Search results for: random routing optimization technique
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11050

Search results for: random routing optimization technique

9070 Molecular and Electronic Structure of Chromium (III) Cyclopentadienyl Complexes

Authors: Salem El-Tohami Ashoor

Abstract:

Here we show that the reduction of [Cr(ArN(CH2)3NAr)2Cl2] (1) where (Ar = 2,6-Pri2C6H3) and in presence of NaCp (2) (Cp= C5H5 = cyclopentadien), with a center coordination η5 interaction between Cp as co-ligand and chromium metal center, this was optimization by using density functional theory (DFT) and then was comparing with experimental data, also other possibility of Cp interacted with ion metal were tested like η1 ,η2 ,η3 and η4 under optimization system. These were carried out under investigation of density functional theory (DFT) calculation, and comparing together. Other methods, explicitly including electron correlation, are necessary for more accurate calculations; MB3LYP ( Becke)( Lee–Yang–Parr ) level of theory often being used to obtain more exact results. These complexes were estimated of electronic energy for molecular system, because it accounts for all electron correlation interactions. The optimised of [Cr(ArN(CH2)3NAr)2(η5-Cp)] (Ar = 2,6-Pri2C6H3 and Cp= C5H5) was found to be thermally more stable than others of chromium cyclopentadienyl. By using Dewar-Chatt-Duncanson model, as a basis of the molecular orbital (MO) analysis and showed the highest occupied molecular orbital (HOMO) and lowest occupied molecular orbital LUMO.

Keywords: Chromium(III) cyclopentadienyl complexes, DFT, MO, HOMO, LUMO

Procedia PDF Downloads 490
9069 Electrocardiogram Signal Denoising Using a Hybrid Technique

Authors: R. Latif, W. Jenkal, A. Toumanari, A. Hatim

Abstract:

This paper presents an efficient method of electrocardiogram signal denoising based on a hybrid approach. Two techniques are brought together to create an efficient denoising process. The first is an Adaptive Dual Threshold Filter (ADTF) and the second is the Discrete Wavelet Transform (DWT). The presented approach is based on three steps of denoising, the DWT decomposition, the ADTF step and the highest peaks correction step. This paper presents some application of the approach on some electrocardiogram signals of the MIT-BIH database. The results of these applications are promising compared to other recently published techniques.

Keywords: hybrid technique, ADTF, DWT, thresholding, ECG signal

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9068 Utilization of Mustard Leaves (Brassica juncea) Powder for the Development of Cereal Based Extruded Snacks

Authors: Maya S. Rathod, Bahadur Singh Hathan

Abstract:

Mustard leaves are rich in folates, vitamin A, K and B-complex. Mustard greens are low in calories and fats and rich in dietary fiber. They are rich in potassium, manganese, iron, copper, calcium, magnesium and low in sodium. It is very rich in antioxidants and Phytonutrients. For the optimization of process variables (moisture content and mustard leave powder), the experiments were conducted according to central composite Face Centered Composite design of RSM. The mustard leaves powder was replaced with composite flour (a combination of rice, chickpea and corn in the ratio of 70:15:15). The extrudate was extruded in a twin screw extruder at a barrel temperature of 120°C. The independent variables were mustard leaves powder (2-10 %) and moisture content (12-20 %). Responses analyzed were bulk density, water solubility index, water absorption index, lateral expansion, hardness, antioxidant activity, total phenolic content and overall acceptability. The optimum conditions obtained were 7.19 g mustard leaves powder in 100 g premix having 16.8 % moisture content (w.b).

Keywords: extrusion, mustard leaves powder, optimization, response surface methodology

Procedia PDF Downloads 528
9067 Enhancing Protein Incorporation in Calcium Phosphate Coating on Titanium by Rapid Biomimetic Co-Precipitation Technique

Authors: J. Suwanprateeb, F. Thammarakcharoen

Abstract:

Calcium phosphate coating (CaP) has been employed for protein delivery, but the typical direct protein adsorption on the coating led to low incorporation content and fast release of the protein from the coating. By using bovine serum albumin (BSA) as a model protein, rapid biomimetic co-precipitation between calcium phosphate and BSA was employed to control the distribution of BSA within calcium phosphate coating during biomimetic formation on titanium surface for only 6 h at 50 oC in an accelerated calcium phosphate solution. As a result, the amount of BSA incorporation and release duration could be increased by using a rapid biomimetic co-precipitation technique. Up to 43 fold increases in the BSA incorporation content and the increase from 6 h to more than 360 h in release duration compared to typical direct adsorption technique were observed depending on the initial BSA concentration used during co-precipitation (1, 10, and 100 microgram/ml). From X-ray diffraction and Fourier transform infrared spectroscopy studies, the coating composition was not altered with the incorporation of BSA by this rapid biomimetic co-precipitation and mainly comprised octacalcium phosphate and hydroxyapatite. However, the microstructure of calcium phosphate crystals changed from straight, plate-like units to curved, plate-like units with increasing BSA content.

