Search results for: Taguchi experimental design
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 17696

Search results for: Taguchi experimental design

9326 The Application of Image Analyzer to Study the Effects of Pericarp in the Imbibition Process of Melia dubia Seeds

Authors: Satya Srii, V., Nethra, N.

Abstract:

An image analyzer system is described to study the process of imbibition in Melia dubia seeds. The experimental system consisted of control C (seeds with intact pericarp) with two treatments, namely T1 (seeds with pericarp punctured) and T2 (naked seeds without pericarp). The measurement software in the image analyzer can determine the area and perimeter as descriptors of changes in seed size during swelling resulting from imbibition. Using the area and perimeter parameter, the imbibition process in C, T1, and T2 was described by a series of curves similar to the triphasic pattern of water uptake, with the extent and rate depending upon the treatment. Naked seeds without pericarp (T2) took lesser time to reach phase III during imbition followed by seeds with pericarp punctured (T1) while the seeds with intact pericarp (C) were the slowest to attain phase III. This shows the effect of pericarp in acting as a potential inhibitor to imbibition inducing a large delay in germination. The sensitivity and feasibility of the method to investigate individual seeds within a population imply that the image analyzer has high potential in seed biology studies.

Keywords: germination, imbibition, image analyzer, Melia dubia, pericarp

Procedia PDF Downloads 125
9325 Sentiment Analysis of Ensemble-Based Classifiers for E-Mail Data

Authors: Muthukumarasamy Govindarajan

Abstract:

Detection of unwanted, unsolicited mails called spam from email is an interesting area of research. It is necessary to evaluate the performance of any new spam classifier using standard data sets. Recently, ensemble-based classifiers have gained popularity in this domain. In this research work, an efficient email filtering approach based on ensemble methods is addressed for developing an accurate and sensitive spam classifier. The proposed approach employs Naive Bayes (NB), Support Vector Machine (SVM) and Genetic Algorithm (GA) as base classifiers along with different ensemble methods. The experimental results show that the ensemble classifier was performing with accuracy greater than individual classifiers, and also hybrid model results are found to be better than the combined models for the e-mail dataset. The proposed ensemble-based classifiers turn out to be good in terms of classification accuracy, which is considered to be an important criterion for building a robust spam classifier.

Keywords: accuracy, arcing, bagging, genetic algorithm, Naive Bayes, sentiment mining, support vector machine

Procedia PDF Downloads 128
9324 Providing Open Access for Scholarly Information in Libya

Authors: Mohamed Abolgasem Arteimi, Ahlam Al-Tajori

Abstract:

This paper describes an ongoing project at the Libyan Academy. The project aims to build digital library for thesis and dissertations (ETD). The researchers developed a system based on Greenstone open source systems for building ETD digital library. A metadata for theses and dissertations was developed. The paper addresses issues related to project design, development and user satisfaction. Conclusions highlighted some important lessons learned to date.

Keywords: digital library, electronic theses and dissertations, open access, ETD, metadata

Procedia PDF Downloads 301
9323 A Genetic Algorithm Based Ensemble Method with Pairwise Consensus Score on Malware Cacophonous Labels

Authors: Shih-Yu Wang, Shun-Wen Hsiao

Abstract:

In the field of cybersecurity, there exists many vendors giving malware samples classified results, namely naming after the label that contains some important information which is also called AV label. Lots of researchers relay on AV labels for research. Unfortunately, AV labels are too cluttered. They do not have a fixed format and fixed naming rules because the naming results were based on each classifiers' viewpoints. A way to fix the problem is taking a majority vote. However, voting can sometimes create problems of bias. Thus, we create a novel ensemble approach which does not rely on the cacophonous naming result but depend on group identification to aggregate everyone's opinion. To achieve this purpose, we develop an scoring system called Pairwise Consensus Score (PCS) to calculate result similarity. The entire method architecture combine Genetic Algorithm and PCS to find maximum consensus in the group. Experimental results revealed that our method outperformed the majority voting by 10% in term of the score.

Keywords: genetic algorithm, ensemble learning, malware family, malware labeling, AV labels

Procedia PDF Downloads 73
9322 High-Throughput, Purification-Free, Multiplexed Profiling of Circulating miRNA for Discovery, Validation, and Diagnostics

Authors: J. Hidalgo de Quintana, I. Stoner, M. Tackett, G. Doran, C. Rafferty, A. Windemuth, J. Tytell, D. Pregibon

Abstract:

We have developed the Multiplexed Circulating microRNA assay that allows the detection of up to 68 microRNA targets per sample. The assay combines particle­based multiplexing, using patented Firefly hydrogel particles, with single­ step RT-PCR signal. Thus, the Circulating microRNA assay leverages PCR sensitivity while eliminating the need for separate reverse transcription reactions and mitigating amplification biases introduced by target­-specific qPCR. Furthermore, the ability to multiplex targets in each well eliminates the need to split valuable samples into multiple reactions. Results from the Circulating microRNA assay are interpreted using Firefly Analysis Workbench, which allows visualization, normalization, and export of experimental data. To aid discovery and validation of biomarkers, we have generated fixed panels for Oncology, Cardiology, Neurology, Immunology, and Liver Toxicology. Here we present the data from several studies investigating circulating and tumor microRNA, showcasing the ability of the technology to sensitively and specifically detect microRNA biomarker signatures from fluid specimens.

