Search results for: integrated definition for process description capture (IDEF3) method

Authors: Amara Prakasa Rao, N. V. S. N. Sarma

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This paper describes the synthesis of linear array geometry with minimum sidelobe level and null control using the Taguchi method. Based on the concept of the orthogonal array, Taguchi method effectively reduces the number of tests required in an optimization process. Taguchi method has been successfully applied in many fields such as mechanical, chemical engineering, power electronics, etc. Compared to other evolutionary methods such as genetic algorithms, simulated annealing and particle swarm optimization, the Taguchi method is much easier to understand and implement. It requires less computational/iteration processing to optimize the problem. Different cases are considered to illustrate the performance of this technique. Simulation results show that this method outperforms the other evolution algorithms (like GA, PSO) for smart antenna systems design.

Keywords: array factor, beamforming, null placement, optimization method, orthogonal array, Taguchi method, smart antenna system

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Authors: Hacene Benkhoula, Mohamed Badreddine Benabdella, Hamid Bouzeboudja, Abderrahmane Asraoui

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The wind is a random variable difficult to master, for this, we developed a mathematical and statistical methods enable to modeling and forecast wind power. Gaussian Processes (GP) is one of the most widely used families of stochastic processes for modeling dependent data observed over time, or space or time and space. GP is an underlying process formed by unrecognized operator’s uses to solve a problem. The purpose of this paper is to present how to forecast wind power by using the GP. The Gaussian process method for forecasting are presented. To validate the presented approach, a simulation under the MATLAB environment has been given.

Keywords: wind power, Gaussien process, modelling, forecasting

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Authors: Musarrat Jabeen

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Thoughtful intelligence offers a sustainable position to enhance the influence of decision-makers. Thoughtful Intelligence implies the understanding to realize the impact of one’s thoughts, words and actions on the survival, dignity and development of the individuals, groups and nations. Thoughtful intelligence has received minimal consideration in the area of Decision Support Systems, with an end goal to evaluate the quantity of knowledge and its viability. This pattern degraded the imbibed contribution of thoughtful intelligence required for sustainable decision making. Given the concern, this paper concentrates on the question: How to present a model of Thoughtful Decision Support System (TDSS)? The aim of this paper is to appreciate the concepts of thoughtful intelligence and insinuate a Decision Support System based on thoughtful intelligence. Thoughtful intelligence includes three dynamic competencies: i) Realization about long term impacts of decisions that are made in a specific time and space, ii) A great sense of taking actions, iii) Intense interconnectivity with people and nature and; seven associate competencies, of Righteousness, Purposefulness, Understanding, Contemplation, Sincerity, Mindfulness, and Nurturing. The study utilizes two methods: Focused group discussion to count prevailing Decision Support Systems; 70% results of focus group discussions found six decision support systems and the positive inexistence of thoughtful intelligence among decision support systems regarding sustainable decision making. Delphi focused on defining thoughtful intelligence to model (TDSS). 65% results helped to conceptualize (definition and description) of thoughtful intelligence. TDSS is offered here as an addition in the decision making literature. The clients are top leaders.

Keywords: thoughtful intelligence, sustainable decision making, thoughtful decision support system

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Authors: Chih-Jer Lin, Jian-Hong Hou

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Industry 4.0 is a vision of integrated industry implemented by artificial intelligent computing, software, and Internet technologies. The main goal of industry 4.0 is to deal with the difficulty owing to competitive pressures in the marketplace. For today’s manufacturing factories, the type of production is changed from mass production (high quantity production with low product variety) to medium quantity-high variety production. To offer flexibility, better quality control, and improved productivity, robot manipulators are used to combine material processing, material handling, and part positioning systems into an integrated manufacturing system. To implement the automated system for sheet metal bending operations, motion planning of a 7-degrees of freedom (DOF) robot is studied in this paper. A virtual reality (VR) environment of a bending cell, which consists of the robot and a bending machine, is established using the virtual robot experimentation platform (V-REP) simulator. For sheet metal bending operations, the robot only needs six DOFs for the pick-and-place or tracking tasks. Therefore, this 7 DOF robot has more DOFs than the required to execute a specified task; it can be called a redundant robot. Therefore, this robot has kinematic redundancies to deal with the task-priority problems. For redundant robots, Pseudo-inverse of the Jacobian is the most popular motion planning method, but the pseudo-inverse methods usually lead to a kind of chaotic motion with unpredictable arm configurations as the Jacobian matrix lose ranks. To overcome the above problem, we proposed a method to formulate the motion planning problems as optimization problem. Moreover, a genetic algorithm (GA) based method is proposed to deal with motion planning of the redundant robot. Simulation results validate the proposed method feasible for motion planning of the redundant robot in an automated sheet-metal bending operations.

Keywords: redundant robot, motion planning, genetic algorithm, obstacle avoidance

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Authors: Roberta Martino, Viviana Ventre

