Search results for: traffic speed prediction.

Authors: Khampheth Bounnady, Boontee Kruatrachue, Somkiat Wangsiripitak

Abstract:

This paper proposed high level feature for online Lao handwritten recognition. This feature must be high level enough so that the feature is not change when characters are written by different persons at different speed and different proportion (shorter or longer stroke, head, tail, loop, curve). In this high level feature, a character is divided in to sequence of curve segments where a segment start where curve reverse rotation (counter clockwise and clockwise). In each segment, following features are gathered cumulative change in direction of curve (- for clockwise), cumulative curve length, cumulative length of left to right, right to left, top to bottom and bottom to top ( cumulative change in X and Y axis of segment). This feature is simple yet robust for high accuracy recognition. The feature can be gather from parsing the original time sampling sequence X, Y point of the pen location without re-sampling. We also experiment on other segmentation point such as the maximum curvature point which was widely used by other researcher. Experiments results show that the recognition rates are at 94.62% in comparing to using maximum curvature point 75.07%. This is due to a lot of variations of turning points in handwritten.

Keywords: Handwritten feature, chain code, Lao handwritten recognition.

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Authors: Eugene Y. C. Wong, Henry Y. K. Lau, Mardjuki Raman

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CO₂ emissions from maritime transport operations represent a substantial part of the total greenhouse gas emission. Vessels are designed with better energy efficiency. Minimizing CO₂ emission in maritime operations plays an important role in supply chain decarbonisation. This paper reviews the initiatives on slow steaming operations towards the reduction of carbon emission. It investigates the relationship and impact among slow steaming cost reduction, carbon emission reduction, and shipment delay. A scenario-based cost-driven decision support model is developed to facilitate the selection of the optimal slow steaming options, considering the cost on bunker fuel consumption, available speed, carbon emission, and shipment delay. The incorporation of the social cost of cargo is reviewed and suggested. Additional measures on the effect of vessels sizes, routing, and type of fuels towards decarbonisation are discussed.

Keywords: Slow steaming, carbon emission, maritime logistics, sustainability, green supply chain.

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Authors: Karunakar A K, Manohara Pai M M

Abstract:

In 3D-wavelet video coding framework temporal filtering is done along the trajectory of motion using Motion Compensated Temporal Filtering (MCTF). Hence computationally efficient motion estimation technique is the need of MCTF. In this paper a predictive technique is proposed in order to reduce the computational complexity of the MCTF framework, by exploiting the high correlation among the frames in a Group Of Picture (GOP). The proposed technique applies coarse and fine searches of any fast block based motion estimation, only to the first pair of frames in a GOP. The generated motion vectors are supplied to the next consecutive frames, even to subsequent temporal levels and only fine search is carried out around those predicted motion vectors. Hence coarse search is skipped for all the motion estimation in a GOP except for the first pair of frames. The technique has been tested for different fast block based motion estimation algorithms over different standard test sequences using MC-EZBC, a state-of-the-art scalable video coder. The simulation result reveals substantial reduction (i.e. 20.75% to 38.24%) in the number of search points during motion estimation, without compromising the quality of the reconstructed video compared to non-predictive techniques. Since the motion vectors of all the pair of frames in a GOP except the first pair will have value ±1 around the motion vectors of the previous pair of frames, the number of bits required for motion vectors is also reduced by 50%.

Keywords: Motion Compensated Temporal Filtering, predictivemotion estimation, lifted wavelet transform, motion vector

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Authors: Ahmad Tariq Sheikh, Shahzad Amin Sheikh

Abstract:

A new distance-adjusted approach is proposed in which static square contours are defined around an estimated symbol in a QAM constellation, which create regions that correspond to fixed step sizes and weighting factors. As a result, the equalizer tap adjustment consists of a linearly weighted sum of adaptation criteria that is scaled by a variable step size. This approach is the basis of two new algorithms: the Variable step size Square Contour Algorithm (VSCA) and the Variable step size Square Contour Decision-Directed Algorithm (VSDA). The proposed schemes are compared with existing blind equalization algorithms in the SCA family in terms of convergence speed, constellation eye opening and residual ISI suppression. Simulation results for 64-QAM signaling over empirically derived microwave radio channels confirm the efficacy of the proposed algorithms. An RTL implementation of the blind adaptive equalizer based on the proposed schemes is presented and the system is configured to operate in VSCA error signal mode, for square QAM signals up to 64-QAM.

