Search results for: aqueous extract of ginger root (AEGR)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4106

Search results for: aqueous extract of ginger root (AEGR)

1886 Detection of Concrete Reinforcement Damage Using Piezoelectric Materials: Analytical and Experimental Study

Authors: C. P. Providakis, G. M. Angeli, M. J. Favvata, N. A. Papadopoulos, C. E. Chalioris, C. G. Karayannis

Abstract:

An effort for the detection of damages in the reinforcement bars of reinforced concrete members using PZTs is presented. The damage can be the result of excessive elongation of the steel bar due to steel yielding or due to local steel corrosion. In both cases the damage is simulated by considering reduced diameter of the rebar along the damaged part of its length. An integration approach based on both electromechanical admittance methodology and guided wave propagation technique is used to evaluate the artificial damage on the examined longitudinal steel bar. Two actuator PZTs and a sensor PZT are considered to be bonded on the examined steel bar. The admittance of the Sensor PZT is calculated using COMSOL 3.4a. Fast Furrier Transformation for a better evaluation of the results is employed. An effort for the quantification of the damage detection using the root mean square deviation (RMSD) between the healthy condition and damage state of the sensor PZT is attempted. The numerical value of the RSMD yields a level for the difference between the healthy and the damaged admittance computation indicating this way the presence of damage in the structure. Experimental measurements are also presented.

Keywords: concrete reinforcement, damage detection, electromechanical admittance, experimental measurements, finite element method, guided waves, PZT

Procedia PDF Downloads 253
1885 Identification of Landslide Features Using Back-Propagation Neural Network on LiDAR Digital Elevation Model

Authors: Chia-Hao Chang, Geng-Gui Wang, Jee-Cheng Wu

Abstract:

The prediction of a landslide is a difficult task because it requires a detailed study of past activities using a complete range of investigative methods to determine the changing condition. In this research, first step, LiDAR 1-meter by 1-meter resolution of digital elevation model (DEM) was used to generate six environmental factors of landslide. Then, back-propagation neural networks (BPNN) was adopted to identify scarp, landslide areas and non-landslide areas. The BPNN uses 6 environmental factors in input layer and 1 output layer. Moreover, 6 landslide areas are used as training areas and 4 landslide areas as test areas in the BPNN. The hidden layer is set to be 1 and 2; the hidden layer neurons are set to be 4, 5, 6, 7 and 8; the learning rates are set to be 0.01, 0.1 and 0.5. When using 1 hidden layer with 7 neurons and the learning rate sets to be 0.5, the result of Network training root mean square error is 0.001388. Finally, evaluation of BPNN classification accuracy by the confusion matrix shows that the overall accuracy can reach 94.4%, and the Kappa value is 0.7464.

Keywords: digital elevation model, DEM, environmental factors, back-propagation neural network, BPNN, LiDAR

Procedia PDF Downloads 143
1884 Toxicity and Larvicidal Activity of Cholesta-β-D-Glucopyranoside Isolated from Combretum molle R.

Authors: Abdu Zakari, Sai’d Jibril, Adoum A. Omar

Abstract:

The leaves of Combretum molle was selected on the basis of its uses in folk medicine as insecticides. The leave extracts of Combretum molle was tested against the larvae of Artemia salina, i.e. Brine Shrimp Lethality Test (BST), Culex quinquefasciatus Say (Filaria disease vector) i.e. Larvicidal Test, using crude ethanol, n-hexane, chloroform, ethyl acetate, and methanol extracts. The methanolic extract proved to be the most effective in inducing complete lethality at minimum doses both in the BST and the Larvicidal activity test. The LC50¬ values obtained are 24.85 µg/ml and 0.4µg/ml respectively. The bioactivity-guided column chromatography afforded the pure compound ACM–3. ACM-3 was not active in the BST with LC50 value >1000µg/ml, but was active in the Larvicidal activity test with LC50 value 4.0µg/ml. ACM-3 was proposed to have the structure I, (Cholesta-β-D-Glucopyranoside).

Keywords: toxicity, larvicidal, Combretum molle, Artemia salina, Culex quinquefasciatus Say.