Keywords: biomarkers, biofluids, miRNA, photolithography, flowcytometry

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9321 Six-Phase Tooth-Coil Winding Starter-Generator Embedded in Aerospace Engine

Authors: Flur R. Ismagilov, Vyacheslav E. Vavilov, Denis V. Gusakov

Abstract:

This paper is devoted to solve the problem of increasing the electrification of aircraft engines by installing a synchronous generator at high pressure shaft. Technical solution of this problem by various research centers is discussed. A design solution of the problem was proposed. To evaluate the effectiveness of the proposed cooling system, thermal analysis was carried out in ANSYS software.

Keywords: starter-generator, more electrical engine, aircraft engines, high pressure shaft, synchronous generator

Procedia PDF Downloads 245
9320 Improvement of Oran Sebkha Soil by Dredged Sediments from Chorfa Dam in Algeria

Authors: Z. Aloui-Labiod, H. Trouzine, M. S. Ghembaza

Abstract:

Geotechnical properties of dredged sediment from Chorfa dam in Algeria and their mixtures (5%, 10%, 15%, 20%, and 25%)with bentonite were investigated through with bentonite were investigated through a series of laboratory experimental tests in order to investigate possibilities of their usage as a barrier against the spread out of the Sebkha of Oran in the northwest of Algeria. Grain size and Atterberg limits tests, chemical and mineral analyses, and compaction, vertical swelling, and horizontal and vertical permeability tests were performed on the soils and their mixtures using tap water and the salty Sebkha water. The results indicate that the bentonite specimens remolded and inundated with Sebkha salty water have less swell potential than those prepared with tap water. The addition of bentonite to Chorfa sediment increases the density, limit liquid, specific surface, and swell potential of the mixtures. Compaction tests show a decrease in the optimum moisture and an increase in maximum dry densities as the bentonite content increases. The horizontal and vertical permeabilities decrease relatively with the addition of bentonite.

Keywords: dredged sediment, bentonite, salty water, barrier

Procedia PDF Downloads 412
9319 Hyperspectral Imagery for Tree Speciation and Carbon Mass Estimates

Authors: Jennifer Buz, Alvin Spivey

Abstract:

The most common greenhouse gas emitted through human activities, carbon dioxide (CO2), is naturally consumed by plants during photosynthesis. This process is actively being monetized by companies wishing to offset their carbon dioxide emissions. For example, companies are now able to purchase protections for vegetated land due-to-be clear cut or purchase barren land for reforestation. Therefore, by actively preventing the destruction/decay of plant matter or by introducing more plant matter (reforestation), a company can theoretically offset some of their emissions. One of the biggest issues in the carbon credit market is validating and verifying carbon offsets. There is a need for a system that can accurately and frequently ensure that the areas sold for carbon credits have the vegetation mass (and therefore for carbon offset capability) they claim. Traditional techniques for measuring vegetation mass and determining health are costly and require many person-hours. Orbital Sidekick offers an alternative approach that accurately quantifies carbon mass and assesses vegetation health through satellite hyperspectral imagery, a technique which enables us to remotely identify material composition (including plant species) and condition (e.g., health and growth stage). How much carbon a plant is capable of storing ultimately is tied to many factors, including material density (primarily species-dependent), plant size, and health (trees that are actively decaying are not effectively storing carbon). All of these factors are capable of being observed through satellite hyperspectral imagery. This abstract focuses on speciation. To build a species classification model, we matched pixels in our remote sensing imagery to plants on the ground for which we know the species. To accomplish this, we collaborated with the researchers at the Teakettle Experimental Forest. Our remote sensing data comes from our airborne “Kato” sensor, which flew over the study area and acquired hyperspectral imagery (400-2500 nm, 472 bands) at ~0.5 m/pixel resolution. Coverage of the entire teakettle experimental forest required capturing dozens of individual hyperspectral images. In order to combine these images into a mosaic, we accounted for potential variations of atmospheric conditions throughout the data collection. To do this, we ran an open source atmospheric correction routine called ISOFIT1 (Imaging Spectrometer Optiman FITting), which converted all of our remote sensing data from radiance to reflectance. A database of reflectance spectra for each of the tree species within the study area was acquired using the Teakettle stem map and the geo-referenced hyperspectral images. We found that a wide variety of machine learning classifiers were able to identify the species within our images with high (>95%) accuracy. For the most robust quantification of carbon mass and the best assessment of the health of a vegetated area, speciation is critical. Through the use of high resolution hyperspectral data, ground-truth databases, and complex analytical techniques, we are able to determine the species present within a pixel to a high degree of accuracy. These species identifications will feed directly into our carbon mass model.

Keywords: hyperspectral, satellite, carbon, imagery, python, machine learning, speciation

Procedia PDF Downloads 105
9318 Ground State Phases in Two-Mode Quantum Rabi Models

Authors: Suren Chilingaryan

Abstract:

We study two models describing a single two-level system coupled to two boson field modes in either a parallel or orthogonal setup. Both models may be feasible for experimental realization through Raman adiabatic driving in cavity QED. We study their ground state configurations; that is, we find the quantum precursors of the corresponding semi-classical phase transitions. We found that the ground state configurations of both models present the same critical coupling as the quantum Rabi model. Around this critical coupling, the ground state goes from the so-called normal configuration with no excitation, the qubit in the ground state and the fields in the quantum vacuum state, to a ground state with excitations, the qubit in a superposition of ground and excited state, while the fields are not in the vacuum anymore, for the first model. The second model shows a more complex ground state configuration landscape where we find the normal configuration mentioned above, two single-mode configurations, where just one of the fields and the qubit are excited, and a dual-mode configuration, where both fields and the qubit are excited.

