Search results for: fruits processing

Authors: Pratibha Srivastava, Ayyamperumal Jeyaprakash, Gary Steck

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Exotic, invasive tephritid fruit flies (Diptera: Tephritidae) are a major concern to fruit and vegetable production in the USA. Timely detection and identification of these agricultural pests facilitate the possibility of eradication from newly invaded areas. They spread primarily as larvae in infested fruits carried in commerce or personal baggage. Identification of larval stages to species level is difficult but necessary to determine pest loads and their pathways into the USA. The main focus of this study is the New World genus, Anastrepha. Many of its constituent taxa are pests of major economic importance. This study is significant for national quarantine use, as morphological diagnostics to separate larvae of the various members remain poorly developed. Elongation factor 1 alpha sequences were amplified from Anastrepha fraterculus specimens collected from South America (Ecuador and Peru). Phylogenetic analysis was performed to characterize the Anastrepha fraterculus complex at a molecular level.

Keywords: anastrepha, diptera, elongation factor, fruit fly

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Authors: Lukas Ded

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Studying the tissue structure and histogenesis in the natural, 3D context is challenging but highly beneficial process. Contrary to classical approach of the physical tissue sectioning and subsequent imaging, it enables to study the relationships of individual cellular and histological structures in their native context. Recent developments in the tissue clearing approaches and microscopic volume imaging/data processing enable the application of these methods also in the areas of developmental and reproductive biology. Here, using the CLARITY tissue procedure and 3D confocal volume imaging we optimized the protocol for clearing, staining and imaging of the mice seminiferous tubules isolated from the testes without cardiac perfusion procedure. Our approach enables the high magnification and fine resolution axial imaging of the whole diameter of the seminiferous tubules with possible unlimited lateral length imaging. Hence, the large continuous pieces of the seminiferous tubule can be scanned and digitally reconstructed for the study of the single tubule seminiferous stages using nuclear dyes. Furthermore, the application of the antibodies and various molecular dyes can be used for molecular labeling of individual cellular and subcellular structures and resulting 3D images can highly increase our understanding of the spatiotemporal aspects of the seminiferous tubules development and sperm ultrastructure formation. Finally, our newly developed algorithms for 3D data processing enable the massive parallel processing of the large amount of individual cell and tissue fluorescent signatures and building the robust spermatogenic models under physiological and pathological conditions.

Keywords: CLARITY, spermatogenesis, testis, tissue clearing, volume imaging

Procedia PDF Downloads 136

Authors: P. S. Surya Meghana, K. Lingeshwaran, C. Kannan, V. Raghavendran, C. Priya

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One of the most basic and powerful tools in all of science and medicine is the light microscope, the fundamental device for laboratory as well as research purposes. With the improving technology, the need for portable, economic and user-friendly instruments is in high demand. The conventional microscope fails to live up to the emerging trend. Also, adequate access to healthcare is not widely available, especially in developing countries. The most basic step towards the curing of a malady is the diagnosis of the disease itself. The main aim of this paper is to diagnose Malaria with the most common device, cell phones, which prove to be the immediate solution for most of the modern day needs with the development of wireless infrastructure allowing to compute and communicate on the move. This opened up the opportunity to develop novel imaging, sensing, and diagnostics platforms using mobile phones as an underlying platform to address the global demand for accurate, sensitive, cost-effective, and field-portable measurement devices for use in remote and resource-limited settings around the world.

