Search results for: leak detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3534

Search results for: leak detection

1644 Diagnosis of Diabetes Using Computer Methods: Soft Computing Methods for Diabetes Detection Using Iris

Authors: Piyush Samant, Ravinder Agarwal

Abstract:

Complementary and Alternative Medicine (CAM) techniques are quite popular and effective for chronic diseases. Iridology is more than 150 years old CAM technique which analyzes the patterns, tissue weakness, color, shape, structure, etc. for disease diagnosis. The objective of this paper is to validate the use of iridology for the diagnosis of the diabetes. The suggested model was applied in a systemic disease with ocular effects. 200 subject data of 100 each diabetic and non-diabetic were evaluated. Complete procedure was kept very simple and free from the involvement of any iridologist. From the normalized iris, the region of interest was cropped. All 63 features were extracted using statistical, texture analysis, and two-dimensional discrete wavelet transformation. A comparison of accuracies of six different classifiers has been presented. The result shows 89.66% accuracy by the random forest classifier.

Keywords: complementary and alternative medicine, classification, iridology, iris, feature extraction, disease prediction

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1643 Tetracycline as Chemosensor for Simultaneous Recognition of Al³⁺: Application to Bio-Imaging for Living Cells

Authors: Jesus Alfredo Ortega Granados, Pandiyan Thangarasu

Abstract:

Antibiotic tetracycline presents as a micro-contaminant in fresh water, wastewater and soils, causing environmental and health problems. In this work, tetracycline (TC) has been employed as chemo-sensor for the recognition of Al³⁺ without interring other ions, and the results show that it enhances the fluorescence intensity for Al³⁺ and there is no interference from other coexisting cation ions (Cd²⁺, Ni²⁺, Co²⁺, Sr²⁺, Mg²⁺, Fe³⁺, K⁺, Sm³⁺, Ag⁺, Na⁺, Ba²⁺, Zn²⁺, and Mn²⁺). For the addition of Cu²⁺ to [TET-Al³⁺], it appears that the intensity of fluorescence has been quenched. Other combinations of metal ions in addition to TC do not change the fluorescence behavior. The stoichiometry determined by Job´s plot for the interaction of TC with Al³⁺ was found to be 1:1. Importantly, the detection of Al³⁺⁺ successfully employed in the real samples like living cells, and it was found that TC efficiently performs as a fluorescent probe for Al³⁺ ion in living systems, especially in Saccharomyces cerevisiae; this is confirmed by confocal laser scanning microscopy.

Keywords: chemo-sensor, recognition of Al³⁺ ion, Saccharomyces cerevisiae, tetracycline,

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1642 Simulation and Experimentation Investigation of Infrared Non-Destructive Testing on Thermal Insulation Material

Authors: Bi Yan-Qiang, Shang Yonghong, Lin Boying, Ji Xinyan, Li Xiyuan

Abstract:

The heat-resistant material has important application in the aerospace field. The reliability of the connection between the heat-resisting material and the body determines the success or failure of the project. In this paper, lock-in infrared thermography non-destructive testing technology is used to detect the stability of the thermal-resistant structure. The phase relationship between the temperature and the heat flow is calculated by the numerical method, and the influence of the heating frequency and power is obtained. The correctness of the analysis is verified by the experimental method. Through the research, it can provide the basis for the parameter setting of heat flux including frequency and power, improve the efficiency of detection and the reliability of connection between the heat-resisting material and the body.

Keywords: infrared non-destructive, thermal insulation material, reliability, connection

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1641 Identity Verification Using k-NN Classifiers and Autistic Genetic Data

Authors: Fuad M. Alkoot

Abstract:

DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

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1640 On the Interactive Search with Web Documents

Authors: Mario Kubek, Herwig Unger

Abstract:

Due to the large amount of information in the World Wide Web (WWW, web) and the lengthy and usually linearly ordered result lists of web search engines that do not indicate semantic relationships between their entries, the search for topically similar and related documents can become a tedious task. Especially, the process of formulating queries with proper terms representing specific information needs requires much effort from the user. This problem gets even bigger when the user's knowledge on a subject and its technical terms is not sufficient enough to do so. This article presents the new and interactive search application DocAnalyser that addresses this problem by enabling users to find similar and related web documents based on automatic query formulation and state-of-the-art search word extraction. Additionally, this tool can be used to track topics across semantically connected web documents

Keywords: DocAnalyser, interactive web search, search word extraction, query formulation, source topic detection, topic tracking

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1639 AI-Based Information System for Hygiene and Safety Management of Shared Kitchens

Authors: Jongtae Rhee, Sangkwon Han, Seungbin Ji, Junhyeong Park, Byeonghun Kim, Taekyung Kim, Byeonghyeon Jeon, Jiwoo Yang

