Search results for: Nomenclature: k : time step

Authors: C. A. Barros, Ana P. Barroso

Abstract:

Any industrial company needs to determine the amount of variation that exists within its measurement process and guarantee the reliability of their data, studying the performance of their measurement system, in terms of linearity, bias, repeatability and reproducibility and stability. This issue is critical for automotive industry suppliers, who are required to be certified by the 16949:2016 standard (replaces the ISO/TS 16949) of International Automotive Task Force, defining the requirements of a quality management system for companies in the automotive industry. Measurement System Analysis (MSA) is one of the mandatory tools. Frequently, the measurement system in companies is not connected to the equipment and do not incorporate the methods proposed by the Automotive Industry Action Group (AIAG). To address these constraints, an R&D project is in progress, whose objective is to develop a web and cloud-based MSA tool. This MSA tool incorporates Industry 4.0 concepts, such as, Internet of Things (IoT) protocols to assure the connection with the measuring equipment, cloud computing, artificial intelligence, statistical tools, and advanced mathematical algorithms. This paper presents the preliminary findings of the project. The web and cloud-based MSA tool is innovative because it implements all statistical tests proposed in the MSA-4 reference manual from AIAG as well as other emerging methods and techniques. As it is integrated with the measuring devices, it reduces the manual input of data and therefore the errors. The tool ensures traceability of all performed tests and can be used in quality laboratories and in the production lines. Besides, it monitors MSAs over time, allowing both the analysis of deviations from the variation of the measurements performed and the management of measurement equipment and calibrations. To develop the MSA tool a ten-step approach was implemented. Firstly, it was performed a benchmarking analysis of the current competitors and commercial solutions linked to MSA, concerning Industry 4.0 paradigm. Next, an analysis of the size of the target market for the MSA tool was done. Afterwards, data flow and traceability requirements were analysed in order to implement an IoT data network that interconnects with the equipment, preferably via wireless. The MSA web solution was designed under UI/UX principles and an API in python language was developed to perform the algorithms and the statistical analysis. Continuous validation of the tool by companies is being performed to assure real time management of the ‘big data’. The main results of this R&D project are: MSA Tool, web and cloud-based; Python API; New Algorithms to the market; and Style Guide of UI/UX of the tool. The MSA tool proposed adds value to the state of the art as it ensures an effective response to the new challenges of measurement systems, which are increasingly critical in production processes. Although the automotive industry has triggered the development of this innovative MSA tool, other industries would also benefit from it. Currently, companies from molds and plastics, chemical and food industry are already validating it.

Keywords: Automotive industry, Industry 4.0, internet of things, IATF 16949:2016, measurement system analysis.

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Authors: Myungsook Klassen

Abstract:

Training neural networks to capture an intrinsic property of a large volume of high dimensional data is a difficult task, as the training process is computationally expensive. Input attributes should be carefully selected to keep the dimensionality of input vectors relatively small. Technical indexes commonly used for stock market prediction using neural networks are investigated to determine its effectiveness as inputs. The feed forward neural network of Levenberg-Marquardt algorithm is applied to perform one step ahead forecasting of NASDAQ and Dow stock prices.

Keywords: Stock Market Prediction, Neural Networks, Levenberg-Marquadt Algorithm, Technical Indexes

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Authors: Ye. B. Utepov, A. S. Tulebekova, A. B. Kazkeyev

Abstract:

Maturity sensors are used to determine concrete strength by the non-destructive method. The method of placement of the maturity sensors determines their number required for a certain frame of a monolithic building. This paper proposes a cheap prototype of an embedded wireless sensor for monitoring concrete structures, as well as an alternative strategy for placing sensors based on the transitional boundaries of the temperature distribution of concrete curing, which were determined by building a heat map of the temperature distribution, where unknown values are calculated by the method of inverse distance weighing. The developed prototype can simultaneously measure temperature and relative humidity over a smartphone-controlled time interval. It implements a maturity method to assess the in-situ strength of concrete, which is considered an alternative to the traditional shock impulse and compression testing method used in Kazakhstan. The prototype was tested in laboratory and field conditions. The tests were aimed at studying the effect of internal and external temperature and relative humidity on concrete's strength gain. Based on an experimentally poured concrete slab with randomly integrated maturity sensors, it the transition boundaries form elliptical forms were determined. Temperature distribution over the largest diameter of the ellipses was plotted, resulting in correct and inverted parabolas. As a result, the distance between the closest opposite crossing points of the parabolas is accepted as the maximum permissible step for setting the maturity sensors. The proposed placement strategy can be applied to sensors that measure various continuous phenomena such as relative humidity. Prototype testing has also revealed Bluetooth inconvenience due to weak signal and inability to access multiple prototypes simultaneously. For this reason, further prototype upgrades are planned in the future work.

