Search results for: business intelligence capability

Authors: František Šebek, Petr Kubík, Jindřich Petruška, Jiří Hůlka

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Present study is aimed on the cutting process of circular cross-section rods where the fracture is used to separate one rod into two pieces. Incorporating the phenomenological ductile fracture model into the explicit formulation of finite element method, the process can be analyzed without the necessity of realizing too many real experiments which could be expensive in case of repetitive testing in different conditions. In the present paper, the steel AISI 1045 was examined and the tensile tests of smooth and notched cylindrical bars were conducted together with biaxial testing of the notched tube specimens to calibrate material constants of selected phenomenological ductile fracture models. These were implemented into the Abaqus/Explicit through user subroutine VUMAT and used for cutting process simulation. As the calibration process is based on variables which cannot be obtained directly from experiments, numerical simulations of fracture tests are inevitable part of the calibration. Finally, experiments regarding the cutting process were carried out and predictive capability of selected fracture models is discussed. Concluding remarks then make the summary of gained experience both with the calibration and application of particular ductile fracture criteria.

Keywords: Ductile fracture, phenomenological criteria, cutting process, explicit formulation, AISI 1045 steel.

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Authors: Niyati Parameswaran, Bharathi Muthu, Madiajagan Muthaiyan

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This paper presents Qmulus- a Cloud Based GPS Model. Qmulus is designed to compute the best possible route which would lead the driver to the specified destination in the shortest time while taking into account real-time constraints. Intelligence incorporated to Qmulus-s design makes it capable of generating and assigning priorities to a list of optimal routes through customizable dynamic updates. The goal of this design is to minimize travel and cost overheads, maintain reliability and consistency, and implement scalability and flexibility. The model proposed focuses on reducing the bridge between a Client Application and a Cloud service so as to render seamless operations. Qmulus-s system model is closely integrated and its concept has the potential to be extended into several other integrated applications making it capable of adapting to different media and resources.

Keywords: Cloud Services, GPS, Real-Time Constraints, Shortest Path, System Management and Traffic Routing

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Authors: Maciej Mitręga

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This paper contributes to our knowledge about buyerseller relations by identifying barriers and conflict situations associated with maintaining and developing durable business relationships by small companies. The contribution of prior studies with regard to negative aspects of marketing relationships is presented in the first section. The international research results are discussed with regard to the existing conceptualizations and main research implications identified at the end.

Keywords: Relationship marketing, barriers, conflict, SME, international research.

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Authors: K. Sandjak, B. Tiliouine

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Structural analysis of flexible pavements has been and still is currently performed using multi-layer elastic theory. However, for thinly surfaced pavements subjected to low to medium volumes of traffics, the importance of non-linear stress-strain behavior of unbound granular materials (UGM) requires the use of more sophisticated numerical models for structural design and performance of such pavements. In the present work, nonlinear unbound aggregates constitutive model is implemented within an axisymmetric finite element code developed to simulate the nonlinear behavior of pavement structures including two local aggregates of different mineralogical nature, typically used in Algerian pavements. The performance of the mechanical model is examined about its capability of representing adequately, under various conditions, the granular material non-linearity in pavement analysis. In addition, deflection data collected by Falling Weight Deflectometer (FWD) are incorporated into the analysis in order to assess the sensitivity of critical pavement design criteria and pavement design life to the constitutive model. Finally, conclusions of engineering significance are formulated. 

Keywords: Nonlinear resilient behavior, unbound granular materials, RLT test results, FWD backcalculations, finite element simulations, pavement response and performance.

