Search results for: analytic network process

Authors: Chen-Fang Tsai, Shin-Li Lu

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Distribution-free control chart is an oncoming area from the statistical process control charts in recent years. Some researchers have developed various nonparametric control charts and investigated the detection capability of these charts. The major advantage of nonparametric control charts is that the underlying process is not specifically considered the assumption of normality or any parametric distribution. In this paper, two nonparametric exponentially weighted moving average (EWMA) control charts based on nonparametric tests, namely NE-S and NE-M control charts, are proposed for monitoring process variability. Generally, weighted moving average (GWMA) control charts are extended by utilizing design and adjustment parameters for monitoring the changes in the process variability, namely NG-S and NG-M control charts. Statistical performance is also investigated on NG-S and NG-M control charts with run rules. Moreover, sensitivity analysis is performed to show the effects of design parameters under the nonparametric NG-S and NG-M control charts.

Keywords: Distribution-free control chart, EWMA control charts, GWMA control charts

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Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

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In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: brain-computer interface, speech recognition, artificial neural network, electroencephalography, EEG, wernicke area

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Authors: F. Lhafiane, A. Elbyed, M. Bouchoum

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The design of Reverse logistics Network has attracted growing attention with the stringent pressures from both environmental awareness and business sustainability. Reverse logistical activities include return, remanufacture, disassemble and dispose of products can be quite complex to manage. In addition, demand can be difficult to predict, and decision making is one of the challenges tasks. This complexity has amplified the need to develop an integrated architecture for product return as an enterprise system. The main purpose of this paper is to design Multi agent system (MAS) architecture using the Prometheus methodology to efficiently manage reverse logistics processes. The proposed MAS architecture includes five types of agents: Gate keeping Agent, Collection Agent, Sorting Agent, Processing Agent and Disposal Agent which act respectively during the five steps of reverse logistics Network.

Keywords: reverse logistics, multi agent system, prometheus methodology

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Authors: Usama Shahid

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Be it written documents, news columns, or students' essays, verifying the content can be a time-consuming task. Apart from the spelling and grammar mistakes, the proofreader is also supposed to verify whether the content included in the essay or document is relevant or not. The irrelevant content in any document or essay is referred to as off-topic text and in this paper, we will address the problem of off-topic text detection from a document using machine learning techniques. Our study aims to identify the off-topic content from a document using Echo state network model and we will also compare data with other models. The previous study uses Convolutional Neural Networks and TFIDF to detect off-topic text. We will rearrange the existing datasets and take new classifiers along with new word embeddings and implement them on existing and new datasets in order to compare the results with the previously existing CNN model.

Keywords: off topic, text detection, eco state network, machine learning

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Authors: Priyal Motwani

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The current market for bamboo products in India is about Rs. 21000 crores and is highly unorganised and fragmented. In this study, we have closely analysed the structure and functions of a major bamboo craft based organisation in Kerela, India and elaborated about its value chain, product mix, pricing strategy and supply chain, collaborations and competitive landscape. We have identified six major bottlenecks that are prevalent in such organisations, based on the Indian context, in relation to their product mix, asset management, and supply chain- corresponding waste management and retail network. The study has identified that the target customers for the bamboo based products and alternative revenue streams (eco-tourism, microenterprises, training), by carrying out secondary and primary research (5000 sample space), that can boost the existing revenue by 150%. We have then recommended an optimum product mix-covering premium, medium and low valued processing, for medium sized bamboo based organisations, in accordance with their capacity to maximize their revenue potential. After studying such organisations and their counter parts, the study has established an optimum retail network, considering B2B, B2C physical and online retail, to maximize their sales to their target groups. On the basis of the results obtained from the analysis of the future and present trends, our study gives recommendations to improve the revenue potential of bamboo based organisation in India and promote sustainability.