Abstract:

The shared kitchen is a concept that transfers the value of the sharing economy to the kitchen. It is a type of kitchen equipped with cooking facilities that allows multiple companies or chefs to share time and space and use it jointly. These shared kitchens provide economic benefits and convenience, such as reduced investment costs and rent, but also increase the risk of safety management, such as cross-contamination of food ingredients. Therefore, to manage the safety of food ingredients and finished products in a shared kitchen where several entities jointly use the kitchen and handle various types of food ingredients, it is critical to manage followings: the freshness of food ingredients, user hygiene and safety and cross-contamination of cooking equipment and facilities. In this study, it propose a machine learning-based system for hygiene safety and cross-contamination management, which are highly difficult to manage. User clothing management and user access management, which are most relevant to the hygiene and safety of shared kitchens, are solved through machine learning-based methodology, and cutting board usage management, which is most relevant to cross-contamination management, is implemented as an integrated safety management system based on artificial intelligence. First, to prevent cross-contamination of food ingredients, we use images collected through a real-time camera to determine whether the food ingredients match a given cutting board based on a real-time object detection model, YOLO v7. To manage the hygiene of user clothing, we use a camera-based facial recognition model to recognize the user, and real-time object detection model to determine whether a sanitary hat and mask are worn. In addition, to manage access for users qualified to enter the shared kitchen, we utilize machine learning based signature recognition module. By comparing the pairwise distance between the contract signature and the signature at the time of entrance to the shared kitchen, access permission is determined through a pre-trained signature verification model. These machine learning-based safety management tasks are integrated into a single information system, and each result is managed in an integrated database. Through this, users are warned of safety dangers through the tablet PC installed in the shared kitchen, and managers can track the cause of the sanitary and safety accidents. As a result of system integration analysis, real-time safety management services can be continuously provided by artificial intelligence, and machine learning-based methodologies are used for integrated safety management of shared kitchens that allows dynamic contracts among various users. By solving this problem, we were able to secure the feasibility and safety of the shared kitchen business.

Keywords: artificial intelligence, food safety, information system, safety management, shared kitchen

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1638 Durable Phantom Production Identical to Breast Tissue for Use in Breast Cancer Detection Research Studies

Authors: Hayrettin Eroglu, Adem Kara

Abstract:

Recently there has been significant attention given to imaging of the biological tissues via microwave imaging techniques. In this study, a phantom for the test and calibration of Microwave imaging used in detecting unhealthy breast structure or tumors was produced by using sol gel method. The liquid and gel phantoms being used nowadays are not durable due to evaporation and their organic ingredients, hence a new design was proposed. This phantom was fabricated from materials that were widely available (water, salt, gelatin, and glycerol) and was easy to make. This phantom was aimed to be better from the ones already proposed in the literature in terms of its durability and stability. S Parameters of phantom was measured with 1-18 GHz Probe Kit and permittivity was calculated via Debye method in “85070” commercial software. One, three, and five-week measurements were taken for this phantom. Finally, it was verified that measurement results were very close to the real biological tissue measurement results.

Keywords: phantom, breast tissue, cancer, microwave imaging

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1637 Green Synthesis of Red-Fluorescent Gold Nanoclusters: Characterization and Application for Breast Cancer Detection

Authors: Agnė Mikalauskaitė, Renata Karpicz, Vitalijus Karabanovas, Arūnas Jagminas

Abstract:

The use of biocompatible precursors for the synthesis and stabilization of fluorescent gold nanoclusters (NCs) with strong red photoluminescence creates an important link between natural sciences and nanotechnology. Herein, we report the cost-effective synthesis of Au nanoclusters by templating and reduction of chloroauric acid with the cheap amino acid food supplements. This synthesis under the optimized conditions leads to the formation of biocompatible Au NCs having good stability and intense red photoluminescence, peaked at 680 to 705 nm, with a quantum yield (QY) of ≈7% and the average lifetime of up to several µs. The composition and luminescent properties of the obtained NCs were compared with ones formed via well-known bovine serum albumin reduction approach. Our findings implied that synthesized Au NCs tend to accumulate in more tumorigenic breast cancer cells (line MDA-MB-213) and after dialysis can be prospective for bio imagining.