Keywords: Heat map, placement strategy, temperature and relative humidity, wireless embedded sensor.

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Authors: X. Z. Gao, S. J. Ovaska, X. Wang

Abstract:

Prediction of sinusoidal signals with time-varying frequencies has been an important research topic in power electronics systems. To solve this problem, we propose a new fuzzy predictive filtering scheme, which is based on a Finite Impulse Response (FIR) filter bank. Fuzzy logic is introduced here to provide appropriate interpolation of individual filter outputs. Therefore, instead of regular 'hard' switching, our method has the advantageous 'soft' switching among different filters. Simulation comparisons between the fuzzy predictive filtering and conventional filter bank-based approach are made to demonstrate that the new scheme can achieve an enhanced prediction performance for slowly changing sinusoidal input signals.

Keywords: Predictive filtering, fuzzy logic, sinusoidal signals, time-varying frequencies.

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Authors: Imran Ahmed, Muhammad Islam, Syed Inayat Ali Shah, Awais Adnan

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The identification and classification of weeds are of major technical and economical importance in the agricultural industry. To automate these activities, like in shape, color and texture, weed control system is feasible. The goal of this paper is to build a real-time, machine vision weed control system that can detect weed locations. In order to accomplish this objective, a real-time robotic system is developed to identify and locate outdoor plants using machine vision technology and pattern recognition. The algorithm is developed to classify images into broad and narrow class for real-time selective herbicide application. The developed algorithm has been tested on weeds at various locations, which have shown that the algorithm to be very effectiveness in weed identification. Further the results show a very reliable performance on weeds under varying field conditions. The analysis of the results shows over 90 percent classification accuracy over 140 sample images (broad and narrow) with 70 samples from each category of weeds.

Keywords: Weed detection, Image Processing, real-timerecognition, Standard Deviation.

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Authors: Amir Azizi, Amir Yazid B. Ali, Loh Wei Ping

Abstract:

Throughput is an important measure of performance of production system. Analyzing and modeling of production throughput is complex in today-s dynamic production systems due to uncertainties of production system. The main reasons are that uncertainties are materialized when the production line faces changes in setup time, machinery break down, lead time of manufacturing, and scraps. Besides, demand changes are fluctuating from time to time for each product type. These uncertainties affect the production performance. This paper proposes Bayesian inference for throughput modeling under five production uncertainties. Bayesian model utilized prior distributions related to previous information about the uncertainties where likelihood distributions are associated to the observed data. Gibbs sampling algorithm as the robust procedure of Monte Carlo Markov chain was employed for sampling unknown parameters and estimating the posterior mean of uncertainties. The Bayesian model was validated with respect to convergence and efficiency of its outputs. The results presented that the proposed Bayesian models were capable to predict the production throughput with accuracy of 98.3%.

Keywords: Bayesian inference, Uncertainty modeling, Monte Carlo Markov chain, Gibbs sampling, Production throughput

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Authors: C. Bruni, F. Delli Priscoli, G. Koch, I. Marchetti

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The Connection Admission Control (CAC) problem is formulated in this paper as a discrete time optimal control problem. The control variables account for the acceptance/ rejection of new connections and forced dropping of in-progress connections. These variables are constrained to meet suitable conditions which account for the QoS requirements (Link Availability, Blocking Probability, Dropping Probability). The performance index evaluates the total throughput. At each discrete time, the problem is solved as an integer-valued linear programming one. The proposed procedure was successfully tested against suitably simulated data.