Keywords: quantum optics, quantum phase transition, cavity QED, circuit QED

Procedia PDF Downloads 354
9317 An Image Segmentation Algorithm for Gradient Target Based on Mean-Shift and Dictionary Learning

Authors: Yanwen Li, Shuguo Xie

Abstract:

In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: gradient image, segmentation and extract, mean-shift algorithm, dictionary iearning

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9316 Kinetic Modeling Study and Scale-Up of Niogas Generation Using Garden Grass and Cattle Dung as Feedstock

Authors: Tumisang Seodigeng, Hilary Rutto

Abstract:

In this study we investigate the use of a laboratory batch digester to derive kinetic parameters for anaerobic digestion of garden grass and cattle dung. Laboratory experimental data from a 5 liter batch digester operating at mesophilic temperature of 32 C is used to derive parameters for Michaelis-Menten kinetic model. These fitted kinetics are further used to predict the scale-up parameters of a batch digester using DynoChem modeling and scale-up software. The scale-up model results are compared with performance data from 20 liter, 50 liter, and 200 liter batch digesters. Michaelis-Menten kinetic model shows to be a very good and easy to use model for kinetic parameter fitting on DynoChem and can accurately predict scale-up performance of 20 liter and 50 liter batch reactor based on parameters fitted on a 5 liter batch reactor.

Keywords: Biogas, kinetics, DynoChem Scale-up, Michaelis-Menten

Procedia PDF Downloads 479
9315 An Improved Tracking Approach Using Particle Filter and Background Subtraction

Authors: Amir Mukhtar, Dr. Likun Xia

Abstract:

An improved, robust and efficient visual target tracking algorithm using particle filtering is proposed. Particle filtering has been proven very successful in estimating non-Gaussian and non-linear problems. In this paper, the particle filter is used with color feature to estimate the target state with time. Color distributions are applied as this feature is scale and rotational invariant, shows robustness to partial occlusion and computationally efficient. The performance is made more robust by choosing the different (YIQ) color scheme. Tracking is performed by comparison of chrominance histograms of target and candidate positions (particles). Color based particle filter tracking often leads to inaccurate results when light intensity changes during a video stream. Furthermore, background subtraction technique is used for size estimation of the target. The qualitative evaluation of proposed algorithm is performed on several real-world videos. The experimental results demonstrate that the improved algorithm can track the moving objects very well under illumination changes, occlusion and moving background.

Keywords: tracking, particle filter, histogram, corner points, occlusion, illumination

Procedia PDF Downloads 362
9314 Investigation of the Capability of REALP5 to Solve Complex Fuel Geometry

Authors: D. Abdelrazek, M. NaguibAly, A. A. Badawi, Asmaa G. Abo Elnour, A. A. El-Kafas

Abstract:

This work is developed within IAEA Coordinated Research Program 1496, “Innovative methods in research reactor analysis: Benchmark against experimental data on neutronics and thermal-hydraulic computational methods and tools for operation and safety analysis of research reactors.” The study investigates the capability of Code RELAP5/Mod3.4 to solve complex geometry complexity. Its results are compared to the results of PARET, a common code in thermal hydraulic analysis for research reactors, belonging to MTR-PC groups. The WWR-SM reactor at the Institute of Nuclear Physics (INP) in the Republic of Uzbekistan is simulated using both PARET and RELAP5 at steady state. Results from the two codes are compared. REALP5 code succeeded in solving the complex fuel geometry. The PARET code needed some calculations to obtain the final result. Although the final results from the PARET are more accurate, the small differences in both results makes using RELAP5 code recommended in case of complex fuel assemblies.

Keywords: complex fuel geometry, PARET, RELAP5, WWR-SM reactor

Procedia PDF Downloads 319
9313 Comparative Isotherms Studies on Adsorptive Removal of Methyl Orange from Wastewater by Watermelon Rinds and Neem-Tree Leaves

Authors: Sadiq Sani, Muhammad B. Ibrahim

Abstract:

Watermelon rinds powder (WRP) and neem-tree leaves powder (NLP) were used as adsorbents for equilibrium adsorption isotherms studies for detoxification of methyl orange dye (MO) from simulated wastewater. The applicability of the process to various isotherm models was tested. All isotherms from the experimental data showed excellent linear reliability (R2: 0.9487-0.9992) but adsorptions onto WRP were more reliable (R2: 0.9724-0.9992) than onto NLP (R2: 0.9487-0.9989) except for Temkin’s Isotherm where reliability was better onto NLP (R2: 0.9937) than onto WRP (R2: 0.9935). Dubinin-Radushkevich’s monolayer adsorption capacities for both WRP and NLP (qD: 20.72 mg/g, 23.09 mg/g) were better than Langmuir’s (qm: 18.62 mg/g, 21.23 mg/g) with both capacities higher for adsorption onto NLP (qD: 23.09 mg/g; qm: 21.23 mg/g) than onto WRP (qD: 20.72 mg/g; qm: 18.62 mg/g). While values for Langmuir’s separation factor (RL) for both adsorbents suggested unfavourable adsorption processes (RL: -0.0461, -0.0250), Freundlich constant (nF) indicated favourable process onto both WRP (nF: 3.78) and NLP (nF: 5.47). Adsorption onto NLP had higher Dubinin-Radushkevich’s mean free energy of adsorption (E: 0.13 kJ/mol) than WRP (E: 0.08 kJ/mol) and Temkin’s heat of adsorption (bT) was better onto NLP (bT: -0.54 kJ/mol) than onto WRP (bT: -0.95 kJ/mol) all of which suggested physical adsorption.