Keywords: gold nanoclusters, proteins, materials chemistry, red-photoluminescence, bioimaging

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1636 Inspection of Railway Track Fastening Elements Using Artificial Vision

Authors: Abdelkrim Belhaoua, Jean-Pierre Radoux

Abstract:

In France, the railway network is one of the main transport infrastructures and is the second largest European network. Therefore, railway inspection is an important task in railway maintenance to ensure safety for passengers using significant means in personal and technical facilities. Artificial vision has recently been applied to several railway applications due to its potential to improve the efficiency and accuracy when analyzing large databases of acquired images. In this paper, we present a vision system able to detect fastening elements based on artificial vision approach. This system acquires railway images using a CCD camera installed under a control carriage. These images are stitched together before having processed. Experimental results are presented to show that the proposed method is robust for detection fasteners in a complex environment.

Keywords: computer vision, image processing, railway inspection, image stitching, fastener recognition, neural network

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1635 Monitoring of Potato Rot Nematode (Ditylenchus destructor Thorne, 1945) in Southern Georgia Nematode Fauna Diversity of Rhizosphere

Authors: E. Tskitishvili, L. Jgenti, I. Eliava, T. Tskitishvili, N. Bagathuria, M. Gigolashvili

Abstract:

The nematode fauna of 20 agrocenosis (soil, tuber of potato, green parts of plant, roots) was studied in four regions in South Georgia (Akhaltsikhe, Aspindza, Akhalkalaki, Ninotsminda). In all, there were registered 173 forms of free-living and Phyto-parasitic nematodes, including 132 forms which were specified according to their species. A few exemplars of potato root nematode (Ditylenchus destructor) were identified in soil samples taken in Ninotsminda, Akhalkalaki and Aspinda stations, i.e. invasion is weak. Based on our data, potato Ditylenchus was not found in any of the researched tubers, while based on the data of previous years the most of tubers were infested. The cysts of 'golden nematodes' were not found during inspection of material for detection of Globoderosis

Keywords: ditylenchus, monitoring, nematoda, potato

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1634 An Exploitation of Electrical Sensors in Monitoring Pool Chlorination

Authors: Fahad Alamoudi, Yaser Miaji

Abstract:

The growing popularity of swimming pools and other activities in the water for sport, fitness, therapy or just enjoyable relaxation have led to the increased use of swimming pools and the establishment of a variety of specific-use pools such as spa pools, water slides, and more recently, hydrotherapy and wave pools. In this research, a few simple equipment is used for test, detect and alert for detection of water cleanness and pollution. YSI Photometer Systems, TDSTestr High model, Rio 12HF and Electrode A1. The researchers used electrolysis as a method of separating bonded elements and compounds by passing an electric current through them. The results which use 41 experiments show the higher the salt concentration, the more efficient the electrode and the smaller the gap between the plates, the lower the electrode voltage. Furthermore, it is proved that the larger the surface area, the lower the cell voltage and the higher current used the more chlorine produced.

Keywords: photometer, electrode, electrolysis, swimming pool chlorination

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1633 Reinforcement Learning the Born Rule from Photon Detection

Authors: Rodrigo S. Piera, Jailson Sales Ara´ujo, Gabriela B. Lemos, Matthew B. Weiss, John B. DeBrota, Gabriel H. Aguilar, Jacques L. Pienaar

Abstract:

The Born rule was historically viewed as an independent axiom of quantum mechanics until Gleason derived it in 1957 by assuming the Hilbert space structure of quantum measurements [1]. In subsequent decades there have been diverse proposals to derive the Born rule starting from even more basic assumptions [2]. In this work, we demonstrate that a simple reinforcement-learning algorithm, having no pre-programmed assumptions about quantum theory, will nevertheless converge to a behaviour pattern that accords with the Born rule, when tasked with predicting the output of a quantum optical implementation of a symmetric informationally-complete measurement (SIC). Our findings support a hypothesis due to QBism (the subjective Bayesian approach to quantum theory), which states that the Born rule can be thought of as a normative rule for making decisions in a quantum world [3].

Keywords: quantum Bayesianism, quantum theory, quantum information, quantum measurement

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1632 Early Warning Signals: Role and Status of Risk Management in Small and Medium Enterprises

Authors: Alexander Kelíšek, Denisa Janasová, Veronika Mitašová

Abstract:

Weak signals using is often associated with early warning. It is possible to find a link between early warning, respectively early problems detection and risk management. The idea of early warning is very important in the context of crisis management because of the risk prevention possibility. Weak signals are likened to risk symptoms. Nowadays, their usefulness as a tool of proactive problems solving is emphasized. Based on it, it is possible to use weak signals not only in strategic planning, project management, or early warning system, but also as a subsidiary element in risk management. The main question is how to effectively integrate weak signals into risk management. The main aim of the paper is to point out the possibilities of weak signals using in small and medium enterprises risk management.

