Search results for: real algebraic geometry

Authors: Christhu Raj M. R., Rajeev Sukumaran

Abstract:

Underwater acoustic networks have attracted great attention in the last few years because of its numerous applications. High data rate can be achieved by efficiently modeling the physical layer in the network protocol stack. In Acoustic medium, propagation speed of the acoustic waves is dependent on many parameters such as temperature, salinity, density, and depth. Acoustic propagation speed cannot be modeled using standard empirical formulas such as Urick and Thorp descriptions. In this paper, we have modeled the acoustic channel using real time data of temperature, salinity, and speed of Bay of Bengal (Indian Coastal Region). We have modeled the acoustic channel by using Mackenzie speed equation and real time data obtained from National Institute of Oceanography and Technology. It is found that acoustic propagation speed varies between 1503 m/s to 1544 m/s as temperature and depth differs. The simulation results show that temperature, salinity, depth plays major role in acoustic propagation and data rate increases with appropriate data sets substituted in the simulated model.

Keywords: Underwater Acoustics, Mackenzie Speed Equation, Temperature, Salinity.

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Authors: Yuan Zheng

Abstract:

3D model-based vehicle matching provides a new way for vehicle recognition, localization and tracking. Its key is to construct an evaluation function, also called fitness function, to measure the degree of vehicle matching. The existing fitness functions often poorly perform when the clutter and occlusion exist in traffic scenarios. In this paper, we present a practical and efficient fitness function. Unlike the existing evaluation functions, the proposed fitness function is to study the vehicle matching problem from both local and global perspectives, which exploits the pixel gradient information as well as the silhouette information. In view of the discrepancy between 3D vehicle model and real vehicle, a weighting strategy is introduced to differently treat the fitting of the model’s wireframes. Additionally, a normalization operation for the model’s projection is performed to improve the accuracy of the matching. Experimental results on real traffic videos reveal that the proposed fitness function is efficient and robust to the cluttered background and partial occlusion.

Keywords: 3D-2D matching, fitness function, 3D vehicle model, local image gradient, silhouette information.

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Authors: Maziar A. Sharbafi, Caro Lucas, Aida Mohammadinejad, Mostafa Yaghobi

Abstract:

The Combination of path planning and path following is the main purpose of this paper. This paper describes the developed practical approach to motion control of the MRL small size robots. An intelligent controller is applied to control omni-directional robots motion in simulation and real environment respectively. The Brain Emotional Learning Based Intelligent Controller (BELBIC), based on LQR control is adopted for the omni-directional robots. The contribution of BELBIC in improving the control system performance is shown as application of the emotional learning in a real world problem. Optimizing of the control effort can be achieved in this method too. Next the implicit communication method is used to determine the high level strategies and coordination of the robots. Some simple rules besides using the environment as a memory to improve the coordination between agents make the robots' decision making system. With this simple algorithm our team manifests a desirable cooperation.

Keywords: multi-agent systems (MAS), Emotional learning, MIMO system, BELBIC, LQR, Communication via environment

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Authors: C. Malça, N. Alves, A. Mateus

Abstract:

This work was one of the tasks of the Manufacturing2Client project, whose objective was to develop a frontal deflector to be commercialized in the automotive industry, using new project and manufacturing methods. In this task, in particular, it was proposed to develop the ability to predict computationally the aerodynamic influence of flow in vehicles, in an effort to reduce fuel consumption in vehicles from class 3 to 8. With this aim, two deflector models were developed and their aerodynamic performance analyzed. The aerodynamic study was done using the Computational Fluid Dynamics (CFD) software Ansys CFX and allowed the calculation of the drag coefficient caused by the vehicle motion for the different configurations considered. Moreover, the reduction of diesel consumption and carbon dioxide (CO2) emissions associated with the optimized deflector geometry could be assessed.

Keywords: Aerodynamic analysis, CFD, CO2 emissions, Drag coefficient, Frontal deflector, Fuel consumption.

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Authors: C. Bunsanit

Abstract:

This paper presents the refinement method for two beams formation of wideband smart antenna. The refinement method for weighting coefficients is based on Fully Spatial Signal Processing by taking Inverse Discrete Fourier Transform (IDFT), and its simulation results are presented using MATLAB. The radiation pattern is created by multiplying the incoming signal with real weights and then summing them together. These real weighting coefficients are computed by IDFT method; however, the range of weight values is relatively wide. Therefore, for reducing this range, the refinement method is used. The radiation pattern concerns with five input parameters to control. These parameters are maximum weighting coefficient, wideband signal, direction of mainbeam, beamwidth, and maximum of minor lobe level. Comparison of the obtained simulation results between using refinement method and taking only IDFT shows that the refinement method works well for wideband two beams formation.