Keywords: Connection Admission Control, Optimal Control, Integer valued Linear Programming, Quality of Service Requirements, Robust Control.

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Authors: W. Kritsarikan, T. Patcharawit, T. Yingnakorn, S. Khumkoa

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Neodymium-iron-boron (NdFeB) magnets classified as high-power magnets are widely used in various applications such as automotive, electrical and medical devices. Because significant amounts of rare earth metals will be subjected to shortages in the future, therefore domestic NdFeB magnet waste recycling should therefore be developed in order to reduce social and environmental impacts towards a circular economy. Each type of wastes has different characteristics and compositions. As a result, these directly affect recycling efficiency as well as types and purity of the recyclable products. This research, therefore, focused on the recycling of manufacturing NdFeB magnet waste obtained from the sintering stage of magnet production and the waste contained 23.6% Nd, 60.3% Fe and 0.261% B in order to recover high purity neodymium oxide (Nd2O3) using hybrid metallurgical process via oxidative roasting and selective leaching techniques. The sintered NdFeB waste was first ground to under 70 mesh prior to oxidative roasting at 550–800 oC to enable selective leaching of neodymium in the subsequent leaching step using H2SO4 at 2.5 M over 24 h. The leachate was then subjected to drying and roasting at 700–800 oC prior to precipitation by oxalic acid and calcination to obtain Nd2O3 as the recycling product. According to XRD analyses, it was found that increasing oxidative roasting temperature led to an increasing amount of hematite (Fe2O3) as the main composition with a smaller amount of magnetite (Fe3O4) found. Peaks of Nd2O3 were also observed in a lesser amount. Furthermore, neodymium iron oxide (NdFeO3) was present and its XRD peaks were pronounced at higher oxidative roasting temperatures. When proceeded to acid leaching and drying, iron sulfate and neodymium sulfate were mainly obtained. After the roasting step prior to water leaching, iron sulfate was converted to form Fe2O3 as the main compound, while neodymium sulfate remained in the ingredient. However, a small amount of Fe3O4 was still detected by XRD. The higher roasting temperature at 800 oC resulted in a greater Fe2O3 to Nd2(SO4)3 ratio, indicating a more effective roasting temperature. Iron oxides were subsequently water leached and filtered out while the solution contained mainly neodymium sulfate. Therefore, low oxidative roasting temperature not exceeding 600 oC followed by acid leaching and roasting at 800 oC gave the optimum condition for further steps of precipitation and calcination to finally achieve Nd2O3.

Keywords: NdFeB magnet waste, oxidative roasting, recycling, selective leaching

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Authors: Paul B. Stone, Subhashini Ganapathy, Mary E. Fendley, Layla Akilan

Abstract:

As notifications become more common through mobile devices, it is important to understand the impact of wearable devices for improved user experience of man-machine interfaces. This study examined the use of a wearable device for a real-time system using a computer simulated petrochemical system. The key research question was to determine how using information provided by the wearable device can improve human performance through measures of situational awareness and decision making. Results indicate that there was a reduction in response time when using the watch and there was no difference in situational awareness. Perception of using the watch was positive, with 83% of users finding value in using the watch and receiving haptic feedback.

Keywords: computer applications, haptic feedback, petrochemical systems, situational awareness, wearable technology

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Authors: Kumara Jayapathma J. H. M. S. S., Dampegama S. D. P. J.

Abstract:

Lands are valuable & limited resource which constantly changes with the growth of the population. An efficient and good land management system is essential to avoid conflicts associated with lands. This paper aims to design the prototype model of a Mobile GIS Land use and Land Information System in real-time. Homagama Divisional Secretariat Division situated in the western province of Sri Lanka was selected as the study area. The prototype model was developed after reviewing related literature. The methodology was consisted of designing and modeling the prototype model into an application running on a mobile platform. The system architecture mainly consists of a Google mapping app for real-time updates with firebase support tools. Thereby, the method of implementation consists of front-end and back-end components. Software tools used in designing applications are Android Studio with JAVA based on GeoJSON File structure. Android Studio with JAVA in GeoJSON File Synchronize to Firebase was found to be the perfect mobile solution for continuously updating Land use and Land Information System (LIS) in real-time in the present scenario. The mobile-based land use and LIS developed in this study are multiple user applications catering to different hierarchy levels such as basic users, supervisory managers, and database administrators. The benefits of this mobile mapping application will help public sector field officers with non-GIS expertise to overcome the land use planning challenges with land use updated in real-time.

