Search results for: Supply chain delivery models

Authors: Rajendra M Sonar

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The future of business intelligence (BI) is to integrate intelligence into operational systems that works in real-time analyzing small chunks of data based on requirements on continuous basis. This is moving away from traditional approach of doing analysis on ad-hoc basis or sporadically in passive and off-line mode analyzing huge amount data. Various AI techniques such as expert systems, case-based reasoning, neural-networks play important role in building business intelligent systems. Since BI involves various tasks and models various types of problems, hybrid intelligent techniques can be better choice. Intelligent systems accessible through web services make it easier to integrate them into existing operational systems to add intelligence in every business processes. These can be built to be invoked in modular and distributed way to work in real time. Functionality of such systems can be extended to get external inputs compatible with formats like RSS. In this paper, we describe a framework that use effective combinations of these techniques, accessible through web services and work in real-time. We have successfully developed various prototype systems and done few commercial deployments in the area of personalization and recommendation on mobile and websites.

Keywords: Business Intelligence, Customer Relationship Management, Hybrid Intelligent Systems, Personalization and Recommendation (P&R), Recommender Systems.

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Authors: A. Boudjemai , M.H. Bouanane, Mankour, R. Amri, H. Salem, B. Chouchaoui

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The purpose of this paper is to perform a multidisciplinary design and analysis (MDA) of honeycomb panels used in the satellites structural design. All the analysis is based on clamped-free boundary conditions. In the present work, detailed finite element models for honeycomb panels are developed and analysed. Experimental tests were carried out on a honeycomb specimen of which the goal is to compare the previous modal analysis made by the finite element method as well as the existing equivalent approaches. The obtained results show a good agreement between the finite element analysis, equivalent and tests results; the difference in the first two frequencies is less than 4% and less than 10% for the third frequency. The results of the equivalent model presented in this analysis are obtained with a good accuracy. Moreover, investigations carried out in this research relate to the honeycomb plate modal analysis under several aspects including the structural geometrical variation by studying the various influences of the dimension parameters on the modal frequency, the variation of core and skin material of the honeycomb. The various results obtained in this paper are promising and show that the geometry parameters and the type of material have an effect on the value of the honeycomb plate modal frequency.

Keywords: Satellite, honeycomb, finite element method, modal frequency, dynamic.

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Authors: Mohd Azman Abdul Latif, Erwan Basiron

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A flaw or drift from expected operational performance in one component (NAND, PMIC, controller, DRAM, etc.) may affect the reliability of the entire Solid State Drive (SSD) system. Therefore, it is important to ensure the required quality of each individual component through qualification testing specified using standards or user requirements. Qualification testing is time-consuming and comes at a substantial cost for product manufacturers. A highly technical team, from all the eminent stakeholders is embarking on reliability prediction from beginning of new product development, identify critical to reliability parameters, perform full-blown characterization to embed margin into product reliability and establish control to ensure the product reliability is sustainable in the mass production. The paper will discuss a comprehensive development framework, comprehending SSD end to end from design to assembly, in-line inspection, in-line testing and will be able to predict and to validate the product reliability at the early stage of new product development. During the design stage, the SSD will go through intense reliability margin investigation with focus on assembly process attributes, process equipment control, in-process metrology and also comprehending forward looking product roadmap. Once these pillars are completed, the next step is to perform process characterization and build up reliability prediction modeling. Next, for the design validation process, the reliability prediction specifically solder joint simulator will be established. The SSD will be stratified into Non-Operating and Operating tests with focus on solder joint reliability and connectivity/component latent failures by prevention through design intervention and containment through Temperature Cycle Test (TCT). Some of the SSDs will be subjected to the physical solder joint analysis called Dye and Pry (DP) and Cross Section analysis. The result will be feedbacked to the simulation team for any corrective actions required to further improve the design. Once the SSD is validated and is proven working, it will be subjected to implementation of the monitor phase whereby Design for Assembly (DFA) rules will be updated. At this stage, the design change, process and equipment parameters are in control. Predictable product reliability at early product development will enable on-time sample qualification delivery to customer and will optimize product development validation, effective development resource and will avoid forced late investment to bandage the end-of-life product failures. Understanding the critical to reliability parameters earlier will allow focus on increasing the product margin that will increase customer confidence to product reliability.

Keywords: e2e reliability prediction, SSD, TCT, Solder Joint Reliability, NUDD, connectivity issues, qualifications, characterization and control.

