Search results for: sesimic data processing

Authors: Pei-Jyun Hsieh, Cheng-Hsuan Li, Bor-Chen Kuo

Abstract:

For hyperspectral image classification, feature reduction is an important pre-processing for avoiding the Hughes phenomena due to the difficulty for collecting training samples. Hence, lots of researches developed feature selection methods such as F-score, HSIC (Hilbert-Schmidt Independence Criterion), and etc., to improve hyperspectral image classification. However, most of them only consider the class separability in the original space, i.e., a linear class separability. In this study, we proposed a nonlinear class separability measure based on kernel trick for selecting an appropriate feature subset. The proposed nonlinear class separability was formed by a generalized RBF kernel with different bandwidths with respect to different features. Moreover, it considered the within-class separability and the between-class separability. A genetic algorithm was applied to tune these bandwidths such that the smallest with-class separability and the largest between-class separability simultaneously. This indicates the corresponding feature space is more suitable for classification. In addition, the corresponding nonlinear classification boundary can separate classes very well. These optimal bandwidths also show the importance of bands for hyperspectral image classification. The reciprocals of these bandwidths can be viewed as weights of bands. The smaller bandwidth, the larger weight of the band, and the more importance for classification. Hence, the descending order of the reciprocals of the bands gives an order for selecting the appropriate feature subsets. In the experiments, three hyperspectral image data sets, the Indian Pine Site data set, the PAVIA data set, and the Salinas A data set, were used to demonstrate the selected feature subsets by the proposed nonlinear feature selection method are more appropriate for hyperspectral image classification. Only ten percent of samples were randomly selected to form the training dataset. All non-background samples were used to form the testing dataset. The support vector machine was applied to classify these testing samples based on selected feature subsets. According to the experiments on the Indian Pine Site data set with 220 bands, the highest accuracies by applying the proposed method, F-score, and HSIC are 0.8795, 0.8795, and 0.87404, respectively. However, the proposed method selects 158 features. F-score and HSIC select 168 features and 217 features, respectively. Moreover, the classification accuracies increase dramatically only using first few features. The classification accuracies with respect to feature subsets of 10 features, 20 features, 50 features, and 110 features are 0.69587, 0.7348, 0.79217, and 0.84164, respectively. Furthermore, only using half selected features (110 features) of the proposed method, the corresponding classification accuracy (0.84168) is approximate to the highest classification accuracy, 0.8795. For other two hyperspectral image data sets, the PAVIA data set and Salinas A data set, we can obtain the similar results. These results illustrate our proposed method can efficiently find feature subsets to improve hyperspectral image classification. One can apply the proposed method to determine the suitable feature subset first according to specific purposes. Then researchers can only use the corresponding sensors to obtain the hyperspectral image and classify the samples. This can not only improve the classification performance but also reduce the cost for obtaining hyperspectral images.

Keywords: hyperspectral image classification, nonlinear feature selection, kernel trick, support vector machine

Procedia PDF Downloads 262

Authors: Nazim Uddin, Yohiko Nakaura, Kazutaka Yamamoto

Abstract:

Compote (fruit in syrup) of pineapple (Ananas comosus L. Merrill) is expected to have a high market potential as one of convenient ready-to-eat (RTE) foods worldwide. High hydrostatic pressure (HHP) in combination with low temperature (LT) was applied to the processing of pineapple compote as well as medium HHP (MHHP) in combination with medium-high temperature (MHT) since both processes can enhance liquid impregnation and inactivate microbes. MHHP+MHT (55 or 65 °C) process, as well as the HHP+LT process, has successfully inactivated the microbes in the compote to a non-detectable level. Although the compotes processed by MHHP+MHT or HHP+LT have lost the fresh texture as in a similar manner as those processed solely by heat, it was indicated that the texture degradations by heat were suppressed under MHHP. Degassing process reduced the hardness, while calcium (Ca) contributed to be retained hardness in MHT and MHHP+MHT processes. Electrical impedance measurement supported the damage due to degassing and heat. The color, Brix, and appearance were not affected by the processing methods significantly. MHHP+MHT and HHP+LT processes may be applicable to produce high-quality, safe RTE pineapple compotes. Further studies on the optimization of packaging and storage condition will be indispensable for commercialization.

Keywords: compote of pineapple, RTE, medium high hydrostatic pressure, postharvest loss, texture

Procedia PDF Downloads 135

Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek

Abstract:

Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.