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Empirical evidence has, over time, confirmed that the behavior of individuals is inconsistent with the descriptions provided by the Discounted Utility Model, an essential reference for calculating the utility of intertemporal prospects. The model assumes that individuals calculate the utility of intertemporal prospectuses by adding up the values of all outcomes obtained by multiplying the cardinal utility of the outcome by the discount function estimated at the time the outcome is received. The trend of the discount function is crucial for the preferences of the decision maker because it represents the perception of the future, and its trend causes temporally consistent or temporally inconsistent preferences. In particular, because different formulations of the discount function lead to various conclusions in predicting choice, the descriptive ability of models with a hyperbolic trend is greater than linear or exponential models. Suboptimal choices from any time point of view are the consequence of this mechanism, the psychological factors of which are encapsulated in the discount rate trend. In addition, analyzing the decision-making process from a psychological perspective, there is an equivalence between the selection of dominated prospects and a degree of impatience that decreases over time. The first part of the paper describes and investigates the anomalies of the discounted utility model by relating the cognitive distortions of the decision-maker to the emotional factors that are generated during the evaluation and selection of alternatives. Specifically, by studying the degree to which impatience decreases, it’s possible to quantify how the psychological and emotional mechanisms of the decision-maker result in a lack of decision persistence. In addition, this description presents inconsistency as the consequence of an inconsistent attitude towards time-delayed choices. The second part of the paper presents an experimental phase in which we show the relationship between inconsistency and impatience in different contexts. Analysis of the degree to which impatience decreases confirms the influence of the decision maker's emotional impulses for each anomaly in the utility model discussed in the first part of the paper. This work provides an application in the field of personalized behavioral finance. Indeed, the numerous behavioral diversities, evident even in the degrees of decrease in impatience in the experimental phase, support the idea that optimal strategies may not satisfy individuals in the same way. With the aim of homogenizing the categories of investors and to provide a personalized approach to advice, the results proven in the experimental phase are used in a complementary way with the information in the field of behavioral finance to implement the Analytical Hierarchy Process model in intertemporal choices, useful for strategic personalization. In the construction of the Analytic Hierarchy Process, the degree of decrease in impatience is understood as reflecting irrationality in decision-making and is therefore used for the construction of weights between anomalies and behavioral traits.

Keywords: analytic hierarchy process, behavioral finance, financial anomalies, impatience, time inconsistency

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Authors: Mark Harmon, Abdolghani Ebrahimi, Patrick Lucey, Diego Klabjan

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In this paper, we predict the likelihood of a player making a shot in basketball from multiagent trajectories. Previous approaches to similar problems center on hand-crafting features to capture domain-specific knowledge. Although intuitive, recent work in deep learning has shown, this approach is prone to missing important predictive features. To circumvent this issue, we present a convolutional neural network (CNN) approach where we initially represent the multiagent behavior as an image. To encode the adversarial nature of basketball, we use a multichannel image which we then feed into a CNN. Additionally, to capture the temporal aspect of the trajectories, we use “fading.” We find that this approach is superior to a traditional FFN model. By using gradient ascent, we were able to discover what the CNN filters look for during training. Last, we find that a combined FFN+CNN is the best performing network with an error rate of 39%.

Keywords: basketball, computer vision, image processing, convolutional neural network

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Authors: Rima Abu Jaber Bransi, Rawya Jarjoura Burbara

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This study deals with two pioneering approaches in teaching Arabic as a mother tongue: first, computerization of literary and functional texts in the mother tongue; second, the pioneering model in teaching writing skills by computerization. The significance of the study lies in its treatment of a serious problem that is faced in the era of technology, which is the widening gap between the pupils and their mother tongue. The innovation in the study is that it introduces modern methods and tools and a pioneering instructional model that turns the process of mother tongue teaching into an effective, meaningful, interesting and motivating experience. In view of the Arabic language diglossia, standard Arabic and spoken Arabic, which constitutes a serious problem to the pupil in understanding unused words, and in order to bridge the gap between the pupils and their mother tongue, we resorted to computerized techniques; we took texts from the pre-Islamic period (Jahiliyya), starting with the Mu'allaqa of Imru' al-Qais and other selected functional texts and computerized them for teaching in an interesting way that saves time and effort, develops high thinking strategies, expands the literary good taste among the pupils, and gives the text added values that neither the book, the blackboard, the teacher nor the worksheets provide. On the other hand, we have developed a pioneering computerized model that aims to develop the pupil's ability to think, to provide his imagination with the elements of growth, invention and connection, and motivate him to be creative, and raise level of his scores and scholastic achievements. The model consists of four basic stages in teaching according to the following order: 1. The Preparatory stage, 2. The reading comprehension stage, 3. The writing stage, 4. The evaluation stage. Our lecture will introduce a detailed description of the model with illustrations and samples from the units that we built through highlighting some aspects of the uniqueness and innovation that are specific to this model and the different integrated tools and techniques that we developed. One of the most significant conclusions of this research is that teaching languages through the employment of new computerized strategies is very likely to get the Arabic speaking pupils out of the circle of passive reception into active and serious action and interaction. The study also emphasizes the argument that the computerized model of teaching can change the role of the pupil's mind from being a store of knowledge for a short time into a partner in producing knowledge and storing it in a coherent way that prevents its forgetfulness and keeping it in memory for a long period of time. Consequently, the learners also turn into partners in evaluation by expressing their views, giving their notes and observations, and application of the method of peer-teaching and learning.

Keywords: classical poetry, computerization, diglossia, writing skill

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Authors: Jin Lin, Shouxiang Lu, Kim Meow Liew

