Search results for: Parallel Processing.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2088

Search results for: Parallel Processing.

1428 Nonlinear Slow Shear Alfven Waves in Electron- Positron-Ion Plasma Including Full Ion Dynamics

Authors: B. Ghosh, H. Sahoo, K. K. Mondal

Abstract:

Propagation of arbitrary amplitude nonlinear Alfven waves has been investigated in low but finite β electron-positron-ion plasma including full ion dynamics. Using Sagdeev pseudopotential method an energy integral equation has been derived. The Sagdeev potential has been calculated for different plasma parameters and it has been shown that inclusion of ion parallel motion along the magnetic field changes the nature of slow shear Alfven wave solitons from dip type to hump type. The effects of positron concentration, plasma-β and obliqueness of the wave propagation on the solitary wave structure have also been examined.

Keywords: Alfven waves, Sagdeev potential, Solitary waves.

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1427 Kaikaku - Radical Improvement in Production

Authors: D. Gåsvaer, J. von Axelson

Abstract:

Considering today-s increasing speed of change, radical and innovative improvement - Kaikaku, is a necessity parallel to continuous incremental improvement - Kaizen, especially for SME-s in order to attain the competitive edge needed to be profitable. During 2011, a qualitative single case study with the objective of realizing a kaikaku in production has been conducted. The case study was run as a one year project using a collaborative approach including both researchers and company representatives. The case study was conducted with the purpose of gaining further knowledge about kaikaku realization as well as its implications. The empirical results provide insights about the great productivity results achieved by applying a specific kaikaku realization approach. However, it also sheds light on the difficulty and contradiction of combining innovation management and production system development.

Keywords: Kaikaku, Radical improvement, manufacturing, innovation capability

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1426 Single-qubit Quantum Gates using Magneto-optic Kerr Effect

Authors: Pradeep Kumar K

Abstract:

We propose the use of magneto-optic Kerr effect (MOKE) to realize single-qubit quantum gates. We consider longitudinal and polar MOKE in reflection geometry in which the magnetic field is parallel to both the plane of incidence and surface of the film. MOKE couples incident TE and TM polarized photons and the Hamiltonian that represents this interaction is isomorphic to that of a canonical two-level quantum system. By varying the phase and amplitude of the magnetic field, we can realize Hadamard, NOT, and arbitrary phase-shift single-qubit quantum gates. The principal advantage is operation with magnetically non-transparent materials.

Keywords: Quantum computing, qubit, magneto-optic kerr effect (MOKE), magneto-optical interactions, continuous variables.

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1425 Nano-Texturing of Single Crystalline Silicon via Cu-Catalyzed Chemical Etching

Authors: A. A. Abaker Omer, H. B. Mohamed Balh, W. Liu, A. Abas, J. Yu, S. Li, W. Ma, W. El Kolaly, Y. Y. Ahmed Abuker

Abstract:

We have discovered an important technical solution that could make new approaches in the processing of wet silicon etching, especially in the production of photovoltaic cells. During its inferior light-trapping and structural properties, the inverted pyramid structure outperforms the conventional pyramid textures and black silicone. The traditional pyramid textures and black silicon can only be accomplished with more advanced lithography, laser processing, etc. Importantly, our data demonstrate the feasibility of an inverted pyramidal structure of silicon via one-step Cu-catalyzed chemical etching (CCCE) in Cu (NO3)2/HF/H2O2/H2O solutions. The effects of etching time and reaction temperature on surface geometry and light trapping were systematically investigated. The conclusion shows that the inverted pyramid structure has ultra-low reflectivity of ~4.2% in the wavelength of 300~1000 nm; introduce of Cu particles can significantly accelerate the dissolution of the silicon wafer. The etching and the inverted pyramid structure formation mechanism are discussed. Inverted pyramid structure with outstanding anti-reflectivity includes useful applications throughout the manufacture of semi-conductive industry-compatible solar cells, and can have significant impacts on industry colleagues and populations.