Keywords: die-map clustering, feature extraction, pattern recognition, semiconductor manufacturing process

Procedia PDF Downloads 401

Authors: Abdullah Khuwaileh

Abstract:

The central aim of this paper is to investigate writing skills in the two languages involved, English and Arabic, and to see whether there is an association between poor writing across languages. That is to say, and it is thought that learners might be excellent in their L1 (Language 1: Arabic) but not in L2 (language 2: English). However, our experimental research findings resulted in an interesting association between L1 and L2. Data were collected from 150 students (chosen randomly) who wrote about the same topic in English and Arabic. Topics needed no preparation as they were common and well-known. Scripts were assessed respectively by ELT (English Language Teaching) and Arabic specialists. The study confirms that poor writing in English correlates with similar deficiencies in the mother tongue (Arabic). Thus, the common assumption in ELT that all learners are fully competent in their first language skills is unfounded. Therefore, the criticism of ELT programs for speakers of Arabic, based on poor writing skills in English and good writing in Arabic is not justified. The findings of this paper can be extended to other learners of English who speak Arabic as a first language and English as a foreign and/or second language. The study is concluded with several research and practical recommendations

Keywords: language, writing, culture, l1

Procedia PDF Downloads 87

Authors: Maryam Aloshan, Imam Mohammad Ibn Saud, Ahmad Khudair

Abstract:

This study assesses the data governance maturity of nonprofit organizations in Riyadh, Saudi Arabia, using the National Data Maturity Index (NDI) framework developed by the Saudi Data and Artificial Intelligence Authority (SDAIA). Employing a survey designed around the NDI model, data maturity levels were evaluated across 14 dimensions using a 5-point Likert scale. The results reveal a spectrum of maturity levels among the organizations surveyed: while some medium-sized associations reached the ‘Defined’ stage, others, including large associations, fell within the ‘Absence of Capabilities’ or ‘Building’ phases, with no organizations achieving the advanced ‘Established’ or ‘Pioneering’ levels. This variation suggests an emerging recognition of data governance but underscores the need for targeted interventions to bridge the maturity gap. The findings point to a significant opportunity to elevate data governance capabilities in Saudi nonprofits through customized capacity-building initiatives, including training, mentorship, and best practice sharing. This study contributes valuable insights into the digital transformation journey of the Saudi nonprofit sector, aligning with national goals for data-driven governance and organizational efficiency.

Keywords: nonprofit organizations-national data maturity index (NDI), Saudi Arabia- SDAIA, data governance, data maturity

Procedia PDF Downloads 13

Authors: Zhenqiu Liu

Abstract:

Visualizing the heterogeneity within cell-populations for single-cell RNA-seq data is crucial for studying the functional diversity of a cell. However, because of the high level of noises, outlier, and dropouts, it is very challenging to measure the cell-to-cell similarity (distance), visualize and cluster the data in a low-dimension. Minimum volume embedding (MVE) projects the data into a lower-dimensional space and is a promising tool for data visualization. However, it is computationally inefficient to solve a semi-definite programming (SDP) when the sample size is large. Therefore, it is not applicable to single-cell RNA-seq data with thousands of samples. In this paper, we develop an efficient algorithm with an accelerated proximal gradient method and visualize the single-cell RNA-seq data efficiently. We demonstrate that the proposed approach separates known subpopulations more accurately in single-cell data sets than other existing dimension reduction methods.

Keywords: single-cell RNA-seq, minimum volume embedding, visualization, accelerated proximal gradient method

Procedia PDF Downloads 227

Authors: Sara Ibn El Ahrache, Tajje-eddine Rachidi, Hassan Badir, Abderrahmane Sbihi

Abstract:

Recently, there has been increasing confidence for a favorable usage of big data drawn out from the huge amount of information deposited in a cloud computing system. Data kept on such systems can be retrieved through the network at the user’s convenience. However, the data that users send include private information, and therefore, information leakage from these data is now a major social problem. The usage of secret sharing schemes for cloud computing have lately been approved to be relevant in which users deal out their data to several servers. Notably, in a (k,n) threshold scheme, data security is assured if and only if all through the whole life of the secret the opponent cannot compromise more than k of the n servers. In fact, a number of secret sharing algorithms have been suggested to deal with these security issues. In this paper, we present a Mapreduce implementation of Shamir’s secret sharing scheme to increase its performance and to achieve optimal security for cloud data. Different tests were run and through it has been demonstrated the contributions of the proposed approach. These contributions are quite considerable in terms of both security and performance.

Keywords: cloud computing, data security, Mapreduce, Shamir's secret sharing

Procedia PDF Downloads 306

Authors: A. E. El-Henawey, A. A. El-Kouny, M. M. Abd –El-Halim

Abstract:

Moving target indication (MTI) which is an anti-clutter technique that limits the display of clutter echoes. It uses the radar received information primarily to display moving targets only. The purpose of MTI is to discriminate moving targets from a background of clutter or slowly-moving chaff particles as shown in this paper. Processing system in these radars is so massive and complex; since it is supposed to perform a great amount of processing in very short time, in most radar applications the response of a single canceler is not acceptable since it does not have a wide notch in the stop-band. A double-delay canceler is an MTI delay-line canceler employing the two-delay-line configuration to improve the performance by widening the clutter-rejection notches, as compared with single-delay cancelers. This canceler is also called a double canceler, dual-delay canceler, or three-pulse canceler. In this paper, a double delay line canceler is chosen for study due to its simplicity in both concept and implementation. Discussing the implementation of a simple digital moving target indicator (DMTI) using FPGA which has distinct advantages compared to other application specific integrated circuit (ASIC) for the purposes of this work. The FPGA provides flexibility and stability which are important factors in the radar application.

