Search results for: optical time domain reflectometer (OTDR)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7627

Search results for: optical time domain reflectometer (OTDR)

5947 Seismic Analysis of Structurally Hybrid Wind Mill Tower

Authors: Atul K. Desai, Hemal J. Shah

Abstract:

The tall windmill towers are designed as monopole tower or lattice tower. In the present research, a 125-meter high hybrid tower which is a combination of lattice and monopole type is proposed. The response of hybrid tower is compared with conventional monopole tower. The towers were analyzed in finite element method software considering nonlinear seismic time history load. The synthetic seismic time history for different soil is derived using the SeismoARTIF software. From the present research, it is concluded that, in the hybrid tower, we are not getting resonance condition. The base shear is less in hybrid tower compared to monopole tower for different soil conditions.

Keywords: Dynamic analysis, hybrid wind mill tower, resonance condition, synthetic time history.

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5946 Biosynthesis of Titanium Dioxide Nanoparticles and Their Antibacterial Property

Authors: Prachi Singh

Abstract:

This paper presents a low-cost, eco-friendly and reproducible microbe mediated biosynthesis of TiO2 nanoparticles. TiO2 nanoparticles synthesized using the bacterium, Bacillus subtilis, from titanium as a precursor, were confirmed by TEM analysis. The morphological characteristics state spherical shape, with the size of individual or aggregate nanoparticles, around 30-40 nm. Microbial resistance represents a challenge for the scientific community to develop new bioactive compounds. Here, the antibacterial effect of TiO2 nanoparticles on Escherichia coli was investigated, which was confirmed by CFU (Colony-forming unit). Further, growth curve study of E. coli Hb101 in the presence and absence of TiO2 nanoparticles was done. Optical density decrease was observed with the increase in the concentration of TiO2. It could be attributed to the inactivation of cellular enzymes and DNA by binding to electron-donating groups such as carboxylates, amides, indoles, hydroxyls, thiols, etc. which cause little pores in bacterial cell walls, leading to increased permeability and cell death. This justifies that TiO2 nanoparticles have efficient antibacterial effect and have potential to be used as an antibacterial agent for different purposes.

Keywords: Antibacterial effect, CFU, Escherichia coli Hb101, growth curve, TEM, TiO2 nanoparticle, toxicity, UV-Vis.

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5945 Coding based Synchronization Algorithm for Secondary Synchronization Channel in WCDMA

Authors: Deng Liao, Dongyu Qiu, Ahmed K. Elhakeem

Abstract:

A new code synchronization algorithm is proposed in this paper for the secondary cell-search stage in wideband CDMA systems. Rather than using the Cyclically Permutable (CP) code in the Secondary Synchronization Channel (S-SCH) to simultaneously determine the frame boundary and scrambling code group, the new synchronization algorithm implements the same function with less system complexity and less Mean Acquisition Time (MAT). The Secondary Synchronization Code (SSC) is redesigned by splitting into two sub-sequences. We treat the information of scrambling code group as data bits and use simple time diversity BCH coding for further reliability. It avoids involved and time-costly Reed-Solomon (RS) code computations and comparisons. Analysis and simulation results show that the Synchronization Error Rate (SER) yielded by the new algorithm in Rayleigh fading channels is close to that of the conventional algorithm in the standard. This new synchronization algorithm reduces system complexities, shortens the average cell-search time and can be implemented in the slot-based cell-search pipeline. By taking antenna diversity and pipelining correlation processes, the new algorithm also shows its flexible application in multiple antenna systems.

Keywords: WCDMA cell-search, synchronization algorithm, secondary synchronization channel, antenna diversity.