Keywords: bamboo, bottlenecks, optimization, product mix, retail network, value chain

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Authors: Sasan Talebnezhad, Parviz Hamidia

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GPC and RMS analysis showed no distinct difference between PE 100 On, Off, and Reference grade. But FTIR spectra and multiple endothermic peaks obtained from SSA analysis, attributed to heterogeneity of ethylene sequence length, lamellar thickness and also the non-uniformity of short chain branching, showed sharp discrepancy and proposed a blend structure of high-density polyethylenes in PE 100 grade. Catalysis along with process parameters dictates poly blend PE 100 structure. This in-reactor blend is a mixture of compatible co-crystallized phases with different crystalinity, forming a physical semi hard and soft segment network responsible for improved impact properties in PE 100 pipe grade. We propose a new approach for PE100 evaluation that is more efficient than normal microstructure characterization.

Keywords: HDPE, pipe grade, in-reactor blend, hard and soft segments

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Authors: H. Anzai, H. Nakayama, H. Kaminaga, Y. Morimoto, Y. Miyadera, S. Nakamura

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Various research resources such as papers and presentation slides are handled in the process of research activities. It is extremely important for smooth progress of the research to skillfully manage those research resources and utilize them for further investigations. However, number of the research resources increases more and more. Moreover, there are the differences in usage of each kind of research resource and their accumulation styles. So, it is actually difficult to satisfactorily manage and use the accumulated research resources. Therefore, a lack of tidiness of the resources causes the problems such as an oversight of the problem to be polish. Although there have existed research projects on support for management of research resources and for sharing of know-how, almost existing systems have not been effective enough since these systems have not sufficiently considered the polish process. This paper mainly describes a system that enables the strategic management of research resources together with polish process and their practical use.

Keywords: research resource, polish process, information sharing, knowledge management, information visualization

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Authors: T. V. K. Gupta, J. Ramkumar, Puneet Tandon, N. S. Vyas

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Abrasive Water Jet Machining (AWJM) is an unconventional machining process well known for machining hard to cut materials. The primary research focus on the process was for through cutting and a very limited literature is available on pocket milling using AWJM. The present work is an attempt to use this process for milling applications considering a set of various process parameters. Four different input parameters, which were considered by researchers for part separation, are selected for the above application i.e. abrasive size, flow rate, standoff distance, and traverse speed. Pockets of definite size are machined to investigate surface roughness, material removal rate, and pocket depth. Based on the data available through experiments on SS304 material, it is observed that higher traverse speeds gives a better finish because of reduction in the particle energy density and lower depth is also observed. Increase in the standoff distance and abrasive flow rate reduces the rate of material removal as the jet loses its focus and occurrence of collisions within the particles. ANOVA for individual output parameter has been studied to know the significant process parameters.

Keywords: abrasive flow rate, surface finish, abrasive size, standoff distance, traverse speed

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Authors: Dae Kyung Choi, Won Man Park, Kyungsoo Kim, Yoon Hyuk Kim

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The interspinous process devices have been recently used due to its advantages such as minimal invasiveness and less subsidence of the implant to the osteoporotic bone. In this paper, we have analyzed the influences of ligature tightening of several interspinous process devices using finite element analysis. Four types of interspinous process implants were inserted to the L3-4 spinal motion segment based on their surgical protocols. Inferior plane of L4 vertebra was fixed and 7.5 Nm of extension moment were applied on superior plane of L3 vertebra with 400N of compressive load along follower load direction and pretension of the ligature. The stability of the spinal unit was high enough than that of intact model. The higher value of pretension in the ligature led the decrease of dynamic stabilization effect in cases of the WallisTM, DiamTM, Viking, and Spear®. The results of present study could be used to evaluate surgical option and validate the biomechanical characteristics of the spinal implants.

Keywords: interspinous process device, bone fracture risk, lumbar spine, finite element analysis

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Authors: Muhammet Erbay

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The phenomenon of communication that has been studied by different disciplines has social, political and economical aspects. The scope of communication has extended from a traditional content to the modern world which is under the control of mass media. Nowadays, thanks to globalization and technological facilities, many companies, public or international institutions take advantage of new communication technologies and overhaul their policies. European Union (EU) is one of the effective institutions in this sphere. It aims to harmonize the communication infrastructure and policies of member countries which have gone through the process of political unification. It is a significant problem for the unification of EU to have legal restrictions or critical differences in communication facilities among countries while technology stands at the center of economic and social life. Therefore, EU institutions place a particular importance to their communication policies. Besides, communication processes have a vital importance in creating a European public opinion in the process of political integration. Based on the evaluation above, the aim of this paper is to analyze the cohesion process of Turkey that tries to take an active role in EU communication policies and has on-going negotiations. This article does not only confine itself to the technical details of communication policies but also aims to evaluate socio-political dimension of the process. Therefore, a corporate review has been featured in the study and Turkey's compliance process in communication policies on European Union has been evaluated by the means of deduction method. Some problematic areas have been identified in compliance process on communication policies such as human rights and minority rights, whereas compliance process on communication infrastructure and technology proceeds effectively.

