Search results for: upper bound technique

Authors: Shady Gamal Aziz Shehata

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Difficulty in defining construction quality arises due to perception based on the nature and requirements of the market, the different partners themselves and the results they want. Quantitative research was used in this constructivist research. A case-based study was conducted to assess the structures of positive attitudes and expectations in the context of quality improvement. A survey based on expert opinions was analyzed among construction organizations/companies operating in the construction industry in Pakistan. The financial strength, management structure and construction experience of the construction companies formed the basis of their selection. A good concept is visible at the project level and is seen as the most valuable part of the construction project. Each quality improvement technique was expected to increase the user's profits by improving the efficiency of the construction project. The Survey is useful for construction professionals to evaluate current construction concepts and expectations for the application of quality improvement techniques in construction projects.

Keywords: correlation analysis, lean construction tools, lean construction, logistic regression analysis, risk management, safety construction quality, expectation, improvement, perception

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Authors: Agria Rhamdhan

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WhatsApp as the most popular mobile messaging app has been used as evidence in many criminal cases. As the use of mobile messages generates large amounts of data, forensic investigation faces the challenge of large data problems. The hardest part of finding this important evidence is because current practice utilizes tools and technique that require manual analysis to check all messages. That way, analyze large sets of mobile messaging data will take a lot of time and effort. Our work offers methodologies based on forensic triage to reduce large data to manageable sets resulting easier to do detailed reviews, then show the results through interactive visualization to show important term, entities and relationship through intelligent ranking using Term Frequency-Inverse Document Frequency (TF-IDF) and Latent Dirichlet Allocation (LDA) Model. By implementing this methodology, investigators can improve investigation processing time and result's accuracy.

Keywords: forensics, triage, visualization, WhatsApp

Procedia PDF Downloads 156

Authors: Jihede Haj Messaoud, Hamdi Omar, Hela Fakhfakh Ben Jemia, Chokri Yaich

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The Upper Lutetian alternating marl–limestone succession of Reineche Member was deposited over a warm shallow carbonate platform that permits Nummulites proliferation. High-resolution studies of 30 meters thick Nummulites-bearing Reineche Member, cropping out in Central Tunisia (Jebel Siouf), have been undertaken, regarding pronounced cyclical sedimentary sequences, in order to investigate the periodicity of cycles and their related orbital-scale oceanic and climatic changes. The palaeoenvironmental and palaeoclimatic data are preserved in several proxies obtainable through high-resolution sampling and laboratories measurement and analysis as magnetic susceptibility (MS) and carbonates contents in conjunction with a wireline logging tools. The time series analysis of proxies permits to establish cyclicity orders present in the studied intervals which could be linked to the orbital cycles. MS records provide high-resolution proxies for relative sea level change in Late Lutetian strata. The spectral analysis of MS fluctuations confirmed the orbital forcing by the presence of the complete suite of orbital frequencies in the precession of 23 ka, the obliquity of 41 ka, and notably the two modes of eccentricity of 100 and 405 ka. Regarding the two periodic sedimentary cycles detected by wavelet analysis of proxy fluctuations which coincide with the long-term 405 ka eccentricity cycle, the Reineche Member spanned 0,8 Myr. Wireline logging tools as gamma ray and sonic were used as a proxies to decipher cyclicity and trends in sedimentation and contribute to identifying and correlate units. There are used to constraint the highest frequency cyclicity modulated by a long term wavelength cycling apparently controlled by clay content. Interpreted as a result of variations in carbonate productivity, it has been suggested that the marl-limestone couplets, represent the sedimentary response to the orbital forcing. The calculation of cycle durations through Reineche Member, is used as a geochronometer and permit the astronomical calibration of the geologic time scale. Furthermore, MS coupled with carbonate contents, and fossil occurrences provide strong evidence for combined detrital inputs and marine surface carbonate productivity cycles. These two synchronous processes were driven by the precession index and ‘fingerprinted’ in the basic marl–limestone couplets, modulated by orbital eccentricity.