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5944 Physical Activity and Cognitive Functioning Relationship in Children

Authors: Comfort Mokgothu

Abstract:

This study investigated the relation between processing information and fitness level of active (fit) and sedentary (unfit) children drawn from rural and urban areas in Botswana. It was hypothesized that fit children would display faster simple reaction time (SRT), choice reaction times (CRT) and movement times (SMT). 60, third grade children (7.0 – 9.0 years) were initially selected and based upon fitness testing, 45 participated in the study (15 each of fit urban, unfit urban, fit rural). All children completed anthropometric measures, skinfold testing and submaximal cycle ergometer testing. The cognitive testing included SRT, CRT, SMT and Choice Movement Time (CMT) and memory sequence length. Results indicated that the rural fit group exhibited faster SMT than the urban fit and unfit groups. For CRT, both fit groups were faster than the unfit group. Collectively, the study shows that the relationship that exists between physical fitness and cognitive function amongst the elderly can tentatively be extended to the pediatric population. Physical fitness could be a factor in the speed at which we process information, including decision making, even in children.

Keywords: Decision making, fitness, information processing, reaction time, cognition movement time.

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5943 Bias Optimization of Mach-Zehnder Modulator Considering RF Gain on OFDM Radio-Over-Fiber System

Authors: Ghazi Al Sukkar, Yazid Khattabi, Shifen Zhong

Abstract:

Most of the recent wireless LANs, broadband access networks, and digital broadcasting use Orthogonal Frequency Division Multiplexing techniques. In addition, the increasing demand of Data and Internet makes fiber optics an important technology, as fiber optics has many characteristics that make it the best solution for transferring huge frames of Data from a point to another. Radio over fiber is the place where high quality RF is converted to optical signals over single mode fiber. Optimum values for the bias level and the switching voltage for Mach-Zehnder modulator are important for the performance of radio over fiber links. In this paper, we propose a method to optimize the two parameters simultaneously; the bias and the switching voltage point of the external modulator of a radio over fiber system considering RF gain. Simulation results show the optimum gain value under these two parameters.

Keywords: OFDM, Mach Zehnder Bias Voltage, switching voltage, radio-over-fiber, RF gain.

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5942 Application of a Time-Frequency-Based Blind Source Separation to an Instantaneous Mixture of Secondary Radar Sources

Authors: M. Tria, M. Benidir, E. Chaumette

Abstract:

In Secondary Surveillance Radar (SSR) systems, it is more difficult to locate and recognise aircrafts in the neighbourhood of civil airports since aerial traffic becomes greater. Here, we propose to apply a recent Blind Source Separation (BSS) algorithm based on Time-Frequency Analysis, in order to separate messages sent by different aircrafts and falling in the same radar beam in reception. The above source separation method involves joint-diagonalization of a set of smoothed version of spatial Wigner-Ville distributions. The technique makes use of the difference in the t-f signatures of the nonstationary sources to be separated. Consequently, as the SSR sources emit different messages at different frequencies, the above fitted to this new application. We applied the technique in simulation to separate SSR replies. Results are provided at the end of the paper.

Keywords: Blind Source Separation, Time-Frequency Analysis, Secondary Radar

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5941 Investigating the Vehicle-Bicyclists Conflicts Using LIDAR Sensor Technology at Signalized Intersections

Authors: Alireza Ansariyar, Mansoureh Jeihani

Abstract:

Light Detection and Ranging (LiDAR) sensors is capable of recording traffic data including the number of passing vehicles and bicyclists, the speed of vehicles and bicyclists, and the number of conflicts among both road users. In order to collect real-time traffic data and investigate the safety of different road users, a LiDAR sensor was installed at Cold Spring Ln – Hillen Rd intersection in Baltimore city. The frequency and severity of collected real-time conflicts were analyzed and the results highlighted that 122 conflicts were recorded over a 10-month time interval from May 2022 to February 2023. By employing an image-processing algorithm, a safety Measure of Effectiveness (MOE) aims to identify critical zones for bicyclists upon entering each respective zone at the signalized intersection. Considering the trajectory of conflicts, the results of analysis demonstrated that conflicts in the northern approach (zone N) are more frequent and severe. Additionally, sunny weather is more likely to cause severe vehicle-bike conflicts.

