Search results for: logical framework matrix

Authors: Florian Wohlfeil, Orestis Terzidis, Louisa Hellmann

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Radical technological innovations enable companies to reach strong market positions and are thus desirable. On the other hand, the innovation process is related to significant costs and risks. Hence, the knowledge of the factors that influence success is crucial for technology driven companies. In a previous study, we have developed a conceptual framework of 25 Critical Success Factors for radical technological innovations and mapped them to four main categories: Technology, Organization, Market, and Process. We refer to it as the Technology-Organization-Market-Process (TOMP) framework. Taking the TOMP framework as a reference model, we conducted a structured and focused literature review of eleven standard books on the topic of radical technological innovation. With this approach, we aim to evaluate, expand, and clarify the set of Critical Success Factors detailed in the TOMP framework. Overall, the set of factors and their allocation to the main categories of the TOMP framework could be confirmed. However, the factor organizational home is not emphasized and discussed in most of the reviewed literature. On the other hand, an additional factor that has not been part of the TOMP framework is described to be important – strategy fit. Furthermore, the factors strategic alliances and platform strategy appear in the literature but in a different context compared to the reference model.

Keywords: Critical Success Factors, radical technological innovation, TOMP framework, innovation process

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Authors: Kyle De Freitas, Margaret Bernard

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Enabling data mining analysis among a wider audience of educators is an active area of research within the educational data mining (EDM) community. The paper proposes a framework for developing an environment that caters for educators who have little technical data mining skills as well as for more advanced users with some data mining expertise. This framework architecture was developed through the review of the strengths and weaknesses of existing models in the literature. The proposed framework provides a modular architecture for future researchers to focus on the development of specific areas within the EDM process. Finally, the paper also highlights a strategy of enabling analysis through either the use of predefined questions or a guided data mining process and highlights how the developed questions and analysis conducted can be reused and extended over time.

Keywords: educational data mining, learning management system, learning analytics, EDM framework

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Authors: Frezer Alem Kebede

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The notion of viewing ICT as merely support for the business process has shifted towards viewing ICT as a critical business enabler. As such, the need for ICT devices has increased, contributing to high electronic equipment acquisition and disposal. Hence, its use and disposal must be seen in light of environmental sustainability, i.e., in terms of green use and disposal. However, there are limited studies on green Use and Disposal framework to be used as guiding lens by organizations in developing countries. And this study endeavors to address that need taking one of the largest multinational ICT intensive company in the country. The design and development of this framework passed through several stages, initially factors affecting green use and disposal were identified after quantitative and qualitative data analysis then there were multiple brainstorming sessions for the design enhancement as participative modelling was employed. Given the difference in scope and magnitude of the challenges identified, the proposed framework approaches green use and disposal in four imperatives; strategically, tactically, operationally and through continuous improvement.

Keywords: energy efficiency, green disposal, green ICT, green use, green use and disposal framework, sustainability

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Authors: Anli Du Preez, James Bekker

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Data is currently one of the most critical and influential emerging technologies. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data are ever actually analyzed for value creation. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen’s framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application.

Keywords: Data analytics, Industrial engineering, Machine learning, Value creation

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Authors: Ahmed Tarek, Ahmed Alveed

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In the theory of computing, there are a wide variety of direct and indirect proof techniques. However, mathematical induction (MI) stands out to be one of the most powerful proof techniques for proving hypotheses, theorems, and new results. There are variations of mathematical induction-based proof techniques, which are broadly classified into three categories, such as structural induction (SI), weak induction (WI), and strong induction (SI). In this expository paper, several different variants of the mathematical induction techniques are explored, and the specific scenarios are discussed where a specific induction technique stands out to be more advantageous as compared to other induction strategies. Also, the essential difference among the variants of mathematical induction are explored. The points of separation among mathematical induction, recursion, and logical deduction are precisely analyzed, and the relationship among variations of recurrence relations, and mathematical induction are being explored. In this context, the application of recurrence relations, and mathematical inductions are considered together in a single framework for codewords over a given alphabet.

