Search results for: financial bubble detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6371

Search results for: financial bubble detection

2321 Health Assessment and Disorders of External Respiration Function among Physicians

Authors: A. G. Margaryan

Abstract:

Aims and Objectives: Assessment of health status and detection disorders of external respiration functions (ERF) during preventative medical examination among physicians of Armenia. Subjects and Methods: Overall, fifty-nine physicians (17 men and 42 women) were examined and spirometry was carried out. The average age of the physicians was 50 years old. The studies were conducted on the Micromedical MicroLab 3500 Spirometer. Results: 25.4% among 59 examined physicians are overweight; 22.0% of them suffer from obesity. Two physicians are currently smokers. About half of the examined physicians (50.8%) at the time of examination were diagnosed with some diseases and had different health-related problems (excluding the problems related to vision and hearing). FVC was 2.94±0.1, FEV1 – 2.64±0.1, PEF – 329.7±19.9, and FEV1%/FVC – 89.7±1.3. Pathological changes of ERF are identified in 23 (39.0%) cases. 28.8% of physicians had first degree of restrictive disorders, 3.4% – first degree of combined obstructive/ restrictive disorders, 6.8% – second degree of combined obstructive/ restrictive disorders. Only three physicians with disorders of the ERF were diagnosed with chronic bronchitis and bronchial asthma. There were no statistically significant changes in ERF depending on the severity of obesity (P> 0.05). Conclusion: The study showed the prevalence of ERF among physicians, observing mainly mild and moderate changes in ERF parameters.

Keywords: Armenia, external respiration function, health status, physicians

Procedia PDF Downloads 199
2320 Study of Electro Magnetic Acoustic Transducer to Detect Flaw in Pipeline

Authors: Yu-Lin Shen, Ming-Kuen Chang

Abstract:

In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electro Magnetic Acoustic Transducer Testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length.. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, NDT, artificial defect, ultrasonic testing

Procedia PDF Downloads 473
2319 Detecting HCC Tumor in Three Phasic CT Liver Images with Optimization of Neural Network

Authors: Mahdieh Khalilinezhad, Silvana Dellepiane, Gianni Vernazza

Abstract:

The aim of the present work is to build a model based on tissue characterization that is able to discriminate pathological and non-pathological regions from three-phasic CT images. Based on feature selection in different phases, in this research, we design a neural network system that has optimal neuron number in a hidden layer. Our approach consists of three steps: feature selection, feature reduction, and classification. For each ROI, 6 distinct set of texture features are extracted such as first order histogram parameters, absolute gradient, run-length matrix, co-occurrence matrix, autoregressive model, and wavelet, for a total of 270 texture features. We show that with the injection of liquid and the analysis of more phases the high relevant features in each region changed. Our results show that for detecting HCC tumor phase3 is the best one in most of the features that we apply to the classification algorithm. The percentage of detection between these two classes according to our method, relates to first order histogram parameters with the accuracy of 85% in phase 1, 95% phase 2, and 95% in phase 3.

Keywords: multi-phasic liver images, texture analysis, neural network, hidden layer

Procedia PDF Downloads 260
2318 Water Detection in Aerial Images Using Fuzzy Sets

Authors: Caio Marcelo Nunes, Anderson da Silva Soares, Gustavo Teodoro Laureano, Clarimar Jose Coelho

Abstract:

This paper presents a methodology to pixel recognition in aerial images using fuzzy $c$-means algorithm. This algorithm is a alternative to recognize areas considering uncertainties and inaccuracies. Traditional clustering technics are used in recognizing of multispectral images of earth's surface. This technics recognize well-defined borders that can be easily discretized. However, in the real world there are many areas with uncertainties and inaccuracies which can be mapped by clustering algorithms that use fuzzy sets. The methodology presents in this work is applied to multispectral images obtained from Landsat-5/TM satellite. The pixels are joined using the $c$-means algorithm. After, a classification process identify the types of surface according the patterns obtained from spectral response of image surface. The classes considered are, exposed soil, moist soil, vegetation, turbid water and clean water. The results obtained shows that the fuzzy clustering identify the real type of the earth's surface.

Keywords: aerial images, fuzzy clustering, image processing, pattern recognition

Procedia PDF Downloads 480
2317 Attendance Management System Implementation Using Face Recognition

Authors: Zainab S. Abdullahi, Zakariyya H. Abdullahi, Sahnun Dahiru

Abstract:

Student attendance in schools is a very important aspect in school management record. In recent years, security systems have become one of the most demanding systems in school. Every institute have its own method of taking attendance, many schools in Nigeria use the old fashion way of taking attendance. That is writing the students name and registration number in a paper and submitting it to the lecturer at the end of the lecture which is time-consuming and insecure, because some students can write for their friends without the lecturer’s knowledge. In this paper, we propose a system that takes attendance using face recognition. There are many automatic methods available for this purpose i.e. biometric attendance, but they all waste time, because the students have to follow a queue to put their thumbs on a scanner which is time-consuming. This attendance is recorded by using a camera attached in front of the class room and capturing the student images, detect the faces in the image and compare the detected faces with database and mark the attendance. The principle component analysis was used to recognize the faces detected with a high accuracy rate. The paper reviews the related work in the field of attendance system, then describe the system architecture, software algorithm and result.