Keywords: Android, Firebase, GeoJSON, GIS, JAVA, JSON, LIS, mobile GIS, real-time, REST API.

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Authors: Chongtham Jiten, K. Chandramani Singh, Radhapiyari Laishram

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Nanocrystalline powders of the lead-free piezoelectric material, tantalum-substituted potassium sodium niobate (K0.5Na0.5)(Nb0.9Ta0.1)O3 (KNNT), were produced using a Retsch PM100 planetary ball mill by setting the milling time to 15h, 20h, 25h, 30h, 35h and 40h, at a fixed speed of 250rpm. The average particle size of the milled powders was found to decrease from 12nm to 3nm as the milling time increases from 15h to 25h, which is in agreement with the existing theoretical model. An anomalous increase to 98nm and then a drop to 3nm in the particle size were observed as the milling time further increases to 30h and 40h respectively. Various sizes of these starting KNNT powders were used to investigate the effect of milling time on the microstructure, dielectric properties, phase transitions and piezoelectric properties of the resulting KNNT ceramics. The particle size of starting KNNT was somewhat proportional to the grain size. As the milling time increases from 15h to 25h, the resulting ceramics exhibit enhancement in the values of relative density from 94.8% to 95.8%, room temperature dielectric constant (εRT) from 878 to 1213, and piezoelectric charge coefficient (d33) from 108pC/N to 128pC/N. For this range of ceramic samples, grain size refinement suppresses the maximum dielectric constant (εmax), shifts the Curie temperature (Tc) to a lower temperature and the orthorhombic-tetragonal phase transition (Tot) to a higher temperature. Further increase of milling time from 25h to 40h produces a gradual degradation in the values of relative density, εRT, and d33 of the resulting ceramics.

Keywords: Ceramics, Dielectric, High-energy milling, Perovskite.

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Authors: Guo Wenyu, Qu Youli

Abstract:

A practical and simple self-indexing data structure, Partitioned Elias-Fano (PEF) - Compressed Suffix Arrays (CSA), is built in linear time for the CSA based on PEF indexes. Moreover, the PEF-CSA is compared with two classical compressed indexing methods, Ferragina and Manzini implementation (FMI) and Sad-CSA on different type and size files in Pizza & Chili. The PEF-CSA performs better on the existing data in terms of the compression ratio, count, and locates time except for the evenly distributed data such as proteins data. The observations of the experiments are that the distribution of the φ is more important than the alphabet size on the compression ratio. Unevenly distributed data φ makes better compression effect, and the larger the size of the hit counts, the longer the count and locate time.

Keywords: Compressed suffix array, self-indexing, partitioned Elias-Fano, PEF-CSA.

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Authors: Jaruwan Chutrtong, Tanakwan Bussabun

Abstract:

Study production of tempeh inoculums powder by freeze-drying comparison with dry at 50°C and the sun bask for developing efficient tempeh inoculums for tempeh producing. Rhizopus oligosporus in PDA slant cultures was incubated at 30^oC for 3-5 days until spores and mycelium. Preparation spores suspension with sterilized water and then count the number of started spores. Fill spores suspension in Rice flour and soy flour, mixed with water (in the ratio 10: 7), which is steamed and sterilized at 121°C 15min. Incubated at room temperature for 4 days, count number of spores. Then take the progressive infection and full spore dough to dry at 50°C, sun bask, and lyophilize. Grind to powder. Then pack in plastic bags, stored at 5°C. To investigate quality of inoculums which use different methods, tempeh was fermented every 4 weeks for 24 weeks of the experiment. The result found that rice flour is not suitable to use as raw material in the production of powdered spores.  Fungi can growth rarely. Less number of spores and requires more time than soy flour. For drying method, lyophilization is the least possible time. Samples from this method are very hard and very dark and harder to grind than other methods. Drying at 50°C takes longer time than lyophilization but can also set time use for drying. Character of the dry samples is hard solid and brown color, but can be grinded easier. The sun drying takes the longest time, can’t determine the exact time. When the spore powder was used to fermented tempeh immediately, product has similar characters as which use spores that was fresh prepared. The tempeh has normal quality. When spore powder stored at low temperature, tempeh from storage spore in weeks 4, 8 and 12 is still normal. Time spending in production was close to the production of fresh spores. After storage  spores for 16 and 20 weeks, tempeh is still normal but growth and sporulation were take longer time than usual (about 6 hours). At 24 week storage, fungal growth is not good, made tempeh looks inferior to normal color, also smell and texture.

