Search results for: Agilent’s Advanced Design system (ADS) and lumped elements.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 12521

Search results for: Agilent’s Advanced Design system (ADS) and lumped elements.

3911 Laboratory Investigations on Mechanical Properties of High Volume Fly Ash Concrete and Composite Sections

Authors: Aravindkumar B. Harwalkar, S. S. Awanti

Abstract:

Use of fly ash as a supplementary cementing material in large volumes can bring both technological and economic benefits for concrete industry. In this investigation mix proportions for high volume fly ash concrete were determined at cement replacement levels of 50%, 55%, 60% and 65% with low calcium fly ash. Flexural and compressive strengths of different mixes were measured at ages of 7, 28 and 90 days. Flexural strength of composite section prepared from pavement quality and lean high volume fly ash concrete was determined at the age of 28 days. High volume fly ash concrete mixes exhibited higher rate of strength gain and age factors than corresponding reference concrete mixes. The optimum cement replacement level for pavement quality concrete was found to be 60%. The consideration of bond between pavement quality and lean of high volume fly ash concrete will be beneficial in design of rigid pavements.

Keywords: Keywords—Composite section, Compressive strength, Flexural strength, Fly ash.

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3910 Artificial Neural Network Models of the Ruminal pH in Holstein Steers

Authors: Alireza Vakili, Mohsen Danesh Mesgaran, Majid Abdollazade

Abstract:

In this study four Holstein steers with rumen fistula fed 7 kg of dry matter (DM) of diets differing in concentrate to alfalfa hay ratios as 60:40, 70:30, 80:20, and 90:10 in a 4 × 4 latin square design. The pH of the ruminal fluid was measured before the morning feeding (0.0 h) to 8 h post feeding. In this study, a two-layered feed-forward neural network trained by the Levenberg-Marquardt algorithm was used for modelling of ruminal pH. The input variables of the network were time, concentrate to alfalfa hay ratios (C/F), non fiber carbohydrate (NFC) and neutral detergent fiber (NDF). The output variable was the ruminal pH. The modeling results showed that there was excellent agreement between the experimental data and predicted values, with a high determination coefficient (R2 >0.96). Therefore, we suggest using these model-derived biological values to summarize continuously recorded pH data.

Keywords: Ruminal pH, Artificial Neural Network (ANN), Non Fiber Carbohydrate, Neutral Detergent Fiber.

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3909 Simulation versus Hands-On Learning Methodologies: A Comparative Study for Engineering and Technology Curricula

Authors: Mohammed T. Taher, Usman Ghani, Ahmed S. Khan

Abstract:

This paper compares the findings of two studies conducted to determine the effectiveness of simulation-based, hands-on and feedback mechanism on students learning by answering the following questions: 1). Does the use of simulation improve students’ learning outcomes? 2). How do students perceive the instructional design features embedded in the simulation program such as exploration and scaffolding support in learning new concepts? 3.) What is the effect of feedback mechanisms on students’ learning in the use of simulation-based labs? The paper also discusses the other aspects of findings which reveal that simulation by itself is not very effective in promoting student learning. Simulation becomes effective when it is followed by hands-on activity and feedback mechanisms. Furthermore, the paper presents recommendations for improving student learning through the use of simulation-based, hands-on, and feedback-based teaching methodologies.

Keywords: Simulation-based teaching, hands-on learning, feedback-based learning, scaffolding.

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3908 Optimal Design for SARMA(P,Q)L Process of EWMA Control Chart

Authors: Y. Areepong

Abstract:

The main goal of this paper is to study Statistical Process Control (SPC) with Exponentially Weighted Moving Average (EWMA) control chart when observations are serially-correlated. The characteristic of control chart is Average Run Length (ARL) which is the average number of samples taken before an action signal is given. Ideally, an acceptable ARL of in-control process should be enough large, so-called (ARL0). Otherwise it should be small when the process is out-of-control, so-called Average of Delay Time (ARL1) or a mean of true alarm. We find explicit formulas of ARL for EWMA control chart for Seasonal Autoregressive and Moving Average processes (SARMA) with Exponential white noise. The results of ARL obtained from explicit formula and Integral equation are in good agreement. In particular, this formulas for evaluating (ARL0) and (ARL1) be able to get a set of optimal parameters which depend on smoothing parameter (λ) and width of control limit (H) for designing EWMA chart with minimum of (ARL1).