Procedia PDF Downloads 397
1883 Meticulous Doxorubicin Release from pH-Responsive Nanoparticles Entrapped within an Injectable Thermoresponsive Depot

Authors: Huayang Yu, Nicola Ingram, David C. Green, Paul D. Thornton

Abstract:

The dual stimuli-controlled release of doxorubicin from gel-embedded nanoparticles is reported. Non-cytotoxic polymer nanoparticles are formed from poly(ethylene glycol)-b-poly(benzyl glutamate) that, uniquely, contain a central ester link. This connection renders the nanoparticles pH-responsive, enabling extensive doxorubicin release in acidic solutions (pH 6.5), but not in solutions of physiological pH (pH 7.4). Doxorubicin loaded nanoparticles were found to be stable for at least 31 days and lethal against the three breast cancer cell lines tested. Furthermore, doxorubicin-loaded nanoparticles could be incorporated within a thermoresponsive poly(2-hydroxypropyl methacrylate) gel depot, which forms immediately upon injection of poly(2-hydroxypropyl methacrylate) into aqueous solution. The combination of the poly(2-hydroxypropyl methacrylate) gel and poly(ethylene glycol)-b-poly(benzyl glutamate) nanoparticles yields an injectable doxorubicin delivery system that facilities near-complete drug release when maintained at elevated temperatures (37 °C) in acidic solution (pH 6.5). In contrast, negligible payload release occurs when the material is stored at room temperature in a non-acidic solution (pH 7.4). The system has great potential as a vehicle for the prolonged, site-specific release of chemotherapeutics.

Keywords: biodegradable, nanoparticle, polymer, thermoresponsive

Procedia PDF Downloads 133
1882 Imputing Missing Data in Electronic Health Records: A Comparison of Linear and Non-Linear Imputation Models

Authors: Alireza Vafaei Sadr, Vida Abedi, Jiang Li, Ramin Zand

Abstract:

Missing data is a common challenge in medical research and can lead to biased or incomplete results. When the data bias leaks into models, it further exacerbates health disparities; biased algorithms can lead to misclassification and reduced resource allocation and monitoring as part of prevention strategies for certain minorities and vulnerable segments of patient populations, which in turn further reduce data footprint from the same population – thus, a vicious cycle. This study compares the performance of six imputation techniques grouped into Linear and Non-Linear models on two different realworld electronic health records (EHRs) datasets, representing 17864 patient records. The mean absolute percentage error (MAPE) and root mean squared error (RMSE) are used as performance metrics, and the results show that the Linear models outperformed the Non-Linear models in terms of both metrics. These results suggest that sometimes Linear models might be an optimal choice for imputation in laboratory variables in terms of imputation efficiency and uncertainty of predicted values.

Keywords: EHR, machine learning, imputation, laboratory variables, algorithmic bias

Procedia PDF Downloads 83
1881 Modelling and Simulation of Biomass Pyrolysis

Authors: P. Ahuja, K. S. S. Sai Krishna

Abstract:

There is a concern over the energy shortage in the modern societies as it is one of the primary necessities. Renewable energy, mainly biomass, is found to be one feasible solution as it is inexhaustible and clean energy source all over the world. Out of various methods, thermo chemical conversion is considered to be the most common and convenient method to extract energy from biomass. The thermo-chemical methods that are employed are gasification, liquefaction and combustion. On gasification biomass yields biogas, on liquefaction biomass yields bio-oil and on combustion biomass yields bio-char. Any attempt to biomass gasification, liquefaction or combustion calls for a good understanding of biomass pyrolysis. So, Irrespective of the method used the first step towards the thermo-chemical treatment of biomass is pyrolysis. Pyrolysis mainly converts the solid mass into liquid with gas and residual char as the byproducts. Liquid is used for the production of heat, power and many other chemicals whereas the gas and char can be used as fuels to generate heat.

Keywords: biomass, fluidisation, pyrolysis, simulation

Procedia PDF Downloads 339
1880 Detection of Concrete Reinforcement Damage Using Piezoelectric Materials: Analytical and Experimental Study

Authors: C. P. Providakis, G. M. Angeli, M. J. Favvata, N. A. Papadopoulos, C. E. Chalioris, C. G. Karayannis

Abstract:

An effort for the detection of damages in the reinforcement bars of reinforced concrete members using PZTs is presented. The damage can be the result of excessive elongation of the steel bar due to steel yielding or due to local steel corrosion. In both cases the damage is simulated by considering reduced diameter of the rebar along the damaged part of its length. An integration approach based on both electro-mechanical admittance methodology and guided wave propagation technique is used to evaluate the artificial damage on the examined longitudinal steel bar. Two actuator PZTs and a sensor PZT are considered to be bonded on the examined steel bar. The admittance of the Sensor PZT is calculated using COMSOL 3.4a. Fast Furrier Transformation for a better evaluation of the results is employed. An effort for the quantification of the damage detection using the root mean square deviation (RMSD) between the healthy condition and damage state of the sensor PZT is attempted. The numerical value of the RSMD yields a level for the difference between the healthy and the damaged admittance computation indicating this way the presence of damage in the structure. Experimental measurements are also presented.