Keywords: Freeze drying, preparation, spore powder, tempeh.

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Authors: N. Seyedrazi, S. H. Razavi, Z. Emam-Djomeh

Abstract:

In this research, natural canthaxanthin as one of the most important carotenoids was extracted from Dietzia natronolimnaea HS-1. The changes of canthaxanthin enriched in oilin- water emulsions with vegetable oil (5 mg/ 100 mL), Arabic gum (5 mg/100 mL), and potassium sorbate (0.5 g/100 mL) was investigated. The effects of different pH (3, 5 and 7), as well as, time treatment (3, 18 and 33 days) in the environmental temperature (24°C) on the degradation were studied by response surface methodology (RSM). The Hunter values (L*, a*, and b*) and the concentration of canthaxanthin (C, mg/L) illustrated more degradation of this pigment at low pHs (pH≤ 4) by passing the time (days≥10) with R² 97.00%, 91.31%, 97.60%, and 99.54% for C, L*, a*, and b* respectively. The predicted model were found to be significant (p<0.05).

Keywords: Degradation, Emulsion, Response SurfaceMethodology (RSM)

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Authors: Yongkun Li, Meng Hu

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A stage-structured predator-prey system with two time delays is considered. By analyzing the corresponding characteristic equation, the local stability of a positive equilibrium is investigated and the existence of Hopf bifurcations is established. Formulae are derived to determine the direction of bifurcations and the stability of bifurcating periodic solutions by using the normal form theory and center manifold theorem. Numerical simulations are carried out to illustrate the theoretical results. Based on the global Hopf bifurcation theorem for general functional differential equations, the global existence of periodic solutions is established.

Keywords: Predator-prey system, stage structure, time delay, HOPF bifurcation, periodic solution, stability.

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Authors: Kejun Zhuang, Hailong Zhu

Abstract:

The dynamics of a delayed mathematical model for Hes1 oscillatory expression are investigated. The linear stability of positive equilibrium and existence of local Hopf bifurcation are studied. Moreover, the global existence of large periodic solutions has been established due to the global bifurcation theorem.

Keywords: Hes1, Hopf bifurcation, time delay, transcriptional repression loop

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Authors: Wan Nural Jawahir Wan Yussof, Hans Burkhardt

Abstract:

Liver segmentation is the first significant process for liver diagnosis of the Computed Tomography. It segments the liver structure from other abdominal organs. Sophisticated filtering techniques are indispensable for a proper segmentation. In this paper, we employ a 3D anisotropic diffusion as a preprocessing step. While removing image noise, this technique preserve the significant parts of the image, typically edges, lines or other details that are important for the interpretation of the image. The segmentation task is done by using thresholding with automatic threshold values selection and finally the false liver region is eliminated using 3D connected component. The result shows that by employing the 3D anisotropic filtering, better liver segmentation results could be achieved eventhough simple segmentation technique is used.

Keywords: 3D Anisotropic Diffusion, non-linear filtering, CT Liver.

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Authors: B. Vahdani, S. M. Mousavi, R. Tavakkoli-Moghaddam

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Nowadays, the plant location selection has a critical impact on the performance of numerous companies. In this paper, a methodology is presented to solve this problem. The three decision making methods, namely Delphi, AHP and improved VIKOR, are hybridized in order to make the best use of information available based on the decision makers or experts. In this respect, the aim of using Delphi is to select the most influential criteria by a few decision makers. The AHP is utilized to give weights of the selected criteria. Finally, the improved VIKOR method is applied to rank alternatives. At the end of paper, an application example demonstrates the applicability of the proposed methodology.