Keywords: biomimetic, Calcium Phosphate Coating, protein, titanium

Procedia PDF Downloads 374
9066 Communication in a Heterogeneous Ad Hoc Network

Authors: C. Benjbara, A. Habbani

Abstract:

Wireless networks are getting more and more used in every new technology or feature, especially those without infrastructure (Ad hoc mode) which provide a low cost alternative to the infrastructure mode wireless networks and a great flexibility for application domains such as environmental monitoring, smart cities, precision agriculture, and so on. These application domains present a common characteristic which is the need of coexistence and intercommunication between modules belonging to different types of ad hoc networks like wireless sensor networks, mesh networks, mobile ad hoc networks, vehicular ad hoc networks, etc. This vision to bring to life such heterogeneous networks will make humanity duties easier but its development path is full of challenges. One of these challenges is the communication complexity between its components due to the lack of common or compatible protocols standard. This article proposes a new patented routing protocol based on the OLSR standard in order to resolve the heterogeneous ad hoc networks communication issue. This new protocol is applied on a specific network architecture composed of MANET, VANET, and FANET.

Keywords: Ad hoc, heterogeneous, ID-Node, OLSR

Procedia PDF Downloads 199
9065 Modeling and Optimization of Performance of Four Stroke Spark Ignition Injector Engine

Authors: A. A. Okafor, C. H. Achebe, J. L. Chukwuneke, C. G. Ozoegwu

Abstract:

The performance of an engine whose basic design parameters are known can be predicted with the assistance of simulation programs into the less time, cost and near value of actual. This paper presents a comprehensive mathematical model of the performance parameters of four stroke spark ignition engine. The essence of this research work is to develop a mathematical model for the analysis of engine performance parameters of four stroke spark ignition engine before embarking on full scale construction, this will ensure that only optimal parameters are in the design and development of an engine and also allow to check and develop the design of the engine and it’s operation alternatives in an inexpensive way and less time, instead of using experimental method which requires costly research test beds. To achieve this, equations were derived which describe the performance parameters (sfc, thermal efficiency, mep and A/F). The equations were used to simulate and optimize the engine performance of the model for various engine speeds. The optimal values obtained for the developed bivariate mathematical models are: sfc is 0.2833kg/kwh, efficiency is 28.77% and a/f is 20.75.

Keywords: bivariate models, engine performance, injector engine, optimization, performance parameters, simulation, spark ignition

Procedia PDF Downloads 315
9064 Initial Dip: An Early Indicator of Neural Activity in Functional Near Infrared Spectroscopy Waveform

Authors: Mannan Malik Muhammad Naeem, Jeong Myung Yung

Abstract:

Functional near infrared spectroscopy (fNIRS) has a favorable position in non-invasive brain imaging techniques. The concentration change of oxygenated hemoglobin and de-oxygenated hemoglobin during particular cognitive activity is the basis for this neuro-imaging modality. Two wavelengths of near-infrared light can be used with modified Beer-Lambert law to explain the indirect status of neuronal activity inside brain. The temporal resolution of fNIRS is very good for real-time brain computer-interface applications. The portability, low cost and an acceptable temporal resolution of fNIRS put it on a better position in neuro-imaging modalities. In this study, an optimization model for impulse response function has been used to estimate/predict initial dip using fNIRS data. In addition, the activity strength parameter related to motor based cognitive task has been analyzed. We found an initial dip that remains around 200-300 millisecond and better localize neural activity.

Keywords: fNIRS, brain-computer interface, optimization algorithm, adaptive signal processing

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9063 Selection of Optimal Reduced Feature Sets of Brain Signal Analysis Using Heuristically Optimized Deep Autoencoder

Authors: Souvik Phadikar, Nidul Sinha, Rajdeep Ghosh

Abstract:

In brainwaves research using electroencephalogram (EEG) signals, finding the most relevant and effective feature set for identification of activities in the human brain is a big challenge till today because of the random nature of the signals. The feature extraction method is a key issue to solve this problem. Finding those features that prove to give distinctive pictures for different activities and similar for the same activities is very difficult, especially for the number of activities. The performance of a classifier accuracy depends on this quality of feature set. Further, more number of features result in high computational complexity and less number of features compromise with the lower performance. In this paper, a novel idea of the selection of optimal feature set using a heuristically optimized deep autoencoder is presented. Using various feature extraction methods, a vast number of features are extracted from the EEG signals and fed to the autoencoder deep neural network. The autoencoder encodes the input features into a small set of codes. To avoid the gradient vanish problem and normalization of the dataset, a meta-heuristic search algorithm is used to minimize the mean square error (MSE) between encoder input and decoder output. To reduce the feature set into a smaller one, 4 hidden layers are considered in the autoencoder network; hence it is called Heuristically Optimized Deep Autoencoder (HO-DAE). In this method, no features are rejected; all the features are combined into the response of responses of the hidden layer. The results reveal that higher accuracy can be achieved using optimal reduced features. The proposed HO-DAE is also compared with the regular autoencoder to test the performance of both. The performance of the proposed method is validated and compared with the other two methods recently reported in the literature, which reveals that the proposed method is far better than the other two methods in terms of classification accuracy.