Keywords: adsorption isotherms, methyl orange, neem leaves, watermelon rinds

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9312 The Convolution Recurrent Network of Using Residual LSTM to Process the Output of the Downsampling for Monaural Speech Enhancement

Authors: Shibo Wei, Ting Jiang

Abstract:

Convolutional-recurrent neural networks (CRN) have achieved much success recently in the speech enhancement field. The common processing method is to use the convolution layer to compress the feature space by multiple upsampling and then model the compressed features with the LSTM layer. At last, the enhanced speech is obtained by deconvolution operation to integrate the global information of the speech sequence. However, the feature space compression process may cause the loss of information, so we propose to model the upsampling result of each step with the residual LSTM layer, then join it with the output of the deconvolution layer and input them to the next deconvolution layer, by this way, we want to integrate the global information of speech sequence better. The experimental results show the network model (RES-CRN) we introduce can achieve better performance than LSTM without residual and overlaying LSTM simply in the original CRN in terms of scale-invariant signal-to-distortion ratio (SI-SNR), speech quality (PESQ), and intelligibility (STOI).

Keywords: convolutional-recurrent neural networks, speech enhancement, residual LSTM, SI-SNR

Procedia PDF Downloads 183
9311 Tribological Behavior of Pongamia Oil Based Biodiesel Blended Lubricant at Different Load

Authors: Yashvir Singh, Amneesh Singla, Swapnil Bhurat

Abstract:

Around the globe, there is demand for the development of bio-based lubricant which will be biodegradable, non toxic, and environmentally-friendly. This paper outlines the friction and wear characteristics of ponagamia biodiesel contaminated bio-lubricant by using pin-on-disc tribometer. To formulate the bio-lubricants, Ponagamia oil based biodiesel were blended in the ratios 5, 10, and 20% by volume with the base lubricant SAE 20 W 40. Tribological characteristics of these blends were carried out at 2.5 m/s sliding velocity and loads applied were 50, 100, 150 N. Experimental results showed that the lubrication regime that occurred during the test was boundary lubrication while the main wear mechanisms was the adhesive wear. During testing, the lowest wear was found with the addition of 5 and 10% Ponagamia oil based biodiesel, and above this contamination, the wear rate was increased considerably. The addition of 5 and 10% Ponagamia oil based biodiesel with the base lubricant acted as a very good lubricant additive which reduced the friction and wear rate during the test. It has been concluded that the PBO 5 and PBO 10 can act as an alternative lubricant to increase the mechanical efficiency at 2.5 m/s sliding velocity and contribute in reduction of dependence on the petroleum based products.

Keywords: friction, load, pongamia oil blend, sliding velocity, wear

Procedia PDF Downloads 300
9310 Peat Soil Stabilization by Using Sugarcane Bagasse Ash (SCBA)

Authors: Mohd. Khaidir Abu Talib, Noriyuki Yasufuku, Ryohei Ishikura

Abstract:

It is well recognized that peat can impede the proper hydration of cement because of high organic content, presence of humic acid and less solid particles. That means the large amount of cement is required in order to neutralize the acids or otherwise the process of the peat stabilization remains retarded. Nevertheless, adding a great quantity of cement into the peat is absolutely an unfriendly and uneconomical solution. Sugarcane production is world number one commodities and produced a lot of bagasse. Bagasse is burnt to generate power required for diverse activities in the factory and leave bagasse ash as a waste. Increasing concern of disposal of bagasse residual creates interest to explore the potential application of this material. The objective of this study is to develop alternative binders that are environment friendly and contribute towards sustainable management by utilizing sugarcane bagasse ash (SCBA) in the stabilization of peat soil. Alongside SCBA, Ordinary Portland Cement (OPC), calcium chloride (CaCl2) and silica sand (K7) were used as additives to stabilize the peat that sampled from Hokkaido, Japan. In obtaining the optimal mix design, specimens of stabilized peat were tested in unconfined compression. It was found that stabilized peat comprising 20% and 5% (PCB1-20 and PCB2-5) partial replacement of OPC with SCBA 1 and SCBA 2 attain the maximum unconfined compressive strength (UCS) and discovered greater than untreated soil (P) and UCS of peat-cement (PC) specimen. At the optimal mix design, the UCS of the stabilized peat specimens increased with increasing of curing time, preloading during curing, OPC dosage and K7 dosage. For PCB1-20 mixture, inclusion of a minimum OPC dosage of 300 kg/m3 and K7 dosage of 500 kg/m3 along with curing under 20kPa pressure is recommendable for the peat stabilization to be effective. However for PCB2-5 mixture, it suggested to use more OPC and K7 dosage or alternatively increase the preloading during curing to 40kPa in order to achieve minimum strength target. It can be concluded that SCBA 1 has better quality than SCBA 2 in peat stabilization especially the contribution made by its fine particle size.

