Search results for: Task Graphs

Authors: Tosin Osasona

Abstract:

The Nigeria Police Force bears the constitutional mandate as the primary policing agency for the protection of life and property within Nigeria; however, the police have an historical ill-reputation for corruption, ineptitude and impunity. Using the institutional theory of police as the framework of analysis, the paper argues that the performance of the police in Nigeria mirrors the dominant political, social and economic institutions and the structural environment of the Nigerian state. The article puts in perspective the deliberate political decision to underfund the police, leaving officers of the force the extra task of foraging for funds to undertake the duty that the Nigeria state primarily exists for; the article further explores the nexus between corruption in the police in Nigeria and the issue of funding. The article finds that the Nigerian state, by deliberately under-funding the police, while expecting the agency to perform its duties, has indirectly sanctioned the corruption of the force and approved the cooption of the institution of police and policing for private use in Nigeria.

Keywords: Funding, policing, Nigeria Police Force, corruption.

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Authors: Felix Dobslaw

Abstract:

In this paper, a framework for the simplification and standardization of metaheuristic related parameter-tuning by applying a four phase methodology, utilizing Design of Experiments and Artificial Neural Networks, is presented. Metaheuristics are multipurpose problem solvers that are utilized on computational optimization problems for which no efficient problem specific algorithm exist. Their successful application to concrete problems requires the finding of a good initial parameter setting, which is a tedious and time consuming task. Recent research reveals the lack of approach when it comes to this so called parameter-tuning process. In the majority of publications, researchers do have a weak motivation for their respective choices, if any. Because initial parameter settings have a significant impact on the solutions quality, this course of action could lead to suboptimal experimental results, and thereby a fraudulent basis for the drawing of conclusions.

Keywords: Parameter-Tuning, Metaheuristics, Design of Experiments, Artificial Neural Networks.

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Authors: Majid Tolouei-Rad, Ankit Shah

Abstract:

Drilling is the most common machining operation and it forms the highest machining cost in many manufacturing activities including automotive engine production. The outcome of this operation depends upon many factors including utilization of proper cutting tool geometry, cutting tool material and the type of coating used to improve hardness and resistance to wear, and also cutting parameters. With the availability of a large array of tool geometries, materials and coatings, is has become a challenging task to select the best tool and cutting parameters that would result in the lowest machining cost or highest profit rate. This paper describes an algorithm developed to help achieve good performances in drilling operations by automatically determination of proper cutting tools and cutting parameters. It also helps determine machining sequences resulting in minimum tool changes that would eventually reduce machining time and cost where multiple tools are used.

Keywords: Cutting tool, drilling, machining, algorithm.

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Authors: R. K. Agrawal, Rajni Bala

Abstract:

Developing an accurate classifier for high dimensional microarray datasets is a challenging task due to availability of small sample size. Therefore, it is important to determine a set of relevant genes that classify the data well. Traditionally, gene selection method often selects the top ranked genes according to their discriminatory power. Often these genes are correlated with each other resulting in redundancy. In this paper, we have proposed a hybrid method using feature ranking and wrapper method (Genetic Algorithm with multiclass SVM) to identify a set of relevant genes that classify the data more accurately. A new fitness function for genetic algorithm is defined that focuses on selecting the smallest set of genes that provides maximum accuracy. Experiments have been carried on four well-known datasets1. The proposed method provides better results in comparison to the results found in the literature in terms of both classification accuracy and number of genes selected.

Keywords: Gene selection, genetic algorithm, microarray datasets, multi-class SVM.

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Authors: Koray U. Erbas

Abstract:

Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: Convolutional Neural Network, Deep Learning, Deep Learning Based FER, Facial Emotion Recognition.

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Authors: S. Saraç, F. Kara, C.Vural

Abstract:

High-frequency (HF) communications have been used by military organizations for more than 90 years. The opportunity of very long range communications without the need for advanced equipment makes HF a convenient and inexpensive alternative of satellite communications. Besides the advantages, voice and data transmission over HF is a challenging task, because the HF channel generally suffers from Doppler shift and spread, multi-path, cochannel interference, and many other sources of noise. In constructing an HF data modem, all these effects must be taken into account. STANAG 4539 is a NATO standard for high-speed data transmission over HF. It allows data rates up to 12800 bps over an HF channel of 3 kHz. In this work, an efficient implementation of STANAG 4539 on a single Texas Instruments- TMS320C6747 DSP chip is described. The state-of-the-art algorithms used in the receiver and the efficiency of the implementation enables real-time high-speed data / digitized voice transmission over poor HF channels.