Keywords: attendance system, face detection, face recognition, PCA

Procedia PDF Downloads 363
2316 The Relationship between Inventory Management and Profitability: A Comparative Research on Turkish Firms Operated in Weaving Industry, Eatables Industry, Wholesale and Retail Industry

Authors: Gamze Sekeroglu, Mikail Altan

Abstract:

Working capital is identified as firm’s all current assets. Inventories which are one of the working capital elements are very important among current assets for firms. Because, profitability is an indicator for firms’ financial success is provided with minimum cost and optimum inventory quantity. So in this study, it is investigated as comparatively that the effect of inventory management on the profitability of Turkish firms which operated in weaving industry, eatables industry, wholesale and retail industry in between 2003 – 2012 years. Research data consist of profitability ratios and inventory turnovers ratio calculated by using balance sheets and income statements of firms which operated in Borsa Istanbul (BIST). In this research, the relationship between inventories and profitability is investigated by using SPSS-20 software with regression and correlation analysis. The results achieved from three industry departments which exist in study interpreted as comparatively. Accordingly, it is determined that there is a positive relationship between inventory management and profitability in eatables industry. However, it was founded that there is no relationship between inventory management and profitability in weaving industry and wholesale and retail industry.

Keywords: profitability, regression analysis, inventory management, working capital

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2315 Rauvolfine B Isolated from the Bark of Rauvolfia reflexa (Apocynaceae) Induces Apoptosis through Activation of Caspase-9 Coupled with S Phase Cell Cycle Arrest

Authors: Mehran Fadaeinasab, Hamed Karimian, Najihah Mohd Hashim, Hapipah Mohd Ali

Abstract:

In this study, three indole alkaloids namely; rauvolfine B, macusine B, and isoreserpiline have been isolated from the dichloromethane crude extract of Rauvolfia reflexa bark (Apocynaceae). The structural elucidation of the isolated compounds has been performed using spectral methods such as UV, IR, MS, 1D, and 2D NMR. Rauvolfine B showed anti proliferation activity on HCT-116 cancer cell line, its cytotoxicity induction was observed using MTT assay in eight different cell lines. Annexin-V is serving as a marker for apoptotic cells and the Annexin-V-FITC assay was carried out to observe the detection of cell-surface Phosphatidylserine (PS). Apoptosis was confirmed by using caspase-8 and -9 assays. Cell cycle arrest was also investigated using flowcytometric analysis. rauvolfine B had exhibited significantly higher cytotoxicity against HCT-116 cell line. The treatment significantly arrested HCT-116 cells in the S phase. Together, the results presented in this study demonstrated that rauvolfine B inhibited the proliferation of HCT-116 cells and programmed cell death followed by cell cycle arrest.

Keywords: apocynacea, indole alkaloid, apoptosis, cell cycle arrest

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2314 Comparative Analysis of Patent Protection between Health System and Enterprises in Shanghai, China

Authors: Na Li, Yunwei Zhang, Yuhong Niu

Abstract:

The study discussed the patent protections of health system and enterprises in Shanghai. The comparisons of technical distribution and scopes of patent protections between Shanghai health system and enterprises were used by the methods of IPC classification, co-words analysis and visual social network. Results reflected a decreasing order within IPC A61 area, namely A61B, A61K, A61M, and A61F. A61B required to be further investigated. The highest authorized patents A61B17 of A61B of IPC A61 area was found. Within A61B17, fracture fixation, ligament reconstruction, cardiac surgery, and biopsy detection were regarded as common concerned fields by Shanghai health system and enterprises. However, compared with cardiac closure which Shanghai enterprises paid attention to, Shanghai health system was more inclined to blockages and hemostatic tools. The results also revealed that the scopes of patent protections of Shanghai enterprises were relatively centralized. Shanghai enterprises had a series of comprehensive strategies for protecting core patents. In contrast, Shanghai health system was considered to be lack of strategic patent protections for core patents.