Keywords: peat stabilization, sugarcane bagasse ash utilization, partial cement replacement, unconfined strength

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9309 Pharmacophore-Based Modeling of a Series of Human Glutaminyl Cyclase Inhibitors to Identify Lead Molecules by Virtual Screening, Molecular Docking and Molecular Dynamics Simulation Study

Authors: Ankur Chaudhuri, Sibani Sen Chakraborty

Abstract:

In human, glutaminyl cyclase activity is highly abundant in neuronal and secretory tissues and is preferentially restricted to hypothalamus and pituitary. The N-terminal modification of β-amyloids (Aβs) peptides by the generation of a pyro-glutamyl (pGlu) modified Aβs (pE-Aβs) is an important process in the initiation of the formation of neurotoxic plaques in Alzheimer’s disease (AD). This process is catalyzed by glutaminyl cyclase (QC). The expression of QC is characteristically up-regulated in the early stage of AD, and the hallmark of the inhibition of QC is the prevention of the formation of pE-Aβs and plaques. A computer-aided drug design (CADD) process was employed to give an idea for the designing of potentially active compounds to understand the inhibitory potency against human glutaminyl cyclase (QC). This work elaborates the ligand-based and structure-based pharmacophore exploration of glutaminyl cyclase (QC) by using the known inhibitors. Three dimensional (3D) quantitative structure-activity relationship (QSAR) methods were applied to 154 compounds with known IC50 values. All the inhibitors were divided into two sets, training-set, and test-sets. Generally, training-set was used to build the quantitative pharmacophore model based on the principle of structural diversity, whereas the test-set was employed to evaluate the predictive ability of the pharmacophore hypotheses. A chemical feature-based pharmacophore model was generated from the known 92 training-set compounds by HypoGen module implemented in Discovery Studio 2017 R2 software package. The best hypothesis was selected (Hypo1) based upon the highest correlation coefficient (0.8906), lowest total cost (463.72), and the lowest root mean square deviation (2.24Å) values. The highest correlation coefficient value indicates greater predictive activity of the hypothesis, whereas the lower root mean square deviation signifies a small deviation of experimental activity from the predicted one. The best pharmacophore model (Hypo1) of the candidate inhibitors predicted comprised four features: two hydrogen bond acceptor, one hydrogen bond donor, and one hydrophobic feature. The Hypo1 was validated by several parameters such as test set activity prediction, cost analysis, Fischer's randomization test, leave-one-out method, and heat map of ligand profiler. The predicted features were then used for virtual screening of potential compounds from NCI, ASINEX, Maybridge and Chembridge databases. More than seven million compounds were used for this purpose. The hit compounds were filtered by drug-likeness and pharmacokinetics properties. The selective hits were docked to the high-resolution three-dimensional structure of the target protein glutaminyl cyclase (PDB ID: 2AFU/2AFW) to filter these hits further. To validate the molecular docking results, the most active compound from the dataset was selected as a reference molecule. From the density functional theory (DFT) study, ten molecules were selected based on their highest HOMO (highest occupied molecular orbitals) energy and the lowest bandgap values. Molecular dynamics simulations with explicit solvation systems of the final ten hit compounds revealed that a large number of non-covalent interactions were formed with the binding site of the human glutaminyl cyclase. It was suggested that the hit compounds reported in this study could help in future designing of potent inhibitors as leads against human glutaminyl cyclase.

Keywords: glutaminyl cyclase, hit lead, pharmacophore model, simulation

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9308 A Practical and Efficient Evaluation Function for 3D Model Based Vehicle Matching

Authors: Yuan Zheng

Abstract:

3D model-based vehicle matching provides a new way for vehicle recognition, localization and tracking. Its key is to construct an evaluation function, also called fitness function, to measure the degree of vehicle matching. The existing fitness functions often poorly perform when the clutter and occlusion exist in traffic scenarios. In this paper, we present a practical and efficient fitness function. Unlike the existing evaluation functions, the proposed fitness function is to study the vehicle matching problem from both local and global perspectives, which exploits the pixel gradient information as well as the silhouette information. In view of the discrepancy between 3D vehicle model and real vehicle, a weighting strategy is introduced to differently treat the fitting of the model’s wireframes. Additionally, a normalization operation for the model’s projection is performed to improve the accuracy of the matching. Experimental results on real traffic videos reveal that the proposed fitness function is efficient and robust to the cluttered background and partial occlusion.

Keywords: 3D-2D matching, fitness function, 3D vehicle model, local image gradient, silhouette information

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9307 Router 1X3 - RTL Design and Verification

Authors: Nidhi Gopal

Abstract:

Routing is the process of moving a packet of data from source to destination and enables messages to pass from one computer to another and eventually reach the target machine. A router is a networking device that forwards data packets between computer networks. It is connected to two or more data lines from different networks (as opposed to a network switch, which connects data lines from one single network). This paper mainly emphasizes upon the study of router device, its top level architecture, and how various sub-modules of router i.e. Register, FIFO, FSM and Synchronizer are synthesized, and simulated and finally connected to its top module.