Keywords: Cu-catalyzed chemical etching, inverted pyramid nanostructured, reflection, solar cells.

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1424 EEG-Based Fractal Analysis of Different Motor Imagery Tasks using Critical Exponent Method

Authors: Montri Phothisonothai, Masahiro Nakagawa

Abstract:

The objective of this paper is to characterize the spontaneous Electroencephalogram (EEG) signals of four different motor imagery tasks and to show hereby a possible solution for the present binary communication between the brain and a machine ora Brain-Computer Interface (BCI). The processing technique used in this paper was the fractal analysis evaluated by the Critical Exponent Method (CEM). The EEG signal was registered in 5 healthy subjects,sampling 15 measuring channels at 1024 Hz.Each channel was preprocessed by the Laplacian space ltering so as to reduce the space blur and therefore increase the spaceresolution. The EEG of each channel was segmented and its Fractaldimension (FD) calculated. The FD was evaluated in the time interval corresponding to the motor imagery and averaged out for all the subjects (each channel). In order to characterize the FD distribution,the linear regression curves of FD over the electrodes position were applied. The differences FD between the proposed mental tasks are quantied and evaluated for each experimental subject. The obtained results of the proposed method are a substantial fractal dimension in the EEG signal of motor imagery tasks and can be considerably utilized as the multiple-states BCI applications.

Keywords: electroencephalogram (EEG), motor imagery tasks, mental tasks, biomedical signals processing, human-machine interface, fractal analysis, critical exponent method (CEM).

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1423 Simultaneous Reaction-Separation in a Microchannel Reactor with the Aid of a Guideline Structure

Authors: Salah Aljbour, Hiroshi Yamada, Tomohiko Tagawa

Abstract:

A microchannel with two inlets and two outlets was tested as a potential reactor to carry out two-phase catalytic phase transfer reaction with phase separation at the exit of the microchannel. The catalytic phase transfer reaction between benzyl chloride and sodium sulfide was chosen as a model reaction. The effect of operational time on the conversion was studied. By utilizing a multiphase parallel flow inside the microchannel reactor with the aid of a guideline structure, the catalytic phase reaction followed by phase separation could be ensured. The organic phase could be separated completely from one exit and part of the aqueous phase was separated purely and could be reused with slightly affecting the catalytic phase transfer reaction.

Keywords: Green engineering, microchannel reactor, multiphase reaction, process intensification.

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1422 Hand Gesture Detection via EmguCV Canny Pruning

Authors: N. N. Mosola, S. J. Molete, L. S. Masoebe, M. Letsae

Abstract:

Hand gesture recognition is a technique used to locate, detect, and recognize a hand gesture. Detection and recognition are concepts of Artificial Intelligence (AI). AI concepts are applicable in Human Computer Interaction (HCI), Expert systems (ES), etc. Hand gesture recognition can be used in sign language interpretation. Sign language is a visual communication tool. This tool is used mostly by deaf societies and those with speech disorder. Communication barriers exist when societies with speech disorder interact with others. This research aims to build a hand recognition system for Lesotho’s Sesotho and English language interpretation. The system will help to bridge the communication problems encountered by the mentioned societies. The system has various processing modules. The modules consist of a hand detection engine, image processing engine, feature extraction, and sign recognition. Detection is a process of identifying an object. The proposed system uses Canny pruning Haar and Haarcascade detection algorithms. Canny pruning implements the Canny edge detection. This is an optimal image processing algorithm. It is used to detect edges of an object. The system employs a skin detection algorithm. The skin detection performs background subtraction, computes the convex hull, and the centroid to assist in the detection process. Recognition is a process of gesture classification. Template matching classifies each hand gesture in real-time. The system was tested using various experiments. The results obtained show that time, distance, and light are factors that affect the rate of detection and ultimately recognition. Detection rate is directly proportional to the distance of the hand from the camera. Different lighting conditions were considered. The more the light intensity, the faster the detection rate. Based on the results obtained from this research, the applied methodologies are efficient and provide a plausible solution towards a light-weight, inexpensive system which can be used for sign language interpretation.