Keywords: High frequency, modem, STANAG 4539.

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Authors: Majid Tolouei-Rad, Peter Kalivitis

Abstract:

Industrial robots become useless without end-effectors that for many instances are in the form of friction grippers. Commonly friction grippers apply frictional forces to different objects on the basis of programmers- experiences. This puts a limitation on the effectiveness of gripping force that may result in damaging the object. This paper describes various stages of design and development of a low cost sensor-based robotic gripper that would facilitate the task of applying right gripping forces to different objects. The gripper is also equipped with range sensors in order to avoid collisions of the gripper with objects. It is a fully functional automated pick and place gripper which can be used in many industrial applications. Yet it can also be altered or further developed in order to suit a larger number of industrial activities. The current design of gripper could lead to designing completely automated robot grippers able to improve the efficiency and productivity of industrial robots.

Keywords: Control system, end-effector, robot, sensor

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Authors: Sa’ed Abed, Mohammad H. Al Shayeji, Ovais Ahmed, Sahel Alouneh

Abstract:

Session Initiation Protocol (SIP) is a signaling layer protocol for building, adjusting and ending sessions among participants including Internet conferences, telephone calls and multimedia distribution. SIP facilitates user movement by proxying and forwarding requests to the present location of the user. In this paper, we provide a formal Specification and Description Language (SDL) and Message Sequence Chart (MSC) to model and define the Internet Engineering Task Force (IETF) SIP protocol and its sample services resulted from informal SIP specification. We create an “Abstract User Interface” using case analysis so that can be applied to identify SIP services more explicitly. The issued sample SIP features are then used as case scenarios; they are revised in MSCs format and validated to their corresponding SDL models.

Keywords: Modeling, MSC, SDL, SIP, validating.

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Authors: Amany M. El-Zonkoly, Hussein Desouki

Abstract:

Distance protection of transmission lines including advanced flexible AC transmission system (FACTS) devices has been a very challenging task. FACTS devices of interest in this paper are static synchronous series compensators (SSSC) and unified power flow controller (UPFC). In this paper, a new algorithm is proposed to detect and classify the fault and identify the fault position in a transmission line with respect to a FACTS device placed in the midpoint of the transmission line. Discrete wavelet transformation and wavelet entropy calculations are used to analyze during fault current and voltage signals of the compensated transmission line. The proposed algorithm is very simple and accurate in fault detection and classification. A variety of fault cases and simulation results are introduced to show the effectiveness of such algorithm.

Keywords: Entropy calculation, FACTS, SSSC, UPFC, wavelet transform.

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Authors: Igor Astrov, Mikhail Pikkov

Abstract:

This paper focuses on a critical component of the situational awareness (SA), the neural control of depth flight of an autonomous underwater vehicle (AUV). Constant depth flight is a challenging but important task for AUVs to achieve high level of autonomy under adverse conditions. With the SA strategy, we proposed a multirate neural control of an AUV trajectory using neural network model reference controller for a nontrivial mid-small size AUV "r2D4" stochastic model. This control system has been demonstrated and evaluated by simulation of diving maneuvers using software package Simulink. From the simulation results it can be seen that the chosen AUV model is stable in the presence of high noise, and also can be concluded that the fast SA of similar AUV systems with economy in energy of batteries can be asserted during the underwater missions in search-and-rescue operations.

Keywords: Autonomous underwater vehicles, multirate systems, neurocontrollers, situational awareness.

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Authors: Satish Kumar

Abstract:

The feature extraction method(s) used to recognize hand-printed characters play an important role in ICR applications. In order to achieve high recognition rate for a recognition system, the choice of a feature that suits for the given script is certainly an important task. Even if a new feature required to be designed for a given script, it is essential to know the recognition ability of the existing features for that script. Devanagari script is being used in various Indian languages besides Hindi the mother tongue of majority of Indians. This research examines a variety of feature extraction approaches, which have been used in various ICR/OCR applications, in context to Devanagari hand-printed script. The study is conducted theoretically and experimentally on more that 10 feature extraction methods. The various feature extraction methods have been evaluated on Devanagari hand-printed database comprising more than 25000 characters belonging to 43 alphabets. The recognition ability of the features have been evaluated using three classifiers i.e. k-NN, MLP and SVM.

