Search results for: abnormal activity detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9845

Search results for: abnormal activity detection

8675 Damage Detection in Beams Using Wavelet Analysis

Authors: Goutham Kumar Dogiparti, D. R. Seshu

Abstract:

In the present study, wavelet analysis was used for locating damage in simply supported and cantilever beams. Study was carried out varying different levels and locations of damage. In numerical method, ANSYS software was used for modal analysis of damaged and undamaged beams. The mode shapes obtained from numerical analysis is processed using MATLAB wavelet toolbox to locate damage. Effect of several parameters such as (damage level, location) on the natural frequencies and mode shapes were also studied. The results indicated the potential of wavelets in identifying the damage location.

Keywords: damage, detection, beams, wavelets

Procedia PDF Downloads 366
8674 Phytochemistry and Biological Activity of Extracts of the Red Raspberry Rubus rosifolius

Authors: Theresa Campbell, Camille Bowen-Forbes, William Aalbersberg

Abstract:

Differences in the sensory properties of two subtly distinct varieties of Rubus rosifolius lead to the examination of their anthocyanin, essential oil and polyphenol profiles. In both cases, notable differences were identified. Pelargonidin-3-rhutinoside (17.2 mg/100 g FW) and Cyanidin-3-glucoside (66.2 mg/100g FW) proved to be the dominant anthocyanins in the red and wine red varieties respectively. Linalool and terpineol were the major constituents of the essential oil from the red variety; however, those of the wine red variety are unidentified. In regard to phenolic compounds, caffeic acid and quercetin were in a higher concentration in the red variety (1.85 and 0.73 mg/100g FW respectively, compared to 1.22 and 0.34 mg/100g FW respectively in the wine red fruits); while ellagic acid and ferulic acid were of a higher concentration in the wine red variety (0.92 and 0.84mg/100g FW respectively, compared to 0.15 and 0.48 mg/100g FW respectively in the red variety). The methanol extract of both fruit varieties showed great antioxidant activity. Analysis of the antimicrobial activity of the fruit extracts against the growth of drug resistant pathogens revealed that they are active against methicillin resistant S. aureus (MRSA), rifampicin resistant S. aureus (RRSA), wild-type S. aureus (WTSA) and vancomycin-resistant Enterococcus faecium (VREF). Activity was also reported against several food-borne pathogens including two strains of E. coli, L. monocytogenes and Enterobacter aerogenes. The cytotoxicity of the various extracts was assessed and the essential oil extracts exhibited superior activity. The phenolic composition and biological activity of the fruits indicate that their consumption is beneficial to health and also that their incorporation into functional foods and nutraceuticals should be considered.

Keywords: phytochemicals, antimicrobial, cytotoxic, Rubus rosifolius

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8673 Evaluation of Different Liquid Scintillation Counting Methods for 222Rn Determination in Waters

Authors: Jovana Nikolov, Natasa Todorovic, Ivana Stojkovic

Abstract:

Monitoring of 222Rn in drinking or surface waters, as well as in groundwater has been performed in connection with geological, hydrogeological and hydrological surveys and health hazard studies. Liquid scintillation counting (LSC) is often preferred analytical method for 222Rn measurements in waters because it allows multiple-sample automatic analysis. LSC method implies mixing of water samples with organic scintillation cocktail, which triggers radon diffusion from the aqueous into organic phase for which it has a much greater affinity, eliminating possibility of radon emanation in that manner. Two direct LSC methods that assume different sample composition have been presented, optimized and evaluated in this study. One-phase method assumed direct mixing of 10 ml sample with 10 ml of emulsifying cocktail (Ultima Gold AB scintillation cocktail is used). Two-phase method involved usage of water-immiscible cocktails (in this study High Efficiency Mineral Oil Scintillator, Opti-Fluor O and Ultima Gold F are used). Calibration samples were prepared with aqueous 226Ra standard in glass 20 ml vials and counted on ultra-low background spectrometer Quantulus 1220TM equipped with PSA (Pulse Shape Analysis) circuit which discriminates alpha/beta spectra. Since calibration procedure is carried out with 226Ra standard, which has both alpha and beta progenies, it is clear that PSA discriminator has vital importance in order to provide reliable and precise spectra separation. Consequentially, calibration procedure was done through investigation of PSA discriminator level influence on 222Rn efficiency detection, using 226Ra calibration standard in wide range of activity concentrations. Evaluation of presented methods was based on obtained efficiency detections and achieved Minimal Detectable Activity (MDA). Comparison of presented methods, accuracy and precision as well as different scintillation cocktail’s performance was considered from results of measurements of 226Ra spiked water samples with known activity and environmental samples.

Keywords: 222Rn in water, Quantulus1220TM, scintillation cocktail, PSA parameter

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8672 Isolation of Protease Producing Bacteria from Soil Sediments of Ayiramthengu Mangrove Ecosystem

Authors: Reshmi Vijayan

Abstract:

Alkaline protease is one of the most important enzymes in the biological world. Microbial production of alkaline protease is getting more attention from researchers due to its unique properties and substantial activity. Microorganisms are the most common sources of commercial enzymes due to their physiological and biochemical properties. The study was conducted on Ayiramthenghu mangrove sediments to isolate protease producing bacteria. All the isolates were screened for proteolytic activity on a skim milk agar plate at 37˚C for 48hrs. Protease activities were determined by the formation of a clear zone around the colonies on Skim milk agar medium. The activity of the enzyme was measured by the tyrosine standard curve, and it was found to be 0.186285 U/ml/min.