Keywords: cellular, hand-held, health care, image processing, malarial parasites, microscope

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Authors: Pontsho E. Tseke, Phatu W. Mashela

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Cucurbitacin-containing phytonematicides had been consistent in suppressing root-knot (Meloidogyne species) when used in dried crude form, with limited evidence whether the efficacy could be affected when fresh fruits were used during fermentation. The objective of this study was to determine the influence of Nemafric-BL phytonematicide prepared using fermented crude extracts of fresh fruit from wild watermelon (Cucumis africanus) on the growth of tomato (Solanum lycopersicum) plants and suppression of Meloidogyne species. Seedlings of tomato cultivar ‘Floradade’ were inoculated with 3 000 eggs and second-stage juveniles (J2) of M. incognita race 2 in pot trials, with treatments comprising 0, 2, 4, 8, 16, 32 and 64 % Nemafric-BL phytonematicide. At 56 days after inoculation, the phytonematicide reduced eggs and J2 in roots by 84-97%, J2 in soil by 49-96% and total nematodes by 70-97%. Plant variables and concentrations of Nemafric-BL phytonematicide exhibited positive quadratic relations, with 74-98% associations. In conclusion, fresh fruit of C. africanus could be used for the preparation of Nemafric-BL phytonematicide, particularly in cases where the dry infrastructure is not available.

Keywords: Cucurbitacin B, density-dependent growth, effective microorganisms, quadratic relations

Procedia PDF Downloads 185

Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

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Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000 cm-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R2 = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R2 = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, pasta, moisture determination, food engineering

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Authors: Sruthi Raveendran

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Developmental dyslexia, characterized by reading difficulties despite normal intelligence, presents a significant challenge for bilingual children navigating languages with varying degrees of orthographic transparency. This study bridges a critical gap in dyslexia interventions for bilingual populations in India by examining how consistency and predictability of letter-sound relationships in a writing system (orthographic transparency) influence the ability to understand and manipulate the building blocks of sound in language (phonological processing). The study employed a computerized visual rhyme-judgment task with concurrent EEG (electroencephalogram) recording. The task compared reaction times, accuracy of performance, and event-related potential (ERP) components (N170, N400, and LPC) for rhyming and non-rhyming stimuli in two orthographies: English (opaque orthography) and Kannada (transparent orthography). As hypothesized, the results revealed advantages in phonological processing tasks for transparent orthography (Kannada). Children with dyslexia were faster and more accurate when judging rhymes in Kannada compared to English. This suggests that a language with consistent letter-sound relationships (transparent orthography) facilitates processing, especially for tasks that involve manipulating sounds within words (rhyming). Furthermore, brain activity measured by event-related potentials (ERP) showed less effort required for processing words in Kannada, as reflected by smaller N170, N400, and LPC amplitudes. These findings highlight the crucial role of orthographic transparency in optimizing reading performance for bilingual children with dyslexia. These findings emphasize the need for language-specific intervention strategies that consider the unique linguistic characteristics of each language. While acknowledging the complexity of factors influencing dyslexia, this research contributes valuable insights into the impact of orthographic transparency on phonological awareness in bilingual children. This knowledge paves the way for developing tailored interventions that promote linguistic inclusivity and optimize literacy outcomes for children with dyslexia.

Keywords: developmental dyslexia, phonological awareness, rhyme judgment, orthographic transparency, Kannada, English, N170, N400, LPC

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Authors: Ahd Aljarf, Saad Amin

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Images are important source of information used as evidence during any investigation process. Their clarity and accuracy is essential and of the utmost importance for any investigation. Images are vulnerable to losing blocks and having noise added to them either after alteration or when the image was taken initially, therefore, having a high performance image processing system and it is implementation is very important in a forensic point of view. This paper focuses on improving the quality of the forensic images. For different reasons packets that store data can be affected, harmed or even lost because of noise. For example, sending the image through a wireless channel can cause loss of bits. These types of errors might give difficulties generally for the visual display quality of the forensic images. Two of the images problems: noise and losing blocks are covered. However, information which gets transmitted through any way of communication may suffer alteration from its original state or even lose important data due to the channel noise. Therefore, a developed system is introduced to improve the quality and clarity of the forensic images.