Keywords: alphabet, codeword, deduction, mathematical, induction, recurrence relation, strong induction, structural induction, weak induction

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Authors: Smita Sonker

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Various investigators have determined the degree of approximation of conjugate signals (functions) of functions belonging to different classes Lipα, Lip(α,p), Lip(ξ(t),p), W(Lr,ξ(t), (β ≥ 0)) by matrix summability means, lower triangular matrix operator, product means (i.e. (C,1)(E,1), (C,1)(E,q), (E,q)(C,1) (N,p,q)(E,1), and (E,q)(N,pn) of their conjugate trigonometric Fourier series. In this paper, we shall determine the degree of approximation of 2π-periodic function conjugate functions of f belonging to the function classes Lipα and W(Lr; ξ(t); (β ≥ 0)) by (C1.T) -means of their conjugate trigonometric Fourier series. On the other hand, we shall review above-mentioned work in the light of Lenski.

Keywords: signals, trigonometric fourier approximation, class W(L^r, \xi(t), conjugate fourier series

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Authors: Qiuyu Dai, Haochong Zhang, Xiangrong Liu

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Diagonal sparse matrix-vector multiplication is a well-studied topic in the fields of scientific computing and big data processing. However, when diagonal sparse matrices are stored in DIA format, there can be a significant number of padded zero elements and scattered points, which can lead to a degradation in the performance of the current DIA kernel. This can also lead to excessive consumption of computational and memory resources. In order to address these issues, the authors propose the DIA-Adaptive scheme and its kernel, which leverages the parallel instruction sets on MLU. The researchers analyze the effect of allocating a varying number of threads, clusters, and hardware architectures on the performance of SpMV using different formats. The experimental results indicate that the proposed DIA-Adaptive scheme performs well and offers excellent parallelism.

Keywords: adaptive method, DIA, diagonal sparse matrices, MLU, sparse matrix-vector multiplication

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Authors: Ming-Jen Huang, Chun-Fang Huang, Chiching Wei

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With the recent advance of the deep neural network, we observe new applications of NLP (natural language processing) and CV (computer vision) powered by deep neural networks for processing business documents. However, creating a real-world document processing system needs to integrate several NLP and CV tasks, rather than treating them separately. There is a need to have a unified approach for processing documents containing textual and graphical elements with rich formats, diverse layout arrangement, and distinct semantics. In this paper, a framework that fulfills this unified approach is presented. The framework includes a representation model definition for holding the information generated by various tasks and specifications defining the coordination between these tasks. The framework is a blueprint for building a system that can process documents with rich formats, styles, and multiple types of elements. The flexible and lightweight design of the framework can help build a system for diverse business scenarios, such as contract monitoring and reviewing.

Keywords: document processing, framework, formal definition, machine learning

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Authors: Laura Dembovska, Diana Bajare, Vitalijs Lusis, Genadijs Sahmenko, Aleksandrs Korjakins

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This study focused on the mechanical properties of the fibre reinforced High Performance Concrete. The most important benefits of addition of fibres to the concrete mix are the hindrance of the development of microcracks, the delay of the propagation of microcracks to macroscopic cracks and the better ductility after microcracks have been occurred. This work presents an extensive comparative experimental study on six different types of fibres (alkali resistant glass, polyvinyl alcohol fibres, polypropylene fibres and carbon fibres) with the same binding High Performance Concrete matrix. The purpose was to assess the influence of the type of fibre on the mechanical properties of Fibre Reinforced High Performance Concrete. Therefore, in this study three main objectives have been chosen: 1) analyze the structure of the bulk cementitious matrix, 2) determine the influence of fibres and distribution in the matrix on the mechanical properties of fibre reinforced High Performance Concrete and 3) characterize the microstructure of the fibre-matrix interface. Acknowledgement: This study was partially funded by European Regional Development Fund project Nr.1.1.1.1/16/A/007 “A New Concept for Sustainable and Nearly Zero-Energy Buildings” and COST Action TU1404 Conference grants project.

Keywords: high performance concrete, fibres, mechanical properties, microstructure

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Authors: Anjela Koblischka-Veneva, Michael R. Koblischka