Keywords: protease, protease assay, skim milk agar medium, mangrove ecosystem

Procedia PDF Downloads 101
8671 A Static Android Malware Detection Based on Actual Used Permissions Combination and API Calls

Authors: Xiaoqing Wang, Junfeng Wang, Xiaolan Zhu

Abstract:

Android operating system has been recognized by most application developers because of its good open-source and compatibility, which enriches the categories of applications greatly. However, it has become the target of malware attackers due to the lack of strict security supervision mechanisms, which leads to the rapid growth of malware, thus bringing serious safety hazards to users. Therefore, it is critical to detect Android malware effectively. Generally, the permissions declared in the AndroidManifest.xml can reflect the function and behavior of the application to a large extent. Since current Android system has not any restrictions to the number of permissions that an application can request, developers tend to apply more than actually needed permissions in order to ensure the successful running of the application, which results in the abuse of permissions. However, some traditional detection methods only consider the requested permissions and ignore whether it is actually used, which leads to incorrect identification of some malwares. Therefore, a machine learning detection method based on the actually used permissions combination and API calls was put forward in this paper. Meanwhile, several experiments are conducted to evaluate our methodology. The result shows that it can detect unknown malware effectively with higher true positive rate and accuracy while maintaining a low false positive rate. Consequently, the AdaboostM1 (J48) classification algorithm based on information gain feature selection algorithm has the best detection result, which can achieve an accuracy of 99.8%, a true positive rate of 99.6% and a lowest false positive rate of 0.

Keywords: android, API Calls, machine learning, permissions combination

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8670 Medium Design and Optimization for High Β-Galactosidase Producing Microbial Strains from Dairy Waste through Fermentation

Authors: Ashish Shukla, K. P. Mishra, Pushplata Tripathi

Abstract:

This paper investigates the production and optimization of β-galactosidase enzyme using synthetic medium by isolated wild strains (S1, S2) mutated strains (M1, M2) through SSF and SmF. Among the different cell disintegration methods used, the highest specific activity was obtained when the cells were permeabilized using isoamyl alcohol. Wet lab experiments were performed to investigate the effects of carbon and nitrogen substrates present in Vogel’s medium on β-galactosidase enzyme activity using S1, S2, and M1, M2 strains through SSF. SmF experiments were performed for effects of carbon and nitrogen sources in YLK2Mg medium on β-galactosidase enzyme activity using S1, S2 and M1, M2 strains. Effect of pH on β-galactosidase enzyme production was also done using S1, S2, and M1, M2 strains. Results were found to be very appreciable in all the cases.

Keywords: β-galactosidase, cell disintegration, permeabilized, SSF, SmF

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8669 Development of an Aptamer-Molecularly Imprinted Polymer Based Electrochemical Sensor to Detect Pathogenic Bacteria

Authors: Meltem Agar, Maisem Laabei, Hannah Leese, Pedro Estrela

Abstract:

Pathogenic bacteria and the diseases they cause have become a global problem. Their early detection is vital and can only be possible by detecting the bacteria causing the disease accurately and rapidly. Great progress has been made in this field with the use of biosensors. Molecularly imprinted polymers have gain broad interest because of their excellent properties over natural receptors, such as being stable in a variety of conditions, inexpensive, biocompatible and having long shelf life. These properties make molecularly imprinted polymers an attractive candidate to be used in biosensors. In this study it is aimed to produce an aptamer-molecularly imprinted polymer based electrochemical sensor by utilizing the properties of molecularly imprinted polymers coupled with the enhanced specificity offered by DNA aptamers. These ‘apta-MIP’ sensors were used for the detection of Staphylococcus aureus and Escherichia coli. The experimental parameters for the fabrication of sensor were optimized, and detection of the bacteria was evaluated via Electrochemical Impedance Spectroscopy. Sensitivity and selectivity experiments were conducted. Furthermore, molecularly imprinted polymer only and aptamer only electrochemical sensors were produced separately, and their performance were compared with the electrochemical sensor produced in this study. Aptamer-molecularly imprinted polymer based electrochemical sensor showed good sensitivity and selectivity in terms of detection of Staphylococcus aureus and Escherichia coli. The performance of the sensor was assessed in buffer solution and tap water.

Keywords: aptamer, electrochemical sensor, staphylococcus aureus, molecularly imprinted polymer

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8668 The Antioxidant Gel Mask Supplies Of Bitter Melon's Extract ( Momordica charantia Linn.)