Keywords: image filtering, image reconstruction, image processing, forensic images

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Authors: Dina K. Badawy, Dina M. Ibrahim, Alsayed A. Sallam

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Distributed database is a collection of logically related databases that cooperate in a transparent manner. Query processing uses a communication network for transmitting data between sites. It refers to one of the challenges in the database world. The development of sophisticated query optimization technology is the reason for the commercial success of database systems, which complexity and cost increase with increasing number of relations in the query. Mariposa, query trading and query trading with processing task-trading strategies developed for autonomous distributed database systems, but they cause high optimization cost because of involvement of all nodes in generating an optimal plan. In this paper, we proposed a modification on the autonomous strategy K-QTPT that make the seller’s nodes with the lowest cost have gradually high priorities to reduce the optimization time. We implement our proposed strategy and present the results and analysis based on those results.

Keywords: autonomous strategies, distributed database systems, high priority, query optimization

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Authors: Somayeh Komeylian

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Array signal processing techniques have been recently developing in a variety application of the performance enhancement of receivers by refraining the power of jamming and interference signals. In this scenario, biases induced to the antenna array receiver degrade significantly the accurate estimation of the carrier phase. Owing to the integration of frequency becomes the carrier phase, we have obtained the unbiased doppler frequency for the high precision estimation of carrier phase. The unbiased characteristic of Doppler frequency to the power jamming and the other interference signals allows achieving the highly accurate estimation of phase carrier. In this study, we have rigorously investigated the unbiased characteristic of Doppler frequency to the variation of the antenna array geometries. The simulation results have efficiently verified that the Doppler frequency remains also unbiased and accurate to the variation of antenna array geometries.

Keywords: array signal processing, unbiased doppler frequency, GNSS, carrier phase, and slowly fluctuating point target

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Authors: Leonardo Alfredo Mendoza, Cristian Munoz, Marco Aurelio Pacheco, Manoela Kohler, Evelyn Batista, Rodrigo Moura

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Natural Language Processing (NLP) techniques are increasingly more powerful to be able to interpret the feelings and reactions of a person to a product or service. Sentiment analysis has become a fundamental tool for this interpretation but has few applications in languages other than English. This paper presents a classification of sentiment analysis in Portuguese with a base of comments from social networks in Portuguese. A word embedding's representation was used with a 50-Dimension GloVe pre-trained model, generated through a corpus completely in Portuguese. To generate this classification, the bidirectional long short-term memory and bidirectional Gated Recurrent Unit (GRU) models are used, reaching results of 99.1%.

Keywords: natural processing language, sentiment analysis, bidirectional long short-term memory, BI-LSTM, gated recurrent unit, GRU

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Authors: Azam Fazelpour, Saeed R. Dehghani, Vlastimil Masek, Yuri S. Muzychka

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The study uses an image analysis technique employing thermal imaging to measure the percentage of areas with various temperatures on a freezing surface. An image segmentation method using threshold values is applied to a sequence of image recording the freezing process. The phenomenon is transient and temperatures vary fast to reach the freezing point and complete the freezing process. Freezing salt water is subjected to the salt rejection that makes the freezing point dynamic and dependent on the salinity at the phase interface. For a specific area of freezing, nucleation starts from one side and end to another side, which causes a dynamic and transient temperature in that area. Thermal cameras are able to reveal a difference in temperature due to their sensitivity to infrared radiance. Using Experimental setup, a video is recorded by a thermal camera to monitor radiance and temperatures during the freezing process. Image processing techniques are applied to all frames to detect and classify temperatures on the surface. Image processing segmentation method is used to find contours with same temperatures on the icing surface. Each segment is obtained using the temperature range appeared in the image and correspond pixel values in the image. Using the contours extracted from image and camera parameters, stratified areas with different temperatures are calculated. To observe temperature contours on the icing surface using the thermal camera, the salt water sample is dropped on a cold surface with the temperature of -20°C. A thermal video is recorded for 2 minutes to observe the temperature field. Examining the results obtained by the method and the experimental observations verifies the accuracy and applicability of the method.

