Search results for: ray patterns
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2858

Search results for: ray patterns

1418 Automatic Identification and Monitoring of Wildlife via Computer Vision and IoT

Authors: Bilal Arshad, Johan Barthelemy, Elliott Pilton, Pascal Perez

Abstract:

Getting reliable, informative, and up-to-date information about the location, mobility, and behavioural patterns of animals will enhance our ability to research and preserve biodiversity. The fusion of infra-red sensors and camera traps offers an inexpensive way to collect wildlife data in the form of images. However, extracting useful data from these images, such as the identification and counting of animals remains a manual, time-consuming, and costly process. In this paper, we demonstrate that such information can be automatically retrieved by using state-of-the-art deep learning methods. Another major challenge that ecologists are facing is the recounting of one single animal multiple times due to that animal reappearing in other images taken by the same or other camera traps. Nonetheless, such information can be extremely useful for tracking wildlife and understanding its behaviour. To tackle the multiple count problem, we have designed a meshed network of camera traps, so they can share the captured images along with timestamps, cumulative counts, and dimensions of the animal. The proposed method takes leverage of edge computing to support real-time tracking and monitoring of wildlife. This method has been validated in the field and can be easily extended to other applications focusing on wildlife monitoring and management, where the traditional way of monitoring is expensive and time-consuming.

Keywords: computer vision, ecology, internet of things, invasive species management, wildlife management

Procedia PDF Downloads 138
1417 Depositional Facies, High Resolution Sequence Stratigraphy, Reservoir Characterization of Early Oligocene Carbonates (Mukta Formation) Of North & Northwest of Heera, Mumbai Offshore

Authors: Almas Rajguru, Archana Kamath, Rachana Singh

Abstract:

The study aims to determine the depositional facies, high-resolution sequence stratigraphy, and diagenetic processes of Early Oligocene carbonates in N & N-W of Heera, Mumbai Offshore. Foraminiferal assemblage and microfacies from cores of Well A, B, C, D and E are indicative of facies association related to four depositional environments, i.e., restricted inner lagoons-tidal flats, shallow open lagoons, high energy carbonate bars-shoal complex and deeper mid-ramps of a westerly dipping homoclinal carbonate ramp. Two high-frequency (4th Order) depositional sequences bounded by sequence boundary, DS1 and DS2, displaying hierarchical stacking patterns, are identified and correlated across wells. Vadose zone diagenesis effect during short diastem/ subaerial exposure has rendered good porosity due to dissolution in HST carbonates and occasionally affected underlying TST sediments (Well D, C and E). On mapping and correlating the sequences, the presence of thin carbonate bars that can be potential reservoirs are envisaged along NW-SE direction, towards north and south of Wells E, D and C. A more pronounced development of these bars in the same orientation can be anticipated towards the west of the study area.

Keywords: sequence stratigraphy, depositional facies, diagenesis petrography, early Oligocene, Mumbai offshore

Procedia PDF Downloads 77
1416 Recognizing Customer Preferences Using Review Documents: A Hybrid Text and Data Mining Approach

Authors: Oshin Anand, Atanu Rakshit

Abstract:

The vast increment in the e-commerce ventures makes this area a prominent research stream. Besides several quantified parameters, the textual content of reviews is a storehouse of many information that can educate companies and help them earn profit. This study is an attempt in this direction. The article attempts to categorize data based on a computed metric that quantifies the influencing capacity of reviews rendering two categories of high and low influential reviews. Further, each of these document is studied to conclude several product feature categories. Each of these categories along with the computed metric is converted to linguistic identifiers and are used in an association mining model. The article makes a novel attempt to combine feature attraction with quantified metric to categorize review text and finally provide frequent patterns that depict customer preferences. Frequent mentions in a highly influential score depict customer likes or preferred features in the product whereas prominent pattern in low influencing reviews highlights what is not important for customers. This is achieved using a hybrid approach of text mining for feature and term extraction, sentiment analysis, multicriteria decision-making technique and association mining model.

Keywords: association mining, customer preference, frequent pattern, online reviews, text mining

Procedia PDF Downloads 388
1415 Structural and Magnetic Properties of NiFe2O4 Spinel Ferrite Nanoparticles Synthesized by Starch-Assisted Sol-Gel Auto-Combustion Method

Authors: R. S. Yadav, J. Havlica, I. Kuřitka, Z. Kozakova, J. Masilko, L. Kalina, M. Hajdúchová, V. Enev, J. Wasserbauer

Abstract:

Nickel spinel ferrite NiFe2O4 nanoparticles with different particle size at different annealing temperature were synthesized using the starch-assisted sol-gel auto-combustion method. The synthesized nanoparticles were characterized by conventional powder X-ray diffraction (XRD) spectroscopy, Raman Spectroscopy, Fourier Transform Infrared Spectroscopy, Field-Emission Scanning Electron Microscopy, X-ray Photoelectron Spectroscopy and Vibrating Sample Magnetometer. The XRD patterns confirmed the formation of NiFe2O4 spinel ferrite nanoparticles. Field-Emission Scanning Electron Microscopy revealed that particles are of spherical morphology with particle size 5-20 nm at lower annealing temperature. An infrared spectroscopy study showed the presence of two principal absorption bands in the frequency range around 525 cm-1 (ν1) and around 340 cm-1 (ν2); which indicate the presence of tetrahedral and octahedral group complexes, respectively, within the spinel ferrite nanoparticles. Raman spectroscopy study also indicated the change in octahedral and tetrahedral site related Raman modes in nickel ferrite nanoparticles with change of particle size. This change in magnetic behavior with change of particle size of NiFe2O4 nanoparticles was observed.