Keywords: autoencoder, brainwave signal analysis, electroencephalogram, feature extraction, feature selection, optimization

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9062 Peak Frequencies in the Collective Membrane Potential of a Hindmarsh-Rose Small-World Neural Network

Authors: Sun Zhe, Ruggero Micheletto

Abstract:

As discussed extensively in many studies, noise in neural networks have an important role in the functioning and time evolution of the system. The mechanism by which noise induce stochastic resonance enhancing and influencing certain operations is not clarified nor is the mechanism of information storage and coding. With the present research we want to study the role of noise, especially focusing on the frequency peaks in a three variable Hindmarsh−Rose Small−World network. We investigated the behaviour of the network to external noises. We demonstrate that a variation of signal to noise ratio of about 10 dB induces an increase in membrane potential signal of about 15%, averaged over the whole network. We also considered the integral of the whole membrane potential as a paradigm of internal noise, the one generated by the brain network. We showed that this internal noise is attenuated with the size of the network or with the number of random connections. By means of Fourier analysis we found that it has distinct peaks of frequencies, moreover, we showed that increasing the size of the network introducing more neurons, reduced the maximum frequencies generated by the network, whereas the increase in the number of random connections (determined by the small-world probability p) led to a trend toward higher frequencies. This study may give clues on how networks utilize noise to alter the collective behaviour of the system in their operations.

Keywords: neural networks, stochastic processes, small-world networks, discrete Fourier analysis

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9061 Improved Predictive Models for the IRMA Network Using Nonlinear Optimisation

Authors: Vishwesh Kulkarni, Nikhil Bellarykar

Abstract:

Cellular complexity stems from the interactions among thousands of different molecular species. Thanks to the emerging fields of systems and synthetic biology, scientists are beginning to unravel these regulatory, signaling, and metabolic interactions and to understand their coordinated action. Reverse engineering of biological networks has has several benefits but a poor quality of data combined with the difficulty in reproducing it limits the applicability of these methods. A few years back, many of the commonly used predictive algorithms were tested on a network constructed in the yeast Saccharomyces cerevisiae (S. cerevisiae) to resolve this issue. The network was a synthetic network of five genes regulating each other for the so-called in vivo reverse-engineering and modeling assessment (IRMA). The network was constructed in S. cereviase since it is a simple and well characterized organism. The synthetic network included a variety of regulatory interactions, thus capturing the behaviour of larger eukaryotic gene networks on a smaller scale. We derive a new set of algorithms by solving a nonlinear optimization problem and show how these algorithms outperform other algorithms on these datasets.

Keywords: synthetic gene network, network identification, optimization, nonlinear modeling

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9060 Numerical Buckling of Composite Cylindrical Shells under Axial Compression Using Asymmetric Meshing Technique (AMT)

Authors: Zia R. Tahir, P. Mandal

Abstract:

This paper presents the details of a numerical study of buckling and post buckling behaviour of laminated carbon fiber reinforced plastic (CFRP) thin-walled cylindrical shell under axial compression using asymmetric meshing technique (AMT) by ABAQUS. AMT is considered to be a new perturbation method to introduce disturbance without changing geometry, boundary conditions or loading conditions. Asymmetric meshing affects both predicted buckling load and buckling mode shapes. Cylindrical shell having lay-up orientation [0°/+45°/-45°/0°] with radius to thickness ratio (R/t) equal to 265 and length to radius ratio (L/R) equal to 1.5 is analysed numerically. A series of numerical simulations (experiments) are carried out with symmetric and asymmetric meshing to study the effect of asymmetric meshing on predicted buckling behaviour. Asymmetric meshing technique is employed in both axial direction and circumferential direction separately using two different methods, first by changing the shell element size and varying the total number elements, and second by varying the shell element size and keeping total number of elements constant. The results of linear analysis (Eigenvalue analysis) and non-linear analysis (Riks analysis) using symmetric meshing agree well with analytical results. The results of numerical analysis are presented in form of non-dimensional load factor, which is the ratio of buckling load using asymmetric meshing technique to buckling load using symmetric meshing technique. Using AMT, load factor has about 2% variation for linear eigenvalue analysis and about 2% variation for non-linear Riks analysis. The behaviour of load end-shortening curve for pre-buckling is same for both symmetric and asymmetric meshing but for asymmetric meshing curve behaviour in post-buckling becomes extraordinarily complex. The major conclusions are: different methods of AMT have small influence on predicted buckling load and significant influence on load displacement curve behaviour in post buckling; AMT in axial direction and AMT in circumferential direction have different influence on buckling load and load displacement curve in post-buckling.