Keywords: magnetic susceptibility, cyclostratigraphy, orbital forcing, spectral analysis, Lutetian

Procedia PDF Downloads 282

Authors: Amir Doustgani

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Melt electrospinning is a safe and simple technique for the production of micro and nanofibers which can be an alternative to conventional solvent electrospinning. The effects of various melt-electrospinning parameters, including molecular weight, electric field strength, flow rate and temperature on the morphology and fiber diameter of polylactic acid were studied. It was shown that molecular weight was the predominant factor in determining the obtainable fiber diameter of the collected fibers. An orthogonal design was used to examine process parameters. Results showed that molecular weight is the most effective parameter on the average fiber diameter of melt electrospun PLA nanofibers and the flow rate has the less important impact. Mean fiber diameter increased by increasing MW and flow rate, but decreased by increasing electric field strength and temperature. MFD of optimized fibers was below 100 nm and the result of software was in good agreement with the experimental condition.

Keywords: fiber formation, processing, spinning, melt blowing

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Authors: Abderrahmen Aloulou, Younes Boujelbene

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The current paper displays a new method of extracting information content from options prices by eliminating biases caused by daily variation of contract maturity. Based on Kernel regression tool, this non-parametric technique serves to obtain a spectrum of interpolated options with constant maturity horizons from negotiated optional contracts on the S&P TSX 60 index. This method makes it plausible to compare daily risk neutral densities from which extracting time continuous indicators allows the detection traders attitudes’ evolution, such as, belief homogeneity, asymmetry and extreme Risk Perception. Our findings indicate that the applied method contribute to develop effective trading strategies and to adjust monetary policies through controlling trader’s reactions to economic and monetary news.

Keywords: risk neutral densities, kernel, constant maturity horizons, homogeneity, asymmetry and extreme risk perception

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Authors: Srinivasulu Dasaiah, Kalyan Yakkala, Gangadhar Battala, Pavan Kumar Pindi, Ramakrishna Naidu Gurijala

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Tinospora cordifolia leaves biomass used for the removal fluoride from aqueous solutions. Batch biosorption technique was applied, pH, contact time, biosorbent dose and initial fluoride concentration was studied. The Scanning Electron Microscopy (SEM) and Fourier Transform Infrared (FTIR) techniques used to study the surface characteristics and the presence of chemical functional groups on the biosorbent. Biosorption isotherm models and kinetic models were applied to understand the sorption mechanism. Results revealed that pH, contact time, biosorbent dose and initial fluoride concentration played a significant effect on fluoride removal from aqueous solutions. The developed biosorbent derived from Tinospora cordifolia leaves biomass found to be a low-cost biosorbent and could be used for the effective removal of fluoride in synthetic as well as real water samples.

Keywords: biosorption, contact time, fluoride, isotherms

Procedia PDF Downloads 164

Authors: A. Nabhan, Mohamed R. El-Sharkawy, A. Rashed

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The main aim of this paper is to dedicate the belt drive system faults like cogs missing, misalignment and belt worm using vibration analysis technique. Experimentally, the belt drive test-rig is equipped to measure vibrations signals under different operating conditions. Finite element 3D model of belt drive system is created and vibration response analyzed using commercial finite element software ABAQUS/CAE.  Root mean square (RMS) and Crest Factor will serve as indicators of average amplitude of envelope analysis signals. The vibration signals pattern obtained from the simulation model and experimental data have the same characteristics. It can be concluded that each case of the RMS is more effective in detecting the defect for acceleration response. While Crest Factor parameter has a response with the displacement and velocity of vibration signals. Also it can be noticed that the model has difficulty in completing the solution when the misalignment angle is higher than 1 degree.

Keywords: simulation model, misalignment, cogs missing, vibration analysis

Procedia PDF Downloads 276

Authors: Nadia Diyana Mohd Muhaiyuddin, Dayang Rohaya Awang Rambli

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The aim of our work is to identify whether user’s calmness can be a factor to elicit user’s spatial presence experience. Hence, a systematic mental model technique called repertory grid was selected to collect data because users can freely give their opinions in this approach. Three image-based virtual reality (IBVR) environments were created to satisfy the requirement of the repertory grid. Different virtual environments were necessary to allow users to compare and give feedback. Result was analyzed by using descriptive analysis through the SPSS software. The result revealed that ‘users feel calm’ is accepted as one of the factors that can elicit spatial presence. Users also highlighted five IBVR characteristics that could elicit spatial presence, namely, calm sound, calm content, calm color, calm story line, and the calm feeling of the user.