Keywords: Canny pruning, hand recognition, machine learning, skin tracking.

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1421 An Accurate Computation of Block Hybrid Method for Solving Stiff Ordinary Differential Equations

Authors: A. M. Sagir

Abstract:

In this paper, self-starting block hybrid method of order (5,5,5,5)T is proposed for the solution of the special second order ordinary differential equations with associated initial or boundary conditions. The continuous hybrid formulations enable us to differentiate and evaluate at some grids and off – grid points to obtain four discrete schemes, which were used in block form for parallel or sequential solutions of the problems. The computational burden and computer time wastage involved in the usual reduction of second order problem into system of first order equations are avoided by this approach. Furthermore, a stability analysis and efficiency of the block method are tested on stiff ordinary differential equations, and the results obtained compared favorably with the exact solution.

Keywords: Block Method, Hybrid, Linear Multistep Method, Self – starting, Special Second Order.

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1420 Mind Your Product-Market Strategy on Selecting Marketing Inputs: An Uncertainty Approach in Indian Context

Authors: Susmita Ghosh, Bhaskar Bhowmick

Abstract:

Market is an important factor for start-ups to look into during decision-making in product development and related areas. Emerging country markets are more uncertain in terms of information availability and institutional supports. The literature review of market uncertainty reveals the need for identifying factors representing the market uncertainty. This paper identifies factors for market uncertainty using Exploratory Factor Analysis (EFA) and confirmed the number of factor retention using an alternative factor retention criterion ‘Parallel Analysis’. 500 entrepreneurs, engaged in start-ups from all over India participated in the study. This paper concludes with the factor structure of ‘market uncertainty’ having dimensions of uncertainty in industry orientation, uncertainty in customer orientation and uncertainty in marketing orientation.

Keywords: Uncertainty, market, orientation, competitor, demand.

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1419 Normal and Peaberry Coffee Beans Classification from Green Coffee Bean Images Using Convolutional Neural Networks and Support Vector Machine

Authors: Hira Lal Gope, Hidekazu Fukai

Abstract:

The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.

Keywords: Convolutional neural networks, coffee bean, peaberry, sorting, support vector machine.

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1418 Harnessing the Power of AI: Transforming DevSecOps for Enhanced Cloud Security

Authors: Ashly Joseph, Jithu Paulose

Abstract:

The increased usage of cloud computing has revolutionized the IT landscape, but it has also raised new security concerns. DevSecOps emerged as a way for tackling these difficulties by integrating security into the software development process. However, the rising complexity and sophistication of cyber threats need more advanced solutions. This paper looks into the usage of artificial intelligence (AI) techniques in the DevSecOps framework to increase cloud security. This study uses quantitative and qualitative techniques to assess the usefulness of AI approaches such as machine learning, natural language processing, and deep learning in reducing security issues. This paper thoroughly examines the symbiotic relationship between AI and DevSecOps, concentrating on how AI may be seamlessly integrated into the continuous integration and continuous delivery (CI/CD) pipeline, automated security testing, and real-time monitoring methods. The findings emphasize AI's huge potential to improve threat detection, risk assessment, and incident response skills. Furthermore, the paper examines the implications and challenges of using AI in DevSecOps workflows, considering factors like as scalability, interpretability, and adaptability. This paper adds to a better understanding of AI's revolutionary role in cloud security and provides valuable insights for practitioners and scholars in the field.

Keywords: Cloud Security, DevSecOps, Artificial Intelligence, AI, Machine Learning, Natural Language Processing, NLP, cybersecurity, AI-driven Security.