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In this contribution, the Transmission-Kikuchi Diffraction (TKD, or sometimes called t-EBSD) is applied to bulk, melt-grown YBa₂Cu₃O₇ (YBCO) superconductors prepared by the MTMG (melt-textured melt-grown) technique and the infiltration growth (IG) technique. TEM slices required for the analysis were prepared by means of Focused Ion-Beam (FIB) milling using mechanically polished sample surfaces, which enable a proper selection of the interesting regions for investigations. The required optical transparency was reached by an additional polishing step of the resulting surfaces using FIB-Ga-ion and Ar-ion milling. The improved spatial resolution of TKD enabled the investigation of the tiny YBa₂Cu₃O₅ (Y-211) particles having a diameter of about 50-100 nm embedded within the YBCO matrix and of other added secondary phase particles. With the TKD technique, the microstructural properties of the YBCO matrix are studied in detail. It is observed that the matrix shows the effects of stress/strain, depending on the size and distribution of the embedded particles, which are important for providing additional flux pinning centers in such superconducting bulk samples. Using the Kernel Average Misorientation (KAM) maps, the strain induced in the superconducting matrix around the particles, which increases the flux pinning effectivity, can be clearly revealed. This type of analysis of the EBSD/TKD data is, therefore, also important for other material systems, where nanoparticles are embedded in a matrix.

Keywords: transmission Kikuchi diffraction, EBSD, TKD, embedded particles, superconductors YBa₂Cu₃O₇

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Authors: Malihe Aliasgari, Yousef Nejatbakhsh

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The era of Big Data and the immensity of real-life datasets compels computation tasks to be performed in a distributed fashion, where the data is dispersed among many servers that operate in parallel. However, massive parallelization leads to computational bottlenecks due to faulty servers and stragglers. Stragglers refer to a few slow or delay-prone processors that can bottleneck the entire computation because one has to wait for all the parallel nodes to finish. The problem of straggling processors, has been well studied in the context of distributed computing. Recently, it has been pointed out that, for the important case of linear functions, it is possible to improve over repetition strategies in terms of the tradeoff between performance and latency by carrying out linear precoding of the data prior to processing. The key idea is that, by employing suitable linear codes operating over fractions of the original data, a function may be completed as soon as enough number of processors, depending on the minimum distance of the code, have completed their operations. The problem of matrix-matrix multiplication in the presence of practically big sized of data sets faced with computational and memory related difficulties, which makes such operations are carried out using distributed computing platforms. In this work, we study the problem of distributed matrix-matrix multiplication W = XY under storage constraints, i.e., when each server is allowed to store a fixed fraction of each of the matrices X and Y, which is a fundamental building of many science and engineering fields such as machine learning, image and signal processing, wireless communication, optimization. Non-secure and secure matrix multiplication are studied. We want to study the setup, in which the identity of the matrix of interest should be kept private from the workers and then obtain the recovery threshold of the colluding model, that is, the number of workers that need to complete their task before the master server can recover the product W. The problem of secure and private distributed matrix multiplication W = XY which the matrix X is confidential, while matrix Y is selected in a private manner from a library of public matrices. We present the best currently known trade-off between communication load and recovery threshold. On the other words, we design an achievable PSGPD scheme for any arbitrary privacy level by trivially concatenating a robust PIR scheme for arbitrary colluding workers and private databases and the proposed SGPD code that provides a smaller computational complexity at the workers.

Keywords: coded distributed computation, private information retrieval, secret sharing, stragglers

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Authors: Slimane Souag, Amel Graa, Farid Benhamida

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In this paper we present a new method for solving the secured power flow problem by the economic dispatch using DC power flow method and Generation Shift Distribution Factor (GSDF), in this work we create a graphical interface in LabVIEW as a virtual instrument. Hence the dc power flow reduces the power flow problem to a set of linear equations, which make the iterative calculation very fast and the GSFD matrix present the effects of single and multiple generator MW change on the transmission line. The effectiveness of the method developed is identified through its application to an IEEE-14 bus test system. The calculation results show excellent performance of the proposed method, in regard to computation time and quality of results.

Keywords: electrical power system security, economic dispatch, sensitivity matrix, labview

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Authors: Vladimir Simovic, Matija Varga, Tonco Marusic

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This research paper shows matrix technology models and examples of information systems in education (in the Republic of Croatia and in the Germany) in support of business, education (when learning and teaching) and e-learning. Here we researched and described the aims and objectives of the main process in education and technology, with main matrix classes of data. In this paper, we have example of matrix technology with detailed description of processes related to specific data classes in the processes of education and an example module that is support for the process: ‘Filling in the directory and the diary of work’ and ‘evaluation’. Also, on the lower level of the processes, we researched and described all activities which take place within the lower process in education. We researched and described the characteristics and functioning of modules: ‘Fill the directory and the diary of work’ and ‘evaluation’. For the analysis of the affinity between the aforementioned processes and/or sub-process we used our application model created in Visual Basic, which was based on the algorithm for analyzing the affinity between the observed processes and/or sub-processes.