Keywords: CFRP composite cylindrical shell, asymmetric meshing technique, primary buckling, secondary buckling, linear eigenvalue analysis, non-linear riks analysis

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9059 Coating of Polyelectrolyte Multilayer Thin Films on Poly(S/EGDMA) HIPE Loaded with Hydroxyapatite as a Scaffold for Tissue Engineering Application

Authors: Kornkanok Noulta, Pornsri Pakeyangkoon, Stephen T. Dubas, Pomthong Malakul, Manit Nithithanakul

Abstract:

In recent years, interest in the development of material for tissue engineering application has increased considerably. Poly(High Internal Phase Emulsion) (PolyHIPE) foam is a material that is good candidate for used in tissue engineering application due to its 3D structure and highly porous with interconnected pore. The PolyHIPE was prepared from poly (styrene/ethylene glycol dimethacrylate) through high internal phase emulsion polymerization technique and loaded with hydroxyapatite (HA) to improve biocompatibility. To further increase hydrophilicity of the obtained polyHIPE, layer-by-layer polyelectrolyte multilayers (PEM) technique was used. A surface property of polyHIPE was characterized by contact angle measurement. Morphology and pore size was observed by scanning electron microscope (SEM). The cell viability was revealed by the 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) assay technique.

Keywords: polyelectrolyte multilayer thin film, high internal phase emulsion, polyhipe foam, scaffold, tissue engineering

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9058 Silymarin Loaded Mesoporous Silica Nanoparticles: Preparation, Optimization, Pharmacodynamic and Oral Multi-Dose Safety Assessment

Authors: Sarah Nasr, Maha M. A. Nasra, Ossama Y. Abdallah

Abstract:

The present work aimed to prepare Silymarin loaded MCM-41 type mesoporous silica nanoparticles (MSNs) and to assess the system’s solubility enhancement ability on the pharmacodynamic performance of Silymarin as a hepatoprotective agent. MSNs prepared by soft-templating technique, were loaded with Silymarin, characterized for particle size, zeta potential, surface properties, DSC and XRPD. DSC and specific surface area data confirmed deposition of Silymarin in an amorphous state in MSNs’ pores. In-vitro drug dissolution testing displayed enhanced dissolution rate of Silymarin upon loading on MSNs. High dose Acetaminophen was then used to inflict hepatic injury upon albino male Wistar rats simultaneously receiving either free Silymarin, Silymarin loaded MSNs or blank MSNs. Plasma AST, ALT, albumin and total protein and liver homogenate content of TBARs or LDH as measures of antioxidant drug action were assessed for all animal groups. Results showed a significant superiority of Silymarin loaded MSNs to free drug in almost all parameters. Meanwhile prolonged administration of blank MSNs had no evident toxicity on rats.

Keywords: mesoporous silica nanoparticles, safety, solubility enhancement, silymarin

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9057 Drying and Transport Processes in Distributed Hydrological Modelling Based on Finite Volume Schemes (Iber Model)

Authors: Carlos Caro, Ernest Bladé, Pedro Acosta, Camilo Lesmes

Abstract:

The drying-wet process is one of the topics to be more careful in distributed hydrological modeling using finite volume schemes as a means of solving the equations of Saint Venant. In a hydrologic and hydraulic computer model, surface flow phenomena depend mainly on the different flow accumulation and subsequent runoff generation. These accumulations are generated by routing, cell by cell, from the heights of water, which begin to appear due to the rain at each instant of time. Determine when it is considered a dry cell and when considered wet to include in the full calculation is an issue that directly affects the quantification of direct runoff or generation of flow at the end of a zone of contribution by accumulations flow generated from cells or finite volume.

Keywords: hydrology, transport processes, hydrological modelling, finite volume schemes

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9056 Methodology of Construction Equipment Optimization for Earthwork

Authors: Jaehyun Choi, Hyunjung Kim, Namho Kim

Abstract:

Earthwork is one of the critical civil construction operations that require large-quantities of resources due to its intensive dependency upon construction equipment. Therefore, efficient construction equipment management can highly contribute to productivity improvements and cost savings. Earthwork operation utilizes various combinations of construction equipment in order to meet project requirements such as time and cost. Identification of site condition and construction methods should be performed in advance in order to develop a proper execution plan. The factors to be considered include capacity of equipment assigned, the method of construction, the size of the site, and the surrounding condition. In addition, optimal combination of various construction equipment should be selected. However, in real world practice, equipment utilization plan is performed based on experience and intuition of management. The researchers evaluated the efficiency of various alternatives of construction equipment combinations by utilizing the process simulation model, validated the model from a case study project, and presented a methodology to find optimized plan among alternatives.