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1417 Using High Performance Computing for Online Flood Monitoring and Prediction

Authors: Stepan Kuchar, Martin Golasowski, Radim Vavrik, Michal Podhoranyi, Boris Sir, Jan Martinovic

Abstract:

The main goal of this article is to describe the online flood monitoring and prediction system Floreon+ primarily developed for the Moravian-Silesian region in the Czech Republic and the basic process it uses for running automatic rainfall-runoff and hydrodynamic simulations along with their calibration and uncertainty modeling. It takes a long time to execute such process sequentially, which is not acceptable in the online scenario, so the use of a high performance computing environment is proposed for all parts of the process to shorten their duration. Finally, a case study on the Ostravice River catchment is presented that shows actual durations and their gain from the parallel implementation.

Keywords: Flood prediction process, High performance computing, Online flood prediction system, Parallelization.

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1416 HIV Modelling - Parallel Implementation Strategies

Authors: Dimitri Perrin, Heather J. Ruskin, Martin Crane

Abstract:

We report on the development of a model to understand why the range of experience with respect to HIV infection is so diverse, especially with respect to the latency period. To investigate this, an agent-based approach is used to extract highlevel behaviour which cannot be described analytically from the set of interaction rules at the cellular level. A network of independent matrices mimics the chain of lymph nodes. Dealing with massively multi-agent systems requires major computational effort. However, parallelisation methods are a natural consequence and advantage of the multi-agent approach and, using the MPI library, are here implemented, tested and optimized. Our current focus is on the various implementations of the data transfer across the network. Three communications strategies are proposed and tested, showing that the most efficient approach is communication based on the natural lymph-network connectivity.

Keywords: HIV, Immune modelling, MPI, Parallelisation.

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1415 Application of Multi-objective Optimization Packages in Design of an Evaporator Coil

Authors: A.Mosavi

Abstract:

A novel methodology has been used to design an evaporator coil of a refrigerant. The methodology used is through a complete Computer Aided Design /Computer Aided Engineering approach, by means of a Computational Fluid Dynamic/Finite Element Analysis model which is executed many times for the thermal-fluid exploration of several designs' configuration by an commercial optimizer. Hence the design is carried out automatically by parallel computations, with an optimization package taking the decisions rather than the design engineer. The engineer instead takes decision regarding the physical settings and initializing of the computational models to employ, the number and the extension of the geometrical parameters of the coil fins and the optimization tools to be employed. The final design of the coil geometry found to be better than the initial design.

Keywords: Multi-objective shape optimization, Heat Transfer, multi-physics structures, modeFRONTIER

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1414 Analytical Comparison of Conventional Algorithms with Vedic Algorithm for Digital Multiplier

Authors: Akhilesh G. Naik, Dipankar Pal

Abstract:

In today’s scenario, the complexity of digital signal processing (DSP) applications and various microcontroller architectures have been increasing to such an extent that the traditional approaches to multiplier design in most processors are becoming outdated for being comparatively slow. Modern processing applications require suitable pipelined approaches, and therefore, algorithms that are friendlier with pipelined architectures. Traditional algorithms like Wallace Tree, Radix-4 Booth, Radix-8 Booth, Dadda architectures have been proven to be comparatively slow for pipelined architectures. These architectures, therefore, need to be optimized or combined with other architectures amongst them to enhance its performances and to be made suitable for pipelined hardware/architectures. Recently, Vedic algorithm mathematically has proven to be efficient by appearing to be less complex and with fewer steps for its output establishment and have assumed renewed importance. This paper describes and shows how the Vedic algorithm can be better suited for pipelined architectures and also can be combined with traditional architectures and algorithms for enhancing its ability even further. In this paper, we also established that for complex applications on DSP and other microcontroller architectures, using Vedic approach for multiplication proves to be the best available and efficient option.

Keywords: Wallace tree, Radix-4 Booth, Radix-8 Booth, Dadda, Vedic, Single-Stage Karatsuba, Looped Karatsuba.