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Authors: Chiang-Ho Cheng, An-Shik Yang, Hong-Yih Cheng, Ming-Yu Lai

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This paper presents the design and fabrication of a novel piezoelectric actuator for a gas micro pump with check valve having the advantages of miniature size, light weight and low power consumption. The micro pump is designed to have eight major components, namely a stainless steel upper cover layer, a piezoelectric actuator, a stainless steel diaphragm, a PDMS chamber layer, two stainless steel channel layers with two valve seats, a PDMS check valve layer with two cantilever-type check valves and an acrylic substrate. A prototype of the gas micro pump, with a size of 52 mm × 50 mm × 5.0 mm, is fabricated by precise manufacturing. This device is designed to pump gases with the capability of performing the self-priming and bubble-tolerant work mode by maximizing the stroke volume of the membrane as well as the compression ratio via minimization of the dead volume of the micro pump chamber and channel. By experiment apparatus setup, we can get the real-time values of the flow rate of micro pump and the displacement of the piezoelectric actuator, simultaneously. The gas micro pump obtained higher output performance under the sinusoidal waveform of 250 Vpp. The micro pump achieved the maximum pumping rates of 1185 ml/min and back pressure of 7.14 kPa at the corresponding frequency of 120 and 50 Hz.

Keywords: PDMS, Check valve, Micro pump, Piezoelectric.

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Authors: An-Jui. Li, Kelvin Lim, Chien-Kuo Chiu, Benson Hsiung

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This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.

Keywords: Landslide, limit analysis, ANN, soil properties.

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Authors: B. Janani, S. Thiruvenkadam

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In this work, the system evaluates the impact of considering a stochastic approach on the day ahead basis Unit Commitment. Comparisons between stochastic and deterministic Unit Commitment solutions are provided. The Unit Commitment model consists in the minimization of the total operation costs considering unit’s technical constraints like ramping rates, minimum up and down time. Load shedding and wind power spilling is acceptable, but at inflated operational costs. The evaluation process consists in the calculation of the optimal unit commitment and in verifying the fulfillment of the considered constraints. For the calculation of the optimal unit commitment, an algorithm based on the Benders Decomposition, namely on the Dual Dynamic Programming, was developed. Two approaches were considered on the construction of stochastic solutions. Data related to wind power outputs from two different operational days are considered on the analysis. Stochastic and deterministic solutions are compared based on the actual measured wind power output at the operational day. Through a technique capability of finding representative wind power scenarios and its probabilities, the system can analyze a more detailed process about the expected final operational cost.

Keywords: Benders’ decomposition, network constrained AC unit commitment, stochastic programming, wind power uncertainty.

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Authors: C. Ardil

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Aircraft selection decisions can be challenging due to their multidimensional and interdisciplinary nature. They involve multiple stakeholders with conflicting objectives and numerous alternative options with uncertain outcomes. This study focuses on the analysis of aerial firefighting aircraft that can be chosen for the Air Fire Service to extinguish forest fires. To make such a selection, the characteristics of the fire zones must be considered, and the capability to manage the logistics involved in such operations, as well as the purchase and maintenance of the aircraft, must be determined. The selection of firefighting aircraft is particularly complex because they have longer fleet lives and require more demanding operation and maintenance than scheduled passenger air service. This paper aims to use the fuzzy proximity measure method to select the most appropriate aerial firefighting aircraft based on decision criteria using multiple attribute decision making analysis. Following fuzzy decision analysis, the most suitable aerial firefighting aircraft is ranked and determined for the Air Fire Service.

Keywords: Aerial firefighting aircraft selection, multiple criteria decision making, fuzzy sets, standard fuzzy sets, determinate fuzzy sets, indeterminate fuzzy sets, proximity measure method, Minkowski distance family function, Hausdorff distance function, MCDM, PMM, PMM-F

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Authors: Chien-Chun Hung, Chun-Fong Wu

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It is important for a commander to have real-time information to aware situations and to make decision in the battlefield. Results of modern technique developments have brought in this kind of information for military purposes. Unmanned aerial vehicle (UAV) is one of the means to gather intelligence owing to its widespread applications. It is still not clear whether or not the mini UAV with short-range wireless transmission system is used as a reconnaissance system in Taiwanese. In this paper, previous experience on the research of the sort of aerial vehicles has been applied with a data-relay system using the ZigBee modulus. The mini UAV developed is expected to be able to collect certain data in some appropriate theaters. The omni-directional antenna with high gain is also integrated into mini UAV to fit the size-reducing trend of airborne sensors. Two advantages are so far obvious. First, mini UAV can fly higher than usual to avoid being attacked from ground fires. Second, the data will be almost gathered during all maneuvering attitudes.