Authors: N. S. Risqina, G. Edijanti, P. S. Nurita, L. Endang, R. A. Siti, R. Tri

Abstract:

Skin is an important and vital organs and also as a mirror of health and life. Facial skin care is one of the main emphasis to get the beautiful, healthy, and fresh skin. Potentially antioxidant phenolic compounds shows, antimutagen, antitumor, anti-inflammatory, and anti-cancer. Flavonoids are a group of polyphenolic compounds that have the nature of free radicals, inhibiting the oxidative and hydrolytic enzymes as well as anti-inflammatory. Bitter melon (Momordica charantia Linn) is a plant that contains flavonoids, and phenolic antioxidant activity. Bitter melon has strong antioxidant activity that can counteract the free radicals.These compounds can prevent free radicals that cause premature aging. Gel masks including depth cleansing is the cosmetics which work in depth and could raise the dead skin cells. Measurement of antioxidant activity of the extract and gel mask is done by using the immersion method of DPPH. IC50 value of ethanol extract of bitter melon fruit of 287.932 ppm. The preparation of gel mask bitter melon fruit extract, necessary to test the effectiveness of antioxidants using DPPH method is done by measuring the inhibition of DPPH and using UV spectrophotometer at the wavelength of maximum DPPH solution. Tests conducted at the beginning and end of the evaluation (day 0 and day 28). The purpose of this study is to determine the antioxidant activity of the bitter melon's extract and to determine the antioxidant activity of ethanol extract gel mask pare in varying concentrations, ie 1xIC100 (0.295%), 2xIC100 (0.590%) and 4xIC100 (1.180%). Evaluation of physical properties of the preparation on (Day-0,7,14,21, and 28) and evaluation of antioxidant activity (day 0 and 28). Data were analyzed using One Way ANOVA to determine differences in the physical properties of each formula. The statistical results showed that differences in the formula and storage time affects the adhesion, dispersive power, dry time and pH it is shown on a significant value of p <0.05, but longer storage does not affect the pH because the significance value p> 0,05. The antioxidant test showed that there are differences in antioxidant activity in all formulas. Measurement of antioxidant activity of bitter melon fruit extract gel mask on day 0 with a concentration of 0.295%, 0.590%, and 1.180%, respectively, are 124,209.277 ppm, ppm 83819.223 and 47323.592 ppm, whereas day 28 consecutive 130 411, 495 ppm, and 53239.806 95561.645 ppm ppm. The Conclusions drawn that there are antioxidant activity in preparation gel mask of bitter melon fruit extract. The antioxidant activity of bitter melon fruit extract gel mask on the day 0 with a concentration of 0.295%, 0.590%, and 1.180%, respectively, are 124,209.277 ppm, ppm 83819.223 and 47323.592 ppm, whereas on day 28 of antioxidant activity gel mask bitter melon fruit extract with a concentration of 0.295%, 0.590%, and 1.180% in succession, namely: 130,411.495 ppm, ppm 95561.645 and 53239.806 ppm.

Keywords: antioxdant, bitter melon, gel mask, IC50

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8667 Biomonitoring of Marine Environment by Using a Bioindicator Donax trunculus (Mollusca, Bivalvia) from the Gulf of Annaba (Algeria): Biomarkers Responses

Authors: Karima Sifi, Noureddine Soltani

Abstract:

Annaba gulf is the most important touristic and economic area located on the east coast of Algeria. However, these fishery resources are threatened by the pollution due to the progress of economic activity. As part of a biomonitoring program on the quality of waters of the Gulf of Annaba, the specific activity of two biomarkers, acetylcholinesterase (AChE) and glutathion S-transferase (GST) has been measured in edible bivalve Donax trunculus. The samples have been collected during the year 2013 in two sites: El Battah, distant from polluted sources, and Sidi Salem, located near the harbor and different industrial waste. The results showed a significant inhibition of AChE activity and a significant increase in the activity of the GST in samples collected from Sidi Salem as compared to El Battah. The inhibition of the AChE and the increase of the GST in Sidi Salem are in relation with the level of exposition of this site to the pollution.

Keywords: Donax trunculus, annaba gulf, acetylcholinesterase, glutathion s-transferase, biomonitoring, pollution

Procedia PDF Downloads 389
8666 Measurement of Natural Radioactivity and Health Hazard Index Evaluation in Major Soils of Tin Mining Areas of Perak

Authors: Habila Nuhu

Abstract:

Natural radionuclides in the environment can significantly contribute to human exposure to ionizing radiation. The knowledge of their levels in an environment can help the radiological protection agencies in policymaking. Measurement of natural radioactivity in major soils in the tin mining state of Perak Malaysia has been conducted using an HPGe detector. Seventy (70) soil samples were collected at widely distributed locations in the state. Six major soil types were sampled, and thirteen districts around the state were covered. The following were the results of the 226Ra (238U), 228Ra (232Th), and 40K activity in the soil samples: 226Ra (238U) has a mean activity concentration of 191.83 Bq kg⁻¹, more than five times the UNSCEAR reference limits of 35 Bq kg⁻¹. The mean activity concentration of 228Ra (232Th) with a value of 232.41 Bq kg⁻¹ is over seven times the UNSCEAR reference values of 30 Bq kg⁻¹. The average concentration of 40K activity was 275.24 Bq kg⁻¹, which was less than the UNSCEAR reference limit of 400 Bq Kg⁻¹. The range of external hazards index (Hₑₓ) values was from 1.03 to 2.05, while the internal hazards index (Hin) was from 1.48 to 3.08. The Hex and Hin should be less than one for minimal external and internal radiation threats as well as secure use of soil material for building construction. The Hₑₓ and Hin results generally indicate that while using the soil types and their derivatives as building materials in the study area, care must be taken.