Keywords: Decision making, Plant location selection, Delphi, AHP, Improved VIKOR.

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Authors: Alemu Moges Belay

Abstract:

In the 1980s, companies began to feel the effect of three major influences on their product development: newer and innovative technologies, increasing product complexity and larger organizations. And therefore companies were forced to look for new product development methods. This paper tries to focus on the two of new product development methods (DFM and CE). The aim of this paper is to see and analyze different product development methods specifically on Design for Manufacturability and Concurrent Engineering. Companies can achieve and be benefited by minimizing product life cycle, cost and meeting delivery schedule. This paper also presents simplified models that can be modified and used by different companies based on the companies- objective and requirements. Methodologies that are followed to do this research are case studies. Two companies were taken and analysed on the product development process. Historical data, interview were conducted on these companies in addition to that, Survey of literatures and previous research works on similar topics has been done during this research. This paper also tries to show the implementation cost benefit analysis and tries to calculate the implementation time. From this research, it has been found that the two companies did not achieve the delivery time to the customer. Some of most frequently coming products are analyzed and 50% to 80 % of their products are not delivered on time to the customers. The companies are following the traditional way of product development that is sequentially design and production method, which highly affect time to market. In the case study it is found that by implementing these new methods and by forming multi disciplinary team in designing and quality inspection; the company can reduce the workflow steps from 40 to 30.

Keywords: Design for manufacturability, Concurrent Engineering, Time-to-Market, Product development

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Authors: Syed Zohaib Javaid Zaidi, W. Iqbal

Abstract:

The industrial automation is dependent upon pneumatic control systems. The industrial units are now controlled with digital control systems to tackle the process variables like Temperature, Pressure, Flow rates and Composition.

This research work produces an evaluation of the response time fluctuations for proportional mode, proportional integral and proportional integral derivative modes of automated chemical process control. The controller output is measured for different values of gain with respect to time in three modes (P, PI and PID). In case of P-mode for different values of gain the controller output has negligible change. When the controller output of PI-mode is checked for constant gain, it can be seen that by decreasing the integral time the controller output has showed more fluctuations. The PID mode results have found to be more interesting in a way that when rate minute has changed, the controller output has also showed fluctuations with respect to time.  The controller output for integral mode and derivative mode are observed with lesser steady state error, minimum offset and larger response time to control the process variable.   The tuning parameters in case of P-mode are only steady state gain with greater errors with respect to controller output. The integral mode showed controller outputs with intermediate responses during integral gain (ki).  By increasing the rate minute the derivative gain (kd) also increased which showed the controlled oscillations in case of PID mode and lesser overshoot.

Keywords: Controller Output, P, PI &PID modes, Steady state gain.

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Authors: Hatem Hajri, Mohamed-Cherif Rahal

Abstract:

Both Lidars and Radars are sensors for obstacle detection. While Lidars are very accurate on obstacles positions and less accurate on their velocities, Radars are more precise on obstacles velocities and less precise on their positions. Sensor fusion between Lidar and Radar aims at improving obstacle detection using advantages of the two sensors. The present paper proposes a real-time Lidar/Radar data fusion algorithm for obstacle detection and tracking based on the global nearest neighbour standard filter (GNN). This algorithm is implemented and embedded in an automative vehicle as a component generated by a real-time multisensor software. The benefits of data fusion comparing with the use of a single sensor are illustrated through several tracking scenarios (on a highway and on a bend) and using real-time kinematic sensors mounted on the ego and tracked vehicles as a ground truth.

Keywords: Ground truth, Hungarian algorithm, lidar Radar data fusion, global nearest neighbor filter.