Keywords: nickel ferrite, nanoparticles, magnetic property, NiFe2O4

Procedia PDF Downloads 383
1414 AI-Driven Forecasting Models for Anticipating Oil Market Trends and Demand

Authors: Gaurav Kumar Sinha

Abstract:

The volatility of the oil market, influenced by geopolitical, economic, and environmental factors, presents significant challenges for stakeholders in predicting trends and demand. This article explores the application of artificial intelligence (AI) in developing robust forecasting models to anticipate changes in the oil market more accurately. We delve into various AI techniques, including machine learning, deep learning, and time series analysis, that have been adapted to analyze historical data and current market conditions to forecast future trends. The study evaluates the effectiveness of these models in capturing complex patterns and dependencies in market data, which traditional forecasting methods often miss. Additionally, the paper discusses the integration of external variables such as political events, economic policies, and technological advancements that influence oil prices and demand. By leveraging AI, stakeholders can achieve a more nuanced understanding of market dynamics, enabling better strategic planning and risk management. The article concludes with a discussion on the potential of AI-driven models in enhancing the predictive accuracy of oil market forecasts and their implications for global economic planning and strategic resource allocation.

Keywords: AI forecasting, oil market trends, machine learning, deep learning, time series analysis, predictive analytics, economic factors, geopolitical influence, technological advancements, strategic planning

Procedia PDF Downloads 35
1413 A Verification Intellectual Property for Multi-Flow Rate Control on Any Single Flow Bus Functional Model

Authors: Pawamana Ramachandra, Jitesh Gupta, Saranga P. Pogula

Abstract:

In verification of high volume and complex packet processing IPs, finer control of flow management aspects (for example, rate, bits/sec etc.) per flow class (or a virtual channel or a software thread) is needed. When any Software/Universal Verification Methodology (UVM) thread arbitration is left to the simulator (e.g., Verilog Compiler Simulator (VCS) or Incisive Enterprise Simulator core simulation engine (NCSIM)), it is hard to predict its pattern of resulting distribution of bandwidth by the simulator thread arbitration. In many cases, the patterns desired in a test scenario may not be accomplished as the simulator might give a different distribution than what was required. This can lead to missing multiple traffic scenarios, specifically deadlock and starvation related. We invented a component (namely Flow Manager Verification IP) to be intervening between the application (test case) and the protocol VIP (with UVM sequencer) to control the bandwidth per thread/virtual channel/flow. The Flow Manager has knobs visible to the UVM sequence/test to configure the required distribution of rate per thread/virtual channel/flow. This works seamlessly and produces rate stimuli to further harness the Design Under Test (DUT) with asymmetric inputs compared to the programmed bandwidth/Quality of Service (QoS) distributions in the Design Under Test.

Keywords: flow manager, UVM sequencer, rated traffic generation, quality of service

Procedia PDF Downloads 99
1412 Towards a Broader Understanding of Journal Impact: Measuring Relationships between Journal Characteristics and Scholarly Impact

Authors: X. Gu, K. L. Blackmore

Abstract:

The impact factor was introduced to measure the quality of journals. Various impact measures exist from multiple bibliographic databases. In this research, we aim to provide a broader understanding of the relationship between scholarly impact and other characteristics of academic journals. Data used for this research were collected from Ulrich’s Periodicals Directory (Ulrichs), Cabell’s (Cabells), and SCImago Journal & Country Rank (SJR) from 1999 to 2015. A master journal dataset was consolidated via Journal Title and ISSN. We adopted a two-step analysis process to study the quantitative relationships between scholarly impact and other journal characteristics. Firstly, we conducted a correlation analysis over the data attributes, with results indicating that there are no correlations between any of the identified journal characteristics. Secondly, we examined the quantitative relationship between scholarly impact and other characteristics using quartile analysis. The results show interesting patterns, including some expected and others less anticipated. Results show that higher quartile journals publish more in both frequency and quantity, and charge more for subscription cost. Top quartile journals also have the lowest acceptance rates. Non-English journals are more likely to be categorized in lower quartiles, which are more likely to stop publishing than higher quartiles. Future work is suggested, which includes analysis of the relationship between scholars and their publications, based on the quartile ranking of journals in which they publish.

Keywords: academic journal, acceptance rate, impact factor, journal characteristics

Procedia PDF Downloads 304
1411 Dynamics of Museum Visitors’ Experiences Studies: A Bibliometric Analysis

Authors: Tesfaye Fentaw Nigatu, Alexander Trupp, Teh Pek Yen

Abstract:

Research on museums and the experiences of visitors has flourished in recent years, especially after museums became centers of edutainment beyond preserving heritage resources. This paper aims to comprehensively understand the changes, continuities, and future research development directions of museum visitors’ experiences. To identify current research trends, the paper summarizes and analyses research article publications from 1986 to 2023 on museum visitors' experiences. Bibliometric analysis software VOSviewer and Harzing POP (Publish or Perish) were used to analyze 407 academic articles. The articles were generated from the Scopus database. The study attempted to map new insights for future scholars and academics to expand the scope of museum visitors’ experience studies by analyzing keywords, citation patterns, influential articles in the field, publication trends, collaborations between authors, institutions, and clusters of highly cited articles. Accessibility to museums, social media usage within museums, aesthetics in museum settings, mixed reality experiences, sustainability issues, and emotions have emerged as key research areas in the study of museum visitors' experiences. The results benefit stakeholders and researchers in advancing the collective progress of considering recent research trends to stay informed about the latest developments and breakthroughs in the global academic landscape and visitors’ experiences development in the museum.

