Search results for: fuzzy logic based analysis

Authors: Liu Yao, B. T. Wan Maseri, Wan Mohd, B. T. Nurul Izzah, Mohd Shah, Wei Wei

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Effectively managing knowledge has become a vital weapon for businesses to survive or to succeed in the increasingly competitive market. But do they perform environmental analysis when managing knowledge? If yes, how is the level and significance? This paper established a conceptual framework covering the basic knowledge management activities (KMA) to examine their contribution towards organizational performance (OP). Environmental analysis (EA) was then investigated from both internal and external aspects, to identify its effects on that contribution. Data was collected from 400 Chinese SMEs by questionnaires. Cronbach's α and factor analysis were conducted. Regression results show that the external analysis presents higher level than internal analysis. However, the internal analysis mediates the effects of external analysis on the KMA-OP relation and plays more significant role in the relation comparing with the external analysis. Thus, firms shall improve environmental analysis especially the internal analysis to enhance their KM practices.

Keywords: knowledge management, environmental analysis, performance, mediating, small sized enterprises, medium sized enterprises

Procedia PDF Downloads 615

Authors: Alexander Dolin

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In the practice of Faith-based counseling, the clinician frequently faces multifaceted issues that come together when theological directives meet professional ethics to create a special set of dilemmas. The study narrates one working through the professional dilemmas of these Faith-based counselors, thereby looking into the tensions between the necessity of fidelity to faith and the requirements to follow the American Counseling Association Code of Ethics. Through a qualitative analysis of interviews with practitioners from various denominational backgrounds, the study has identified common ethical challenges and best practices that enable the integration of faith and ethics in practice. The findings provide insight into how faith-based counselors would reconcile a situation of conflict between religious belief and professional obligations but are striving to provide care that honors both their spiritual convictions and ethical responsibilities. This will add to existing discussions related to ethical decision-making in faith-based counseling by providing practical ways of dealing with these dilemmas in support of the counselor's professional integrity and spiritual mission.

Keywords: ethics, faith, common challenges, practical tools, counseling

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Authors: Daniel Alvarado Valencia

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Nowadays, the market offers us solutions for everything, creating the idea of an immediate availability of anything we could desire, and the Internet is the mean through which to obtain all this. The proposal of this conference is that this logic puts the subjects in a situation of self-exploitation, and considers the psyche as a productive force by configuring affection and desire from a neoliberal value perspective. It uses Tinder, starting from ethnographical data from Mexico City users, as an example for this. Tinder is an application created to get dates, have sexual encounters and find a partner. It works from the creation and management of a digital profile. It is an example of how futuristic and lonely the current era can be since we got used to interact with other people through screens and images. However, at the same time, it provides solutions to loneliness, since technology transgresses, invades and alters social practices in different ways. Tinder fits into this contemporary context, it is a concrete example of the processes of technification in which social bonds develop through certain devices offered by neoliberalism, through consumption, and where the search of love and courtship are possible through images and their consumption.

Keywords: desire, image, merchandise, neoliberalism

Procedia PDF Downloads 121

Authors: Chitra Rajagopal, Indra Deo Kumar, Ila Chauhan, Ruchi Joshi, Binoy Bhargavan

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Reliability and safety are essential for the success of mission-critical and safety-critical defense systems. Humans are part of the entire life cycle of defense systems development and deployment. The majority of industrial accidents or disasters are attributed to human errors. Therefore, considerations of human performance and human reliability are critical in all complex systems, including defense systems. Defense systems are operating from the ground, naval and aerial platforms in diverse conditions impose unique physical and psychological challenges to the human operators. Some of the safety and mission-critical defense systems with human-machine interactions are fighter planes, submarines, warships, combat vehicles, aerial and naval platforms based missiles, etc. Human roles and responsibilities are also going through a transition due to the infusion of artificial intelligence and cyber technologies. Human operators, not accustomed to such challenges, are more likely to commit errors, which may lead to accidents or loss events. In such a scenario, it is imperative to understand the human factors in defense systems for better systems performance, safety, and cost-effectiveness. A case study using Task Analysis (TA) based methodology for assessment and reduction of human errors in the Air and Missile Defense System in the context of emerging technologies were presented. Action-oriented task analysis techniques such as Hierarchical Task Analysis (HTA) and Operator Action Event Tree (OAET) along with Critical Action and Decision Event Tree (CADET) for cognitive task analysis was used. Human factors assessment based on the task analysis helps in realizing safe and reliable defense systems. These techniques helped in the identification of human errors during different phases of Air and Missile Defence operations, leading to meet the requirement of a safe, reliable and cost-effective mission.