Keywords: Average Run Length1, Optimal parameters, Exponentially Weighted Moving Average (EWMA) control chart.

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3907 TheAnalyzer: Clustering-Based System for Improving Business Productivity by Analyzing User Profiles to Enhance Human-Computer Interaction

Authors: D. S. A. Nanayakkara, K. J. P. G. Perera

Abstract:

E-commerce platforms have revolutionized the shopping experience, offering convenient ways for consumers to make purchases. To improve interactions with customers and optimize marketing strategies, it is essential for businesses to understand user behavior, preferences, and needs on these platforms. This paper focuses on recommending businesses to customize interactions with users based on their behavioral patterns, leveraging data-driven analysis and machine learning techniques. Businesses can improve engagement and boost the adoption of e-commerce platforms by aligning behavioral patterns with user goals of usability and satisfaction. We propose TheAnalyzer, a clustering-based system designed to enhance business productivity by analyzing user-profiles and improving human-computer interaction. TheAnalyzer seamlessly integrates with business applications, collecting relevant data points based on users' natural interactions without additional burdens such as questionnaires or surveys. It defines five key user analytics as features for its dataset, which are easily captured through users' interactions with e-commerce platforms. This research presents a study demonstrating the successful distinction of users into specific groups based on the five key analytics considered by TheAnalyzer. With the assistance of domain experts, customized business rules can be attached to each group, enabling TheAnalyzer to influence business applications and provide an enhanced personalized user experience. The outcomes are evaluated quantitatively and qualitatively, demonstrating that utilizing TheAnalyzer’s capabilities can optimize business outcomes, enhance customer satisfaction, and drive sustainable growth. The findings of this research contribute to the advancement of personalized interactions in e-commerce platforms. By leveraging user behavioral patterns and analyzing both new and existing users, businesses can effectively tailor their interactions to improve customer satisfaction, loyalty and ultimately drive sales.

Keywords: Data clustering, data standardization, dimensionality reduction, human-computer interaction, user profiling.

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3906 Assessing Water Quality Using GIS: The Case of Northern Lebanon Miocene Aquifer

Authors: M. Saba, A. Iaaly, E. Carlier, N. Georges

Abstract:

This research focuses on assessing the ground water quality of Northern Lebanon affected by saline water intrusion. The chemical, physical and microbiological parameters were collected in various seasons spanning over the period of two years. Results were assessed using Geographic Information System (GIS) due to its visual capabilities in presenting the pollution extent in the studied region. Future projections of the excessive pumping were also simulated using GIS in order to assess the extent of the problem of saline intrusion in the near future.

Keywords: GIS, saline water, quality control, drinkable water quality standards, pumping.

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3905 A Multimodal Approach for Biometric Authentication with Multiple Classifiers

Authors: Sorin Soviany, Cristina Soviany, Mariana Jurian

Abstract:

The paper presents a multimodal approach for biometric authentication, based on multiple classifiers. The proposed solution uses a post-classification biometric fusion method in which the biometric data classifiers outputs are combined in order to improve the overall biometric system performance by decreasing the classification error rates. The paper shows also the biometric recognition task improvement by means of a carefully feature selection, as much as not all of the feature vectors components support the accuracy improvement.

Keywords: biometric fusion, multiple classifiers

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3904 Minimum Energy of a Prismatic Joint with out: Actuator: Application on RRP Robot

Authors: Tawiwat V., Tosapolporn P., Kedit J.

Abstract:

This research proposes the state of art on how to control or find the trajectory paths of the RRP robot when the prismatic joint is malfunction. According to this situation, the minimum energy of the dynamic optimization is applied. The RRP robot or similar systems have been used in many areas such as fire fighter truck, laboratory equipment and military truck for example a rocket launcher. In order to keep on task that assigned, the trajectory paths must be computed. Here, the open loop control is applied and the result of an example show the reasonable solution which can be applied to the controllable system.

Keywords: RRP robot, Optimal Control, Minimum Energy and Under Actuator.

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3903 New Delay-dependent Stability Conditions for Neutral Systems with Nonlinear Perturbations

Authors: Lianglin Xiong, Xiuyong Ding, Shouming Zhong

Abstract:

In this paper, the problem of asymptotical stability of neutral systems with nonlinear perturbations is investigated. Based on a class of novel augment Lyapunov functionals which contain freeweighting matrices, some new delay-dependent asymptotical stability criteria are formulated in terms of linear matrix inequalities (LMIs) by using new inequality analysis technique. Numerical examples are given to demonstrate the derived condition are much less conservative than those given in the literature.