Keywords: early warning system, weak signals, risk management, small and medium enterprises (SMEs)

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1631 A Polyphonic Look at Trends

Authors: Turquesa Topper

Abstract:

The reflection focuses on recording and explaining the considerations, conceptualizations and methodological approach with which from the University, that is to say, from the academic field, the study of Trends is addressed with the intention of training professionals in the area, an area that requires disciplinary boundaries and builds a polyphonic vision. When referring to the objective of our Laboratory the detection of aesthetic trends of consumption, we find ourselves in the requirement to define our object: trends, aesthetic trends of consumption, more specifically. The pages cover a conception of trends from a theoretical framework that incorporates contributions from linguistics, semiotics, sociology, cultural studies and project disciplines, in order to consolidate a polyphonic look. The text investigates in the pre-discursive aspect of the trends, in the circulation of the notion of style and in the dynamics of affirmation - denial as the constitutive dynamics of Fashion linked to any process of innovation. From such inquiry, it is presented to Fashion as a system that operates directly on the construction of socio-individual identities unfolding through the liquefaction of signs in trends.

Keywords: fashion, methodology, narrative, trends

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1630 A Synthetic Strategy to Attach 2,6-Dichlorophenolindophenol onto Multi Walled Carbon Nanotubes and Their Application for Electrocatalytic Determination of Sulfide

Authors: Alireza Mohadesi, Ashraf Salmanipour

Abstract:

A chemically modified glassy carbon electrode for electrocatalytic determination of sulfide was developed using multiwalled carbon nanotubes (MWCNTs) covalently immobilized with 2,6-dichlorophenolindophenol (DPIP). The immobilization of 2,6-dichlorophenolindophenol with MWCNTs was performed with a new synthetic strategy and characterized by UV–visible absorption spectroscopy, Fourier transform infrared spectroscopy and cyclic voltammetry. The cyclic voltammetric response of DPIP grafted onto MWCNTs indicated that it promotes the low potential, sensitive and stable determination of sulfide. The dependence of response currents on the concentration of sulfide was examined and was linear in the range of 10 - 1100 µM. The detection limit of sulfide was 5 µM and RSD for 100 and 500 µM sulfides were 1.8 and 1.3 %. Many interfering species had little or no effect on the determination of sulfide. The procedure was applied to determination of sulfide in waters samples.

Keywords: functionalized carbon nanotubes, sulfide, biological samples, 2, 6-dichlorophenolindophenol

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1629 Development on the Modeling Driven Architecture

Authors: Sahar Shahsavaripour Ghazanfarpour

Abstract:

As our daily life depends on quality of built services by systems and using devices in our environment; so education and model of software′s quality will be so important. By daily growth in software′s systems and using them so much, progressing process and requirements′ evaluation in primary level of progress especially architecture level in software get more important. Modern driver architecture changes an in dependent model of a level into some specific models that their purpose is reducing number of software changes into an executive model. Process of designing software engineering is mid-automated. The needed quality attribute in designing architecture and quality attribute in representation are in architecture models. The main problem is the relationship between needs, and elements in some aspect with implicit models and input sources in process. It’s because there is no detection ability. The MART profile is use to describe real-time properties and perform plat form modeling.

Keywords: MDA, DW, OMG, UML, AKB, software architecture, ontology, evaluation

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1628 Variation of Inductance in a Switched-Reluctance Motor under Various Rotor Faults

Authors: Muhammad Asghar Saqib, Saad Saleem Khan, Syed Abdul Rahman Kashif

Abstract:

In order to have higher efficiency, performance and reliability the regular monitoring of an electrical motor is required. This article presents a novel view of the air-gap magnetic field analysis of a switched reluctance motor under rotor cracks and rotor tilt along its shaft axis. The fault diagnosis is illustrated on the basis of a 3-D model of the motor using finite element analysis (FEA). The analytical equations of flux linkages have been used to determine the inductance. The results of the 3-D finite element analysis on a 6/4 switched reluctance motor (SRM) shows the variation of mutual inductance with the tilting of the rotor shaft and cracked rotor conditions. These results present useful information regarding the detection of shaft tilting and cracked rotors.

Keywords: switched reluctance motor, finite element analysis, cracked rotor, 3-D modelling of a srm

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1627 Thickness Measurement and Void Detection in Concrete Elements through Ultrasonic Pulse

Authors: Leonel Lipa Cusi, Enrique Nestor Pasquel Carbajal, Laura Marina Navarro Alvarado, José Del Álamo Carazas

Abstract:

This research analyses the accuracy of the ultrasound and the pulse echo ultrasound technic to find voids and to measure thickness of concrete elements. These mentioned air voids are simulated by polystyrene expanded and hollow containers of thin thickness made of plastic or cardboard of different sizes and shapes. These targets are distributed strategically inside concrete at different depths. For this research, a shear wave pulse echo ultrasonic device of 50 KHz is used to scan the concrete elements. Despite the small measurements of the concrete elements and because of voids’ size are near the half of the wavelength, pre and post processing steps like voltage, gain, SAFT, envelope and time compensation were made in order to improve imaging results.