Keywords: activity concentration, hazard index, soil samples, tin mining

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8665 Antiplatelet Activity of Nitrated Fatty Acids from Tomato Pomace

Authors: Lyanne Rodriguez, Eduardo Fuente, Andrés Trostchansky, Ivan Palomo

Abstract:

Cardiovascular diseases (CVD) are the leading cause of death in the world. The development of platelet-rich thrombi has been considered a trigger for acute cardiovascular events. A healthy diet, rich in fruit and vegetables, has been related to increased protection against cardiovascular events. Previous studies have observed that tomato pomace has a potent antiplatelet activity, due could be attributed to its high content of fatty acids (> 30%). It has been shown that unsaturated fatty acids can undergo endogenous intracellular nitration reactions during digestion after lipid consumption. Additionally, nitrated fatty acids (NO2-FA) can significantly reduce atherosclerotic lesion formation, inhibiting the expression of adhesion molecules on dysfunctional endothelium and platelet activation. In this work, we have proposed the nitration of fatty acids present in tomato pomace to improve its antiplatelet action. The gastric digestion of the tomato pomace allowed the nitration of the fatty acids, while by HPLC/MS/MS we were able to identify and quantify the nitrated fatty acids. The nitrated tomase extracts showed antiplatelet potential when platelets were stimulated with TRAP-6 and collagen. This activity was related to the presence of nitrated linoleic acid, which inhibited platelet activation by flow cytometry. The knowledge about the antiplatelet activity of nitrated fatty acids from tomato pomace will further develop new and more effective agents.

Keywords: cardiovascular, tomato extracts, nitrated fatty acids, antiplatelet activity

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8664 Antimicrobial Activity of Olive Mill Wastewater Fractions

Authors: Chahinez Ait Si Said, Ouassila Touafek, Mohamed Reda Zahi, Smain Sabour, ‎Mohamed El Hattab ‎

Abstract:

Oil mill wastewater (OMW) is a major effluent of the olive industry resulting from olive ‎oil extraction which is a great source for the development of new drugs. The present ‎study aimed to evaluate the antimicrobial activity of seven different fractions separated ‎from OMW extract. The sample was recovered from an oil mill in the Blida region ‎‎(Algeria). A crude ethyl acetate extract was prepared from OMW according to a well-‎established protocol; the yield of the extract obtained was 4%. From the extract, ‎different fractions were prepared by fractionating the total extract with an open column ‎chromatography. The obtained fractions were submitted to antimicrobial activity ‎screening in a comparative purpose. All the fractions obtained show great antimicrobial ‎potential. ‎Phytochemical study of the different fractions was assessed by evaluating the total ‎phenolic compounds for all fractions studied as the main compounds found in OMW ‎were phenols like hydroxytyrosol, tyrosol, phenolic acids like caffeic, quinic and ferulic ‎acids which show great therapeutic activities. ‎

Keywords: olive mill wastewater, fractionation, total phenolic compound, antimicrobial activity

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8663 Early Screening of Risk Ergonomics among Workers at Madura's Batik Industrial: Rapid Entire Body Assessment and Quick Exposure Checklist

Authors: Abdul Kadir, L. Meily Kurniawidjaja

Abstract:

Batik Madura workers are exposed to many Musculoskeletal Disorders risk factors, particularly Low Back Pain (LBP). This study was conducted as an early detection of ergonomic risk level on Workers Industrial Sentra Batik Madura in Dusun Banyumas, Klampar Subdistrict, Proppo Pamekasan, Madura, East Java. This study includes 12 workers who 11 workers had pain in the upper and lower part of the neck, back, wrist right hand, also 10 workers had pain in the right shoulder. This is a descriptive observational study with cross-sectional approach. Qualitative research by observing workers activity such as draw and putting the wax motif, fabric dyeing, fabric painting, discoloration, washing, and drying. The results are workers have identified ergonomic hazards such as awkward postures, twisting movements, repetitive, and static work postures. Using the method of REBA and QEC, the results get a very high-risk level of activity in each of Madura batik making process is the draw and putting the wax motif, coloring, painting, discoloration, washing, and drying. The level of risk can be reduced by improvement of work equipment include the provision of seats, strut fabric, high settings furnaces, drums, coloring basin, and washing tub.

Keywords: activities of Madura's batik, ergonomic risk level, equipment, QEC (Quick Exposure Checklist), REBA (Rapid Entire Body Assessment)

Procedia PDF Downloads 195
8662 Hedgerow Detection and Characterization Using Very High Spatial Resolution SAR DATA

Authors: Saeid Gharechelou, Stuart Green, Fiona Cawkwell

Abstract:

Hedgerow has an important role for a wide range of ecological habitats, landscape, agriculture management, carbon sequestration, wood production. Hedgerow detection accurately using satellite imagery is a challenging problem in remote sensing techniques, because in the special approach it is very similar to line object like a road, from a spectral viewpoint, a hedge is very similar to a forest. Remote sensors with very high spatial resolution (VHR) recently enable the automatic detection of hedges by the acquisition of images with enough spectral and spatial resolution. Indeed, recently VHR remote sensing data provided the opportunity to detect the hedgerow as line feature but still remain difficulties in monitoring the characterization in landscape scale. In this research is used the TerraSAR-x Spotlight and Staring mode with 3-5 m resolution in wet and dry season in the test site of Fermoy County, Ireland to detect the hedgerow by acquisition time of 2014-2015. Both dual polarization of Spotlight data in HH/VV is using for detection of hedgerow. The varied method of SAR image technique with try and error way by integration of classification algorithm like texture analysis, support vector machine, k-means and random forest are using to detect hedgerow and its characterization. We are applying the Shannon entropy (ShE) and backscattering analysis in single and double bounce in polarimetric analysis for processing the object-oriented classification and finally extracting the hedgerow network. The result still is in progress and need to apply the other method as well to find the best method in study area. Finally, this research is under way to ahead to get the best result and here just present the preliminary work that polarimetric image of TSX potentially can detect the hedgerow.