Keywords: spatial presence, presence, virtual reality, image-based virtual reality, human-computer interaction

Procedia PDF Downloads 273

Authors: He Lingsong, Wang Junfeng, Tan Qiong, Xu Jiang

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The paper describes efforts on reconstruction methods of engineering testing and measurement technology course by applying new techniques and applications. Firstly, flipped classroom was introduced. In-class time was used for in-depth discussions and interactions while theory concept teaching was done by self-study course outside of class. Secondly, two hands-on practices of technique applications, including the program design of MATLAB Signal Analysis and the measurement application of Arduino sensor, have been covered in class. Class was transformed from an instructor-centered teaching process into an active student-centered learning process, consisting of the pre-class massive open online course (MOOC), in-class discussion and after-class practice. The third is to change sole written homework to the research-oriented application practice assignments, so as to enhance the breadth and depth of the course.

Keywords: testing and measurement, flipped classroom, MOOC, research-oriented learning, practice-oriented learning

Procedia PDF Downloads 133

Authors: Jatinderkumar R. Saini, Nikita. R. Sonthalia, Khushbu. A. Dodiya

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Research leads to development of science and technology and hence to the betterment of humankind. Journals and conferences provide a platform to receive large number of research papers for publications and presentations before the expert and scientific community. In order to assure quality of such papers, they are also sent to reviewers for their comments. In order to maintain good ethical standards, the research papers are sent to reviewers in such a way that they do not know each other’s identity. This technique is called double-blind review process. It is called single-blind review process, if identity of any one party (generally authors) is disclosed to the other. This paper presents the techniques by which identity of author as well as reviewer could be made out even through double-blind review process. It is proposed that the characteristics and techniques presented here will help journals and conferences in assuring intentional or unintentional disclosure of identity revealing information by either party to the other.

Keywords: author, conference, double blind paper, journal, reviewer, single blind paper

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Authors: Maharjan Shree Kumar

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Climate change impacts are observed in all livelihood sectors primarily in agriculture and forestry. Multiple factors have influenced the climate vulnerabilities and adaptations in agricultural at the household level. This study focused on the factors affecting adaptation in agriculture in Madi and Deukhuri valleys of Central and Western Nepal. The systematic random sampling technique was applied to select 154 households in Madi and 150 households in Deukhuri. The main purpose of the study was to analyze the socio-economic factors that either influence or restrain the farmers’ adaptation to climate change at the household level by applying the linear probability model. Based on the analysis, it is revealed that crop diversity, education, training and total land holding (acre) were positively significant for adaptation choices the study sites. Rest of the variables were not significant though indicated positive as expected except age, occupation, ethnicity, family size, and access to credit.

Keywords: adaptation, agriculture, climate, factors, Nepal

Procedia PDF Downloads 135

Authors: Mary Ghobrial, Sahar Wefky

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Marine macroalgae have proven to be rich source of bioactive compounds with biomedical potential, not only for human but also for veterinary medicine. Emergence of microbial disease in aquaculture industries implies serious loses. Usage of commercial antibiotics for fish disease treatment produces undesirable side effects. Marine organisms are a rich source of structurally novel biologically active metabolites. Competition for space and nutrients led to the evolution of antimicrobial defense strategies in the aquatic environment. The interest in marine organisms as a potential and promising source of pharmaceutical agents has increased in the last years. Many bioactive and pharmacologically active substances have been isolated from microalgae. Compounds with antibacterial, antifungal and antiviral activities have been also detected in green, brown and red algae. Selected species of marine benthic algae belonging to the Phaeophyta and Rhodophyta, collected from different coastal areas of Alexandria (Egypt), were investigated for their antibacterial and antifungal, activities. Macroalgae samples were collected during low tide from the Alexandria Mediterranean coast. Samples were air dried under shade at room temperature. The dry algae were ground, using electric mixer grinder. They were soaked in 10 ml of each of the solvents acetone, ethanol, methanol and hexane. Antimicrobial activity was evaluated using well-cut diffusion technique In vitro screening of organic solvent extracts from the marine macroalgae Laurencia pinnatifida, Pterocladia capillaceae, Stepopodium zonale, Halopteris scoparia and Sargassum hystrix, showed specific activity in inhibiting the growth of five virulent strains of bacteria pathogenic to fish Pseudomonas fluorescens, Aeromonas hydrophila, Vibrio anguillarum, V. tandara, Escherichia coli and two fungi Aspergillus flavus and A. niger. Results showed that, acetone and ethanol extracts of all test macroalgae exhibited antibacterial activity, while acetone extract of the brown Sargassum hystrix displayed the highest antifungal activity. The extracts of seaweeds inhibited bacteria more strongly than fungi and species of the Rhodophyta showed the greatest activity against the bacteria rather than fungi tested. The gas liquid chromatography coupled with mass spectrometry detection technique allows good qualitative and quantitative analysis of the fractionated extracts with high sensitivity to the smaller amounts of components. Results indicated that, the main common component in the acetone extracts of L. pinnatifida and P. capillacea is 4-hydroxy-4-methyl2-pentanone representing 64.38 and 58.60%. Thus, the extracts derived from the red macroalgae were more efficient than those obtained from the brown macroalgae in combating bacterial pathogens rather than pathogenic fungi. The most preferred species over all was the red Laurencia pinnatifida. In conclusion, the present study provides the potential of red and brown macroalgae extracts for development of anti-pathogenic agents for use in fish aquaculture.