Keywords: defence systems, reliability, risk, safety

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Authors: M. S. Ahmed, F. A. Mohammad

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The aim of this paper is to perform experimental modal analysis (EMA) of reinforced concrete (RC) square slabs. EMA is the process of determining the modal parameters (Natural Frequencies, damping factors, modal vectors) of a structure from a set of frequency response functions FRFs (curve fitting). Although experimental modal analysis (or modal testing) has grown steadily in popularity since the advent of the digital FFT spectrum analyzer in the early 1970’s, studying all members and materials using such method have not yet been well documented. Therefore, in this work, experimental tests were conducted on RC square specimens (0.6m x 0.6m with 40 mm). Experimental analysis is based on freely supported boundary condition. Moreover, impact testing as a fast and economical means of finding the modes of vibration of a structure was used during the experiments. In addition, Pico Scope 6 device and MATLAB software were used to acquire data, analyze and plot Frequency Response Function (FRF). The experimental natural frequencies which were extracted from measurements exhibit good agreement with analytical predictions. It is showed that EMA method can be usefully employed to perform the dynamic behavior of RC slabs.

Keywords: natural frequencies, mode shapes, modal analysis, RC slabs

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Authors: Irina Maria Artinescu, Costin Radu Boldea, Eduard-Ionut Matei

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The paper is a comparative study of two classical variants of parallel projection methods for solving the convex feasibility problem with their equivalents that involve variable weights in the construction of the solutions. We used a graphical representation of these methods for inpainting a convex area of an image in order to investigate their effectiveness in image reconstruction applications. We also presented a numerical analysis of the convergence of these four algorithms in terms of the average number of steps and execution time in classical CPU and, alternatively, in parallel GPU implementation.

Keywords: convex feasibility problem, convergence analysis, inpainting, parallel projection methods

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Authors: R. K. Chaurasiya, N. D. Londhe, S. Ghosh

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The study of the electrical signals produced by neural activities of human brain is called Electroencephalography. In this paper, we propose an automatic and efficient EEG signal classification approach. The proposed approach is used to classify the EEG signal into two classes: epileptic seizure or not. In the proposed approach, we start with extracting the features by applying Discrete Wavelet Transform (DWT) in order to decompose the EEG signals into sub-bands. These features, extracted from details and approximation coefficients of DWT sub-bands, are used as input to Principal Component Analysis (PCA). The classification is based on reducing the feature dimension using PCA and deriving the support-vectors using Support Vector Machine (SVM). The experimental are performed on real and standard dataset. A very high level of classification accuracy is obtained in the result of classification.

Keywords: discrete wavelet transform, electroencephalogram, pattern recognition, principal component analysis, support vector machine

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Authors: Young-Cheol Choi, Joo-Hyung Kim, Gyu-Don Moon

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This paper discusses the effect of Na2O (alkali) content, SiO2/Na2O mole ratio, and elevated temperature on the mechanical performance of fly-ash-based inorganic green geopolymer composites. Fly-ash-based geopolymers, which were manufactured with varying alkali contents (4–8 % of fly ash weight) and SiO2/Na2O mole ratios (0.6–1.4), were subjected to elevated temperatures up to 900 ºC ; the geopolymer composites and their performance were evaluated on the basis of weight loss and strength loss after temperature exposure. In addition, mineralogical changes due to the elevated temperature exposure were studied using x-ray diffraction. Investigations of microstructures and microprobe analysis were performed using mercury intrusion porosimetry. The results showed that the fly-ash-based geopolymer responded significantly to high-temperature conditions.