Keywords: concrete reinforcement, damage detection, electromechanical admittance, experimental measurements, finite element method, guided waves, PZT

Procedia PDF Downloads 291
1879 Performance Evaluation of Moringa Oleifera as Coagulant for Treating Abattoir Wastewater

Authors: Adesiji Adeolu Richard, Hassa Musa, Osita Evaritus Asogwa, Mary Oluwatobi Odekunle, Mangey Jarumi Akila

Abstract:

In this paper, extract from raw Moringa Oleifera seeds for the treatment of 40 liters of abattoir wastewater was studied for a period of ten (10) weeks. A completely randomized design with loading dosages of 10, 12, 14, 16, 18, and 20g of processed Moringa Oleifera seed was used in the treatment. A control sample (with no Moringa Oleifera treatment) was also included. The physical and chemical properties of abattoir wastewater were investigated before and after treatment. The turbidity value was reduced drastically after the treatments from 15.40 to 7.63 mg/l for 16g dosage in week 7. Total alkalinity, Total hardness, Conductivity, Calcium, and Biological Oxygen Demand were all found to be reduced in concentration within the second and fourth weeks of the experiment with 14 to 16g of Moringa Oleifera dosage. The results generally showed that 16g/500ml of Moringa Oleifera was able to treat abattoir wastewater after weeks of the experiment.

Keywords: Moringa Oleifera, abattoir wastewater, turbidity, conductivity, pH

Procedia PDF Downloads 117
1878 Mining Multicity Urban Data for Sustainable Population Relocation

Authors: Xu Du, Aparna S. Varde

Abstract:

In this research, we propose to conduct diagnostic and predictive analysis about the key factors and consequences of urban population relocation. To achieve this goal, urban simulation models extract the urban development trends as land use change patterns from a variety of data sources. The results are treated as part of urban big data with other information such as population change and economic conditions. Multiple data mining methods are deployed on this data to analyze nonlinear relationships between parameters. The result determines the driving force of population relocation with respect to urban sprawl and urban sustainability and their related parameters. Experiments so far reveal that data mining methods discover useful knowledge from the multicity urban data. This work sets the stage for developing a comprehensive urban simulation model for catering to specific questions by targeted users. It contributes towards achieving sustainability as a whole.

Keywords: data mining, environmental modeling, sustainability, urban planning

Procedia PDF Downloads 307
1877 NR/PEO Block Copolymer: A Chelating Exchanger for Metal Ions

Authors: M. S. Mrudula, M. R. Gopinathan Nair

Abstract:

In order to utilize the natural rubber for developing new green polymeric materials for specialty applications, we have prepared natural rubber and polyethylene oxide based polymeric networks by two shot method. The polymeric networks thus formed have been used as chelating exchanger for metal ion binding. Chelating exchangers are, in general, coordinating copolymers containing one or more electron donor atoms such as N, S, O, and P that can form coordinate bonds with metals. Hydrogels are water- swollen network of hydrophilic homopolymer or copolymers. They acquire a great interest due to the facility of the incorporation of different chelating groups into the polymeric networks. Such polymeric hydrogels are promising materials in the field of hydrometallurgical applications and water purification due to their chemical stability. The current study discusses the swelling response of the polymeric networks as a function of time, temperature, pH and [NaCl] and sorption studies. Equilibrium swelling has been observed to depend on both structural aspects of the polymers and environmental factors. Metal ion sorption shows that these polymeric networks can be used for removal, separation, and enrichment of metal ions from aqueous solutions and can play an important role for environmental remediation of municipal and industrial wastewater.

Keywords: block copolymer, adsorption, chelating exchanger, swelling study, polymer, metal complexes

Procedia PDF Downloads 342
1876 Monthly River Flow Prediction Using a Nonlinear Prediction Method

Authors: N. H. Adenan, M. S. M. Noorani

Abstract:

River flow prediction is an essential to ensure proper management of water resources can be optimally distribute water to consumers. This study presents an analysis and prediction by using nonlinear prediction method involving monthly river flow data in Tanjung Tualang from 1976 to 2006. Nonlinear prediction method involves the reconstruction of phase space and local linear approximation approach. The phase space reconstruction involves the reconstruction of one-dimensional (the observed 287 months of data) in a multidimensional phase space to reveal the dynamics of the system. Revenue of phase space reconstruction is used to predict the next 72 months. A comparison of prediction performance based on correlation coefficient (CC) and root mean square error (RMSE) have been employed to compare prediction performance for nonlinear prediction method, ARIMA and SVM. Prediction performance comparisons show the prediction results using nonlinear prediction method is better than ARIMA and SVM. Therefore, the result of this study could be used to developed an efficient water management system to optimize the allocation water resources.