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In a fire accident, fire smoke often poses a serious threat to human safety especially in the enclosed space such as submarine and space-crafts environment. Efficient removal of the hazardous gas products particularly a large amount of CO and CO₂ gases from these confined space is critical for the security of the staff and necessary for the post-fire environment recovery. In this work, Cu-Mn-Ce composite oxide catalysts coupled with CO₂ sorbents were prepared using wet impregnation method, solid-state impregnation method and wet/solid-state impregnation method. The as-prepared samples were tested dynamically and isothermally for CO oxidation and CO₂ sorption and further characterized by the X-ray diffraction (XRD), nitrogen adsorption and desorption, and field emission scanning electron microscopy (FE-SEM). The results showed that all the samples were able to catalyze CO into CO₂ and capture CO₂ in situ by chemisorption. Among all the samples, the sample synthesized by the wet/solid-state impregnation method showed the highest catalytic activity toward CO oxidation and the fine ability of CO₂ sorption. The sample prepared by the solid-state impregnation method showed the second CO oxidation performance, while the coupled sample using the wet impregnation method exhibited much poor CO oxidation activity. The various CO oxidation and CO₂ sorption properties of the samples might arise from the different dispersed states of the CO₂ sorbent in the CO catalyst, owing to the different preparation methods. XRD results confirmed the high-dispersed sorbent phase in the samples prepared by the wet and solid impregnation method, while that of the sample prepared by wet/solid-state impregnation method showed the larger bulk phase as indicated by the high-intensity diffraction peaks. Nitrogen adsorption and desorption results further revealed that the latter sample had a higher surface area and pore volume, which were beneficial for the CO oxidation over the catalyst. Hence, the Cu-Mn-Ce oxide catalyst coupled with CO₂ sorbent using wet/solid-state impregnation method could be a good choice for fire smoke removal in the enclosed space.

Keywords: CO oxidation, CO₂ sorption, preparation methods, smoke removal

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Authors: Laila Oubahman, Duleba Szabolcs

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Public transport stakeholders aim to increase the ridership ratio by encouraging citizens to use common transportation modes. For this sight, improving service quality is a crucial option to reach the quality desired by users and reduce the gap between desired and perceived quality. Multi-criteria decision aid has been applied in literature in recent decades because it provides efficient models to assess the most impacting criteria on the overall assessment. In this paper, the PROMETHEE method is combined with the best-worst approach to construct a consensual model that avoids rank reversal to support stakeholders in ameliorating service quality.

Keywords: best-worst method, MCDA, PROMETHEE, public transport

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Authors: Mazifah Simis, Azahan Awang, Kadir Arifin

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The brownfield regeneration is being implemented in developped countries. However, as a group 1 developing country in the South East Asia, the rapid development and increasing number of urban population in Malaysia have urged the needs to incorporate the brownfield regeneration into its physical planning development. The increasing number of urban ex-landfills is seen as a new resource that could overcome the issues of inadequate urban green space provisions. With regards to the new development approach in urban planning, this perception study aims to identify the sustainable planning approach based on what the stakeholders have in mind. Respondents consist of 375 local communities within four urban ex-landfill areas and 61 landscape architect and town planner officers in the Malaysian Local Authorities. Three main objectives are set to be achieved, which are (i) to identify ex-landfill issues that need to be overcome prior to the ex-landfill redevelopment (ii) to identify the most suitable types of ex-landfill redevelopment, and (iii) to identify the priority function for ex-landfill redevelopment as the public parks. From the data gathered through the survey method, the order of priorities based on stakeholders' perception was produced. The results show different perception among the stakeholders, but they agreed to the development of the public park as the main development. Hence, this study attempts to produce an integrated approach as a model for sustainable ex-landfill redevelopment that could be accepted by the stakeholders as a beneficial future development that could change the image of 296 ex-landfills in Malaysia into the urban public parks by the year 2020.

Keywords: brownfield regeneration, ex-landfill redevelopment, integrated approach, stakeholders' perception

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Authors: Elin Cahyaningsih, Dana Indra Sensuse, Wahyu Catur Wibowo, Sofiyanti Indriasari

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Bureaucracy reform program drives Indonesian government to change their management and supporting unit in order to enhance their organization performance. Information technology as one of supporting unit became one of strategic plan that organization tried to improve, because IT can automate and speed up process, reduce business process life cycle become more effective and efficient. Knowledge management system is a technology application for supporting knowledge management implementation in government which is requirement based on problem and potential functionality of each knowledge management process. Define knowledge management that suitable for each organization it is difficult, that why we should make the knowledge management system strategy as an alignment of knowledge management process in the organization. Knowledge management system is one of information system development in people perspective, because this system has high dependency in human interaction and participation. Strategic plan for developing knowledge management system can be determine using some of information system strategic methods. This research conducted to define type of strategic method of information system, stage of activity each method, the strategic method strength and weakness. The author use literature review methods for identify and classify strategic methods of information system for differentiate method type, categorize common activities, strength and weakness. Result of this research are determine and compare six strategic information system methods, there are Balanced Scorecard, Five Force Porter, SWOT analysis, Value Chain Analysis, Risk Analysis and Gap Analysis. Balanced Scorecard and Risk Analysis believe as common strategic method that usually used and have the highest excellence strength.

Keywords: knowledge management system, balanced scorecard, five force, risk analysis, gap analysis, value chain analysis, SWOT analysis

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Authors: Evan Lowhorn, Rocio Alba-Flores

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The purpose of this work is to develop a method for classifying hand signals and using the output in a drone control algorithm. To achieve this, methods based on Convolutional Neural Networks (CNN) were applied. CNN's are a subset of deep learning, which allows grid-like inputs to be processed and passed through a neural network to be trained for classification. This type of neural network allows for classification via imaging, which is less intrusive than previous methods using biosensors, such as EMG sensors. Classification CNN's operate purely from the pixel values in an image; therefore they can be used without additional exteroceptive sensors. A development bench was constructed using a desktop computer connected to a high-definition webcam mounted on a scissor arm. This allowed the camera to be pointed downwards at the desk to provide a constant solid background for the dataset and a clear detection area for the user. A MATLAB script was created to automate dataset image capture at the development bench and save the images to the desktop. This allowed the user to create their own dataset of 12,000 images within three hours. These images were evenly distributed among seven classes. The defined classes include forward, backward, left, right, idle, and land. The drone has a popular flip function which was also included as an additional class. To simplify control, the corresponding hand signals chosen were the numerical hand signs for one through five for movements, a fist for land, and the universal “ok” sign for the flip command. Transfer learning with PyTorch (Python) was performed using a pre-trained 18-layer residual learning network (ResNet-18) to retrain the network for custom classification. An algorithm was created to interpret the classification and send encoded messages to a Ryze Tello drone over its 2.4 GHz Wi-Fi connection. The drone’s movements were performed in half-meter distance increments at a constant speed. When combined with the drone control algorithm, the classification performed as desired with negligible latency when compared to the delay in the drone’s movement commands.