Keywords: fly ash, geopolymer, micro-structure, high-temperature, mechanical structural

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Authors: Nasser Salah Eldin Mohammed Salih Shebka

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Current problematic issues in AI fields are mainly due to those of knowledge representation conceptual theories, which in turn reflected on the entire scope of cognitive sciences. Knowledge representation methods and tools are driven from theoretical concepts regarding human scientific perception of the conception, nature, and process of knowledge acquisition, knowledge engineering and knowledge generation. And although, these theoretical conceptions were themselves driven from the study of the human knowledge representation process and related theories; some essential factors were overlooked or underestimated, thus causing critical methodological deficiencies in the conceptual theories of human knowledge and knowledge representation conceptions. The evaluation criteria of human cumulative knowledge from the perspectives of nature and theoretical aspects of knowledge representation conceptions are affected greatly by the very materialistic nature of cognitive sciences. This nature caused what we define as methodological deficiencies in the nature of theoretical aspects of knowledge representation concepts in AI. These methodological deficiencies are not confined to applications of knowledge representation theories throughout AI fields, but also exceeds to cover the scientific nature of cognitive sciences. The methodological deficiencies we investigated in our work are: - The Segregation between cognitive abilities in knowledge driven models.- Insufficiency of the two-value logic used to represent knowledge particularly on machine language level in relation to the problematic issues of semantics and meaning theories. - Deficient consideration of the parameters of (existence) and (time) in the structure of knowledge. The latter requires that we present a more detailed introduction of the manner in which the meanings of Existence and Time are to be considered in the structure of knowledge. This doesn’t imply that it’s easy to apply in structures of knowledge representation systems, but outlining a deficiency caused by the absence of such essential parameters, can be considered as an attempt to redefine knowledge representation conceptual approaches, or if proven impossible; constructs a perspective on the possibility of simulating human cognition on machines. Furthermore, a redirection of the aforementioned expressions is required in order to formulate the exact meaning under discussion. This redirection of meaning alters the role of Existence and time factors to the Frame Work Environment of knowledge structure; and therefore; knowledge representation conceptual theories. Findings of our work indicate the necessity to differentiate between two comparative concepts when addressing the relation between existence and time parameters, and between that of the structure of human knowledge. The topics presented throughout the paper can also be viewed as an evaluation criterion to determine AI’s capability to achieve its ultimate objectives. Ultimately, we argue some of the implications of our findings that suggests that; although scientific progress may have not reached its peak, or that human scientific evolution has reached a point where it’s not possible to discover evolutionary facts about the human Brain and detailed descriptions of how it represents knowledge, but it simply implies that; unless these methodological deficiencies are properly addressed; the future of AI’s qualitative progress remains questionable.

Keywords: cognitive sciences, knowledge representation, ontological reasoning, temporal logic

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Authors: Rawaa H. El-Bidweihy, Hisham M. Abdelsalam, Ihab A. El-Khodary

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In an era where machines run and shape our world, the need for a stable, non-ending source of energy emerges. In this study, the focus was on the solar energy in Egypt as a renewable source, the most important factors that could affect the solar energy’s market share throughout its life cycle production were analyzed and filtered, the relationships between them were derived before structuring a Bayesian network. Also, forecasted models were built for multiple factors to predict the states in Egypt by 2035, based on historical data and patterns, to be used as the nodes’ states in the network. 37 factors were found to might have an impact on the use of solar energy and then were deducted to 12 factors that were chosen to be the most effective to the solar energy’s life cycle in Egypt, based on surveying experts and data analysis, some of the factors were found to be recurring in multiple stages. The presented Bayesian network could be used later for scenario and decision analysis of using solar energy in Egypt, as a stable renewable source for generating any type of energy needed.

Keywords: ARIMA, auto correlation, Bayesian network, forecasting models, life cycle, partial correlation, renewable energy, SARIMA, solar energy

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Authors: Vish Putcha, Chandrasekhar Putcha, Siva Hari