Keywords: designing, education management, information systems, matrix technology, process affinity

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Authors: Ishak Ramli, Mohamad Noorman Masrek, Muhamad Abdul Aziz Ab Gani

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Islam places restrictions and limitation to the creation and ownership of visual art. Not all forms of visual arts are permissible in Islam. However, guidance on the creation and ownership of visual arts is not made plain and clear not only to the Islamic followers but also to the art community. Given this gap, this study attempts to develop a conceptual framework that will guide artist and art collectors on what constitute to valid and acceptable through the Islamic perspective. Based on this framework, several research checklist are proposed. It is highly useful especially for the researchers who are interested to study the topic. Qualitative research is the best choice to test run the paper work to attempt all the checklist which are formed.

Keywords: contemporary visual art, Shariah, conceptual framework, Islam

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Authors: Oluwagbenga B. Fatile, Felix U. Idu, Olajide T. Sanya

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This paper reports the viability of developing Zn-27Al alloy matrix hybrid composites reinforced with alumina, graphite and fly ash (a solid waste byproduct of coal in thermal power plants). This research work was aimed at developing low cost-high performance Zn-27Al matrix composite with low density. Alumina particulates (Al2O3), graphite added with 0, 2, 3, 4, and 5 wt% fly ash were utilized to prepare 10wt% reinforcing phase with Zn-27Al alloy as matrix using two-step stir casting method. Density measurement estimated percentage porosity, tensile testing, micro hardness measurement, and optical microscopy were used to assess the performance of the composites produced. The results show that the hardness, ultimate tensile strength, and percent elongation of the hybrid composites decrease with increase in fly ash content. The maximum decrease in hardness and ultimate tensile strength of 13.72% and 15.25% respectively were observed for composite grade containing 5wt% fly ash. The percentage elongation of composite sample without fly ash is 8.9% which is comparable with that of the sample containing 2wt% fly ash with percentage elongation of 8.8%. The fracture toughness of the fly ash containing composites was, however, superior to those of composites without fly ash with 5wt% fly ash containing composite exhibiting the highest fracture toughness. The results show that fly ash can be utilized as complementary reinforcement in ZA-27 alloy matrix composite to reduce cost.

Keywords: fly ash, hybrid composite, mechanical behaviour, stir-cast

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Authors: P. Abachi, S. Karami, K. Purazrang

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The amorphous reinforcements (metallic glasses) can be considered as promising options for reinforcing light-weight aluminum and its alloys. By using the proper type of reinforcement, one can overcome to drawbacks such as interfacial de-cohesion and undesirable reactions which can be created at ceramic particle and metallic matrix interface. In this work, the Zr-based amorphous phase was produced via mechanical milling of elemental powders. Based on Miedema semi-empirical Model and diagrams for formation enthalpies and/or Gibbs free energies of Zr-Cu amorphous phase in comparison with the crystalline phase, the glass formability range was predicted. The composite was produced using the powder mixture of the aluminum and metallic glass and spark plasma sintering (SPS) at the temperature slightly above the glass transition Tg of the metallic glass particles. The selected temperature and rapid sintering route were suitable for consolidation of an aluminum matrix without crystallization of amorphous phase. To characterize amorphous phase formation, X-ray diffraction (XRD) phase analyses were performed on powder mixture after specified intervals of milling. The microstructure of the composite was studied by optical and scanning electron microscope (SEM). Uniaxial compression tests were carried out on composite specimens with the dimension of 4 mm long and a cross-section of 2 ˟ 2mm2. The micrographs indicated an appropriate reinforcement distribution in the metallic matrix. The comparison of stress–strain curves of the consolidated composite and the non-reinforced Al matrix alloy in compression showed that the enhancement of yield strength and mechanical strength are combined with an appreciable plastic strain at fracture. It can be concluded that metallic glasses (amorphous phases) are alternative reinforcement material for lightweight metal matrix composites capable of producing high strength and adequate ductility. However, this is in the expense of minor density increase.