Keywords: Fully spatial signal processing, beam forming, refinement method, smart antenna, weighting coefficient, wideband.

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Authors: Saeed H. Nasiri, Rahim Faez, Bita Davoodi, Maryam Farrokhi

Abstract:

Bode stability analysis based on transmission line modeling (TLM) for single wall carbon nanotube (SWCNT) interconnects used in 3D-VLSI circuits is investigated for the first time. In this analysis, the dependence of the degree of relative stability for SWCNT interconnects on the geometry of each tube has been acquired. It is shown that, increasing the length and diameter of each tube, SWCNT interconnects become more stable.

Keywords: Bode stability criterion, Interconnects, Interlayer via, Single wall carbon nanotubes, Transmission line method, Time domain analysis

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Authors: Mohamed Ghorab

Abstract:

Local generated and distributed system for thermal and electrical energy is sighted in the near future to reduce transmission losses instead of the centralized system. Distributed Energy Resources (DER) is designed at different sizes (small and medium) and it is incorporated in energy distribution between the hubs. The energy generated from each technology at each hub should meet the local energy demands. Economic and environmental enhancement can be achieved when there are interaction and energy exchange between the hubs. Network energy system and CO₂ optimization between different six hubs presented Canadian community level are investigated in this study. Three different scenarios of technology systems are studied to meet both thermal and electrical demand loads for the six hubs. The conventional system is used as the first technology system and a reference case study. The conventional system includes boiler to provide the thermal energy, but the electrical energy is imported from the utility grid. The second technology system includes combined heat and power (CHP) system to meet the thermal demand loads and part of the electrical demand load. The third scenario has integration systems of CHP and Organic Rankine Cycle (ORC) where the thermal waste energy from the CHP system is used by ORC to generate electricity. General Algebraic Modeling System (GAMS) is used to model DER system optimization based on energy economics and CO₂ emission analyses. The results are compared with the conventional energy system. The results show that scenarios 2 and 3 provide an annual total cost saving of 21.3% and 32.3 %, respectively compared to the conventional system (scenario 1). Additionally, Scenario 3 (CHP & ORC systems) provides 32.5% saving in CO₂ emission compared to conventional system subsequent case 2 (CHP system) with a value of 9.3%.  

Keywords: Distributed energy resources, network energy system, optimization, microgeneration system.

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Authors: Parvinder S. Sandhu, Iqbaldeep Kaur, Amit Verma, Samriti Jindal, Shailendra Singh

Abstract:

Biometric measures of one kind or another have been used to identify people since ancient times, with handwritten signatures, facial features, and fingerprints being the traditional methods. Of late, Systems have been built that automate the task of recognition, using these methods and newer ones, such as hand geometry, voiceprints and iris patterns. These systems have different strengths and weaknesses. This work is a two-section composition. In the starting section, we present an analytical and comparative study of common biometric techniques. The performance of each of them has been viewed and then tabularized as a result. The latter section involves the actual implementation of the techniques under consideration that has been done using a state of the art tool called, MATLAB. This tool aids to effectively portray the corresponding results and effects.

Keywords: Matlab, Recognition, Facial Vectors, Functions.

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Authors: M. Ramadan, B. Salah

Abstract:

This paper introduces a framework to digitalize lean manufacturing tools to enhance smart lean-based manufacturing environments or Lean 4.0 manufacturing systems. The paper discusses the integration between lean tools and the powerful features of recent real-time data capturing systems with the help of Information and Communication Technologies (ICT) to develop an intelligent real-time monitoring and controlling system of production operations concerning lean targets. This integration is represented in the Lean 4.0 system called Dynamic Value Stream Mapping (DVSM). Moreover, the paper introduces the practice of Radio Frequency Identification (RFID) and ICT to smartly support lean tools and practices during daily production runs to keep the lean system alive and effective. This work introduces a practical description of how the lean method tools 5S, standardized work, and poka-yoke can be digitalized and smartly monitored and controlled through DVSM. A framework of the three tools has been discussed and put into practice in a German switchgear manufacturer.