Keywords: Asymptotical stability, neutral system, nonlinear perturbation, delay-dependent, linear matrix inequality (LMI).

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3902 Ultimate Load Capacity of the Cable Tower of Liede Bridge

Authors: Weifeng Wang, Xilong Chen, Xianwei Zeng

Abstract:

The cable tower of Liede Bridge is a double-column curved-lever arched-beam portal framed structure. Being novel and unique in structure, its cable tower differs in complexity from traditional ones. This paper analyzes the ultimate load capacity of cable tower by adopting the finite element calculations and model tests which indicate that constitutive relations applied here give a better simulation of actual failure process of prestressed reinforced concrete. In vertical load, horizontal load and overloading tests, the stepped loading of the tower model is of linear relationship, and the test data has good repeatability. All suggests that the cable tower has good bearing capacity, rational design and high emergency capacity.

Keywords: Cable tower of Liede Bridge, ultimate load capacity, model test, nonlinear finite element method

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3901 Non-Polynomial Spline Solution of Fourth-Order Obstacle Boundary-Value Problems

Authors: Jalil Rashidinia, Reza Jalilian

Abstract:

In this paper we use quintic non-polynomial spline functions to develop numerical methods for approximation to the solution of a system of fourth-order boundaryvalue problems associated with obstacle, unilateral and contact problems. The convergence analysis of the methods has been discussed and shown that the given approximations are better than collocation and finite difference methods. Numerical examples are presented to illustrate the applications of these methods, and to compare the computed results with other known methods.

Keywords: Quintic non-polynomial spline, Boundary formula, Convergence, Obstacle problems.

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3900 Adopting Collaborative Business Processes to Prevent the Loss of Information in Public Administration Organisations

Authors: A. Capodieci, G. Del Fiore, L. Mainetti

Abstract:

Recently, the use of web 2.0 tools has increased in companies and public administration organisations. This phenomenon, known as "Enterprise 2.0", has, de facto, modified common organisational and operative practices. This has led “knowledge workers” to change their working practices through the use of Web 2.0 communication tools. Unfortunately, these tools have not been integrated with existing enterprise information systems, a situation that could potentially lead to a loss of information. This is an important problem in an organisational context, because knowledge of information exchanged within the organisation is needed to increase the efficiency and competitiveness of the organisation. In this article we demonstrate that it is possible to capture this knowledge using collaboration processes, which are processes of abstraction created in accordance with design patterns and applied to new organisational operative practices.

Keywords: Business Practices, Business Process Patterns, Collaboration Tools, Enterprise 2.0, Knowledge Workers.

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3899 Method of Moments Applied to a Cuboidal Cavity Resonator: Effect of Gravitational Field Produced by a Black Hole

Authors: Arti Vaish, Harish Parthasarathy

Abstract:

This paper deals with the formulation of Maxwell-s equations in a cavity resonator in the presence of the gravitational field produced by a blackhole. The metric of space-time due to the blackhole is the Schwarzchild metric. Conventionally, this is expressed in spherical polar coordinates. In order to adapt this metric to our problem, we have considered this metric in a small region close to the blackhole and expressed this metric in a cartesian system locally.

Keywords: Method of moments, General theory of relativity, Electromagnetism, Metric tensor, schwarzchild metric, Wave Equation.

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3898 Parametrization of Piezoelectric Vibration Energy Harvesters for Low Power Embedded Systems

Authors: Yannick Verbelen, Tim Dekegel, Ann Peeters, Klara Stinders, Niek Blondeel, Sam De Winne, An Braeken, Abdellah Touhafi

Abstract:

Matching an embedded electronic application with a cantilever vibration energy harvester remains a difficult endeavour due to the large number of factors influencing the output power. In the presented work, complementary balanced energy harvester parametrization is used as a methodology for simplification of harvester integration in electronic applications. This is achieved by a dual approach consisting of an adaptation of the general parametrization methodology in conjunction with a straight forward harvester benchmarking strategy. For this purpose, the design and implementation of a suitable user friendly cantilever energy harvester benchmarking platform is discussed. Its effectiveness is demonstrated by applying the methodology to a commercially available Mide V21BL vibration energy harvester, with excitation amplitude and frequency as variables.