Keywords: ice contour boundary, image processing, image segmentation, salt ice, thermal image

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Authors: Evans Belly, Imdad Rizvi, M. M. Kadam

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Satellite imagery is one of the emerging technologies which are extensively utilized in various applications such as detection/extraction of man-made structures, monitoring of sensitive areas, creating graphic maps etc. The main approach here is the automated detection of buildings from very high resolution (VHR) optical satellite images. Initially, the shadow, the building and the non-building regions (roads, vegetation etc.) are investigated wherein building extraction is mainly focused. Once all the landscape is collected a trimming process is done so as to eliminate the landscapes that may occur due to non-building objects. Finally the label method is used to extract the building regions. The label method may be altered for efficient building extraction. The images used for the analysis are the ones which are extracted from the sensors having resolution less than 1 meter (VHR). This method provides an efficient way to produce good results. The additional overhead of mid processing is eliminated without compromising the quality of the output to ease the processing steps required and time consumed.

Keywords: building detection, shadow detection, landscape generation, label, partitioning, very high resolution (VHR) satellite imagery

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Authors: R. N. Karthik Babu, R. Sarvesh, A. Rajendra Prasad, G. Swaminathan

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M42 is a molybdenum-series high-speed alloy steel widely used because of its better hot-hardness and wear resistance. These steels are conventionally heat treated in a salt bath furnace with up to three stages of preheating with predetermined soaking and holding periods. Such methods often involve long periods of processing with a large amount of energy consumed. In this study, the M42 steel samples were heat-treated by rapidly heating the specimens to the austenising temperature of 1260 °C and cooled conventionally by quenching in a neutral salt bath at a temperature of 550 °C with the aid of a hybrid microwave furnace. As metals reflect microwaves, they cannot directly be heated up when placed in a microwave furnace. The technology used herein requires the specimens to be placed in a crucible lined with SiC which is a good absorber of microwaves and the SiC lining heats the metal through radiation which facilitates the volumetric heating of the metal. A sample of similar dimensions was heat treated conventionally and cooled in the same manner. Conventional tempering process was then carried out on both these samples and analysed for various parameters such as micro-hardness, processing time, etc. Microstructure analysis and scanning electron microscopy was also carried out. The objective of the study being that similar or better properties, with substantial time and energy saving and cost cutting are achievable by rapid heat treatment through hybrid microwave furnaces. It is observed that the heat treatment is done with substantial time and energy savings, and also with minute improvement in mechanical properties of the tool steel heat treated.

Keywords: rapid heating, heat treatment, metal processing, microwave heating

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Authors: Ramandeep Kaur, Kamaljit Kaur

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In recent years, the technology of the remote sensing is growing rapidly. Image enhancement is one of most commonly used of image processing operations. Noise reduction plays very important role in digital image processing and various technologies have been located ahead to reduce the noise of the remote sensing images. The noise reduction using wavelet coefficients based on Orthogonal Matching Pursuit (OMP) has less consequences on the edges than available methods but this is not as establish in edge preservation techniques. So in this paper we provide a new technique minimum patch based noise reduction OMP which reduce the noise from an image and used edge preservation patch which preserve the edges of the image and presents the superior results than existing OMP technique. Experimental results show that the proposed minimum patch approach outperforms over existing techniques.

Keywords: image denoising, minimum patch, OMP, WCOMP

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Authors: Janusz Getta, Zhaoxi Pan

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Performance-based quality evaluation of database conceptual schemas is an important aspect of database design process. It is evident that different conceptual schemas provide different logical schemas and performance of user applications strongly depends on logical and physical database structures. This work presents the entire process of performance-based quality evaluation of conceptual schemas. First, we show format. Then, the paper proposes a new specification of object algebra for representation of conceptual level database applications. Transformation of conceptual schemas and expression of object algebra into implementation schema and implementation in a particular database system allows for precise estimation of the processing costs of database applications and as a consequence for precise evaluation of performance-based quality of conceptual schemas. Then we describe an experiment as a proof of concept for the evaluation procedure presented in the paper.