Keywords: communication policies, European Union, integration, Turkey

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Authors: Noha Al Majid, Said Mazer, Moulhime El Bekkali, Catherine Algani, Mahmoud Mehdi

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A low noise figure (NF) and high linearity V-band Low Noise Amplifier (LNA) is reported in this article. The LNA compromises a three-stage cascode configuration. This LNA will be used as a part of a WPAN (Wireless Personal Area Network) receiver in the millimeter-wave band at 60 GHz. It is designed according to the MMIC technology (Monolithic Microwave Integrated Circuit) in PH 15 process from UMS foundry and uses a 0.15 μm GaAs PHEMT (Pseudomorphic High Electron Mobility Transistor). The particularity of this LNA compared to other LNAs in literature is its very low noise figure which is equal to 1 dB and its high linearity (IIP3 is about 22 dB). The LNA consumes 0.24 Watts, achieving a high gain which is about 23 dB, an input return loss better than -10 dB and an output return loss better than -8 dB.

Keywords: low noise amplifier, V-band, MMIC technology, LNA, amplifier, cascode, pseudomorphic high electron mobility transistor (PHEMT), high linearity

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Authors: Nadira Zaidi

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The aim of this study is to gain direct feedback of interviewees in a simulated interview process. Reflection based on qualitative data analysis has been utilized through the Gibbs Reflective Cycle, with 30 students as respondents at the Undergraduate level. The respondents reflected on the positive and negative aspects of this active learning process in order to increase their performance in actual job interviews. Results indicate that students engaged in the process successfully imbibed the feedback that they received from the interviewers and also identified the areas that needed improvement.

Keywords: experiential learning, positive and negative impact, reflection, simulated

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Authors: Saad Bakkali

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Morocco is a major producer of phosphate, with an annual output of 19 million tons and reserves in excess of 35 billion cubic meters. This represents more than 75% of world reserves. Resistivity surveys have been successfully used in the Oulad Abdoun phosphate basin. A Schlumberger resistivity survey over an area of 50 hectares was carried out. A new field procedure based on analytic signal response of resistivity data was tested to deal with the presence of phosphate deposit disturbances. A resistivity map was expected to allow the electrical resistivity signal to be imaged in 2D. 2D wavelet is standard tool in the interpretation of geophysical potential field data. Wavelet transform is particularly suitable in denoising, filtering and analyzing geophysical data singularities. Wavelet transform tools are applied to analysis of a moroccan phosphate deposit ‘disturbances’. Wavelet approach applied to modeling surface phosphate “disturbances” was found to be consistently useful.

Keywords: resistivity, Schlumberger, phosphate, wavelet, Morocco

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Authors: Pankaj Chandna, Dinesh Kumar

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The present work analyses different parameters of end milling to minimize the surface roughness for AISI D2 steel. D2 Steel is generally used for stamping or forming dies, punches, forming rolls, knives, slitters, shear blades, tools, scrap choppers, tyre shredders etc. Surface roughness is one of the main indices that determines the quality of machined products and is influenced by various cutting parameters. In machining operations, achieving desired surface quality by optimization of machining parameters, is a challenging job. In case of mating components the surface roughness become more essential and is influenced by the cutting parameters, because, these quality structures are highly correlated and are expected to be influenced directly or indirectly by the direct effect of process parameters or their interactive effects (i.e. on process environment). In this work, the effects of selected process parameters on surface roughness and subsequent setting of parameters with the levels have been accomplished by Taguchi’s parameter design approach. The experiments have been performed as per the combination of levels of different process parameters suggested by L9 orthogonal array. Experimental investigation of the end milling of AISI D2 steel with carbide tool by varying feed, speed and depth of cut and the surface roughness has been measured using surface roughness tester. Analyses of variance have been performed for mean and signal-to-noise ratio to estimate the contribution of the different process parameters on the process.