Keywords: Adaptive filtering, Blind Equalization, Square Contour Algorithm.

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Authors: Rajesh Mehra, Bharti Thakur

Abstract:

In this paper, an Infinite Impulse Response (IIR) filter has been designed and simulated on an Field Programmable Gate Arrays (FPGA). The implementation is based on Multiply Add and Accumulate (MAC) algorithm which uses multiply operations for design implementation. Parallel Pipelined structure is used to implement the proposed IIR Filter taking optimal advantage of the look up table of target device. The designed filter has been synthesized on Digital Signal Processor (DSP) slice based FPGA to perform multiplier function of MAC unit. The DSP slices are useful to enhance the speed performance. The proposed design is simulated with Matlab, synthesized with Xilinx Synthesis Tool, and implemented on FPGA devices. The Virtex 5 FPGA based design can operate at an estimated frequency of 81.5 MHz as compared to 40.5 MHz in case of Spartan 3 ADSP based design. The Virtex 5 based implementation also consumes less slices and slice flip flops of target FPGA in comparison to Spartan 3 ADSP based implementation to provide cost effective solution for signal processing applications.

Keywords: Butterworth, DSP, IIR, MAC, FPGA.

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Authors: Uma Batra, Seema Kapoor

Abstract:

Commercial hydroxyapatite (HA) was reinforced by adding 2, 5, and 10 wt % of 28.5%CaO-28.5%P2O5-38%Na2 O- 5%CaF2 based glass and then sintered. Although HA shows good biocompatibility with the human body, its applications are limited to non load-bearing areas and coatings due to its poor mechanical properties. These mechanical properties can be improved substantially with addition of glass ceramics by sintering. In this study, the effects of sintering hydroxyapatite with above specified phosphate glass additions are quantified. Each composition was sintered over a range of temperatures. Scanning electron microscopy and x-ray diffraction were used to characterize the microstructure and phases of the composites. The density, microhardness, and compressive strength were measured using Archimedes Principle, Vickers Microhardness Tester (at 0.98 N), and Instron Universal Testing Machine (cross speed of 0.5 mm/min) respectively. These results were used to indicate which composition provided suitable material for use in hard tissue replacement. Composites containing 10 wt % glass additions formed dense HA/TCP (tricalcium phosphate) composite materials possessing good compressive strength and hardness than HA. In-vitro bioactivity was assessed by evaluating changes in pH and Ca2+ ion concentration of SBF-simulated body fluid on immersion of these composites in it for two weeks.

Keywords: Bioglass, Composite, Hydroxyapatite, Sintering.

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Authors: Z. N. Haji, S. O. Oyadiji, H. Samami, O. Farrell

Abstract:

The prediction of the vibration response of rubber products by analytical or numerical method depends mainly on the predefined intrinsic material properties such as Young’s modulus, damping factor and Poisson’s ratio. Such intrinsic properties are determined experimentally by subjecting a bonded rubber sample to compression tests. The compression tests on such a sample yield an apparent Young’s modulus which is greater in magnitude than the intrinsic Young’s modulus of the rubber. As a result, many analytical equations have been developed to determine Young’s modulus from an apparent Young’s modulus of bonded rubber materials. In this work, the applicability of some of these analytical equations is assessed via experimental testing. The assessment is based on testing of vulcanized nitrile butadiene rubber (NBR70) samples using tensile test and compression test methods. The analytical equations are used to determine the intrinsic Young’s modulus from the apparent modulus that is derived from the compression test data of the bonded rubber samples. Then, these Young’s moduli are compared with the actual Young’s modulus that is derived from the tensile test data. The results show significant discrepancy between the Young’s modulus derived using the analytical equations and the actual Young’s modulus.

Keywords: Bonded rubber, quasi-static test, shape factor, apparent Young’s modulus.