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1413 Organization Model of Semantic Document Repository and Search Techniques for Studying Information Technology

Authors: Nhon Do, Thuong Huynh, An Pham

Abstract:

Nowadays, organizing a repository of documents and resources for learning on a special field as Information Technology (IT), together with search techniques based on domain knowledge or document-s content is an urgent need in practice of teaching, learning and researching. There have been several works related to methods of organization and search by content. However, the results are still limited and insufficient to meet user-s demand for semantic document retrieval. This paper presents a solution for the organization of a repository that supports semantic representation and processing in search. The proposed solution is a model which integrates components such as an ontology describing domain knowledge, a database of document repository, semantic representation for documents and a file system; with problems, semantic processing techniques and advanced search techniques based on measuring semantic similarity. The solution is applied to build a IT learning materials management system of a university with semantic search function serving students, teachers, and manager as well. The application has been implemented, tested at the University of Information Technology, Ho Chi Minh City, Vietnam and has achieved good results.

Keywords: document retrieval system, knowledgerepresentation, document representation, semantic search, ontology.

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1412 Tidal Data Analysis using ANN

Authors: Ritu Vijay, Rekha Govil

Abstract:

The design of a complete expansion that allows for compact representation of certain relevant classes of signals is a central problem in signal processing applications. Achieving such a representation means knowing the signal features for the purpose of denoising, classification, interpolation and forecasting. Multilayer Neural Networks are relatively a new class of techniques that are mathematically proven to approximate any continuous function arbitrarily well. Radial Basis Function Networks, which make use of Gaussian activation function, are also shown to be a universal approximator. In this age of ever-increasing digitization in the storage, processing, analysis and communication of information, there are numerous examples of applications where one needs to construct a continuously defined function or numerical algorithm to approximate, represent and reconstruct the given discrete data of a signal. Many a times one wishes to manipulate the data in a way that requires information not included explicitly in the data, which is done through interpolation and/or extrapolation. Tidal data are a very perfect example of time series and many statistical techniques have been applied for tidal data analysis and representation. ANN is recent addition to such techniques. In the present paper we describe the time series representation capabilities of a special type of ANN- Radial Basis Function networks and present the results of tidal data representation using RBF. Tidal data analysis & representation is one of the important requirements in marine science for forecasting.

Keywords: ANN, RBF, Tidal Data.

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1411 Influence of Microstructural Features on Wear Resistance of Biomedical Titanium Materials

Authors: Mohsin T. Mohammed, Zahid A. Khan, Arshad N. Siddiquee

Abstract:

The field of biomedical materials plays an imperative requisite and a critical role in manufacturing a variety of biological artificial replacements in a modern world. Recently, titanium (Ti) materials are being used as biomaterials because of their superior corrosion resistance and tremendous specific strength, free- allergic problems and the greatest biocompatibility compared to other competing biomaterials such as stainless steel, Co-Cr alloys, ceramics, polymers, and composite materials. However, regardless of these excellent performance properties, Implantable Ti materials have poor shear strength and wear resistance which limited their applications as biomaterials. Even though the wear properties of Ti alloys has revealed some improvements, the crucial effectiveness of biomedical Ti alloys as wear components requires a comprehensive deep understanding of the wear reasons, mechanisms, and techniques that can be used to improve wear behavior. This review examines current information on the effect of thermal and thermomechanical processing of implantable Ti materials on the long-term prosthetic requirement which related with wear behavior. This paper focuses mainly on the evolution, evaluation and development of effective microstructural features that can improve wear properties of bio grade Ti materials using thermal and thermomechanical treatments.

Keywords: Wear Resistance, Heat Treatment, Thermomechanical Processing, Biomedical Titanium Materials.

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1410 Simulation Study of Lateral Trench Gate Power MOSFET on 4H-SiC

Authors: Yashvir Singh, Mayank Joshi

Abstract:

A lateral trench-gate power metal-oxide-semiconductor on 4H-SiC is proposed. The device consists of two separate trenches in which two gates are placed on both sides of P-body region resulting two parallel channels. Enhanced current conduction and reduced-surface-field effect in the structure provide substantial improvement in the device performance. Using two dimensional simulations, the performance of proposed device is evaluated and compare of with that of the conventional device for same cell pitch. It is demonstrated that the proposed structure provides two times higher output current, 11% decrease in threshold voltage, 70% improvement in transconductance, 70% reduction in specific ON-resistance, 52% increase in breakdown voltage, and nearly eight time improvement in figure-of-merit over the conventional device.