Keywords: LiDAR sensor, Post Encroachment Time threshold, vehicle-bike conflicts, measure of effectiveness, weather condition.

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5940 Arrival and Departure Scheduling at Hub Airports Considering Airlines Level

Authors: A. Nourmohammadzadeh, R. Tavakkoli- Moghaddam

Abstract:

As the air traffic increases at a hub airport, some flights cannot land or depart at their preferred target time. This event happens because the airport runways become occupied to near their capacity. It results in extra costs for both passengers and airlines because of the loss of connecting flights or more waiting, more fuel consumption, rescheduling crew members, etc. Hence, devising an appropriate scheduling method that determines a suitable runway and time for each flight in order to efficiently use the hub capacity and minimize the related costs is of great importance. In this paper, we present a mixed-integer zero-one model for scheduling a set of mixed landing and departing flights (despite of most previous studies considered only landings). According to the fact that the flight cost is strongly affected by the level of airline, we consider different airline categories in our model. This model presents a single objective minimizing the total sum of three terms, namely 1) the weighted deviation from targets, 2) the scheduled time of the last flight (i.e., makespan), and 3) the unbalancing the workload on runways. We solve 10 simulated instances of different sizes up to 30 flights and 4 runways. Optimal solutions are obtained in a reasonable time, which are satisfactory in comparison with the traditional rule, namely First- Come-First-Serve (FCFS) that is far apart from optimality in most cases.

Keywords: Arrival and departure scheduling, Airline level, Mixed-integer model

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5939 An Ontology for Investment in Chinese Steel Company

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

Abstract:

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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5938 Analysis of Temperature Change under Global Warming Impact using Empirical Mode Decomposition

Authors: Md. Khademul Islam Molla, Akimasa Sumi, M. Sayedur Rahman

Abstract:

The empirical mode decomposition (EMD) represents any time series into a finite set of basis functions. The bases are termed as intrinsic mode functions (IMFs) which are mutually orthogonal containing minimum amount of cross-information. The EMD successively extracts the IMFs with the highest local frequencies in a recursive way, which yields effectively a set low-pass filters based entirely on the properties exhibited by the data. In this paper, EMD is applied to explore the properties of the multi-year air temperature and to observe its effects on climate change under global warming. This method decomposes the original time-series into intrinsic time scale. It is capable of analyzing nonlinear, non-stationary climatic time series that cause problems to many linear statistical methods and their users. The analysis results show that the mode of EMD presents seasonal variability. The most of the IMFs have normal distribution and the energy density distribution of the IMFs satisfies Chi-square distribution. The IMFs are more effective in isolating physical processes of various time-scales and also statistically significant. The analysis results also show that the EMD method provides a good job to find many characteristics on inter annual climate. The results suggest that climate fluctuations of every single element such as temperature are the results of variations in the global atmospheric circulation.

Keywords: Empirical mode decomposition, instantaneous frequency, Hilbert spectrum, Chi-square distribution, anthropogenic impact.

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5937 A Meta-Heuristic Algorithm for Set Covering Problem Based on Gravity

Authors: S. Raja Balachandar, K. Kannan

Abstract:

A new Meta heuristic approach called "Randomized gravitational emulation search algorithm (RGES)" for solving large size set covering problems has been designed. This algorithm is found upon introducing randomization concept along with the two of the four primary parameters -velocity- and -gravity- in physics. A new heuristic operator is introduced in the domain of RGES to maintain feasibility specifically for the set covering problem to yield best solutions. The performance of this algorithm has been evaluated on a large set of benchmark problems from OR-library. Computational results showed that the randomized gravitational emulation search algorithm - based heuristic is capable of producing high quality solutions. The performance of this heuristic when compared with other existing heuristic algorithms is found to be excellent in terms of solution quality.

Keywords: Set covering problem, velocity, gravitational force, Newton's law, meta heuristic, combinatorial optimization.