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Authors: Mohammad Namazi, Mohammad Sadeghzadeh Maharluie

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Predicting earnings management is vital for the capital market participants, financial analysts and managers. The aim of this research is attempting to respond to this query: Is there a significant difference between the regression model and neural networks’ models in predicting earnings management, and which one leads to a superior prediction of it? In approaching this question, a Linear Regression (LR) model was compared with two neural networks including Multi-Layer Perceptron (MLP), and Generalized Regression Neural Network (GRNN). The population of this study includes 94 listed companies in Tehran Stock Exchange (TSE) market from 2003 to 2011. After the results of all models were acquired, ANOVA was exerted to test the hypotheses. In general, the summary of statistical results showed that the precision of GRNN did not exhibit a significant difference in comparison with MLP. In addition, the mean square error of the MLP and GRNN showed a significant difference with the multi variable LR model. These findings support the notion of nonlinear behavior of the earnings management. Therefore, it is more appropriate for capital market participants to analyze earnings management based upon neural networks techniques, and not to adopt linear regression models.

Keywords: Earnings management, generalized regression neural networks, linear regression, multi-layer perceptron, Tehran stock exchange.

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Authors: Tanveer A. Khan, Xue Y. Deng, Yan K. Wang, Xu Si-Wen

Abstract:

Experiments have been carried out at sub-critical Reynolds number to investigate free-to-roll motions induced by forebody and/or wings complex flow on a 30° swept back nonslender wings-slender body-model for static and dynamic (pitch-up) cases. For the dynamic (pitch-up) case it has been observed that roll amplitude decreases and lag increases with increase in pitching speed. Decrease in roll amplitude with increase in pitch rate is attributed to low disturbing rolling moment due to weaker interaction between forebody and wing flow components. Asymmetric forebody vortices dominate and control the roll motion of the model in dynamic case when non-dimensional pitch rate ≥ 1x10-2. Effectiveness of the active control scheme utilizing rotating nose with artificial tip perturbation is observed to be low in the angle of attack region where the complex flow over the wings has contributions from both forebody and wings.

Keywords: Artificial Tip Perturbation, ExperimentalInvestigations, Forebody Asymmetric Vortices, Non-slender Wings-Body Model, Wing Rock

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Authors: Aya Maher

Abstract:

The growing problem of youth unemployment in Egypt after the 25th January Revolution has directed the attention of some human resource experts towards considering remote employment as a partial remedy for the unemployed youth instead of the unavailable traditional jobs, a trend which will also help with the congested offices and unsolved traffic problem in Cairo and spread a flexible work culture, but despite of that, the main issue remains unresolved for these organizations to deal with the system challenges. In the past few years, in developed countries, there has been a growing trend for many companies to shift to remote employment instead of the traditional office employment for many reasons: due to the growing technological advances that helped some employees do their work from home on a part time basis, the need for achieving an employee-s work balance in the middle of unbalanced complicated life, top management focus on employee-s productivity rather their time spent at work. The objective of this paper is to study and analyze the advantages and challenges that Egypt-s labor force will be facing in their implementation of remote or virtual employment in both government and private organizations after the 25th January revolution. Therefore, the research question will be: What are the advantages and different challenges that Egyptian organizations might face in their implementation for remote employment system and how can they manage these challenges for the system to work effectively? The study is divided into six main parts: the introduction, objective and importance of the study, research problem, methodology, experience of some countries that implemented remote employment, advantages and challenges of implementing remote employment in Egypt and then the conclusion which discuses the results and recommendations of the study.

Keywords: 25th January Revolution, Egypt, Remote Employment, Telework, Work From Home (WFH).

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Authors: Jyong Lin, Shih-Chang Chen, Yu-Tsen Shih, Shi-Huang Chen

Abstract:

This paper presents a remote on-line diagnostic system for vehicles via the use of On-Board Diagnostic (OBD), GPS, and 3G techniques. The main parts of the proposed system are on-board computer, vehicle monitor server, and vehicle status browser. First, the on-board computer can obtain the location of deriver and vehicle status from GPS receiver and OBD interface, respectively. Then on-board computer will connect with the vehicle monitor server through 3G network to transmit the real time vehicle system status. Finally, vehicle status browser could show the remote vehicle status including vehicle speed, engine rpm, battery voltage, engine coolant temperature, and diagnostic trouble codes. According to the experimental results, the proposed system can help fleet managers and car knockers to understand the remote vehicle status. Therefore this system can decrease the time of fleet management and vehicle repair due to the fleet managers and car knockers who find the diagnostic trouble messages in time.