Keywords: 4H-SiC, lateral, trench-gate, power MOSFET.

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1409 A Semi-Cylindrical Capacitive Sensor Used for Soil Moisture Measurement

Authors: Subir Das, Tuhin Subhra Sarkar, Badal Chakraborty

Abstract:

Differing from the structure of traditional parallel plate capacitive sensor a semi cylindrical capacitive sensor has been introduced in this present work to measure the soil moisture conveniently. Here, the numerical analysis method to evaluate the capacitance from the semi-cylindrical capacitive sensor is analyzed and discussed. The changes of capacitance with the variation of soil moisture obtained linear in the nano farad range (nF) and which converted into voltage variation by using proper signal conditioning circuit. Experimental results depict the satisfactory performance of the sensor for measurement of soil moisture in the range of 0 to 70%. We investigated the linearity of 4% of FSO and sensitivity of 70 mV/unit percentage changes in soil moisture level (DB).

Keywords: Semi cylindrical Capacitive Sensor, Capacitance to Voltage converter Circuit, Soil Moisture.

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1408 Unsteady Transient Free Convective Flow of an Incompressible Viscous Fluid under Influence of Uniform Transverse Magnetic Field

Authors: Praveen Saraswat, Vipin Kumar Verma, Rudraman Singh

Abstract:

The unsteady transient free convection flow of an incompressible dissipative viscous fluid between parallel plates at different distances have been investigated under porous medium. Due to presence of heat flux under the influence of uniform transverse magnetic field the velocity distribution and the temperature distribution, is shown graphically. Since exact solution is not possible so we find parametrical solution by perturbation technique. The result is shown in graph for different parameters. We notice that heat generation effects fluid velocity keeping in which of free convection which cools.

Keywords: Transient, Convection, MHD, Viscous, Porous.

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1407 Correlation Analysis to Quantify Learning Outcomes for Different Teaching Pedagogies

Authors: Kanika Sood, Sijie Shang

Abstract:

A fundamental goal of education includes preparing students to become a part of the global workforce by making beneficial contributions to society. In this paper, we analyze student performance for multiple courses that involve different teaching pedagogies: a cooperative learning technique and an inquiry-based learning strategy. Student performance includes student engagement, grades, and attendance records. We perform this study in the Computer Science department for online and in-person courses for 450 students. We will perform correlation analysis to study the relationship between student scores and other parameters such as gender, mode of learning. We use natural language processing and machine learning to analyze student feedback data and performance data. We assess the learning outcomes of two teaching pedagogies for undergraduate and graduate courses to showcase the impact of pedagogical adoption and learning outcome as determinants of academic achievement. Early findings suggest that when using the specified pedagogies, students become experts on their topics and illustrate enhanced engagement with peers.

Keywords: Bag-of-words, cooperative learning, education, inquiry-based learning, in-person learning, Natural Language Processing, online learning, sentiment analysis, teaching pedagogy.

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1406 Lean Thinking Process in the Determination of Design Suggestions to Optimize Treatment of WEEE

Authors: Anastasia Katsamaki, Nikolaos Bilalis, Vassilis Dedoussis

Abstract:

This work proposes a set of actions to assist redesign procedure in existing products of Electric and Electronic Equipment (EEE). The aim is to improve their environmental behavior after their withdrawal in the End-of-Life (EOL) phase. In the beginning data collection takes place. Then follows selection and implementation of the optimal EOL Treatment Strategy (EOL_TS) and its results- evaluation concerning the environment. In parallel, product design characteristics that can be altered are selected based on their significance for the environment in the EOL stage. All results from the previous stages are combined and possible redesign actions are formulated for further examination and afterwards configuration in the design stage. The applied method to perform these tasks is Lean Thinking (LT). At the end, results concerning the application of the proposed method on a distribution transformer are presented.

