spatial audio processing. The musical genre is classified based on content analysis of the musical segment detected from the audio stream. In parallel with the classification, the spatial audio quality is achieved by adding an artificial reverberation in a virtual acoustic space to the input mono sound. Thereafter, the spatial sound is boosted with the given frequency gains based on the musical genre when played back. Experiments measured the accuracy of detecting the musical segment from the audio stream and its musical genre classification. A listening test was performed based on the virtual acoustic space based spatial audio processing.

Fractional Order Feedback Control of a Ball and Beam System

In this paper, fractional order feedback control of a ball beam model is investigated. The ball beam model is a particular example of the double Integrator system having strongly nonlinear characteristics and unstable dynamics which make the control of such system a challenging task. Most of the work in fractional order control systems are in theoretical nature and controller design and its implementation in practice is very small. In this work, a successful attempt has been made to design a fractional order PIλDμcontroller for a benchmark laboratory ball and beam model. Better performance can be achieved using a fractional order PID controller and it is demonstrated through simulations results with a comparison to the classic PID controller.

A Combined Meta-Heuristic with Hyper-Heuristic Approach to Single Machine Production Scheduling Problem

This paper is concerned with minimization of mean tardiness and flow time in a real single machine production scheduling problem. Two variants of genetic algorithm as metaheuristic are combined with hyper-heuristic approach are proposed to solve this problem. These methods are used to solve instances generated with real world data from a company. Encouraging results are reported.

The SEMONT Monitoring and Risk Assessment of Environmental EMF Pollution

Wireless communications have been expanded very fast in recent decades. This technology relies on an extensive network of base stations and antennas, using radio frequency signals to transmit information. Devices that use wireless communication, while offering various services, basically act as sources of non-ionizing electromagnetic fields (EMF). Such devices are permanently present in human vicinity and almost constantly radiate, causing EMF pollution of the environment. This fact has initiated development of modern systems for observation of the EMF pollution, as well as for risk assessment. This paper presents the Serbian electromagnetic field monitoring network – SEMONT, designed for automated, remote and continuous broadband monitoring of EMF in the environment. Measurement results of the SEMONT monitoring at one of the test locations, within the main campus of the University of Novi Sad, are presented and discussed, along with corresponding exposure assessment of the general population, regarding the Serbian legislation.

CDM Controller Order and Disturbance Rejection Ability

The coefficient diagram method is primarily an algebraic control design method whose objective is to easily obtain a good controller with minimum user effort. As a matter of fact, if a system model, in the form of linear differential equations, is known, the user only need to define a time-constant and the controller order. The later can be established regarding the expected disturbance type via a lookup table first published by Koksal and Hamamci in 2004. However an inaccuracy in this table was detected and pointed-out in the present work. Moreover the above mentioned table was expanded in order to enclose any k order type disturbance.

Development of Web-Based Remote Desktop to Provide Adaptive User Interfaces in Cloud Platform

Cloud virtualization technologies are becoming more and more prevalent, cloud users usually encounter the problem of how to access to the virtualized remote desktops easily over the web without requiring the installation of special clients. To resolve this issue, we took advantage of the HTML5 technology and developed web-based remote desktop. It permits users to access the terminal which running in our cloud platform from anywhere. We implemented a sketch of web interface following the cloud computing concept that seeks to enable collaboration and communication among users for high performance computing. Given the development of remote desktop virtualization, it allows to shift the user’s desktop from the traditional PC environment to the cloud platform, which is stored on a remote virtual machine rather than locally. This proposed effort has the potential to positively provide an efficient, resilience and elastic environment for online cloud service. This is also made possible by the low administrative costs as well as relatively inexpensive end-user terminals and reduced energy expenses.

Intrabody Communication Using Different Ground Configurations in Digital Door Lock

Intrabody communication (IBC) is a new way of transferring data using human body as a medium. Minute current can travel though human body without any harm. IBC can remove electrical wires for human area network. IBC can be also a secure communication network system unlike wireless networks which can be accessed by anyone with bad intentions. One of the IBC systems is based on frequency shift keying modulation where individual data are transmitted to the external devices for the purpose of secure access such as digital door lock. It was found that the quality of IBC data transmission was heavily dependent on ground configurations of electronic circuits. Reliable IBC transmissions were not possible when both of the transmitter and receiver used batteries as circuit power source. Transmission was reliable when power supplies were used as power source for both transmitting and receiving sites because the common ground was established through the grounds of instruments such as power supply and oscilloscope. This was due to transmission dipole size and the ground effects of floor and AC power line. If one site used battery as power source and the other site used the AC power as circuit power source, transmission was possible.

Brainwave Classification for Brain Balancing Index (BBI) via 3D EEG Model Using k-NN Technique

In this paper, the comparison between k-Nearest Neighbor (kNN) algorithms for classifying the 3D EEG model in brain balancing is presented. The EEG signal recording was conducted on 51 healthy subjects. Development of 3D EEG models involves pre-processing of raw EEG signals and construction of spectrogram images. Then, maximum PSD values were extracted as features from the model. There are three indexes for balanced brain; index 3, index 4 and index 5. There are significant different of the EEG signals due to the brain balancing index (BBI). Alpha-α (8–13 Hz) and beta-β (13–30 Hz) were used as input signals for the classification model. The k-NN classification result is 88.46% accuracy. These results proved that k-NN can be used in order to predict the brain balancing application.