Keywords: Diagnostic Trouble Code (DTC), Electronic Control Unit (ECU), Global Position System (GPS), On-Board Diagnostic (OBD).

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Authors: Arūnas Burinskas

Abstract:

Although Europe is on the threshold of a new industrial revolution called Industry 4.0, many believe that this will increase the flexibility of production, the mass adaptation of products to consumers and the speed of their service; it will also improve product quality and dramatically increase productivity. However, as expected, all the benefits of Industry 4.0 face many of the inevitable changes and challenges they pose. One of them is the inevitable transformation of current competition and business models. This article examines the possible results of competitive conversion from the classic Bertrand and Cournot models to qualitatively new competition based on innovation. Ability to deliver a new product quickly and the possibility to produce the individual design (through flexible and quickly configurable factories) by reducing equipment failures and increasing process automation and control is highly important. This study shows that the ongoing transformation of the competition model is changing the game. This, together with the creation of complex value networks, means huge investments that make it particularly difficult for small and medium-sized enterprises. In addition, the ongoing digitalization of data raises new concerns regarding legal obligations, intellectual property, and security.

Keywords: Bertrand and Cournot Competition, competition model, Industry 4.0, industrial organization, monopolistic competition.

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Authors: Taylan Kabbani, Ekrem Duman

Abstract:

Deep Reinforcement Learning (DRL) algorithms can scale to previously intractable problems. The automation of profit generation in the stock market is possible using DRL, by combining  the financial assets price ”prediction” step and the ”allocation” step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. This work represents a DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem as a Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. We then solved the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm and achieved a 2.68 Sharpe ratio on the test dataset. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of DRL in financial markets over other types of machine learning and proves its credibility and advantages of strategic decision-making.

Keywords: Autonomous agent, deep reinforcement learning, MDP, sentiment analysis, stock market, technical indicators, twin delayed deep deterministic policy gradient.

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Authors: Kittisak Kerdprasop, Nittaya Kerdprasop

Abstract:

The problem of frequent pattern discovery is defined as the process of searching for patterns such as sets of features or items that appear in data frequently. Finding such frequent patterns has become an important data mining task because it reveals associations, correlations, and many other interesting relationships hidden in a database. Most of the proposed frequent pattern mining algorithms have been implemented with imperative programming languages. Such paradigm is inefficient when set of patterns is large and the frequent pattern is long. We suggest a high-level declarative style of programming apply to the problem of frequent pattern discovery. We consider two languages: Haskell and Prolog. Our intuitive idea is that the problem of finding frequent patterns should be efficiently and concisely implemented via a declarative paradigm since pattern matching is a fundamental feature supported by most functional languages and Prolog. Our frequent pattern mining implementation using the Haskell and Prolog languages confirms our hypothesis about conciseness of the program. The comparative performance studies on line-of-code, speed and memory usage of declarative versus imperative programming have been reported in the paper.

Keywords: Frequent pattern mining, functional programming, pattern matching, logic programming.

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Authors: Bakhiet, Shenouda, Gamal Abouzeid Abdel-Rahim, Norihiro Izumi

Abstract:

The correct design of the regulators structure requires complete prediction of the ultimate dimensions of the scour hole profile formed downstream the solid apron. The study of scour downstream regulator is studied either on solid aprons by means of velocity distribution or on movable bed by studying the topography of the scour hole formed in the downstream. In this paper, a new technique was developed to study the scour hole downstream regulators on movable beds. The study was divided into two categories; the first is to find out the sum of the lengths of rigid apron behind the gates in addition to the length of scour hole formed downstream, while the second is to find the minimum length of rigid apron behind the gates to prevent erosion downstream it. The study covers free and submerged hydraulic jump conditions in both symmetrical and asymmetrical under-gated regulations. From the comparison between the studied categories, we found that the minimum length of rigid apron to prevent scour (Ls) is greater than the sum of the lengths of rigid apron and that of scour hole formed behind it (L+Xs). On the other hand, the scour hole dimensions in case of submerged hydraulic jump is always greater than free one, also the scour hole dimensions in asymmetrical operation is greater than symmetrical one.