Keywords: Lean manufacturing, Industry 4.0, radio frequency identification, value stream mapping.

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Authors: Raimund Leitner, Susanne Rosskopf

Abstract:

Near-infrared (NIR) spectroscopy is a widely used method for material identification for laboratory and industrial applications. While standard spectrometers only allow measurements at one sampling point at a time, NIR Spectral Imaging techniques can measure, in real-time, both the size and shape of an object as well as identify the material the object is made of. The online classification and sorting of recovered paper with NIR Spectral Imaging (SI) is used with success in the paper recycling industry throughout Europe. Recently, the globalisation of the recycling material streams caused that water-based flexographic-printed newspapers mainly from UK and Italy appear also in central Europe. These flexo-printed newspapers are not sufficiently de-inkable with the standard de-inking process originally developed for offset-printed paper. This de-inking process removes the ink from recovered paper and is the fundamental processing step to produce high-quality paper from recovered paper. Thus, the flexo-printed newspapers are a growing problem for the recycling industry as they reduce the quality of the produced paper if their amount exceeds a certain limit within the recovered paper material. This paper presents the results of a research project for the development of an automated entry inspection system for recovered paper that was jointly conducted by CTR AG (Austria) and PTS Papiertechnische Stiftung (Germany). Within the project an NIR SI prototype for the identification of flexo-printed newspaper has been developed. The prototype can identify and sort out flexoprinted newspapers in real-time and achieves a detection accuracy for flexo-printed newspaper of over 95%. NIR SI, the technology the prototype is based on, allows the development of inspection systems for incoming goods in a paper production facility as well as industrial sorting systems for recovered paper in the recycling industry in the near future.

Keywords: spectral imaging, imaging spectroscopy, NIR, waterbasedflexographic, flexo-printed, recovered paper, real-time classification.

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Authors: B. Kędra, R. Małkowski

Abstract:

This paper presents information on Power System Component Simulator – a device designed for LINTE^2 laboratory owned by Gdansk University of Technology in Poland. In this paper, we first provide an introductory information on the Power System Component Simulator and its capabilities. Then, the concept of the unit is presented. Requirements for the unit are described as well as proposed and introduced functions are listed. Implementation details are given. Hardware structure is presented and described. Information about used communication interface, data maintenance and storage solution, as well as used Simulink real-time features are presented. List and description of all measurements is provided. Potential of laboratory setup modifications is evaluated. Lastly, the results of experiments performed using Power System Component Simulator are presented. This includes simulation of under frequency load shedding, frequency and voltage dependent characteristics of groups of load units, time characteristics of group of different load units in a chosen area.

Keywords: Power converter, Simulink real-time, MATLAB, load, tap controller.

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Authors: Anahita Farhang Ghahfarokhi, Alessandro Berti, Wil M.P. van der Aalst

Abstract:

Process mining provides ways to analyze business processes. Common process mining techniques consider the process as a whole. However, in real-life business processes, different behaviors exist that make the overall process too complex to interpret. Process comparison is a branch of process mining that isolates different behaviors of the process from each other by using process cubes. Process cubes organize event data using different dimensions. Each cell contains a set of events that can be used as an input to apply process mining techniques. Existing work on process cubes assume single case notions. However, in real processes, several case notions (e.g., order, item, package, etc.) are intertwined. Object-centric process mining is a new branch of process mining addressing multiple case notions in a process. To make a bridge between object-centric process mining and process comparison, we propose a process cube framework, which supports process cube operations such as slice and dice on object-centric event logs. To facilitate the comparison, the framework is integrated with several object-centric process discovery approaches.

Keywords: Process mining, multidimensional process mining, multi-perspective business processes, OLAP, process cubes, process discovery.

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Authors: C. Ardil

Abstract:

This paper aims to select the best military attack helicopter to purchase by the Armed Forces and provide greater reconnaissance and offensive combat capability in military operations. For this purpose, a multiple criteria decision analysis method integrated with the variance weight procedure was applied to the military attack helicopter selection problem. A real military aviation case problem is conducted to support the Armed Forces decision-making process and contributes to the better performance of the Armed Forces. Application of the methodology resulted in ranking lists for ordering and prioritizing attack helicopters, providing transparency and simplicity to the decision-making process. Nine military attack helicopter models were analyzed in the light of strategic, tactical, and operational criteria, considering attack helicopters. The selected military attack helicopter would be used for fire support and reconnaissance activities required by the Armed Forces operation. This study makes a valuable contribution to the problem of military attack helicopter selection, as it represents a state-of-the-art application of the MCDMA method to contribute to the solution of a real problem of the Armed Forces. The methodology presented in this paper can be used to solve real problems of a wide variety, especially strategic, tactical and operational, and is, therefore, a very useful method for decision making.