Keywords: Energy harvesting, vibrations, piezoelectric transducers, embedded systems, harvester parametrization.

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3897 Using Automatic Ontology Learning Methods in Human Plausible Reasoning Based Systems

Authors: A. R. Vazifedoost, M. Rahgozar, F. Oroumchian

Abstract:

Knowledge discovery from text and ontology learning are relatively new fields. However their usage is extended in many fields like Information Retrieval (IR) and its related domains. Human Plausible Reasoning based (HPR) IR systems for example need a knowledge base as their underlying system which is currently made by hand. In this paper we propose an architecture based on ontology learning methods to automatically generate the needed HPR knowledge base.

Keywords: Ontology Learning, Human Plausible Reasoning, knowledge extraction, knowledge representation.

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3896 An Approach to Adaptive Load Balancing for RFID Middlewares

Authors: Heung Seok Chae, Jaegeol Park

Abstract:

Recently, there have been an increasing interest in RFID system and RFID systems have been applied to various applications. Load balancing is a fundamental technique for providing scalability of systems by moving workload from overloaded nodes to under-loaded nodes. This paper presents an approach to adaptive load balancing for RFID middlewares. Workloads of RFID middlewares can have a considerable variation according to the location of the connected RFID readers and can abruptly change at a particular instance. The proposed approach considers those characteristics of RFID middle- wares to provide an efficient load balancing.

Keywords: RFID middleware, Adaptive load balancing.

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3895 A Study of Gas Metal Arc Welding Affecting Mechanical Properties of Austenitic Stainless Steel AISI 304

Authors: Sittichai K., Santirat N., Sompong., P

Abstract:

The objective of this research was to study influence parameters affecting to mechanical property of austenitic stainless steel grade 304 (AISI 304) with Gas Metal Arc Welding (GMAW). The research was applying factorial design experiment, which have following interested parameters: welding current at 80, 90, and 100 Amps, welding speeds at 250, 300, and 350 mm/min, and shield gas of 75% Ar + 25% CO2, 70% Ar + 25% CO2 + 5% O2 and 69.5% Ar + 25% CO2 + 5% O2 + 0.5% He gas. The study was done in following aspects: ultimate tensile strength and elongation. A research study of ultimate tensile strength found that main factor effect, which had the highest strength to AISI 304 welding was shield gas of 70% Ar + 25% CO2 + 5% O2 at average of 954.81 N/mm2. Result of the highest elongation was showed significantly different at interaction effect between shield gas of 69.5%Ar+25%CO2+5%O2+.5%He and welding speed at 250 mm/min at 47.94%.

Keywords: Austenitic Stainless Steel AISI 304/ Mechanical Property/ Welding Gas Shield/ Gas Shield

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3894 An Approximate Engineering Method for Aerodynamic Heating Solution around Blunt Body Nose

Authors: Sahar Noori, Seyed Amir Hossein, Mohammad Ebrahimi

Abstract:

This paper is devoted to predict laminar and turbulent heating rates around blunt re-entry spacecraft at hypersonic conditions. Heating calculation of a hypersonic body is normally performed during the critical part of its flight trajectory. The procedure is of an inverse method, where a shock wave is assumed, and the body shape that supports this shock, as well as the flowfield between the shock and body, are calculated. For simplicity the normal momentum equation is replaced with a second order pressure relation; this simplification significantly reduces computation time. The geometries specified in this research, are parabola and ellipsoids which may have conical after bodies. An excellent agreement is observed between the results obtained in this paper and those calculated by others- research. Since this method is much faster than Navier-Stokes solutions, it can be used in preliminary design, parametric study of hypersonic vehicles.

Keywords: Aerodynamic Heating, Blunt Body, Hypersonic Flow, Laminar, Turbulent.

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3893 Effects of Synchronous Music on Gymnastics' Motor Skills Performance among Undergraduate Female Students in Physical Education College

Authors: Sanaa Ali Ahmed Alrashid

Abstract:

The present study aimed to investigate the effect of synchronous music in Gymnastics' motor skill performance among undergraduate female students in physical education college at Basra University. The researcher used experimental design. 20 female students of physical education divided equally into two groups, (10) experimental group with music, (10) control group without music. All participants complete 6 weeks in testing. Data analysis based on T-test shows significant difference at (α = 0.05) in all skills level between experimental and control groups in favor of experimental group. Results of this study contribute to developing the role of synchronous music in improving gymnastic skills performance.