Keywords: classification, computer vision, convolutional neural networks, drone control

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Authors: Suguru Miyauchi, Toshiyuki Hayase

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Biological membranes have selective permeability, and the capsules or cells enclosed by the membrane show the deformation by the osmotic flow. This mass transport phenomenon is observed everywhere in a living body. For the understanding of the mass transfer in a body, it is necessary to consider the mass transfer phenomenon across the membrane as well as the deformation of the membrane by a flow. To our knowledge, in the numerical analysis, the method for mass transfer across the moving membrane has not been established due to the difficulty of the treating of the mass flux permeating through the moving membrane with selective permeability. In the existing methods for the mass transfer across the membrane, the approximate delta function is used to communicate the quantities on the interface. The methods can reproduce the permeation of the solute, but cannot reproduce the non-permeation. Moreover, the computational accuracy decreases with decreasing of the permeable coefficient of the membrane. This study aims to develop the numerical method capable of treating three-dimensional problems of mass transfer across the moving flexible membrane. One of the authors developed the numerical method with high accuracy based on the finite element method. This method can capture the discontinuity on the membrane sharply due to the consideration of the jumps in concentration and concentration gradient in the finite element discretization. The formulation of the method takes into account the membrane movement, and both permeable and non-permeable membranes can be treated. However, searching the cross points of the membrane and fluid element boundaries and splitting the fluid element into sub-elements are needed for the numerical integral. Therefore, cumbersome operation is required for a three-dimensional problem. In this paper, we proposed an improved method to avoid the search and split operations, and confirmed its effectiveness. The membrane shape was treated implicitly by introducing the level set function. As the construction of the level set function, the membrane shape in one fluid element was expressed by the shape function of the finite element method. By the numerical experiment, it was found that the shape function with third order appropriately reproduces the membrane shapes. The same level of accuracy compared with the previous method using search and split operations was achieved by using a number of sampling points of the numerical integral. The effectiveness of the method was confirmed by solving several model problems.

Keywords: finite element method, level set method, mass transfer, membrane permeability

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Authors: Siming Xie

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In social networks, the term homophily refers to the tendency of agents with similar characteristics to link with one another and is so robustly observed across many contexts and dimensions. The starting point of my research is the observation that the “type” of agents is not a single exogenous variable. Agents, despite their differences in race, religion, and other hard to alter characteristics, may share interests and engage in activities that cut across those predetermined lines. This research aims to capture the interactions of homophily effects in a model where agents have two-dimension characteristics (i.e., race and personal hobbies such as basketball, which one either likes or dislikes) and with biases in meeting opportunities and in favor of same-type friendships. A novel feature of my model is providing a matching process with biased meeting probability on different dimensions, which could help to understand the structuring process in multidimensional networks without missing layer interdependencies. The main contribution of this study is providing a welfare based matching process for agents with multi-dimensional characteristics. In particular, this research shows that the biases in meeting opportunities on one dimension would lead to the emergence of homophily on the other dimension. The objective of this research is to determine the pattern of homophily in network formations, which will shed light on our understanding of segregation and its remedies. By constructing a two-dimension matching process, this study explores a method to describe agents’ homophilous behavior in a social network with multidimension and construct a game in which the minorities and majorities play different strategies in a society. It also shows that the optimal strategy is determined by the relative group size, where society would suffer more from social segregation if the two racial groups have a similar size. The research also has political implications—cultivating the same characteristics among agents helps diminishing social segregation, but only if the minority group is small enough. This research includes both theoretical models and empirical analysis. Providing the friendship formation model, the author first uses MATLAB to perform iteration calculations, then derives corresponding mathematical proof on previous results, and last shows that the model is consistent with empirical evidence from high school friendships. The anonymous data comes from The National Longitudinal Study of Adolescent Health (Add Health).

Keywords: homophily, multidimension, social networks, friendships

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Authors: Maryam Mohammadi, Mohammadjavad Mahdavinejad, Mojtaba Ansari

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The main driving force for increasing movement towards the design of High-Performance Buildings (HPB) are building codes and rating systems that address the various components of the building and their impact on the environment and energy conservation through various methods like prescriptive methods or simulation-based approaches. The methods and tools developed to meet these needs, which are often based on building performance simulation tools (BPST), have limitations in terms of compatibility with the integrated design process (IDP) and HPB design, as well as use by architects in the early stages of design (when the most important decisions are made). To overcome these limitations in recent years, efforts have been made to develop Design Decision Support Systems, which are often based on artificial intelligence. Numerous needs and steps for designing and developing a Decision Support System (DSS), which complies with the early stages of energy-efficient architecture design -consisting of combinations of different methods in an integrated package- have been listed in the literature. While various review studies have been conducted in connection with each of these techniques (such as optimizations, sensitivity and uncertainty analysis, etc.) and their integration of them with specific targets; this article is a critical and holistic review of the researches which leads to the development of applicable systems or introduction of a comprehensive framework for developing models complies with the IDP. Information resources such as Science Direct and Google Scholar are searched using specific keywords and the results are divided into two main categories: Simulation-based DSSs and Meta-simulation-based DSSs. The strengths and limitations of different models are highlighted, two general conceptual models are introduced for each category and the degree of compliance of these models with the IDP Framework is discussed. The research shows movement towards Multi-Level of Development (MOD) models, well combined with early stages of integrated design (schematic design stage and design development stage), which are heuristic, hybrid and Meta-simulation-based, relies on Big-real Data (like Building Energy Management Systems Data or Web data). Obtaining, using and combining of these data with simulation data to create models with higher uncertainty, more dynamic and more sensitive to context and culture models, as well as models that can generate economy-energy-efficient design scenarios using local data (to be more harmonized with circular economy principles), are important research areas in this field. The results of this study are a roadmap for researchers and developers of these tools.