Keywords: Movable bed, Regulators, Scour, Symmetrical and asymmetrical operation

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Authors: Worachat Wannawong, Usa W. Humphries, Prungchan Wongwises, Suphat Vongvisessomjai

Abstract:

The three steps of the standard one-way nested grid for a regional scale of the third generation WAve Model Cycle 4 (WAMC4) is scrutinized. The model application is enabled to solve the energy balance equation on a coarse resolution grid in order to produce boundary conditions for a smaller area by the nested grid technique. In the present study, the model takes a full advantage of the fine resolution of wind fields in space and time produced by the available U.S. Navy Global Atmospheric Prediction System (NOGAPS) model with 1 degree resolution. The nested grid application of the model is developed in order to gradually increase the resolution from the open ocean towards the South China Sea (SCS) and the Gulf of Thailand (GoT) respectively. The model results were compared with buoy observations at Ko Chang, Rayong and Huahin locations which were obtained from the Seawatch project. In addition, the results were also compared with Satun based weather station which was provided from Department of Meteorology, Thailand. The data collected from this station presented the significant wave height (Hs) reached 12.85 m. The results indicated that the tendency of the Hs from the model in the spherical coordinate propagation with deep water condition in the fine grid domain agreed well with the Hs from the observations.

Keywords: energy balance equation, Gulf of Thailand, nested gridapplication, South China Sea, wave model.

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Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

Abstract:

In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: Data Estimation, link data, machine learning, road network.

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Authors: Ly. Benbahouche

Abstract:

Currently, several soft switching topologies have been studied to achieve high power switching efficiency, reduced cost, improved reliability and reduced parasites. It is well known that improvement in power electronics systems always depend on advanced in power devices. The IGBT has been successfully used in a variety of switching applications such as motor drives and appliance control because of its superior characteristics.

The aim of this paper is focuses on simulation and explication of the internal dynamics of IGBTs behaviour under the most popular soft switching schemas that is Zero Current Switching (ZCS) environments.

The main purpose of this paper is to point out some mechanisms relating to current tail during the turn-off and examination of the response at turn-off with variation of temperature, inductance L, snubber capacitors Cs, and bus voltage in order to achieve an improved understanding of internal carrier dynamics. It is shown that the snubber capacitor, the inductance and even the temperature controls the magnitude and extent of the tail current, hence the turn-off time (switching speed of the device).

Moreover, it has also been demonstrated that the ZCS switching can be utilized efficiently to improve and reduce the power losses as well as the turn-off time. Furthermore, the turn-off loss in ZCS was found to depend on the time of switching of the device.

Keywords: PT-IGBT, ZCS, turn-off losses, dV/dt.

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Authors: J. F. Viljoen, Catherine Foxcroft

Abstract:

Expert sight readers rely on their ability to recognize patterns in scores, their inner hearing and prediction skills in order to perform complex sight reading exercises. They also have the ability to observe deviations from expected patterns in musical scores. This increases the “Eye-hand span” (reading ahead of the point of playing) in order to process the elements in the score. The study aims to investigate the gaze patterns of expert and non-expert sight readers focusing on key and time signatures. 20 musicians were tasked with playing 12 sight reading examples composed for one hand and five examples composed for two hands to be performed on a piano keyboard. These examples were composed in different keys and time signatures and included accidentals and changes of time signature to test this theory. Results showed that the experts fixate more and for longer on key and time signatures as well as deviations in examples for two hands than the non-expert group. The inverse was true for the examples for one hand, where expert sight readers showed fewer and shorter fixations on key and time signatures as well as deviations. This seems to suggest that experts focus more on the key and time signatures as well as deviations in complex scores to facilitate sight reading. The examples written for one appeared to be too easy for the expert sight readers, compromising gaze patterns.