Keywords: earthwork operation, construction equipment, process simulation, optimization

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9055 The Excess Loop Delay Calibration in a Bandpass Continuous-Time Delta Sigma Modulators Based on Q-Enhanced LC Filter

Authors: Sorore Benabid

Abstract:

The Q-enhanced LC filters are the most used architecture in the Bandpass (BP) Continuous-Time (CT) Delta-Sigma (ΣΔ) modulators, due to their: high frequencies operation, high linearity than the active filters and a high quality factor obtained by Q-enhanced technique. This technique consists of the use of a negative resistance that compensate the ohmic losses in the on-chip inductor. However, this technique introduces a zero in the filter transfer function which will affect the modulator performances in term of Dynamic Range (DR), stability and in-band noise (Signal-to-Noise Ratio (SNR)). In this paper, we study the effect of this zero and we demonstrate that a calibration of the excess loop delay (ELD) is required to ensure the best performances of the modulator. System level simulations are done for a 2ndorder BP CT (ΣΔ) modulator at a center frequency of 300MHz. Simulation results indicate that the optimal ELD should be reduced by 13% to achieve the maximum SNR and DR compared to the ideal LC-based ΣΔ modulator.

Keywords: continuous-time bandpass delta-sigma modulators, excess loop delay, on-chip inductor, Q-enhanced LC filter

Procedia PDF Downloads 317
9054 Quantum Inspired Security on a Mobile Phone

Authors: Yu Qin, Wanjiaman Li

Abstract:

The widespread use of mobile electronic devices increases the complexities of mobile security. This thesis aims to provide a secure communication environment for smartphone users. Some research proves that the one-time pad is one of the securest encryption methods, and that the key distribution problem can be solved by using the QKD (quantum key distribution). The objective of this project is to design an Android APP (application) to exchange several random keys between mobile phones. Inspired by QKD, the developed APP uses the quick response (QR) code as a carrier to dispatch large amounts of one-time keys. After evaluating the performance of APP, it allows the mobile phone to capture and decode 1800 bytes of random data in 600ms. The continuous scanning mode of APP is designed to improve the overall transmission performance and user experience, and the maximum transmission rate of this mode is around 2200 bytes/s. The omnidirectional readability and error correction capability of QR code gives it a better real-life application, and the features of adequate storage capacity and quick response optimize overall transmission efficiency. The security of this APP is guaranteed since QR code is exchanged face-to-face, eliminating the risk of being eavesdropped. Also, the id of QR code is the only message that would be transmitted through the whole communication. The experimental results show this project can achieve superior transmission performance, and the correlation between the transmission rate of the system and several parameters, such as the QR code size, has been analyzed. In addition, some existing technologies and the main findings in the context of the project are summarized and critically compared in detail.

Keywords: one-time pad, QKD (quantum key distribution), QR code, application

Procedia PDF Downloads 138
9053 Adsorption of Cerium as One of the Rare Earth Elements Using Multiwall Carbon Nanotubes from Aqueous Solution: Modeling, Equilibrium and Kinetics

Authors: Saeb Ahmadi, Mohsen Vafaie Sefti, Mohammad Mahdi Shadman, Ebrahim Tangestani

Abstract:

Carbon nanotube has shown great potential for the removal of various inorganic and organic components due to properties such as large surface area and high adsorption capacity. Central composite design is widely used method for determining optimal conditions. Also due to the economic reasons and wide application, the rare earth elements are important components. The analyses of cerium (Ce(III)) adsorption as one of the Rare Earth Elements (REEs) adsorption on Multiwall Carbon Nanotubes (MWCNTs) have been studied. The optimization process was performed using Response Surface Methodology (RSM). The optimum amount conditions were pH of 4.5, initial Ce (III) concentration of 90 mg/l and MWCNTs dosage of 80 mg. Under this condition, the optimum adsorption percentage of Ce (III) was obtained about 96%. Next, at the obtained optimum conditions the kinetic and isotherm studied and result showed the pseudo-second order and Langmuir isotherm are more fitted with experimental data than other models.

Keywords: cerium, rare earth element, MWCNTs, adsorption, optimization

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9052 Optimization of Temperature for Crystal Violet Dye Adsorption Using Castor Leaf Powder by Response Surface Methodology

Authors: Vipan Kumar Sohpal

Abstract:

Temperature effect on the adsorption of crystal violet dye (CVD) was investigated using a castor leaf powder (CLP) that was prepared from the mature leaves of castor trees, through chemical reaction. The optimum values of pH (8), adsorbent dose (10g/L), initial dye concentration (10g/L), time (2hrs), and stirrer speed (120 rpm) were fixed to investigate the influence of temperature on adsorption capacity, percentage of removal of dye and free energy. A central composite design (CCD) was successfully employed for experimental design and analysis of the results. The combined effect of temperature, absorbance, and concentration on the dye adsorption was studied and optimized using response surface methodology. The optimum values of adsorption capacity, percentage of removal of dye and free energy were found to be 0.965(mg/g), 93.38 %, -8202.7(J/mol) at temperature 55.97 °C having desirability > 90% for removal of crystal violet dye respectively. The experimental values were in good agreement with predicted values.