Keywords: TerraSAR-X, hedgerow detection, high resolution SAR image, dual polarization, polarimetric analysis

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8661 Time Parameter Based for the Detection of Catastrophic Faults in Analog Circuits

Authors: Arabi Abderrazak, Bourouba Nacerdine, Ayad Mouloud, Belaout Abdeslam

Abstract:

In this paper, a new test technique of analog circuits using time mode simulation is proposed for the single catastrophic faults detection in analog circuits. This test process is performed to overcome the problem of catastrophic faults being escaped in a DC mode test applied to the inverter amplifier in previous research works. The circuit under test is a second-order low pass filter constructed around this type of amplifier but performing a function that differs from that of the previous test. The test approach performed in this work is based on two key- elements where the first one concerns the unique square pulse signal selected as an input vector test signal to stimulate the fault effect at the circuit output response. The second element is the filter response conversion to a square pulses sequence obtained from an analog comparator. This signal conversion is achieved through a fixed reference threshold voltage of this comparison circuit. The measurement of the three first response signal pulses durations is regarded as fault effect detection parameter on one hand, and as a fault signature helping to hence fully establish an analog circuit fault diagnosis on another hand. The results obtained so far are very promising since the approach has lifted up the fault coverage ratio in both modes to over 90% and has revealed the harmful side of faults that has been masked in a DC mode test.

Keywords: analog circuits, analog faults diagnosis, catastrophic faults, fault detection

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8660 The Correlation of Physical Activity and Plantar Pressure in Young Adults

Authors: Lovro Štefan

Abstract:

Background: The main purpose of the present study was to explore the correlations between physical activity and peak plantar pressure in dynamic mode. Methods: Participants were one hundred forty-six first-year university students (30.8% girls). Plantar pressure generated under each region of the foot (forefoot, midfoot, and heel) was measured by using Zebris dynamometric platform (Isny, Germany). The level of physical activity (PA) was calculated with the International Physical Activity questionnaire (IPAQ - short form). Results: In boys, forefoot peak plantar pressure was correlated with moderate PA (MPA; r=-0.21), vigorous PA (VPA; r=-0.18), and moderate-to-vigorous PA (MVPA; r=-0.28). No significant correlations with other foot regions (p>0.05) were observed. In girls, forefoot peak plantar pressure was correlated with MPA (r =-0.30), VPA (r=-0.39) and MVPA (r=-0.38). Also, heel peak pressure was significantly correlated with MPA (r=-0.33), while no significant correlations with VPA (r=0.05) and MVPA (r=-0.15) were observed. Conclusion: This study shows that different intensities of PA were mostly correlated with forefoot peak plantar pressure in both boys and girls. Therefore, strategies that reduce plantar pressure through a more active lifestyle should be implemented within the education system.

Keywords: pedobarography, youth, exercise, associations

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8659 The Application and Relevance of Costing Techniques in Service Oriented Business Organisations: A Review of the Activity-Based Costing (ABC) Technique

Authors: Udeh Nneka Evelyn

Abstract:

The shortcomings of traditional costing system, in terms of validity, accuracy, consistency and relevance increased the need for modern management accounting system. ABC (Activity-Based Costing) can be used as a modern tool for planning, control and decision making for management. Past studies on activity-based costing (ABC) system have focused on manufacturing firms thereby making the studies on service firms scanty to some extent. This paper reviewed the application and relevance of activity-based costing techniques in service oriented business organisations by employing a qualitative research method which relied heavily on literature review of past and current relevant articles focusing on activity-based costing (ABC). Findings suggest that ABC is not only appropriate for use in a manufacturing environment; it is also most appropriate for service organizations such as financial institutions, the healthcare industry, and government organizations. In fact, some banking and financial institutions have been applying the concept for years under other names. One of them is unit costing, which is used to calculate the cost of banking services by determining the cost and consumption of each unit of output of functions required to deliver the service. ABC in very basic terms may provide very good payback for businesses. Some of the benefits that relate directly to the financial services industry are: Identification of the most profitable customers; more accurate product and service pricing; increase product profitability; well-organized process costs.

Keywords: profitability, activity-based costing (ABC), management accounting, manufacture

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8658 Fake News Detection for Korean News Using Machine Learning Techniques

Authors: Tae-Uk Yun, Pullip Chung, Kee-Young Kwahk, Hyunchul Ahn

Abstract:

Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection using machine learning techniques over the past years. But, there have been no prior studies proposed an automated fake news detection method for Korean news to our best knowledge. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (topic modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as logistic regression, backpropagation network, support vector machine, and deep neural network can be applied. To validate the effectiveness of the proposed method, we collected about 200 short Korean news from Seoul National University’s FactCheck. which provides with detailed analysis reports from 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

Keywords: fake news detection, Korean news, machine learning, text mining

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8657 Evaluation of Anti-Inflammatory Activities in Wild Herb Urginea wightii

Authors: S. K. Hemalata, M. N. Shiva Kameshwari

Abstract:

The present work focusses on anti-inflammatory action of Urginea wightii in-vitro. Urginea wightii is a member of Hyacinthaceae and considered to be wonder plant because of its varied important medicinal properties. The plant is endemic to India, Africa, and Mediterranian regions. Presence of alkaloids, flavonoid-glycosides especially flavonone derivatives are responsible for the strong anti-inflammatory activity of Urginea wightii. In present research work, anti-inflammatory activity of methanol extract of the bulb powder was tested on Male Wistar Rats. In these test animals, inflammation was induced by injecting carrageenan as the irritant to induce paw edema in Wistar rats. Inflammation of Paw edema was treated with both plant extract and Pyrox gel a known synthetic anti-inflammatory drug through external application. The result indicated that anti-inflammatory activity of Urginea wightii extract was almost similar to the synthetic Pyrox gel. This disproves the modern world's scepticism towards the herbal medicines and encourages to rely on natural plant extracts.

Keywords: anti-inflammatory activity, flavonoid-glycosides, Pyrox gel, Urginia wightii

Procedia PDF Downloads 169
8656 An Automated R-Peak Detection Method Using Common Vector Approach

Authors: Ali Kirkbas

Abstract:

R peaks in an electrocardiogram (ECG) are signs of cardiac activity in individuals that reveal valuable information about cardiac abnormalities, which can lead to mortalities in some cases. This paper examines the problem of detecting R-peaks in ECG signals, which is a two-class pattern classification problem in fact. To handle this problem with a reliable high accuracy, we propose to use the common vector approach which is a successful machine learning algorithm. The dataset used in the proposed method is obtained from MIT-BIH, which is publicly available. The results are compared with the other popular methods under the performance metrics. The obtained results show that the proposed method shows good performance than that of the other. methods compared in the meaning of diagnosis accuracy and simplicity which can be operated on wearable devices.

Keywords: ECG, R-peak classification, common vector approach, machine learning

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8655 Electromyography Activity of the Rectus Femoris and Biceps Femoris Muscles during Prostration and Squat Exercise

Authors: M. K. Mohd Safee, W. A. B. Wan Abas, F. Ibrahim, N. A. Abu Osman, N. A Abdul Malik

Abstract:

This paper investigates the activity of the rectus femoris (RF) and biceps femoris (BF) in healthy subjects during salat (prostration) and specific exercise (squat exercise) using electromyography (EMG). A group of undergraduates aged between 19 to 25 years voluntarily participated in this study. The myoelectric activity of the muscles were recorded and analyzed. The finding indicated that there were contractions of the muscles during the salat and exercise with almost same EMG’s level. From the result, Wilcoxon’s Rank Sum test showed significant difference between prostration and squat exercise (p<0.05) but the differences was very small; RF (8.63%MVC) and BF (11.43%MVC). Therefore, salat may be useful in strengthening exercise and also in rehabilitation programs for lower limb activities. This pilot study conducted initial research into the biomechanical responses of human muscles in various positions of salat.

Keywords: electromyography, exercise, muscle, salat

Procedia PDF Downloads 720
8654 Image Classification with Localization Using Convolutional Neural Networks

Authors: Bhuyain Mobarok Hossain

Abstract:

Image classification and localization research is currently an important strategy in the field of computer vision. The evolution and advancement of deep learning and convolutional neural networks (CNN) have greatly improved the capabilities of object detection and image-based classification. Target detection is important to research in the field of computer vision, especially in video surveillance systems. To solve this problem, we will be applying a convolutional neural network of multiple scales at multiple locations in the image in one sliding window. Most translation networks move away from the bounding box around the area of interest. In contrast to this architecture, we consider the problem to be a classification problem where each pixel of the image is a separate section. Image classification is the method of predicting an individual category or specifying by a shoal of data points. Image classification is a part of the classification problem, including any labels throughout the image. The image can be classified as a day or night shot. Or, likewise, images of cars and motorbikes will be automatically placed in their collection. The deep learning of image classification generally includes convolutional layers; the invention of it is referred to as a convolutional neural network (CNN).

Keywords: image classification, object detection, localization, particle filter

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8653 Synthesis of Highly Sensitive Molecular Imprinted Sensor for Selective Determination of Doxycycline in Honey Samples

Authors: Nadia El Alami El Hassani, Soukaina Motia, Benachir Bouchikhi, Nezha El Bari

Abstract:

Doxycycline (DXy) is a cycline antibiotic, most frequently prescribed to treat bacterial infections in veterinary medicine. However, its broad antimicrobial activity and low cost, lead to an intensive use, which can seriously affect human health. Therefore, its spread in the food products has to be monitored. The scope of this work was to synthetize a sensitive and very selective molecularly imprinted polymer (MIP) for DXy detection in honey samples. Firstly, the synthesis of this biosensor was performed by casting a layer of carboxylate polyvinyl chloride (PVC-COOH) on the working surface of a gold screen-printed electrode (Au-SPE) in order to bind covalently the analyte under mild conditions. Secondly, DXy as a template molecule was bounded to the activated carboxylic groups, and the formation of MIP was performed by a biocompatible polymer by the mean of polyacrylamide matrix. Then, DXy was detected by measurements of differential pulse voltammetry (DPV). A non-imprinted polymer (NIP) prepared in the same conditions and without the use of template molecule was also performed. We have noticed that the elaborated biosensor exhibits a high sensitivity and a linear behavior between the regenerated current and the logarithmic concentrations of DXy from 0.1 pg.mL−1 to 1000 pg.mL−1. This technic was successfully applied to determine DXy residues in honey samples with a limit of detection (LOD) of 0.1 pg.mL−1 and an excellent selectivity when compared to the results of oxytetracycline (OXy) as analogous interfering compound. The proposed method is cheap, sensitive, selective, simple, and is applied successfully to detect DXy in honey with the recoveries of 87% and 95%. Considering these advantages, this system provides a further perspective for food quality control in industrial fields.