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5936 Concept Abduction in Description Logics with Cardinality Restrictions

Authors: Viet-Hoang Vu, Nhan Le-Thanh

Abstract:

Recently the usefulness of Concept Abduction, a novel non-monotonic inference service for Description Logics (DLs), has been argued in the context of ontology-based applications such as semantic matchmaking and resource retrieval. Based on tableau calculus, a method has been proposed to realize this reasoning task in ALN, a description logic that supports simple cardinality restrictions as well as other basic constructors. However, in many ontology-based systems, the representation of ontology would require expressive formalisms for capturing domain-specific constraints, this language is not sufficient. In order to increase the applicability of the abductive reasoning method in such contexts, we would like to present in the scope of this paper an extension of the tableaux-based algorithm for dealing with concepts represented inALCQ, the description logic that extends ALN with full concept negation and quantified number restrictions.

Keywords: Abductive reasoning, description logics, semantic matchmaking, non-monotonic inference, tableaux-based method.

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5935 Denitrification of Wastewater Containing High Nitrate Using a Bioreactor System Packed by Microbial Cellulose

Authors: H. Godini, A. Rezaee, A. Jafari, S. H. Mirhousaini

Abstract:

A Laboratory-scale packed bed reactor with microbial cellulose as the biofilm carrier was used to investigate the denitrification of high-strength nitrate wastewater with specific emphasis on the effect the nitrogen loading rate and hydraulic retention time. Ethanol was added as a carbon source for denitrification. As a result of this investigation, it was found that up to 500 mg/l feed nitrate concentration the present system is able to produce an effluent with nitrate content below 10 ppm at 3 h hydraulic retention time. The highest observed denitrification rate was 4.57 kg NO3-N/ (m3 .d) at a nitrate load of 5.64 kg NO3- N/(m3 .d), and removal efficiencies higher than 90% were obtained for loads up to 4.2 kg NO3-N/(m3 .d). A mass relation between COD consumed and NO3-N removed around 2.82 was observed. This continuous-flow bioreactor proved an efficient denitrification system with a relatively low retention time.

Keywords: Biological nitrate removal, Denitrification, Microbial cellulose, Packed-bed reactor.

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5934 Conceptualizing the Knowledge to Manage and Utilize Data Assets in the Context of Digitization: Case Studies of Multinational Industrial Enterprises

Authors: Martin Böhmer, Agatha Dabrowski, Boris Otto

Abstract:

The trend of digitization significantly changes the role of data for enterprises. Data turn from an enabler to an intangible organizational asset that requires management and qualifies as a tradeable good. The idea of a networked economy has gained momentum in the data domain as collaborative approaches for data management emerge. Traditional organizational knowledge consequently needs to be extended by comprehensive knowledge about data. The knowledge about data is vital for organizations to ensure that data quality requirements are met and data can be effectively utilized and sovereignly governed. As this specific knowledge has been paid little attention to so far by academics, the aim of the research presented in this paper is to conceptualize it by proposing a “data knowledge model”. Relevant model entities have been identified based on a design science research (DSR) approach that iteratively integrates insights of various industry case studies and literature research.

Keywords: Data management, digitization, Industry 4.0, knowledge engineering, metamodel.

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5933 Real-Time Hand Tracking and Gesture Recognition System Using Neural Networks

Authors: Tin Hninn Hninn Maung

Abstract:

This paper introduces a hand gesture recognition system to recognize real time gesture in unstrained environments. Efforts should be made to adapt computers to our natural means of communication: Speech and body language. A simple and fast algorithm using orientation histograms will be developed. It will recognize a subset of MAL static hand gestures. A pattern recognition system will be using a transforrn that converts an image into a feature vector, which will be compared with the feature vectors of a training set of gestures. The final system will be Perceptron implementation in MATLAB. This paper includes experiments of 33 hand postures and discusses the results. Experiments shows that the system can achieve a 90% recognition average rate and is suitable for real time applications.