Keywords: D2 steel, orthogonal array, optimization, surface roughness, Taguchi methodology

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Authors: Usman Abubakar, Xiaoyuan Wang, Sayyed Haleem Shah, Sadiq Ur Rahman, Rabiu Saleh Zakariyya

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High-speed Permanent magnet synchronous machine (HSPMSM) uses in different industrial applications like blowers, compressors as a result of its superb performance. Nevertheless, the over-temperature rise of both winding and PM is one of their substantial problem for a high-power HSPMSM, which affects its lifespan and performance. According to the literature, HSPMSM with a Hybrid cooling configuration has a much lower temperature rise than non-hybrid cooling. This paper presents the design 185kW, 26K rpm with two different cooling configurations, i.e., hybrid cooling configuration (forced air and housing spiral water jacket) and non-hybrid (forced air cooling assisted with winding’s potting material and sleeve’s material) to enhance the heat dissipation of winding and PM respectively. Firstly, the machine’s electromagnetic design is conducted by the finite element method to accurately account for machine losses. Then machine’s cooling configurations are introduced, and their effectiveness is validated by lumped parameter thermal network (LPTN). Investigation shows that using potting, sleeve materials to assist non-hybrid cooling configuration makes the machine’s winding and PM temperature closer to hybrid cooling configuration. Therefore, the machine with non-hybrid cooling is prototyped and tested due to its simplicity, lower energy consumption and can still maintain the lifespan and performance of the HSPMSM.

Keywords: airflow network, axial ventilation, high-speed PMSM, thermal network

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Authors: Harvard Najoan, Sarwono Sutikno, Yusep Rosmansyah

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Most enterprises are now using information technology services as their assets to support business objectives. These kinds of services are provided by the internal service provider (inside the enterprise) or external service provider (outside enterprise). To deliver quality information technology services, the service provider (which from now on will be called ‘organization’) either internal or external, must have a standard for service management system. At present, the standard that is recognized as best practice for service management system for the organization is international standard ISO/IEC 20000:2011. The most important part of this international standard is the first part or ISO/IEC 20000-1:2011-Service Management System Requirement, because it contains 22 for organization processes as a requirement to be implemented in an organizational environment in order to build, manage and deliver quality service to the customer. Assessing organization management processes is the first step to implementing ISO/IEC 20000:2011 into the organization management processes. This assessment needs Process Assessment Model (PAM) as an assessment instrument. PAM comprises two parts: Process Reference Model (PRM) and Measurement Framework (MF). PRM is built by transforming the 22 process of ISO/IEC 20000-1:2011 and MF is based on ISO/IEC 33020. This assessment instrument was designed to assess the capability of service management process in Divisi Teknologi dan Sistem Informasi (Information Systems and Technology Division) as an internal organization of PT Pos Indonesia. The result of this assessment model can be proposed to improve the capability of service management system.

Keywords: ISO/IEC 20000-1:2011, ISO/IEC 33020:2015, process assessment, process capability, service management system

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Authors: Khaled Sellami, Lynda Sellami, Pierre F. Tiako

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Ubiquitous computing helps make data and services available to users anytime and anywhere. This makes the cooperation of devices a crucial need. In return, such cooperation causes an overload of the devices and/or networks, resulting in network malfunction and suspension of its activities. Our goal in this paper is to propose an approach of devices reconfiguration in order to help to reduce the energy consumption in ubiquitous environments. The idea is that when high-energy consumption is detected, we proceed to a change in component distribution on the devices to reduce and/or balance the energy consumption. We also investigate the possibility to detect high-energy consumption of devices/network based on devices abilities. As a result, our idea realizes a reconfiguration of devices aimed at reducing the consumption of energy and/or load balancing in ubiquitous environments.