Keywords: Mini UAV, reconnaissance, wireless transmission, ZigBee modulus.

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Authors: Nicolò Vaiana, Giorgio Serino

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The nonlinear time history analysis of seismically base-isolated structures can require a significant computational effort when the behavior of each seismic isolator is predicted by adopting the widely used differential equation Bouc-Wen model. In this paper, a nonlinear exponential model, able to simulate the response of seismic isolation bearings within a relatively large displacements range, is described and adopted in order to reduce the numerical computations and speed up the nonlinear dynamic analysis. Compared to the Bouc-Wen model, the proposed one does not require the numerical solution of a nonlinear differential equation for each time step of the analysis. The seismic response of a 3d base-isolated structure with a lead rubber bearing system subjected to harmonic earthquake excitation is simulated by modeling each isolator using the proposed analytical model. The comparison of the numerical results and computational time with those obtained by modeling the lead rubber bearings using the Bouc-Wen model demonstrates the good accuracy of the proposed model and its capability to reduce significantly the computational effort of the analysis.

Keywords: Base isolation, computational efficiency, nonlinear exponential model, nonlinear time history analysis.

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Authors: Tengku Mohd T. Sembok

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Documents retrieval in Information Retrieval Systems (IRS) is generally about understanding of information in the documents concern. The more the system able to understand the contents of documents the more effective will be the retrieval outcomes. But understanding of the contents is a very complex task. Conventional IRS apply algorithms that can only approximate the meaning of document contents through keywords approach using vector space model. Keywords may be unstemmed or stemmed. When keywords are stemmed and conflated in retrieving process, we are a step forwards in applying semantic technology in IRS. Word stemming is a process in morphological analysis under natural language processing, before syntactic and semantic analysis. We have developed algorithms for Malay and Arabic and incorporated stemming in our experimental systems in order to measure retrieval effectiveness. The results have shown that the retrieval effectiveness has increased when stemming is used in the systems.

Keywords: Information Retrieval, Natural Language Processing, Artificial Intelligence.

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Authors: Edelyn Alicar-Cadorna

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This study assessed the productivity and performance of the barangays in the Heritage City of Vigan in terms of the barangays- resource requirements, management of resources, produced goods and services, and outcomes of service delivery. The descriptive research design was used in the study employing the input-process-output-outcomes model. Findings of this study showed that the barangays were strong in terms of resource requirements which enabled them to produce goods and services. The barangays were also strong in terms of management of resources in development planning. They also showed great potential along fiscal administration, and had a moderately high capability in organization and management. However, the barangays appeared to be most wanting in the area of barangay legislation, but they were strong in community mobilization and they had strong linkages with POs, NGOs and educational institutions. In the delivery of social services, the barangays favored the maintenance of day care centers. However, the barangays seem to be weak in the delivery of economic services. They fared well along providing protective services such as in establishing a Barangay Disaster Coordinating Council and organizing a group of Barangay Tanod. In terms of environmental services, the barangays performed garbage collection and disposal; however, garbage still found their way in the streets in some barangays. The services delivered had effected an improved status of the barangays. However, the barangays are still facing some problems.

Keywords: Barangays, Performance and Productivity.

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Authors: H. Iranmanesh, M. Madadi

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Work Breakdown Structure (WBS) is one of the most vital planning processes of the project management since it is considered to be the fundamental of other processes like scheduling, controlling, assigning responsibilities, etc. In fact WBS or activity list is the heart of a project and omission of a simple task can lead to an irrecoverable result. There are some tools in order to generate a project WBS. One of the most powerful tools is mind mapping which is the basis of this article. Mind map is a method for thinking together and helps a project manager to stimulate the mind of project team members to generate project WBS. Here we try to generate a WBS of a sample project involving with the building construction using the aid of mind map and the artificial intelligence (AI) programming language. Since mind map structure can not represent data in a computerized way, we convert it to a semantic network which can be used by the computer and then extract the final WBS from the semantic network by the prolog programming language. This method will result a comprehensive WBS and decrease the probability of omitting project tasks.