Keywords: conceptual schema, implementation schema, logical schema, object algebra, performance evaluation, query processing

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Authors: Merzougui Imene, Gherib Asma, Henchiri Cherifa

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This study has allowed to confirm the physico chemical characteristics and fatty acid composition by GC of the oil of Pistacia lentiscus extracted by traditional method and evaluate its effect on some blood lipid parameters. The results showed that the main physico chemical characteristics of Pistacia lentiscus oil are: moisture (0.84 %), a relatively high iodine value (80,44) indicating that this oil has an important degree of unsaturation. The oil is mainly composed of unsaturated fatty acids (MUFA) where oleic acid dominate with 47,01 % of total fatty acids and PUFA's represented by linoleic acid (19,26 %). Concerning the biological survey, oil, at 10% and 20% doses of diet for 15 and 30 days of two periods of treatment, resulted in beneficial effects on the lipid profile of Wistar albinos rats previously fed with animal and vegetable fats. We observed decreases in total cholesterol, triglycerides (TGA), total lipids and LDL-C, and an increase in HDL-C "good cholesterol" probably related to the presence of a large amount of (MUFA) and (PUFA).

Keywords: Pistacia lentiscus, oil, lipid profile, monounsaturated fatty acids, polyunsaturated fatty acids

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Authors: Ruomeng Xiao, Zhulin Zong, Longfa Yang

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Aiming at the problem that the target signal is difficult to detect under the strong ground clutter environment, this paper proposes a clutter suppression algorithm based on the combination of singular value decomposition and the Mallat fast wavelet algorithm. The method first carries out singular value decomposition on the radar echo data matrix, realizes the initial separation of target and clutter through the threshold processing of singular value, and then carries out wavelet decomposition on the echo data to find out the target location, and adopts the discard method to select the appropriate decomposition layer to reconstruct the target signal, which ensures the minimum loss of target information while suppressing the clutter. After the verification of the measured data, the method has a significant effect on the target extraction under low SCR, and the target reconstruction can be realized without the prior position information of the target and the method also has a certain enhancement on the output SCR compared with the traditional single wavelet processing method.

Keywords: clutter suppression, singular value decomposition, wavelet transform, Mallat algorithm, low SCR

Procedia PDF Downloads 118

Authors: M. A. Alavianmehr, A. Tashk, A. Sodagaran

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Modeling background and moving objects are significant techniques for video surveillance and other video processing applications. This paper presents a foreground detection algorithm that is robust against illumination changes and noise based on adaptive mixture Gaussian model (GMM), and provides a novel and practical choice for intelligent video surveillance systems using static cameras. In the previous methods, the image of still objects (background image) is not significant. On the contrary, this method is based on forming a meticulous background image and exploiting it for separating moving objects from their background. The background image is specified either manually, by taking an image without vehicles, or is detected in real-time by forming a mathematical or exponential average of successive images. The proposed scheme can offer low image degradation. The simulation results demonstrate high degree of performance for the proposed method.

Keywords: image processing, background models, video surveillance, foreground detection, Gaussian mixture model

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Authors: Pan Long, Bi Dongjie, Li Xifeng, Xie Yongle

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The near-field synthetic aperture radar (SAR) imaging is an advanced nondestructive testing and evaluation (NDT&E) technique. This paper investigates the complex-valued signal processing related to the near-field SAR imaging system, where the measurement data turns out to be noncircular and improper, meaning that the complex-valued data is correlated to its complex conjugate. Furthermore, we discover that the degree of impropriety of the measurement data and that of the target image can be highly correlated in near-field SAR imaging. Based on these observations, A modified generalized sparse Bayesian learning algorithm is proposed, taking impropriety and noncircularity into account. Numerical results show that the proposed algorithm provides performance gain, with the help of noncircular assumption on the signals.