Keywords: bacteria, fungi, extracts, solvents

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Authors: José A. Menezes, Giordano Cabral, Bruno T. Gomes

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Choosing good features is an essential part of machine learning. Recent techniques aim to automate this process. For instance, feature learning intends to learn the transformation of raw data into a useful representation to machine learning tasks. In automatic audio classification tasks, this is interesting since the audio, usually complex information, needs to be transformed into a computationally convenient input to process. Another technique tries to generate features by searching a feature space. Genetic algorithms, for instance, have being used to generate audio features by combining or modifying them. We find this approach particularly interesting and, despite the undeniable advances of feature learning approaches, we wanted to take a step forward in the use of genetic algorithms to find audio features, combining them with more conventional methods, like PCA, and inserting search control mechanisms, such as constraints over a confusion matrix. This work presents the results obtained on particular audio classification problems.

Keywords: feature generation, feature learning, genetic algorithm, music information retrieval

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Authors: Ritesh Joshi, Kishan Fuse, Gopal Zinzala, Nishit Nirmal

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Ti-6Al-4V is a titanium alloy having high strength, low weight and corrosion resistant which is a required characteristic for a material to be used in aerospace industry. Titanium, being a hard alloy is difficult to the machine via conventional methods, so it is a call to use non-conventional processes. In present work, the effects on Ti-6Al-4V by drilling a hole of Ø 6 mm using copper (99%) electrode in Electric Discharge Machining (EDM) process is analyzed. Effect of various input parameters like peak current, pulse-on time and pulse-off time on output parameters viz material removal rate (MRR) and electrode wear rate (EWR) is studied. Multi-objective optimization technique Grey relational analysis is used for process optimization. Experiments are designed using an L9 orthogonal array. ANOVA is used for finding most contributing parameter followed by confirmation tests for validating the results. Improvement of 7.45% in gray relational grade is observed.

Keywords: ANOVA, electric discharge machining, grey relational analysis, Ti-6Al-4V

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Authors: R. Benakcha, M. Omari

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Powders of La1-xMgxAlO3 (0 ≤ x ≤ 5) oxides, with large surface areas were synthesized by sol-gel process, utilizing citric acid. Heating of a mixed solution of CA, EtOH, and nitrates of lanthanum, aluminium and magnesium at 70°C gave transparent gel without any precipitation. The formation of pure perovskite La1-xMgxAlO3, occurred when the precursor was heat-treated at 800°C for 6 h. No X-ray diffraction evidence for the presence of crystalline impurities was obtained. The La1-xMgxAlO3 powders prepared by the sol-gel method have a considerably large surface area in the range of 12.9–20 m^2.g^-1 when compared with 0.3 m^2.g^-1 for the conventional solid-state reaction of LaAlO3. The structural characteristics were examined by means of conventional techniques namely X-ray diffraction, infrared spectroscopy, thermogravimetry and differential thermal (TG-DTA) and specific surface SBET. Pore diameters and crystallite sizes are in the 8.8-11.28 nm and 25.4-30.5 nm ranges, respectively. The sol-gel method is a simple technique that has several advantages. In addition to that of not requiring high temperatures, it has the potential to synthesize many kinds of mixed oxides and obtain other materials homogeneous and large purities. It also allows formatting a variety of materials: very fine powders, fibers and films.