Keywords: Cognition, eye tracking, musical notation, sight reading.

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Authors: M. Hari Prabhu

Abstract:

This paper is based on the performance of the Switched Reluctance Motor (SRM) drives using Z-Source Inverter with the simplified rule base of Fuzzy Logic Controller (FLC) with the output scaling factor (SF) self-tuning mechanism are proposed. The aim of this paper is to simplify the program complexity of the controller by reducing the number of fuzzy sets of the membership functions (MFs) without losing the system performance and stability via the adjustable controller gain. ZSI exhibits both voltage-buck and voltage-boost capability. It reduces line harmonics, improves reliability, and extends output voltage range. The output SF of the controller can be tuned continuously by a gain updating factor, whose value is derived from fuzzy logic, with the plant error and error change ratio as input variables. Then the results, carried out on a four-phase 6/8 pole SRM based on the dSPACEDS1104 platform, to show the feasibility and effectiveness of the devised methods and also performance of the proposed controllers will be compared with conventional counterpart.

Keywords: Fuzzy logic controller, scaling factor (SF), switched reluctance motor (SRM), variable-speed drives.

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Authors: Somkiat Tangjitsitcharoen, Siripong Damrongthaveesak

Abstract:

This paper presents an advance in monitoring and process control of surface roughness in CNC machine for the turning and milling processes. An integration of the in-process monitoring and process control of the surface roughness is proposed and developed during the machining process by using the cutting force ratio. The previously developed surface roughness models for turning and milling processes of the author are adopted to predict the inprocess surface roughness, which consist of the cutting speed, the feed rate, the tool nose radius, the depth of cut, the rake angle, and the cutting force ratio. The cutting force ratios obtained from the turning and the milling are utilized to estimate the in-process surface roughness. The dynamometers are installed on the tool turret of CNC turning machine and the table of 5-axis machining center to monitor the cutting forces. The in-process control of the surface roughness has been developed and proposed to control the predicted surface roughness. It has been proved by the cutting tests that the proposed integration system of the in-process monitoring and the process control can be used to check the surface roughness during the cutting by utilizing the cutting force ratio.

Keywords: Turning, milling, monitoring, surface roughness, cutting force ratio.

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Authors: Venerando E. Amaro, Francisco Gabriel F. de Lima, Marcelo S.T. Santos

Abstract:

The morphological short-term evolution of Ponta do Tubarão Island (PTI) was investigated through high accurate surveys based on post-processed kinematic (PPK) relative positioning on Global Navigation Satellite Systems (GNSS). PTI is part of a barrier island system on a high energy northeast Brazilian coastal environment and also an area of high environmental sensitivity. Surveys were carried out quarterly over a two years period from May 2010 to May 2012. This paper assesses statically the performance of digital elevation models (DEM) derived from different interpolation methods to represent morphologic features and to quantify volumetric changes and TIN models shown the best results to that purposes. The MDE allowed quantifying surfaces and volumes in detail as well as identifying the most vulnerable segments of the PTI to erosion and/or accumulation of sediments and relate the alterations to climate conditions. The coastal setting and geometry of PTI protects a significant mangrove ecosystem and some oil and gas facilities installed in the vicinities from damaging effects of strong oceanwaves and currents. Thus, the maintenance of PTI is extremely required but the prediction of its longevity is uncertain because results indicate an irregularity of sedimentary balance and a substantial decline in sediment supply to this coastal area.

Keywords: DEM, GNSS, short-term monitoring, Brazil.

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Authors: Alia Alghosoun, Michael Herty, Mohammed Seaid

Abstract:

We present a new class of numerical techniques to solve shallow water flows over dry areas including run-up. Many recent investigations on wave run-up in coastal areas are based on the well-known shallow water equations. Numerical simulations have also performed to understand the effects of several factors on tsunami wave impact and run-up in the presence of coastal areas. In all these simulations the shallow water equations are solved in entire domain including dry areas and special treatments are used for numerical solution of singularities at these dry regions. In the present study we propose a new method to deal with these difficulties by reformulating the shallow water equations into a new system to be solved only in the wetted domain. The system is obtained by a change in the coordinates leading to a set of equations in a moving domain for which the wet/dry interface is the reconstructed using the wave speed. To solve the new system we present a finite volume method of Lax-Friedrich type along with a modified method of characteristics. The method is well-balanced and accurately resolves dam-break problems over dry areas.