Keywords: doxycycline, electrochemical sensor, food control, gold nanoparticles, honey, molecular imprinted polymer

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8652 Machine Learning Strategies for Data Extraction from Unstructured Documents in Financial Services

Authors: Delphine Vendryes, Dushyanth Sekhar, Baojia Tong, Matthew Theisen, Chester Curme

Abstract:

Much of the data that inform the decisions of governments, corporations and individuals are harvested from unstructured documents. Data extraction is defined here as a process that turns non-machine-readable information into a machine-readable format that can be stored, for instance, in a database. In financial services, introducing more automation in data extraction pipelines is a major challenge. Information sought by financial data consumers is often buried within vast bodies of unstructured documents, which have historically required thorough manual extraction. Automated solutions provide faster access to non-machine-readable datasets, in a context where untimely information quickly becomes irrelevant. Data quality standards cannot be compromised, so automation requires high data integrity. This multifaceted task is broken down into smaller steps: ingestion, table parsing (detection and structure recognition), text analysis (entity detection and disambiguation), schema-based record extraction, user feedback incorporation. Selected intermediary steps are phrased as machine learning problems. Solutions leveraging cutting-edge approaches from the fields of computer vision (e.g. table detection) and natural language processing (e.g. entity detection and disambiguation) are proposed.

Keywords: computer vision, entity recognition, finance, information retrieval, machine learning, natural language processing

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8651 Community Structure Detection in Networks Based on Bee Colony

Authors: Bilal Saoud

Abstract:

In this paper, we propose a new method to find the community structure in networks. Our method is based on bee colony and the maximization of modularity to find the community structure. We use a bee colony algorithm to find the first community structure that has a good value of modularity. To improve the community structure, that was found, we merge communities until we get a community structure that has a high value of modularity. We provide a general framework for implementing our approach. We tested our method on computer-generated and real-world networks with a comparison to very known community detection methods. The obtained results show the effectiveness of our proposition.

Keywords: bee colony, networks, modularity, normalized mutual information

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8650 QSAR and Anti-Depressant Studies of Some Novel Phenothiazine Derivatives

Authors: D. L. Tambe, S. Dighe Nachiket

Abstract:

Objective: Depression is a common but serious illness and the phenothiazine derivatives shows prominent effect against the depression hence work was undertaken to validate this use scientifically. Material and Methods: Synthesis of phenothiazine derivatives are done by the substitution of various groups, but the basic scheme of synthesis is started with synthesis of 4-(Cyclohexylidene) Benzoic acid using PABA. After that with the further six step of synthesis of 3-(10H-phenothiazin-2-yl)-N, 5-diphenyl-4H-1, 2, 4-triazol-4-amine is done which is final product. Antidepressant activity of all the synthesized compounds was evaluated by despair swim test by using Sprague Dawley Rats. Standard drug imipramine was used as the control. In the despair swim test, all the synthesized derivatives showed antidepressant activity. Results: Among the all phenothiazine derivatives four compounds (6.6-7.2 (14H –phenyl ), 9.43 (1H OH), 8.50 (1H NH phenothiazine),6.85-8.21(14H phenyl), 8.50 (1H NH phenothiazine), 11.82 (1H – OH), 6.6-7.2 (8H –phenyl ), 9.43 (1H OH), 8.50 (1H NH phenothiazine), 4.2 (1H NH) and 6.85-8.21(8H phenyl), 8.50 (1H NH phenothiazine), 3.9 (1H NH) 11.82 (1H – OH) showed significant antidepressant activity comparing with control drug imipramine. Conclusion: Various Novel phenothiazine derivatives show more potent antidepressant activity and it plays more beneficial role in human health for the treatment of depression.

Keywords: antidepressant activities, despair swim test, phenothiazine, Sprague Dawley Rats

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8649 Voice Liveness Detection Using Kolmogorov Arnold Networks

Authors: Arth J. Shah, Madhu R. Kamble

Abstract:

Voice biometric liveness detection is customized to certify an authentication process of the voice data presented is genuine and not a recording or synthetic voice. With the rise of deepfakes and other equivalently sophisticated spoofing generation techniques, it’s becoming challenging to ensure that the person on the other end is a live speaker or not. Voice Liveness Detection (VLD) system is a group of security measures which detect and prevent voice spoofing attacks. Motivated by the recent development of the Kolmogorov-Arnold Network (KAN) based on the Kolmogorov-Arnold theorem, we proposed KAN for the VLD task. To date, multilayer perceptron (MLP) based classifiers have been used for the classification tasks. We aim to capture not only the compositional structure of the model but also to optimize the values of univariate functions. This study explains the mathematical as well as experimental analysis of KAN for VLD tasks, thereby opening a new perspective for scientists to work on speech and signal processing-based tasks. This study emerges as a combination of traditional signal processing tasks and new deep learning models, which further proved to be a better combination for VLD tasks. The experiments are performed on the POCO and ASVSpoof 2017 V2 database. We used Constant Q-transform, Mel, and short-time Fourier transform (STFT) based front-end features and used CNN, BiLSTM, and KAN as back-end classifiers. The best accuracy is 91.26 % on the POCO database using STFT features with the KAN classifier. In the ASVSpoof 2017 V2 database, the lowest EER we obtained was 26.42 %, using CQT features and KAN as a classifier.