Keywords: crystal violet dye, CVD, castor leaf powder, CLP, response surface methodology, temperature, optimization

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9051 Effect of E-Governance and E-Learning Platform on Access to University Education by Public Servants in Nigeria

Authors: Nwamaka Patricia Ibeme, Musa Zakari

Abstract:

E-learning is made more effective because; it is enable student to students to easily interact, share, and collaborate across time and space with the help of e-governance platform. Zoom and the Microsoft classroom team can invite students from all around the world to join a conversation on a certain subject simultaneously. E-governance may be able to work on problem solving skills, as well as brainstorming and developing ideas. As a result of the shared experiences and knowledge, students are able to express themselves and reflect on their own learning." For students, e-governance facilities provide greater opportunity for students to build critical (higher order) thinking abilities through constructive learning methods. Students' critical thinking abilities may improve with more time spent in an online classroom. Students' inventiveness can be enhanced through the use of computer-based instruction. Discover multimedia tools and produce products in the styles that are easily available through games, Compact Disks, and television. The use of e-learning has increased both teaching and learning quality by combining student autonomy, capacity, and creativity over time in developed countries." Teachers are catalysts for the integration of technology through Information and Communication Technology, and e-learning supports teaching by simplifying access to course content." Creating an Information and Communication Technology class will be much easier if educational institutions provide teachers with the assistance, equipment, and resources they need. The study adopted survey research design. The populations of the study are Students and staff. The study adopted a simple random sampling technique to select a representative population. Both primary and secondary method of data collection was used to obtain the data. A chi-square statistical technique was used to analyze. Finding from the study revealed that e-learning has increase accesses to universities educational by public servants in Nigeria. Public servants in Nigeria have utilized e-learning and Online Distance Learning (ODL) programme to into various degree programmes. Finding also shows that E-learning plays an important role in teaching because it is oriented toward the use of information and communication technologies that have become a part of the everyday life and day-to-day business. E-learning contributes to traditional teaching methods and provides many advantages to society and citizens. The study recommends that the e-learning tools and internet facilities should be upgrade to foster any network challenges in the online facilitation and lecture delivery system.

Keywords: E-governance, E-learning, online distance learning, university education public servants, Nigeria

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9050 Emotional Intelligence as Predictor of Academic Success among Third Year College Students of PIT

Authors: Sonia Arradaza-Pajaron

Abstract:

College students are expected to engage in an on-the-job training or internship for completion of a course requirement prior to graduation. In this scenario, they are exposed to the real world of work outside their training institution. To find out their readiness both emotionally and academically, this study has been conducted. A descriptive-correlational research design was employed and random sampling technique method was utilized among 265 randomly selected third year college students of PIT, SY 2014-15. A questionnaire on Emotional Intelligence (bearing the four components namely; emotional literacy, emotional quotient competence, values and beliefs and emotional quotient outcomes) was fielded to the respondents and GWA was extracted from the school automate. Data collected were statistically treated using percentage, weighted mean and Pearson-r for correlation. Results revealed that respondents’ emotional intelligence level is moderately high while their academic performance is good. A high significant relationship was found between the EI component; Emotional Literacy and their academic performance while only significant relationship was found between Emotional Quotient Outcomes and their academic performance. Therefore, if EI influences academic performance significantly when correlated, a possibility that their OJT performance can also be affected either positively or negatively. Thus, EI can be considered predictor of their academic and academic-related performance. Based on the result, it is then recommended that the institution would try to look deeply into the consideration of embedding emotional intelligence as part of the (especially on Emotional Literacy and Emotional Quotient Outcomes of the students) college curriculum. It can be done if the school shall have an effective Emotional Intelligence framework or program manned by qualified and competent teachers, guidance counselors in different colleges in its implementation.

Keywords: academic performance, emotional intelligence, college students, academic success

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9049 Optimal Scheduling of Trains in Complex National Scale Railway Networks

Authors: Sanat Ramesh, Tarun Dutt, Abhilasha Aswal, Anushka Chandrababu, G. N. Srinivasa Prasanna

Abstract:

Optimal Schedule Generation for a large national railway network operating thousands of passenger trains with tens of thousands of kilometers of track is a grand computational challenge in itself. We present heuristics based on a Mixed Integer Program (MIP) formulation for local optimization. These methods provide flexibility in scheduling new trains with varying speed and delays and improve utilization of infrastructure. We propose methods that provide a robust solution with hundreds of trains being scheduled over a portion of the railway network without significant increases in delay. We also provide techniques to validate the nominal schedules thus generated over global correlated variations in travel times thereby enabling us to detect conflicts arising due to delays. Our validation results which assume only the support of the arrival and departure time distributions takes an order of few minutes for a portion of the network and is computationally efficient to handle the entire network.