Keywords: Run-up waves, Shallow water equations, finite volume method, wet/dry interface, dam-break problem.

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Authors: Kenneth M. Oba

Abstract:

This study investigated factors affecting the price of cement in Nigeria, and developed a mathematical model that can predict future cement prices. Cement is key in the Nigerian construction industry. The changes in price caused by certain factors could affect economic and infrastructural development; hence there is need for proper proactive planning. Secondary data were collected from published information on cement between 2014 and 2019. In addition, questionnaires were sent to some domestic cement retailers in Port Harcourt in Nigeria, to obtain the actual prices of cement between the same periods. The study revealed that the most critical factors affecting the price of cement in Nigeria are inflation rate, population growth rate, and Gross Domestic Product (GDP) growth rate. With the use of data from United Nations, International Monetary Fund, and Central Bank of Nigeria databases, amongst others, a Multiple Linear Regression model was formulated. The model was used to predict the price of cement for 2020-2025. The model was then tested with 95% confidence level, using a two-tailed t-test and an F-test, resulting in an R² of 0.8428 and R² (adj.) of 0.6069. The results of the tests and the correlation factors confirm the model to be fit and adequate. This study will equip researchers and stakeholders in the construction industry with information for planning, monitoring, and management of present and future construction projects that involve the use of cement.

Keywords: Cement price, multiple linear regression model, Nigerian Construction Industry, price prediction.

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Authors: Rachid Zentar, Mokrane Bala, Pascal Boustingorry

Abstract:

The prediction of the rheological behavior of concrete is at the center of current concerns of the concrete industry for different reasons. The shortage of good quality standard materials combined with variable properties of available materials imposes to improve existing models to take into account these variations at the design stage of concrete. The main reasons for improving the predictive models are, of course, saving time and cost at the design stage as well as to optimize concrete performances. In this study, we will highlight the different properties of the granular mixtures that affect the rheological properties of concrete. Our objective is to identify the intrinsic parameters of the aggregates which make it possible to predict the yield stress of concrete. The work was done using two typologies of grains: crushed and rolled aggregates. The experimental results have shown that the rheology of concrete is improved by increasing the packing density of the granular mixture using rolled aggregates. The experimental program realized allowed to model the yield stress of concrete by a modified model of Chateau et al. through a dimensionless parameter following Krieger-Dougherty law. The modelling confirms that the yield stress of concrete depends not only on the properties of cement paste but also on the packing density of the granular skeleton and the shape of grains.

Keywords: Crushed aggregates, intrinsic viscosity, packing density, rolled aggregates, slump, yield stress of concrete.

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Authors: Vijay Kumar Sharma, Manisha Pattanaik, Balwinder Raj

Abstract:

Minimizations of power dissipation, chip area with higher circuit performance are the necessary and key parameters in deep submicron regime. The leakage current increases sharply in deep submicron regime and directly affected the power dissipation of the logic circuits. In deep submicron region the power dissipation as well as high performance is the crucial concern since increasing importance of portable systems. Number of leakage reduction techniques employed to reduce the leakage current in deep submicron region but they have some trade-off to control the leakage current. ONOFIC approach gives an excellent agreement between power dissipation and propagation delay for designing the efficient CMOS logic circuits. In this article ONOFIC approach is compared with LECTOR technique and output results show that ONOFIC approach significantly reduces the power dissipation and enhance the speed of the logic circuits. The lower power delay product is the big outcome of this approach and makes it an influential leakage reduction technique.