Keywords: aircraft selection, military attack helicopter selection, attack helicopter fleet planning, MCDMA, multiple criteria analysis, multiple criteria decision making analysis, distance function measure

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Authors: Rami N. Khushaba, Ahmed Al-Ani, Adel Al-Jumaily

Abstract:

One of the approaches enabling people with amputated limbs to establish some sort of interface with the real world includes the utilization of the myoelectric signal (MES) from the remaining muscles of those limbs. The MES can be used as a control input to a multifunction prosthetic device. In this control scheme, known as the myoelectric control, a pattern recognition approach is usually utilized to discriminate between the MES signals that belong to different classes of the forearm movements. Since the MES is recorded using multiple channels, the feature vector size can become very large. In order to reduce the computational cost and enhance the generalization capability of the classifier, a dimensionality reduction method is needed to identify an informative yet moderate size feature set. This paper proposes a new fuzzy version of the well known Fisher-s Linear Discriminant Analysis (LDA) feature projection technique. Furthermore, based on the fact that certain muscles might contribute more to the discrimination process, a novel feature weighting scheme is also presented by employing Particle Swarm Optimization (PSO) for estimating the weight of each feature. The new method, called PSOFLDA, is tested on real MES datasets and compared with other techniques to prove its superiority.

Keywords: Discriminant Analysis, Pattern Recognition, SignalProcessing.

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Authors: Sabrina Gaito, Andrea Greppi, Giuliano Grossi

Abstract:

In this paper we present a technique to speed up ICA based on the idea of reducing the dimensionality of the data set preserving the quality of the results. In particular we refer to FastICA algorithm which uses the Kurtosis as statistical property to be maximized. By performing a particular Johnson-Lindenstrauss like projection of the data set, we find the minimum dimensionality reduction rate ¤ü, defined as the ratio between the size k of the reduced space and the original one d, which guarantees a narrow confidence interval of such estimator with high confidence level. The derived dimensionality reduction rate depends on a system control parameter β easily computed a priori on the basis of the observations only. Extensive simulations have been done on different sets of real world signals. They show that actually the dimensionality reduction is very high, it preserves the quality of the decomposition and impressively speeds up FastICA. On the other hand, a set of signals, on which the estimated reduction rate is greater than 1, exhibits bad decomposition results if reduced, thus validating the reliability of the parameter β. We are confident that our method will lead to a better approach to real time applications.

Keywords: Independent Component Analysis, FastICA algorithm, Higher-order statistics, Johnson-Lindenstrauss lemma.

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Authors: Mallikarjuna Rao Gundavarapu, Ch. Mallikarjuna Rao, K. Anuradha Bai

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Real Time Video Tracking is a challenging task for computing professionals. The performance of video tracking techniques is greatly affected by background detection and elimination process. Local regions of the image frame contain vital information of background and foreground. However, pixel-level processing of local regions consumes a good amount of computational time and memory space by traditional approaches. In our approach we have explored the concurrent computational ability of General Purpose Graphic Processing Units (GPGPU) to address this problem. The Gaussian Mixture Model (GMM) with adaptive weighted kernels is used for detecting the background. The weights of the kernel are influenced by local regions and are updated by inter-frame variations of these corresponding regions. The proposed system has been tested with GPU devices such as GeForce GTX 280, GeForce GTX 280 and Quadro K2000. The results are encouraging with maximum speed up 10X compared to sequential approach.

Keywords: Connected components, Embrace threads, Local weighted kernel, Structuring element.

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Authors: A. K. Al-Othman, F. S. Al-Fares, K. M. EL-Nagger

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This paper presents a new optimization technique based on quantum computing principles to solve a security constrained power system economic dispatch problem (SCED). The proposed technique is a population-based algorithm, which uses some quantum computing elements in coding and evolving groups of potential solutions to reach the optimum following a partially directed random approach. The SCED problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Real Coded Quantum-Inspired Evolution Algorithm (RQIEA) is then applied to solve the constrained optimization formulation. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that RQIEA is very applicable for solving security constrained power system economic dispatch problem (SCED).