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Authors: Paola Lecca, Lorenzo Dematte, Corrado Priami

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The present models and simulation algorithms of intracellular stochastic kinetics are usually based on the premise that diffusion is so fast that the concentrations of all the involved species are homogeneous in space. However, recents experimental measurements of intracellular diffusion constants indicate that the assumption of a homogeneous well-stirred cytosol is not necessarily valid even for small prokaryotic cells. In this work a mathematical treatment of diffusion that can be incorporated in a stochastic algorithm simulating the dynamics of a reaction-diffusion system is presented. The movement of a molecule A from a region i to a region j of the space is represented as a first order reaction Ai k- ! Aj , where the rate constant k depends on the diffusion coefficient. The diffusion coefficients are modeled as function of the local concentration of the solutes, their intrinsic viscosities, their frictional coefficients and the temperature of the system. The stochastic time evolution of the system is given by the occurrence of diffusion events and chemical reaction events. At each time step an event (reaction or diffusion) is selected from a probability distribution of waiting times determined by the intrinsic reaction kinetics and diffusion dynamics. To demonstrate the method the simulation results of the reaction-diffusion system of chaperoneassisted protein folding in cytoplasm are shown.

Keywords: Reaction-diffusion systems, diffusion coefficient, stochastic simulation algorithm.

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Authors: H. Feza Carlak, N. G. Gencer

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To increase the temperature contrast in thermal images, the characteristics of the electrical conductivity and thermal imaging modalities can be combined. In this experimental study, it is objected to observe whether the temperature contrast created by the tumor tissue can be improved just due to the current application within medical safety limits. Various thermal breast phantoms are developed to simulate the female breast tissue. In vitro experiments are implemented using a thermal infrared camera in a controlled manner. Since experiments are implemented in vitro, there is no metabolic heat generation and blood perfusion. Only the effects and results of the electrical stimulation are investigated. Experimental study is implemented with two-dimensional models. Temperature contrasts due to the tumor tissues are obtained. Cancerous tissue is determined using the difference and ratio of healthy and tumor images. 1 cm diameter single tumor tissue causes almost 40 °mC temperature contrast on the thermal-breast phantom. Electrode artifacts are reduced by taking the difference and ratio of background (healthy) and tumor images. Ratio of healthy and tumor images show that temperature contrast is increased by the current application.

Keywords: Medical diagnostic imaging, breast phantom, active thermography, breast cancer detection.

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Authors: N. J. Imu, N. Rabbani, Md E. Hossain

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Achieving national climate goals requires transforming the energy system and increasing the use of renewable energy in Bangladesh as renewable energy offers an environmentally friendly energy supply. In view of this, Bangladesh has set a goal of 100% renewable power generation by 2050. Among all the renewable energy, solar is the most effective and popular source of renewable energy in Bangladesh. In order to build up on-grid and off-grid solar systems to increase energy transformation, monocrystalline type (highly efficient) solar module, and the polycrystalline type (low-efficient) solar module are commonly used. Due to their low price and availability, polycrystalline-type solar modules dominated the local market in the past years. However, in recent times the use of monocrystalline types modules has increased considerably owing to the significant decrease in price difference that existed between these two modules. Despite the deployment of both mono- and poly-crystalline modules in the market, the proliferation of low-quality solar panels are dominating the market resulting in reduced generation of solar electricity than expected. This situation is further aggravated by insufficient information regarding the effect of solar irradiation on solar module performance in relation to the quality of the materials used for the production of the module. This research aims to evaluate the efficiency of monocrystalline and polycrystalline solar modules that are available in Bangladesh by considering seasonal variations. Both types of solar modules have been tested for three different capacities 45W, 60W, and 100W in Dhaka regions to evaluate their power generation capability under Standard Test Conditions (STC). Module testing data were recorded twelve months in a full year from January to December. Data for solar irradiation were collected using HT304N while HT I-V400 multifunction instrument was used for testing voltage and current of photovoltaic (PV) systems and complete power quality analyzer. Results obtained in this study indicated differences between the efficiencies of polycrystalline and monocrystalline solar modules under the country’s solar irradiation. The average efficiencies of 45W, 60W, and 100W monocrystalline solar panels were recorded as 11.73%, 13.41%, and 15.37% respectively while for polycrystalline panels were 8.66%, 9.37%, and 12.34%. Monocrystalline solar panels, which offer greater working output than polycrystalline ones, are also represented by the Pearson Correlation value. The output of polycrystalline solar panels fluctuated highly with the changes in irradiation and temperature whereas monocrystalline panels were much stable.