Keywords: ubiquitous computing, load balancing, device energy consumption, reconfiguration

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Authors: G. Quiroga-Cubides, A. Díaz, M. Gómez

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The genus Azotobacter has been widely used as bio-fertilizer due to its significant effects on the stimulation and promotion of plant growth in various agricultural species of commercial interest. In order to obtain significantly viable cellular concentration, a scale-up strategy for a liquid fermentation process (SmF) with two strains of A. chroococcum (named Ac1 and Ac10) was validated and adjusted at laboratory and pilot scale. A batch fermentation process under previously defined conditions was carried out on a biorreactor Infors®, model Minifors of 3.5 L, which served as a baseline for this research. For the purpose of increasing process efficiency, the effect of the reduction of stirring speed was evaluated in combination with a fed-batch-type fermentation laboratory scale. To reproduce the efficiency parameters obtained, a scale-up strategy with geometric and fluid dynamic behavior similarities was evaluated. According to the analysis of variance, this scale-up strategy did not have significant effect on cellular concentration and in laboratory and pilot fermentations (Tukey, p > 0.05). Regarding air consumption, fermentation process at pilot scale showed a reduction of 23% versus the baseline. The percentage of reduction related to energy consumption reduction under laboratory and pilot scale conditions was 96.9% compared with baseline.

Keywords: Azotobacter chroococcum, scale-up, liquid fermentation, fed-batch process

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Authors: Brandon Foggo, Nanpeng Yu

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Power distribution circuits undergo frequent network topology changes that are often left undocumented. As a result, the documentation of a circuit’s connectivity becomes inaccurate with time. The lack of reliable circuit connectivity information is one of the biggest obstacles to model, monitor, and control modern distribution systems. To enhance the reliability and efficiency of electric power distribution systems, the circuit’s connectivity information must be updated periodically. This paper focuses on one critical component of a distribution circuit’s topology - the secondary transformer to phase association. This topology component describes the set of phase lines that feed power to a given secondary transformer (and therefore a given group of power consumers). Finding the documentation of this component is call Phase Identification, and is typically performed with physical measurements. These measurements can take time lengths on the order of several months, but with supervised learning, the time length can be reduced significantly. This paper compares several such methods applied to Phase Identification for a large range of real distribution circuits, describes a method of training data selection, describes preprocessing steps unique to the Phase Identification problem, and ultimately describes a method which obtains high accuracy (> 96% in most cases, > 92% in the worst case) using only 5% of the measurements typically used for Phase Identification.

Keywords: distribution network, machine learning, network topology, phase identification, smart grid

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Authors: Hoang Van Ngoc, Nguyen Thu Huong, Nguyen Quang Bau

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Using the quantum kinetic equation for electrons interacting with acoustic phonon, the density of the constant current associated with the drag of charge carriers in cylindrical quantum wire by a linearly polarized electromagnetic wave, a DC electric field and a laser radiation field is calculated. The density of the constant current is studied as a function of the frequency of electromagnetic wave, as well as the frequency of laser field and the basic elements of quantum wire with a parabolic potential. The analytic expression of the constant current density is numerically evaluated and plotted for a specific quantum wires GaAs/AlGaAs to show the dependence of the constant current density on above parameters. All these results of quantum wire compared with bulk semiconductors and superlattices to show the difference.

Keywords: The photon-drag effect, the constant current density, quantum wire, parabolic potential

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Authors: Marziyeh Khavari

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In recent decades, climate change, global warming, and the growing population worldwide face some challenges, such as increasing food consumption and shortage of resources. Assessing how climate change could disturb crops, especially hazelnut production, seems crucial for sustainable agriculture production. For hazelnut cultivation in the mid-warm condition, such as in Iran, here we present an investigation of climate parameters and how much they are effective on fertility and nut production of hazelnut trees. Therefore, the climate change of the northern zones in Iran has investigated (1960-2017) and was reached an uptrend in temperature. Furthermore, the descriptive analysis performed on six cultivars during seven years shows how this small-scale survey could demonstrate the effects of climate change on hazelnut production and stability. Results showed that some climate parameters are more significant on nut production, such as solar radiation, soil temperature, relative humidity, and precipitation. Moreover, some cultivars have produced more stable production, for instance, Negret and Segorbe, while the Mervill de Boliver recorded the most variation during the study. Another aspect that needs to be met is training and predicting an actual model to simulate nut production through a neural network and linear regression simulation. The study developed and estimated the ANN model's generalization capability with different criteria such as RMSE, SSE, and accuracy factors for dependent and independent variables (environmental and yield traits). The models were trained and tested while the accuracy of the model is proper to predict hazelnut production under fluctuations in weather parameters.