Keywords: FPGA, MTI, double delay line canceler, Doppler Shift

Procedia PDF Downloads 643

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

Procedia PDF Downloads 144

Authors: Kyle De Freitas, Margaret Bernard

Abstract:

Enabling data mining analysis among a wider audience of educators is an active area of research within the educational data mining (EDM) community. The paper proposes a framework for developing an environment that caters for educators who have little technical data mining skills as well as for more advanced users with some data mining expertise. This framework architecture was developed through the review of the strengths and weaknesses of existing models in the literature. The proposed framework provides a modular architecture for future researchers to focus on the development of specific areas within the EDM process. Finally, the paper also highlights a strategy of enabling analysis through either the use of predefined questions or a guided data mining process and highlights how the developed questions and analysis conducted can be reused and extended over time.

Keywords: educational data mining, learning management system, learning analytics, EDM framework

Procedia PDF Downloads 324

Authors: Vikrum Malhotra, Manpreet Kaur, Ayesha Ghotto

Abstract:

Background: Cardiac registries such as ACC Percutaneous Coronary Intervention Registry require high quality data to be abstracted, including data elements such as nuclear cardiology, diagnostic coronary angiography, and PCI. Introduction: The audit tool created is used by data abstractors to provide data audits and assess the accuracy and inter-rater reliability of abstraction performed by the abstractors for a health system. This audit tool solution has been developed across 13 registries, including ACC/NCDR registries, PCI, STS, Get with the Guidelines. Methodology: The data audit tool was used to audit internal registry abstraction for all data elements, including stress test performed, type of stress test, data of stress test, results of stress test, risk/extent of ischemia, diagnostic catheterization detail, and PCI data elements for ACC/NCDR PCI registries. This is being used across 20 hospital systems internally and providing abstraction and audit services for them. Results: The data audit tool had inter-rater reliability and accuracy greater than 95% data accuracy and IRR score for the PCI registry in 50 PCI registry cases in 2021. Conclusion: The tool is being used internally for surgical societies and across hospital systems. The audit tool enables the abstractor to be assessed by an external abstractor and includes all of the data dictionary fields for each registry.

Keywords: abstraction, cardiac registry, cardiovascular registry, registry, data

Procedia PDF Downloads 104

Authors: Seyed Esmail Seyedi Bariran, Laysheng Ewe, Amy Ling

Abstract:

Since supplier selection appears as a vital decision, selecting supplier based on the best and most accurate ways has a lot of importance for enterprises. In this study, a new Artificial Intelligence approach is exerted to remove weaknesses of supplier selection. The paper has three parts. First part is choosing the appropriate criteria for assessing the suppliers’ performance. Next one is collecting the data set based on experts. Afterwards, the data set is divided into two parts, the training data set and the testing data set. By the training data set the best structure of GEP and ANN are selected and to evaluate the power of the mentioned methods the testing data set is used. The result obtained shows that the accuracy of GEP is more than ANN. Moreover, unlike ANN, a mathematical equation is presented by GEP for the supplier selection.

Keywords: supplier selection, automotive supply chains, ANN, GEP

Procedia PDF Downloads 630

Authors: Wided Bakari, Patrce Bellot, Mahmoud Neji

Abstract:

With the development of electronic media and the heterogeneity of Arabic data on the Web, the idea of building a clean corpus for certain applications of natural language processing, including machine translation, information retrieval, question answer, become more and more pressing. In this manuscript, we seek to create and develop our own corpus of pair’s questions-texts. This constitution then will provide a better base for our experimentation step. Thus, we try to model this constitution by a method for Arabic insofar as it recovers texts from the web that could prove to be answers to our factual questions. To do this, we had to develop a java script that can extract from a given query a list of html pages. Then clean these pages to the extent of having a database of texts and a corpus of pair’s question-texts. In addition, we give preliminary results of our proposal method. Some investigations for the construction of Arabic corpus are also presented in this document.