Keywords: Features, Hand-printed, Devanagari, Classifier, Database

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Authors: Tanuj Kanchan, Anadi Gupta, Kewal Krishan

Abstract:

Human skull is shown to exhibit numerous sexually dimorphic traits. Estimation of sex is a challenging task especially when a part of skull is brought for medicolegal investigation. The present research was planned to evaluate the sexing potential of the dimensions of foramen magnum in forensic identification by craniometric analysis. Length and breadth of the foramen magnum was measured using Vernier calipers and the area of foramen magnum was calculated. The length, breadth, and area of foramen magnum were found to be larger in males than females. Sexual dimorphism index was calculated to estimate the sexing potential of each variable. The study observations are suggestive of the limited utility of the craniometric analysis of foramen magnum during the examination of skull and its parts in estimation of sex.

Keywords: Forensic Anthropology, Skeletal remains, Identification, Sex estimation, Foramen magnum.

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Authors: Kenny Raharjo, Ramon Lawrence

Abstract:

Game designers have the challenging task of building games that engage players to spend their time and money on the game. There are an infinite number of game variations and design choices, and it is hard to systematically determine game design choices that will have positive experiences for players. In this work, we demonstrate how multi-arm bandits can be used to automatically explore game design variations to achieve improved player metrics. The advantage of multi-arm bandits is that they allow for continuous experimentation and variation, intrinsically converge to the best solution, and require no special infrastructure to use beyond allowing minor game variations to be deployed to users for evaluation. A user study confirms that applying multi-arm bandits was successful in determining the preferred game variation with highest play time metrics and can be a useful technique in a game designer's toolkit.

Keywords: Game design, multi-arm bandit, design exploration and data mining, player metric optimization and analytics.

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Authors: S. Grace Sahaya Sheba, R. Omegala Priakumari

Abstract:

Polyethylene glycol (PEG) is a condensation polymer of ethylene oxide and water. It is soluble in water and in many organic solvents. PEG is used to make emulsifying agents, detergents, soaps, plasticizers, ointments etc. Ethanol (C₂H₅OH) also known as ethyl alcohol is a well-known organic compound and has wide applications in chemical industry as it is used as a solvent for paint, varnish, in preserving biological specimens, used as a fuel mixed with petrol etc. Though their chemical and physical properties are already studied, still because of their uses in day to day life the authors thought it is better to study some more of their physical properties like ultrasonic velocity and hence adiabatic compressibility, free length, etc. A detailed study of such properties and some excess parameters like excess adiabatic compressibility, excess free volume and few more in the liquid mixtures of these two compounds with PEG as a solute and Ethanol as a solvent at various mole fractions may throw some light on deeper understanding of molecular interaction between the solute and the solvent supported by NMR, IR etc. Hence the present research work is on ultrasonics/allied studies on these two liquid mixtures. Ultrasonic velocity (U), density (ρ) and viscosity (η) at room temperature and at different mole fraction from 0 to 0.055 of ethanol in PEG have been experimentally carried out by the authors. Acoustical parameters such as adiabatic compressibility (β), free volume (V_f), acoustic impedance (Z), internal pressure (π_i), intermolecular free length (L_f) and relaxation time (τ) were calculated from the experimental data. We have calculated excess parameters like excess adiabatic compressibility (β^E), excess internal pressure (π_i^E) free length (L_f^E) and excess acoustic impedance (Z^E) etc for these two chosen liquid mixtures. The excess compressibility is positive and maximum around a mole fraction 0.007 and excess internal pressure is negative and maximum at the same mole fraction and longer free length. The results are analyzed and it may be concluded that the molecular interactions between the solute and the solvent is not strong and it may be weak. Appropriate graphs are drawn.

Keywords: Adiabatic Compressibility, Binary mixture, Induce dipole, Polarizability, Ultrasonic.

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Authors: Sepehr Aslani, Homayoun Mahdavi-Nasab

Abstract:

Automated motion detection and tracking is a challenging task in traffic surveillance. In this paper, a system is developed to gather useful information from stationary cameras for detecting moving objects in digital videos. The moving detection and tracking system is developed based on optical flow estimation together with application and combination of various relevant computer vision and image processing techniques to enhance the process. To remove noises, median filter is used and the unwanted objects are removed by applying thresholding algorithms in morphological operations. Also the object type restrictions are set using blob analysis. The results show that the proposed system successfully detects and tracks moving objects in urban videos.