Keywords: co-words analysis, IPC classification, patent protection, technical distribution

Procedia PDF Downloads 133
2313 Identifying the Barriers Facing Chinese Small and Medium-Sized Enterprises and Evaluating the Effectiveness of Public Supports

Authors: A. Yongsheng Guo, B. Obedat. Abdulazeez, C. Xiaoxian Zhu

Abstract:

This study aimed to identify the barriers to the development of small and medium-sized enterprises (SMEs) in China and build a theoretical framework to evaluate the support provided by the authorities and institutions. A grounded theory approach was adopted to collect and analyze data. 32 interviews were conducted with SME managers, and open, axial and selective coding was utilized to develop themes. Based on institutional theory, grounded theory models were used to present findings. The findings showed that the main barriers in the business environment were defaulting on contracts, bureaucracy in procedures, lack of financial and legal support, limited intermediaries and channels, and poor quality of products and services. This study found that many programs were provided to support SMEs. A theoretical framework was developed to evaluate the performance of the programs from the managers’ perspective. The concepts of economy, efficiency and effectiveness were used to evaluate the perceived value of the programs. This study suggests that specialized programs are needed to suit sector-specific requirements, and creative packages are helpful in supporting SMEs' growth.

Keywords: business support, public economics, public programme, SME

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2312 Glucose Monitoring System Using Machine Learning Algorithms

Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

Abstract:

The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

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2311 Fabrication of Modified Chitosan-Gold Nanoshell with Mercaptopropionic Acid(MPA) for γ-Aminobutyric Acid Detection as a Surface-Enhanced Raman Scattering Substrate

Authors: Bi Wa, Su-Yeon Kwon, Ik-Joong Kang

Abstract:

Surface-enhanced Raman Scattering (SERS) as the principle for enhancing Raman scattering by molecules adsorbed on rough metal surfaces or by nanostructures is used to detect the concentration change of γ-Aminobutyric Acid (GABA). GABA is the mainly inhibitory neurotransmitter in the mammalian central nervous system in the human body. It plays such significant role in reducing neuronal excitability throughout the nervous system. In this case, the Mercaptopropionic Acid (MPA) is used to modified chitosan –gold nanoshell, which enhances the absorption between GABA and Chitosan-gold nanoshell. The sulfur end of the MPA is linked to gold which is the surface of the chitosan nanoparticles via the very strong S–Au bond, while a functional group (carboxyl group) attached to GABA. The controlling of particles’ size and the surface morphology are also the important factors during the whole experiment. The particle around 100nm is using to link to MPA, and the range of GABA from 1mM to 30mM was detected by the Raman Scattering to obtain the calibrate curve. In this study, DLS, SEM, FT-IR, UV, SERS were used to analyze the products to obtain the conclusion.

Keywords: chitosan-gold nanoshell, mercaptopropionic acid, γ-aminobutyric acid, surface-enhanced raman scattering

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2310 Electroactive Ferrocenyl Dendrimers as Transducers for Fabrication of Label-Free Electrochemical Immunosensor

Authors: Sudeshna Chandra, Christian Gäbler, Christian Schliebe, Heinrich Lang

Abstract:

Highly branched dendrimers provide structural homogeneity, controlled composition, comparable size to biomolecules, internal porosity and multiple functional groups for conjugating reactions. Electro-active dendrimers containing multiple redox units have generated great interest in their use as electrode modifiers for development of biosensors. The electron transfer between the redox-active dendrimers and the biomolecules play a key role in developing a biosensor. Ferrocenes have multiple and electrochemically equivalent redox units that can act as electron “pool” in a system. The ferrocenyl-terminated polyamidoamine dendrimer is capable of transferring multiple numbers of electrons under the same applied potential. Therefore, they can be used for dual purposes: one in building a film over the electrode for immunosensors and the other for immobilizing biomolecules for sensing. Electrochemical immunosensor, thus developed, exhibit fast and sensitive analysis, inexpensive and involve no prior sample pre-treatment. Electrochemical amperometric immunosensors are even more promising because they can achieve a very low detection limit with high sensitivity. Detection of the cancer biomarkers at an early stage can provide crucial information for foundational research of life science, clinical diagnosis and prevention of disease. Elevated concentration of biomarkers in body fluid is an early indication of some type of cancerous disease and among all the biomarkers, IgG is the most common and extensively used clinical cancer biomarkers. We present an IgG (=immunoglobulin) electrochemical immunosensor using a newly synthesized redox-active ferrocenyl dendrimer of generation 2 (G2Fc) as glassy carbon electrode material for immobilizing the antibody. The electrochemical performance of the modified electrodes was assessed in both aqueous and non-aqueous media using varying scan rates to elucidate the reaction mechanism. The potential shift was found to be higher in an aqueous electrolyte due to presence of more H-bond which reduced the electrostatic attraction within the amido groups of the dendrimers. The cyclic voltammetric studies of the G2Fc-modified GCE in 0.1 M PBS solution of pH 7.2 showed a pair of well-defined redox peaks. The peak current decreased significantly with the immobilization of the anti-goat IgG. After the immunosensor is blocked with BSA, a further decrease in the peak current was observed due to the attachment of the protein BSA to the immunosensor. A significant decrease in the current signal of the BSA/anti-IgG/G2Fc/GCE was observed upon immobilizing IgG which may be due to the formation of immune-conjugates that blocks the tunneling of mass and electron transfer. The current signal was found to be directly related to the amount of IgG captured on the electrode surface. With increase in the concentration of IgG, there is a formation of an increasing amount of immune-conjugates that decreased the peak current. The incubation time and concentration of the antibody was optimized for better analytical performance of the immunosensor. The developed amperometric immunosensor is sensitive to IgG concentration as low as 2 ng/mL. Tailoring of redox-active dendrimers provides enhanced electroactivity to the system and enlarges the sensor surface for binding the antibodies. It may be assumed that both electron transfer and diffusion contribute to the signal transformation between the dendrimers and the antibody.