Keywords: aluminum matrix composite, amorphous phase, mechanical alloying, spark plasma sintering

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Authors: Nevena Jakovčević Stor, Ivan Slapničar

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Any polynomial can be expressed as a characteristic polynomial of a complex symmetric arrowhead matrix. This expression is not unique. If the polynomial is real with only real distinct roots, the matrix can be chosen as real. By using accurate forward stable algorithm for computing eigen values of real symmetric arrowhead matrices we derive a forward stable algorithm for computation of roots of such polynomials in O(n^2 ) operations. The algorithm computes each root to almost full accuracy. In some cases, the algorithm invokes extended precision routines, but only in the non-iterative part. Our examples include numerically difficult problems, like the well-known Wilkinson’s polynomials. Our algorithm compares favorably to other method for polynomial root-finding, like MPSolve or Newton’s method.

Keywords: roots of polynomials, eigenvalue decomposition, arrowhead matrix, high relative accuracy

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Authors: Wan Noorul Hafilah Binti Wan Ariffin

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Dam safety management is the crucial infrastructure as dam failure has a catastrophic effect on the community. Dam safety management is the effective framework of key actions and activities for the dam owner to manage the safety of the dam for its entire life cycle. However, maintaining dam safety is a challenging task as there are changes in current dam states. These changes introduce new risks to the dam's safety, which had not been considered when the dam was designed. A new framework has to be developed to adapt to the changes in the dam risk and make the dams resilient. This study proposes a risk-based decision-making adaptation framework for dam safety management. The research focuses on climate change's impact on hydrological situations as it causes floods and damages the dam structure. The risk analysis framework is adopted to improve the dam management strategies. The proposed study encompasses four phases. To start with, measuring the effect by assessing the impact of climate change on embankment dam, the second phase is to analyze the potential embankment dam failures. The third is analyzing the different components of risks related to the dam and, finally, developing a robust decision-making framework.

Keywords: climate change, embankment dam, failure, risk-informed decision making

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Authors: Birgul Hizlar, Sibel Karakaya

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Recently, increasing attention has been given to carotenoid bioaccessibility and bioavailability in the field of nutrition research. As a consequence of their lipophilic nature and their specific localization in plant-based tissues, carotenoid bioaccessibility and bioavailability is generally quite low in raw fruits and vegetables, since carotenoids need to be released from the cellular matrix and incorporated in the lipid fraction during digestion before being absorbed. Today’s approach related to improving the bioaccessibility is to design food matrix. Recently, the newest approach, excipient food, has been introduced to improve the bioavailability of orally administered bioactive compounds. The main idea is combining food and another food (the excipient food) whose composition and/or structure is specifically designed for improving health benefits. In this study, effects of food processing, food matrix and the addition of excipient foods on the carotenoid bioaccessibility of carrots were determined. Different excipient foods (olive oil, lemon juice and whey curd) and different food matrices (grating, boiling and mashing) were used. Total carotenoid contents of the grated, boiled and mashed carrots were 57.23, 51.11 and 62.10 μg/g respectively. No significant differences among these values indicated that these treatments had no effect on the release of carotenoids from the food matrix. Contrary to, changes in the food matrix, especially mashing caused significant increase in the carotenoid bioaccessibility. Although the carotenoid bioaccessibility was 10.76% in grated carrots, this value was 18.19% in mashed carrots (p<0.05). Addition of olive oil and lemon juice as excipients into the grated carrots caused 1.23 times and 1.67 times increase in the carotenoid content and the carotenoid bioaccessibility respectively. However, addition of the excipient foods in the boiled carrot samples did not influence the release of carotenoid from the food matrix. Whereas, up to 1.9 fold increase in the carotenoid bioaccessibility was determined by the addition of the excipient foods into the boiled carrots. The bioaccessibility increased from 14.20% to 27.12% by the addition of olive oil, lemon juice and whey curd. The highest carotenoid content among mashed carrots was found in the mashed carrots incorporated with olive oil and lemon juice. This combination also caused a significant increase in the carotenoid bioaccessibility from 18.19% to 29.94% (p<0.05). When compared the results related with the effect of the treatments on the carotenoid bioaccessibility, mashed carrots containing olive oil, lemon juice and whey curd had the highest carotenoid bioaccessibility. The increase in the bioaccessibility was approximately 81% when compared to grated and mashed samples containing olive oil, lemon juice and whey curd. In conclusion, these results demonstrated that the food matrix and addition of the excipient foods had a significant effect on the carotenoid content and the carotenoid bioaccessibility.