Keywords: data packets, networking, router, routing

Procedia PDF Downloads 785
9306 Cognitive Footprints: Analytical and Predictive Paradigm for Digital Learning

Authors: Marina Vicario, Amadeo Argüelles, Pilar Gómez, Carlos Hernández

Abstract:

In this paper, the Computer Research Network of the National Polytechnic Institute of Mexico proposes a paradigmatic model for the inference of cognitive patterns in digital learning systems. This model leads to metadata architecture useful for analysis and prediction in online learning systems; especially on MOOc's architectures. The model is in the design phase and expects to be tested through an institutional of courses project which is going to develop for the MOOc.

Keywords: cognitive footprints, learning analytics, predictive learning, digital learning, educational computing, educational informatics

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9305 Experimental Investigation of Air Gap Membrane Distillation System with Heat Recovery

Authors: Yasser Elhenaw, A. Farag, Mohamed El-Ghandour, M. Shatat, G. H. Moustafa

Abstract:

This study investigates the performance of two spiral-wound Air Gap Membrane Distillation (AGMD) units. These units are connected in two different configurations in order to be tested and compared experimentally. In AGMD, the coolant water is used to condensate water vapor leaving membrane via condensing plate. The rejected cooling water has a relativity high temperature which can be used, depending on operation parameters, to increase the thermal efficiency and water productivity. In the first configuration, the seawater feed flows parallel and equally through both units then rejected. The coolant water is divided into the two units, and the heat source is divided into the two heat exchangers. In the second one, only the feed of the first unit is heated while the cooling rejected from the unit is used in heating the feed to the second. The performance of the system, estimated by the water productivity as well as the Gain Output Ratio (GOR), is measured for the two configurations at different feed flow rates, temperatures and salinities. The results show that at steady state condition, the heat recovery configurations lead to an increase in water productivity by 25%.

Keywords: membrane distillation, heat transfer, heat recovery, desalination

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9304 Discrete Group Search Optimizer for the Travelling Salesman Problem

Authors: Raed Alnajjar, Mohd Zakree, Ahmad Nazri

Abstract:

In this study, we apply Discrete Group Search Optimizer (DGSO) for solving Traveling Salesman Problem (TSP). The DGSO is a nature inspired optimization algorithm that imitates the animal behavior, especially animal searching behavior. The proposed DGSO uses a vector representation and some discrete operators, such as destruction, construction, differential evolution, swap and insert. The TSP is a well-known hard combinatorial optimization problem, which seeks to find the shortest path among numbers of cities. The performance of the proposed DGSO is evaluated and tested on benchmark instances which listed in LIBTSP dataset. The experimental results show that the performance of the proposed DGSO is comparable with the other methods in the state of the art for some instances. The results show that DGSO outperform Ant Colony System (ACS) in some instances whilst outperform other metaheuristic in most instances. In addition to that, the new results obtained a number of optimal solutions and some best known results. DGSO was able to obtain feasible and good quality solution across all dataset.

Keywords: discrete group search optimizer (DGSO); Travelling salesman problem (TSP); Variable neighborhood search(VNS)

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9303 Stakeholder Mapping and Requirements Identification for Improving Traceability in the Halal Food Supply Chain

Authors: Laila A. H. F. Dashti, Tom Jackson, Andrew West, Lisa Jackson

Abstract:

Traceability systems are important in the agri-food and halal food sectors for monitoring ingredient movements, tracking sources, and ensuring food integrity. However, designing a traceability system for the halal food supply chain is challenging due to diverse stakeholder requirements and complex needs. Existing literature on stakeholder mapping and identifying requirements for halal food supply chains is limited. To address this gap, a pilot study was conducted to identify the objectives, requirements, and recommendations of stakeholders in the Kuwaiti halal food industry. The study collected data through semi-structured interviews with an international halal food manufacturer based in Kuwait. The aim was to gain a deep understanding of stakeholders' objectives, requirements, processes, and concerns related to the design of a traceability system in the country's halal food sector. Traceability systems are being developed and tested in the agri-food and halal food sectors due to their ability to monitor ingredient movements, track sources, and detect potential issues related to food integrity. Designing a traceability system for the halal food supply chain poses significant challenges due to diverse stakeholder requirements and the complexity of their needs (including varying food ingredients, different sources, destinations, supplier processes, certifications, etc.). Achieving a halal food traceability solution tailored to stakeholders' requirements within the supply chain necessitates prior knowledge of these needs. Although attempts have been made to address design-related issues in traceability systems, literature on stakeholder mapping and identification of requirements specific to halal food supply chains is scarce. Thus, this pilot study aims to identify the objectives, requirements, and recommendations of stakeholders in the halal food industry. The paper presents insights gained from the pilot study, which utilized semi-structured interviews to collect data from a Kuwait-based international halal food manufacturer. The objective was to gain an in-depth understanding of stakeholders' objectives, requirements, processes, and concerns pertaining to the design of a traceability system in Kuwait's halal food sector. The stakeholder mapping results revealed that government entities, food manufacturers, retailers, and suppliers are key stakeholders in Kuwait's halal food supply chain. Lessons learned from this pilot study regarding requirement capture for traceability systems include the need to streamline communication, focus on communication at each level of the supply chain, leverage innovative technologies to enhance process structuring and operations and reduce halal certification costs. The findings also emphasized the limitations of existing traceability solutions, such as limited cooperation and collaboration among stakeholders, high costs of implementing traceability systems without government support, lack of clarity regarding product routes, and disrupted communication channels between stakeholders. These findings contribute to a broader research program aimed at developing a stakeholder requirements framework that utilizes "business process modelling" to establish a unified model for traceable stakeholder requirements.