Keywords: bibliometric analysis, museum, network analysis, visitors’ experiences, visual analysis

Procedia PDF Downloads 68
1410 Mathematical Study for Traffic Flow and Traffic Density in Kigali Roads

Authors: Kayijuka Idrissa

Abstract:

This work investigates a mathematical study for traffic flow and traffic density in Kigali city roads and the data collected from the national police of Rwanda in 2012. While working on this topic, some mathematical models were used in order to analyze and compare traffic variables. This work has been carried out on Kigali roads specifically at roundabouts from Kigali Business Center (KBC) to Prince House as our study sites. In this project, we used some mathematical tools to analyze the data collected and to understand the relationship between traffic variables. We applied the Poisson distribution method to analyze and to know the number of accidents occurred in this section of the road which is from KBC to Prince House. The results show that the accidents that occurred in 2012 were at very high rates due to the fact that this section has a very narrow single lane on each side which leads to high congestion of vehicles, and consequently, accidents occur very frequently. Using the data of speeds and densities collected from this section of road, we found that the increment of the density results in a decrement of the speed of the vehicle. At the point where the density is equal to the jam density the speed becomes zero. The approach is promising in capturing sudden changes on flow patterns and is open to be utilized in a series of intelligent management strategies and especially in noncurrent congestion effect detection and control.

Keywords: statistical methods, traffic flow, Poisson distribution, car moving technics

Procedia PDF Downloads 282
1409 Iris Feature Extraction and Recognition Based on Two-Dimensional Gabor Wavelength Transform

Authors: Bamidele Samson Alobalorun, Ifedotun Roseline Idowu

Abstract:

Biometrics technologies apply the human body parts for their unique and reliable identification based on physiological traits. The iris recognition system is a biometric–based method for identification. The human iris has some discriminating characteristics which provide efficiency to the method. In order to achieve this efficiency, there is a need for feature extraction of the distinct features from the human iris in order to generate accurate authentication of persons. In this study, an approach for an iris recognition system using 2D Gabor for feature extraction is applied to iris templates. The 2D Gabor filter formulated the patterns that were used for training and equally sent to the hamming distance matching technique for recognition. A comparison of results is presented using two iris image subjects of different matching indices of 1,2,3,4,5 filter based on the CASIA iris image database. By comparing the two subject results, the actual computational time of the developed models, which is measured in terms of training and average testing time in processing the hamming distance classifier, is found with best recognition accuracy of 96.11% after capturing the iris localization or segmentation using the Daughman’s Integro-differential, the normalization is confined to the Daugman’s rubber sheet model.

Keywords: Daugman rubber sheet, feature extraction, Hamming distance, iris recognition system, 2D Gabor wavelet transform

Procedia PDF Downloads 65
1408 Attachment Patterns in a Sample of South African Children at Risk in Middle Childhood

Authors: Renate Gericke, Carol Long

Abstract:

Despite the robust empirical support of attachment, advancement in the description and conceptualization of attachment has been slow and has not significantly advanced beyond the identification of attachment security or type (namely, secure, avoidant, ambivalent and disorganized). This has continued despite papers arguing for theoretical refinement in the classification of attachment presentations. For thinking and practice to advance, it is critically important that these categories and their assessment be interrogated in different contexts and across developmental age. To achieve this, a quantitative design was used with descriptive and inferential statistics, and general linear models were employed to analyze the data. The Attachment Story Completion Test (ASCT) was administered to 105 children between the ages of eight and twelve from socio-economically deprived contexts with high exposure to trauma. A staggering 93% of the children had insecure attachments (specifically, avoidant 37%, disorganized 34% and ambivalent 22%) and attachment was more complex than currently conceptualized in the attachment literature. Primary attachment did not only present as one of four discreet categories, but 70% of the sample had a complex attachment with more than one type of maternal attachment style. Attachment intensity also varied along a continuum (between 1 and 5). The findings have implications for a) research that has not considered the potential complexity of attachment or attachment intensity, b) policy to more actively support mother-infant dyads, particularly in high-risk contexts and c) question the applicability of a western conceptualization of a primary maternal attachment figure in non-western collectivist societies.

Keywords: attachment, children at risk, middle childhood, non-western context

Procedia PDF Downloads 192
1407 Development of Restricted Formula SAE Intake Manifold Using 1D and Flow Simulations Based on Track Analysis

Authors: Sahil Kapahi

Abstract:

A Formula SAE competition is characterized by typical track layouts having slaloms, tight corners and short straights, which favor a particular range of engine speed for a given set of gear ratios. Therefore, it is imperative that the power-train is optimized for the corresponding engine rpm band. This paper describes the process of designing, simulating and validating an air intake manifold for an inline four cylinder four-stroke internal combustion gasoline engine based on analysis of required vehicle performance. The requirements for the design of subject intake were set considering the rules of FSAE competitions and analysis of engine performance patterns for typical competition scenarios, carried out using OPTIMUMLAP software. Manifold geometry was optimized using results of air flow simulations performed on ANSYS CFX, and subsequent effect of this geometry on the engine was modeled using 1D simulation on Ricardo WAVE. A design was developed to meet the targeted performance standards in terms of engine torque output and volumetric efficiency. Finally, the intake manifold was manufactured and assembled onto the vehicle, and the engine output of the vehicle with the designed intake was studied using a dynamometer. The results of the dynamometer testing were then validated against predicted values derived from the Ricardo WAVE modeling and benefits to performance of the vehicle were established.