Keywords: Arabic, web, corpus, search engine, URL, question, corpus building, script, Google, html, txt

Procedia PDF Downloads 322

Authors: Adamu Abubakar, Abdulganiyu Yunusa, Likkason Othniel Kamfani, Abdulrahman Idris Augie

Abstract:

This research study is being carried out in accordance with the Gwandu formation's potential exploratory activities in the inland basin of northwest Nigeria.The present research aims to identify and characterize subsurface anomalies within Gwandu formation using electrical resistivity tomography (ERT) and magnetic surveys, providing valuable insights for mineral exploration. The study utilizes various data enhancement techniques like derivatives, upward continuation, and spectral analysis alongside 2D modeling of electrical imaging profiles to analyze subsurface structures and anomalies. Data was collected through ERT and magnetic surveys, with subsequent processing including derivatives, spectral analysis, and 2D modeling. The results indicate significant subsurface structures such as faults, folds, and sedimentary layers. The study area's geoelectric and magnetic sections illustrate the depth and distribution of sedimentary formations, enhancing understanding of the geological framework. Thus, showed that the entire formations of Eocene sediment of Gwandu are overprinted by the study area's Tertiary strata. The NE to SW and E to W cross-profile for the pseudo geoelectric sections beneath the study area were generated using a two-dimensional (2D) electrical resistivity imaging. 2D magnetic modelling, upward continuation, and derivative analysis are used to delineate the signatures of subsurface magnetic anomalies. The results also revealed The sediment thickness by surface depth ranges from ∼4.06 km and ∼23.31 km. The Moho interface, the lower and upper mantle crusts boundary, and magnetic crust are all located at depths of around ∼10.23 km. The vertical distance between the local models of the foundation rocks to the north and south of the Sokoto Group was approximately ∼6 to ∼8 km and ∼4.5 km, respectively.

Keywords: high-resolution aeromagnetic data, electrical resistivity imaging, subsurface anomalies, 2d dorward modeling

Procedia PDF Downloads 12

Authors: Yasuyuki Takahashi, Maya Yamashita, Kyoko Saito

Abstract:

In general, dynamic SPECT data acquisition needs a few minutes for one rotation. Thus, the time-activity curve (TAC) derived from the dynamic SPECT is relatively coarse. In order to effectively shorten the interval, between data points, we adopted a 180-degree interpolation method. This method is already used for reconstruction of the X-ray CT data. In this study, we applied this 180-degree interpolation method to SPECT and investigated its effectiveness.To briefly describe the 180-degree interpolation method: the 180-degree data in the second half of one rotation are combined with the 180-degree data in the first half of the next rotation to generate a 360-degree data set appropriate for the time halfway between the first and second rotations. In both a phantom and a patient study, the data points from the interpolated images fell in good agreement with the data points tracking the accumulation of 99mTc activity over time for appropriate region of interest. We conclude that data derived from interpolated images improves the apparent time resolution of dynamic SPECT.

Keywords: dynamic SPECT, time resolution, 180-degree interpolation method, 99mTc-GSA.

Procedia PDF Downloads 492

Authors: Omid Shahmirzadi, Adam Lugowski, Kenneth Younge

Abstract:

Automatic measurement of semantic text similarity is an important task in natural language processing. In this paper, we evaluate the performance of different vector space models to perform this task. We address the real-world problem of modeling patent-to-patent similarity and compare TFIDF (and related extensions), topic models (e.g., latent semantic indexing), and neural models (e.g., paragraph vectors). Contrary to expectations, the added computational cost of text embedding methods is justified only when: 1) the target text is condensed; and 2) the similarity comparison is trivial. Otherwise, TFIDF performs surprisingly well in other cases: in particular for longer and more technical texts or for making finer-grained distinctions between nearest neighbors. Unexpectedly, extensions to the TFIDF method, such as adding noun phrases or calculating term weights incrementally, were not helpful in our context.

Keywords: big data, patent, text embedding, text similarity, vector space model

Procedia PDF Downloads 173

Authors: M. Kharrat, G. Moreau, Z. Aboura

Abstract:

The latest advances in the weaving industry, combined with increasingly sophisticated means of materials processing, have made it possible to produce complex 3D composite structures. Mainly used in aeronautics, composite materials with 3D architecture offer better mechanical properties than 2D reinforced composites. Nevertheless, these materials require a good understanding of their behavior. Because of the complexity of such materials, the damage mechanisms are multiple, and the scenario of their appearance and evolution depends on the nature of the exerted solicitations. The AE technique is a well-established tool for discriminating between the damage mechanisms. Suitable sensors are used during the mechanical test to monitor the structural health of the material. Relevant AE-features are then extracted from the recorded signals, followed by a data analysis using pattern recognition techniques. In order to better understand the damage scenarios of interlock composite materials, a multi-instrumentation was set-up in this work for tracking damage initiation and development, especially in the vicinity of the first significant damage, called macro-damage. The deployed instrumentation includes video-microscopy, Digital Image Correlation, Acoustic Emission (AE) and micro-tomography. In this study, a multi-variable AE data analysis approach was developed for the discrimination between the different signal classes representing the different emission sources during testing. An unsupervised classification technique was adopted to perform AE data clustering without a priori knowledge. The multi-instrumentation and the clustered data served to label the different signal families and to build a learning database. This latter is useful to construct a supervised classifier that can be used for automatic recognition of the AE signals. Several materials with different ingredients were tested under various solicitations in order to feed and enrich the learning database. The methodology presented in this work was useful to refine the damage threshold for the new generation materials. The damage mechanisms around this threshold were highlighted. The obtained signal classes were assigned to the different mechanisms. The isolation of a 'noise' class makes it possible to discriminate between the signals emitted by damages without resorting to spatial filtering or increasing the AE detection threshold. The approach was validated on different material configurations. For the same material and the same type of solicitation, the identified classes are reproducible and little disturbed. The supervised classifier constructed based on the learning database was able to predict the labels of the classified signals.