Keywords: Hand gesture recognition, Orientation Histogram, Myanmar Alphabet Language, Perceptronnetwork, MATLAB.

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5932 A Modified Decoupled Semi-Analytical Approach Based On SBFEM for Solving 2D Elastodynamic Problems

Authors: M. Fakharian, M. I. Khodakarami

Abstract:

In this paper, a new trend for improvement in semianalytical method based on scale boundaries in order to solve the 2D elastodynamic problems is provided. In this regard, only the boundaries of the problem domain discretization are by specific subparametric elements. Mapping functions are uses as a class of higherorder Lagrange polynomials, special shape functions, Gauss-Lobatto- Legendre numerical integration, and the integral form of the weighted residual method, the matrix is diagonal coefficients in the equations of elastodynamic issues. Differences between study conducted and prior research in this paper is in geometry production procedure of the interpolation function and integration of the different is selected. Validity and accuracy of the present method are fully demonstrated through two benchmark problems which are successfully modeled using a few numbers of DOFs. The numerical results agree very well with the analytical solutions and the results from other numerical methods.

Keywords: 2D Elastodynamic Problems, Lagrange Polynomials, G-L-Lquadrature, Decoupled SBFEM.

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5931 Failure Analysis of a Medium Duty Vehicle Leaf Spring

Authors: Gül Çevik

Abstract:

This paper summarizes the work conducted to assess the root cause of the failure of a medium commercial vehicle leaf spring failed in service. Macro- and micro-fractographic analyses by scanning electron microscope as well as material verification tests were conducted in order to understand the failure mechanisms and root cause of the failure. Findings from the fractographic analyses indicated that failure mechanism is fatigue. Crack initiation was identified to have occurred from a point on the top surface near to the front face and to the left side. Two other crack initiation points were also observed, however, these cracks did not propagate. The propagation mode of the fatigue crack revealed that the cyclic loads resulting in crack initiation and propagation were unidirectional bending. Fractographic analyses have also showed that the root cause of the fatigue crack initiation and propagation was loading the part above design stress. Material properties of the part were also verified by chemical composition analysis, microstructural analysis by optical microscopy and hardness tests.

Keywords: Leaf spring, failure analysis, fatigue, fractography.

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5930 Multi-Objective Multi-Mode Resource-Constrained Project Scheduling Problem by Preemptive Fuzzy Goal Programming

Authors: Phruksaphanrat B.

Abstract:

This research proposes a preemptive fuzzy goal programming model for multi-objective multi-mode resource constrained project scheduling problem. The objectives of the problem are minimization of the total time and the total cost of the project. Objective in a multi-mode resource-constrained project scheduling problem is often a minimization of makespan. However, both time and cost should be considered at the same time with different level of important priorities. Moreover, all elements of cost functions in a project are not included in the conventional cost objective function. Incomplete total project cost causes an error in finding the project scheduling time. In this research, preemptive fuzzy goal programming is presented to solve the multi-objective multi-mode resource constrained project scheduling problem. It can find the compromise solution of the problem. Moreover, it is also flexible in adjusting to find a variety of alternative solutions. 

Keywords: Multi-mode resource constrained project scheduling problem, Fuzzy set, Goal programming, Preemptive fuzzy goal programming.

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5929 Eye Tracking: Biometric Evaluations of Instructional Materials for Improved Learning

Authors: Janet Holland

Abstract:

Eye tracking is a great way to triangulate multiple data sources for deeper, more complete knowledge of how instructional materials are really being used and emotional connections made. Using sensor based biometrics provides a detailed local analysis in real time expanding our ability to collect science based data for a more comprehensive level of understanding, not previously possible, for teaching and learning. The knowledge gained will be used to make future improvements to instructional materials, tools, and interactions. The literature has been examined and a preliminary pilot test was implemented to develop a methodology for research in Instructional Design and Technology. Eye tracking now offers the addition of objective metrics obtained from eye tracking and other biometric data collection with analysis for a fresh perspective.