Keywords: Solar energy, solar irradiation, efficiency, polycrystalline solar module, monocrystalline solar module, SPSS analysis.

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Authors: Nahlah Abbas, Saleh A. Wasimi, Nadhir Al-Ansari

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The Greater Zab and Lesser Zab are the major tributaries of Tigris River contributing the largest flow volumes into the river. The impacts of climate change on water resources in these basins have not been well addressed. To gain a better understanding of the effects of climate change on water resources of the study area in near future (2049-2069) as well as in distant future (2080-2099), Soil and Water Assessment Tool (SWAT) was applied. The model was first calibrated for the period from 1979 to 2004 to test its suitability in describing the hydrological processes in the basins. The SWAT model showed a good performance in simulating streamflow. The calibrated model was then used to evaluate the impacts of climate change on water resources. Six general circulation models (GCMs) from phase five of the Coupled Model Intercomparison Project (CMIP5) under three Representative Concentration Pathways (RCPs) RCP 2.6, RCP 4.5, and RCP 8.5 for periods of 2049-2069 and 2080-2099 were used to project the climate change impacts on these basins. The results demonstrated a significant decline in water resources availability in the future.

Keywords: Tigris River, climate change, water resources, SWAT.

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Authors: S. Karabulut, A. Güllü, A. Güldas, R. Gürbüz

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This study investigates the effects of the lead angle and chip thickness variation on surface roughness during the machining of compacted graphite iron using ceramic cutting tools under dry cutting conditions. Analytical models were developed for predicting the surface roughness values of the specimens after the face milling process. Experimental data was collected and imported to the artificial neural network model. A multilayer perceptron model was used with the back propagation algorithm employing the input parameters of lead angle, cutting speed and feed rate in connection with chip thickness. Furthermore, analysis of variance was employed to determine the effects of the cutting parameters on surface roughness. Artificial neural network and regression analysis were used to predict surface roughness. The values thus predicted were compared with the collected experimental data, and the corresponding percentage error was computed. Analysis results revealed that the lead angle is the dominant factor affecting surface roughness. Experimental results indicated an improvement in the surface roughness value with decreasing lead angle value from 88° to 45°.

Keywords: CGI, milling, surface roughness, ANN, regression, modeling, analysis.

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Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: Cyber-security, Intrusion Detection Systems, Temporal Graph Network, Anomaly Detection.

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Authors: Mohammad Ahmad, Sander Gersen, Erwin Wilbers

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Carbon capture, transport and underground storage have become a major solution to reduce CO₂ emissions from power plants and other large CO₂ sources. A big part of this captured CO₂ stream is transported at high pressure dense phase conditions and stored in offshore underground depleted oil and gas fields. CO₂ is also transported in offshore pipelines to be used for enhanced oil and gas recovery. The captured CO₂ stream with impurities may contain water that causes severe corrosion problems, flow assurance failure and might damage valves and instrumentations. Thus, free water formation should be strictly prevented. The purpose of this work is to study the solubility of water in pure CO₂ and in CO₂ mixtures under real pipeline pressure (90-150 bar) and temperature operation conditions (5-35°C). A set up was constructed to generate experimental data. The results show the solubility of water in CO₂ mixtures increasing with the increase of the temperature or/and with the increase in pressure. A drop in water solubility in CO₂ is observed in the presence of impurities. The data generated were then used to assess the capabilities of two mixture models: the GERG-2008 model and the EOS-CG model. By generating the solubility data, this study contributes to determine the maximum allowable water content in CO₂ pipelines.

Keywords: Carbon capture and storage, water solubility, equation of states.