Keywords: ferrocenyl dendrimers, electrochemical immunosensors, immunoglobulin, amperometry

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2309 New Insights Into Fog Role In Atmospheric Deposition Using Satellite Images

Authors: Suruchi

Abstract:

This study aims to examine the spatial and temporal patterns of fog occurrences across Czech Republic. It utilizes satellite imagery and other data sources to achieve this goal. The main objective is to understand the role of fog in atmospheric deposition processes and its potential impact on the environment and ecosystems. Through satellite image analysis, the study will identify and categorize different types of fog, including radiation fog, orographic fog, and mountain fog. Fog detection algorithms and cloud type products will be evaluated to assess the frequency and distribution of fog events throughout the Czech Republic. Furthermore, the regions covered by fog will be classified based on their fog type and associated pollution levels. This will provide insights into the variability in fog characteristics and its implications for atmospheric deposition. Spatial analysis techniques will be used to pinpoint areas prone to frequent fog events and evaluate their pollution levels. Statistical methods will be employed to analyze patterns in fog occurrence over time and its connection with environmental factors. The ultimate goal of this research is to offer fresh perspectives on fog's role in atmospheric deposition processes, enhancing our understanding of its environmental significance and informing future research and environmental management initiatives.

Keywords: pollution, GIS, FOG, satellie, atmospheric deposition

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2308 The Relation between Body Mass Index and Menstrual Cycle Disorders in Medical Students of University Pelita Harapan, Indonesia

Authors: Gabriella Tjondro, Julita Dortua Laurentina Nainggolan

Abstract:

Introduction: There are several things affecting menstrual cycle, namely, nutritional status, diet, financial status of one’s household and exercises. The most commonly used parameter to calculate the fat in a human body is body mass index. Therefore, it is necessary to do research to prevent complications caused by menstrual disorder in the future. Design Study: This research is an observational analytical study with the cross-sectional-case control approach. Participants (n = 124; median age = 19.5 years ± SD 3.5) were classified into 2 groups: normal, NM (n = 62; BMI = 18-23 kg/m2) and obese, OB (n = 62; BMI = > 25 kg/m2). BMI was calculated from the equation; BMI = weight, kg/height, m2. Results: There were 79.10% from obese group who experienced menstrual cycle disorders (n=53, 79.10%; p value 0.00; OR 5.25) and 20.90% from normal BMI group with menstrual cycle disorders. There were several factors in this research that also influence the menstrual cycle disorders such as stress (44.78%; p value 0.00; OR 1.85), sleep disorders (25.37%; p value 0.00; OR 1.01), physical activities (25.37%; p value 0.00; OR 1.24) and diet (10.45%; p value 0.00; OR 1.07). Conclusion: There is a significant relation between body mass index (obese) and menstrual cycle disorders. However, BMI is not the only factor that affects the menstrual cycle disorders. There are several factors that also can affect menstrual cycle disorders, in this study we use stress, sleep disorders, physical activities and diet, in which none of them are dominant.

Keywords: menstrual disorders, menstrual cycle, obesity, body mass index, stress, sleep disorders, physical activities, diet

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2307 Integrating AI into Breast Cancer Diagnosis: Aligning Perspectives for Effective Clinical Practice

Authors: Mehrnaz Mostafavi, Mahtab Shabani, Alireza Azani, Fatemeh Ghafari

Abstract:

Artificial intelligence (AI) can transform breast cancer diagnosis and therapy by providing sophisticated solutions for screening, imaging interpretation, histopathological analysis, and treatment planning. This literature review digs into the many uses of AI in breast cancer treatment, highlighting the need for collaboration between AI scientists and healthcare practitioners. It emphasizes advances in AI-driven breast imaging interpretation, such as computer-aided detection and diagnosis (CADe/CADx) systems and deep learning algorithms. These have shown significant potential for improving diagnostic accuracy and lowering radiologists' workloads. Furthermore, AI approaches such as deep learning have been used in histopathological research to accurately predict hormone receptor status and categorize tumor-associated stroma from regular H&E stains. These AI-powered approaches simplify diagnostic procedures while providing insights into tumor biology and prognosis. As AI becomes more embedded in breast cancer care, it is crucial to ensure its ethical, efficient, and patient-focused implementation to improve outcomes for breast cancer patients ultimately.