Keywords: Area of interest, eye tracking, biometrics, fixation, fixation count, fixation sequence, fixation time, gaze points, heat map, saccades, time to first fixation.

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5928 Implementation of Neural Network Based Electricity Load Forecasting

Authors: Myint Myint Yi, Khin Sandar Linn, Marlar Kyaw

Abstract:

This paper proposed a novel model for short term load forecast (STLF) in the electricity market. The prior electricity demand data are treated as time series. The model is composed of several neural networks whose data are processed using a wavelet technique. The model is created in the form of a simulation program written with MATLAB. The load data are treated as time series data. They are decomposed into several wavelet coefficient series using the wavelet transform technique known as Non-decimated Wavelet Transform (NWT). The reason for using this technique is the belief in the possibility of extracting hidden patterns from the time series data. The wavelet coefficient series are used to train the neural networks (NNs) and used as the inputs to the NNs for electricity load prediction. The Scale Conjugate Gradient (SCG) algorithm is used as the learning algorithm for the NNs. To get the final forecast data, the outputs from the NNs are recombined using the same wavelet technique. The model was evaluated with the electricity load data of Electronic Engineering Department in Mandalay Technological University in Myanmar. The simulation results showed that the model was capable of producing a reasonable forecasting accuracy in STLF.

Keywords: Neural network, Load forecast, Time series, wavelettransform.

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5927 Retrieval Augmented Generation against the Machine: Merging Human Cyber Security Expertise with Generative AI

Authors: Brennan Lodge

Abstract:

Amidst a complex regulatory landscape, Retrieval Augmented Generation (RAG) emerges as a transformative tool for Governance Risk and Compliance (GRC) officers. This paper details the application of RAG in synthesizing Large Language Models (LLMs) with external knowledge bases, offering GRC professionals an advanced means to adapt to rapid changes in compliance requirements. While the development for standalone LLMs is exciting, such models do have their downsides. LLMs cannot easily expand or revise their memory, and they cannot straightforwardly provide insight into their predictions, and may produce “hallucinations.” Leveraging a pre-trained seq2seq transformer and a dense vector index of domain-specific data, this approach integrates real-time data retrieval into the generative process, enabling gap analysis and the dynamic generation of compliance and risk management content. We delve into the mechanics of RAG, focusing on its dual structure that pairs parametric knowledge contained within the transformer model with non-parametric data extracted from an updatable corpus. This hybrid model enhances decision-making through context-rich insights, drawing from the most current and relevant information, thereby enabling GRC officers to maintain a proactive compliance stance. Our methodology aligns with the latest advances in neural network fine-tuning, providing a granular, token-level application of retrieved information to inform and generate compliance narratives. By employing RAG, we exhibit a scalable solution that can adapt to novel regulatory challenges and cybersecurity threats, offering GRC officers a robust, predictive tool that augments their expertise. The granular application of RAG’s dual structure not only improves compliance and risk management protocols but also informs the development of compliance narratives with pinpoint accuracy. It underscores AI’s emerging role in strategic risk mitigation and proactive policy formation, positioning GRC officers to anticipate and navigate the complexities of regulatory evolution confidently.

Keywords: Retrieval Augmented Generation, Governance Risk and Compliance, Cybersecurity, AI-driven Compliance, Risk Management, Generative AI.

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5926 Power Distance and Knowledge Management from a Post-Taylorist Perspective

Authors: John Walton, Vishal Parikh

Abstract:

Contact centres have been exemplars of scientific management in the discipline of operations management for more than a decade now. With the movement of industries from a resource based economy to knowledge based economy businesses have started to realize the customer eccentricity being the key to sustainability amidst high velocity of the market. However, as technologies have converged and advanced, so have the contact centres. Contact Centres have redirected the supply chains and the concept of retailing is highly diminished due to over exaggeration of cost reduction strategies. In conditions of high environmental velocity together with services featuring considerable information intensity contact centres will require up to date and enlightened agents to satisfy the demands placed upon them by those requesting their services. In this paper we examine salient factors such as Power Distance, Knowledge structures and the dynamics of job specialisation and enlargement to suggest critical success factors in the domain of contact centres.