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Authors: Anis Gharbi

Abstract:

This paper considers the problem of scheduling maintenance actions for identical aircraft gas turbine engines. Each one of the turbines consists of parts which frequently require replacement. A finite inventory of spare parts is available and all parts are ready for replacement at any time. The inventory consists of both new and refurbished parts. Hence, these parts have different field lives. The goal is to find a replacement part sequencing that maximizes the time that the aircraft will keep functioning before the inventory is replenished. The problem is formulated as an identical parallel machine scheduling problem where the minimum completion time has to be maximized. Two models have been developed. The first one is an optimization model which is based on a 0-1 linear programming formulation, while the second one is an approximate procedure which consists in decomposing the problem into several two-machine subproblems. Each subproblem is optimally solved using the first model. Both models have been implemented using Lingo and have been tested on two sets of randomly generated data with up to 150 parts and 10 turbines. Experimental results show that the optimization model is able to solve only instances with no more than 4 turbines, while the decomposition procedure often provides near-optimal solutions within a maximum CPU time of 3 seconds.

Keywords: Aircraft turbines, Scheduling, Identical parallel machines, 0-1 linear programming, Heuristic.

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Authors: S. Madhavi, S. Abirami, C. Bharathi, B. Ekambaram, T. Krishna Sankar, A. Nattudurai, N. Vijayarangan

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The high utilization rate of Automated Teller Machine (ATM) has inevitably caused the phenomena of waiting for a long time in the queue. This in turn has increased the out of stock situations. The ATM utilization helps to determine the usage level and states the necessity of the ATM based on the utilization of the ATM system. The time in which the ATM used more frequently (peak time) and based on the predicted solution the necessary actions are taken by the bank management. The analysis can be done by using the concept of Data Mining and the major part are analyzed based on the predictive data mining. The results are predicted from the historical data (past data) and track the relevant solution which is required. Weka tool is used for the analysis of data based on predictive data mining.

Keywords: ATM, Bank Management, Data Mining, Historical data, Predictive Data Mining, Weka tool.

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Authors: Chih Chin Yang, Lan Hui Huang, Bo Shum Chen, Jia Liang Ke, Chung Lun Tsai

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The control of oxygen flow rate during growth of titanium dioxide by mass flow controller in DC plasma sputtering growth system is studied. The impedance of TiO2 films for inductance effect is influenced by annealing time and oxygen flow rate. As annealing time is increased, the inductance of TiO2 film is the more. The growth condition of optimum and maximum inductance for TiO2 film to serve as sensing device are oxygen flow rate of 15 sccm and large annealing time. The large inductance of TiO2 film will be adopted to fabricate the biosensor to obtain the high sensitivity of sensing in biology.

Keywords: Annealed, Inductance, Silicon substarte, Titanium dioxide

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Authors: F.J. Suárez, J.C. Granda, J. Molleda, D.F. García

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A prototype for audio and video capture and compression in real time on a Linux platform has been developed. It is able to visualize both the captured and the compressed video at the same time, as well as the captured and compressed audio with the goal of comparing their quality. As it is based on free code, the final goal is to run it in an embedded system running Linux. Therefore, we would implement a node to capture and compress such multimedia information. Thus, it would be possible to consider the project within a larger one aimed at live broadcast of audio and video using a streaming server which would communicate with our node. Then, we would have a very powerful and flexible system with several practical applications.

Keywords: Audio and video compression, Linux platform, live streaming, real time, visualization of captured and compressed video.

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Authors: Arti Vaish, Harish Parthasarathy

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The scalar wave equation for a potential in a curved space time, i.e., the Laplace-Beltrami equation has been studied in this work. An action principle is used to derive a finite element algorithm for determining the modes of propagation inside a waveguide of arbitrary shape. Generalizing this idea, the Maxwell theory in a curved space time determines a set of linear partial differential equations for the four electromagnetic potentials given by the metric of space-time. Similar to the Einstein-s formulation of the field equations of gravitation, these equations are also derived from an action principle. In this paper, the expressions for the action functional of the electromagnetic field have been derived in the presence of gravitational field.

Keywords: General theory of relativity, electromagnetism, metric tensor, Maxwells equations, test functions, finite element method.

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Authors: Liliana Feleagă, Niculae Feleagă, Vasile Răileanu

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Although agriculture is an important part of the world economy, accounting in agriculture still has many shortcomings. The adoption of IAS 41 “Agriculture” has tried to improve this situation and increase the comparability of financial statements of entities in the agricultural sector. Although controversial, IAS 41 is the first step of a consistent transition to fair value assessment in the agricultural sector. The objective of our work is the analysis of IAS 41 and current accounting agricultural situation in Romania. Accounting regulations in Romania are in accordance with European directives and, in many respects, converged with IFRS referential. Provisions of IAS 41, however, are not reflected directly in Romanian regulations. With the increase of forest land transactions, it is expected that recognition and measurement of biological assets under IAS 41 to become a necessity.