Keywords: river flow, nonlinear prediction method, phase space, local linear approximation

Procedia PDF Downloads 409
1875 Generalized Extreme Value Regression with Binary Dependent Variable: An Application for Predicting Meteorological Drought Probabilities

Authors: Retius Chifurira

Abstract:

Logistic regression model is the most used regression model to predict meteorological drought probabilities. When the dependent variable is extreme, the logistic model fails to adequately capture drought probabilities. In order to adequately predict drought probabilities, we use the generalized linear model (GLM) with the quantile function of the generalized extreme value distribution (GEVD) as the link function. The method maximum likelihood estimation is used to estimate the parameters of the generalized extreme value (GEV) regression model. We compare the performance of the logistic and the GEV regression models in predicting drought probabilities for Zimbabwe. The performance of the regression models are assessed using the goodness-of-fit tests, namely; relative root mean square error (RRMSE) and relative mean absolute error (RMAE). Results show that the GEV regression model performs better than the logistic model, thereby providing a good alternative candidate for predicting drought probabilities. This paper provides the first application of GLM derived from extreme value theory to predict drought probabilities for a drought-prone country such as Zimbabwe.

Keywords: generalized extreme value distribution, general linear model, mean annual rainfall, meteorological drought probabilities

Procedia PDF Downloads 198
1874 Design and Characterization of Aromatase Inhibitor Loaded Nanoparticles for the Treatment of Breast Cancer

Authors: Harish K. Chandrawanshi, Mithun S. Rajput, Neelima Choure, Purnima Dey Sarkar, Shailesh Jain

Abstract:

The present research study aimed to fabricate and evaluate biodegradable nanoparticles of aromatase inhibitor letrozole, intended for breast cancer therapy. Letrozole loaded poly(D,L-lactide-co-glycolide acid) nanoparticles were prepared by solvent evaporation method using dichlorometane as solvent (oil phase) and polyvinyl alcohol (PVA) as aqueous phase. Prepared nanoparticles were characterized by particle size, infrared spectra, drug loading efficiency, drug entrapment efficiency and in vitro release and also evaluated for in vivo anticancer activity. The high speed homogenizer was used to produce stable nanoparticles of mean size range 198.35 ± 0.04 nm with high entrapment efficiency (69.86 ± 2.78%). Percentage of drug and homogenization speed significantly influenced the particle size, entrapment efficiency and release (p<0.05). The nanoparticles show significant in vivo anticancer activity against Ehrlich ascites carcinoma in mice. The significant system sustained the release of letrozole drug effectively and further investigation could exhibit its potential usefulness in breast cancer therapy.

Keywords: breast cancer/therapy, letrozole, nanoparticles, PLGA

Procedia PDF Downloads 578
1873 Feature Extractions of EMG Signals during a Constant Workload Pedaling Exercise

Authors: Bing-Wen Chen, Alvin W. Y. Su, Yu-Lin Wang

Abstract:

Electromyography (EMG) is one of the important indicators during exercise, as it is closely related to the level of muscle activations. This work quantifies the muscle conditions of the lower limbs in a constant workload exercise. Surface EMG signals of the vastus laterals (VL), vastus medialis (VM), rectus femoris (RF), gastrocnemius medianus (GM), gastrocnemius lateral (GL) and Soleus (SOL) were recorded from fourteen healthy males. The EMG signals were segmented in two phases: activation segment (AS) and relaxation segment (RS). Period entropy (PE), peak count (PC), zero crossing (ZC), wave length (WL), mean power frequency (MPF), median frequency (MDF) and root mean square (RMS) are calculated to provide the quantitative information of the measured EMG segments. The outcomes reveal that the PE, PC, ZC and RMS have significantly changed (p<.001); WL presents moderately changed (p<.01); MPF and MDF show no changed (p>.05) during exercise. The results also suggest that the RS is also preferred for performance evaluation, while the results of the extracted features in AS are usually affected directly by the amplitudes. It is further found that the VL exhibits the most significant changes within six muscles during pedaling exercise. The proposed work could be applied to quantify the stamina analysis and to predict the instant muscle status in athletes.

Keywords: electromyographic feature extraction, muscle status, pedaling exercise, relaxation segment

Procedia PDF Downloads 300
1872 Removal of Heavy Metals from Aqueous Solutions by Low-Cost Materials: A Review

Authors: I. Nazari, B. Shaabani, P. Abaasifar

Abstract:

In small quantities certain heavy metals are nutritionally essential for a healthy life. The heavy metals linked most often to human poisoning are lead, mercury, arsenic, and cadmium. Other heavy metals including copper, zinc and chromium are actually required by the body in small quantity but can also be toxic in large doses. Nowadays, we have contamination to this heavy metals in some untreated industrial waste waters and even in several populated cities drinking waters around the world. The contamination of ground and underground water sources to heavy metals can be concentrated and travel up to food chain by drinking water and agricultural products. In recent years, the need for safe and economical methods for removal of heavy metals from contaminated water has necessitated research interest towards the finding low-cost alternatives. Bio-adsorbents have emerged as low-cost and efficient materials for the removal of heavy metals from waste and ground waters. The bio-adsorbents have an affinity for heavy metals ions to form metal complexes or chelates due to having functional groups including carboxyl, hydroxyl, imidazole, and etc. The objective of this study is to review researches in less expensive adsorbents and their utilization possibilities for various low-cost bio-adsorbents such as coffee beans, rice husk, and saw dust for the removal of heavy metals from contaminated waters.