Keywords: supply chain, traceability system, halal food, stakeholders’ requirements

Procedia PDF Downloads 91
9302 An Approach towards Smart Future: Ict Infrastructure Integrated into Urban Water Networks

Authors: Ahsan Ali, Mayank Ostwal, Nikhil Agarwal

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Abstract—According to a World Bank report, millions of people across the globe still do not have access to improved water services. With uninterrupted growth of cities and urban inhabitants, there is a mounting need to safeguard the sustainable expansion of cities. Efficient functioning of the urban components and high living standards of the residents are needed to be ensured. The water and sanitation network of an urban development is one of its most essential parts of its critical infrastructure. The growth in urban population is leading towards increased water demand, and thus, the local water resources are severely strained. 'Smart water' is referred to water and waste water infrastructure that is able to manage the limited resources and the energy used to transport it. It enables the sustainable consumption of water resources through co-ordinate water management system, by integrating Information Communication Technology (ICT) solutions, intended at maximizing the socioeconomic benefits without compromising the environmental values. This paper presents a case study from a medium sized city in North-western Pakistan. Currently, water is getting contaminated due to the proximity between water and sewer pipelines in the study area, leading to public health issues. Due to unsafe grey water infiltration, the scarce ground water is also getting polluted. This research takes into account the design of smart urban water network by integrating ICT (Information and Communication Technology) with urban water network. The proximity between the existing water supply network and sewage network is analyzed and a design of new water supply system is proposed. Real time mapping of the existing urban utility networks will be projected with the help of GIS applications. The issue of grey water infiltration is addressed by providing sustainable solutions with the help of locally available materials, keeping in mind the economic condition of the area. To deal with the current growth of urban population, it is vital to develop new water resources. Hence, distinctive and cost effective procedures to harness rain water would be suggested as a part of the research study experiment.

Keywords: GIS, smart water, sustainability, urban water management

Procedia PDF Downloads 196
9301 Hygrothermal Interactions and Energy Consumption in Cold Climate Hospitals: Integrating Numerical Analysis and Case Studies to Investigate and Analyze the Impact of Air Leakage and Vapor Retarding

Authors: Amir E. Amirzadeh, Richard K. Strand

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Moisture-induced problems are a significant concern for building owners, architects, construction managers, and building engineers, as they can have substantial impacts on building enclosures' durability and performance. Computational analyses, such as hygrothermal and thermal analysis, can provide valuable information and demonstrate the expected relative performance of building enclosure systems but are not grounded in absolute certainty. This paper evaluates the hygrothermal performance of common enclosure systems in hospitals in cold climates. The study aims to investigate the impact of exterior wall systems on hospitals, focusing on factors such as durability, construction deficiencies, and energy performance. The study primarily examines the impact of air leakage and vapor retarding layers relative to energy consumption. While these factors have been studied in residential and commercial buildings, there is a lack of information on their impact on hospitals in a holistic context. The study integrates various research studies and professional experience in hospital building design to achieve its objective. The methodology involves surveying and observing exterior wall assemblies, reviewing common exterior wall assemblies and details used in hospital construction, performing simulations and numerical analyses of various variables, validating the model and mechanism using available data from industry and academia, visualizing the outcomes of the analysis, and developing a mechanism to demonstrate the relative performance of exterior wall systems for hospitals under specific conditions. The data sources include case studies from real-world projects and peer-reviewed articles, industry standards, and practices. This research intends to integrate and analyze the in-situ and as-designed performance and durability of building enclosure assemblies with numerical analysis. The study's primary objective is to provide a clear and precise roadmap to better visualize and comprehend the correlation between the durability and performance of common exterior wall systems used in the construction of hospitals and the energy consumption of these buildings under certain static and dynamic conditions. As the construction of new hospitals and renovation of existing ones have grown over the last few years, it is crucial to understand the effect of poor detailing or construction deficiencies on building enclosure systems' performance and durability in healthcare buildings. This study aims to assist stakeholders involved in hospital design, construction, and maintenance in selecting durable and high-performing wall systems. It highlights the importance of early design evaluation, regular quality control during the construction of hospitals, and understanding the potential impacts of improper and inconsistent maintenance and operation practices on occupants, owner, building enclosure systems, and Heating, Ventilation, and Air Conditioning (HVAC) systems, even if they are designed to meet the project requirements.