Keywords: complex-valued signal processing, synthetic aperture radar, 2-D radar imaging, compressive sensing, sparse Bayesian learning

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Authors: Muhammad Faiz Liew Abdullah, Bhagwan Das, Nor Shahida, Abdul Fattah Chandio

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This study presents the designed features of Graphical User Interface (GUI) for chromatic dispersion (CD) reduction using digital signal processing (DSP) techniques. GUI is specially designed for windows platform. The obtained simulation results from matlab are presented via this GUI. After importing results from matlab in GUI, It will present your work on any windows7 and onwards versions platforms without matlab software. First part of the GUI contains the research methodology block diagram and in the second part, output for each stage is shown in separate reserved area for the result display. Each stage of methodology has the captions to display the results. This GUI will be very helpful during presentations instead of making slides this GUI will present all your work easily in the absence of other software’s such as Matlab, Labview, MS PowerPoint. GUI is designed using C programming in MS Visio Studio.

Keywords: Matlab simulation results, C programming, MS VISIO studio, chromatic dispersion

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Authors: Walid Fantazi

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The development of sensor technology (such as microelectromechanical systems (MEMS), wireless communications, embedded systems, distributed processing and wireless sensor applications) has contributed to a broad range of WSN applications which are capable of collecting a large amount of spatiotemporal data in real time. These systems require real-time data processing to manage storage in real time and query the data they process. In order to cover these needs, we propose in this paper a Snapshot spatiotemporal data model based on object-oriented concepts. This model allows saving storing and reducing data redundancy which makes it easier to execute spatiotemporal queries and save analyzes time. Further, to ensure the robustness of the system as well as the elimination of congestion from the main access memory we propose a spatiotemporal indexing technique in RAM called Captree *. As a result, we offer an RIA (Rich Internet Application) -based SOA application architecture which allows the remote monitoring and control.

Keywords: WSN, indexing data, SOA, RIA, geographic information system

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Authors: Ramesh Rajagopalan, Adam Dahlstrom

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Noise removal techniques play a vital role in the performance of electrocardiographic (ECG) signal processing systems. ECG signals can be corrupted by various kinds of noise such as baseline wander noise, electromyographic interference, and power-line interference. One of the significant challenges in ECG signal processing is the degradation caused by additive 50 or 60 Hz power-line interference. This work investigates the removal of power line interference and suppression of transient response for filtering noise corrupted ECG signals. We demonstrate the effectiveness of Infinite Impulse Response (IIR) notch filter with time varying pole radius for improving the transient behavior. The temporary change in the pole radius of the filter diminishes the transient behavior. Simulation results show that the proposed IIR filter with time varying pole radius outperforms traditional IIR notch filters in terms of mean square error and transient suppression.

Keywords: notch filter, ECG, transient, pole radius

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Authors: Natalia Fijol, Aji P. Mathew

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We present the processing and characterisation of three-dimensional (3D) monolith filters based on polylactic acid (PLA) reinforced with various nature-derived nanospecies such as hydroxyapatite, modified cellulose fibers and chitin fibers. The nanospecies of choice were dispersed in PLA through Thermally Induced Phase Separation (TIPS) method. The biocomposites were developed via solvent-assisted blending and the obtained pellets were further single-screw extruded into 3D-printing filaments and processed into various geometries using Fused Deposition Modelling (FDM) technique. The printed prototypes included cubic, cylindrical and hour-glass shapes with diverse patterns of printing infill as well as varying pore structure including uniform and multiple level gradual pore structure. The pores and channel structure as well as overall shape of the prototypes were designed in attempt to optimize the flux and maximize the adsorption-active time. FDM is a cost and energy-efficient method, which does not require expensive tools and elaborated post-processing maintenance. Therefore, FDM offers the possibility to produce customized, highly functional water purification filters with tuned porous structures suitable for removal of wide range of common water pollutants. Moreover, as 3D printing becomes more and more available worldwide, it allows producing portable filters at the place and time where they are most needed. The study demonstrates preparation route for the PLA-based, fully biobased composite and their processing via FDM technique into water purification filters, addressing water treatment challenges on an industrial scale.