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In the current digital era of free trading and pandemic-driven remote work culture, markets worldwide gained momentum for retail investors to trade from anywhere easily. The number of retail traders rose to 24% of the market from 15% at the pre-pandemic level. Most of them are young retail traders with high-risk tolerance compared to the previous generation of retail traders. This trend boosted the growth of subscription-based market predictors and market data vendors. Young traders are betting on these predictors, assuming one of them is correct. However, 90% of retail traders are on the losing end. This paper presents multiple indicators and attempts to derive behavioral patterns from the underlying stocks. The two major indicators that traders and investors follow are technical and fundamental. The famous investor, Warren Buffett, adheres to the “Value Investing” method that is based on a stock’s fundamental Analysis. In this paper, we present multiple indicators from various methods to understand the behavior patterns of stocks. For this research, we picked five stocks with a market capitalization of more than $200M, listed on the exchange for more than 20 years, and from different industry sectors. To study the behavioral pattern over time for these five stocks, a total of 8 indicators are chosen from fundamental, technical, and financial indicators, such as Price to Earning (P/E), Price to Book Value (P/B), Debt to Equity (D/E), Beta, Volatility, Relative Strength Index (RSI), Moving Averages and Dividend yields, followed by detailed mathematical Analysis. This is an interdisciplinary paper between various disciplines of Engineering, Accounting, and Finance. The research takes a new approach to identify clear indicators affecting stocks. Statistical Analysis of the data will be performed in terms of the probabilistic distribution, then follow and then determine the probability of the stock price going over a specific target value. The Chi-square test will be used to determine the validity of the assumed distribution. Preliminary results indicate that this approach is working well. When the complete results are presented in the final paper, they will be beneficial to the community.

Keywords: stock pattern, stock market analysis, stock predictions, trading, investing, fundamental analysis, technical analysis, quantitative trading, financial analysis, behavioral analysis

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Authors: K. N. Dinesh Babu, P. K. Gargava

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Energization of a transformer results in sudden flow of current which is an effect of core magnetization. This current will be dominated by the presence of second harmonic, which in turn is used to segregate fault and inrush current, thus guaranteeing proper operation of the relay. This additional security in the relay sometimes obstructs or delays differential protection in a specific scenario, when the 2^nd harmonic content was present during a genuine fault. This kind of scenario can result in isolation of the transformer by Buchholz and pressure release valve (PRV) protection, which is acted when fault creates more damage in transformer. Such delays involve a huge impact on the insulation failure, and chances of repairing or rectifying fault of problem at site become very dismal. Sometimes this delay can cause fire in the transformer, and this situation becomes havoc for a sub-station. Such occurrences have been observed in field also when differential relay operation was delayed by 10-15 ms by second harmonic blocking in some specific conditions. These incidences have led to the need for an alternative solution to eradicate such unwarranted delay in operation in future. Modern numerical relay, called as intelligent electronic device (IED), is embedded with advanced protection features which permit higher flexibility and better provisions for tuning of protection logic and settings. Such flexibility in transformer protection IEDs, enables incorporation of alternative methods such as dynamic switching of second harmonic feature for blocking the differential protection with additional security. The analysis and precautionary measures carried out in this case, have been simulated and discussed in this paper to ensure that similar solutions can be adopted to inhibit analogous issues in future.

Keywords: differential protection, intelligent electronic device (IED), 2nd harmonic inhibit, inrush inhibit

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Authors: Bin Liu

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Protein remote homology detection and fold recognition are two most important tasks in protein sequence analysis, which is critical for protein structure and function studies. In this study, we combined the profile-based features with various string kernels, and constructed several computational predictors for protein remote homology detection and fold recognition. Experimental results on two widely used benchmark datasets showed that these methods outperformed the competing methods, indicating that these predictors are useful computational tools for protein sequence analysis. By analyzing the discriminative features of the training models, some interesting patterns were discovered, reflecting the characteristics of protein superfamilies and folds, which are important for the researchers who are interested in finding the patterns of protein folds.

Keywords: protein remote homology detection, protein fold recognition, profile-based features, Support Vector Machines (SVMs)

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Authors: Rashmi Raghunandan, Sanjana Shankar, Rakshitha K. Bhat

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Social media contributes a vast amount of data and information about individuals to the internet. This project will greatly reduce the need for unnecessary manual analysis of large and diverse social media profiles by filtering out and combining the useful information from various social media profiles, eliminating irrelevant data. It differs from the existing social media aggregators in that it does not provide a consolidated view of various profiles. Instead, it provides consolidated INFORMATION derived from the subject’s posts and other activities. It also allows analysis over multiple profiles and analytics based on several profiles. We strive to provide a query system to provide a natural language answer to questions when a user does not wish to go through the entire profile. The information provided can be filtered according to the different use cases it is used for.