Keywords: Deep submicron, Leakage Current, LECTOR, ONOFIC, Power Delay Product

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Authors: Ying Shang, Chencheng Wang

Abstract:

The wind field is the main driving factor for the spread of forest fires. For the simulation results of forest fire spread to be more accurate, it is necessary to obtain more detailed wind field data. Therefore, this paper studied the mountainous fine wind field simulation method coupled with WRF (Weather Research and Forecasting Model) and CFD (Computational Fluid Dynamics) to realize the numerical simulation of the wind field in a mountainous area with a scale of 30 m and a small measurement error. Local topographical changes have an important impact on the wind field. Based on the Rothermel fire spread model, a forest fire in Idaho in the western United States was simulated. The historical data proved that the simulation results had a good accuracy. They showed that the fire spread rate will decrease rapidly with time and then reach a steady state. After reaching a steady state, the fire spread growth area will not only be affected by the slope, but will also show a significant quadratic linear positive correlation with the wind speed change.

Keywords: Wind field, numerical simulation, forest fire spread, fire behavior model, complex terrain.

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Authors: Fei Long Wei, Hua Yang, Hai Tao Zhang, Zhou Ping Yin

Abstract:

In this study, an local invariant generalized Houghtransform (LI-GHT) method is proposed for integrated circuit (IC) visual positioning. The original generalized Hough transform (GHT) is robust to external noise; however, it is not suitable for visual positioning of IC chips due to the four-dimensionality (4D) of parameter space which leads to the substantial storage requirement and high computational complexity. The proposed LI-GHT method can reduce the dimensionality of parameter space to 2D thanks to the rotational invariance of local invariant geometric feature and it can estimate the accuracy position and rotation angle of IC chips in real-time under noise and blur influence. The experiment results show that the proposed LI-GHT can estimate position and rotation angle of IC chips with high accuracy and fast speed. The proposed LI-GHT algorithm was implemented in IC visual positioning system of radio frequency identification (RFID) packaging equipment.

Keywords: Integrated Circuit Visual Positioning, Generalized Hough Transform, Local invariant Generalized Hough Transform, ICpacking equipment.

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Authors: A. Soualem

Abstract:

Springback is a significant problem in the sheet metal forming process. When the tools are released after the stage of forming, the product springs out, because of the action of the internal stresses. In many cases the deviation of form is too large and the compensation of the springback is necessary. The precise prediction of the springback of product is increasingly significant for the design of the tools and for compensation because of the higher ratio of the yield stress to the elastic modulus. The main object in this paper was to study the effect of the anisotropy on the springback for three directions of rolling: 0°, 45° and 90°. At the same time, we highlighted the influence of three different metallic materials: Aluminum, Steel and Galvanized steel. The original of our purpose consist on tests which are ensured by adapting a U-type stretching-bending device on a tensile testing machine, where we studied and quantified the variation of the springback according to the direction of rolling. We also showed the role of lubrication in the reduction of the springback. Moreover, in this work, we have studied important characteristics in deep drawing process which is a springback. We have presented defaults that are showed in this process and many parameters influenced a springback. Finally, our results works lead us to understand the influence of grains orientation with different metallic materials on the springback and drawing some conclusions how to concept deep drawing tools. In addition, the conducted work represents a fundamental contribution in the discussion the industry application.

Keywords: Deep-Drawing, Grains orientation, Laminate Tool, Springback.

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Authors: Sotirios Raptis

Abstract:

Linking social needs to social classes using different criteria may lead to social services misuse. The paper discusses using ML and Neural Networks (NNs) in linking public services in Scotland in the long term and advocates, this can result in a reduction of the services cost connecting resources needed in groups for similar services. The paper combines typical regression models with clustering and cross-correlation as complementary constituents to predict the demand. Insurance companies and public policymakers can pack linked services such as those offered to the elderly or to low-income people in the longer term. The work is based on public data from 22 services offered by Public Health Services (PHS) Scotland and from the Scottish Government (SG) from 1981 to 2019 that are broken into 110 years series called factors and uses Linear Regression (LR), Autoregression (ARMA) and 3 types of back-propagation (BP) Neural Networks (BPNN) to link them under specific conditions. Relationships found were between smoking related healthcare provision, mental health-related health services, and epidemiological weight in Primary 1(Education) Body Mass Index (BMI) in children. Primary component analysis (PCA) found 11 significant factors while C-Means (CM) clustering gave 5 major factors clusters.

Keywords: Probability, cohorts, data frames, services, prediction.

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