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Authors: A. M. Tarola, R. Preti, A. M. Girelli, P. Campana

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Goat dairy products are gaining popularity worldwide. In developing countries, but also in many marginal regions of the Mediterranean area, goats represent a great part of the economy and ensure food security. In fact, these small ruminants are able to convert efficiently poor weedy plants and small trees into traditional products of high nutritional quality, showing great resilience to different climatic and environmental conditions. In developed countries, goat milk is appreciated for the presence of health-promoting compounds, bioactive compounds such as conjugated linoleic acids, oligosaccharides, sphingolipids and polyammines. This paper focuses on the recent advances in literature on the nutritional properties of goat milk and on innovative techniques to improve its quality as to become a promising functional food. The environmental sustainability of different methodologies of production has also been examined. Goat milk is valued today as a food of high nutritional value and functional properties as well as small environmental footprint. It is widely consumed in many countries due to high nutritional value, lower allergenic potential, and better digestibility when compared to bovine milk, that makes this product suitable for infants, elderly or sensitive patients. The main differences in chemical composition between a cow and goat milk rely on fat globules that in goat milk are smaller and in fatty acids that present a smaller chain length, while protein, fat, and lactose concentration are comparable. Milk nutritional properties have demonstrated to be strongly influenced by animal diet, genotype, and welfare, but also by season and production systems. Furthermore, there is a growing interest in the dairy industry in goat milk for its relatively high concentration of prebiotics and a good amount of probiotics, which have recently gained importance for their therapeutic potential. Therefore, goat milk is studied as a promising matrix to develop innovative functional foods. In addition to the economic and nutritional value, goat milk is considered a sustainable product for its small environmental footprint, as they require relatively little water and land, and less medical treatments, compared to cow, these characteristics make its production naturally vocated to organic farming. Organic goat milk production has becoming more and more interesting both for farmers and consumers as it can answer to several concerns like environment protection, animal welfare and economical sustainment of rural populations living in marginal lands. These evidences make goat milk an ancient food with novel properties and advantages to be valorized and exploited.

Keywords: Goat milk, nutritional quality, bioactive compounds, sustainable production.

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Authors: A. Jamekhorshid, G. Karimi, I. Noshadi, A. Jahangiri

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Non-uniform current distribution in polymer electrolyte membrane fuel cells results in local over-heating, accelerated ageing, and lower power output than expected. This issue is very critical when fuel cell experiences water flooding. In this work, the performance of a PEM fuel cell is investigated under cathode flooding conditions. Two-dimensional partially flooded GDL models based on the conservation laws and electrochemical relations are proposed to study local current density distributions along flow fields over a wide range of cell operating conditions. The model results show a direct association between cathode inlet humidity increases and that of average current density but the system becomes more sensitive to flooding. The anode inlet relative humidity shows a similar effect. Operating the cell at higher temperatures would lead to higher average current densities and the chance of system being flooded is reduced. In addition, higher cathode stoichiometries prevent system flooding but the average current density remains almost constant. The higher anode stoichiometry leads to higher average current density and higher sensitivity to cathode flooding.

Keywords: Current distribution, Flooding, Hydrogen energysystem, PEM fuel cell.

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Authors: Humayun Murshed, Shibly Abdullah

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The research conducted in early seventies apparently assumed the existence of a universal decision model for union negotiators and furthermore tended to regard financial information as a ‘neutral’ input into a rational decision making process. However, research in the eighties began to question the neutrality of financial information as an input in collective bargaining rather viewing it as a potentially effective means for controlling the labour force. Furthermore, this later research also started challenging the simplistic assumptions relating particularly to union objectives which have underpinned the earlier search for universal union decision models. Despite the above developments there seems to be a dearth of studies in developing countries concerning the use of financial information in collective bargaining. This paper seeks to begin to remedy this deficiency. Utilising a case study approach based on two enterprises, one in the public sector and the other a multinational, the universal decision model is rejected and it is argued that the decision whether or not to use financial information is a contingent one and such a contingency is largely defined by the context and environment in which both union and management negotiators work. An attempt is also made to identify the factors constraining as well as promoting the use of financial information in collective bargaining, these being regarded as unique to the organisations within which the case studies are conducted.

Keywords: Collective Bargaining, Developing Countries, Disclosures, Financial Information.

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Authors: Shrey Sharma, Gunjan Kumar Verma

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High density electrical prospecting has been widely used in groundwater investigation, civil engineering and environmental survey. For efficient inversion, the forward modeling routine, sensitivity calculation, and inversion algorithm must be efficient. This paper attempts to provide a brief summary of the past and ongoing developments of the method. It includes reviews of the procedures used for data acquisition, processing and inversion of electrical resistivity data based on compilation of academic literature. In recent times there had been a significant evolution in field survey designs and data inversion techniques for the resistivity method. In general 2-D inversion for resistivity data is carried out using the linearized least-square method with the local optimization technique .Multi-electrode and multi-channel systems have made it possible to conduct large 2-D, 3-D and even 4-D surveys efficiently to resolve complex geological structures that were not possible with traditional 1-D surveys. 3-D surveys play an increasingly important role in very complex areas where 2-D models suffer from artifacts due to off-line structures. Continued developments in computation technology, as well as fast data inversion techniques and software, have made it possible to use optimization techniques to obtain model parameters to a higher accuracy. A brief discussion on the limitations of the electrical resistivity method has also been presented.