Keywords: 1 D Simulation, air flow simulation, ANSYS CFX, four-stroke engine, OPTIMUM LAP, Ricardo WAVE

Procedia PDF Downloads 246
1406 Production of Novel Antibiotics by Importing eryK and eryG Genes in Streptomyces fradiae

Authors: Neda Gegar Goshe, Hossein Rassi

Abstract:

The antibacterial properties of macrolide antibiotics (such as erythromycin and tylosin) depend ultimately on the glycosylation of otherwise inactive polyketide lactones. Among the sugars commonly found in such macrolides are various 6-deoxyhexoses including the 3-dimethylamino sugars mycaminose and desosamine (4-deoxymycaminose). Some macrolides (such as tylosin) possess multiple sugar moieties, whereas others (such as erythromycin) have two sugar substituents. Streptomyces fradiae is an ideal host for development of generic polyketide-overproducing strains because it contains three of the most common precursors-malonyl-CoA, methylmalonyl-CoA and ethylmalonyl-CoA-used by modular PKS, and is a host that is amenable to genetic manipulation. As patterns of glycosylation markedly influence a macrolide's drug activity, there is considerable interest in the possibility of using combinatorial biosynthesis to generate new pairings of polyketide lactones with sugars, especially 6-deoxyhexoses. Here, we report a successful attempt to alter the aminodeoxyhexose-biosynthetic capacity of Streptomyces fradiae (a producer of tylosin) by importing genes from the erythromycin producer Saccharopolyspora erythraea. The biotransformation of erythromycin-D into the desired major component erythromycin-A involves two final enzymatic reactions, EryK-catalyzed hydroxylation at the C-12 position of the aglycone and EryG-catalyzed O methylation at the C-3 position of macrose .This engineered S. fradiae produced substantial amounts of two potentially useful macrolides that had not previously been obtained by fermentation.

Keywords: Streptomyces fradiae, eryK and eryG genes, tylosin, antibiotics

Procedia PDF Downloads 325
1405 Personality as a Predictor of Knowledge Hiding Behavior: Case Study of Alpha Electronics

Authors: Sadeeqa Khan, Muhammad Usman

Abstract:

Employees’ knowledge hiding behaviors can be detrimental to employees’ interpersonal relationships and individual and organizational learning and creativity. However, to the best of the authors’ knowledge, the literature on the contingencies, antecedents and outcomes of employees’ knowledge hiding behaviors is still in its infancy. On the other hand, not everyone who hides knowledge hides it the same way, as individuals are different, so do their behaviors. This study explores the links between employees’ personality traits and their knowledge hiding behaviors. By using a single case study as a research methodology and collecting data through 28 semi-structured interviews from employees working in Alpha Electronics (the pseudo name of the company to ascertain anonymity) operating in Pakistan, we foreground the patterns of relationships between employees’ personality traits and knowledge hiding behaviors – rationalized hiding, evasive hiding and playing dumb. Our findings suggest that employees high on extraversion involve in evasive knowledge hiding; while employees low on extraversion (introverts) demonstrate rationalized hiding. Moreover, both extrovert and introvert employees involve in playing dumb in situations that involve risk for their jobs and careers. For instance, when knowledge is requested from their managers, both extrovert and introvert employees tend to play dumb, as in such cases, evasive and rationalized hiding can be harmful to their job and career-related interests and motives. Other than theoretical contributions, the study offers important implications for organizations faced with the challenges of shortage of skills and knowledge.

Keywords: knowledge hiding, personality, rationalized hiding, playing dumb, evasive hiding

Procedia PDF Downloads 215
1404 Isolation, Identification and Antimicrobial Susceptibility of Mycobacterium tuberculosis among Pulmonary Tuberculosis Patients

Authors: Naima Nur, Safa Islam, Saeema Islam, Faridul Alam

Abstract:

Background: Drug-resistant pulmonary tuberculosis (DR-PTB), particularly multidrug-resistant tuberculosis (MDR-TB) and pre-extensive drug-resistant (pre-XDR), is a major challenge in effectively controlling TB, especially in developing. This study aimed to identify the strains of M. tuberculosis complex (MTC) and drug resistance patterns among the pulmonary tuberculosis patients. Methods: The study used a cross-sectional design, and 815 patients were recruited randomly in three study periods. In the first-period, 210 treated PTB patients, who were completed their treatment, received their diagnoses using light microscopy, fluorescence microscopy and cultured on Lowenstein-Jensen (L-J) slant, and then strains were identified as MTC by biochemical tests, and then sensitivity test in National Institute of Diseases of the Chest and Hospital. In the second-period, 220 re-treated PTB patients, who were completed their treatment, received their diagnoses using culture on L-J slant, line probe assay (LPA), and GeneXpert in the same hospital. In the last-period, during treatment, 385 MDR-PTB patients received their diagnoses using culture on L-J slant and LPA in the same hospital. Results: Among sixty-two (29.5%) PTB patients, 13% were sensitive to all first-line anti-TB drugs, 26% were MDR-TB patients, and 14.2% were pre-XDR-TB among 14 MDR-TB patients. After three years, 31% were MDR-TB among 220 re-treated PTB patients. After five years, 16.4% was pre-XDR-TB among 385 MDR-TB patients. Compared to females, male patients were significantly higher at all times. Conclusion: The current study demonstrated that in three study periods, the proportions of DR-TB, MDR-TB, and pre-XDR patients were an alarming issue and increasing daily.