Keywords: social network, analysis, Facebook, Linkedin, git, big data

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Authors: Ranjitkumar Patil

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Age estimation has importance in forensic dentistry. Dental age estimation has emerged as an alternative to skeletal age determination. The methods based on stages of tooth formation, as appreciated on radiographs, seem to be more appropriate in the assessment of age than those based on skeletal development. The study was done to evaluate dental age in the north Indian population using Cameriere’s method. Aims/Objectives: The study was conducted to assess the dental age of North Indian children using Cameriere’s method and to compare the chronological age and dental age for validation of the Cameriere’s method in the north Indian population. A comparative study of 02-year duration on the OPG (using PLANMECA Promax 3D) data of 497 individuals with ages ranging from 5 to 15 years was done based on simple random technique ethical approval obtained from institutional ethical committee. The data was obtained based on inclusion and exclusion criteria and was analyzed by software for dental age estimation. Statistical analysis: The student’s t-test was used to compare the morphological variables of males with those of females and to compare observed age with estimated age. The regression formula was also calculated. Results: Present study was a comparative study of 497 subjects with a distribution between males and females, with their dental age assessed by using a Panoramic radiograph, following the method described by Cameriere, which is widely accepted. Statistical analysis in our study indicated that gender does not have a significant influence on age estimation. (R2= 0.787). Conclusion: This infers that Cameriere’s method can be effectively applied to the north Indian population.

Keywords: forensic, dental age, skeletal age, chronological age, Cameriere’s method

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Authors: Kaining Zhang, Lang Chen, Danyang Liu, Jianying Lu, Kun Yang, Junying Wu

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In order to solve the problem of a large amount of simulation and limited simulation scale in the first-principle molecular dynamics simulation of energetic material detonation reaction, we established an artificial intelligence model for analyzing and predicting the detonation reaction mechanism of CL-20 based on the first-principle molecular dynamics simulation of the multiscale shock technique (MSST). We employed principal component analysis to identify the dominant charge features governing molecular reactions. We adopted the K-means clustering algorithm to cluster the reaction paths and screen out the key reactions. We introduced the neural network algorithm to construct the mapping relationship between the charge characteristics of the molecular structure and the key reaction characteristics so as to establish a calculation method for predicting detonation reactions based on the charge characteristics of CL-20 and realize the rapid analysis of the reaction mechanism of energetic materials.

Keywords: energetic material detonation reaction, first-principle molecular dynamics simulation of multiscale shock technique, neural network, CL-20

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Authors: Marcelo Franzkowiak Stahlschmidt

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This paper discusses the experiments carried out based on the wire drawing process analysis and later annealing on lead furnace on a galvanizing line. Using Design of Experiments methodology, the aim of this work is to understand the occurrence of lead entrainment originating from the annealed wires in order to decrease this problem. Wire samples were collected from wire drawing machines and galvanizing line and submitted to surface roughness analysis and its implications on lead drag out based on wire speed, wire diameter, lead bath temperature, thermal capacity of the lead kettle, wire surface condition, wire roughness and wire superficial cleanliness. Proposals to decrease lead drag out were made in order to increase wire drawing machines and galvanizing line performance.

Keywords: wire drawing process, galvanizing, heat treatment, lead

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Authors: Loubna Tani, Nabih Elouzzani

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Crosstalk among interconnects and printed-circuit board (PCB) traces is a major limiting factor of signal quality in high-speed digital and communication equipments especially when fast data buses are involved. Such a bus is considered as a planar multiconductor transmission line. This paper will demonstrate how the finite difference time domain (FDTD) method provides an exact solution of the transmission-line equations to analyze the near end and the far end crosstalk. In addition, this study makes it possible to analyze the rise time effect on the near and far end voltages of the victim conductor. The paper also discusses a statistical analysis, based upon a set of several simulations. Such analysis leads to a better understanding of the phenomenon and yields useful information.

Keywords: multiconductor transmission line, crosstalk, finite difference time domain (FDTD), printed-circuit board (PCB), rise time, statistical analysis

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Authors: Javier Parra-Domínguez, Juan Manuel Corchado

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At present, public efficiency is a concept that intends to maximize return on public investment focus on minimizing the use of resources and maximizing the outputs. The concept takes into account statistical criteria drawn up according to techniques such as DEA (Data Envelopment Analysis). The purpose of the current work is to consider, more precisely, the theoretical application of CBR (Case-Based Reasoning) from economics and computer science, as a preliminary step to improving the efficiency of law enforcement agencies (public sector). With the aim of increasing the efficiency of the public sector, we have entered into a phase whose main objective is the implementation of new technologies. Our main conclusion is that the application of computer techniques, such as CBR, has become key to the efficiency of the public sector, which continues to require economic valuation based on methodologies such as DEA. As a theoretical result and conclusion, the incorporation of CBR systems will reduce the number of inputs and increase, theoretically, the number of outputs generated based on previous computer knowledge.