Keywords: integrated design process, design decision support system, meta-simulation based, early stage, big data, energy efficiency

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Authors: Amir Seyfoori, Ehsan Samiei, Mohsen Akbari

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The use of microtechnology for detection and high yield isolation of circulating tumor cells (CTCs) has shown enormous promise as an indication of clinical metastasis prognosis and cancer treatment monitoring. The Immunomagnetic assay has been also coupled to microtechnology to improve the selectivity and efficiency of the current methods of cancer biomarker isolation. In this way, generation and configuration of the local high gradient magnetic field play essential roles in such assay. Additionally, considering the intrinsic heterogeneity of cancer cells, real-time analysis of isolated cells is necessary to characterize their responses to therapy. Totally, on-chip isolation and monitoring of the specific tumor cells is considered as a pressing need in the way of modified cancer therapy. To address these challenges, we have developed a bi-layer magnetic-based microfluidic chip for enhanced CTC detection and capturing. Micromagnet arrays at the bottom layer of the chip were fabricated using a new method of magnetic nanoparticle paste deposition so that they were arranged at the center of the chain microchannel with the lowest fluid velocity zone. Breast cancer cells labelled with EPCAM-conjugated smart microgels were immobilized on the tip of the micromagnets with greater localized magnetic field and stronger cell-micromagnet interaction. Considering different magnetic nano-powder usage (MnFe2O4 & gamma-Fe2O3) and micromagnet shapes (ellipsoidal & arrow), the capture efficiency of the systems was adjusted while the higher CTC capture efficiency was acquired for MnFe2O4 arrow micromagnet as around 95.5%. As a proof of concept of on-chip tumor cell monitoring, magnetic smart microgels made of thermo-responsive poly N-isopropylacrylamide-co-acrylic acid (PNIPAM-AA) composition were used for both purposes of targeted cell capturing as well as cell monitoring using antibody conjugation and fluorescent dye loading at the same time. In this regard, magnetic microgels were successfully used as cell tracker after isolation process so that by raising the temperature up to 37⁰ C, they released the contained dye and stained the targeted cell just after capturing. This microfluidic device was able to provide a platform for detection, isolation and efficient real-time analysis of specific CTCs in the liquid biopsy of breast cancer patients.

Keywords: circulating tumor cells, microfluidic, immunomagnetic, cell isolation

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Authors: Archana Thangavelu, Han-Ik Park, Young-Chul Park, Joon-Hong Park

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In this numerical study, we have proposed a method for evaluation of backward extrusion process of pressure vessel made up of steel. Demand for lighter and stiffer products have been increasing in the last years especially in automobile engineering. Through detailed finite element analysis, effective stress, strain and velocity profile have been obtained with optimal range. The process design of a forward and backward extrusion axe-symmetric part has been studied. Forging is mainly carried out because forged products are highly reliable and possess superior mechanical properties when compared to normal products. Performing computational simulations of 3D hot forging with various dimensions of billet and optimization of weight is carried out using Taguchi Orthogonal Array (OA) Optimization technique. The technique used in this study can be used for newly developed materials to investigate its forgeability for much complicated shapes in closed hot die forging process.

Keywords: backward extrusion, hot forging, optimization, finite element analysis, Taguchi method

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Authors: Ksenia Meshkova

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With increasing amount of multimedia data, it is very important to automate and speed up the process of obtaining meta. This process means not just recognition of some object or its movement, but recognition of the entire scene versus separate frames and having timeline segmentation as a final result. Labeling datasets is time consuming, besides, attributing characteristics to particular scenes is clearly difficult due to their nature. In this article, we will consider autoencoders application to unsupervised scene recognition and clusterization based on interpretable features. Further, we will focus on particular types of auto encoders that relevant to our study. We will take a look at the specificity of deep learning related to information theory and rate-distortion theory and describe the solutions empowering poor interpretability of deep learning in media content processing. As a conclusion, we will present the results of the work of custom framework, based on autoencoders, capable of scene recognition as was deeply studied above, with highlights generation resulted out of this recognition. We will not describe in detail the mathematical description of neural networks work but will clarify the necessary concepts and pay attention to important nuances.

Keywords: neural networks, computer vision, representation learning, autoencoders

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Authors: Anna Makuch, Grzegorz Kokot, Konstanty Skalski, Jakub Banczorowski