Keywords: Resistivity, inversion, optimization.

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Authors: E. Binaeian, SH. Soroushnia

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Acute toxicity of nano SiO2, ZnO, MCM-41 (Meso pore silica), Cu, Multi Wall Carbon Nano Tube (MWCNT), Single Wall Carbon Nano Tube (SWCNT) , Fe (Coated) to bacteria Vibrio fischeri using a homemade luminometer , was evaluated. The values of the nominal effective concentrations (EC), causing 20% and 50% inhibition of biouminescence, using two mathematical models at two times of 5 and 30 minutes were calculated. Luminometer was designed with Photomultiplier (PMT) detector. Luminol chemiluminescence reaction was carried out for the calibration graph. In the linear calibration range, the correlation coefficients and coefficient of Variation (CV) were 0.988 and 3.21% respectively which demonstrate the accuracy and reproducibility of the instrument that are suitable. The important part of this research depends on how to optimize the best condition for maximum bioluminescence. The culture of Vibrio fischeri with optimal conditions in liquid media, were stirring at 120 rpm at a temperature of 150C to 180C and were incubated for 24 to 72 hours while solid medium was held at 180C and for 48 hours. Suspension of nanoparticles ZnO, after 30 min contact time to bacteria Vibrio fischeri, showed the highest toxicity while SiO2 nanoparticles showed the lowest toxicity. After 5 min exposure time, the toxicity of ZnO was the strongest and MCM-41 was the weakest toxicant component.

Keywords: Bioluminescence, effective concentration, nanomaterials, toxicity, Vibrio fischeri.

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Authors: Hui-Yu Huang, Shih-Hang Hsu

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In this paper, we propose a robust scheme to work face alignment and recognition under various influences. For face representation, illumination influence and variable expressions are the important factors, especially the accuracy of facial localization and face recognition. In order to solve those of factors, we propose a robust approach to overcome these problems. This approach consists of two phases. One phase is preprocessed for face images by means of the proposed illumination normalization method. The location of facial features can fit more efficient and fast based on the proposed image blending. On the other hand, based on template matching, we further improve the active shape models (called as IASM) to locate the face shape more precise which can gain the recognized rate in the next phase. The other phase is to process feature extraction by using principal component analysis and face recognition by using support vector machine classifiers. The results show that this proposed method can obtain good facial localization and face recognition with varied illumination and local distortion.

Keywords: Gabor filter, improved active shape model (IASM), principal component analysis (PCA), face alignment, face recognition, support vector machine (SVM)

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Authors: Rong Liu, Kuiying Chen, Ju Chen, Jingrong Zhao, Ming Liang

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This article presents modeling studies of NiAl alloy under solid-particle erosion and liquid-drop erosion. In the solid-particle erosion simulation, attention is paid to the oxide scale thickness variation on the alloy in high-temperature erosion environments. The erosion damage is assumed to be deformation wear and cutting wear mechanisms, incorporating the influence of the oxide scale on the eroded surface; thus the instantaneous oxide thickness is the result of synergetic effect of erosion and oxidation. For liquid-drop erosion, special interest is in investigating the effects of drop velocity and drop size on the damage of the target surface. The models of impact stress wave, mean depth of penetration, and maximum depth of erosion rate (Max DER) are employed to develop various maps for NiAl alloy, including target thickness vs. drop size (diameter), rate of mean depth of penetration (MDRP) vs. drop impact velocity, and damage threshold velocity (DTV) vs. drop size.

Keywords: Liquid-drop erosion, NiAl alloy, oxide scale thickness, solid-particle erosion.

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Authors: Abhishek Soni, A. Kumaraswamy, M. S. Mahesh

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Bullet penetration in steel plate is investigated with the help of three-dimensional, non-linear, transient, dynamic, finite elements analysis using explicit time integration code LSDYNA. The effect of large strain, strain-rate and temperature at very high velocity regime was studied from number of simulations of semi-spherical nose shape bullet penetration through single layered circular plate with 2 mm thickness at impact velocities of 500, 1000, and 1500 m/s with the help of Johnson Cook material model. Mie-Gruneisen equation of state is used in conjunction with Johnson Cook material model to determine pressure-volume relationship at various points of interests. Two material models viz. Plastic-Kinematic and Johnson- Cook resulted in different deformation patterns in steel plate. It is observed from the simulation results that the velocity drop and loss of kinetic energy occurred very quickly up to perforation of plate, after that the change in velocity and changes in kinetic energy are negligibly small. The physics behind this kind of behaviour is presented in the paper.