Keywords: ultrasonic, concrete, thickness, pulse echo, void

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1626 Ultrasonography of Low Extremities Veins Before and After Replacement of Knee Joint by Endoprosthesis

Authors: A. V. Alabut, V. D. Sikilinda, N. J. Nelasov, O. L. Eroshenko, M. N. Morgunov, I. V. Koroleva

Abstract:

We have analyzed the results of treatment of 204 patients with knee prosthetic arthroplasty. For the purpose of active delineation of vascular pathology triplex sonography of arterial and venous vessels of low extremities was performed in all cases in the preoperative period. When it was necessary, reconstructive vascular surgery was implemented to improve peripheral circulation and reduce the hazard of thrombosis after knee replacement. The combination of specific and nonspecific methods of thromboprophylaxis was used in perioperative period. On 7-10 day and 2.5-3 month after prosthetic arthroplasty, all patients iteratively underwent triple sonography. In case of detection of floating thrombus, urgent venous ligation was performed. Active diagnostics of venous thrombosis gave the opportunity to avoid fatal pulmonary embolism.

Keywords: knee replacement, venous thrombosis, pulmonary embolism, vascular surgery

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1625 Full Characterization of Heterogeneous Antibody Samples under Denaturing and Native Conditions on a Hybrid Quadrupole-Orbitrap Mass Spectrometer

Authors: Rowan Moore, Kai Scheffler, Eugen Damoc, Jennifer Sutton, Aaron Bailey, Stephane Houel, Simon Cubbon, Jonathan Josephs

Abstract:

Purpose: MS analysis of monoclonal antibodies (mAbs) at the protein and peptide levels is critical during development and production of biopharmaceuticals. The compositions of current generation therapeutic proteins are often complex due to various modifications which may affect efficacy. Intact proteins analyzed by MS are detected in higher charge states that also provide more complexity in mass spectra. Protein analysis in native or native-like conditions with zero or minimal organic solvent and neutral or weakly acidic pH decreases charge state value resulting in mAb detection at higher m/z ranges with more spatial resolution. Methods: Three commercially available mAbs were used for all experiments. Intact proteins were desalted online using size exclusion chromatography (SEC) or reversed phase chromatography coupled on-line with a mass spectrometer. For streamlined use of the LC- MS platform we used a single SEC column and alternately selected specific mobile phases to perform separations in either denaturing or native-like conditions: buffer A (20 % ACN, 0.1 % FA) with Buffer B (100 mM ammonium acetate). For peptide analysis mAbs were proteolytically digested with and without prior reduction and alkylation. The mass spectrometer used for all experiments was a commercially available Thermo Scientific™ hybrid Quadrupole-Orbitrap™ mass spectrometer, equipped with the new BioPharma option which includes a new High Mass Range (HMR) mode that allows for improved high mass transmission and mass detection up to 8000 m/z. Results: We have analyzed the profiles of three mAbs under reducing and native conditions by direct infusion with offline desalting and with on-line desalting via size exclusion and reversed phase type columns. The presence of high salt under denaturing conditions was found to influence the observed charge state envelope and impact mass accuracy after spectral deconvolution. The significantly lower charge states observed under native conditions improves the spatial resolution of protein signals and has significant benefits for the analysis of antibody mixtures, e.g. lysine variants, degradants or sequence variants. This type of analysis requires the detection of masses beyond the standard mass range ranging up to 6000 m/z requiring the extended capabilities available in the new HMR mode. We have compared each antibody sample that was analyzed individually with mixtures in various relative concentrations. For this type of analysis, we observed that apparent native structures persist and ESI is benefited by the addition of low amounts of acetonitrile and formic acid in combination with the ammonium acetate-buffered mobile phase. For analyses on the peptide level we analyzed reduced/alkylated, and non-reduced proteolytic digests of the individual antibodies separated via reversed phase chromatography aiming to retrieve as much information as possible regarding sequence coverage, disulfide bridges, post-translational modifications such as various glycans, sequence variants, and their relative quantification. All data acquired were submitted to a single software package for analysis aiming to obtain a complete picture of the molecules analyzed. Here we demonstrate the capabilities of the mass spectrometer to fully characterize homogeneous and heterogeneous therapeutic proteins on one single platform. Conclusion: Full characterization of heterogeneous intact protein mixtures by improved mass separation on a quadrupole-Orbitrap™ mass spectrometer with extended capabilities has been demonstrated.