Keywords: aluminate, lanthan, perovskite, sol-gel

Procedia PDF Downloads 266

Authors: Michela Quadrini

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Chord diagrams occur in mathematics, from the study of RNA to knot theory. They are widely used in theory of knots and links for studying the finite type invariants, whereas in molecular biology one important motivation to study chord diagrams is to deal with the problem of RNA structure prediction. An RNA molecule is a linear polymer, referred to as the backbone, that consists of four types of nucleotides. Each nucleotide is represented by a point, whereas each chord of the diagram stands for one interaction for Watson-Crick base pairs between two nonconsecutive nucleotides. A chord diagram is an oriented circle with a set of n pairs of distinct points, considered up to orientation preserving diffeomorphisms of the circle. A linear chord diagram (LCD) is a special kind of graph obtained cutting the oriented circle of a chord diagram. It consists of a line segment, called its backbone, to which are attached a number of chords with distinct endpoints. There is a natural fattening on any linear chord diagram; the backbone lies on the real axis, while all the chords are in the upper half-plane. Each linear chord diagram has a natural genus of its associated surface. To each chord diagram and linear chord diagram, it is possible to associate the intersection graph. It consists of a graph whose vertices correspond to the chords of the diagram, whereas the chord intersections are represented by a connection between the vertices. Such intersection graph carries a lot of information about the diagram. Our goal is to define an LCD equivalence class in terms of identity of intersection graphs, from which many chord diagram invariants depend. For studying these invariants, we introduce a new representation of Linear Chord Diagrams based on a set of appropriate topological operators that permits to model LCD in terms of the relations among chords. Such set is composed of: crossing, nesting, and concatenations. The crossing operator is able to generate the whole space of linear chord diagrams, and a multiple context free grammar able to uniquely generate each LDC starting from a linear chord diagram adding a chord for each production of the grammar is defined. In other words, it allows to associate a unique algebraic term to each linear chord diagram, while the remaining operators allow to rewrite the term throughout a set of appropriate rewriting rules. Such rules define an LCD equivalence class in terms of the identity of intersection graphs. Starting from a modelled RNA molecule and the linear chord, some authors proposed a topological classification and folding. Our LCD equivalence class could contribute to the RNA folding problem leading to the definition of an algorithm that calculates the free energy of the molecule more accurately respect to the existing ones. Such LCD equivalence class could be useful to obtain a more accurate estimate of link between the crossing number and the topological genus and to study the relation among other invariants.

Keywords: chord diagrams, linear chord diagram, equivalence class, topological language

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Authors: Safia Akram

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The influence of nanofluid with different waveforms in the presence of inclined asymmetric channel on peristaltic transport of a pseudoplastic fluid is examined. The governing equations for two-dimensional and two directional flows of a pseudoplastic fluid along with nanofluid are modeled and then simplified under the assumptions of long wavelength and low Reynolds number approximation. The exact solutions for temperature and nanoparticle volume fraction are calculated. Series solution of the stream function and pressure gradient are carried out using perturbation technique. The flow quantities have been examined for various physical parameters of interest. It was found, that the magnitude value of the velocity profile decreases with an increase in volume flow rate (Q) and relaxation times (ζ) and increases in sinusoidal, multisinusoidal, trapezoidal and triangular waves. It was also observed that the size of the trapping bolus decreases with the drop of the width of the channel ‘d’ and increases with a rise of relaxation times ζ.

Keywords: nanofluid particles, peristaltic flow, pseudoplastic fluid, different waveforms, inclined asymmetric channel

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Authors: Martha Ndeley, John Ikome

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In this paper, we expand the scope of constraint-directed techniques to deal with the case of transportation schedule with capacity restrictions where the scheduling problem includes alternative activities. That is, not only does the scheduling problem consist of determining when an activity is to be executed, but also determining which set of alternative activities is to be executed at all level of transportation from input to output. Such problems encompass both alternative resource problems and alternative process plan problems. We formulate a constraint-based representation of alternative activities to model problems containing such choices. We then extend existing constraint-directed scheduling heuristic commitment techniques and propagators to reason directly about the fact that an activity does not necessarily have to exist in a final transportation schedule without being completed. Tentative results show that an algorithm using a novel texture-based heuristic commitment technique propagators achieves the best overall performance of the techniques tested.