Keywords: multi-drug resistant, drug-resistant, pre-extensive drug resistant, pulmonary tuberculosis

Procedia PDF Downloads 55
1403 Characteristics of Business Models of Industrial-Internet-of-Things Platforms

Authors: Peter Kress, Alexander Pflaum, Ulrich Loewen

Abstract:

The number of Internet-of-Things (IoT) platforms is steadily increasing across various industries, especially for smart factories, smart homes and smart mobility. Also in the manufacturing industry, the number of Industrial-IoT platforms is growing. Both IT players, start-ups and increasingly also established industry players and small-and-medium-enterprises introduce offerings for the connection of industrial equipment on platforms, enabled by advanced information and communication technology. Beside the offered functionalities, the established ecosystem of partners around a platform is one of the key differentiators to generate a competitive advantage. The key question is how platform operators design the business model around their platform to attract a high number of customers and partners to co-create value for the entire ecosystem. The present research tries to answer this question by determining the key characteristics of business models of successful platforms in the manufacturing industry. To achieve that, the authors selected an explorative qualitative research approach and created an inductive comparative case study. The authors generated valuable descriptive insights of the business model elements (e.g., value proposition, pricing model or partnering model) of various established platforms. Furthermore, patterns across the various cases were identified to derive propositions for the successful design of business models of platforms in the manufacturing industry.

Keywords: industrial-internet-of-things, business models, platforms, ecosystems, case study

Procedia PDF Downloads 243
1402 Defect Identification in Partial Discharge Patterns of Gas Insulated Switchgear and Straight Cable Joint

Authors: Chien-Kuo Chang, Yu-Hsiang Lin, Yi-Yun Tang, Min-Chiu Wu

Abstract:

With the trend of technological advancement, the harm caused by power outages is substantial, mostly due to problems in the power grid. This highlights the necessity for further improvement in the reliability of the power system. In the power system, gas-insulated switches (GIS) and power cables play a crucial role. Long-term operation under high voltage can cause insulation materials in the equipment to crack, potentially leading to partial discharges. If these partial discharges (PD) can be analyzed, preventative maintenance and replacement of equipment can be carried out, there by improving the reliability of the power grid. This research will diagnose defects by identifying three different defects in GIS and three different defects in straight cable joints, for a total of six types of defects. The partial discharge data measured will be converted through phase analysis diagrams and pulse sequence analysis. Discharge features will be extracted using convolutional image processing, and three different deep learning models, CNN, ResNet18, and MobileNet, will be used for training and evaluation. Class Activation Mapping will be utilized to interpret the black-box problem of deep learning models, with each model achieving an accuracy rate of over 95%. Lastly, the overall model performance will be enhanced through an ensemble learning voting method.

Keywords: partial discharge, gas-insulated switches, straight cable joint, defect identification, deep learning, ensemble learning

Procedia PDF Downloads 78
1401 Development of Lectin-Based Biosensor for Glycoprofiling of Clinical Samples: Focus on Prostate Cancer

Authors: Dominika Pihikova, Stefan Belicky, Tomas Bertok, Roman Sokol, Petra Kubanikova, Jan Tkac

Abstract:

Since aberrant glycosylation is frequently accompanied by both physiological and pathological processes in a human body (cancer, AIDS, inflammatory diseases, etc.), the analysis of tumor-associated glycan patterns have a great potential for the development of novel diagnostic approaches. Moreover, altered glycoforms may assist as a suitable tool for the specificity and sensitivity enhancement in early-stage prostate cancer diagnosis. In this paper we discuss the construction and optimization of ultrasensitive sandwich biosensor platform employing lectin as glycan-binding protein. We focus on the immunoassay development, reduction of non-specific interactions and final glycoprofiling of human serum samples including both prostate cancer (PCa) patients and healthy controls. The fabricated biosensor was measured by label-free electrochemical impedance spectroscopy (EIS) with further lectin microarray verification. Furthermore, we analyzed different biosensor interfaces with atomic force microscopy (AFM) in nanomechanical mapping mode showing a significant differences in the altitude. These preliminary results revealing an elevated content of α-2,3 linked sialic acid in PCa patients comparing with healthy controls. All these experiments are important step towards development of point-of-care devices and discovery of novel glyco-biomarkers applicable in cancer diagnosis.

Keywords: biosensor, glycan, lectin, prostate cancer

Procedia PDF Downloads 372
1400 BodeACD: Buffer Overflow Vulnerabilities Detecting Based on Abstract Syntax Tree, Control Flow Graph, and Data Dependency Graph

Authors: Xinghang Lv, Tao Peng, Jia Chen, Junping Liu, Xinrong Hu, Ruhan He, Minghua Jiang, Wenli Cao

Abstract:

As one of the most dangerous vulnerabilities, effective detection of buffer overflow vulnerabilities is extremely necessary. Traditional detection methods are not accurate enough and consume more resources to meet complex and enormous code environment at present. In order to resolve the above problems, we propose the method for Buffer overflow detection based on Abstract syntax tree, Control flow graph, and Data dependency graph (BodeACD) in C/C++ programs with source code. Firstly, BodeACD constructs the function samples of buffer overflow that are available on Github, then represents them as code representation sequences, which fuse control flow, data dependency, and syntax structure of source code to reduce information loss during code representation. Finally, BodeACD learns vulnerability patterns for vulnerability detection through deep learning. The results of the experiments show that BodeACD has increased the precision and recall by 6.3% and 8.5% respectively compared with the latest methods, which can effectively improve vulnerability detection and reduce False-positive rate and False-negative rate.