Keywords: Optical flow estimation, moving object detection, tracking, morphological operation, blob analysis.

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Authors: Santirat Nansaarng, Sittichai Kaewkuekool, Supreeya Siripattanakunkajorn

Abstract:

The purpose of this research was to study the inspector performance by using computer based training (CBT). Visual inspection task was printed circuit board (PCB) simulated on several types of defects. Subjects were 16 undergraduate randomly selected from King Mongkut-s University of Technology Thonburi and test for 20/20. Then, they were equally divided on performance into two groups (control and treatment groups) and were provided information before running the experiment. Only treatment group was provided feedback information after first experiment. Results revealed that treatment group was showed significantly difference at the level of 0.01. The treatment group showed high percentage on defects detected. Moreover, the attitude of inspectors on using the CBT to inspection was showed on good. These results have been showed that CBT could be used for training to improve inspector performance.

Keywords: Training, Feedback, Computer based Training (CBT)

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Authors: Milorad Pavlovic, Sebastiano Trevisani, Antonella Cecchi

Abstract:

In this paper, a procedure for the evaluation of seismic behavior of slender masonry structures (towers, bell towers, chimneys, minarets, etc.) is presented. The presented procedure is based on a full three-dimensional modal analyses and frequency measurements. As well-known, masonry is a composite material formed by bricks, or stone blocks, and mortar arranged more or less regularly and adopted for many centuries as structural material. Dynamic actions may represent the major risk of collapse of brickworks, and despite the progress achieved so far in science and mechanics; the assessment of their seismic performance remains a challenging task. Then, reliable physical and numerical models are worthy of recommendation. In this paper, attention is paid to the historical bell tower of the Basilica of Santa Maria Gloriosa dei Frari - usually called Frari - one of the greatest churches in Venice, Italy.

Keywords: Bell tower, FEM, masonry, modal analysis, non-destructive testing.

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Authors: Mohammed Alkahtani, Ali Ahmad, Saber Darmoul, Shatha Samman, Ayoub Al-zabidi, Khaled Ba Matraf

Abstract:

Education systems are complex and involve interactions between humans (teachers and students); media based technologies, lectures, classrooms, etc. to provide educational services. The education system performance is characterized by how well students learn, which is measured using student grades on exams and quizzes, achievements on standardized tests, among others. Advances in portable communications technologies, such as mobile phones, tablets, and laptops, created a different type of classroom, where students seem to engage in more than just the intended learning activities. The performance of more than one task in parallel or in rapid transition is commonly known as multitasking. Several operations in educational systems are performed simultaneously, resulting in a multitasking education environment. This paper surveys existing research on multitasking in educational settings, summarizes literature findings, provides a synthesis of the impact of multitasking on performance, and identifies directions of future research.

Keywords: Education systems, GPA, multitasking, performance.

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Authors: Tadayoshi Horita, Masakazu Akiba, Mina Terauchi, Tsuneo Kanno

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This paper gives a consideration of the achievement of productive level parallel programming skills, based on the data of the graduation studies in the Polytechnic University of Japan. The data show that most students can achieve only parallel programming skills during the graduation study (about 600 to 700 hours), if the programming environment is limited to GPGPUs. However, the data also show that it is a very high level task that a student achieves productive level parallel programming skills during only the graduation study. In addition, it shows that the parallel programming environments for GPGPU, such as CUDA and OpenCL, may be more suitable for parallel computing education than other environments such as MPI on a cluster system and Cell.B.E. These results must be useful for the areas of not only software developments, but also hardware product developments using computer technologies.

Keywords: Parallel computing, programming education, GPU, GPGPU, CUDA, OpenCL, MPI, Cell.B.E.