Keywords: heavy metals, water pollution, bio-adsorbents, low cost adsorbents

Procedia PDF Downloads 355
1871 Applying Genetic Algorithm in Exchange Rate Models Determination

Authors: Mehdi Rostamzadeh

Abstract:

Genetic Algorithms (GAs) are an adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this study, we apply GAs for fundamental and technical models of exchange rate determination in exchange rate market. In this framework, we estimated absolute and relative purchasing power parity, Mundell-Fleming, sticky and flexible prices (monetary models), equilibrium exchange rate and portfolio balance model as fundamental models and Auto Regressive (AR), Moving Average (MA), Auto-Regressive with Moving Average (ARMA) and Mean Reversion (MR) as technical models for Iranian Rial against European Union’s Euro using monthly data from January 1992 to December 2014. Then, we put these models into the genetic algorithm system for measuring their optimal weight for each model. These optimal weights have been measured according to four criteria i.e. R-Squared (R2), mean square error (MSE), mean absolute percentage error (MAPE) and root mean square error (RMSE).Based on obtained Results, it seems that for explaining of Iranian Rial against EU Euro exchange rate behavior, fundamental models are better than technical models.

Keywords: exchange rate, genetic algorithm, fundamental models, technical models

Procedia PDF Downloads 271
1870 Analysis of the Significance of Multimedia Channels Using Sparse PCA and Regularized SVD

Authors: Kourosh Modarresi

Abstract:

The abundance of media channels and devices has given users a variety of options to extract, discover, and explore information in the digital world. Since, often, there is a long and complicated path that a typical user may venture before taking any (significant) action (such as purchasing goods and services), it is critical to know how each node (media channel) in the path of user has contributed to the final action. In this work, the significance of each media channel is computed using statistical analysis and machine learning techniques. More specifically, “Regularized Singular Value Decomposition”, and “Sparse Principal Component” has been used to compute the significance of each channel toward the final action. The results of this work are a considerable improvement compared to the present approaches.

Keywords: multimedia attribution, sparse principal component, regularization, singular value decomposition, feature significance, machine learning, linear systems, variable shrinkage

Procedia PDF Downloads 308
1869 Crude Palm Oil Antioxidant Extraction and the Antioxidation Activity

Authors: Supriyono Supriyono, Sumardiyono Sumardiyono, Peni Pujiastuti, Dian Indriana Hapsari

Abstract:

Crude palm oil (CPO) is a vegetable oil that came from a palm tree bunch. The productivity of the oil is 12 ton/hectare/year. Thus palm oil tree was known as highest vegetable oil yield. It was grown across Equatorial County, especially in Malaysia and Indonesia. The greenish-red color on CPO was come from carotenoid. Carotenoid is one of the antioxidants that could be extracted. Carotenoid could be used as functional food and other purposes. Another antioxidant that also found in CPO is tocopherol. The aim of the research work is to find antioxidant activity on CPO comparing to the synthetic antioxidant that available in a market. In this research work, antioxidant was extracted by a mixture of acetone and n.hexane, while the activity of the antioxidant extract was determined by DPPH method. Antioxidant activity of the extracted compound about 46% compared to pure tocopherol. While the solvent mixture compose by 90% acetone and 10% n. hexane meet the best on the antioxidant activity.

Keywords: antioxidant, beta carotene, crude palm oil, DPPH, tocopherol

Procedia PDF Downloads 211
1868 Malachite Green and Red Congo Dyes Adsorption onto Chemical Treated Sewage Sludge

Authors: Zamouche Meriem, Mehcene Ismahan, Temmine Manel, Bencheikh Lehocine Mosaab, Meniai Abdeslam Hassen

Abstract:

In this study, the adsorption of Malachite Green (MG) by chemical treated sewage sludge has been studied. The sewage sludge, collected from drying beds of the municipal wastewater treatment station of IBN ZIED, Constantine, Algeria, was treated by different acids such us HNO₃, H₂SO₄, H₃PO₄ for modifying its aptitude to removal the MG from aqueous solutions. The results obtained shows that the sewage sludge activated by sulfuric acid give the highest elimination amounts of MG (9.52 mg/L) compared by the other acids used. The effects of operation parameters have been investigated, the results obtained show that the adsorption capacity per unit of adsorbent mass decreases from 18.69 to 1.20 mg/g when the mass of the adsorbent increases from 0.25 to 4 g respectively, the optimum mass for which a maximum of elimination of the dye is equal to 0.5g. The increasing in the temperature of the solution results in a slight decrease in the adsorption capacity of the chemically treated sludge. The highest amount of dye adsorbed by CSSS (9.56 mg/g) was observed for the optimum temperature of 25°C. The chemical activated sewage sludge proved its effectiveness for the removal of the Red Congo (RC), but by comparison the adsorption of the two dyes studies, we noted that the sludge has more affinity to adsorb the (MG).