Keywords: mixed integer programming, optimization, railway network, train scheduling

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9048 Quality Assurance Practices in the Universities of Pakistan: Physical Facilities as Encouragement

Authors: Ijaz Ahamad Tatlah

Abstract:

The justification of this study was to identify about physical facilities as encouragement to Quality Assurance Practices (QAP) in the Universities of Pakistan concerning the views of students, teachers and Directors of Quality Enhancement Cells’ (QEC’s) and to differentiate the views of students, teachers and Directors of QECs in relation to physical facilities about quality assurance practices in the universities of Pakistan. It was a quantitative and qualitative research study. This study was conducted on a sample of 28 universities (public and private sector) of Pakistan by using random and purposive sampling technique. Questionnaires and semi-structured interviews were planned to gather information from students, teachers and Directors of QECs in relation to physical facilities about quality assurance practices in the universities of Pakistan. The data was analyzed by using Descriptive, inferential statistics, and thematic coding. The study revealed that students, teachers and Directors of QEC’s faced a lot of problems and issues without physical facilities. Quality assurance Agency (QAA), Quality Assurance Department (QAD) and Higher Education commission (HEC) all are relevant Pakistani Agencies, which are working consistently of both sectors i.e. public and private to supervise, guide and facilitate the universities of Pakistan for developing quality assurance practices. Majority of the students teachers and Directors’ of QECs opined that books, research journals, manuals for use of science laboratories, equipment for experiments and update computers were available for teachers and students’ in the universities. It was suggested by the students teachers and Directors of QECs of universities that Quality Assurance Practices (QAP) can be accelerated by thinking the following steps: provision of sufficient resources, add the latest software for computers laboratories and new edition of books.

Keywords: physical facilities, quality assurance practices, library, laboratory

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9047 Research on Carbon Fiber Tow Spreading Technique with Multi-Rolls

Authors: Soon Ok Jo, Han Kyu Jeung, Si Woo Park

Abstract:

With the process of consistent expansion of carbon fiber in width (Carbon Fiber Tow Spreading Technique), it can be expected that such process can enhance the production of carbon fiber reinforced composite material and quality of the product. In this research, the method of mechanically expanding carbon fiber and increasing its width was investigated by using various geometric rolls. In addition, experimental type of carbon fiber expansion device was developed and tested using 12K carbon fiber. As a result, the effects of expansion of such fiber under optimized operating conditions and geometric structure of an elliptical roll, were analyzed.

Keywords: carbon fiber, tow spreading fiber, pre-preg, roll structure

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9046 Optimization of 3D Printing Parameters Using Machine Learning to Enhance Mechanical Properties in Fused Deposition Modeling (FDM) Technology

Authors: Darwin Junnior Sabino Diego, Brando Burgos Guerrero, Diego Arroyo Villanueva

Abstract:

Additive manufacturing, commonly known as 3D printing, has revolutionized modern manufacturing by enabling the agile creation of complex objects. However, challenges persist in the consistency and quality of printed parts, particularly in their mechanical properties. This study focuses on addressing these challenges through the optimization of printing parameters in FDM technology, using Machine Learning techniques. Our aim is to improve the mechanical properties of printed objects by optimizing parameters such as speed, temperature, and orientation. We implement a methodology that combines experimental data collection with Machine Learning algorithms to identify relationships between printing parameters and mechanical properties. The results demonstrate the potential of this methodology to enhance the quality and consistency of 3D printed products, with significant applications across various industrial fields. This research not only advances understanding of additive manufacturing but also opens new avenues for practical implementation in industrial settings.

Keywords: 3D printing, additive manufacturing, machine learning, mechanical properties

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9045 Resistivity Tomography Optimization Based on Parallel Electrode Linear Back Projection Algorithm

Authors: Yiwei Huang, Chunyu Zhao, Jingjing Ding

Abstract:

Electrical Resistivity Tomography has been widely used in the medicine and the geology, such as the imaging of the lung impedance and the analysis of the soil impedance, etc. Linear Back Projection is the core algorithm of Electrical Resistivity Tomography, but the traditional Linear Back Projection can not make full use of the information of the electric field. In this paper, an imaging method of Parallel Electrode Linear Back Projection for Electrical Resistivity Tomography is proposed, which generates the electric field distribution that is not linearly related to the traditional Linear Back Projection, captures the new information and improves the imaging accuracy without increasing the number of electrodes by changing the connection mode of the electrodes. The simulation results show that the accuracy of the image obtained by the inverse operation obtained by the Parallel Electrode Linear Back Projection can be improved by about 20%.