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Authors: Yifan Fan, Xudong Luo, Pingping Lin

Abstract:

An essential task in the field of artificial intelligence is to allow computers to interact with people through natural language. Therefore, researches such as virtual assistants and dialogue systems have received widespread attention from industry and academia. The response generation plays a crucial role in dialogue systems, so to push forward the research on this topic, this paper surveys various methods for response generation. We sort out these methods into three categories. First one includes finite state machine methods, framework methods, and instance methods. The second contains full-text indexing methods, ontology methods, vast knowledge base method, and some other methods. The third covers retrieval methods and generative methods. We also discuss some hybrid methods based knowledge and deep learning. We compare their disadvantages and advantages and point out in which ways these studies can be improved further. Our discussion covers some studies published in leading conferences such as IJCAI and AAAI in recent years.

Keywords: Retrieval, generative, deep learning, response generation, knowledge.

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Authors: A. M. Jungudo, M. A. Lasan

Abstract:

Affordable housing has long been one of the basic necessities of life to man. The ever rising prices of building materials are one of the major causes of housing shortage in many developing countries. Breaching the gap of housing needs in developing countries like Nigeria is an awaiting task longing for attention. This is due to lack of research in the development of local materials that will suit the troubled economies of these countries. The use of earth material to meet the housing needs is a sustainable option and its material is freely available universally. However, people are doubtful of using the earth material due to its modest outlook and uncertain durability. This research aims at enhancing the durability of Compressed Earth Bricks (CEBs) using stone dust as a stabilizer. The result indicates that partial replacement of lateritic soil with stone dust at 30% improves its compressive strength along with abrasive resistance.

Keywords: Laterite, stone dust, compressed earth bricks, durability.

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Authors: Mohamed A. Sullabi

Abstract:

The importance of the formal specification in the software life cycle is barely concealing to anyone. Formal specifications use mathematical notation to describe the properties of information system precisely, without unduly constraining the way in how these properties are achieved. Having a correct and quality software specification is not easy task. This study concerns with how a group of rectifiers can communicate with each other and work to prepare and produce a correct formal software specification. WBCS has been implemented based mainly in the proposed supported cooperative work model and a survey conducted on the existing Webbased collaborative writing tools. This paper aims to assess the feasibility of executing the web-based collaboration process using WBCS. The purpose of conducting this test is to test the system as a whole for functionality and fitness for use based on the evaluation test plan.

Keywords: Formal methods, Formal specifications, collaborative writing, Usability testing.

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Authors: P. Georgieva, S. Feyo de Azevedo

Abstract:

This paper is focused on issues of process modeling and two model based control strategies of a fed-batch sugar crystallization process applying the concept of artificial neural networks (ANNs). The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. Two control alternatives are considered – model predictive control (MPC) and feedback linearizing control (FLC). Adequate ANN process models are first built as part of the controller structures. MPC algorithm outperforms the FLC approach with respect to satisfactory reference tracking and smooth control action. However, the MPC is computationally much more involved since it requires an online numerical optimization, while for the FLC an analytical control solution was determined.

Keywords: artificial neural networks, nonlinear model control, process identification, crystallization process

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Authors: Muhammad R. Ahmed, Xu Huang, Dharmendra Sharma

Abstract:

Despite extensive study on wireless sensor network security, defending internal attacks and finding abnormal behaviour of the sensor are still difficult and unsolved task. The conventional cryptographic technique does not give the robust security or detection process to save the network from internal attacker that cause by abnormal behavior. The insider attacker or abnormally behaved sensor identificationand location detection framework using false massage detection and Time difference of Arrival (TDoA) is presented in this paper. It has been shown that the new framework can efficiently identify and detect the insider attacker location so that the attacker can be reprogrammed or subside from the network to save from internal attack.

Keywords: Insider Attaker identification, Abnormal Behaviour, Location detection, Time difference of Arrival (TDoA), Wireless sensor network

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Authors: Hoong C. Chin, Soon H. Chew, Zhaoxia Wang

Abstract:

Work on sustainable developments and the call for action in education for sustainable development have been ongoing for a number of years. Training engineering students with the relevant competencies, particularly in sustainable development literacy, has been identified as an urgent task in universities. This requires not only a holistic, multi-disciplinary approach to education but also a suitable training environment to develop the needed skills and to inculcate the appropriate attitudes in students towards sustainable development. To demonstrate how this can be done, a module involving an overseas field trip was introduced in 2013 at the National University of Singapore. This paper provides details of the module and describes its training philosophy and methods. Measured against the student learning outcomes, stipulated by the Engineering Accreditation Board, the module scored well on all of them, particularly those related to complex problem solving, environmental and sustainability awareness, multi-disciplinary team work and varied-level communications.