Keywords: carrot, carotenoids, excipient foods, food matrix

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Authors: Anjela Koblischka-Veneva, Michael Koblischka

Abstract:

In this contribution, the transmission-Kikuchi diffrac-tion (TKD, or sometimes called t-EBSD) is applied to bulk, melt-grown YBa2Cu3O7 (YBCO) superconductors prepared by the MTMG (melt-textured melt-grown) technique and the infiltration (IG) growth technique. TEM slices required for the analysis were prepared by means of focused ion-beam (FIB) milling using mechanically polished sample surfaces, which enable a proper selection of the in-teresting regions for investigations. The required optical transparency was reached by an additional polishing step of the resulting surfaces using FIB-Ga-ion and Ar-ion milling. The improved spatial resolution of TKD enabled the investigation of the tiny Y2BaCuO5 (Y-211) particles having a diameter of about 50-100 nm embedded within the YBCO matrix and of other added secondary phase particles. With the TKD technique, the microstructural properties of the YBCO matrix are studied in detail. It is observed that the matrix shows effects of stress/strain, depending on the size and distribution of the embedded particles, which are important for providing additional flux pinning centers in such superconducting bulk samples. Using the Kernel average misorientation (KAM) maps, the strain induced in the superconducting matrix around the particles, which increases the flux pinning effectivity, can be clearly revealed. This type of analysis of the EBSD/TKD data is, therefore, also important for other material systems, where nanoparticles are embedded in a matrix.

Keywords: electron backscatter Diffraction, transmission Kikuchi diffraction, SEM, YBCO, microstructure, nanoparticles

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Authors: William Xiu Shun Wong, Myungsu Lim, Yoonjin Hyun, Chen Liu, Seongi Choi, Dasom Kim, Kee-Young Kwahk, Namgyu Kim

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Recently, many users have begun to frequently share their opinions on diverse issues using various social media. Therefore, numerous governments have attempted to establish or improve national policies according to the public opinions captured from various social media. In this paper, we indicate several limitations of the traditional approaches to analyze public opinion on science and technology and provide an alternative methodology to overcome these limitations. First, we distinguish between the science and technology analysis phase and the social issue analysis phase to reflect the fact that public opinion can be formed only when a certain science and technology is applied to a specific social issue. Next, we successively apply a start list and a stop list to acquire clarified and interesting results. Finally, to identify the most appropriate documents that fit with a given subject, we develop a new logical filter concept that consists of not only mere keywords but also a logical relationship among the keywords. This study then analyzes the possibilities for the practical use of the proposed methodology thorough its application to discover core issues and public opinions from 1,700,886 documents comprising SNS, blogs, news, and discussions.

Keywords: big data, social network analysis, text mining, topic modeling

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Authors: Haijie Li, Xuping Zhang

Abstract:

This paper presents a computationally efficient method for the modeling of robot manipulators with flexible links and joints. This approach combines the Discrete Time Transfer Matrix Method with the Finite Segment Method, in which the flexible links are discretized by a number of rigid segments connected by torsion springs; and the flexibility of joints are modeled by torsion springs. The proposed method avoids the global dynamics and has the advantage of modeling non-uniform manipulators. Experiments and simulations of a single-link flexible manipulator are conducted for verifying the proposed methodologies. The simulations of a three-link robot arm with links and joints flexibility are also performed.

Keywords: flexible manipulator, transfer matrix method, linearization, finite segment method

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Authors: Diana López-Soto, Soumaya Yacout, Francisco Ángel-Bello

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Although inventories are considered as stocks of money sitting on shelve, they are needed in order to secure a constant and continuous production. Therefore, companies need to have control over the amount of inventory in order to find the balance between excessive and shortage of inventory. The classification of items according to certain criteria such as the price, the usage rate and the lead time before arrival allows any company to concentrate its investment in inventory according to certain ranking or priority of items. This makes the decision making process for inventory management easier and more justifiable. The purpose of this paper is to present a new approach for the classification of new items based on the already existing criteria. This approach is called the Logical Analysis of Data (LAD). It is used in this paper to assist the process of ABC items classification based on multiple criteria. LAD is a data mining technique based on Boolean theory that is used for pattern recognition. This technique has been tested in medicine, industry, credit risk analysis, and engineering with remarkable results. An application on ABC inventory classification is presented for the first time, and the results are compared with those obtained when using the well-known AHP technique and the ANN technique. The results show that LAD presented very good classification accuracy.