Keywords: acoustic emission, classifier, damage mechanisms, first damage threshold, interlock composite materials, pattern recognition

Procedia PDF Downloads 154

Authors: Ramadas Narayanan, Surya Bhattrai, Vu Hoan

Abstract:

Threshing and cleaning are crucial post-harvest procedures that are carried out to separate the grain or seed from the harvested plant and eliminate any potential contaminants or foreign debris. After harvesting, threshing and cleaning are necessary for the clean seeds to guarantee high quality and acceptable for consumption or further processing. For mechanised production, threshing can be conducted in a thresher. Afterwards, the seeds are to be cleaned in dedicated seed-cleaning facilities. This research investigates the effectiveness of Kimseed cleaning equipment MK3, designed for grain crops for processing new crops such as sesame, fennel and kalonji. Subsequently, systematic trials were conducted to adapt the equipment to the applications in sesame and spice crops. It was done to develop methods for mechanising harvest and post-harvest operations. For sesame, it is recommended to have t a two-step process in the cleaning machine to remove large and small contaminants. The first step is to remove the large contaminants, and the second is to remove the smaller ones. The optimal parameters for cleaning fennel are a shaker frequency of 6.0 to 6.5 Hz and an airflow of 1.0 to 1.5 m/s. The optimal parameters for cleaning kalonji are a shaker frequency of 5.5Hz to 6.0 Hz and airflow of 1.0 to under 1.5m/s.

Keywords: sustainable mechanisation, sead cleaning process, optimal setting, shaker frequency

Procedia PDF Downloads 71

Authors: Chajira Garrote, Laura Arango, Lourdes Merino

Abstract:

This research explains how to obtain nutritious powder from a variety of ripe mango peels Hilacha (Mangifera indica L.) to use it as a food additive. Also, this study intends to use efficiently the by-products resulting from the operations of mango pulp manufacturing process by processing companies with the aim of giving them an added value. The physical and chemical characteristics of the mango peels and the benefits that may help humans, were studied. Unit operations are explained for the processing of mango peels and the production of nutritive powder as a food additive. Emphasis is placed on the preliminary operations applied to the raw material and on the drying method, which is very important in this project to obtain the suitable characteristics of the nutritive powder. Once the powder was obtained, it was subjected to laboratory tests to determine its functional properties: water retention capacity (WRC) and oil retention capacity (ORC), also a sensory analysis for the powder was performed to determine the product profile. The nutritive powder from the ripe mango peels reported excellent WRC and ORC values: 7.236 g of water / g B.S. and 1.796 g water / g B.S. respectively and the sensory analysis defined a complete profile of color, odor and texture of the nutritive powder, which is suitable to use it in the food industry.

Keywords: mango, peel, powder, nutritive, functional properties, sensory analysis

Procedia PDF Downloads 352

Authors: Win Nee Phong, Tau Chuan Ling, Pau Loke Show

Abstract:

From an industrial perspective, the exploitation of microalgae for protein source is of great economical and commercial interest due to numerous attractive characteristics. Nonetheless, the release of protein from microalgae is limited by the multiple layers of the rigid thick cell wall that generally contain a large proportion of cellulose. Thus an efficient cell disruption process is required to rupture the cell wall. The conventional downstream processing methods which typically involve several unit operational steps such as disruption, isolation, extraction, concentration and purification are energy-intensive and costly. To reduce the overall cost and establish a feasible technology for the success of the large-scale production, microalgal industry today demands a more cost-effective and eco-friendly technique in downstream processing. One of the main challenges to extract the proteins from microalgae is the presence of rigid cell wall. This study aims to provide some guidance on the selection of the efficient solvent to facilitate the proteins released during the cell disruption process. The effects of solvent types such as methanol, ethanol, 1-propanol and water in rupturing the microalgae cell wall were studied. It is interesting to know that water is the most effective solvent to recover proteins from microalgae and the cost is cheapest among all other solvents.