Keywords: Civil engineering education, student learning outcomes, sustainable development.

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Authors: Q. Niu, X. H. Zhou, W. Liu

Abstract:

The cooling channels of injection mould play a crucial role in determining the productivity of moulding process and the product quality. It’s not a simple task to design high quality cooling channels. In this paper, an intelligent cooling channels design system including automatic layout of cooling channels, interference checking and assembly of accessories is studied. Automatic layout of cooling channels using genetic algorithm is analyzed. Through integrating experience criteria of designing cooling channels, considering the factors such as the mould temperature and interference checking, the automatic layout of cooling channels is implemented. The method of checking interference based on distance constraint algorithm and the function of automatic and continuous assembly of accessories are developed and integrated into the system. Case studies demonstrate the feasibility and practicality of the intelligent design system.

Keywords: Injection mould, cooling channel, automatic layout, interference checking.

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Authors: Soe Winn, May Thwe Oo

Abstract:

Business process automation is an important task in an enterprise business environment software development. The requirements of processing acceleration and automation level of enterprises are inherently different from one organization to another. We present a methodology and system for automation of business process management system architecture by multi-agent collaboration based on SOA. Design layer processes are modeled in semantic markup language for web services application. At the core of our system is considering certain types of human tasks to their further automation across over multiple platform environments. An improved abnormality processing with model for automation of BPMS architecture by multi-agent collaboration based on SOA is introduced. Validating system for efficiency of process automation, an application for educational knowledge base instance would also be described.

Keywords: Business process management system, businessprocess automation, multi-agent collaboration, Service OrientedArchitecture, extensible service application

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Authors: Nittaya Kerdprasop, Kittisak Kerdprasop

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Frequent patterns are patterns such as sets of features or items that appear in data frequently. Finding such frequent patterns has become an important data mining task because it reveals associations, correlations, and many other interesting relationships hidden in a dataset. Most of the proposed frequent pattern mining algorithms have been implemented with imperative programming languages such as C, Cµ, Java. The imperative paradigm is significantly inefficient when itemset is large and the frequent pattern is long. We suggest a high-level declarative style of programming using a functional language. Our supposition is that the problem of frequent pattern discovery can be efficiently and concisely implemented via a functional paradigm since pattern matching is a fundamental feature supported by most functional languages. Our frequent pattern mining implementation using the Haskell language confirms our hypothesis about conciseness of the program. The performance studies on speed and memory usage support our intuition on efficiency of functional language.

Keywords: Association, frequent pattern mining, functionalprogramming, pattern matching.

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Authors: Junaid Rashid, Waqar Mehmood, Muhammad Wasif Nisar

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This survey paper shows the recent state of model comparison as it’s applies to Model Driven engineering. In Model Driven Engineering to calculate the difference between the models is a very important and challenging task. There are number of tasks involved in model differencing that firstly starts with identifying and matching the elements of the model. In this paper, we discuss how model matching is accomplished, the strategies, techniques and the types of the model. We also discuss the future direction. We found out that many of the latest model comparison strategies are geared near enabling Meta model and similarity based matching. Therefore model versioning is the most dominant application of the model comparison. Recently to work on comparison for versioning has begun to deteriorate, giving way to different applications. Ultimately there is wide change among the tools in the measure of client exertion needed to perform model comparisons, as some require more push to encourage more sweeping statement and expressive force.

Keywords: Model comparison, model clone detection, model versioning, EMF Model, model diff.

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Authors: Latha Parthiban, R. Subramanian

Abstract:

Heart disease (HD) is a major cause of morbidity and mortality in the modern society. Medical diagnosis is an important but complicated task that should be performed accurately and efficiently and its automation would be very useful. All doctors are unfortunately not equally skilled in every sub specialty and they are in many places a scarce resource. A system for automated medical diagnosis would enhance medical care and reduce costs. In this paper, a new approach based on coactive neuro-fuzzy inference system (CANFIS) was presented for prediction of heart disease. The proposed CANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach which is then integrated with genetic algorithm to diagnose the presence of the disease. The performances of the CANFIS model were evaluated in terms of training performances and classification accuracies and the results showed that the proposed CANFIS model has great potential in predicting the heart disease.

Keywords: CANFIS, genetic algorithms, heart disease, membership function.

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