Keywords: case-based reasoning, knowledge, police, public efficiency

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Authors: Archil Motsonelidze, Vitaly Dvalishvili

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Existing roller compacted concrete (RCC) dams indicate that the layer-by-layer construction method gives considerable economies as compared with the conventional methods. RCC dams have also gained acceptance in the regions of high seismic activity. Earthquake resistance analysis of RCC gravity dams based on nonlinear finite element technique is presented. An elastic-plastic approach is used to describe the material of a dam while it is under static conditions (period of construction). Seismic force, as an acceleration equivalent to that produced by a real earthquake, is supposed to act when the dam is completed. The materials of the dam and foundation may be nonhomogeneous and anisotropic. The “dam-foundation” system is idealized as a plain strain problem.

Keywords: finite element method, layer-by-layer construction, RCC dams, strength analysis

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Authors: Cheng-Lin Liu, Fei Liu

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For the multi-agent systems with agent's dynamics described by high-order integrator, and usual consensus algorithm composed of the state coordination control parts is proposed. Under communication delay, consensus algorithm in asynchronously-coupled form just can make the agents achieve a stationary consensus, and sufficient consensus condition is obtained based on frequency-domain analysis. To recover the original consensus state of the high-order agents without communication delay, besides, a predictor-based consensus algorithm is constructed via multiplying the delayed neighboring agents' states by a delay-related compensation part, and sufficient consensus condition is also obtained. Simulation illustrates the correctness of the results.

Keywords: high-order dynamic agents, communication delay, consensus, predictor-based algorithm

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Authors: Bernardo C. P. Albuquerque, Darym J. F. Campos

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Increasing our ability to solve complex engineering problems is directly related to the processing capacity of computers. By means of such equipments, one is able to fast and accurately run numerical algorithms. Besides the increasing interest in numerical simulations, probabilistic approaches are also of great importance. This way, statistical tools have shown their relevance to the modelling of practical engineering problems. In general, statistical approaches to such problems consider that the random variables involved follow a normal distribution. This assumption tends to provide incorrect results when skew data is present since normal distributions are symmetric about their means. Thus, in order to visualize and quantify this aspect, 9 statistical distributions (symmetric and skew) have been considered to model a hypothetical slope stability problem. The data modeled is the friction angle of a superficial soil in Brasilia, Brazil. Despite the apparent universality, the normal distribution did not qualify as the best fit. In the present effort, data obtained in consolidated-drained triaxial tests and saturated direct shear tests have been modeled and used to analytically derive the probability density function (PDF) of the safety factor of a hypothetical slope based on Mohr-Coulomb rupture criterion. Therefore, based on this analysis, it is possible to explicitly derive the failure probability considering the friction angle as a random variable. Furthermore, it is possible to compare the stability analysis when the friction angle is modelled as a Dagum distribution (distribution that presented the best fit to the histogram) and as a Normal distribution. This comparison leads to relevant differences when analyzed in light of the risk management.

Keywords: statistical slope stability analysis, skew distributions, probability of failure, functions of random variables

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Authors: Esha Saha, Pradip Kumar Ray