Keywords: disulfide bond analysis, intact analysis, native analysis, mass spectrometry, monoclonal antibodies, peptide mapping, post-translational modifications, sequence variants, size exclusion chromatography, therapeutic protein analysis, UHPLC

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1624 An Optimal Steganalysis Based Approach for Embedding Information in Image Cover Media with Security

Authors: Ahlem Fatnassi, Hamza Gharsellaoui, Sadok Bouamama

Abstract:

This paper deals with the study of interest in the fields of Steganography and Steganalysis. Steganography involves hiding information in a cover media to obtain the stego media in such a way that the cover media is perceived not to have any embedded message for its unintended recipients. Steganalysis is the mechanism of detecting the presence of hidden information in the stego media and it can lead to the prevention of disastrous security incidents. In this paper, we provide a critical review of the steganalysis algorithms available to analyze the characteristics of an image stego media against the corresponding cover media and understand the process of embedding the information and its detection. We anticipate that this paper can also give a clear picture of the current trends in steganography so that we can develop and improvise appropriate steganalysis algorithms.

Keywords: optimization, heuristics and metaheuristics algorithms, embedded systems, low-power consumption, steganalysis heuristic approach

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1623 A Green Method for Selective Spectrophotometric Determination of Hafnium(IV) with Aqueous Extract of Ficus carica Tree Leaves

Authors: A. Boveiri Monji, H. Yousefnia, M. Haji Hosseini, S. Zolghadri

Abstract:

A clean spectrophotometric method for the determination of hafnium by using a green reagent, acidic extract of Ficus carica tree leaves is developed. In 6-M hydrochloric acid, hafnium reacts with this reagent to form a yellow product. The formed product shows maximum absorbance at 421 nm with a molar absorptivity value of 0.28 × 104 l mol⁻¹ cm⁻¹, and the method was linear in the 2-11 µg ml⁻¹ concentration range. The detection limit value was found to be 0.312 µg ml⁻¹. Except zirconium and iron, the selectivity was good, and most of the ions did not show any significant spectral interference at concentrations up to several hundred times. The proposed method was green, simple, low cost, and selective.

Keywords: spectrophotometric determination, Ficus caricatree leaves, synthetic reagents, hafnium

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1622 Photoemission Momentum Microscopy of Graphene on Ir (111)

Authors: Anna V. Zaporozhchenko, Dmytro Kutnyakhov, Katherina Medjanik, Christian Tusche, Hans-Joachim Elmers, Olena Fedchenko, Sergey Chernov, Martin Ellguth, Sergej A. Nepijko, Gerd Schoenhense

Abstract:

Graphene reveals a unique electronic structure that predetermines many intriguing properties such as massless charge carriers, optical transparency and high velocity of fermions at the Fermi level, opening a wide horizon of future applications. Hence, a detailed investigation of the electronic structure of graphene is crucial. The method of choice is angular resolved photoelectron spectroscopy ARPES. Here we present experiments using time-of-flight (ToF) momentum microscopy, being an alternative way of ARPES using full-field imaging of the whole Brillouin zone (BZ) and simultaneous acquisition of up to several 100 energy slices. Unlike conventional ARPES, k-microscopy is not limited in simultaneous k-space access. We have recorded the whole first BZ of graphene on Ir(111) including all six Dirac cones. As excitation source we used synchrotron radiation from BESSY II (Berlin) at the U125-2 NIM, providing linearly polarized (both polarizations p- and s-) VUV radiation. The instrument uses a delay-line detector for single-particle detection up the 5 Mcps range and parallel energy detection via ToF recording. In this way, we gather a 3D data stack I(E,kx,ky) of the full valence electronic structure in approx. 20 mins. Band dispersion stacks were measured in the energy range of 14 eV up to 23 eV with steps of 1 eV. The linearly-dispersing graphene bands for all six K and K’ points were simultaneously recorded. We find clear features of hybridization with the substrate, in particular in the linear dichroism in the angular distribution (LDAD). Recording of the whole Brillouin zone of graphene/Ir(111) revealed new features. First, the intensity differences (i.e. the LDAD) are very sensitive to the interaction of graphene bands with substrate bands. Second, the dark corridors are investigated in detail for both, p- and s- polarized radiation. They appear as local distortions of photoelectron current distribution and are induced by quantum mechanical interference of graphene sublattices. The dark corridors are located in different areas of the 6 Dirac cones and show chirality behaviour with a mirror plane along vertical axis. Moreover, two out of six show an oval shape while the rest are more circular. It clearly indicates orientation dependence with respect to E vector of incident light. Third, a pattern of faint but very sharp lines is visible at energies around 22eV that strongly remind on Kikuchi lines in diffraction. In conclusion, the simultaneous study of all six Dirac cones is crucial for a complete understanding of dichroism phenomena and the dark corridor.