Keywords: green, microalgae, protein, solvents

Procedia PDF Downloads 257

Authors: Ruth Goldschmidt, Vyacheslav Kalchenko, Lilah Agemy, Rachel Elmoalem, Avigdor Scherz

Abstract:

Vascular Targeted Photodynamic therapy (VTP) is a new modality for selective cancer treatment that leads to the complete tumor ablation. A photosensitizer, a bacteriochlorophyll derivative in our case, is first administered to the patient and followed by the illumination of the tumor area, by a near-IR laser for its photoactivation. The photoactivated drug releases reactive oxygen species (ROS) in the circulation, which reacts with blood cells and the endothelium leading to the occlusion of the blood vasculature. If the blood vessels are only partially closed, the tumor may recover, and cancer cells could survive. On the other hand, excessive treatment may lead to toxicity of healthy tissues nearby. Simultaneous VTP monitoring and image processing independent of the photoexcitation laser has not yet been reported, to our knowledge. Here we present a method for blood flow monitoring, using a real-time laser speckle imaging (RTLSI) in the tumor during VTP. We have synthesized over the years a library of bacteriochlorophyll derivatives, among them WST11 and STL-6014. Both are water soluble derivatives that are retained in the blood vasculature through their partial binding to HSA. WST11 has been approved in Mexico for VTP treatment of prostate cancer at a certain drug dose, and time/intensity of illumination. Application to other bacteriochlorophyll derivatives or other cancers may require different treatment parameters (such as light/drug administration). VTP parameters for STL-6014 are still under study. This new derivative mainly differs from WST11 by its lack of the central Palladium, and its conjugation to an Arg-Gly-Asp (RGD) sequence. RGD is a tumor-specific ligand that is used for targeting the necrotic tumor domains through its affinity to αVβ3 integrin receptors. This enables the study of cell-targeted VTP. We developed a special RTLSI module, based on Labview software environment for data processing. The new module enables to acquire raw laser speckle images and calculate the values of the laser temporal statistics of time-integrated speckles in real time, without additional off-line processing. Using RTLSI, we could monitor the tumor’s blood flow following VTP in a CT26 colon carcinoma ear model. VTP with WST11 induced an immediate slow down of the blood flow within the tumor and a complete final flow arrest, after some sporadic reperfusions. If the irradiation continued further, the blood flow stopped also in the blood vessels of the surrounding healthy tissue. This emphasizes the significance of light dose control. Using our RTLSI system, we could prevent any additional healthy tissue damage by controlling the illumination time and restrict blood flow arrest within the tumor only. In addition, we found that VTP with STL-6014 was the most effective when the photoactivation was conducted 4h post-injection, in terms of tumor ablation success in-vivo and blood vessel flow arrest. In conclusion, RTSLI application should allow to optimize VTP efficacy vs. toxicity in both the preclinical and clinical arenas.

Keywords: blood vessel occlusion, cancer treatment, photodynamic therapy, real time imaging

Procedia PDF Downloads 222

Authors: Andrés Durán, Brian Castellanos, Marta Quicazán, Carlos Zuluaga-Domínguez

Abstract:

Bee-pollen is an apicultural-derived food product, with a growing appreciation among consumers given the remarkable nutritional and functional composition, in particular, protein (24%), dietary fiber (15%), phenols (15 – 20 GAE/g) and carotenoids (600 – 900 µg/g). These properties are given by the geographical and climatic characteristics of the region where it is collected. There are several countries recognized by their pollen production, e.g. China, United States, Japan, Spain, among others. Beekeepers use traps in the entrance of the hive where bee-pollen is collected. After the removal of foreign particles and drying, this product is ready to be marketed. However, in countries located along the equator, the absence of seasons and a constant tropical climate throughout the year favors a more rapid spoilage condition for foods with elevated water activity. The climatic conditions also trigger the proliferation of microorganisms and insects. This, added to the factor that beekeepers usually do not have adequate processing systems for bee-pollen, leads to deficiencies in the quality and safety of the product. In contrast, the Andean region of South America, lying on equator, typically has a high production of bee-pollen of up to 36 kg/year/hive, being four times higher than in countries with marked seasons. This region is also located in altitudes superior to 2500 meters above sea level, having extremes sun ultraviolet radiation all year long. As a mechanism of defense of radiation, plants produce more secondary metabolites acting as antioxidant agents, hence, plant products such as bee-pollen contain remarkable more phenolics and carotenoids than collected in other places. Considering this, the improvement of bee-pollen processing facilities by technical modifications and the implementation of an integrated cleaning and drying system for the product in an apiary in the area was proposed. The beehives were modified through the installation of alternative bee-pollen traps to avoid sources of contamination. The processing facility was modified according to considerations of Good Manufacturing Practices, implementing the combined use of a cabin dryer with temperature control and forced airflow and a greenhouse-type solar drying system. Additionally, for the separation of impurities, a cyclone type system was implemented, complementary to a screening equipment. With these modifications, a decrease in the content of impurities and the microbiological load of bee-pollen was seen from the first stages, principally with a reduction of the presence of molds and yeasts and in the number of foreign animal origin impurities. The use of the greenhouse solar dryer integrated to the cabin dryer allowed the processing of larger quantities of product with shorter waiting times in storage, reaching a moisture content of about 6% and a water activity lower than 0.6, being appropriate for the conservation of bee-pollen. Additionally, the contents of functional or nutritional compounds were not affected, even observing an increase of up to 25% in phenols content and a non-significant decrease in carotenoids content and antioxidant activity.