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A hospital inventory comprises of a large number and great variety of items for the proper treatment and care of patients, such as pharmaceuticals, medical equipment, surgical items, etc. Improper management of these items, i.e. stockouts, may lead to delay in treatment or other fatal consequences, even death of the patient. So, generally the hospitals tend to overstock items to avoid the risk of stockout which leads to unnecessary investment of money, difficulty in storing, more expiration and wastage, etc. Thus, in such challenging environment, it is necessary for hospitals to follow an inventory policy considering the stochasticity of demand in a hospital. Statistical analysis captures the correlation of patient condition based on bed occupancy with the patient demand which changes stochastically. Due to the dependency on bed occupancy, the markov model is developed that helps to map the changes in demand of hospital inventory based on the changes in the patient condition represented by the movements of bed occupancy states (acute care state, rehabilitative state and long-care state) during the length-of-stay of patient in a hospital. An inventory policy is developed for a hospital based on the fulfillment of patient demand with the objective of minimizing the frequency and quantity of placement of orders of inventoried items. The analytical structure of the model based on probability calculation is provided to show the optimal inventory-related decisions. A case-study is illustrated in this paper for the development of hospital inventory model based on patient demand for multiple inpatient pharmaceutical items. A sensitivity analysis is conducted to investigate the impact of inventory-related parameters on the developed optimal inventory policy. Therefore, the developed model and solution approach may help the hospital managers and pharmacists in managing the hospital inventory in case of stochastic demand of inpatient pharmaceutical items.

Keywords: bed occupancy, hospital inventory, markov model, patient condition, pharmaceutical items

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Authors: Cassandra Pratt Romero, Andres Gomez de Silva Garza

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This paper describes a computational system designed to imitate human inspiration during musical composition. The system is called MIS (Musical Inspiration Simulator). The MIS system is inspired by media to which human beings are exposed daily (visual, textual, or auditory) to create new musical compositions based on the emotions detected in said media. After building the system we carried out a series of evaluations with volunteer users who used MIS to compose music based on images, texts, and audio files. The volunteers were asked to judge the harmoniousness and innovation in the system's compositions. An analysis of the results points to the difficulty of computational analysis of the characteristics of the media to which we are exposed daily, as human emotions have a subjective character. This observation will direct future improvements in the system.

Keywords: human inspiration, musical composition, musical composition by computer, theory of sensation and human perception

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Authors: Liming Chen, Baoxin Xu, Zhaoyun Ding, Bin Liu, Xianqiang Zhu

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In the era of big data, public investors are faced with more complicated information related to investment decisions than ever before. To survive in the fierce competition, it has become increasingly urgent for investors to combine multi-source knowledge and evaluate the companies’ true value efficiently. For this, a rule-based ontology reasoning method is proposed to support steel companies’ value assessment. Considering the delay in financial disclosure and based on cost-benefit analysis, this paper introduces the supply chain enterprises financial analysis and constructs the ontology model used to value the value of steel company. In addition, domain knowledge is formally expressed with the help of Web Ontology Language (OWL) language and SWRL (Semantic Web Rule Language) rules. Finally, a case study on a steel company in China proved the effectiveness of the method we proposed.

Keywords: financial ontology, steel company, supply chain, ontology reasoning

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Authors: Md. Maksudur Rahman Khan, Chee Wai Woon, Huei Ruey Ong, Vignes Rasiah, Chin Kui Cheng, Kar Min Chan, E. Baranitharan

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The present work represents a preparation of non-precious iron-based electrocatalyst (FeN) for ORR in air-cathode microbial fuel cell by pyrolysis treatment. Iron oxalate which recovered from the industrial wastewater and Phenanthroline (Phen) were used as the iron and nitrogen precursors, respectively in preparing FeN catalyst. The performance of as prepared catalyst (FeN) was investigated in a single chambered air cathode MFC in which anaerobic sludge was used as inoculum and palm oil mill effluent as substrate. The maximum open circuit potential (OCV) and the highest power density recorded were 0.543 V and 4.9 mW/m2, respectively. Physical characterization of FeN was elucidated by using Brunauner Emmett Teller (BET), X-Ray Diffraction (XRD) analysis and Field Emission Scanning Electron Microscopy (FESEM) while the electrochemical properties were characterized by cyclic voltammetry (CV) analysis. The presence of biofilm on anode surface was examined using FESEM and confirmed using Infrared Spectroscopy and Thermogravimetric Analysis. The findings of this study demonstrated that FeN is electrochemically active and further modification is needed to increase the ORR catalytic activity.