Keywords: End-of-life treatment, Lean thinking, WEEE

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1405 The Operating Behaviour of Unbalanced Unpaced Merging Assembly Lines

Authors: S. Shaaban, T. McNamara, S. Hudson

Abstract:

This paper reports on the performance of deliberately unbalanced, reliable, non-automated and assembly lines that merge, whose workstations differ in terms of their mean operation times. Simulations are carried out on 5- and 8-station lines with 1, 2 and 4 buffer capacity units, % degrees of line imbalance of 2, 5 and 12, and 24 different patterns of means imbalance. Data on two performance measures, namely throughput and average buffer level were gathered, statistically analysed and compared to a merging balanced line counterpart. It was found that the best configurations are a balanced line arrangement and a monotone decreasing order for each of the parallel merging lines, with the first generally resulting in a lower throughput and the second leading to a lower average buffer level than those of a balanced line.

Keywords: Average buffer level, merging lines, simulation, throughput, unbalanced.

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1404 Robust Fuzzy Control of Nonlinear Fuzzy Impulsive Singular Perturbed Systems with Time-varying Delay

Authors: Caigen Zhou, Haibo Jiang

Abstract:

The problem of robust fuzzy control for a class of nonlinear fuzzy impulsive singular perturbed systems with time-varying delay is investigated by employing Lyapunov functions. The nonlinear delay system is built based on the well-known T–S fuzzy model. The so-called parallel distributed compensation idea is employed to design the state feedback controller. Sufficient conditions for global exponential stability of the closed-loop system are derived in terms of linear matrix inequalities (LMIs), which can be easily solved by LMI technique. Some simulations illustrate the effectiveness of the proposed method.

Keywords: T–S fuzzy model, singular perturbed systems, time-varying delay, robust control.

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1403 Analysis of Translational Ship Oscillations in a Realistic Environment

Authors: Chen Zhang, Bernhard Schwarz-Röhr, Alexander Härting

Abstract:

To acquire accurate ship motions at the center of gravity, a single low-cost inertial sensor is utilized and applied on board to measure ship oscillating motions. As observations, the three axes accelerations and three axes rotational rates provided by the sensor are used. The mathematical model of processing the observation data includes determination of the distance vector between the sensor and the center of gravity in x, y, and z directions. After setting up the transfer matrix from sensor’s own coordinate system to the ship’s body frame, an extended Kalman filter is applied to deal with nonlinearities between the ship motion in the body frame and the observation information in the sensor’s frame. As a side effect, the method eliminates sensor noise and other unwanted errors. Results are not only roll and pitch, but also linear motions, in particular heave and surge at the center of gravity. For testing, we resort to measurements recorded on a small vessel in a well-defined sea state. With response amplitude operators computed numerically by a commercial software (Seaway), motion characteristics are estimated. These agree well with the measurements after processing with the suggested method.

Keywords: Extended Kalman filter, nonlinear estimation, sea trial, ship motion estimation.

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1402 Application of Medium High Hydrostatic Pressure in Preserving Textural Quality and Safety of Pineapple Compote

Authors: Nazim Uddin, Yohiko Nakaura, Kazutaka Yamamoto

Abstract:

Compote (fruit in syrup) of pineapple (Ananas comosus L. Merrill) is expected to have a high market potential as one of convenient ready-to-eat (RTE) foods worldwide. High hydrostatic pressure (HHP) in combination with low temperature (LT) was applied to the processing of pineapple compote as well as medium HHP (MHHP) in combination with medium-high temperature (MHT) since both processes can enhance liquid impregnation and inactivate microbes. MHHP+MHT (55 or 65 °C) process, as well as the HHP+LT process, has successfully inactivated the microbes in the compote to a non-detectable level. Although the compotes processed by MHHP+MHT or HHP+LT have lost the fresh texture as in a similar manner as those processed solely by heat, it was indicated that the texture degradations by heat were suppressed under MHHP. Degassing process reduced the hardness, while calcium (Ca) contributed to be retained hardness in MHT and MHHP+MHT processes. Electrical impedance measurement supported the damage due to degassing and heat. The color, Brix, and appearance were not affected by the processing methods significantly. MHHP+MHT and HHP+LT processes may be applicable to produce high-quality, safe RTE pineapple compotes. Further studies on the optimization of packaging and storage condition will be indispensable for commercialization.