Keywords: band structure, graphene, momentum microscopy, LDAD

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1621 Development of a New Polymeric Material with Controlled Surface Micro-Morphology Aimed for Biosensors Applications

Authors: Elham Farahmand, Fatimah Ibrahim, Samira Hosseini, Ivan Djordjevic, Leo. H. Koole

Abstract:

Compositions of different molar ratios of polymethylmethacrylate-co-methacrylic acid (PMMA-co-MAA) were synthesized via free- radical polymerization. Polymer coated surfaces have been produced on silicon wafers. Coated samples were analyzed by atomic force microscopy (AFM). The results have shown that the roughness of the surfaces have increased by increasing the molar ratio of monomer methacrylic acid (MAA). This study reveals that the gradual increase in surface roughness is due to the fact that carboxylic functional groups have been generated by MAA segments. Such surfaces can be desirable platforms for fabrication of the biosensors for detection of the viruses and diseases.

Keywords: polymethylmethacrylate-co-methacrylic acid (PMMA-co-MAA), polymeric material, atomic force microscopy, roughness, carboxylic functional groups

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1620 Robust Diagnosability of PEMFC Based on Bond Graph LFT

Authors: Ould Bouamama, M. Bressel, D. Hissel, M. Hilairet

Abstract:

Fuel cell (FC) is one of the best alternatives of fossil energy. Recently, the research community of fuel cell has shown a considerable interest for diagnosis in view to ensure safety, security, and availability when faults occur in the process. The problematic for model based FC diagnosis consists in that the model is complex because of coupling of several kind of energies and the numerical values of parameters are not always known or are uncertain. The present paper deals with use of one tool: the Linear Fractional Transformation bond graph tool not only for uncertain modelling but also for monitorability (ability to detect and isolate faults) analysis and formal generation of robust fault indicators with respect to parameter uncertainties.The developed theory applied to a nonlinear FC system has proved its efficiency.

Keywords: bond graph, fuel cell, fault detection and isolation (FDI), robust diagnosis, structural analysis

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1619 Impact of pH Control on Peptide Profile and Antigenicity of Whey Hydrolysates

Authors: Natalia Caldeira De Carvalho, Tassia Batista Pessato, Luis Gustavo R. Fernandes, Ricardo L. Zollner, Flavia Maria Netto

Abstract:

Protein hydrolysates are ingredients of enteral diets and hypoallergenic formulas. Enzymatic hydrolysis is the most commonly used method for reducing the antigenicity of milk protein. The antigenicity and physicochemical characteristics of the protein hydrolysates depend on the reaction parameters. Among them, pH has been pointed out as of the major importance. Hydrolysis reaction in laboratory scale is commonly carried out under controlled pH (pH-stat). However, from the industrial point of view, controlling pH during hydrolysis reaction may be infeasible. This study evaluated the impact of pH control on the physicochemical properties and antigenicity of the hydrolysates of whey proteins with Alcalase. Whey protein isolate (WPI) solutions containing 3 and 7 % protein (w/v) were hydrolyzed with Alcalase 50 and 100 U g-1 protein at 60°C for 180 min. The reactions were carried out under controlled and uncontrolled pH conditions. Hydrolyses performed under controlled pH (pH-stat) were initially adjusted and maintained at pH 8.5. Hydrolyses carried out without pH control were initially adjusted to pH 8.5. Degree of hydrolysis (DH) was determined by OPA method, peptides profile was evaluated by HPLC-RP, and molecular mass distribution by SDS-PAGE/Tricine. The residual α-lactalbumin (α-La) and β-lactoglobulin (β-Lg) concentrations were determined using commercial ELISA kits. The specific IgE and IgG binding capacity of hydrolysates was evaluated by ELISA technique, using polyclonal antibodies obtained by immunization of female BALB/c mice with α-La, β-Lg and BSA. In hydrolysis under uncontrolled pH, the pH dropped from 8.5 to 7.0 during the first 15 min, remaining constant throughout the process. No significant difference was observed between the DH of the hydrolysates obtained under controlled and uncontrolled pH conditions. Although all hydrolysates showed hydrophilic character and low molecular mass peptides, hydrolysates obtained with and without pH control exhibited different chromatographic profiles. Hydrolysis under uncontrolled pH released, predominantly, peptides between 3.5 and 6.5 kDa, while hydrolysis under controlled pH released peptides smaller than 3.5 kDa. Hydrolysis with Alcalase under all conditions studied decreased by 99.9% the α-La and β-Lg concentrations in the hydrolysates detected by commercial kits. In general, β-Lg concentrations detected in the hydrolysates obtained under uncontrolled pH were significantly higher (p<0.05) than those detected in hydrolysates produced with pH control. The anti-α-La and anti-β-Lg IgE and IgG responses to all hydrolysates decreased significantly compared to WPI. Levels of specific IgE and IgG to the hydrolysates were below 25 and 12 ng ml-1, respectively. Despite the differences in peptide composition and α-La and β-Lg concentrations, no significant difference was found between IgE and IgG binding capacity of hydrolysates obtained with or without pH control. These results highlight the impact of pH on the hydrolysates characteristics and their concentrations of antigenic protein. Divergence between the antigen detection by commercial ELISA kits and specific IgE and IgG binding response was found in this study. This result shows that lower protein detection does not imply in lower protein antigenicity. Thus, the use of commercial kits for allergen contamination analysis should be cautious.