Keywords: iron based catalyst, microbial fuel cells, oxygen reduction reaction, palm oil mill effluent

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Authors: Sascha Kraus, Wolfgang Hora, Philipp Stieg, Thomas Niemand, Ferdinand Thies, Matthias Filser

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In most countries, small and medium-sized enterprises (SME) are the backbone of the economy due to their impact on job creation, innovation and wealth creation. Moreover, the ongoing globalization makes it inevitable – even for SME that traditionally focused on their domestic markets – to internationalize their business activities to realize further growth and survive in international markets. Thus, internationalization has become one of the most common growth strategies for SME and has received increasing scholarly attention over the last two decades. One the downside internationalization can be also regarded as the most complex strategy that a firm can undertake. Particularly for family firms, that are often characterized by limited financial capital, a risk-averse nature and limited growth aspirations, it could be argued that family firms are more likely to face greater challenges when taking the pathway to internationalization. Especially the triangulation of family, ownership, and management (so-called ‘familiness’) manifests in a unique behavior and decision-making process which is often characterized by the importance given to noneconomic goals and distinguishes a family firm from other businesses. Taking this into account, the concept of socio-emotional wealth (SEW) has been evolved to describe the behavior of family firms. In order to investigate how different internal and external firm characteristics shape internationalization success of family firms, we drew on a sample consisting of 297 small and medium-sized family firms from Germany, Austria, Switzerland, and Liechtenstein. Thus, we include SEW as essential family firm characteristic and added the two major intra-organizational characteristics, entrepreneurial orientation (EO), absorptive capacity (AC) as well as collaboration intensity (CI) and relational knowledge (RK) as two major external network characteristics. Based on previous research we assume that these characteristics are important to explain internationalization success of family firm SME. Regarding the data analysis, we applied a Fuzzy Set Qualitative Comparative Analysis (fsQCA), an approach that allows identifying configurations of firm characteristics, specifically used to study complex causal relationships where traditional regression techniques reach their limits. Results indicate that several combinations of these family firm characteristics can lead to international success, with no permanently required key characteristic. Instead, there are many roads to walk down for family firms to achieve internationalization success. Consequently, our data states that family owned SME are heterogeneous and internationalization is a complex and dynamic process. Results further show that network related characteristics occur in all sets, thus represent an essential element in the internationalization process of family owned SME. The contribution of our study is twofold, as we investigate different forms of international expansion for family firms and how to improve them. First, we are able to broaden the understanding of the intersection between family firm and SME internationalization with respect to major intra-organizational and network-related variables. Second, from a practical perspective, we offer family firm owners a basis for setting up internal capabilities to achieve international success.

Keywords: entrepreneurial orientation, family firm, fsQCA, internationalization, socio-emotional wealth

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Authors: Nguyen Van Loi, Le Thanh Son, Tran Trung Kien

Abstract:

The paper deals with the problem of the formation of range profiles (RPs) for an X-band coastal surveillance radar. Two popular methods, the difference operator method, and the window-based method, are reviewed and analyzed via two tests with different datasets. The test results show that although the original window-based method achieves a better performance than the difference operator method, it has three main drawbacks that are the use of 3 or 4 peaks of an RP for creating the windows, the extension of the window size using the power sum of three adjacent cells in the left and the right sides of the windows and the same threshold applied for all types of vessels to finish the formation process of RPs. These drawbacks lead to inaccurate RPs due to the low signal-to-clutter ratio. Therefore, some suggestions are proposed to improve the original window-based method.

Keywords: range profile, difference operator method, window-based method, automatic target recognition

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Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

Abstract:

The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm

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Authors: Shao Qi

Abstract:

The article uses the CiteSpace knowledge graph analysis tool to sort and visualize the journal literature on urban plants and habitats in the Web of Science and China National Knowledge Infrastructure databases. Based on a comprehensive interpretation of the visualization results of various data sources and the description of the intrinsic relationship between high-frequency keywords using knowledge mapping, the research hotspots, processes and evolution trends in this field are analyzed. Relevant case studies are also conducted for the hotspot contents to explore the means of landscape intervention and synthesize the understanding of research theories. The results show that (1) from 1999 to 2022, the research direction of urban plants and habitats gradually changed from focusing on plant and animal extinction and biological invasion to the field of human urban habitat creation, ecological restoration, and ecosystem services. (2) The results of keyword emergence and keyword growth trend analysis show that habitat creation research has shown a rapid and stable growth trend since 2017, and ecological restoration has gained long-term sustained attention since 2004. The hotspots of future research on urban plants and habitats in China may focus on habitat creation and ecological restoration.

Keywords: research trends, visual analysis, habitat creation, ecological restoration

Procedia PDF Downloads 61