Keywords: beekeeping, drying, food processing, food safety

Procedia PDF Downloads 103

Authors: Folasade Adegbaju, Olusola Arowolo, Olufisayo Onawumi

Abstract:

Owolowo ile – ege garri processing industry which is a small scale cassava processing industry, located in Ilesha, Osun State was purposively selected as a case study because it is a cooperative business. This industry was established in 1991 by eight men (8) who were mostly retirees. A researcher made questionnaire was used to collect information from thirty (30) respondents: the manager, four official staffs and 25 randomly selected processors in the industry. The study found that within twelve years of the utilization of their self raised initial capital of N240, 000 naira (Two hundred and forty thousand naira) this cassava – based industry had impacted on and attracted the involvement of many more people because within the period of the study (i.e. 2007-2011) the processors had quadrupled in number (e.g. 8 to 30), the facilities (equipment) in use had increased from one machine and a frying pot to many, this translated into being able to produce large quantities of fried garri, fufu and also starch for marketing to the people in Ilesha and neighbouring cities like Ibadan, Lagos, etc. This is indicative of economic growth. The industry also became a source of employment for community members in the sense that, as at the time of study four staffs were employed to work and coordinate the industry. It was observed that despite all odds of small-scale industry and the problem of people migrating from rural to urban area, this agro-based industry still existed successfully in the community, and many of such industry can be replicated by such agricultural cooperative groups nationwide so as to further boost the productivity as well as the economy of the area and nation at large. However, government and individual still have major roles to play in ensuring the growth and development of the nation in this respect.The local agricultural cooperative groups should form regional cooperative consortium with more networking for the farmers, in order to create more jobs for the young ones and to increase agricultural productivity in the country thus resulting in a better and more sustainable economy.

Keywords: agricultural cooperative, cassava processing industry, model, small scale enterprise

Procedia PDF Downloads 289

Authors: Abdullah I. Alkraiji, Thomas W. Jackson, Ian Murray

Abstract:

The proliferation of health data standards today is somewhat overlapping and conflicting, resulting in market confusion and leading to increasing proprietary interests. The government role and support in standardization for health data are thought to be crucial in order to establish credible standards for the next decade, to maximize interoperability across the health sector, and to decrease the risks associated with the implementation of non-standard systems. The normative literature missed out the exploration of the different steps required to be undertaken by the government towards the development of national health data standards. Based on the lessons learned from a qualitative study investigating the different issues to the adoption of health data standards in the major tertiary hospitals in Saudi Arabia and the opinions and feedback from different experts in the areas of data exchange and standards and medical informatics in Saudi Arabia and UK, a list of steps required towards the development of national health data standards was constructed. Main steps are the existence of: a national formal reference for health data standards, an agreed national strategic direction for medical data exchange, a national medical information management plan and a national accreditation body, and more important is the change management at the national and organizational level. The outcome of this study can be used by academics and practitioners to develop the planning of health data standards, and in particular those in developing countries.

Keywords: interoperabilty, medical data exchange, health data standards, case study, Saudi Arabia

Procedia PDF Downloads 338

Authors: SangWon Han, MuWook Pyeon, Sujung Moon, DaeKyo Seo

Abstract:

Recently, technologies based on three-dimensional (3D) space information are being developed and quality of life is improving as a result. Research on real-time digital map (RDM) is being conducted now to provide 3D space information. RDM is a service that creates and supplies 3D space information in real time based on location/shape detection. Research subjects on RDM include the construction of 3D space information with matching image data, complementing the weaknesses of image acquisition using multi-source data, and data collection methods using big data. Using RDM will be effective for space analysis using 3D space information in a U-City and for other space information utilization technologies.

Keywords: RDM, multi-source data, big data, U-City

Procedia PDF Downloads 432

Authors: Musa M. Umar, S. G. Ado

Abstract:

The paper examines the activities of the National Programme for food security (NPFS) for averting food insecurity in Nigeria and beyond. The components of the NPFS include site development, outreach, community development and management support. On each site, core activities comprise crop productivity, production diversification and agro-processing. The outreach activities consist of inputs and commodity marketing, rural finance, strengthening research-extension-farmers-inputs linkages, health and nutrition and expansion of site activities. The community development activities include small-scale rural infrastructure, micro-earth dams and community forestry. The overall benefits include food security, improved productivity, marketing and processing, enhanced land and water use, increased animal production and fish catches, improved nutrition, reduction in post-harvest losses and value addition, improved rural infrastructure and diversification of production leading to improved livelihood. The NPFS would poster sustained development of small-holder agricultural and income generation.