Keywords: hygrothermal analysis, building enclosure, hospitals, energy efficiency, optimization and visualization, uncertainty and decision making

Procedia PDF Downloads 56
9300 Keyloggers Prevention with Time-Sensitive Obfuscation

Authors: Chien-Wei Hung, Fu-Hau Hsu, Chuan-Sheng Wang, Chia-Hao Lee

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Nowadays, the abuse of keyloggers is one of the most widespread approaches to steal sensitive information. In this paper, we propose an On-Screen Prompts Approach to Keyloggers (OSPAK) and its analysis, which is installed in public computers. OSPAK utilizes a canvas to cue users when their keystrokes are going to be logged or ignored by OSPAK. This approach can protect computers against recoding sensitive inputs, which obfuscates keyloggers with letters inserted among users' keystrokes. It adds a canvas below each password field in a webpage and consists of three parts: two background areas, a hit area and a moving foreground object. Letters at different valid time intervals are combined in accordance with their time interval orders, and valid time intervals are interleaved with invalid time intervals. It utilizes animation to visualize valid time intervals and invalid time intervals, which can be integrated in a webpage as a browser extension. We have tested it against a series of known keyloggers and also performed a study with 95 users to evaluate how easily the tool is used. Experimental results made by volunteers show that OSPAK is a simple approach.

Keywords: authentication, computer security, keylogger, privacy, information leakage

Procedia PDF Downloads 104
9299 Numerical Investigation of Embankments for Protecting Rock Fall

Authors: Gökhan Altay, Cafer Kayadelen

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Rock fall is a movement of huge rock blocks from dip slopes due to physical effects. It generally occurs where loose tuffs lying under basalt flow or stringcourse is being constituted by limestone layers which stand on clay. By corrosion of some parts, big cracks occur on layers and these cracks continue to grow with the effect of freezing-thawing. In this way, the breaking rocks fall down from these dip slopes. Earthquakes which can induce lots of rock movements is another reason for rock fall events. In Turkey, we have a large number of regions prone to the earthquake as in the World so this increases the possibility of rock fall events. A great number of rock fall events take place in Turkey as in the World every year. The rock fall events occurring in urban areas cause serious damages in houses, roads and workplaces. Sometimes it also hinders transportation and furthermore it maybe kills people. In Turkey, rock fall events happen mostly in Spring and Winter because of freezing- thawing of water in rock cracks frequently. In mountain and inclined areas, rock fall is risky for engineering construction and environment. Some countries can invest significant money for these risky areas. For instance, in Switzerland, approximately 6.7 million dollars is spent annually for a distance of 4 km, to the systems to prevent rock fall events. In Turkey, we have lots of urban areas and engineering structure that have the rock fall risk. The embankments are preferable for rock fall events because of its low maintenance and repair costs. Also, embankments are able to absorb much more energy according to other protection systems. The current design method of embankments is only depended on field tests results so there are inadequate studies about this design method. In this paper, the field test modeled in three dimensions and analysis are carried out with the help of ANSYS programme. By the help of field test from literature the numerical model validated. After the validity of numerical models additional parametric studies performed. Changes in deformation of embankments are investigated by the changes in, geometry, velocity and impact height of falling rocks.

Keywords: ANSYS, embankment, impact height, numerical analysis, rock fall

Procedia PDF Downloads 497
9298 A Procedure for Post-Earthquake Damage Estimation Based on Detection of High-Frequency Transients

Authors: Aleksandar Zhelyazkov, Daniele Zonta, Helmut Wenzel, Peter Furtner

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In the current research structural health monitoring is considered for addressing the critical issue of post-earthquake damage detection. A non-standard approach for damage detection via acoustic emission is presented - acoustic emissions are monitored in the low frequency range (up to 120 Hz). Such emissions are termed high-frequency transients. Further a damage indicator defined as the Time-Ratio Damage Indicator is introduced. The indicator relies on time-instance measurements of damage initiation and deformation peaks. Based on the time-instance measurements a procedure for estimation of the maximum drift ratio is proposed. Monitoring data is used from a shaking-table test of a full-scale reinforced concrete bridge pier. Damage of the experimental column is successfully detected and the proposed damage indicator is calculated.

Keywords: acoustic emission, damage detection, shaking table test, structural health monitoring

Procedia PDF Downloads 215
9297 Anti-Oxidant and Anti-Bacterial Properties of Camellia sinensis, Tea Plant

Authors: Rini Jarial, Puranjan Mishra, Lakhveer Singh, Sveta Thakur, A. W. Zularisam, Mimi Sakinah

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The aim of the present study was to assess the biological properties of Camellia sinensis and to identify its functional compounds. The methanolic leaves-extract (MLE) of commercial green tea (Camellia sinensis) was assessed for anti-bacterial activities by measuring inhibition zones against a panel of pathogenic bacterial strains using agar diffusion method. The flavonoid (5.0 to 8.0 mg/ml) and protein content (10 to 15 mg/ml) of the MLE were recorded. MLE at a concentration of 25 μg/ml showed marked anti-bacterial activity against all bacterial strains (11-30 mm zone of inhibition) and was maximum against Staphylococcus aureus (30 mm). The MLE of Camellia sinensis had the best MIC values of 2.25 and 0.56 mg/ml against S. aureus and Enterobacter sp., respectively. The MLE also possessed good anti-lipolytic activity (65%) against a Porcine pancreatic lipase (PPL) and cholesterol oxidase inhibition (79%). The present study provided strong experimental evidences that the MLE of Camellia sinensis is not only a potent source of natural anti-oxidants and anti-bacterial activity but also possesses efficient cholesterol degradation and anti-lipolytic activities that might be beneficial in the body weight management.

Keywords: anti-oxidant, anti-bacterial activity, anti-lipolytic activity, Camellia sinensis, phyto-chemicals

Procedia PDF Downloads 275