Keywords: breast cancer, artificial intelligence, cancer diagnosis, clinical practice

Procedia PDF Downloads 66
2306 Development of a Real-Time Brain-Computer Interface for Interactive Robot Therapy: An Exploration of EEG and EMG Features during Hypnosis

Authors: Maryam Alimardani, Kazuo Hiraki

Abstract:

This study presents a framework for development of a new generation of therapy robots that can interact with users by monitoring their physiological and mental states. Here, we focused on one of the controversial methods of therapy, hypnotherapy. Hypnosis has shown to be useful in treatment of many clinical conditions. But, even for healthy people, it can be used as an effective technique for relaxation or enhancement of memory and concentration. Our aim is to develop a robot that collects information about user’s mental and physical states using electroencephalogram (EEG) and electromyography (EMG) signals and performs costeffective hypnosis at the comfort of user’s house. The presented framework consists of three main steps: (1) Find the EEG-correlates of mind state before, during, and after hypnosis and establish a cognitive model for state changes, (2) Develop a system that can track the changes in EEG and EMG activities in real time and determines if the user is ready for suggestion, and (3) Implement our system in a humanoid robot that will talk and conduct hypnosis on users based on their mental states. This paper presents a pilot study in regard to the first stage, detection of EEG and EMG features during hypnosis.

Keywords: hypnosis, EEG, robotherapy, brain-computer interface (BCI)

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2305 Optimized Simultaneous Determination of Theobromine and Caffeine in Fermented and Unfermented Cacao Beans and in Cocoa Products Using Step Gradient Solvent System in Reverse Phase HPLC

Authors: Ian Marc G. Cabugsa, Kim Ryan A. Won

Abstract:

Fast, reliable and simultaneous HPLC analysis of theobromine and caffeine in cacao and cocoa products was optimized in this study. The samples tested were raw, fermented, and roasted cacao beans as well as commercially available cocoa products. The HPLC analysis was carried out using step gradient solvent system with acetonitrile and water buffered with H3PO4 as the mobile phase. The HPLC system was optimized using 273 nm wavelength at 35 °C for the column temperature with a flow rate of 1.0 mL/min. Using this method, the theobromine percent recovery mean, Limit of Detection (LOD) and Limit of Quantification (LOQ) is 118.68(±3.38)%, 0.727 and 1.05 respectively. The percent recovery mean, LOD and LOQ for caffeine is 105.53(±3.25)%, 2.42 and 3.50 respectively. The inter-day and intra-day precision for theobromine is 4.31% and 4.48% respectively, while 7.02% and 7.03% was for caffeine respectively. Compared to the standard method in AOAC using methanol in isocratic solvent system, the results of the study produced lesser chromatogram noise with emphasis on theobromine and caffeine. The method is readily usable for cacao and cocoa substances analyses using HPLC with step gradient capability.

Keywords: cacao, caffeine, HPLC, step gradient solvent system, theobromine

Procedia PDF Downloads 279
2304 Development of Concurrent Engineering through the Application of Software Simulations of Metal Production Processing and Analysis of the Effects of Application

Authors: D. M. Eric, D. Milosevic, F. D. Eric

Abstract:

Concurrent engineering technologies are a modern concept in manufacturing engineering. One of the key goals in designing modern technological processes is further reduction of production costs, both in the prototype and the preparatory part, as well as during the serial production. Thanks to many segments of concurrent engineering, these goals can be accomplished much more easily. In this paper, we give an overview of the advantages of using modern software simulations in relation to the classical aspects of designing technological processes of metal deformation. Significant savings are achieved thanks to the electronic simulation and software detection of all possible irregularities in the functional-working regime of the technological process. In order for the expected results to be optimal, it is necessary that the input parameters are very objective and that they reliably represent the values ​of these parameters in real conditions. Since it is a metal deformation treatment here, the particularly important parameters are the coefficient of internal friction between the working material and the tools, as well as the parameters related to the flow curve of the processing material. The paper will give a presentation for the experimental determination of some of these parameters.

Keywords: production technologies, metal processing, software simulations, effects of application

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2303 Development of Paper Based Analytical Devices for Analysis of Iron (III) in Natural Water Samples

Authors: Sakchai Satienperakul, Manoch Thanomwat, Jutiporn Seedasama

Abstract:

A paper based analytical devices (PADs) for the analysis of Fe (III) ion in natural water samples is developed, using reagent from guava leaf extract. The extraction is simply performed in deionized water pH 7, where tannin extract is obtained and used as an alternative natural reagent. The PADs are fabricated by ink-jet printing using alkenyl ketene dimer (AKD) wax. The quantitation of Fe (III) is carried out using reagent from guava leaf extract prepared in acetate buffer at the ratio of 1:1. A color change to gray-purple is observed by naked eye when dropping sample contained Fe (III) ion on PADs channel. The reflective absorption measurement is performed for creating a standard curve. The linear calibration range is observed over the concentration range of 2-10 mg L-1. Detection limited of Fe (III) is observed at 2 mg L-1. In its optimum form, the PADs is stable for up to 30 days under oxygen free conditions. The small dimensions, low volume requirement and alternative natural reagent make the proposed PADs attractive for on-site environmental monitoring and analysis.