Keywords: production, transportation, scheduling, integrated

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Authors: Ghoutia Naima Sabri, Tayeb Benouaz

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The interaction between wave and electron cyclotron movement when the electron passes through a layer of resonance at a fixed frequency results an Electron Cyclotron (EC) absorption in Tokamak plasma and dependent magnetic field. This technique is the principle of additional heating (ECRH) and the generation of non-inductive current drive (ECCD) in modern fusion devices. In this paper we are interested by the problem of EC absorption which used a microscopic description of kinetic theory treatment versus the propagation which used the cold plasma description. The power absorbed depends on the optical depth which in turn depends on coefficient of absorption and the order of the excited harmonic for O-mode or X-mode. There is another possibility of heating by dissipation of Alfven waves, based on resonance of cold plasma waves, the shear Alfven wave (SW) and the compressional Alfven wave (FW). Once the (FW) power is coupled to (SW), it stays on the magnetic surface and dissipates there, which cause the heating of bulk plasmas.

Keywords: electron cyclotron, heating, plasma, tokamak

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Authors: Xiaofei Hu, Zhiyu Cai, Weian Yao

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V-notch problem under dynamic loading condition is considered in this paper. In the time domain, the precise time domain expanding algorithm is employed, in which a self-adaptive technique is carried out to improve computing accuracy. By expanding variables in each time interval, the recursive finite element formulas are derived. In the space domain, a Symplectic Analytical Singular Element (SASE) for V-notch problem is constructed addressing the stress singularity of the notch tip. Combining with the conventional finite elements, the proposed SASE can be used to solve the dynamic stress intensity factors (DSIFs) in a simple way. Numerical results show that the proposed SASE for V-notch problem subjected to dynamic loading condition is effective and efficient.

Keywords: V-notch, dynamic stress intensity factor, finite element method, precise time domain expanding algorithm

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Authors: Jana Abu Ahmada, Zaineb Mohamed, Ilyasse Aksikas

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The linear quadratic control system of hyperbolic first order partial differential equations (PDEs) are presented. The aim of this research is to control chemical reactions. This is achieved by converting the PDEs system to ordinary differential equations (ODEs) using the method of characteristics to reduce the system to control it by using the integral reinforcement learning. The designed controller is applied to a catalytic cracking reactor. Background—Transport-Reaction systems cover a large chemical and bio-chemical processes. They are best described by nonlinear PDEs derived from mass and energy balances. As a main application to be considered in this work is the catalytic cracking reactor. Indeed, the cracking reactor is widely used to convert high-boiling, high-molecular weight hydrocarbon fractions of petroleum crude oils into more valuable gasoline, olefinic gases, and others. On the other hand, control of PDEs systems is an important and rich area of research. One of the main control techniques is feedback control. This type of control utilizes information coming from the system to correct its trajectories and drive it to a desired state. Moreover, feedback control rejects disturbances and reduces the variation effects on the plant parameters. Linear-quadratic control is a feedback control since the developed optimal input is expressed as feedback on the system state to exponentially stabilize and drive a linear plant to the steady-state while minimizing a cost criterion. The integral reinforcement learning policy iteration technique is a strong method that solves the linear quadratic regulator problem for continuous-time systems online in real time, using only partial information about the system dynamics (i.e. the drift dynamics A of the system need not be known), and without requiring measurements of the state derivative. This is, in effect, a direct (i.e. no system identification procedure is employed) adaptive control scheme for partially unknown linear systems that converges to the optimal control solution. Contribution—The goal of this research is to Develop a characteristics-based optimal controller for a class of hyperbolic PDEs and apply the developed controller to a catalytic cracking reactor model. In the first part, developing an algorithm to control a class of hyperbolic PDEs system will be investigated. The method of characteristics will be employed to convert the PDEs system into a system of ODEs. Then, the control problem will be solved along the characteristic curves. The reinforcement technique is implemented to find the state-feedback matrix. In the other half, applying the developed algorithm to the important application of a catalytic cracking reactor. The main objective is to use the inlet fraction of gas oil as a manipulated variable to drive the process state towards desired trajectories. The outcome of this challenging research would yield the potential to provide a significant technological innovation for the gas industries since the catalytic cracking reactor is one of the most important conversion processes in petroleum refineries.