Keywords: AISI 4340 steel, ballistic impact simulation, bullet penetration, non-linear FEM.

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Authors: Dalia Suša Vugec, Ana-Marija Stjepić, Darija Ivandić Vidović

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Digital transformation is one of the latest trends on the global market. In order to maintain the competitive advantage and sustainability, increasing number of organizations are conducting digital transformation processes. Those organizations are changing their business processes and creating new business models with the help of digital technologies. In that sense, one should also observe the role of business process management (BPM) and its maturity in driving digital transformation. Therefore, the goal of this paper is to investigate the role of BPM in digital transformation process within one organization. Since experiences from practice show that organizations from financial sector could be observed as leaders in digital transformation, an insurance company has been selected to participate in the study. That company has been selected due to the high level of its BPM maturity and the fact that it has previously been through a digital transformation process. In order to fulfill the goals of the paper, several interviews, as well as questionnaires, have been conducted within the selected company. The results are presented in a form of a case study. Results indicate that digital transformation process within the observed company has been successful, with special focus on the development of digital strategy, BPM and change management. The role of BPM in the digital transformation of the observed company is further discussed in the paper.

Keywords: Business process management, case study, Croatia, digital transformation, insurance company.

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Authors: Abdesselem Dakhli, Wajdi Bellil, Chokri Ben Amar

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DNA Barcode provides good sources of needed information to classify living species. The classification problem has to be supported with reliable methods and algorithms. To analyze species regions or entire genomes, it becomes necessary to use the similarity sequence methods. A large set of sequences can be simultaneously compared using Multiple Sequence Alignment which is known to be NP-complete. However, all the used methods are still computationally very expensive and require significant computational infrastructure. Our goal is to build predictive models that are highly accurate and interpretable. In fact, our method permits to avoid the complex problem of form and structure in different classes of organisms. The empirical data and their classification performances are compared with other methods. Evenly, in this study, we present our system which is consisted of three phases. The first one, is called transformation, is composed of three sub steps; Electron-Ion Interaction Pseudopotential (EIIP) for the codification of DNA Barcodes, Fourier Transform and Power Spectrum Signal Processing. Moreover, the second phase step is an approximation; it is empowered by the use of Multi Library Wavelet Neural Networks (MLWNN). Finally, the third one, is called the classification of DNA Barcodes, is realized by applying the algorithm of hierarchical classification.

Keywords: DNA Barcode, Electron-Ion Interaction Pseudopotential, Multi Library Wavelet Neural Networks.

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Authors: Y. Long, L. Liu, K. V. Branin

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One challenge faced by procurement decision-maker during the acquisition process is how to compare similar products from different suppliers and allocate orders among different products or services. This work focuses on allocating orders among multiple suppliers considering rebate. The objective function is to minimize the total acquisition cost including purchasing cost and rebate benefit. Rebate benefit is complex and difficult to estimate at the ordering step. Rebate rules vary for different suppliers and usually change over time. In this work, we developed a system to collect the rebate policies, standardized the rebate policies and developed two-stage optimization models for ordering allocation. Rebate policy with multi-tiers is considered in modeling. The discontinuous cost function of rebate benefit is formulated for different scenarios. A piecewise linear function is used to approximate the discontinuous cost function of rebate benefit. And a Mixed Integer Programing (MIP) model is built for order allocation problem with multi-tier rebate. A case study is presented and it shows that our optimization model can reduce the total acquisition cost by considering rebate rules.

Keywords: Discontinuous cost function, mixed integer programming, optimization, procurement, rebate.