Keywords: climate change, neural network, hazelnut, global warming

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Authors: Supriyono, Sumardiyono, Rendy J. Pramono

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Biodiesel is one of the alternative fuels promising for substituting petrodiesel as energy source which has an advantage as it is sustainable and eco-friendly. Due to the raw material that tends to decompose during storage, biodiesel also has the same characteristic that tends to decompose during storage. Biodiesel decomposition will form higher acid value as the result of oxidation to double bond on a fatty acid compound on biodiesel. Thus, free fatty acid value could be used to evaluate degradation of biodiesel due to the oxidation process. High free fatty acid on biodiesel could impact on the engine performance. Decomposition of biodiesel due to oxidation reaction could prevent by introducing a small amount of antioxidant. The origin of raw materials and the process for producing biodiesel will determine the effectiveness of antioxidant. Biodiesel made from high free fatty acid (FFA) crude palm oil (CPO) by using two steps esterification is vulnerable to oxidation process which is resulted in increasing on the FFA value. Tocopherol also known as vitamin E is one of the antioxidant that could improve the stability of biodiesel due to decomposition by the oxidation process. Tocopherol 0.5% concentration on palm oil biodiesel could reduce 13% of increasing FFA under temperature 80 °C and exposing time 180 minute.

Keywords: antioxidant, palm oil biodiesel, decomposition, oxidation, tocopherol

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Authors: Li Li, Lei Wang, Chenglin Du, Mengxin Ren, Xinzheng Zhang, Wei Cai, Jingjun Xu

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Strong coupling between excitons of quantum dots and plasmons in nanocavites can be realized at room temperature due to the strong confinement of the plasmon fields, which offers building blocks for quantum information systems or ultralow-power switches and lasers. In this work, by using cathodoluminescence, ultrastrong coupling with Rabi splitting above 1 eV between breathing plasmons in Aluminum metal-insulator-metal (MIM) cavity and excited state of CdZnS/ZnS quantum dots was reported in near-UV spectrum. Analytic analysis and full-wave electromagnetic simulations provide the evidence for the strong coupling and confirm the hybridization of the QDs exciton and LSP breathing mode. This study opens the way for new emerging applications based on strongly coupled light-matter states all over the visible region down to ultra-violet frequencies.

Keywords: breathing mode, plasmonics, quantum dot, strong coupling, ultraviolet

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Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

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Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

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Authors: Benzegaou Ali, Brani Benabderrahmane

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This work describes a numerical study of the TOX–clinching process using diffuse elements. A computer code baptized SEMA "Static Explicit Method Analysis" is developed to simulate the clinch joining process. The FE code is based on an Updated Lagrangian scheme. The used resolution method is based on an explicit static approach. The integration of the elasto-plastic behavior law is realized with an algorithm of Simo and Taylor. The tools are represented by plane facets.

Keywords: diffuse elements, numerical simulation, clinching, contact, large deformation

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Authors: Zeplin Jiwa Husada Tarigan, Sautma Ronni Basana, Widjojo Suprapto

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Manufacturing companies in East Java develop their own ERP system or alter the ERP system which is developed by other companies to suit their needs. To make their own system, the companies mostly assign several employees from various departments to create a project team, and the employees are from the departments that are going to utilize the ERP system as the integrated data. The project team decides the making of the ERP system from the preparation stage until the going live implementation process. In designing the business process, the top management is working together with the project team until the project is accomplished. The completion of the ERP projects depends on the project to be undertaken itself, the strategy chosen to complete the project, the work method selection, the measurement system to monitor the project, the evaluation system of the project, and, in the end, the declaration of 'going live' of the ERP project. There is an increase in the business performance for the companies that have implemented the information technology or ERP as they manage to integrate all management functions within their companies. To investigate, some questionnaires are distributed to 100 manufacturing companies, and 90 questionnaires are returned; however, there are only 46 companies that develop their own ERP system, so the response rate is 46%. The result of data analysis using PLS shows that the management competency brings impacts to the project team and the process design. The process design is adjusted to the real process in order to implement the ERP, but it does not bring direct impacts to the business performance. The implementation of ERP brings positive impacts to the company business performance.