Keywords: PDEs, reinforcement iteration, method of characteristics, riccati equation, cracking reactor

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Authors: Smail Boussaadi, Hassina Aliane

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With the rapid growth of scientific literature, it is becoming increasingly challenging for researchers to keep up with the latest findings in their fields. Academic, professional networks play an essential role in connecting researchers and disseminating knowledge. To improve the user experience within these networks, we need effective article recommendation systems that provide personalized content.Current recommendation systems often rely on collaborative filtering or content-based techniques. However, these methods have limitations, such as the cold start problem and difficulty in capturing semantic relationships between articles. To overcome these challenges, we propose a new approach that combines BERTopic (Bidirectional Encoder Representations from Transformers), a state-of-the-art topic modeling technique, with community detection algorithms in a academic, professional network. Experiences confirm our performance expectations by showing good relevance and objectivity in the results.

Keywords: scientific articles, community detection, academic social network, recommender systems, neural topic model

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Authors: Reza Safari, Ali Rajabzadeh Ghatari, Raheleh Hossseinzadeh Mahabadi

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In the present world, there are different pressures on firms such as competition, legislations, social etc. these pressures force the firms to follow “survival” as their primary goal and then growth. One of the main factors that helps firms to reach their goals is proper financial performance. To find out about the financial performance, a firm should monitors its financial performance. Financial performance affected by many factors. This research seeks to clear which financial performance indicators are most important according to Environmental situation of a firm and what are their priorities. To do so, environmental indicators specified as presented on OECD Key Environmental Indicators 2008 and so the financial performance indicators such as Profitability, Liquidity, Gearing, Investor ratios, and etc. At this stage, the affections questioned through questionnaires. After gaining the results, data analyzed using Promethee technique. By using decision matrixes extracted from those techniques an expert system designed. This expert system suggests the suitable financial performance indicators and their ranking by receiving the environment situation given environment indicators weight.

Keywords: environment indicators, financial performance indicators, promethee, expert system

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Authors: M. Karimpour, N. Elkhoury, L. Hitihamillage, S. Moridpour, R. Hesami

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There is a necessity among rail transportation authorities for a superior understanding of the rail track degradation overtime and the factors influencing rail degradation. They need an accurate technique to identify the time when rail tracks fail or need maintenance. In turn, this will help to increase the level of safety and comfort of the passengers and the vehicles as well as improve the cost effectiveness of maintenance activities. An accurate model can play a key role in prediction of the long-term behaviour of railroad tracks. An accurate model can decrease the cost of maintenance. In this research, the rail track degradation is predicted using an autoregressive moving average with exogenous input (ARMAX). An ARMAX has been implemented on Melbourne tram data to estimate the values for the tram track degradation. Gauge values and rail usage in Million Gross Tone (MGT) are the main parameters used in the model. The developed model can accurately predict the future status of the tram tracks.

Keywords: ARMAX, dynamic systems, MGT, prediction, rail degradation

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Authors: Xiaoxin Ye, Guoyi Tang

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The effect of electropulsing ultrasonic shock (EUS) on the surface hardening and microstructure of Ti6Al4V alloy was studied. It was found that electropulsing improved the microhardness dramatically both in the influential depth and maximum value, compared with the only ultrasonic-shocked sample. It’s indicated that refined surface layer with nanocrystalline and improved microhardness were obtained on account of surface severe plastic deformation, dynamic recrystallization (DRX) and phase change, which was implemented at relative low temperature and high strain rate/capacity due to the coupling of the thermal and athermal effects of EUS. It’s different from conventional experiments and theory. It’s discussed that the positive contributions of EPT in the thermodynamics and kinetics of microstructure and properties change were attributed to the reduction of nucleation energy barrier and acceleration of atomic diffusion. Therefore, it’s supposed that EUS is an energy-saving and high-efficiency method of surface treatment technique with the help of high-energy electropulses, which is promising in cost reduction of the surface engineering and energy management.

Keywords: titanium alloys, electropulsing, ultrasonic shock, microhardness, nanocrystalline

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Authors: Surita Maini, Sanjay Dhanka

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Machine learning (ML) involves developing algorithms and statistical models that enable computers to learn and make predictions or decisions based on data without being explicitly programmed. Because of its unlimited abilities ML is gaining popularity in medical sectors; Medical Imaging, Electronic Health Records, Genomic Data Analysis, Wearable Devices, Disease Outbreak Prediction, Disease Diagnosis, etc. In the last few decades, many researchers have tried to diagnose Breast Cancer (BC) using ML, because early detection of any disease can save millions of lives. Working in this direction, the authors have proposed a hybrid ML technique RBF SVM, to predict the BC in earlier the stage. The proposed method is implemented on the Breast Cancer UCI ML dataset with 569 instances and 32 attributes. The authors recorded performance metrics of the proposed model i.e., Accuracy 98.24%, Sensitivity 98.67%, Specificity 97.43%, F1 Score 98.67%, Precision 98.67%, and run time 0.044769 seconds. The proposed method is validated by K-Fold cross-validation.