Keywords: adsorption, chemical activation, malachite green, sewage sludge

Procedia PDF Downloads 188
1867 Swelling Hydrogels on the Base Nitron Fiber Wastes for Water Keeping in Sandy Soils

Authors: Alim Asamatdinov

Abstract:

Superabsorbent polymer hydrogels can swell to absorb huge volumes of water or aqueous solutions. This property has led to many practical applications of these new materials, particularly in agriculture for improving the water retention of soils and the water supply of plants. This article reviews the methods of polymeric hydrogels, measurements and treatments of their properties, as well as their effects on soil and on plant growth. The thermodynamic approach used to describe the swelling behaviour of polymer networks proves to be quite helpful in modelling the hydrogel efficiency of water-absorbing additives. The paper presents the results of a study of the physical and chemical properties of hydrogels based on of the production of "Nitron" (Polyacrylonitrile) wastes fibre and salts of the 3-rd transition metals and formalin. The developed hydrogels HG-Al, HG-Cr and HG-formalin have been tested for water holding the capacity of sand. Such a conclusion was also confirmed by data from the method of determining the wilting point by vegetative thumbnails. In the entering process using a dose of 0.1% of the swelling polymeric hydrogel in sand with a culture of barley the difference between the wilting point in comparison with the control was negligible. This indicates that the moisture which was contained in the hydrogel is involved in moisture availability for plant growth, to the same extent as that in the capillaries.

Keywords: hydrogel, chemical, polymer, sandy, colloid

Procedia PDF Downloads 143
1866 An Effective Route to Control of the Safety of Accessing and Storing Data in the Cloud-Based Data Base

Authors: Omid Khodabakhshi, Amir Rozdel

Abstract:

The subject of cloud computing security research has allocated a number of challenges and competitions because the data center is comprised of complex private information and are always faced various risks of information disclosure by hacker attacks or internal enemies. Accordingly, the security of virtual machines in the cloud computing infrastructure layer is very important. So far, there are many software solutions to develop security in virtual machines. But using software alone is not enough to solve security problems. The purpose of this article is to examine the challenges and security requirements for accessing and storing data in an insecure cloud environment. In other words, in this article, a structure is proposed for the implementation of highly isolated security-sensitive codes using secure computing hardware in virtual environments. It also allows remote code validation with inputs and outputs. We provide these security features even in situations where the BIOS, the operating system, and even the super-supervisor are infected. To achieve these goals, we will use the hardware support provided by the new Intel and AMD processors, as well as the TPM security chip. In conclusion, the use of these technologies ultimately creates a root of dynamic trust and reduces TCB to security-sensitive codes.

Keywords: code, cloud computing, security, virtual machines

Procedia PDF Downloads 189
1865 Robust Features for Impulsive Noisy Speech Recognition Using Relative Spectral Analysis

Authors: Hajer Rahali, Zied Hajaiej, Noureddine Ellouze

Abstract:

The goal of speech parameterization is to extract the relevant information about what is being spoken from the audio signal. In speech recognition systems Mel-Frequency Cepstral Coefficients (MFCC) and Relative Spectral Mel-Frequency Cepstral Coefficients (RASTA-MFCC) are the two main techniques used. It will be shown in this paper that it presents some modifications to the original MFCC method. In our work the effectiveness of proposed changes to MFCC called Modified Function Cepstral Coefficients (MODFCC) were tested and compared against the original MFCC and RASTA-MFCC features. The prosodic features such as jitter and shimmer are added to baseline spectral features. The above-mentioned techniques were tested with impulsive signals under various noisy conditions within AURORA databases.