Keywords: green chemical analysis, guava leaf extract, lab on a chip, paper based analytical device

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2302 Hyperspectral Band Selection for Oil Spill Detection Using Deep Neural Network

Authors: Asmau Mukhtar Ahmed, Olga Duran

Abstract:

Hydrocarbon (HC) spills constitute a significant problem that causes great concern to the environment. With the latest technology (hyperspectral images) and state of the earth techniques (image processing tools), hydrocarbon spills can easily be detected at an early stage to mitigate the effects caused by such menace. In this study; a controlled laboratory experiment was used, and clay soil was mixed and homogenized with different hydrocarbon types (diesel, bio-diesel, and petrol). The different mixtures were scanned with HYSPEX hyperspectral camera under constant illumination to generate the hypersectral datasets used for this experiment. So far, the Short Wave Infrared Region (SWIR) has been exploited in detecting HC spills with excellent accuracy. However, the Near-Infrared Region (NIR) is somewhat unexplored with regards to HC contamination and how it affects the spectrum of soils. In this study, Deep Neural Network (DNN) was applied to the controlled datasets to detect and quantify the amount of HC spills in soils in the Near-Infrared Region. The initial results are extremely encouraging because it indicates that the DNN was able to identify features of HC in the Near-Infrared Region with a good level of accuracy.

Keywords: hydrocarbon, Deep Neural Network, short wave infrared region, near-infrared region, hyperspectral image

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2301 Sustainable Development: Evaluation of an Urban Neighborhood

Authors: Harith Mohammed Benbouali

Abstract:

The concept of sustainable development is becoming increasingly important in our society. The efforts of specialized agencies, cleverly portrayed in the media, allow a widespread environmental awareness. Far from the old environmental movement in the backward-looking nostalgia, the environment is combined with today's progress. Many areas now include these concerns in their efforts, this in order to try to reduce the negative impact of human activities on the environment. The quantitative dimension of development has given way to the quality aspect. However, this feature is not common, and the initial target was abandoned in favor of economic considerations. Specialists in the field of building and construction have constantly sought to further integrate the environmental dimension, creating a seal of high environmental quality buildings. The pursuit of well-being of neighborhood residents and the quality of buildings are also a hot topic in planning. Quality of life is considered so on, since financial concerns dominate to the detriment of the environment and the welfare of the occupants. This work concerns the development of an analytical method based on multiple indicators of objectives across the district. The quantification of indicators related to objectives allows the construction professional, the developer or the community, to quantify and compare different alternatives for development of a neighborhood. This quantification is based on the use of simulation tools and a multi-criteria aggregation.

Keywords: sustainable development, environment, district, indicators, multi-criteria analysis, evaluation

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2300 Detection of Total Aflatoxin in Flour of Wheat and Maize Samples in Albania Using ELISA

Authors: Aferdita Dinaku, Jonida Canaj

Abstract:

Aflatoxins are potentially toxic metabolites produced by certain kinds of fungi (molds) that are found naturally all over the world; they can contaminate food crops and pose a serious health threat to humans by mutagenic and carcinogenic effects. Several types of aflatoxin (14 or more) occur in nature. In Albanian nutrition, cereals (especially wheat and corn) are common ingredients in some traditional meals. This study aimed to investigate the presence of aflatoxins in the flour of wheat and maize that are consumed in Albania’s markets. The samples were collected randomly in different markets in Albania and detected by the ELISA method, measured in 450 nm. The concentration of total aflatoxins was analyzed by enzyme-linked immunosorbent assay (ELISA), and they were ranged between 0.05-1.09 ppb. However, the screened mycotoxin levels in the samples were lower than the maximum permissible limits of European Commission No 1881/2006 (4 μg/kg). The linearity of calibration curves was good for total aflatoxins (B1, B2, G1, G2, M1) (R²=0.99) in the concentration range 0.005-4.05 ppb. The samples were analyzed in two replicated measurements and for each sample, the standard deviation (statistical parameter) is calculated. The results showed that the flour samples are safe, but the necessity of performing such tests is necessary.

Keywords: aflatoxins, ELISA technique, food contamination, flour

Procedia PDF Downloads 155
2299 Offline Signature Verification Using Minutiae and Curvature Orientation

Authors: Khaled Nagaty, Heba Nagaty, Gerard McKee

Abstract:

A signature is a behavioral biometric that is used for authenticating users in most financial and legal transactions. Signatures can be easily forged by skilled forgers. Therefore, it is essential to verify whether a signature is genuine or forged. The aim of any signature verification algorithm is to accommodate the differences between signatures of the same person and increase the ability to discriminate between signatures of different persons. This work presented in this paper proposes an automatic signature verification system to indicate whether a signature is genuine or not. The system comprises four phases: (1) The pre-processing phase in which image scaling, binarization, image rotation, dilation, thinning, and connecting ridge breaks are applied. (2) The feature extraction phase in which global and local features are extracted. The local features are minutiae points, curvature orientation, and curve plateau. The global features are signature area, signature aspect ratio, and Hu moments. (3) The post-processing phase, in which false minutiae are removed. (4) The classification phase in which features are enhanced before feeding it into the classifier. k-nearest neighbors and support vector machines are used. The classifier was trained on a benchmark dataset to compare the performance of the proposed offline signature verification system against the state-of-the-art. The accuracy of the proposed system is 92.3%.