Keywords: Expert System, Mind map, Semantic network, Work breakdown structure,

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Authors: Ferinar Moaidi, Mahdi Moaidi

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Environmental issues and the ever-increasing in demand of electrical energy make it necessary to have distributed generation (DG) resources in the power system. In this research, in order to realize the goals of reducing losses and improving the voltage profile in a microgrid, the allocation and sizing of DGs have been used. The proposed Genetic Algorithm (GA) is described from the array of artificial intelligence methods for solving the problem. The algorithm is implemented on the IEEE 33 buses network. This study is presented in two scenarios, primarily to illustrate the effect of location and determination of DGs has been done to reduce losses and improve the voltage profile. On the other hand, decisions made with the one-level assumptions of load are not universally accepted for all levels of load. Therefore, in this study, load modelling is performed and the results are presented for multi-levels load state.

Keywords: Distributed generation, genetic algorithm, microgrid, load modelling, loss reduction, voltage improvement.

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Authors: Moeiz Miraoui, Chakib Tadj, Chokri ben Amar

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Devices in a pervasive computing system (PCS) are characterized by their context-awareness. It permits them to provide proactively adapted services to the user and applications. To do so, context must be well understood and modeled in an appropriate form which enhance its sharing between devices and provide a high level of abstraction. The most interesting methods for modeling context are those based on ontology however the majority of the proposed methods fail in proposing a generic ontology for context which limit their usability and keep them specific to a particular domain. The adaptation task must be done automatically and without an explicit intervention of the user. Devices of a PCS must acquire some intelligence which permits them to sense the current context and trigger the appropriate service or provide a service in a better suitable form. In this paper we will propose a generic service ontology for context modeling and a context-aware service adaptation based on a service oriented definition of context.

Keywords: Pervasive computing system, context, contextawareness, service, context modeling, ontology, adaptation, machine learning.

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Authors: M. F. Wu, F. T. Cheng, C. S. Wu, M. C. Tan

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It is a critical time to upgrade technology and increase value added with manufacturing skills developing and management strategies that will highly satisfy the customers need in the precision machinery global market. In recent years, the supply side, each precision machinery manufacturers in each country are facing the pressures of price reducing from the demand side voices that pushes the high-end precision machinery manufacturers adopts low-cost and high-quality strategy to retrieve the market. Because of the trend of the global market, the manufacturers must take price reducing strategies and upgrade technology of low-end machinery for differentiations to consolidate the market.By using six key success factors (KSFs), customer perceived value, customer satisfaction, customer service, product design, product effectiveness and machine structure quality are causal conditions to explore the impact of competitive advantage of the enterprise, such as overall profitability and product pricing power. This research uses key success paths (KSPs) approach and f/s QCA software to explore various combinations of causal relationships, so as to fully understand the performance level of KSFs and business objectives in order to achieve competitive advantage. In this study, the combination of a causal relationships, are called Key Success Paths (KSPs). The key success paths guide the enterprise to achieve the specific outcomes of business. The findings of this study indicate that there are thirteen KSPs to achieve the overall profitability, sixteen KSPs to achieve the product pricing power and seventeen KSPs to achieve both overall profitability and pricing power of the enterprise. The KSPs provide the directions of resources integration and allocation, improve utilization efficiency of limited resources to realize the continuous vision of the enterprise.

Keywords: Precision Machinery Industry, Key Success Factors (KSPs), Key Success Paths (KSPs), Overall Profitability, Product Pricing Power, Competitive Advantages.