Keywords: ABC multi-criteria inventory classification, inventory management, multi-class LAD model, multi-criteria classification

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Authors: O. Altuntaş, A. Güral

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The hardness-microstructure relationships of spherical cementite in bainitic matrix obtained by a different heat treatment cycles carried out to high carbon powder metallurgy (P/M) steel were investigated. For this purpose, 1.5 wt.% natural graphite powder admixed in atomized iron powders and the mixed powders were compacted under 700 MPa at room temperature and then sintered at 1150 °C under a protective argon gas atmosphere. The densities of the green and sintered samples were measured via the Archimedes method. A density of 7.4 g/cm³ was obtained after sintering and a density of 94% was achieved. The sintered specimens having primary cementite plus lamellar pearlitic structures were fully quenched from 950 ^°C temperature and then over-tempered at 705 °C temperature for 60 minutes to produce spherical-fine cementite particles in the ferritic matrix. After by this treatment, these samples annealed at 735 °C temperature for 3 minutes were austempered at 300 °C salt bath for a period of 1 to 5 hours. As a result of this process, it could be able to produced spherical cementite particle in the bainitic matrix. This microstructure was designed to improve wear and toughness of P/M steels. The microstructures were characterized and analyzed by SEM and micro and macro hardness.

Keywords: powder metallurgy steel, bainite, cementite, austempering and spheroidization heat treatment

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Authors: Thomas Chinwe Urama, Patrick Oseloka Ezepue, Peters Chimezie Nnanwa

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This paper investigates the universal financial dynamics in two dominant stock markets in Sub-Saharan Africa, through an in-depth analysis of the cross-correlation matrix of price returns in Nigerian Stock Market (NSM) and Johannesburg Stock Exchange (JSE), for the period 2009 to 2013. The strength of correlations between stocks is known to be higher in JSE than that of the NSM. Particularly important for modelling Nigerian derivatives in the future, the interactions of other stocks with the oil sector are weak, whereas the banking sector has strong positive interactions with the other sectors in the stock exchange. For the JSE, it is the oil sector and beverages that have greater sectorial correlations, instead of the banks which have the weaker correlation with other sectors in the stock exchange.

Keywords: random matrix theory, cross-correlations, emerging markets, option pricing, eigenvalues eigenvectors, inverse participation ratios and implied volatility

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Authors: Milena Nanova, Radul Shishkov, Damyan Damov, Martin Georgiev

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This research paper presents an in-depth exploration of the use of generative design in urban residential architecture, with a dual focus on aligning aesthetic values with legal and environmental constraints. The study aims to demonstrate how generative design methodologies can innovate residential building designs that are not only legally compliant and environmentally conscious but also aesthetically compelling. At the core of our research is a specially developed generative design framework tailored for urban residential settings. This framework employs computational algorithms to produce diverse design solutions, meticulously balancing aesthetic appeal with practical considerations. By integrating site-specific features, urban legal restrictions, and environmental factors, our approach generates designs that resonate with the unique character of urban landscapes while adhering to regulatory frameworks. The paper places emphasis on algorithmic implementation of the logical constraint and intricacies in residential architecture by exploring the potential of generative design to create visually engaging and contextually harmonious structures. This exploration also contains an analysis of how these designs align with legal building parameters, showcasing the potential for creative solutions within the confines of urban building regulations. Concurrently, our methodology integrates functional, economic, and environmental factors. We investigate how generative design can be utilized to optimize buildings' performance, considering them, aiming to achieve a symbiotic relationship between the built environment and its natural surroundings. Through a blend of theoretical research and practical case studies, this research highlights the multifaceted capabilities of generative design and demonstrates practical applications of our framework. Our findings illustrate the rich possibilities that arise from an algorithmic design approach in the context of a vibrant urban landscape. This study contributes an alternative perspective to residential architecture, suggesting that the future of urban development lies in embracing the complex interplay between computational design innovation, regulatory adherence, and environmental responsibility.

Keywords: generative design, computational design, parametric design, algorithmic modeling

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Authors: Rogelio Luck, Yucheng Liu

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This paper proposes the continuous-time singular value decomposition (SVD) for the impulse response function, a special kind of Green’s functions e⁻⁽ᵗ⁻ ᵀ⁾, in order to find a set of singular functions and singular values so that the convolutions of such function with the set of singular functions on a specified domain are the solutions to the inhomogeneous differential equations for those singular functions. A numerical example was illustrated to verify the proposed method. Besides the continuous-time SVD, a discrete-time SVD is also presented for the impulse response function, which is modeled using a Toeplitz matrix in the discrete system. The proposed method has broad applications in signal processing, dynamic system analysis, acoustic analysis, thermal analysis, as well as macroeconomic modeling.