Keywords: signature, ridge breaks, minutiae, orientation

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2298 Protection System Mis-operations: Fundamental Concepts and Learning from Indian Power Sector

Authors: Pankaj Kumar Jha, Mahendra Singh Hada, Brijendra Singh

Abstract:

Protection system is an essential feature of the electrical system which helps in detection and removal of faults. Protection system consists of many subsystems like relays, circuit breakers, instrument transformers, auxiliary DC system, auxiliary relays etc. Although the fundamental protective and relay operating concepts are similar throughout the world, there are very significant differences in their implementation. These differences arise through different traditions, operating philosophies, experiences and national standards. Protection system mis-operation due to problem in one or more of its subsystem or inadequate knowledge of numerical relay settings and configuration are very common throughout the world. Protection system mis-operation leads to unstable and unreliable grid operation. In this paper we will discuss about the fundamental concepts of protective relaying and the reasons for protection system mis-operation due to one or more of its subsystems. Many real-world case studies of protection system mis-operation from Indian power sector are discussed in detail in this paper.

Keywords: auxiliary trip relays, bus zone, check zone, CT saturation, dead zone protection, DC ground faults, DMT, DR, end fault protection, instrument transformer, SOTF, STUB

Procedia PDF Downloads 74
2297 Study on Security and Privacy Issues of Mobile Operating Systems Based on Malware Attacks

Authors: Huang Dennis, Aurelio Aziel, Burra Venkata Durga Kumar

Abstract:

Nowadays, smartphones and mobile operating systems have been popularly widespread in our daily lives. As people use smartphones, they tend to store more private and essential data on their devices, because of this it is very important to develop more secure mobile operating systems and cloud storage to secure the data. However, several factors can cause security risks in mobile operating systems such as malware, malicious app, phishing attacks, ransomware, and more, all of which can cause a big problem for users as they can access the user's private data. Those problems can cause data loss, financial loss, identity theft, and other serious consequences. Other than that, during the pandemic, people will use their mobile devices more and do all sorts of transactions online, which may lead to more victims of online scams and inexperienced users being the target. With the increase in attacks, researchers have been actively working to develop several countermeasures to enhance the security of operating systems. This study aims to provide an overview of the security and privacy issues in mobile operating systems, identifying the potential risk of operating systems, and the possible solutions. By examining these issues, we want to provide an easy understanding to users and researchers to improve knowledge and develop more secure mobile operating systems.

Keywords: mobile operating system, security, privacy, Malware

Procedia PDF Downloads 87
2296 Development of a Delivery System for Statin Targeted Spray is a Breakthrough Therapy in Alzheimer’s Prevention

Authors: Fakhr Eddin Alnaal, Angela Dahdal, Duaa Aladib, Sabeen Ibrahim, Ibrahim Ghoraibi, Bissan Ahmed

Abstract:

Dementia is one of the diseases which had several stages and Alzheimer’s term was selected in respect for the first doctor Alzheimer who defined the first symptoms of this diseases in a woman whom was well treated by him. The fact that this is a type of a silent disease on which you have a long-term process of neurological degradation and suddenly gives symptoms which are most often irreversible, on clinical level likely we can consider it as a malignancy, one in terms of that it is sudden shocking irreversible and on the level of behavior and some mortality beside the lack of early detection tools for diagnosis. Therefore, the goal of our project is to test the concept of the ability of Statin in prevention of such disease and we investigated that both on experimental level and most importantly on clinical one, the clinical part was performed in a recognized house of aged people who had accidently a high cholesterol and were for years given Statin to treat that elevation, however after the symptoms of Alzheimer’s appeared and when diagnosed, they were well treated and rapidly recovered compared to Alzheimer’s patients in the same house who did not receive Statin had a mild improvement in their symptoms after the therapy, on the other hand we confirmed such observation by a well-organized experimental work.