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Authors: P. Luangpaiboon, S. Boonhao

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This study proposes a multi-response surface optimization problem (MRSOP) for determining the proper choices of a process parameter design (PPD) decision problem in a noisy environment of a grease position process in an electronic industry. The proposed models attempts to maximize dual process responses on the mean of parts between failure on left and right processes. The conventional modified simplex method and its hybridization of the stochastic operator from the hunting search algorithm are applied to determine the proper levels of controllable design parameters affecting the quality performances. A numerical example demonstrates the feasibility of applying the proposed model to the PPD problem via two iterative methods. Its advantages are also discussed. Numerical results demonstrate that the hybridization is superior to the use of the conventional method. In this study, the mean of parts between failure on left and right lines improve by 39.51%, approximately. All experimental data presented in this research have been normalized to disguise actual performance measures as raw data are considered to be confidential.

Keywords: Grease Position Process, Multi-response Surfaces, Modified Simplex Method, Hunting Search Method, Desirability Function Approach.

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Authors: Emmy Pratiwi, Ketut B. Artana, A. A. B. Dinariyana

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Madura Strait is considered as one of the busiest shipping channels in Indonesia. High vessel traffic density in Madura Strait gives serious threat due to navigational safety in this area, i.e. ship collision. This study is necessary as an attempt to enhance the safety of marine traffic. Fuzzy inference system (FIS) is proposed to calculate risk collision of ships. Collision risk is evaluated based on ship domain, Distance to Closest Point of Approach (DCPA), and Time to Closest Point of Approach (TCPA). Data were collected by utilizing Automatic Identification System (AIS). This study considers several ships’ domain models to give the characteristic of marine traffic in the waterways. Each encounter in the ship domain is analyzed to obtain the level of collision risk. Risk level of ships, as the result in this study, can be used as guidance to avoid the accident, providing brief description about safety traffic in Madura Strait and improving the navigational safety in the area.

Keywords: Automatic identification system, collision risk, DCPA, fuzzy inference system, TCPA.

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Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage

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Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.

Keywords: Equivalent circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square.

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Authors: Radomir Perzina, Jaroslav Ramik

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The Analytic Hierarchy Process is frequently used approach for solving decision making problems. There exists wide range of software programs utilizing that approach. Their main disadvantage is that they are relatively expensive and missing intermediate calculations. This work introduces a Microsoft Excel add-in called DAME – Decision Analysis Module for Excel. Comparing to other computer programs DAME is free, can work with scenarios or multiple decision makers and displays intermediate calculations. Users can structure their decision models into three levels – scenarios/users, criteria and variants. Items on all levels can be evaluated either by weights or pair-wise comparisons. There are provided three different methods for the evaluation of the weights of criteria, the variants as well as the scenarios – Saaty’s Method, Geometric Mean Method and Fuller’s Triangle Method. Multiplicative and additive syntheses are supported. The proposed software package is demonstrated on couple of illustrating examples of real life decision problems.

Keywords: Analytic hierarchy process, multi-criteria decision making, pair-wise comparisons, Microsoft Excel, Scenarios.

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Authors: Lina Galinskaitė, Gytautas Ignatavičius

Abstract:

Animal vehicle collisions (AVCs) affect human safety, cause property damage and wildlife welfare. The number of AVCs are increasing and creating serious implications for the animal conservation and management. Roe deer (Capreolus capreolus) and other large ungulates (moose, wild boar, red deer) are the most frequently collided ungulate with vehicles in Europe. Therefore, we analyzed temporal patterns of roe deer vehicle collisions (RDVC) occurring in Lithuania. Using a comprehensive dataset, consisting of 15,891 data points, we examined the influence of different time units (i.e. time of the day, day of week, month, and season) on RDVC. We identified accident periods within the analyzed time units. Highest frequencies of RDVC occurred on Fridays. Highest frequencies of roe deer-vehicle accidents occurred in May, November and December. Regarding diurnal patterns, most of RDVC occur after sunset and before sunset (during dark hours). Since vehicle collisions with animals showed temporal variation, these should be taken into consideration in developing statistical models of spatial AVC patterns, and also in planning strategies to reduce accident risk.

Keywords: Animal vehicle collision, diurnal patterns, road safety, roe deer, statistical analysis.

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Authors: Andrés Carrión García, Aura López de Murillo, José Jabaloyes Vivas, Angela Grisales del Río

Abstract:

Some quality control tools use non metric subjective information coming from experts, who qualify the intensity of relations existing inside processes, but without quantifying them. In this paper we have developed a quality control analytic tool, measuring the impact or strength of the relationship between process operations and product characteristics. The tool includes two models: a qualitative model, allowing relationships description and analysis; and a formal quantitative model, by means of which relationship quantification is achieved. In the first one, concepts from the Graphs Theory were applied to identify those process elements which can be sources of variation, that is, those quality characteristics or operations that have some sort of prelacy over the others and that should become control items. Also the most dependent elements can be identified, that is those elements receiving the effects of elements identified as variation sources. If controls are focused in those dependent elements, efficiency of control is compromised by the fact that we are controlling effects, not causes. The second model applied adapts the multivariate statistical technique of Covariance Structural Analysis. This approach allowed us to quantify the relationships. The computer package LISREL was used to obtain statistics and to validate the model.