Keywords: electrical resistivity tomography, finite element simulation, image optimization, parallel electrode linear back projection

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9044 Hyper Parameter Optimization of Deep Convolutional Neural Networks for Pavement Distress Classification

Authors: Oumaima Khlifati, Khadija Baba

Abstract:

Pavement distress is the main factor responsible for the deterioration of road structure durability, damage vehicles, and driver comfort. Transportation agencies spend a high proportion of their funds on pavement monitoring and maintenance. The auscultation of pavement distress was based on the manual survey, which was extremely time consuming, labor intensive, and required domain expertise. Therefore, the automatic distress detection is needed to reduce the cost of manual inspection and avoid more serious damage by implementing the appropriate remediation actions at the right time. Inspired by recent deep learning applications, this paper proposes an algorithm for automatic road distress detection and classification using on the Deep Convolutional Neural Network (DCNN). In this study, the types of pavement distress are classified as transverse or longitudinal cracking, alligator, pothole, and intact pavement. The dataset used in this work is composed of public asphalt pavement images. In order to learn the structure of the different type of distress, the DCNN models are trained and tested as a multi-label classification task. In addition, to get the highest accuracy for our model, we adjust the structural optimization hyper parameters such as the number of convolutions and max pooling, filers, size of filters, loss functions, activation functions, and optimizer and fine-tuning hyper parameters that conclude batch size and learning rate. The optimization of the model is executed by checking all feasible combinations and selecting the best performing one. The model, after being optimized, performance metrics is calculated, which describe the training and validation accuracies, precision, recall, and F1 score.

Keywords: distress pavement, hyperparameters, automatic classification, deep learning

Procedia PDF Downloads 73
9043 Active-Material Variation Analysis of a Lithium-Ion Battery

Authors: Muhammad Husnat Khalid, Stephan Bihn, Dirk Uwe Sauer, Nisai Fuengwarodsakul

Abstract:

To combat the effects of climate change, lithium-ion batteries are getting a lot of attention for energy storage. However, due to its diverse range of applications extending from small electronics equipment to energy storage systems, its output requirements, as well as limitations, vary significantly. Many efforts are underway to increase the power and energy output of the cells without any significant compromise on their size and weight. In this paper, different active materials are explored for an existing cell Kokam that initially has graphite as anode and NCO as cathode material. The Pareto front optimization tool is then utilized to pick a cell that gives the optimum results in terms of energy, power, or both. The parameter variation of the cells is done in the MATLAB application ISEA Cell and Pack Database (ICPD) created by the Institute of Power Electronics and Electrical Drives (ISEA) RWTH Aachen, University that creates the physical-chemical model of the existing cells.

Keywords: battery storage system, lithium-ion battery, active material variation, cell design optimization

Procedia PDF Downloads 88
9042 Load Management Using Multiple Sequential Load Shaping Techniques

Authors: Amira M. Attia, Karim H. Youssef, Nabil H. Abbasi

Abstract:

Demand Side Management (DSM) is an essential characteristic of current and future smart grid systems. As one of DSM functions, load management aims to control customers’ total electric consumption and utility’s load factor by using various load shaping techniques. However, applying load shaping techniques such as load shifting, peak clipping, or strategic conservation individually does not provide the desired level of improvement for load factor increment and/or customer’s bill reduction. In this paper, two load shaping techniques will be simulated as constrained optimization problems. The purpose is to reflect the application of combined load shifting and strategic conservation model together at the same time, and the application of combined load shifting and peak clipping model as well. The problem will be formulated and solved by using disciplined convex programming (CVX) based MATLAB® R2013b. Simulation results will be evaluated and compared for studying the most impactful multi-techniques model in improving load curve.

Keywords: convex programing, demand side management, load shaping, multiple, building energy optimization

Procedia PDF Downloads 301
9041 Optimal Allocation of PHEV Parking Lots to Minimize Dstribution System Losses

Authors: Mohsen Mazidi, Ali Abbaspour, Mahmud Fotuhi-Firuzabad, Mohamamd Rastegar

Abstract:

To tackle the air pollution issues, Plug-in Hybrid Electric Vehicles (PHEVs) are proposed as an appropriate solution. Charging a large amount of PHEV batteries, if not controlled, would have negative impacts on the distribution system. The control process of charging of these vehicles can be centralized in parking lots that may provide a chance for better coordination than the individual charging in houses. In this paper, an optimization-based approach is proposed to determine the optimum PHEV parking capacities in candidate nodes of the distribution system. In so doing, a profile for charging and discharging of PHEVs is developed in order to flatten the network load profile. Then, this profile is used in solving an optimization problem to minimize the distribution system losses. The outputs of the proposed method are the proper place for PHEV parking lots and optimum capacity for each parking. The application of the proposed method on the IEEE-34 node test feeder verifies the effectiveness of the method.

Keywords: loss, plug-in hybrid electric vehicle (PHEV), PHEV parking lot, V2G

Procedia PDF Downloads 528