Keywords: vulnerability detection, abstract syntax tree, control flow graph, data dependency graph, code representation, deep learning

Procedia PDF Downloads 170
1399 Influence of Loading Pattern and Shaft Rigidity on Laterally Loaded Helical Piles in Cohesion-Less Soil

Authors: Mohamed Hesham Hamdy Abdelmohsen, Ahmed Shawky Abdul Aziz, Mona Fawzy Al-Daghma

Abstract:

Helical piles are widely used as axially and laterally loaded deep foundations. Once they are required to resist bearing combined loads (BCLs), as axial compression and lateral thrust, different behaviour is expected, necessitating further investigation. The objective of the present article is to clarify the behaviour of a single helical pile of different shaft rigidity embedded in cohesion-less soil and subjected to simultaneous or successive loading patterns of BCLs. The study was first developed analytically and extended numerically. The numerical analysis was further verified through a laboratory experimental program on a set of helical pile models. The results indicate highly interactive effects of the studied parameters, but it is obviously confirmed that the pile performance increases with both the increase of shaft rigidity and the change of BCLs loading pattern from simultaneous to successive. However, it is noted that the increase of vertical load does not always enhance the lateral capacity but may cause a decrement in lateral capacity, as observed with helical piles of flexible shafts. This study provides insightful information for the design of helical piles in structures loaded by complex sequence of forces, wind turbines, and industrial shafts.

Keywords: helical pile, lateral loads, combined loads, cohesion-less soil, analytical, numerical

Procedia PDF Downloads 64
1398 Displacement Fields in Footing-Sand Interactions under Cyclic Loading

Authors: S. Joseph Antony, Z. K. Jahanger

Abstract:

Soils are subjected to cyclic loading in situ in situations such as during earthquakes and in the compaction of pavements. Investigations on the local scale measurement of the displacements of the grain and failure patterns within the soil bed under the cyclic loading conditions are rather limited. In this paper, using the digital particle image velocimetry (DPIV), local scale displacement fields of a dense sand medium interacting with a rigid footing are measured under the plane-strain condition for two commonly used types of cyclic loading, and the quasi-static loading condition for the purposes of comparison. From the displacement measurements of the grains, the failure envelopes of the sand media are also presented. The results show that, the ultimate cyclic bearing capacity (qultcyc) occurred corresponding to a relatively higher settlement value when compared with that of under the quasi-static loading. For the sand media under the cyclic loading conditions considered here, the displacement fields in the soil media occurred more widely in the horizontal direction and less deeper along the vertical direction when compared with that of under the quasi-static loading. The 'dead zone' in the sand grains beneath the footing is identified for all types of the loading conditions studied here. These grain-scale characteristics have implications on the resulting bulk bearing capacity of the sand media in footing-sand interaction problems.

Keywords: cyclic loading, DPIV, settlement, soil-structure interactions, strip footing

Procedia PDF Downloads 167
1397 Production of Novel Antibiotics of Tylosin by Importing eryK and eryG Genes in Streptomyces fradiae

Authors: Neda Gegar Goshe, M. Moradi, Hossein Rassi

Abstract:

The antibacterial properties of macrolide antibiotics (such as erythromycin and tylosin) depend ultimately on the glycosylation of otherwise inactive polyketide lactones. Among the sugars commonly found in such macrolides are various 6-deoxyhexoses including the 3-dimethylamino sugars mycaminose and desosamine (4-deoxymycaminose). Some macrolides (such as tylosin) possess multiple sugar moieties, whereas others (such as erythromycin) have two sugar substituents. Streptomyces fradiae is an ideal host for development of generic polyketide-overproducing strains because it contains three of the most common precursors-malonyl-CoA, methylmalonyl-CoA and ethylmalonyl-CoA-used by modular PKS, and is a host that is amenable to genetic manipulation. As patterns of glycosylation markedly influence a macrolide's drug activity, there is considerable interest in the possibility of using combinatorial biosynthesis to generate new pairings of polyketide lactones with sugars, especially 6-deoxyhexoses. Here, we report a successful attempt to alter the aminodeoxyhexose-biosynthetic capacity of Streptomyces fradiae (a producer of tylosin) by importing genes from the erythromycin producer Saccharopolyspora erythraea. The bio transformation of erythromycin-D into the desired major component erythromycin-A involves two final enzymatic reactions, EryK-catalyzed hydroxylation at the C-12 position of the aglycone and EryG-catalyzed O methylation at the C-3 position of macrose. This engineered S. fradiae produced substantial amounts of two potentially useful macrolides that had not previously been obtained by fermentation.

Keywords: tylosin, eryK and eryG genes, streptomyces fradiae

Procedia PDF Downloads 352
1396 Effect of Sr-Doping on Multiferroic Properties of Ca₁₋ₓSrₓMn₇O₁₂

Authors: Parul Jain, Jitendra Saha, L. C. Gupta, Satyabrata Patnaik, Ashok K. Ganguli, Ratnamala Chatterjee

Abstract:

This study shows how sensitively and drastically multiferroic properties of CaMn₇O₁₂ get modified by isovalent Sr-doping, namely, in Ca₁₋ₓSrₓMn₇O₁₂ for x as small as 0.01 and 0.02. CaMn₇O₁₂ is a type-II multiferroic, wherein polarization is caused by magnetic spin ordering. In this report magnetic and ferroelectric properties of Ca₁₋ₓSrₓMn₇O₁₂ (0 ≤ x ≤ 0.1) are investigated. Samples were prepared by wet sol gel technique using their respective nitrates; powders thus obtained were calcined and sintered in optimized conditions. The X-ray diffraction patterns of all samples doped with Sr concentrations in the range (0 ≤ x ≤ 10%) were found to be free from secondary phases. Magnetization versus temperature and magnetization versus field measurements were carried out using Quantum Design SQUID magnetometer. Pyroelectric current measurements were done for finding the polarization in the samples. Findings of the measurements are: (i) increase of Sr-doping in CaMn₇O₁₂ lattice i.e. for x ≤ 0.02, increases the polarization, whereas decreases the magnetization and the coercivity of the samples; (ii) the material with x = 0.02 exhibits ferroelectric polarization Ps which is more than double the Ps in the un-doped material and the magnetization M is reduced to less than half of that of the pure material; remarkably (iii) the modifications in Ps and M are reversed as x increases beyond x = 0.02 and for x = 0.10, Ps is reduced even below that for the pure sample; (iv) there is no visible change of the two magnetic transitions TN1 (90 K) and TN2 (48 K) of the pure material as a function of x. The strong simultaneous variations of Ps and M for x = 0.02 strongly suggest that either a basic modification of the magnetic structure of the material or a significant change of the coupling of P and M or possibly both.

Keywords: ferroelectric, isovalent, multiferroic, polarization, pyroelectric

Procedia PDF Downloads 462
1395 Career Path: A Tool to Support Talent Management

Authors: Rashi Mahato

Abstract:

Talent management represents an organization’s effort to attract, develop and retain highly skilled and valuable employees. The goal is to have people with capabilities and commitment needed for current and future organizational success. The organizational talent pool is its managerial talent referred to as leadership pipeline. It is managed through various systems and processes to help the organization source, reward, evaluate, develop and move employees into various functions and roles. The pipeline bends, turns, and sometimes breaks as organizations identify who is 'ready now' and who is 'on track' for larger leadership roles. From this perspective, talent management designs structured approach and a robust mechanism for high potential employees to meet organization’s needs. The paper attempts to provide a roadmap and a structured approach towards building a high performing organization through well-defined career path. Managers want career paths to be defined, so that an adequate number of individuals may be identified and prepared to fill future vacancies. Once career progression patterns are identified, more systematic forecasting of talent requirements is possible. For the development of senior management talent or leadership team, career paths are needed as guidelines for talent management across functional and organizational lines. Career path is one of the important tools for talent management and aligning talent with business strategy. This paper briefly describes the approach for career path and the concept of

Keywords: career path, career path framework, lateral movement, talent management

Procedia PDF Downloads 215
1394 Experimental and Numerical Studies on Earthquake Shear Rupture Generation

Authors: Louis N. Y. Wong

Abstract:

En-echelon fractures are commonly found in rocks, which appear as a special set of regularly oriented and spaced fractures. By using both experimental and numerical approaches, this study investigates the interaction among them, and how this interaction finally contributes to the development of a shear rupture (fault), especially in brittle natural rocks. Firstly, uniaxial compression tests are conducted on marble specimens containing en-echelon flaws. The latter is cut by using the water abrasive jet into the rock specimens. The fracturing processes of these specimens leading to the formation of a fault are observed in detail by the use of a high speed camera. The influences of the flaw geometry on the production of tensile cracks and shear cracks, which in turn dictate the coalescence patterns of the entire set of en-echelon flaws are comprehensively studied. Secondly, a numerical study based on a recently developed contact model, flat-joint contact model using the discrete element method (DEM) is carried out to model the present laboratory experiments. The numerical results provide a quantitative assessment of the interaction of en-echelon flaws. Particularly, the evolution of the stress field, as well as the characteristics of new crack initiation, propagation and coalescence associated with the generation of an eventual shear rupture are studied in detail. The numerical results are found to agree well with the experimental results obtained in both microscopic and macroscopic observations.

Keywords: discrete element method, en-echelon flaws, fault, marble

Procedia PDF Downloads 255
1393 Surface Pressure Distributions for a Forebody Using Pressure Sensitive Paint

Authors: Yi-Xuan Huang, Kung-Ming Chung, Ping-Han Chung

Abstract:

Pressure sensitive paint (PSP), which relies on the oxygen quenching of a luminescent molecule, is an optical technique used in wind-tunnel models. A full-field pressure pattern with low aerodynamic interference can be obtained, and it is becoming an alternative to pressure measurements using pressure taps. In this study, a polymer-ceramic PSP was used, using toluene as a solvent. The porous particle and polymer were silica gel (SiO₂) and RTV-118 (3g:7g), respectively. The compound was sprayed onto the model surface using a spray gun. The absorption and emission spectra for Ru(dpp) as a luminophore were respectively 441-467 nm and 597 nm. A Revox SLG-55 light source with a short-pass filter (550 nm) and a 14-bit CCD camera with a long-pass (600 nm) filter were used to illuminate PSP and to capture images. This study determines surface pressure patterns for a forebody of an AGARD B model in a compressible flow. Since there is no experimental data for surface pressure distributions available, numerical simulation is conducted using ANSYS Fluent. The lift and drag coefficients are calculated and in comparison with the data in the open literature. The experiments were conducted using a transonic wind tunnel at the Aerospace Science and Research Center, National Cheng Kung University. The freestream Mach numbers were 0.83, and the angle of attack ranged from -4 to 8 degree. Deviation between PSP and numerical simulation is within 5%. However, the effect of the setup of the light source should be taken into account to address the relative error.