Keywords: singular value decomposition, impulse response function, Green’s function , Toeplitz matrix , Hankel matrix

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Authors: D. Adel, F. Giacomini, R. Gildenhaar, G. Berger, C. Gomes, U. Linow, M. Hardt, B. Peleskae, J. Günster, A. Houshmand, M. Stiller, A. Rack, K. Ghaffar, A. Gamal, M. El Mofty, C. Knabe

Abstract:

The goal of this study was to develop 3D scaffolds from a silica containing calcium alkali orthophosphate utilizing two different fabrication processes, first a replica technique namely the Schwartzwalder Somers method (SSM), and second 3D printing, i.e. Rapid prototyping (RP). First, the mechanical and physical properties of the scaffolds (porosity, compressive strength, and solubility) was assessed and second their potential to facilitate homogenous colonization with osteogenic cells and extracellular bone matrix formation throughout the porous scaffold architecture. To this end murine and rat calavarie osteoblastic cells were dynamically seeded on both scaffold types under perfusion with concentrations of 3 million cells. The amount of cells and extracellular matrix as well as osteogenic marker expression was evaluated using hard tissue histology, immunohistochemistry, and histomorphometric analysis. Total porosities of both scaffolds were 86.9 % and 50% for SSM and RP respectively, Compressive strength values were 0.46 ± 0.2 MPa for SSM and 6.6± 0.8 MPa for RP. Regarding the cellular behavior, RP scaffolds displayed a higher cell and matrix percentage of 24.45%. Immunoscoring yielded strong osteocalcin expression of cells and matrix in RP scaffolds and a moderate expression in SSM scaffolds. 3D printed RP scaffolds displayed superior mechanical and biological properties compared to SSM. 3D printed scaffolds represent excellent candidates for bone tissue engineering.

Keywords: calcium alkali orthophosphate, extracellular matrix mineralization, osteoblast differentiation, rapid prototyping, scaffold

Procedia PDF Downloads 303

Authors: Heba M. Gobara, Ahmed A. M. El-Naggar, Rasha S. El-Sayed, Amal A. AlKahlawy

Abstract:

In this study, metal organic framework (Cr-MIL-101) and TiO₂ nanoparticles were utilized as two semiconductors for water splitting process. The coupling of both semiconductors in order to improve the photocatalytic reactivity for the hydrogen production in presence of methanol as a hole scavenger under visible light (sunlight) has been performed. The forementioned semiconductors and the collected samples after water splitting application are characterized by several techniques viz., XRD, N₂ adsorption-desorption, TEM, ED, EDX, Raman spectroscopy and the total content of carbon. The results revealed an efficient yield of H₂ production with maximum purity 99.3% with the in-situ formation of graphene oxide nanosheets and multiwalled carbon nanotubes coated over the surface of the physically mixed Cr-MIL-101–TiO₂ system. The amount of H₂ gas produced was stored when using Cr-MIL-101 catalyst individually. The obtained data in this work provides promising candidate materials for pure hydrogen production as a clean fuel acquired from the water splitting process. In addition, the in-situ production of graphene nanosheets and carbon nanotubes is counted as promising advances for the presented process.

Keywords: hydrogen production, water splitting, photocatalysts, Graphene

Procedia PDF Downloads 166

Authors: Noriyoshi Yamauchi, Etsuo Horikawa, Takunori Tsuji

Abstract:

Training by exoskeleton robot is drawing attention as a rehabilitation method for body paralysis seen in many cases, and there are many forms that assist with the myoelectric signal generated by exercise commands from the brain. Rehabilitation requires more frequent training, but it is one of the reasons that the technology is required for the identification of the myoelectric potential derivation site and attachment of the device is preventing the spread of paralysis. In this research, we focus on improving the efficiency of gait training by exoskeleton type robots, improvement of myoelectric acquisition and analysis method using active matrix sensing method, and improvement of walking rehabilitation and walking by optimization of robot control.

Keywords: active matrix sensing, brain machine interface (BMI), the central pattern generator (CPG), myoelectric signal processing, robot rehabilitation

Procedia PDF Downloads 368