Keywords: auditory filter, impulsive noise, MFCC, prosodic features, RASTA filter

Procedia PDF Downloads 423
1864 'Spare the Rod and Spoil the Child': The Criminal Career of an Armed Robber

Authors: Mahlogonolo Stephina Thobane

Abstract:

The aim of the study upon which this article is based was “to evaluate the possibility of using criminal career research in the development and evaluation of crime control strategies, particularly for armed robberies.” The research employed a concurrent triangulation mixed-method approach where quantitative and qualitative data were collected concurrently but analysed separately through the use of SPSS and Atlas.ti respectively. Forty offenders incarcerated at six correctional centres around the Gauteng province of South Africa for robbery with aggravating circumstances were interviewed as research participants. Since the researcher had no prior information on the total number of the population, purposive sampling (i.e. snowballing) was executed to draw the sample. This research found that offenders launched their criminal career at a very young age of, 11 years, by committing petty crimes such as theft and then, as they grew older, they progressed to more serious and violent crimes such as vehicle hijacking and Cash-in-Transit (CIT) robberies. Thus, it is pivotal that those responsible for developing crime prevention policies focus on interrupting the root causes of crime in the early stages of one’s life in order to prevent continuation of delinquent behaviour from childhood to adolescence and adulthood.

Keywords: criminal career, robbery with aggravating circumstances, cash-in-transit robbery, criminal career research

Procedia PDF Downloads 443
1863 Enhancing Dents through Lean Six Sigma

Authors: Prateek Guleria, Shubham Sharma, Rakesh Kumar Shukla, Harshit Sharma

Abstract:

Performance measurement of small and medium-sized businesses is the primary need for all companies to survive and thrive in a dynamic global company. A structured and systematic, integrated organization increases employee reliability, sustainability, and loyalty. This paper is a case study of a gear manufacturing industry that was facing the problem of rejection due to dents and damages in gear. The DMAIC cycle, along with different tools used in the research work includes SIPOC (Supply, Input, Process, Output, Control) Pareto analysis, Root & Cause analysis, and FMEA (Failure Mode and Effect Analysis). The six-sigma level was improved from 4.06 to 3.46, and the rejection rate was reduced from 7.44% to 1.56%. These findings highlighted the influence of a Lean Six Sigma module in the gear manufacturing unit, which has already increased operational quality and continuity to increase market success and meet customer expectations. According to the findings, applying lean six sigma tools will result in increased productivity. The results could assist businesses in deciding the quality tools that were likely to improve efficiency, competitiveness, and expense.

Keywords: six sigma, DMAIC, SIPOC, failure mode, effect analysis

Procedia PDF Downloads 112
1862 Nitrogen Doping Effect on Enhancement of Electrochemical Performance of a Carbon Nanotube Based Microsupercapacitor

Authors: Behnoush Dousti, Ye Choi, Gil S. Lee

Abstract:

Microsupercapacitors (MScs) are known as the future of miniaturized energy sources that can be coupled to a battery to deliver stable and constant energy to microelectronics. Among all their counterparts, electrochemical microsupercapacitor have drawn the most research attention due to their higher power density and long cycle life. Designing the microstructure and choosing the electroactive materials are two significant factors that greatly affect the performance of the device. Here, we report successful fabrication and characterization of a microsupercapacitor with interdigitated structure based on Carbon nanotube sheets (CNT sheet). Novel structure of highly aligned CNT sheet as the electrode materials which also offers excellent conductivity and large surface area along with doping with nitrogen, enabled us to develop a device with serval order of magnitude higher electrochemical performance than the pristine CNT in aqueous electrolyte including high specific capacitance and rate capabilities and excellent cycle life over 10000 cycles. Geometric parameters such as finger width and gap size were also studied and it was shown the device performance is much depended on them. Results of this study confirms the potential of CNT sheet for future energy storage devices.

Keywords: carbon nanotube, energy storage systems, microsupercapacitor, nitrogen doping

Procedia PDF Downloads 130
1861 Electrochemical Determination of Caffeine Content in Ethiopian Coffee Samples Using Lignin Modified Glassy Carbon Electrode

Authors: Meareg Amare, Senait Aklog

Abstract:

Lignin film was deposited at the surface of the glassy carbon electrode potential-statically. In contrast to the unmodified glassy carbon electrode, an oxidative peak with an improved current and overpotential for caffeine at the modified electrode showed catalytic activity of the modifier towards oxidation of caffeine. Linear dependence of peak current on caffeine concentration in the range 6 × 10⁻⁶ to 100 × 10⁻⁶ mol L⁻¹ with determination coefficient and method detection limit (LoD = 3 s/slope) of 0.99925 and 8.37 × 10⁻⁷ mol L⁻¹, respectively, supplemented by recovery results of 93.79–102.17%, validated the developed method. An attempt was made to determine the caffeine content of aqueous coffee extracts of Ethiopian coffees grown in four coffee cultivating localities (Wonbera, Wolega, Finoteselam, and Zegie) and hence to evaluate the correlation between users preference and caffeine content. In agreement with reported works, caffeine contents (w/w%) of 0.164 in Wonbera coffee; 0.134 in Wolega coffee; 0.097 in Finoteselam coffee; and 0.089 in Zegie coffee were detected, confirming the applicability of the developed method for determination of caffeine in a complex matrix environment. The result indicated that users’ highest preference for Wonbera and least preference for Zegie cultivated coffees are in agreement with the caffeine content.