Keywords: pressure sensitive paint, forebody, surface pressure, compressible flow

Procedia PDF Downloads 127
1392 Behavior of Laterally Loaded Multi-Helix Helical Piles Under Vertical Loading in Cohesive and Cohesionless Soils

Authors: Mona Fawzy Aldaghma

Abstract:

Helical piles are gaining popularity as a viable deep foundation alternative due to their quick installation and multipurpose use in compression and tension. These piles are commonly used as foundations for constructions such as solar panels, wind turbines and offshore platforms. These structures typically transfer various combinations of loads to their helical-pile foundations, including axial and lateral loads. Further research is needed to determine the effects of loading patterns that may act on helical piles as compounds of axial compression and lateral stresses. Multi helical piles are used to increase the efficiency of these piles. In this study, it investigate the behavior of laterally loaded helical piles with multiple helices when subjected to vertical loading conditions in both cohesive and cohesionless soils. Two models of intermediate shaft rigidity are studied with either two or three helices. Additionally, the vertical loading conditions were altered between successive and simultaneous loading. The cohesionless soil is sand with medium density and the cohesive soil is clay with medium cohesion. The study will carried out with numerical analysis using PLAXIS 3D and will be verified by an experimental tests. The numerical simulations reveal that helical piles exhibit different behavior in cohesive soil compared to cohesionless soil.

Keywords: helical piles, multi-helix, numerical modeling, PLAXIS 3D, cohesive soil, cohesionless soil, experimental

Procedia PDF Downloads 36
1391 Correlation of Residential Community Layout and Neighborhood Relationship: A Morphological Analysis of Tainan Using Space Syntax

Authors: Ping-Hung Chen, Han-Liang Lin

Abstract:

Taiwan has formed diverse settlement patterns in different time and space backgrounds. Various socio-network links are created between individuals, families, communities, and societies, and different living cultures are also derived. But rapid urbanization and social structural change have caused the creation of densely-packed assembly housing complexes and made neighborhood community upward developed. This, among others, seemed to have affected neighborhood relationship and also created social problems. To understand the complex relations and socio-spatial structure of the community, it is important to use mixed methods. This research employs the theory of space syntax to analyze the layout and structural indicators of the selected communities in Tainan city. On the other hand, this research does the survey about residents' interactions and the sense of community by questionnaire of the selected communities. Then the mean values of the syntax measures from each community were correlated with the results of the questionnaire using a Pearson correlation to examine how elements in physical design affect the sense of community and neighborhood relationship. In Taiwan, most urban morphology research methods are qualitative study. This paper tries to use space syntax to find out the correlation between the community layout and the neighborhood relationship. The result of this study could be used in future studies or improve the quality of residential communities in Taiwan.

Keywords: community layout, neighborhood relationship, space syntax, mixed-method

Procedia PDF Downloads 193
1390 Development of a Combustible Gas Detector with Two Sensor Modules to Enable Measuring Range of Low Concentration

Authors: Young Gyu Kim, Sangguk Ahn, Gyoutae Park, Hiesik Kim

Abstract:

In the gas industrial fields, there are many problems to detect extremely small amounts of combustible gas (CH₄) if a conventional semiconductor is used. Those reasons are that measuring is difficult at the low concentration level, the stabilization time is long, and an initial response time is slow. In this study, we propose a method to solve these issues using two specific sensors to overcome the circumstances of temperature and humidity. This idea is to combine a catalytic and a semiconductor type sensor and to utilize every advantage from every sensor’s characteristic. In order to achieve the goal, we reduced fluctuations of a gas sensor for temperature and humidity by applying designed circuits for sensing temperature and humidity. And we induced the best calibration line of gas sensors through adjusting a weight value corresponding to changeable patterns of temperature and humidity after their data are previously acquired and stored. We proposed and developed the gas leak detector using two sensor modules, which is first operated by a semiconductor sensor for measuring small gas quantities and second a catalytic type sensor is detected if measuring range of the first sensor is beyond. We conclusively verified characteristics of sharp sensitivity and fast response time against even at lower gas concentration level through experiments other than a conventional gas sensor. We think that our proposed idea is very useful if another gas leak is developed to enable measuring extremely small quantities of toxic and flammable gases.

Keywords: gas sensor, leak detector, lower concentration, and calibration

Procedia PDF Downloads 240
1389 The Impact of Artificial Intelligence in the Development of Textile and Fashion Industry

Authors: Basem Kamal Abasakhiroun Farag

Abstract:

Fashion, like many other areas of design, has undergone numerous developments over the centuries. The aim of the article is to recognize and evaluate the importance of advanced technologies in fashion design and to examine how they are transforming the role of contemporary fashion designers by transforming the creative process. It also discusses how contemporary culture is involved in such developments and how it influences fashion design in terms of conceptualization and production. The methodology used is based on examining various examples of the use of technology in fashion design and drawing parallels between what was feasible then and what is feasible today. Comparison of case studies, examples of existing fashion designs and experiences with craft methods; We therefore observe patterns that help us predict the direction of future developments in this area. Discussing the technological elements in fashion design helps us understand the driving force behind the trend. The research presented in the article shows that there is a trend towards significantly increasing interest and progress in the field of fashion technology, leading to the emergence of hybrid artisanal methods. In summary, as fashion technologies advance, their role in clothing production is becoming increasingly important, extending far beyond the humble sewing machine.

Keywords: fashion, identity, such, textiles ambient intelligence, proximity sensors, shape memory materials, sound sensing garments, wearable technology bio textiles, fashion trends, nano textiles, new materials, smart textiles, techno textiles fashion design, functional aesthetics, 3D printing.

Procedia PDF Downloads 67