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Authors: Shilpesh R. Rajpurohit, Harshit K. Dave

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Fused deposition modeling (FDM) gains popularity in recent times, due to its capability to create prototype as well as functional end use product directly from CAD file. Parts fabricated using FDM process have mechanical properties comparable with those of injection-molded parts. However, performance of the FDM part is severally affected by the poor mechanical properties of the part due to nature of layered structure of printed part. Mechanical properties of the part can be improved by proper selection of process variables. In the present study, a comparative study between unidirectional and bidirectional raster angle has been carried out at a combination of different layer height and raster width. Unidirectional raster angle varied at five different levels, and bidirectional raster angle has been varied at three different levels. Fabrication of tensile specimen and tensile testing of specimen has been conducted according to ASTM D638 standard. From the results, it can be observed that higher tensile strength has been obtained at 0° raster angle followed by 45°/45° raster angle, while lower tensile strength has been obtained at 90° raster angle. Analysis of fractured surface revealed that failure takes place along with raster deposition direction for unidirectional and zigzag failure can be observed for bidirectional raster angle.

Keywords: Additive manufacturing, fused deposition modeling, raster angle, tensile strength.

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Authors: Sidhartha Panda, N. P. Padhy

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This paper investigates the application of Particle Swarm Optimization (PSO) technique for coordinated design of a Power System Stabilizer (PSS) and a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the power system stability. The design problem of PSS and TCSC-based controllers is formulated as a time domain based optimization problem. PSO algorithm is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. To compare the capability of PSS and TCSC-based controller, both are designed independently first and then in a coordinated manner for individual and coordinated application. The proposed controllers are tested on a weakly connected power system. The eigenvalue analysis and non-linear simulation results are presented to show the effectiveness of the coordinated design approach over individual design. The simulation results show that the proposed controllers are effective in damping low frequency oscillations resulting from various small disturbances like change in mechanical power input and reference voltage setting.

Keywords: Particle swarm optimization, Phillips-Heffron model, power system stability, PSS, TCSC.

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Authors: David E. Culler, Noah D. Anderson

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Integrated systems for product design, manufacturing, and lifecycle management are difficult to implement and customize. Commercial software vendors, including CAD/CAM and third party PDM/PLM developers, create user interfaces and functionality that allow their products to be applied across many industries. The result is that systems become overloaded with functionality, difficult to navigate, and use terminology that is unfamiliar to engineers and production personnel. For example, manufacturers of automotive, aeronautical, electronics, and household products use similar but distinct methods and processes. Furthermore, each company tends to have their own preferred tools and programs for controlling work and information flow and that connect design, planning, and manufacturing processes to business applications. This paper presents a methodology and a case study that addresses these issues and suggests that in the future more companies will develop personalized applications that fit to the natural way that their business operates. A functioning system has been implemented at a highly competitive U.S. aerospace tooling and component supplier that works with many prominent airline manufacturers around the world including The Boeing Company, Airbus, Embraer, and Bombardier Aerospace. During the last three years, the program has produced significant benefits such as the automatic creation and management of component and assembly designs (parametric models and drawings), the extensive use of lightweight 3D data, and changes to the way projects are executed from beginning to end. CATIA (CAD/CAE/CAM) and a variety of programs developed in C#, VB.Net, HTML, and SQL make up the current system. The web-based platform is facilitating collaborative work across multiple sites around the world and improving communications with customers and suppliers. This work demonstrates that the creative use of Application Programming Interface (API) utilities, libraries, and methods is a key to automating many time-consuming tasks and linking applications together.

Keywords: CAD/CAM, CAPP, PDM, PLM, Scalable Systems.