Keywords: Performance, motor skill, music, synchronous.

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3892 Micro-Study of Dissimilar Welded Materials

Authors: E. M. Anawa, A. G. Olabi

Abstract:

The dissimilar joint between aluminum/titanium alloys (Al 6082 and Ti G2) were successfully achieved by CO2 laser welding with a single pass and without filler material using the overlap joint design. Laser welding parameters ranges combinations were experimentally determined using Taguchi approach with the objective of producing welded joint with acceptable welding profile and high quality of mechanical properties. In this study a joining of dissimilar Al 6082 / Ti G2 was resulted in three distinct regions fusion area in the weldment. These regions are studied in terms of its microstructural characteristics and microhardness which are directly affecting the welding quality. The weld metal was mainly composed of martensite alpha prime. In two different metals in the two different sides of joint HAZ, grain growth was detected. The microhardness of the joint distribution also has shown microhardness increasing in the HAZ of two base metals and a varying microhardness in fusion zone.

Keywords: Micro-hardness, Microstructure, laser welding, dissimilar jointed materials.

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3891 Optimization of Copper-Water Negative Inclination Heat Pipe with Internal Composite Wick Structure

Authors: I. Brandys, M. Levy, K. Harush, Y. Haim, M. Korngold

Abstract:

Theoretical optimization of a copper-water negative inclination heat pipe with internal composite wick structure had been performed, regarding a new introduced parameter: the ratio between the coarse mesh wraps and the fine mesh wraps of the composite wick. Since in many cases, the design of a heat pipe matches specific thermal requirements and physical limitations, this work demonstrates the optimization of a 1m length, 8mm internal diameter heat pipe without an adiabatic section, at a negative inclination angle of -10º. The optimization is based on a new introduced parameter, LR: the ratio between the coarse mesh wraps and the fine mesh wraps.

Keywords: Heat pipe, inclination, optimization, ratio.

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3890 Electrostatic and Dielectric Measurements for Hair Building Fibers from DC to Microwave Frequencies

Authors: K. Y. You, Y. L. Then

Abstract:

In recent years, the hair building fiber has become popular, in other words, it is an effective method which helps people who suffer hair loss or sparse hair since the hair building fiber is capable to create a natural look of simulated hair rapidly. In the markets, there are a lot of hair fiber brands that have been designed to formulate an intense bond with hair strands and make the hair appear more voluminous instantly. However, those products have their own set of properties. Thus, in this report, some measurement techniques are proposed to identify those products. Up to five different brands of hair fiber are tested. The electrostatic and dielectric properties of the hair fibers are macroscopically tested using design DC and high frequency microwave techniques. Besides, the hair fibers are microscopically analysis by magnifying the structures of the fiber using scanning electron microscope (SEM). From the SEM photos, the comparison of the uniformly shaped and broken rate of the hair fibers in the different bulk samples can be observed respectively.

Keywords: Hair fiber, electrostatic, dielectric properties, broken rate, microwave techniques.

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3889 A New Method to Estimate the Low Income Proportion: Monte Carlo Simulations

Authors: Encarnación Álvarez, Rosa M. García-Fernández, Juan F. Muñoz

Abstract:

Estimation of a proportion has many applications in economics and social studies. A common application is the estimation of the low income proportion, which gives the proportion of people classified as poor into a population. In this paper, we present this poverty indicator and propose to use the logistic regression estimator for the problem of estimating the low income proportion. Various sampling designs are presented. Assuming a real data set obtained from the European Survey on Income and Living Conditions, Monte Carlo simulation studies are carried out to analyze the empirical performance of the logistic regression estimator under the various sampling designs considered in this paper. Results derived from Monte Carlo simulation studies indicate that the logistic regression estimator can be more accurate than the customary estimator under the various sampling designs considered in this paper. The stratified sampling design can also provide more accurate results.

Keywords:

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3888 ICF Neutron Detection Techniques Based on Doped ZnO Crystal

Authors: L. Chen, X. P. Ouyang, Z. B. Zhang, J. F. Zhang, J. L. Liu

Abstract:

Ultrafast doped zinc oxide crystal promised us a good opportunity to build new instruments for ICF fusion neutron measurement. Two pulsed neutron detectors based on ZnO crystal wafer have been conceptually designed, the superfast ZnO timing detector and the scintillation recoil proton neutron detection system. The structure of these detectors was presented, and some characters were studied as well. The new detectors could be much faster than existing systems, and would be more competent for ICF neutron diagnostics.