Keywords: Post Taylorism, Knowledge Management, Power Distance, Organisational Learning

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5925 Simulation of a Sustainable Cement Supply Chain; Proposal Model Review

Authors: Tarek Elhasia, Bernd Noche, Lima Zhao

Abstract:

In recent years, sustainable supply chain management (SSCM) has been widely researched in academic domain. However, due to the traditional operational role and the complexity of supply chain management in the cement industry, a relatively small amount of research has been conducted on cement supply chain simulation integrated with sustainability criteria. This paper analyses the cement supply chain operations using the Push-Pull supply chain frameworks, the Life Cycle Assessment (LCA) methodology; and proposal integration approach, proposes three supply chain scenarios based on Make-To-Stock (MTS), Pack-To-Order (PTO) and Grind- To-Order (GTO) strategies. A Discrete-Event Simulation (DES) model of SSCM is constructed using Arena software to implement the three-target scenarios. We conclude with the simulation results that (GTO) is the optimal supply chain strategy that demonstrates the best economic, ecological and social performance in the cement industry.

Keywords: Cement industry, simulation, supply chain management (SCM), sustainability.

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5924 Segmentation and Recognition of Handwritten Numeric Chains

Authors: Salim Ouchtati, Bedda Mouldi, Abderrazak Lachouri

Abstract:

In this paper we present an off line system for the recognition of the handwritten numeric chains. Our work is divided in two big parts. The first part is the realization of a recognition system of the isolated handwritten digits. In this case the study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the digits by several methods: the distribution sequence, the Barr features and the centred moments of the different projections and profiles. The second part is the extension of our system for the reading of the handwritten numeric chains constituted of a variable number of digits. The vertical projection is used to segment the numeric chain at isolated digits and every digit (or segment) will be presented separately to the entry of the system achieved in the first part (recognition system of the isolated handwritten digits). The result of the recognition of the numeric chain will be displayed at the exit of the global system.

Keywords: Optical Characters Recognition, Neural networks, Barr features, Image processing, Pattern Recognition, Featuresextraction.

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5923 Experimental Investigation of the Transient Cooling Characteristics of an Industrial Glass Tempering Unit

Authors: Hilmi Yazici, Mehmet Akcay, Mustafa Golcu, Mehmet F. Koseoglu, Yakup Sekmen

Abstract:

Energy consumption rate during the cooling process of industrial glass tempering process is considerably high. In this experimental study the effect of dimensionless jet to jet distance (S/D) and jet to plate distance (H/D) on the cooling time have been investigated. In the experiments 4 mm thick glass samples have been used. Cooling unit consists of 16 mutually placed seamless aluminum nozzles of 8 mm in diameter and 80 mm in length. Nozzles were in staggered arrangement. Experiments were conducted with circular jets for H/D values between 1 and 10, and for S/D values between 2 and 10. During the experiments Reynolds number has been kept constant at 30000. Experimental results showed that the longest cooling time with 87 seconds has been observed in the experiments for S/D=10 and H/D=10 values, while the shortest cooling time with 42.5 seconds has been measured in the experiments for S/D=2 and H/D=4 values.

Keywords: Glass tempering, cooling, Reynolds number, nozzle

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5922 Corrosion Protection of Structural Steel by Surfactant Containing Reagents

Authors: D. Erdenechimeg, T. Bujinlkham, N. Erdenepurev

Abstract:

The anti-corrosion performance of fatty acid coated mild steel samples is studied. Samples of structural steel coated with collector reagents deposited from surfactant in ethanol solution and overcoated with an epoxy barrier paint. A quantitative corrosion rate was determined by linear polarization resistance method using biopotentiostat/galvanostat 400. Coating morphology was determined by scanning electronic microscopy. A test for hydrophobic surface of steel by surfactant was done. From the samples, the main component or high content iron was determined by chemical method and other metal contents were determined by Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES) method. Prior to measuring the corrosion rate, mechanical and chemical treatments were performed to prepare the test specimens. Overcoating the metal samples with epoxy barrier paint after exposing them with surfactant the corrosion rate can be inhibited by 34-35 µm/year.