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Authors: Masaki Yamaguchi, Daimei Sasayama, Shinsuke Washizuka

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The goal of this study was to examine the possibility of salivary cytokines for the screening of attention deficit hyperactivity disorder (ADHD) in children. We carried out a case-control study, including 19 children with ADHD and 17 healthy children (controls). A multiplex bead array immunoassay was used to conduct a multi-analysis of 27 different salivary cytokines. Six salivary cytokines (interleukin (IL)-1β, IL-8, IL12p70, granulocyte colony-stimulating factor (G-CSF), interferon gamma (IFN-γ), and vascular endothelial growth factor (VEGF)) were significantly associated with the presence of ADHD (p < 0.05). An informative salivary cytokine panel was developed using VEGF by logistic regression analysis (odds ratio: 0.251). Receiver operating characteristic analysis revealed that assessment of a panel using VEGF showed “good” capability for discriminating between ADHD patients and controls (area under the curve: 0.778). ADHD has been hypothesized to be associated with reduced cerebral blood flow in the frontal cortex, due to reduced VEGF levels. Our study highlights the possibility of utilizing differential salivary cytokine levels for point-of-care testing (POCT) of biomarkers in children with ADHD.

Keywords: Cytokine, saliva, attention deficit hyperactivity disorder, child, biomarker.

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Authors: I. Yakubu, Y. Y. Ziggah, C. Yeboah

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In the mining environment, tailings dam embankment is among the hazards and risk areas. The tailings dam embankment could fail and result to damages to facilities, human injuries or even fatalities. Periodic monitoring of the dam embankment is needed to help assess the safety of the tailings dam embankment. Artificial intelligence techniques such as fractals can be used to analyse the stability of the monitored dataset from survey measurement techniques. In this paper, the fractal dimension (D) was determined using D = 2-H. The Hurst parameters (H) of each monitored prism were determined by using a time domain of rescaled range programming in MATLAB software. The fractal dimensions of each monitored prism were determined based on the values of H. The results reveal that the values of the determined H were all within the threshold of 0 ≤ H ≤ 1 m. The smaller the H, the bigger the fractal dimension is. Fractal dimension values ranging from 1.359 x 10^-4 m to 1.8843 x 10^-3 m were obtained from the monitored prisms on the based on the tailing dam embankment dataset used. The ranges of values obtained indicate that the tailings dam embankment is stable.

Keywords: Hurst parameter, fractal dimension, tailings dam embankment, surveyed dataset.

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Authors: Jamileh Vasheghani Farahani

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The main purpose of this research is to show the current active faults and active tectonic of the area by three seismic networks in Tehran region: 1-Tehran Disaster Mitigation and Management Organization (TDMMO), 2-Broadband Iranian National Seismic Network Center (BIN), 3-Iranian Seismological Center (IRSC). In this study, we analyzed microearthquakes happened in Tehran city and its surroundings using the Tehran networks from 1996 to 2015. We found some active faults and trends in the region. There is a 200-year history of historical earthquakes in Tehran. Historical and instrumental seismicity show that the east of Tehran is more active than the west. The Mosha fault in the North of Tehran is one of the active faults of the central Alborz. Moreover, other major faults in the region are Kahrizak, Eyvanakey, Parchin and North Tehran faults. An important seismicity region is an intersection of the Mosha and North Tehran fault systems (Kalan village in Lavasan). This region shows a cluster of microearthquakes. According to the historical and microseismic events analyzed in this research, there is a seismic gap in SE of Tehran. The empirical relationship is used to assess the Mmax based on the rupture length. There is a probability of occurrence of a strong motion of 7.0 to 7.5 magnitudes in the region (based on the assessed capability of the major faults such as Parchin and Eyvanekey faults and historical earthquakes).

Keywords: Iran, major faults, microseismicity, Tehran.

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Authors: Jorge Cardoso

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Semantic Web services will enable the semiautomatic and automatic annotation, advertisement, discovery, selection, composition, and execution of inter-organization business logic, making the Internet become a common global platform where organizations and individuals communicate with each other to carry out various commercial activities and to provide value-added services. There is a growing consensus that Web services alone will not be sufficient to develop valuable solutions due the degree of heterogeneity, autonomy, and distribution of the Web. This paper deals with two of the hottest R&D and technology areas currently associated with the Web – Web services and the Semantic Web. It presents the synergies that can be created between Web Services and Semantic Web technologies to provide a new generation of eservices.