Keywords: Accounting Agricultural, Biological Assets, Fair value, IAS 41

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Authors: Hamed Sabahno

Abstract:

In this paper, an inventory model with finite and constant replenishment rate, price dependant demand rate, time value of money and inflation, finite time horizon, lead time and exponential deterioration rate and with the objective of maximizing the present worth of the total system profit is developed. Using a dynamic programming based solution algorithm, the optimal sequence of the cycles can be found and also different optimal selling prices, optimal order quantities and optimal maximum inventories can be obtained for the cycles with unequal lengths, which have never been done before for this model. Also, a numerical example is used to show accuracy of the solution procedure.

Keywords: Deteriorating items, Dynamic programming, Finitereplenishment rate, Inventory control, Operation Research.

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Authors: Javad Razjouyan, Shahriar Gharibzadeh, Ali Fallah, Mehdi Moghaddasi, Mohsen Seyfi, Amir Kasaeian

Abstract:

Paced Auditory Serial Addition Test (PASAT) has been used as a common research tool for different neurological disorders like Multiple Sclerosis. Recently, technology let researchers to introduce a new versions of the visual test, the paced visual serial addition test (PVSAT). In this paper, the computerized version of these two tests is introduced. Beside the number of true responses are interpreted, the reaction time of subjects are calculated by the software. We hypothesize that paying attention to the reaction time may be valuable. For this purpose, sixty eight female normal subjects and fifty eight male normal subjects are enrolled in the study. We investigate the similarity between the PASAT3 and PVSAT3 in number of true responses and the new criterion (the average reaction time of each subject). The similarity between two tests were rejected (p-value = 0.000) which means that these two test differ. The effect of sex in the tests were not approved since the pvalues of different between PASAT3 and PVSAT3 in both sex is the same (p-value = 0.000) which means that male and female subjects performed the tests at no different level of performance. The new criterion shows a negative correlation with the age which offers aged normal subjects may have the same number of true responses as the young subjects but they have latent responses. This will give prove for the importance of reaction time.

Keywords: Paced Auditory Serial Addition Test, Pace Visual Serial Addition Test, reaction time.

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Authors: K. Kalaikumar, E. Baburaj

Abstract:

One of the problems to be addressed in wireless sensor networks is the issues related to cross layer communication. Cross layer architecture shares the information across the layer, ensuring Quality of Services (QoS). With this shared information, MAC protocol adapts effective functionality maintenance such as route selection on changeable sensor network environment. However, time slot assignment and neighbour route selection time duration for cross layer have not been carried out. The time varying physical layer communication over cross layer causes high traffic load in the sensor network. Though, the traffic load was reduced using cross layer optimization procedure, the computational cost is high. To improve communication efficacy in the sensor network, a self-determined time slot based Cross-Layered Neighbour Route Discovery (C-LNRD) method is presented in this paper. In the presented work, the initial process is to discover the route in the sensor network using Dynamic Source Routing based Medium Access Control (MAC) sub layers. This process considers MAC layer operation with dynamic route neighbour table discovery. Then, the discovered route path for packet communication employs Broad Route Distributed Time Slot Assignment method on Cross-Layered Sensor Network system. Broad Route means time slotting on varying length of the route paths. During packet communication in this sensor network, transmission of packets is adjusted over the different time with varying ranges for controlling the traffic rate. Finally, Rayleigh fading model is developed in C-LNRD to identify the performance of the sensor network communication structure. The main task of Rayleigh Fading is to measure the power level of each communication under MAC sub layer. The minimized power level helps to easily reduce the computational cost of packet communication in the sensor network. Experiments are conducted on factors such as power factor, on packet communication, neighbour route discovery time, and information (i.e., packet) propagation speed.

Keywords: Medium access control, neighbour route discovery, wireless sensor network, Rayleigh fading, distributed time slot assignment

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