Keywords: breast cancer, support vector classifier, machine learning, hyper parameter tunning

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Authors: Ho Jeong Jin, Chang Won Seo, Choon Sik Cho, Bong Yong Choi, Kwang Kyun Na, Sang Rok Lee

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In this paper, a radar signal processing technique using the LFM-FSK (Linear Frequency Modulation-Frequency Shift Keying) is proposed for reducing the false alarm rate based on the compressive sensing. The LFM-FSK method combines FMCW (Frequency Modulation Continuous Wave) signal with FSK (Frequency Shift Keying). This shows an advantage which can suppress the ghost phenomenon without the complicated CFAR (Constant False Alarm Rate) algorithm. Moreover, the parametric sparse algorithm applying the compressive sensing that restores signals efficiently with respect to the incomplete data samples is also integrated, leading to reducing the burden of ADC in the receiver of radars. 24 GHz FMCW signal is applied and tested in the real environment with FSK modulated data for verifying the proposed algorithm along with the compressive sensing.

Keywords: compressive sensing, LFM-FSK radar, radar signal processing, sparse algorithm

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Authors: Masood Ahmad, Ataul Aziz Ikram, Ishtiaq Wahid

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Wireless sensor network (WSN) is the interconnection of mobile wireless nodes with limited energy and memory. These networks can be deployed formany critical applications like military operations, rescue management, fire detection and so on. In flat routing structure, every node plays an equal role of sensor and router. The topology may change very frequently due to the mobile nature of nodes in WSNs. The topology maintenance may produce more overhead messages. To avoid topology maintenance overhead messages, an optimized cluster based mobile wireless sensor network using memetic algorithm is proposed in this paper. The nodes in this network are first divided into clusters. The cluster leaders then transmit data to that base station. The network is validated through extensive simulation study. The results show that the proposed technique has superior results compared to existing techniques.

Keywords: WSN, routing, cluster based, meme, memetic algorithm

Procedia PDF Downloads 465

Authors: Jing Zhang

Abstract:

To reduce the carbon footprint of mankind and become more sustainable is one of the major challenges in our era. Internet of Things (IoT) mainly resolves three problems: Things to Things (T2T), Human to Things, H2T), and Human to Human (H2H). Borrowing the classification of IoT, we can find carbon prints of industries also can be divided in these three ways. Therefore, monitoring the routes of generation and circulation of products may help calculate product carbon print. This paper does not consider any technique used by IoT itself, but the ideas of it look at the connection of products. Carbon prints are like a gene or mark of a product from raw materials to the final products, which never leave the products. The contribution of this paper is to combine the characteristics of IoT and the methodology of network science to find a way to calculate the product's carbon footprint. Life cycle assessment, LCA is a traditional and main tool to calculate the carbon print of products. LCA is a traditional but main tool, which includes three kinds.

Keywords: product carbon footprint, Internet of Things, network science, life cycle assessment

Procedia PDF Downloads 105

Authors: A. H. Birniwa, A. A. Salisu, M. Y. Yakasai, A. Sabo, K. Aujara, A. Isma’il

Abstract:

Sisal fibre was extracted from Sisal leaves by enzymatic retting method. A portion of the fibre was subjected to treatment with alkali, benzoyl chloride and silane compounds. Sisal fibre composites were fabricated using unsaturated polyester resin, by hand lay-up technique using both the treated and untreated fibre. Tensile, flexural and water absorption tests were conducted and evaluated on the composites. The results obtained were found to increase in the treated fibre compared to untreated fibre. Surface morphology of the fibre was observed using scanning electron microscopy (SEM) and the result obtained showed variation in the morphology of the treated and untreated fibre. FT-IR results showed inclusion of benzoyl and silane groups on the fibre surface. The fibre chemical modification improves its adhesion to the matrix, mechanical properties of the composites were also found to improve.

Keywords: composite, flexural strength, matrix, sisal fibre

Procedia PDF Downloads 376