Keywords: State Estimation, Fuzzy Linear Regression, FuzzyLinear State Estimator (FLSE) and Measurements Uncertainty.

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Authors: R. Usubamatov, Z. A. Rashid

Abstract:

Simple design of a rotary valve system is capable of controlling intake and exhaust gases, which will eliminate the need of known complex mechanisms. The cost of material and production, maintenance, and noise level of the system can be further reduced. The new mechanism enables the elimination of the overlapping of valves work that reduces gas leakage. This paper examines theoretically the gas flow through the holes of a rotary valve design in a small engine. Preliminary results show that the new gas flow has many positive differences than a conventional poppet-valve system. New dependencies on the gas speed enable the finding of better solutions for the geometry of a rotary valve system that will result in a higher efficiency of an internal-combustion engine of the automotive industry.

Keywords: Gas arrangement, internal combustion engine.

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Authors: Ashwin Belle, Bryce Benson, Mark Salamango, Fadi Islim, Rodney Daniels, Kevin Ward

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A reliable, real-time, and non-invasive system that can identify patients at risk for hemodynamic instability is needed to aid clinicians in their efforts to anticipate patient deterioration and initiate early interventions. The purpose of this pilot study was to explore the clinical capabilities of a real-time analytic from a single lead of an electrocardiograph to correctly distinguish between rapid response team (RRT) activations due to hemodynamic (H-RRT) and non-hemodynamic (NH-RRT) causes, as well as predict H-RRT cases with actionable lead times. The study consisted of a single center, retrospective cohort of 21 patients with RRT activations from step-down and telemetry units. Through electronic health record review and blinded to the analytic’s output, each patient was categorized by clinicians into H-RRT and NH-RRT cases. The analytic output and the categorization were compared. The prediction lead time prior to the RRT call was calculated. The analytic correctly distinguished between H-RRT and NH-RRT cases with 100% accuracy, demonstrating 100% positive and negative predictive values, and 100% sensitivity and specificity. In H-RRT cases, the analytic detected hemodynamic deterioration with a median lead time of 9.5 hours prior to the RRT call (range 14 minutes to 52 hours). The study demonstrates that an electrocardiogram (ECG) based analytic has the potential for providing clinical decision and monitoring support for caregivers to identify at risk patients within a clinically relevant timeframe allowing for increased vigilance and early interventional support to reduce the chances of continued patient deterioration.

Keywords: Critical care, early warning systems, emergency medicine, heart rate variability, hemodynamic instability, rapid response team.

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Authors: Do-Jin Jang, Sung-Ah Kim

Abstract:

In designing a kinetic façade, it is hard for the designer to make digital models due to its complex geometry with motion. This paper aims to present a methodology of converting a point cloud of a physical model into a single digital model with a certain topology and motion. The method uses a Microsoft Kinect sensor, and color markers were defined and applied to three paper folding-inspired designs. Although the resulted digital model cannot represent the whole folding range of the physical model, the method supports the designer to conduct a performance-oriented design process with the rough physical model in the reduced folding range.

Keywords: Design media, kinetic façades, tangible user interface, 3D scanning.

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Authors: Sitalakshmi Venkataraman

Abstract:

Recent scientific investigations indicate that multimodal biometrics overcome the technical limitations of unimodal biometrics, making them ideally suited for everyday life applications that require a reliable authentication system. However, for a successful adoption of multimodal biometrics, such systems would require large heterogeneous datasets with complex multimodal fusion and privacy schemes spanning various distributed environments. From experimental investigations of current multimodal systems, this paper reports the various issues related to speed, error-recovery and privacy that impede the diffusion of such systems in real-life. This calls for a robust mechanism that caters to the desired real-time performance, robust fusion schemes, interoperability and adaptable privacy policies. The main objective of this paper is to present a framework that addresses the abovementioned issues by leveraging on the heterogeneous resource sharing capacities of Grid services and the efficient machine learning capabilities of artificial neural networks (ANN). Hence, this paper proposes a Grid-based neural network framework for adopting multimodal biometrics with the view of overcoming the barriers of performance, privacy and risk issues that are associated with shared heterogeneous multimodal data centres. The framework combines the concept of Grid services for reliable brokering and privacy policy management of shared biometric resources along with a momentum back propagation ANN (MBPANN) model of machine learning for efficient multimodal fusion and authentication schemes. Real-life applications would be able to adopt the proposed framework to cater to the varying business requirements and user privacies for a successful diffusion of multimodal biometrics in various day-to-day transactions.