Keywords: fused deposition modelling, water treatment, biomaterials, 3D printing, nanocellulose, nanochitin, polylactic acid

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Authors: So Yae Koh, YeonWoo Song, Ji-Yeon Ryu, Jeong Yong Moon, Somi Kim Cho

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Blueberry, a perennial shrub, is one of the most popular fruits due to its flavor and strong free radical scavenging properties. In this study, the blueberry puree was fermented by Lactobacillus plantarum CK10 and the antioxidant activities of fermentation products were examined. Various conditions with different supplements (5% sucrose or 10% skim milk) were evaluated for fermentation efficiency and the effects on antioxidant properties. The viable cell count of lactic acid bacteria, pH, total phenolic compounds and flavonoids contents were measured after 7 days of fermentation. DPPH (1,1-diphenyl-2-picrylhydrazyl) and ABTS [2,2’-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid)] radical scavenging activities were highly enhanced compared to non-fermented blueberry puree after fermentation. Interestingly, the antioxidant activities were greatly increased in the fermentation of blueberry puree alone without supplements. The present results indicate that the blueberry puree fermented by Lactobacillus plantarum CK10 could be used as a potential source of natural antioxidants and these findings will facilitate the utilization of blueberry as a resource for food additive.

Keywords: antioxidant activity, blueberry, lactobacillus plantarum CK10, fermentation

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Authors: A. B. M. S. Hossain, A. Abdelgadir, N. A. Ibrahim

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Fresh ripen olive cannot be consumed immediately after harvest due to the excessive bitterness having polyphenol as antioxidant. Industrial processing needs to be edible the fruit. The laboratory processing technique has been used to make it edible by using acid (vinegar, 5% acetic acid) and alkaline solvent (NaOH). Based on the treatment and consequence, innovative data have been found in this regard. The experiment was conducted to investigate biochemical content, nutritional and DNA characterization of olive fruit treated with alkaline (Sodium chloride anhydrous) and acidic solvent (5% acetic acid, vinegar). The treatments were used as control (no water), water control, 10% sodium chloride anhydrous (NaOH), vinegar (5% acetic acid), vinegar + NaOH and vinegar + NaOH + hot water treatment. Our results showed that inverted sugar and glucose content were higher in the vinegar and NaOH treated olive than in other treatments. Fructose content was the highest in vinegar + NaOH treated fruit. Nutrient contents NO3 K, Ca and Na were found higher in the treated fruit than the control fruit. Moreover, maximum K content was observed in the case of all treatments compared to the other nutrient content. The highest acidic (lower pH) condition (sour) was found in treated fruit. DNA yield was found higher in water control than acid and alkaline treated olives. DNA band was wider in the olive treated water control compared to the NaOH, vinegar, vinegar + NaOH and vinegar + NaOH + Hot water treatment. Finally, results suggest that vinegar + NaOH treated olive fruit was the best for fresh olive homemade processing after harvesting for edible purpose.

Keywords: olive, vinegar, sugars, DNA band, bioprocess biotechnology

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Authors: Sihem Oujdi, Hafida Belbachir

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Existing methods of data mining cannot be applied on spatial data because they require spatial specificity consideration, as spatial relationships. This paper focuses on the classification with decision trees, which are one of the data mining techniques. We propose an extension of the C4.5 algorithm for spatial data, based on two different approaches Join materialization and Querying on the fly the different tables. Similar works have been done on these two main approaches, the first - Join materialization - favors the processing time in spite of memory space, whereas the second - Querying on the fly different tables- promotes memory space despite of the processing time. The modified C4.5 algorithm requires three entries tables: a target table, a neighbor table, and a spatial index join that contains the possible spatial relationship among the objects in the target table and those in the neighbor table. Thus, the proposed algorithms are applied to a spatial data pattern in the accidentology domain. A comparative study of our approach with other works of classification by spatial decision trees will be detailed.