Keywords: Kolmogorov Arnold networks, multilayer perceptron, pop noise, voice liveness detection

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8648 Electrophoretic Deposition of Ultrasonically Synthesized Nanostructured Conducting Poly(o-phenylenediamine)-Co-Poly(1-naphthylamine) Film for Detection of Glucose

Authors: Vaibhav Budhiraja, Chandra Mouli Pandey

Abstract:

The ultrasonic synthesis of nanostructured conducting copolymer is an effective technique to synthesize polymer with desired chemical properties. This tailored nanostructure, shows tremendous improvement in sensitivity and stability to detect a variety of analytes. The present work reports ultrasonically synthesized nanostructured conducting poly(o-phenylenediamine)-co-poly(1-naphthylamine) (POPD-co-PNA). The synthesized material has been characterized using Fourier transform infrared spectroscopy (FTIR), ultraviolet-visible spectroscopy, transmission electron microscopy, X-ray diffraction and cyclic voltammetry. FTIR spectroscopy confirmed random copolymerization, while UV-visible studies reveal the variation in polaronic states upon copolymerization. High crystallinity was achieved via ultrasonic synthesis which was confirmed by X-ray diffraction, and the controlled morphology of the nanostructures was confirmed by transmission electron microscopy analysis. Cyclic voltammetry shows that POPD-co-PNA has rather high electrochemical activity. This behavior was explained on the basis of variable orientations adopted by the conducting polymer chains. The synthesized material was electrophoretically deposited at onto indium tin oxide coated glass substrate which is used as cathode and parallel platinum plate as the counter electrode. The fabricated bioelectrode was further used for detection of glucose by crosslinking of glucose oxidase in the PODP-co-PNA film. The bioelectrode shows a surface-controlled electrode reaction with the electron transfer coefficient (α) of 0.72, charge transfer rate constant (ks) of 21.77 s⁻¹ and diffusion coefficient 7.354 × 10⁻¹⁵ cm²s⁻¹.

Keywords: conducting, electrophoretic, glucose, poly (o-phenylenediamine), poly (1-naphthylamine), ultrasonic

Procedia PDF Downloads 143
8647 The Benefits of Mountain Climbing in the Physical Well-Being of Young People

Authors: Zylfi Shehu, Rozeta Shatku

Abstract:

The aim of this study is the identification of the goods and the consequences it brings up the mountain climbing to the youth, how mountain climbing influences in physical activity and the health of young people. Taken to study 37 young people aged 18-30 years, 25 males and 12 females. The selection was made at random and voluntary. Subjects were not professionals but amateurs climbing in the mountain. They were informed and instructed for the test to be carried out. The ascent was made in January 2016 in the Mount of Gjallica in Kukës, Albania, the height of the mountain is 2489 m above sea level. Backpack for each subject weighing 32 kg. Time of ascent, attitude and descent was 6 days. In 22 males, 2 of them did not afford the ascent on the first day and went back. Of the 12 women, 5 of them withdrew on the first day. During the descent on day six, 20 males 7 of them had minor injuries, three with serious injuries. While a total of 7 women, 4 of them had minor injuries and one with serious injuries. Most of the men and women who deal with physical activity throughout life faced the light and were not injured, and the rest that were not dealt with physical activity were more injured. Lack of experience and knowledge was one of the causes of injuries. The subjects had anxiety all the time, uncertainty and fear of avalanches of snow and difficult terrain.

Keywords: climbing, physical activity, young people

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8646 Changes in EEG and Emotion Regulation in the Course of Inward-Attention Meditation Training

Authors: Yuchien Lin

Abstract:

This study attempted to investigate the changes in electroencephalography (EEG) and emotion regulation following eight-week inward-attention meditation training program. The subjects were 24 adults without meditation experiences divided into meditation and control groups. The quantitatively analyzed changes in psychophysiological parameters during inward-attention meditation, and evaluated the emotion scores assessed by the State-Trait Anxiety Inventory (STAI), the Positive and Negative Affect Schedule (PANAS), and the Emotion Regulation Scale (ERS). The results were found: (1) During meditation, significant EEG increased for theta-band activity in the frontal and the bilateral temporal areas, for alpha-band activity in the left and central frontal areas, and for gamma-band activity in the left frontal and the left temporal areas. (2) The meditation group had significantly higher positive affect in posttest than in pretest. (3) There was no significant difference in the changes of EEG spectral characteristics and emotion scores in posttest and pretest for the control group. In the present study, a unique meditative concentration task with a constant level of moderate mental effort focusing on the center of brain was used, so as to enhance frontal midline theta, alpha, and gamma-band activity. These results suggest that this mental training allows individual reach a specific mental state of relaxed but focused awareness. The gamma-band activity, in particular, enhanced over left frontoparietal area may suggest that inward-attention meditation training involves temporal integrative mechanisms and may induce short-term and long-term emotion regulation abilities.

Keywords: meditation, EEG, emotion regulation, gamma activity

Procedia PDF Downloads 215