Keywords: Back Propagation, Grid Services, MultimodalBiometrics, Neural Networks.

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Authors: Gustavo Rodrigues, Hans Weber, Larissa Driemeier

Abstract:

The prevision of post-impact conditions and the behavior of the bodies during the impact have been object of several collision models. The formulation from Hertz’s theory is generally used dated from the 19^th century. These models consider the repulsive force as proportional to the deformation of the bodies under contact and may consider it proportional to the rate of deformation. The objective of the present work is to analyze the behavior of the bodies during impact using the Finite Element Method (FEM) with elastic and plastic material models. The main parameters to evaluate are, the contact force, the time of contact and the deformation of the bodies. An advantage of using the FEM approach is the possibility to apply a plastic deformation to the model according to the material definition: there will be used Johnson–Cook plasticity model whose parameters are obtained through empirical tests of real materials. This model allows analyzing the permanent deformation caused by impact, phenomenon observed in real world depending on the forces applied to the body. These results are compared between them and with the model-based Hertz theory.

Keywords: Collision, finite element method, Hertz’s Theory, impact models.

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Authors: Yu Zhang, Nao-Aki Noda, Kentaro Takaishi

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This paper discusses effects of adhesive thickness, overlap length and material combinations on the single-lap joints strength from the point of singular stress fields. A useful method calculating the ratio of intensity of singular stress is proposed using FEM for different adhesive thickness and overlap length. It is found that the intensity of singular stress increases with increasing adhesive thickness, and decreases with increasing overlap length. The increment and decrement are different depending on material combinations between adhesive and adherent.

Keywords: Adhesive thickness, Overlap length, Intensity ofsingular stress, Single-lap joint

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Authors: Panagiotis Kyratsis, Konstantinos Kakoulis

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Nowadays, the rapid development of CAD systems’ programming environments results in the creation of multiple downstream applications, which are developed and becoming increasingly available. CAD based manufacturing simulations is gradually following the same trend. Drilling is the most popular holemaking process used in a variety of industries. A specially built piece of software that deals with the drilling kinematics is presented. The cutting forces are calculated based on the tool geometry, the cutting conditions and the tool/work-piece materials. The results are verified by experimental work. Finally, the response surface methodology (RSM) is applied and mathematical models of the total thrust force and the thrust force developed because of the main cutting edges are proposed.

Keywords: Application programming interface, CAD, drilling, response surface methodology, RSM.

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Authors: Padmanabhan Balasubramanian, Ryuta Arisaka

Abstract:

Factoring Boolean functions is one of the basic operations in algorithmic logic synthesis. A novel algebraic factorization heuristic for single-output combinatorial logic functions is presented in this paper and is developed based on the set theory paradigm. The impact of factoring is analyzed mainly from a low power design perspective for standard cell based digital designs in this paper. The physical implementation of a number of MCNC/IWLS combinational benchmark functions and sub-functions are compared before and after factoring, based on a simple technology mapping procedure utilizing only standard gate primitives (readily available as standard cells in a technology library) and not cells corresponding to optimized complex logic. The power results were obtained at the gate-level by means of an industry-standard power analysis tool from Synopsys, targeting a 130nm (0.13μm) UMC CMOS library, for the typical case. The wire-loads were inserted automatically and the simulations were performed with maximum input activity. The gate-level simulations demonstrate the advantage of the proposed factoring technique in comparison with other existing methods from a low power perspective, for arbitrary examples. Though the benchmarks experimentation reports mixed results, the mean savings in total power and dynamic power for the factored solution over a non-factored solution were 6.11% and 5.85% respectively. In terms of leakage power, the average savings for the factored forms was significant to the tune of 23.48%. The factored solution is expected to better its non-factored counterpart in terms of the power-delay product as it is well-known that factoring, in general, yields a delay-efficient multi-level solution.

Keywords: Factorization, Set theory, Logic function, Standardcell based design, Low power.