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Cancellous bone is a porous composite of a hierarchical structure and anisotropic properties. The biological tissue is considered to be a viscoelastic material, but many studies based on a nanoindentation method have focused on their elasticity and microhardness. However, the response of many organic materials depends not only on the load magnitude, but also on its duration and time course. Depth Sensing Indentation (DSI) technique has been used for examination of creep in polymers, metals and composites. In the indentation tests on biological samples, the mechanical properties are most frequently determined for animal tissues (of an ox, a monkey, a pig, a rat, a mouse, a bovine). However, there are rare reports of studies of the bone viscoelastic properties on microstructural level. Various rheological models were used to describe the viscoelastic behaviours of bone, identified in the indentation process (e. g Burgers model, linear model, two-dashpot Kelvin model, Maxwell-Voigt model). The goal of the study was to determine the influence of creep effect on the mechanical properties of human cancellous bone in indentation tests. The aim of this research was also the assessment of the material properties of bone structures, having in mind the energy aspects of the curve (penetrator loading-depth) obtained in the loading/unloading cycle. There was considered how the different holding times affected the results within trabecular bone.As a result, indentation creep (CIT), hardness (HM, HIT, HV) and elasticity are obtained. Human trabecular bone samples (n=21; mean age 63±15yrs) from the femoral heads replaced during hip alloplasty were removed and drained from alcohol of 1h before the experiment. The indentation process was conducted using CSM Microhardness Tester equipped with Vickers indenter. Each sample was indented 35 times (7 times for 5 different hold times: t1=0.1s, t2=1s, t3=10s, t4=100s and t5=1000s). The indenter was advanced at a rate of 10mN/s to 500mN. There was used Oliver-Pharr method in calculation process. The increase of hold time is associated with the decrease of hardness parameters (HIT(t1)=418±34 MPa, HIT(t2)=390±50 MPa, HIT(t3)= 313±54 MPa, HIT(t4)=305±54 MPa, HIT(t5)=276±90 MPa) and elasticity (EIT(t1)=7.7±1.2 GPa, EIT(t2)=8.0±1.5 GPa, EIT(t3)=7.0±0.9 GPa, EIT(t4)=7.2±0.9 GPa, EIT(t5)=6.2±1.8 GPa) as well as with the increase of the elastic (Welastic(t1)=4.11∙10-7±4.2∙10-8Nm, Welastic(t2)= 4.12∙10-7±6.4∙10-8 Nm, Welastic(t3)=4.71∙10-7±6.0∙10-9 Nm, Welastic(t4)= 4.33∙10-7±5.5∙10-9Nm, Welastic(t5)=5.11∙10-7±7.4∙10-8Nm) and inelastic (Winelastic(t1)=1.05∙10-6±1.2∙10-7 Nm, Winelastic(t2) =1.07∙10-6±7.6∙10-8 Nm, Winelastic(t3)=1.26∙10-6±1.9∙10-7Nm, Winelastic(t4)=1.56∙10-6± 1.9∙10-7 Nm, Winelastic(t5)=1.67∙10-6±2.6∙10-7)) reaction of materials. The indentation creep increased logarithmically (R2=0.901) with increasing hold time: CIT(t1) = 0.08±0.01%, CIT(t2) = 0.7±0.1%, CIT(t3) = 3.7±0.3%, CIT(t4) = 12.2±1.5%, CIT(t5) = 13.5±3.8%. The pronounced impact of creep effect on the mechanical properties of human cancellous bone was observed in experimental studies. While the description elastic-inelastic, and thus the Oliver-Pharr method for data analysis, may apply in few limited cases, most biological tissues do not exhibit elastic-inelastic indentation responses. Viscoelastic properties of tissues may play a significant role in remodelling. The aspect is still under an analysis and numerical simulations. Acknowledgements: The presented results are part of the research project founded by National Science Centre (NCN), Poland, no.2014/15/B/ST7/03244.

Keywords: bone, creep, indentation, mechanical properties

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Authors: Hao Wang, Shuguo Pan

Abstract:

The Global Navigation Satellite System (GNSS) signal received by the dynamic vehicle in the harsh environment will be frequently interfered with and blocked, which generates gross error affecting the positioning accuracy of the GNSS/Inertial Navigation System (INS) integrated navigation. Therefore, this paper put forward an improved robust Cubature Kalman filter (CKF) algorithm for single-frequency GNSS/INS tightly coupled system ambiguity resolution. Firstly, the dynamic model and measurement model of a single-frequency GNSS/INS tightly coupled system was established, and the method for GNSS integer ambiguity resolution with INS aided is studied. Then, we analyzed the influence of pseudo-range observation with gross error on GNSS/INS integrated positioning accuracy. To reduce the influence of outliers, this paper improved the CKF algorithm and realized an intelligent selection of robust strategies by judging the ill-conditioned matrix. Finally, a field navigation test was performed to demonstrate the effectiveness of the proposed algorithm based on the double-differenced solution mode. The experiment has proved the improved robust algorithm can greatly weaken the influence of separate, continuous, and hybrid observation anomalies for enhancing the reliability and accuracy of GNSS/INS tightly coupled navigation solutions.

Keywords: GNSS/INS integrated navigation, ambiguity resolution, Cubature Kalman filter, Robust algorithm

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Authors: Mokhtar Nikgoo

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Definition of bridge: A bridge is a structure that allows people to pass through the communication road with two points. There are many different types of bridges, each of which is designed to perform a specific function. This article introduces the concept, history, components, uses, types, construction methods, selected factors, damage factors and principles of bridge maintenance. A bridge is a structure to cross a passage such as a water, valley or road without blocking another path underneath. This structure makes it possible to pass obstacles that are difficult or impossible to pass. There are different designs for bridge construction, each of which is used for a particular function and condition. In the old definition, a bridge is an arch over a river, valley, or any type of passage that makes traffic possible. But today, in the topic of urban management, the bridge is considered as a structure to cross physical barriers, so that while using space (not just the surface of the earth), it can facilitate the passage and access to places. The useful life of bridges may be between 30 and 80 years depending on the location and the materials used. But with proper maintenance and improvement, their life may last for hundreds of years.