Keywords: Characteristics matrix, covariance structure analysis, LISREL.

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Authors: Mete Kazaz

Abstract:

Despite the internet, which is one of the mass media that has become quite common in recent years, the relationship of Advertisement with Television and Cinema, which have always drawn attention of researchers as basic media and where visual use is in the foreground, have also become the subject of various studies. Based on the assumption that the known fundamental effects of advertisements on consumers are closely related to the creative process of advertisements as well as the nature and characteristics of the medium where they are used, these basic mass media (Television and Cinema) and the consumer motivations of the advertisements they broadcast have become a focus of study. Given that the viewers of the mass media in question have shifted from a passive position to a more active one especially in recent years and approach contents of advertisements, as they do all contents, in a more critical and “pitiless" manner, it is possible to say that individuals make more use of advertisements than in the past and combine their individual goals with the goals of the advertisements. This study, which aims at finding out what the goals of these new individual advertisement use are, how they are shaped by the distinct characteristics of Television and Cinema, where visuality takes precedence as basic mass media, and what kind of places they occupy in the minds of consumers, has determined consumers- motivations as: “Entertainment", “Escapism", “Play", “Monitoring/Discovery", “Opposite Sex" and “Aspirations and Role Models". This study intends to reveal the differences or similarities among the needs and hence the gratifications of viewers who consume advertisements on Television or at the Cinema, which are two basic media where visuality is prioritized.

Keywords: Cinema, Television, Viewers of Advertisements.

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Authors: Tien-Tung Chung, Chin-Te Lin, Chung-Yun Lee, Kuang-Chao Fan, Shou-Heng Chen

Abstract:

This paper studies the optimum design for reducing optical loss of an 8x8 mechanical type optical switch due to the temperature change. The 8x8 optical switch is composed of a base, 8 input fibers, 8 output fibers, 3 fixed mirrors and 17 movable mirrors. First, an innovative switch configuration is proposed with thermal-compensated design. Most mechanical type optical switches have a disadvantage that their precision and accuracy are influenced by the ambient temperature. Therefore, the thermal-compensated design is to deal with this situation by using materials with different thermal expansion coefficients (α). Second, a parametric modeling program is developed to generate solid models for finite element analysis, and the thermal and structural behaviors of the switch are analyzed. Finally, an integrated optimum design program, combining Autodesk Inventor Professional software, finite element analysis software, and genetic algorithms, is developed for improving the thermal behaviors that the optical loss of the switch is reduced. By changing design parameters of the switch in the integrated design program, the final optimum design that satisfies the design constraints and specifications can be found.

Keywords: Optical switch, finite element analysis, thermal-compensated design, optimum design.

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Authors: Mahmoud M. Tash

Abstract:

The present study was undertaken to investigate the effect of aging parameters (time and temperature) on the mechanical properties of Be-and/or Zr- treated Al-Mg-Zn (7075) alloys. Ultimate tensile strength, 0.5% offset yield strength and % elongation measurements were carried out on specimens prepared from cast and heat treated 7075 alloys containing Be and/or Zr. Different aging treatment were carried out for the as solution treated (SHT) specimens (after quenching in warm water). The specimens were aged at different conditions; Natural and artificial aging was carried out at room temperature, 120C, 150C, 180C and 220C for different periods of time. Duplex aging was performed for SHT conditions (pre-aged at different time and temperature followed by high temperature aging). Ultimate tensile strength, yield strength and % elongation data results as a function of different aging parameters are analysed. A statistical design of experiments (DOE) approach using fractional factorial design is applied to acquire an understanding of the effects of these variables and their interactions on the mechanical properties of Be- and/or Zr- treated 7075 alloys. Mathematical models are developed to relate the alloy mechanical properties with the different aging parameters.

Keywords: Casting, Aging Treatment, Mechanical Properties, Al-Mg-Zn (7075) alloys, Be- and/or Zr-Treatment, Experimental Correlation.

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