Keywords: Corrosion, linear polarization resistance, coating, surfactant.

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5921 Incremental Mining of Shocking Association Patterns

Authors: Eiad Yafi, Ahmed Sultan Al-Hegami, M. A. Alam, Ranjit Biswas

Abstract:

Association rules are an important problem in data mining. Massively increasing volume of data in real life databases has motivated researchers to design novel and incremental algorithms for association rules mining. In this paper, we propose an incremental association rules mining algorithm that integrates shocking interestingness criterion during the process of building the model. A new interesting measure called shocking measure is introduced. One of the main features of the proposed approach is to capture the user background knowledge, which is monotonically augmented. The incremental model that reflects the changing data and the user beliefs is attractive in order to make the over all KDD process more effective and efficient. We implemented the proposed approach and experiment it with some public datasets and found the results quite promising.

Keywords: Knowledge discovery in databases (KDD), Data mining, Incremental Association rules, Domain knowledge, Interestingness, Shocking rules (SHR).

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5920 Nonoscillation Criteria for Nonlinear Delay Dynamic Systems on Time Scales

Authors: Xinli Zhang

Abstract:

In this paper, we consider the nonlinear delay dynamic system xΔ(t) = p(t)f1(y(t)), yΔ(t) = −q(t)f2(x(t − τ )). We obtain some necessary and sufficient conditions for the existence of nonoscillatory solutions with special asymptotic properties of the system. We generalize the known results in the literature. One example is given to illustrate the results.

Keywords: Dynamic system, oscillation, time scales, two-dimensional.

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5919 An Improved Method to Compute Sparse Graphs for Traveling Salesman Problem

Authors: Y. Wang

Abstract:

The Traveling salesman problem (TSP) is NP-hard in combinatorial optimization. The research shows the algorithms for TSP on the sparse graphs have the shorter computation time than those for TSP according to the complete graphs. We present an improved iterative algorithm to compute the sparse graphs for TSP by frequency graphs computed with frequency quadrilaterals. The iterative algorithm is enhanced by adjusting two parameters of the algorithm. The computation time of the algorithm is O(CNmaxn2) where C is the iterations, Nmax is the maximum number of frequency quadrilaterals containing each edge and n is the scale of TSP. The experimental results showed the computed sparse graphs generally have less than 5n edges for most of these Euclidean instances. Moreover, the maximum degree and minimum degree of the vertices in the sparse graphs do not have much difference. Thus, the computation time of the methods to resolve the TSP on these sparse graphs will be greatly reduced.

Keywords: Frequency quadrilateral, iterative algorithm, sparse graph, traveling salesman problem.

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5918 A Hybrid Recommendation System Based On Association Rules

Authors: Ahmed Mohammed K. Alsalama

Abstract:

Recommendation systems are widely used in e-commerce applications. The engine of a current recommendation system recommends items to a particular user based on user preferences and previous high ratings. Various recommendation schemes such as collaborative filtering and content-based approaches are used to build a recommendation system. Most of current recommendation systems were developed to fit a certain domain such as books, articles, and movies. We propose1 a hybrid framework recommendation system to be applied on two dimensional spaces (User × Item) with a large number of Users and a small number of Items. Moreover, our proposed framework makes use of both favorite and non-favorite items of a particular user. The proposed framework is built upon the integration of association rules mining and the content-based approach. The results of experiments show that our proposed framework can provide accurate recommendations to users.

Keywords: Data Mining, Association Rules, Recommendation Systems, Hybrid Systems.

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