Keywords: management competency, project team, process design, ERP implementation, business performance

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Authors: Tatiana A. Dolenko, Sergey A. Burikov, Alexander O. Efitorov, Sergey A. Dolenko

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In this study, a comparative analysis of the approaches associated with the use of neural network algorithms for effective solution of a complex inverse problem – the problem of identifying and determining the individual concentrations of inorganic salts in multicomponent aqueous solutions by the spectra of Raman scattering of light – is performed. It is shown that application of artificial neural networks provides the average accuracy of determination of concentration of each salt no worse than 0.025 M. The results of comparative analysis of input data compression methods are presented. It is demonstrated that use of uniform aggregation of input features allows decreasing the error of determination of individual concentrations of components by 16-18% on the average.

Keywords: inverse problems, multi-component solutions, neural networks, Raman spectroscopy

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Authors: Rama Shanker, Anil Kumar Sachan

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Basic ingredients of concrete are cement, fine aggregate, coarse aggregate and water. To produce a concrete of certain specific properties, optimum proportion of these ingredients are mixed. The important factors which govern the mix design are grade of concrete, type of cement and size, shape and grading of aggregates. Concrete mix design method is based on experimentally evolved empirical relationship between the factors in the choice of mix design. Basic draw backs of this method are that it does not produce desired strength, calculations are cumbersome and a number of tables are to be referred for arriving at trial mix proportion moreover, the variation in attainment of desired strength is uncertain below the target strength and may even fail. To solve this problem, a lot of cubes of standard grades were prepared and attained 28 days strength determined for different combination of cement, fine aggregate, coarse aggregate and water. An artificial neural network (ANN) was prepared using these data. The input of ANN were grade of concrete, type of cement, size, shape and grading of aggregates and output were proportions of various ingredients. With the help of these inputs and outputs, ANN was trained using feed forward back proportion model. Finally trained ANN was validated, it was seen that it gave the result with/ error of maximum 4 to 5%. Hence, specific type of concrete can be prepared from given material properties and proportions of these materials can be quickly evaluated using the proposed ANN.

Keywords: aggregate proportions, artificial neural network, concrete grade, concrete mix design

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Authors: Zhaojun Wang, Zongdi Sun, Zhiyuan Liu

Abstract:

First of all, the carbon trading price and trading volume in Shanghai are transformed by Fourier transform, and the frequency response diagram is obtained. Then, the frequency response diagram is analyzed and the Blackman filter is designed. The Blackman filter is used to filter, and the carbon trading time domain and frequency response diagram are obtained. After wavelet analysis, the carbon trading data were processed; respectively, we got the average value for each 5 days, 10 days, 20 days, 30 days, and 60 days. Finally, the data are used as input of the Back Propagation Neural Network model for prediction.

Keywords: Shanghai carbon trading, carbon trading price, carbon trading volume, wavelet analysis, BP neural network model

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Authors: Nader Khalafian, Mohsen Ghaderi

Abstract:

Field observations have revealed many examples of structures which were damaged due to ground surface deformation caused by the faulting phenomena. In this paper some efforts were made in order to estimate the length and location of the ground surface where large displacements were created due to the reverse faulting. This research has conducted in two steps; (1) in the first step, a 2D explicit finite element model were developed using ABAQUS software. A subroutine for Mohr-Coulomb failure criterion with strain softening model was developed by the authors in order to properly model the stress strain behavior of the soil in the fault rapture zone. The results of the numerical analysis were verified with the results of available centrifuge experiments. Reasonable coincidence was found between the numerical and experimental data. (2) In the second step, the effects of the fault dip angle (δ), depth of soil layer (H), dilation and friction angle of sand (ψ and φ) and the amount of fault offset (d) on the soil surface displacement and fault rupture path were investigated. An artificial neural network-based model (ANN), as a powerful prediction tool, was developed to generate a general model for predicting faulting characteristics. A properly sized database was created to train and test network. It was found that the length and location of the zone of displaced ground surface can be accurately estimated using the proposed model.

Keywords: reverse faulting, surface deformation, numerical, neural network

Procedia PDF Downloads 411