Keywords: ICF fusion neutron detection, proton recoil telescope, superfast timing, ZnO crystal

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3887 A Simulation Study of Direct Injection Compressed Natural Gas Spark Ignition Engine Performance Utilizing Turbulent Jet Ignition with Controlled Air Charge

Authors: Siyamak Ziyaei, Siti Khalijah Mazlan, Petros Lappas

Abstract:

Compressed natural gas (CNG) is primarily composed of methane (CH4), and has a lower carbon to hydrogen ratio than other hydrocarbon fuels such as gasoline (C8H18) and diesel (C12H23). Consequently, it has the potential to reduce CO2 emissions compared to conventional fuels. Although Natural Gas (NG) has environmental advantages compared to other hydrocarbon fuels, its main component, CH4, burns at a slower rate compared to the conventional fuels. A higher pressure and leaner cylinder environment will unravel the slow burn characteristic of CH4. Lean combustion and high compression ratios are well-known methods for increasing the efficiency of internal combustion engines. In order to achieve successful a CNG lean combustion in Spark Ignition (SI) engines, a strong ignition system is essential to avoid engine misfires, especially in ultra-lean conditions. Turbulent Jet Ignition (TJI) is an ignition system that employs a pre-combustion chamber to ignite the lean fuel mixture in the main combustion chamber using a fraction of the total fuel per cycle. TJI enables ultra-lean combustion by providing distributed ignition sites through orifices. The fast burn rate provided by TJI enables the ordinary SI engine to be comparable to other combustion systems such as Homogeneous Charge Compression Ignition (HCCI) or Controlled Auto-Ignition (CAI) in terms of thermal efficiency, through the increased levels of dilution without the need of sophisticated control systems. Due to the physical geometry of TJI, which contains small orifices that connect the pre-chamber to the main chamber, providing the right mixture of fuel and air has been identified as a key challenge due to the insufficient amount of air that is pushed into the pre-chamber during each compression stroke. There is also the problem of scavenging which contributed to the factors that reduces the TJI performance. Combustion residual gases such as CO2, CO and NOx from the previous combustion cycle dilute the pre-chamber fuel-air mixture preventing rapid combustion in the pre-chamber. An air-controlled active TJI is presented in this paper in order to address these issues. By supplying air into the pre-chamber at a sufficient pressure, residual gases are exhausted, and the air-fuel ratio is controlled within the pre-chamber, thereby improving the quality of the combustion. An investigation of the 3D combustion characteristics of a CNG-fueled SI engine using a direct injection fuelling strategy employing an air channel in the prechamber is presented in this paper. Experiments and simulations were performed at the Worldwide Mapping Point (WWMP) at 1500 revolutions per minute (rpm), 3.3 bar Indicated Mean Effective Pressure (IMEP), using only conventional spark plugs as a baseline. With a validated baseline engine simulation, the settings were set for all simulation scenarios at λ=1. Following that, the pre-chambers with and without an auxiliary fuel supply were simulated. In the study of (DI-CNG) SI engine, active TJI was observed to perform better than passive TJI and conventional  spark plug ignition. In conclusion, the active pre-chamber with an air channel demonstrated an improved thermal efficiency (ηth) over other counterparts and conventional spark ignition systems.

Keywords: Turbulent Jet Ignition, Active Air Control Turbulent Jet Ignition, Pre-chamber ignition system, Active and Passive Pre-chamber, thermal efficiency, methane combustion, internal combustion engine combustion emissions.

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3886 Towards a Simulation Model to Ensure the Availability of Machines in Maintenance Activities

Authors: Maryam Gallab, Hafida Bouloiz, Youness Chater, Mohamed Tkiouat

Abstract:

The aim of this paper is to present a model based on multi-agent systems in order to manage the maintenance activities and to ensure the reliability and availability of machines just with the required resources (operators, tools). The interest of the simulation is to solve the complexity of the system and to find results without cost or wasting time. An implementation of the model is carried out on the AnyLogic platform to display the defined performance indicators.

Keywords: Maintenance, complexity, simulation, multi-agent systems, AnyLogic platform.