Keywords: Alzheimer's, dementia, silent disease, statin

Procedia PDF Downloads 131
2295 Off-Line Detection of "Pannon Wheat" Milling Fractions by Near-Infrared Spectroscopic Methods

Authors: E. Izsó, M. Bartalné-Berceli, Sz. Gergely, A. Salgó

Abstract:

The aims of this investigation is to elaborate near-infrared methods for testing and recognition of chemical components and quality in “Pannon wheat” allied (i.e. true to variety or variety identified) milling fractions as well as to develop spectroscopic methods following the milling processes and evaluate the stability of the milling technology by different types of milling products and according to sampling times, respectively. This wheat categories produced under industrial conditions where samples were collected versus sampling time and maximum or minimum yields. The changes of the main chemical components (such as starch, protein, lipid) and physical properties of fractions (particle size) were analysed by dispersive spectrophotometers using visible (VIS) and near-infrared (NIR) regions of the electromagnetic radiation. Close correlation were obtained between the data of spectroscopic measurement techniques processed by various chemometric methods (e.g. principal component analysis (PCA), cluster analysis (CA) and operation condition of milling technology. Its obvious that NIR methods are able to detect the deviation of the yield parameters and differences of the sampling times by a wide variety of fractions, respectively. NIR technology can be used in the sensitive monitoring of milling technology.

Keywords: near infrared spectroscopy, wheat categories, milling process, monitoring

Procedia PDF Downloads 405
2294 The Impact of Alumina Cement on Properties of Portland Cement Slurries and Mortars

Authors: Krzysztof Zieliński, Dariusz Kierzek

Abstract:

The addition of a small amount of alumina cement to Portland cement results in immediate setting, a rapid increase in the compressive strength and a clear increase of the adhesion to concrete substrate. This phenomenon is used, among others, for the production of liquid floor self-levelling compounds. Alumina cement is several times more expensive than Portland cement and is a component having a significant impact on prices of products manufactured with its use. For the production of liquid floor self-levelling compounds, low-alumina cement containing approximately 40% Al2O3 is normally used. The aim of the study was to determine the impact of Portland cement with the addition of alumina cement on the basic physical and mechanical properties of cement slurries and mortars. CEM I 42.5R and three types of alumina cement containing 40%, 50% and 70% of Al2O3 were used for the tests. Mixes containing 4%, 6%, 8%, 10% and 12% of different varieties of alumina cement were prepared; for which, the time of initial and final setting, compressive and flexural strength and adhesion to concrete substrate were determined. The analysis of the obtained test results showed that a similar immediate setting effect and clearly better adhesion strength can be obtained using the addition of 6% of high-alumina cement than 12% of low-alumina cement. As the prices of these cements are similar, this can give significant financial savings in the production of liquid floor self-levelling compounds.

Keywords: alumina cement, immediate setting, compression strength, adhesion to substrate

Procedia PDF Downloads 150
2293 Synthesis of Flower-Like Silver Nanoarchitectures in Special Shapes and Their Applications in Surface-Enhanced Raman Scattering

Authors: Radka Králová, Libor Kvítek, Václav Ranc, Aleš Panáček, Radek Zbořil

Abstract:

Surface–Enhanced Raman Scattering (SERS) is an optical spectroscopic technique with very good potential for sensitive detection of substances. In this research, active substrates with high enhancement were provided. Novel silver particles (nanostructures) with high roughened, flower–like morphology were prepared by reduction of cation complex [Ag(NH3)2]+ in presence of sodium borohydride as reducing agent and stabilized polyacrylic acid. The products were characterized by UV/VIS absorption spectrophotometry. Special shapes of silver particles were determined by scanning electron microscopy (SEM) and transmission electron spectroscopy (TEM). Dispersions of this particle were put on fixed substrate to producing suitable layer for SERS. Adenine was applied as basic substance whose effect of enhancement on the layer of silver nanostructures was studied. By comparison with our work, the important influence of stabilizers, polyacrylic acid with various molecular weight and concentration, on the transfer of particles and formation of new structure was confirmed.

Keywords: metals, nanostructures, chemical reduction, Raman spectroscopy, optical properties

Procedia PDF Downloads 367
2292 Modeling Usage Patterns of Mobile App Service in App Market Using Hidden Markov Model

Authors: Yangrae Cho, Jinseok Kim, Yongtae Park

Abstract:

Mobile app service ecosystem has been abruptly emerged, explosively grown, and dynamically transformed. In contrast with product markets in which product sales directly cause increment in firm’s income, customer’s usage is less visible but more valuable in service market. Especially, the market situation with cutthroat competition in mobile app store makes securing and keeping of users as vital. Although a few service firms try to manage their apps’ usage patterns by fitting on S-curve or applying other forecasting techniques, the time series approaches based on past sequential data are subject to fundamental limitation in the market where customer’s attention is being moved unpredictably and dynamically. We therefore propose a new conceptual approach for detecting usage pattern of mobile app service with Hidden Markov Model (HMM) which is based on the dual stochastic structure and mainly used to clarify unpredictable and dynamic sequential patterns in voice recognition or stock forecasting. Our approach could be practically utilized for app service firms to manage their services’ lifecycles and academically expanded to other markets.

Keywords: mobile app service, usage pattern, Hidden Markov Model, pattern detection

Procedia PDF Downloads 335