Keywords: food-security, community development, post-harvest, production

Procedia PDF Downloads 353

Authors: Go Bong Choi, Shin Je Lee, Sung Jin Yoo, Gibaek Lee, Jong Min Lee

Abstract:

In South Korea, it is difficult to obtain data for statistical pipe assessment. In this paper, to address these issues, we find that various statistical model presented before is how data mixed with noise and are whether apply in South Korea. Three major type of model is studied and if data is presented in the paper, we add noise to data, which affects how model response changes. Moreover, we generate data from model in paper and analyse effect of noise. From this we can find robustness and applicability in Korea of each model.

Keywords: proportional hazard model, survival model, water main deterioration, ecological sciences

Procedia PDF Downloads 741

Authors: Zhengrong Wu, Haibo Yang

Abstract:

In the context of escalating global climate change and environmental degradation, the complexity and frequency of natural disasters are continually increasing. Confronted with an abundance of information regarding natural disasters, traditional knowledge graph construction methods, which heavily rely on grammatical rules and prior knowledge, demonstrate suboptimal performance in processing complex, multi-source disaster information. This study, drawing upon past natural disaster reports, disaster-related literature in both English and Chinese, and data from various disaster monitoring stations, constructs question-answer templates based on large language models. Utilizing the P-Tune method, the ChatGLM2-6B model is fine-tuned, leading to the development of a disaster knowledge graph based on large language models. This serves as a knowledge database support for disaster emergency response.

Keywords: large language model, knowledge graph, disaster, deep learning

Procedia PDF Downloads 54

Authors: Anusha Konduru, Zhiyong Shan, Preethi Santhanam, Vinod Namboodiri, Rajiv Bagai

Abstract:

Mobile applications are increasing in a significant amount, each to address the requirements of many users. However, the quick developments and enhancements are resulting in many underlying defects. Android apps create and handle a large variety of 'instance' data that has to persist across runs, such as the current navigation route, workout results, antivirus settings, or game state. Due to the nature of Android, an app can be paused, sent into the background, or killed at any time. If the instance data is not saved and restored between runs, in addition to data loss, partially-saved or corrupted data can crash the app upon resume or restart. However, it is difficult for the programmer to manually test this issue for all the activities. This results in the issue of data loss that the data entered by the user are not saved when there is any interruption. This issue can degrade user experience because the user needs to reenter the information each time there is an interruption. Automated testing to detect such data loss is important to improve the user experience. This research proposes a tool, DroidDL, a data loss detector for Android, which detects the instance data loss from a given android application. We have tested 395 applications and found 12 applications with the issue of data loss. This approach is proved highly accurate and reliable to find the apps with this defect, which can be used by android developers to avoid such errors.

Keywords: Android, automated testing, activity, data loss

Procedia PDF Downloads 237

Authors: T. Ewetumo, K. D. Adedayo, Festus Ben

Abstract:

Knowledge of the thermal properties of foods is of fundamental importance in the food industry to establish the design of processing equipment. However, for tropical fruit juice, there is very little information in literature, seriously hampering processing procedures. This research work describes the development of an instrument for automated thermal conductivity and thermal diffusivity measurement of tropical fruit juice using a transient thermal probe technique based on line heat principle. The system consists of two thermocouple sensors, constant current source, heater, thermocouple amplifier, microcontroller, microSD card shield and intelligent liquid crystal. A fixed distance of 6.50mm was maintained between the two probes. When heat is applied, the temperature rise at the heater probe measured with time at time interval of 4s for 240s. The measuring element conforms as closely as possible to an infinite line source of heat in an infinite fluid. Under these conditions, thermal conductivity and thermal diffusivity are simultaneously measured, with thermal conductivity determined from the slope of a plot of the temperature rise of the heating element against the logarithm of time while thermal diffusivity was determined from the time it took the sample to attain a peak temperature and the time duration over a fixed diffusivity distance. A constant current source was designed to apply a power input of 16.33W/m to the probe throughout the experiment. The thermal probe was interfaced with a digital display and data logger by using an application program written in C++. Calibration of the instrument was done by determining the thermal properties of distilled water. Error due to convection was avoided by adding 1.5% agar to the water. The instrument has been used for measurement of thermal properties of banana, orange and watermelon. Thermal conductivity values of 0.593, 0.598, 0.586 W/m^o C and thermal diffusivity values of 1.053 ×〖10〗^(-7), 1.086 ×〖10〗^(-7), and 0.959 ×〖10〗^(-7) 〖m/s〗^2 were obtained for banana, orange and water melon respectively. Measured values were stored in a microSD card. The instrument performed very well as it measured the thermal conductivity and thermal diffusivity of the tropical fruit juice samples with statistical analysis (ANOVA) showing no significant difference (p>0.05) between the literature standards and estimated averages of each sample investigated with the developed instrument.

Keywords: thermal conductivity, thermal diffusivity, tropical fruit juice, diffusion equation

Procedia PDF Downloads 355