Keywords: allergy, enzymatic hydrolysis, milk protein, pH conditions, physicochemical characteristics

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1618 An Approach Based on Statistics and Multi-Resolution Representation to Classify Mammograms

Authors: Nebi Gedik

Abstract:

One of the significant and continual public health problems in the world is breast cancer. Early detection is very important to fight the disease, and mammography has been one of the most common and reliable methods to detect the disease in the early stages. However, it is a difficult task, and computer-aided diagnosis (CAD) systems are needed to assist radiologists in providing both accurate and uniform evaluation for mass in mammograms. In this study, a multiresolution statistical method to classify mammograms as normal and abnormal in digitized mammograms is used to construct a CAD system. The mammogram images are represented by wave atom transform, and this representation is made by certain groups of coefficients, independently. The CAD system is designed by calculating some statistical features using each group of coefficients. The classification is performed by using support vector machine (SVM).

Keywords: wave atom transform, statistical features, multi-resolution representation, mammogram

Procedia PDF Downloads 223
1617 Hand Gestures Based Emotion Identification Using Flex Sensors

Authors: S. Ali, R. Yunus, A. Arif, Y. Ayaz, M. Baber Sial, R. Asif, N. Naseer, M. Jawad Khan

Abstract:

In this study, we have proposed a gesture to emotion recognition method using flex sensors mounted on metacarpophalangeal joints. The flex sensors are fixed in a wearable glove. The data from the glove are sent to PC using Wi-Fi. Four gestures: finger pointing, thumbs up, fist open and fist close are performed by five subjects. Each gesture is categorized into sad, happy, and excited class based on the velocity and acceleration of the hand gesture. Seventeen inspectors observed the emotions and hand gestures of the five subjects. The emotional state based on the investigators assessment and acquired movement speed data is compared. Overall, we achieved 77% accurate results. Therefore, the proposed design can be used for emotional state detection applications.

Keywords: emotion identification, emotion models, gesture recognition, user perception

Procedia PDF Downloads 287
1616 Artificial Neural Networks with Decision Trees for Diagnosis Issues

Authors: Y. Kourd, D. Lefebvre, N. Guersi

Abstract:

This paper presents a new idea for fault detection and isolation (FDI) technique which is applied to industrial system. This technique is based on Neural Networks fault-free and Faulty behaviors Models (NNFM's). NNFM's are used for residual generation, while decision tree architecture is used for residual evaluation. The decision tree is realized with data collected from the NNFM’s outputs and is used to isolate detectable faults depending on computed threshold. Each part of the tree corresponds to specific residual. With the decision tree, it becomes possible to take the appropriate decision regarding the actual process behavior by evaluating few numbers of residuals. In comparison to usual systematic evaluation of all residuals, the proposed technique requires less computational effort and can be used for on line diagnosis. An application example is presented to illustrate and confirm the effectiveness and the accuracy of the proposed approach.

Keywords: neural networks, decision trees, diagnosis, behaviors

Procedia PDF Downloads 508
1615 Spatial Audio Player Using Musical Genre Classification

Authors: Jun-Yong Lee, Hyoung-Gook Kim

Abstract:

In this paper, we propose a smart music player that combines the musical genre classification and the spatial audio processing. The musical genre is classified based on content analysis of the musical segment detected from the audio stream. In parallel with the classification, the spatial audio quality is achieved by adding an artificial reverberation in a virtual acoustic space to the input mono sound. Thereafter, the spatial sound is boosted with the given frequency gains based on the musical genre when played back. Experiments measured the accuracy of detecting the musical segment from the audio stream and its musical genre classification. A listening test was performed based on the virtual acoustic space based spatial audio processing.

Keywords: automatic equalization, genre classification, music segment detection, spatial audio processing

Procedia PDF Downloads 429