Keywords: Semantic Web, Web service, Web process, WWW.

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Authors: Abdalla Kablan, Joseph Falzon

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This paper is motivated by the aspect of uncertainty in financial decision making, and how artificial intelligence and soft computing, with its uncertainty reducing aspects can be used for algorithmic trading applications that trade in high frequency. This paper presents an optimized high frequency trading system that has been combined with various moving averages to produce a hybrid system that outperforms trading systems that rely solely on moving averages. The paper optimizes an adaptive neuro-fuzzy inference system that takes both the price and its moving average as input, learns to predict price movements from training data consisting of intraday data, dynamically switches between the best performing moving averages, and performs decision making of when to buy or sell a certain currency in high frequency.

Keywords: Financial decision making, High frequency trading, Adaprive neuro-fuzzy systems, moving average strategy.

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Authors: Phalaunnaphat Siriwongs

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The classroom of the 21st century is an ever changing forum for new and innovative thoughts and ideas. With increasing technology and opportunity, students have rapid access to information that only decades ago would have taken weeks to obtain. Unfortunately, new techniques and technology are not the cure for the fundamental problems that have plagued the classroom ever since education was established. Class size has been an issue long debated in academia. While it is difficult to pin point an exact number, it is clear that in this case more does not mean better. By looking into the success and pitfalls of classroom size the true advantages of smaller classes will become clear. Previously, one class was comprised of 50 students. Being seventeen and eighteen- year- old students, sometimes it was quite difficult for them to stay focused. To help them understand and gain much knowledge, a researcher introduced “The Theory of Multiple Intelligence” and this, in fact, enabled students to learn according to their own learning preferences no matter how they were being taught. In this lesson, the researcher designed a cycle of learning activities involving all intelligences so that everyone had equal opportunities to learn.

Keywords: Multiple intelligences, role play, performance assessment, formative assessment.

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Authors: Annabelle Ogochukwu Onyefulu-Kingston

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One of the major purposes of artificial intelligence (AI) today is to evaluate and analyse millions of micro and macro data in order to determine what is relevant in a particular case and proffer it in an adequate manner. Microdata, as far as it relates to AI in international arbitration, is the millions of key issues specifically mentioned by either one or both parties or by their counsels, arbitrators, or arbitral tribunals in arbitral proceedings. This can be qualifications of expert witness and admissibility of evidence, amongst others. Macro data, on the other hand, refer to data derived from the resolution of the dispute and, consequently, the final and binding award. A notable example of this includes the rationale of the award and specific and general damages awarded, amongst others. This paper aims to critically evaluate and analyses the possibility of technological inclusion in international arbitration. This research will be imploring the qualitative method by evaluating existing literature on the consequence of applying AI to both micro and macro data in international arbitration, and how this can be of assistance to parties, counsels, and arbitrators.

Keywords: AI-based technologies, algorithms, arbitrators, international arbitration.

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Authors: Mine Uslu Uysal

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This paper interested in the mechanical deformation behavior of shear deformable functionally graded ceramic-metal (FGM) plates. Theoretical formulations are based on power law theory when build up functional graded material. The mechanical properties of the plate are graded in the thickness direction according to a power-law Displacement and stress is obtained using finite element method (FEM). The load is supposed to be a uniform distribution over the plate surface (XY plane) and varied in the thickness direction only. An FGM’s gradation in material properties allows the designer to tailor material response to meet design criteria. An FGM made of ceramic and metal can provide the thermal protection and load carrying capability in one material thus eliminating the problem of thermo-mechanical deformation behavior. This thesis will explore analysis of FGM flat plates and shell panels, and their applications to r structural problems. FGMs are first characterized as flat plates under pressure in order to understand the effect variation of material properties has on structural response. In addition, results are compared to published results in order to show the accuracy of modeling FGMs using ABAQUS software.

Keywords: Functionally graded material, finite element method, thermal and structural loading.