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3885 Design, Development by Functional Analysis in UML and Static Test of a Multimedia Voice and Video Communication Platform on IP for a Use Adapted to the Context of Local Businesses in Lubumbashi

Authors: Blaise Fyama, Elie Museng, Grace Mukoma

Abstract:

In this article we present a java implementation of video telephony using the SIP protocol (Session Initiation Protocol). After a functional analysis of the SIP protocol, we relied on the work of Italian researchers of University of Parma-Italy to acquire adequate libraries for the development of our own communication tool. In order to optimize the code and improve the prototype, we used, in an incremental approach, test techniques based on a static analysis based on the evaluation of the complexity of the software with the application of metrics and the number cyclomatic of Mccabe. The objective is to promote the emergence of local start-ups producing IP video in a well understood local context. We have arrived at the creation of a video telephony tool whose code is optimized.

Keywords: Static analysis, coding, complexity, mccabe metrics, Sip, uml.

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3884 A New Sufficient Conditions of Stability for Discrete Time Non-autonomous Delayed Hopfield Neural Networks

Authors: Adnene Arbi, Chaouki Aouiti, Abderrahmane Touati

Abstract:

In this paper, we consider the uniform asymptotic stability, global asymptotic stability and global exponential stability of the equilibrium point of discrete Hopfield neural networks with delays. Some new stability criteria for system are derived by using the Lyapunov functional method and the linear matrix inequality approach, for estimating the upper bound of Lyapunov functional derivative.

Keywords: Hopfield neural networks, uniform asymptotic stability, global asymptotic stability, exponential stability.

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3883 Reliable Consensus Problem for Multi-Agent Systems with Sampled-Data

Authors: S. H. Lee, M. J. Park, O. M. Kwon

Abstract:

In this paper, reliable consensus of multi-agent systems with sampled-data is investigated. By using a suitable Lyapunov-Krasovskii functional and some techniques such as Wirtinger Inequality, Schur Complement and Kronecker Product, the results of such system are obtained by solving a set of Linear Matrix Inequalities (LMIs). One numerical example is included to show the effectiveness of the proposed criteria.

Keywords: Multi-agent, Linear Matrix Inequalities (LMIs), Kronecker Product, Sampled-Data, Lyapunov method.

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3882 Machine Learning Techniques for Short-Term Rain Forecasting System in the Northeastern Part of Thailand

Authors: Lily Ingsrisawang, Supawadee Ingsriswang, Saisuda Somchit, Prasert Aungsuratana, Warawut Khantiyanan

Abstract:

This paper presents the methodology from machine learning approaches for short-term rain forecasting system. Decision Tree, Artificial Neural Network (ANN), and Support Vector Machine (SVM) were applied to develop classification and prediction models for rainfall forecasts. The goals of this presentation are to demonstrate (1) how feature selection can be used to identify the relationships between rainfall occurrences and other weather conditions and (2) what models can be developed and deployed for predicting the accurate rainfall estimates to support the decisions to launch the cloud seeding operations in the northeastern part of Thailand. Datasets collected during 2004-2006 from the Chalermprakiat Royal Rain Making Research Center at Hua Hin, Prachuap Khiri khan, the Chalermprakiat Royal Rain Making Research Center at Pimai, Nakhon Ratchasima and Thai Meteorological Department (TMD). A total of 179 records with 57 features was merged and matched by unique date. There are three main parts in this work. Firstly, a decision tree induction algorithm (C4.5) was used to classify the rain status into either rain or no-rain. The overall accuracy of classification tree achieves 94.41% with the five-fold cross validation. The C4.5 algorithm was also used to classify the rain amount into three classes as no-rain (0-0.1 mm.), few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall accuracy of classification tree achieves 62.57%. Secondly, an ANN was applied to predict the rainfall amount and the root mean square error (RMSE) were used to measure the training and testing errors of the ANN. It is found that the ANN yields a lower RMSE at 0.171 for daily rainfall estimates, when compared to next-day and next-2-day estimation. Thirdly, the ANN and SVM techniques were also used to classify the rain amount into three classes as no-rain, few-rain, and moderate-rain as above. The results achieved in 68.15% and 69.10% of overall accuracy of same-day prediction for the ANN and SVM models, respectively. The obtained results illustrated the comparison of the predictive power of different methods for rainfall estimation.

Keywords: Machine learning, decision tree, artificial neural network, support vector machine, root mean square error.

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