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

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Current real-estate value estimation, difficult for laymen, usually is performed by specialists. This paper presents an automated estimation process based on big data and machine-learning technology that calculates influences of building conditions on real-estate price measurement. The present study analyzed actual building sales sample data for Nonhyeon-dong, Gangnam-gu, Seoul, Korea, measuring the major influencing factors among the various building conditions. Further to that analysis, a prediction model was established and applied using RapidMiner Studio, a graphical user interface (GUI)-based tool for derivation of machine-learning prototypes. The prediction model is formulated by reference to previous examples. When new examples are applied, it analyses and predicts accordingly. The analysis process discerns the crucial factors effecting price increases by calculation of weighted values. The model was verified, and its accuracy determined, by comparing its predicted values with actual price increases.

Keywords: Big data, building-value analysis, machine learning, price prediction.

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Authors: Yi-Hua Chen, Hsiang-Wen Tang, I-Ling Chang, Lien-Wen Chen

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The defect mode of two-dimensional phononic crystals with Archimedean tilings was explored in the present study. Finite element method and supercell method were used to obtain dispersion relation of phononic crystals. The simulations of the acoustic wave propagation within phononic crystals are demonstrated. Around the cavity which is created by removing several cylinders in the perfect Archimedean tilings, whispering-gallery mode (WGM) can be observed. The effects of the cavity geometry on the WGM modes are investigated. The WGM modes with high Q-factor and high cavity pressure can be obtained by phononic crystals with Archimedean tilings.

Keywords: Defect mode, Archimedean tilings, phononic crystals, whispering- gallery modes.

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Authors: D. Vidhyaprakash, A. Elango

Abstract:

In real-time applications, wheeled mobile robots are increasingly used and operated in extreme and diverse conditions traversing challenging surfaces such as a pitted, uneven terrain, natural flat, smooth terrain, as well as wet and dry surfaces. In order to accomplish such tasks, it is critical that the motion control functions without wheel slip and odometry error during the navigation of the two-wheeled mobile robot (WMR). Wheel slip and odometry error are disrupting factors on overall WMR performance in the form of deviation from desired trajectory, navigation, travel time and budgeted energy consumption. The wheeled mobile robot’s ability to operate at peak performance on various work surfaces without wheel slippage and odometry error is directly connected to four main parameters, which are the range of payload distribution, speed, wheel diameter, and wheel width. This paper analyses the effects of those parameters on overall performance and is concerned with determining the ideal range of parameters for optimum performance.

Keywords: Wheeled mobile robot (WMR), terrain, wheel slippage, odometry error, navigation.

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Authors: Trien V. Do, Jong-Weon Lee

Abstract:

This paper describes a 3D modeling system in Augmented Reality environment, named 3DARModeler. It can be considered a simple version of 3D Studio Max with necessary functions for a modeling system such as creating objects, applying texture, adding animation, estimating real light sources and casting shadows. The 3DARModeler introduces convenient, and effective human-computer interaction to build 3D models by combining both the traditional input method (mouse/keyboard) and the tangible input method (markers). It has the ability to align a new virtual object with the existing parts of a model. The 3DARModeler targets nontechnical users. As such, they do not need much knowledge of computer graphics and modeling techniques. All they have to do is select basic objects, customize their attributes, and put them together to build a 3D model in a simple and intuitive way as if they were doing in the real world. Using the hierarchical modeling technique, the users are able to group several basic objects to manage them as a unified, complex object. The system can also connect with other 3D systems by importing and exporting VRML/3Ds Max files. A module of speech recognition is included in the system to provide flexible user interfaces.

Keywords: 3D Modeling, Augmented Reality, GeometricModeling, Virtual Reality

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Authors: Mahdi Mazinani, S. D. Qanadli, Rahil Hosseini, Tim Ellis, Jamshid Dehmeshki

Abstract:

Segmentation and quantification of stenosis is an important task in assessing coronary artery disease. One of the main challenges is measuring the real diameter of curved vessels. Moreover, uncertainty in segmentation of different tissues in the narrow vessel is an important issue that affects accuracy. This paper proposes an algorithm to extract coronary arteries and measure the degree of stenosis. Markovian fuzzy clustering method is applied to model uncertainty arises from partial volume effect problem. The algorithm employs: segmentation, centreline extraction, estimation of orthogonal plane to centreline, measurement of the degree of stenosis. To evaluate the accuracy and reproducibility, the approach has been applied to a vascular phantom and the results are compared with real diameter. The results of 10 patient datasets have been visually judged by a qualified radiologist. The results reveal the superiority of the proposed method compared to the Conventional thresholding Method (CTM) on both datasets.

Keywords: 3D coronary artery tree extraction, segmentation, quantification, fuzzy clustering, and Markov random field

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