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Authors: Chunshien Li, Jhao-Wun Hu, Tai-Wei Chiang, Tsunghan Wu

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Time series forecasting is an important and widely popular topic in the research of system modeling. This paper describes how to use the hybrid PSO-RLSE neuro-fuzzy learning approach to the problem of time series forecasting. The PSO algorithm is used to update the premise parameters of the proposed prediction system, and the RLSE is used to update the consequence parameters. Thanks to the hybrid learning (HL) approach for the neuro-fuzzy system, the prediction performance is excellent and the speed of learning convergence is much faster than other compared approaches. In the experiments, we use the well-known Mackey-Glass chaos time series. According to the experimental results, the prediction performance and accuracy in time series forecasting by the proposed approach is much better than other compared approaches, as shown in Table IV. Excellent prediction performance by the proposed approach has been observed.

Keywords: forecasting, hybrid learning (HL), Neuro-FuzzySystem (NFS), particle swarm optimization (PSO), recursiveleast-squares estimator (RLSE), time series

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Authors: Yose Rizal, Maria Endo Mahata, Mira Andriani, Guoyao Wu

Abstract:

An experiment was conducted with 80 unsexed broilers of the Arbor Acress strain to determine the capability of a carrot and fruit juice wastes mixture (carrot, apple, manggo, avocado, orange, melon and Dutch egg plant) in the same proportion for replacing corn in broiler diet. This study involved a completely randomized design (CRD) with 5 treatments (0, 5, 10, 15, and 20% of juice wastes mixture in diets) and 4 replicates per treatment. Diets were isonitrogenous (22% crude protein) and isocaloric (3000 kcal/kg diet). Measured variables were feed consumption, average daily gain, feed conversion, as well as percentages of abdominal fat pad, carcass, digestive organs (liver, pancreas and gizzard), and heart. Data were analyzed by analysis of variance for CRD. Increasing juice wastes mixture levels in diets increased feed consumption (P<0.05) and average daily gain (P<0.01), while improving feed utilization efficiency (P<0.05). These treatments also affected (P<0.05) abdominal fat pad percentage but had no effect (P>0.05) on carcass, liver, pancreas, gizzard or heart percentages. In conclusion, up to 20% of juice wastes mixture could be included for the broiler diet to effectively replace up to 40% corn in the diet.

Keywords: average daily gain, feed consumption, feedconversion, juice waste mixture

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Authors: Nadya Hajar, Zainal, S., Atikah, O., Tengku Elida, T. Z. M.

Abstract:

Ethanol has been known for a long time, being perhaps the oldest product obtained through traditional biotechnology fermentation. Agriculture waste as substrate in fermentation is vastly discussed as alternative to replace edible food and utilization of organic material. Pineapple peel, highly potential source as substrate is a by-product of the pineapple processing industry. Bio-ethanol from pineapple (Ananas comosus) peel extract was carried out by controlling fermentation without any treatment. Saccharomyces ellipsoides was used as inoculum in this fermentation process as it is naturally found at the pineapple skin. In this study, the capability of Response Surface Methodology (RSM) for optimization of ethanol production from pineapple peel extract using Saccharomyces ellipsoideus in batch fermentation process was investigated. Effect of five test variables in a defined range of inoculum concentration 6- 14% (v/v), pH (4.0-6.0), sugar concentration (14-22°Brix), temperature (24-32°C) and time of incubation (30-54 hrs) on the ethanol production were evaluated. Data obtained from experiment were analyzed with RSM of MINITAB Software (Version 15) whereby optimum ethanol concentration of 8.637% (v/v) was determined. The optimum condition of 14% (v/v) inoculum concentration, pH 6, 22°Brix, 26°C and 30hours of incubation. The significant regression equation or model at the 5% level with correlation value of 99.96% was also obtained.

Keywords: Bio-ethanol, pineapple peel extract, Response Surface Methodology (RSM), Saccharomyces ellipsoideus.

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