Keywords: C4.5 algorithm, decision trees, S-CART, spatial data mining

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Authors: Mrinal Kanti Bhowmik, Shawli Bardhan Jr., Debotosh Bhattacharjee

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Human skin containing temperature value more than absolute zero, discharges infrared radiation related to the frequency of the body temperature. The difference in infrared radiation from the skin surface reflects the abnormality present in human body. Considering the difference, detection and forecasting the temperature variation of the skin surface is the main objective of using Medical Infrared Thermography(MIT) as a diagnostic tool for pain detection. Medical Infrared Thermography(MIT) is a non-invasive imaging technique that records and monitors the temperature flow in the body by receiving the infrared radiated from the skin and represent it through thermogram. The intensity of the thermogram measures the inflammation from the skin surface related to pain in human body. Analysis of thermograms provides automated anomaly detection associated with suspicious pain regions by following several image processing steps. The paper represents a rigorous study based survey related to the processing and analysis of thermograms based on the previous works published in the area of infrared thermal imaging for detecting inflammatory pain diseases like arthritis, spondylosis, shoulder impingement, etc. The study also explores the performance analysis of thermogram processing accompanied by thermogram acquisition protocols, thermography camera specification and the types of pain detected by thermography in summarized tabular format. The tabular format provides a clear structural vision of the past works. The major contribution of the paper introduces a new thermogram acquisition standard associated with inflammatory pain detection in human body to enhance the performance rate. The FLIR T650sc infrared camera with high sensitivity and resolution is adopted to increase the accuracy of thermogram acquisition and analysis. The survey of previous research work highlights that intensity distribution based comparison of comparable and symmetric region of interest and their statistical analysis assigns adequate result in case of identifying and detecting physiological disorder related to inflammatory diseases.

Keywords: acquisition protocol, inflammatory pain detection, medical infrared thermography (MIT), statistical analysis

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Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

Abstract:

Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

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Authors: Heng Sreyly, Phoeurk Chanrith

Abstract:

Fresh-eaten vegetables have become more popular in the Cambodian diet. However, according to WHO, these vegetables should be one of the main sources of infection if contaminated with pathogenic microorganisms. The outbreaks of foodborne diseases related to fresh fruits and vegetables have been increasingly reported and raised concerns regarding the safety of these products. Therefore, it is very important to conduct the determination of virulence factors Escherichia coli and Salmonella spp. in fresh vegetables. This study aims to identify virulence strains of Escherichia coli and Salmonella species from fresh vegetables, including cucumber (Cucumis sativus), saw-herb (Eryngium foetidum), and lettuce (Lactuca sativa) from different market and supermarket in Phnom Penh. The PCR method was used to detect the virulence strains of each sample. The results indicate that there are ninety five samples containing extracted DNA among one hundred and three samples. Moreover, the virulence strain of E. coli and salmonella have been found in leafy vegetables (lettuce and saw-herb) much more than in fruit vegetables (cucumber). This research is mainly used to raise public awareness of washing fresh vegetables with clean water more carefully to reduce adverse health impacts.

Keywords: DNA, virulence factor, Escherichia coli, Salmonella

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Authors: Kavyadevi N., Kaviya G., Gowsalya P., Janani M., Mohanraj S.

Abstract:

Hevea brasiliensis, also known as the rubber tree, is one of the foremost assets of crops in the world. One of the most significant advantages of the Rubber Plant in terms of air oxygenation is its capacity to reduce the likelihood of an individual developing respiratory allergies like asthma. To construct such a system that can properly identify crop diseases and pests and then create a database of insecticides for each pest and disease, we must first give treatment for the illness that has been detected. We shall primarily examine three major leaf diseases since they are economically deficient in this article, which is Bird's eye spot, algal spot and powdery mildew. And the recommended work focuses on disease identification on rubber tree leaves. It will be accomplished by employing one of the superior algorithms. Input, Preprocessing, Image Segmentation, Extraction Feature, and Classification will be followed by the processing technique. We will use time-consuming procedures that they use to detect the sickness. As a consequence, the main ailments, underlying causes, and signs and symptoms of diseases that harm the rubber tree are covered in this study.

Keywords: image processing, python, convolution neural network (CNN), machine learning

Procedia PDF Downloads 76