Keywords: bridge, road construction, surveying, transportation

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Authors: Ifeyinwa Rita Kanu, Thomas Aspray, Adebayo J. Adeloye

Abstract:

As a result of the ambiguity and complexity surrounding anaerobic digester foaming, efforts have been made by various researchers to understand the process of anaerobic digester foaming so as to proffer a solution that can be universally applied rather than site specific. All attempts ranging from experimental analysis to comparative review of other process has been futile at explaining explicitly the conditions and process of foaming in anaerobic digester. Studying the available knowledge on foam formation and relating it to anaerobic digester process and operating condition, this study presents a succinct and enhanced understanding of foaming in anaerobic digesters as well as introducing a simple and novel method to identify the onset of anaerobic digester foaming based on analysis of historical data from a field scale system.

Keywords: anaerobic digester, foaming, biogas, surfactant, wastewater

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Authors: A. Schirru, A. Irimescu, S. Merola, A. d’Adamo, S. Fontanesi

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One of the aspects that are usually neglected during the design phase of an engine is the effect of the spark plug on the flow field inside the combustion chamber. Because of the difficulties in the experimental investigation of the mutual interaction between flow alteration and early flame kernel convection effect inside the engine combustion chamber, CFD-3D simulation is usually exploited in such cases. Experimentally speaking, a particular type of engine has to be used in order to directly observe the flame propagation process. In this study, a double electrode spark plug was fitted into an optically accessible engine and a high-speed camera was used to capture the initial stages of the combustion process. Both the arc and the kernel phases were observed. Then, a morphologic analysis was carried out and the position of the center of mass of the flame, relative to the spark plug position, was calculated. The crossflow orientation was chosen for the spark plug and the kernel growth process was observed for different air-fuel ratios. It was observed that during a normal cycle the flow field between the electrodes tends to transport the arc deforming it. Because of that, the kernel growth phase takes place away from the electrodes and the flame propagates with a preferential direction dictated by the flow field.

Keywords: Combustion, Optically Accessible Engine, Spark-Ignition Engine, Sparl Orientation, Kernel Growth

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Authors: Jaechoul Shin, Juhwan Hwang

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In case of applying the BIM method to the civil engineering in the area of free formed structure, we can expect comparatively high rate of construction productivity as it is in the building engineering area. In this research, we developed quantity calculation error applying it to earthwork and bridge construction (e.g. PSC-I type segmental girder bridge amd integrated bridge of steel I-girders and inverted-Tee bent cap), NATM (New Austrian Tunneling Method) tunnel construction, retaining wall construction, culvert construction and implemented BIM based 3D modeling quantity survey. we confirmed high reliability of the BIM-based method in structure work in which errors occurred in range between -6% ~ +5%. Especially, understanding of the problem and improvement of the existing 2D-CAD based of quantity calculation through rock type quantity calculation error in range of -14% ~ +13% of earthwork quantity calculation. It is benefit and applicability of BIM method in civil engineering. In addition, routine method for quantity of earthwork has the same error tolerance negligible for that of structure work. But, rock type's quantity calculated as the error appears significantly to the reliability of 2D-based volume calculation shows that the problem could be. Through the estimating quantity of earthwork based 3D-BIM, proposed method has better reliability than routine method. BIM, as well as the design, construction, maintenance levels of information when you consider the benefits of integration, the introduction of BIM design in civil engineering and the possibility of applying for the effectiveness was confirmed.

Keywords: BIM, 3D modeling, 3D-BIM, quantity of earthwork

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Authors: Ismail Halijah, Abdullah Rusli

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Introduction: This systematic literature review aims to identify the Knowledge Management Best Practice components in the Knowledge Management Model for Higher Learning Institutions environment. Study design: Systematic literature review. Methods: A systematic literature re-view of Knowledge Management Best Practice to identify and define the components of Best Practice from the Knowledge Management models was conducted recently. Results: This review of published papers of conference and journals’ articles shows the components of Best Practice in Knowledge Management are basically divided into two aspect which is the soft aspect and the hard aspect. The lacks of combination of these two aspects into an integrated model decelerate Knowledge Management Best Practice to fully throttle. Evidence from the literature shows the lack of integration of this two aspects leads to the immaturity of the Higher Learning Institution (HLI) towards the implementation of Knowledge Management System. Conclusion: The first steps of identifying the attributes to measure the Knowledge Management Best Practice components from the models in the literature will led to the definition of the Knowledge Management Best Practice component for the higher learning environment.

Keywords: knowledge management, knowledge management system, knowledge management best practice, knowledge management higher learning institution

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Authors: J. E. O. Hernandez

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In the next 20 years, energy production by burning fuels will increase and so will the atmospheric concentration of CO2 and its well-known threats to life on Earth. The technologies available for capturing CO2 are still dubious and this keeps fostering an interest in bio-inspired approaches. The leading one is the application of carbonic anhydrase (CA) –a superfast biocatalyst able to convert up to one million molecules of CO2 into carbonates in water. However, natural CA underperforms when applied to real smoky CO2 in chimneys and, so far, the efforts to create superior CAs in the lab rely on screening methods running under pristine conditions at the micro level, which are far from resembling those in chimneys. For the evolution of man-made enzymes, selection rather than screening would be ideal but this is challenging because of the need for a suitable artificial environment that is also sustainable for our society. Herein we present the stepwise design and construction of a bioprocess (from bench-scale to semi-pilot) for evolutionary selection experiments. In this bioprocess, reaction and adsorption took place simultaneously at atmospheric pressure in a spray tower. The scrubbing solution was fed countercurrently by reusing municipal pressure and it was mainly prepared with water, carbonic anhydrase and calcium chloride. This bioprocess allowed for the enzymatic carbonation of smoky CO2; the reuse of process water and the recovery of solid carbonates without cooling of smoke, pretreatments, solvent amines and compression of CO2. The average yield of solid carbonates was 0.54 g min-1 or 12-fold the amount produced in serum bottles at lab bench scale. This bioprocess could be used as a tailor-made environment for driving the selection of superior CAs. The bioprocess and its match CA could be sustainably used to reduce global warming by CO2 emissions from exhausts.