Keywords: electrochemical, lignin, caffeine, electrode

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1860 Antimicrobial Activity of Ilex paraguariensis Sub-Fractions after Liquid-Liquid Partitioning

Authors: Sabah El-Sawalhi, Elie Fayad, Roula M. Abdel-Massih

Abstract:

Ilex paraguariensis (Yerba Mate) is a medium to large tree commonly consumed by South Americans. Its leaves and stems are associated with different biological activities. The purpose of this study was to evaluate the antibacterial activity of Yerba Mate against Gram-positive and Gram-negative bacterial strains and its action against some resistant bacteria with different resistance profiles. Yerba Mate aqueous extracts were prepared at 70°C for 2 hrs, and the microdilution method was used to determine the minimum inhibitory concentration (MIC). Gram-positive bacteria exhibited a stronger antibacterial activity (MIC ranged between 0.468 mg/mL and 15 mg/mL) than Gram-negative bacteria. Yerba Mate was also extracted with acetone: water (1:1) and then further sub-fractionated with hexane, chloroform, and ethyl acetate. MIC values against Staphylococcus aureus ranged from 0.78 to 2.5 mg/ml for the chloroform fraction, from 1.56 to 3.75 mg/ml for the ethyl acetate fraction, and 0.78 to 1.87 mg/ml for the water fraction. The water fraction also exhibited antibacterial activity against Salmonella species (MIC ranged from 1.56 mg/ml to 3.12 mg/ml). The water fraction exhibited the highest antibacterial activity among all the fractions obtained. More studies are needed to determine the molecule or molecules responsible for this activity.

Keywords: antibacterial activity, bacterial resistance, minimum inhibitory concentration, yerba mate

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1859 An Ensemble-based Method for Vehicle Color Recognition

Authors: Saeedeh Barzegar Khalilsaraei, Manoocheher Kelarestaghi, Farshad Eshghi

Abstract:

The vehicle color, as a prominent and stable feature, helps to identify a vehicle more accurately. As a result, vehicle color recognition is of great importance in intelligent transportation systems. Unlike conventional methods which use only a single Convolutional Neural Network (CNN) for feature extraction or classification, in this paper, four CNNs, with different architectures well-performing in different classes, are trained to extract various features from the input image. To take advantage of the distinct capability of each network, the multiple outputs are combined using a stack generalization algorithm as an ensemble technique. As a result, the final model performs better than each CNN individually in vehicle color identification. The evaluation results in terms of overall average accuracy and accuracy variance show the proposed method’s outperformance compared to the state-of-the-art rivals.

Keywords: Vehicle Color Recognition, Ensemble Algorithm, Stack Generalization, Convolutional Neural Network

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1858 Anticancer Activity of Gnidia glauca Extracts in Human Breast Cancer Cells

Authors: Vandana Gawande, Chandani Satija

Abstract:

Gnidia glauca is a semi-woody herb of thymelaeaceae family traditionally used as fish poison in India. It is also found in Sri lanka and Africa. In the present study, potential anticancer effect of n-hexane and ethanolic extracts of Gnidia glauca in human breast cancer cells was investigated. Human breast cancer cells (MCF-7) were cultured as monolayers in RPMI 1640 medium. The cells were cultured for 48 hours to allow growth and achieve about 80% confluence in 96-well culture plates. The cells were treated with various concentrations of Gnidia glauca (0.1-100 mg/mL) for 72 hours. Percentage of viable cells after treatment was assessed using a sulforhodamine B colorimetric assay. Both n-hexane and ethanolic extract showed significant cytotoxic activity on MCF-7 cancer cells. This study supports the notion of using Gnidia glauca as a novel anticancer agent for breast cancer.

Keywords: 96 well plate, anticancer activity, Gnidia glauca, MCF-7

Procedia PDF Downloads 288
1857 Timing and Noise Data Mining Algorithm and Software Tool in Very Large Scale Integration (VLSI) Design

Authors: Qing K. Zhu

Abstract:

Very Large Scale Integration (VLSI) design becomes very complex due to the continuous integration of millions of gates in one chip based on Moore’s law. Designers have encountered numerous report files during design iterations using timing and noise analysis tools. This paper presented our work using data mining techniques combined with HTML tables to extract and represent critical timing/noise data. When we apply this data-mining tool in real applications, the running speed is important. The software employs table look-up techniques in the programming for the reasonable running speed based on performance testing results. We added several advanced features for the application in one industry chip design.

Keywords: VLSI design, data mining, big data, HTML forms, web, VLSI, EDA, timing, noise

Procedia PDF Downloads 253