Keywords: Compote of pineapple, ready-to-eat, medium high hydrostatic pressure, postharvest loss, and texture.

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1401 A Nonlinear ODE System for the Unsteady Hydrodynamic Force – A New Approach

Authors: Osama A. Marzouk

Abstract:

We propose a reduced-ordermodel for the instantaneous hydrodynamic force on a cylinder. The model consists of a system of two ordinary differential equations (ODEs), which can be integrated in time to yield very accurate histories of the resultant force and its direction. In contrast to several existing models, the proposed model considers the actual (total) hydrodynamic force rather than its perpendicular or parallel projection (the lift and drag), and captures the complete force rather than the oscillatory part only. We study and provide descriptions of the relationship between the model parameters, evaluated utilizing results from numerical simulations, and the Reynolds number so that the model can be used at any arbitrary value within the considered range of 100 to 500 to provide accurate representation of the force without the need to perform timeconsuming simulations and solving the partial differential equations (PDEs) governing the flow field.

Keywords: reduced-order model, wake oscillator, nonlinear, ODEsystem

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1400 Modelling of Hydric Behaviour of Textiles

Authors: A. Marolleau, F. Salaun, D. Dupont, H. Gidik, S. Ducept.

Abstract:

The goal of this study is to analyze the hydric behaviour of textiles which can impact significantly the comfort of the wearer. Indeed, fabrics can be adapted for different climate if hydric and thermal behaviors are known. In this study, fabrics are only submitted to hydric variations. Sorption and desorption isotherms obtained from the dynamic vapour sorption apparatus (DVS) are fitted with the parallel exponential kinetics (PEK), the Hailwood-Horrobin (HH) and the Brunauer-Emmett-Teller (BET) models. One of the major finding is the relationship existing between PEK and HH models. During slow and fast processes, the sorption of water molecules on the polymer can be in monolayer and multilayer form. According to the BET model, moisture regain, a physical property of textiles, show a linear correlation with the total amount of water taken in monolayer. This study provides potential information of the end uses of these fabrics according to the selected activity level.

Keywords: Comfort, hydric properties, modelling, underwear.

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1399 Enhancing Word Meaning Retrieval Using FastText and NLP Techniques

Authors: Sankalp Devanand, Prateek Agasimani, V. S. Shamith, Rohith Neeraje

Abstract:

Machine translation has witnessed significant advancements in recent years, but the translation of languages with distinct linguistic characteristics, such as English and Sanskrit, remains a challenging task. This research presents the development of a dedicated English to Sanskrit machine translation model, aiming to bridge the linguistic and cultural gap between these two languages. Using a variety of natural language processing (NLP) approaches including FastText embeddings, this research proposes a thorough method to improve word meaning retrieval. Data preparation, part-of-speech tagging, dictionary searches, and transliteration are all included in the methodology. The study also addresses the implementation of an interpreter pattern and uses a word similarity task to assess the quality of word embeddings. The experimental outcomes show how the suggested approach may be used to enhance word meaning retrieval tasks with greater efficacy, accuracy, and adaptability. Evaluation of the model's performance is conducted through rigorous testing, comparing its output against existing machine translation systems. The assessment includes quantitative metrics such as BLEU scores, METEOR scores, Jaccard Similarity etc.

Keywords: Machine translation, English to Sanskrit, natural language processing, word meaning retrieval, FastText embeddings.

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