Keywords: biological carbon capture and sequestration, carbonic anhydrase, directed evolution, global warming

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Authors: Clarinda Vitorino Nhangumbe, Fredericks Ebrahim, Betuel Canhanga

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The price of an option weather derivatives can be approximated as a solution of the two-dimensional convection-diffusion dominant partial differential equation derived from the Ornstein-Uhlenbeck process, where one variable represents the weather dynamics and the other variable represent the underlying weather index. With appropriate financial boundary conditions, the solution of the pricing equation is approximated using a nonstandard finite difference method. It is shown that the proposed numerical scheme preserves positivity as well as stability and consistency. In order to illustrate the accuracy of the method, the numerical results are compared with other methods. The model is tested for real weather data.

Keywords: nonstandard finite differences, Ornstein-Uhlenbeck process, partial differential equations approach, weather derivatives

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Authors: Milica Ž. Karadžić, Lidija R. Jevrić, Sanja Podunavac-Kuzmanović, Strahinja Z. Kovačević, Anamarija I. Mandić, Katarina Penov-Gaši, Andrea R. Nikolić, Aleksandar M. Oklješa

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This study considered selection of the in silico molecular descriptors and the models for newly synthesized steroid derivatives description and their characterization using chemometric techniques. Multiple linear regression (MLR) models were established and gave the best molecular descriptors for quantitative structure-retention relationship (QSRR) modeling of the retention of the investigated molecules. MLR models were without multicollinearity among the selected molecular descriptors according to the variance inflation factor (VIF) values. Used molecular descriptors were ranked using generalized pair correlation method (GPCM). In this method, the significant difference between independent variables can be noticed regardless almost equal correlation between dependent variable. Generated MLR models were statistically and cross-validated and the best models were kept. Models were ranked using sum of ranking differences (SRD) method. According to this method, the most consistent QSRR model can be found and similarity or dissimilarity between the models could be noticed. In this study, SRD was performed using average values of experimentally observed data as a golden standard. Chemometric analysis was conducted in order to characterize newly synthesized steroid derivatives for further investigation regarding their potential biological activity and further synthesis. This article is based upon work from COST Action (CM1105), supported by COST (European Cooperation in Science and Technology).

Keywords: generalized pair correlation method, molecular descriptors, regression analysis, steroids, sum of ranking differences

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Authors: Adebisi A. Sunday, Babajide Adeokin

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The persistent rise in farm theft in rural region of Nigeria is attributed to the lack of adequate and effective policing in the regions; thus, this brought about the inevitable introduction of native charms on farmlands as a means of fortification of harvests against theft in Ayetoro community. The use of charm by farmers as security on farmlands is a traditional crime control mechanism that is largely based on unwritten laws which greatly influenced the lives of people, and their attitudes toward the society. This research presents a qualitative sociological study on how native charms are deployed by farmers for protection against theft. The study investigated the various types of charms that are employed as security measures among farmers in Ayetoro community and the rationale behind the use of these mechanisms as farm security. The study utilized qualitative method to gather data in the research process. Under the qualitative method, in-depth interview method was adopted to generate a robust and detailed data from the respondents. Also the data generated were analysed qualitatively using thematic content analysis and simple description which was preceded by transcription of data from the recorder. It was revealed that amidst numerous charms known, two major charms are used on farmlands as a measure of social control in Ayetoro community, Ogun state South West Nigeria. Furthermore, the result of this study showed that, the desire for safekeeping of harvest from pilferers and the heavy punishments dispense on offenders by native charms are the reasons why farmers deploy charms on their farms. In addition, findings revealed that the adoption of these charms for protection has improved yields among farmers in the community because the safety of harvest has been made possible by virtue of the presence of various charms in the farm lands. Therefore, based on the findings of this study, it is recommended that such measures should be recognized in mainstream social control mechanisms in the fight against crime in Nigeria and the rest of the world. Lastly, native charms could be installed in all social and cooperate organisation and position of authority to prevent theft of valuables and things hold with utmost importance.

Keywords: Ayetoro, farm theft, mechanism, native charms, Pilferer

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Authors: Gary Pattemore, Michael Edgar, Andrew Job, Marina Auad, Kathryn Job

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As critical commodities become more scarce, significant time and resources have been used to better understand complicated ore bodies and extract their full potential. These challenging ore bodies provide several pain points for geologists and engineers to overcome, poor handling of these issues flows downs stream to the processing plant affecting throughput rates and recovery. Many open cut mines utilise blast hole drilling to extract additional information to feed back into the modelling process. This method requires samples to be collected during or after blast hole drilling. Samples are then sent for assay with turnaround times varying from 1 to 12 days. This method is time consuming, costly, requires human exposure on the bench and collects elemental data only. To address this challenge, research has been undertaken to utilise hyperspectral imaging across a broad spectrum to scan samples, collars or take down hole measurements for minerals and moisture content and grade abundances. Automation of this process using unmanned vehicles and on-board processing reduces human in pit exposure to ensure ongoing safety. On-board processing allows data to be integrated into modelling workflows with immediacy. The preliminary results demonstrate numerous direct and indirect benefits from this new technology, including rapid and accurate grade estimates, moisture content and mineralogy. These benefits allow for faster geo modelling updates, better informed mine scheduling and improved downstream blending and processing practices. The paper presents recommendations for implementation of the technology in open cut mining environments.

Keywords: grade control, hyperspectral scanning, artificial intelligence, autonomous mining, machine learning

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