Search results for: prewitt edge detection algorithm

Authors: Srinivasan Chandrasekaran, Manda Hari Venkata Ramachandra Rao

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Increase in the oil and gas exploration in ultra deep-water demands an adaptive structural form of the platform. Triceratops has superior motion characteristics compared to that of the Tension Leg Platform and Single Point Anchor Reservoir platforms, which is well established in the literature. Buoyant legs that support the deck are position-restrained to the sea bed using tethers with high axial pretension. Environmental forces that act on the platform induce dynamic tension variations in the tethers, causing the failure of tethers. The present study investigates the dynamic response behavior of the restraining system of the platform under the failure of a single tether of each buoyant leg in high sea states. Using the rain-flow counting algorithm and the Goodman diagram, fatigue damage caused to the tethers is estimated, and the fatigue life is predicted. Results shows that under failure conditions, the fatigue life of the remaining tethers is quite alarmingly low.

Keywords: fatigue life, pm spectrum, rain flow counting, triceratops, failure analysis

Procedia PDF Downloads 139

Authors: Jeremy Woods, Fanqing Chen

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Rapid genome testing can provide results in at best hours to days, though there are certain clinical decisions that could be guided by genetic test results that need results in hours to minutes. As such, methods of genetic Point of Care Testing (POCT) are required if genetic data is to guide management in illnesses in a wide variety of critical and emergent medical situations such as neonatal sepsis, chemotherapy administration in endometrial cancer, and glucose-6-phosphate dehydrogenase deficiency (G6PD)-associated neonatal hyperbilirubinemia. As such, we developed a POCT “lab-on-chip” technology capable of identifying up to 144 alleles in under an hour. This test required no specialized training to utilize and is suitable to deployment in clinics and hospitals for use by non-laboratory personnel such as nurses. We developed a multiplexed qPCR-based sample-to-answer system with melting curve analysis capable of detecting up to 144 alleles utilizing the Kelliop RapidSeq126 PCR platform combined with a single-use microfluidic cartridge. The RapidSeq126 is the size of a standard desktop printer and the microfluidic cartridges are smaller than a deck of playing cards. Thus the system was deployable in the outpatient setting for clinical trials of MT-RNR1 genotyping. The sample (buccal swab from volunteers or plasmids in media) used for DNA extraction was placed in the cartridge sample inlet prior to inserting the cartridge into the RapidSeq126. The microfluidic cartridge was composed of heat resistant polymer with a sample inlet, 100um conduits, liquid and solid reagents, valves, extraction chamber, lyophilization chamber, 12 PCR reaction chambers, and a waste chamber. No human effort was required for processing the sample and performing the assay other than placing the sample in the cartridge and placing the cartridge in the RapidSeq126. The RapidSeq126 has demonstrated ex vivo detection in plasmids and in vivo detection from human volunteer samples of up to 144 alleles per microfluidic cartridge used and did not require specialized laboratory training to operate. Efficacy was proven for several applications, such as multiple microsatellite instability (MSI) sites (SULF/RYR3/MRE11/ACVR2A/DIDO1/SEC31A/BTBD7), endometrial cancer POLE exonuclease domain (EMD) mutation status, and G6PD variants such as those commonly associated with hemolysis (c.202G>A, c.376A>G, c.680G>A>T, c.968T>C, 404A>C, c.871G>A). The RapidSeq126 system was also able to identify the three MT-RNR1 variants associated with aminoglycoside-induced sensorineural hearing loss (m.1555A>G, m.1095T>C, m.1494C>T). Results were provided in under an hour in a sample-to-answer fashion requiring no processing other than inserting the cartridge with the sample into the RapidSeq126. Results were provided in a digital, HL7-compliant format suitable for interfacing with Electronic Healthcare Record (EHR). The RapidSeq126 system provides a solution for emergency and critical medical situations requiring results in a matter of minutes to hours. The HL7-compliant data format of results enables the RapidSeq126 to interface directly with EHRs to generate best practice advisories and further reduce errors and time to diagnosis by providing digital results.

Keywords: genetic testing, pharmacogenomics, point of care testing, rapid genetic testing

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Authors: Abdolsalam Ghaderi

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In this paper, the single-depot capacitated location-routing problem under uncertainty is presented. The problem aims to find the optimal location of a single depot and the routing of vehicles to serve the customers when the parameters may change under different circumstances. This problem has many applications, especially in the area of supply chain management and distribution systems. To get closer to real-world situations, travel time of vehicles, the fixed cost of vehicles usage and customers’ demand are considered as a source of uncertainty. A combined approach including robust optimization and stochastic programming was presented to deal with the uncertainty in the problem at hand. For this purpose, a mixed integer programming model is developed and a heuristic algorithm based on Variable Neighborhood Search(VNS) is presented to solve the model. Finally, the computational results are presented and future research directions are discussed.

Keywords: location-routing problem, robust optimization, stochastic programming, variable neighborhood search

Procedia PDF Downloads 274

Authors: Zhenyu Zhang, Hsi-Hsien Wei

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Highway network systems play a vital role in disaster response for disaster-damaged areas. Damaged bridges in such network systems can impede disaster response by disrupting transportation of rescue teams or humanitarian supplies. Therefore, emergency inspection and repair of bridges to quickly collect damage information of bridges and recover the functionality of highway networks is of paramount importance to disaster response. A widely used measure of a network’s capability to recover from disasters is resilience. To enhance highway network resilience, plenty of studies have developed various repair scheduling methods for the prioritization of bridge-repair tasks. These methods assume that repair activities are performed after the damage to a highway network is fully understood via inspection, although inspecting all bridges in a regional highway network may take days, leading to the significant delay in repairing bridges. In reality, emergency repair activities can be commenced as soon as the damage data of some bridges that are crucial to emergency response are obtained. Given that emergency bridge inspection and repair (EBIR) activities are executed simultaneously in the response phase, the real-time interactions between these activities can occur – the blockage of highways due to repair activities can affect inspection routes which in turn have an impact on emergency repair scheduling by providing real-time information on bridge damages. However, the impact of such interactions on the optimal emergency inspection routes (EIR) and emergency repair schedules (ERS) has not been discussed in prior studies. To overcome the aforementioned deficiencies, this study develops a routing and scheduling model for EBIR while accounting for real-time inspection-repair interactions to maximize highway network resilience. A stochastic, time-dependent integer program is proposed for the complex and real-time interacting EBIR problem given multiple inspection and repair teams at locations as set post-disaster. A hybrid genetic algorithm that integrates a heuristic approach into a traditional genetic algorithm to accelerate the evolution process is developed. Computational tests are performed using data from the 2008 Wenchuan earthquake, based on a regional highway network in Sichuan, China, consisting of 168 highway bridges on 36 highways connecting 25 cities/towns. The results show that the simultaneous implementation of bridge inspection and repair activities can significantly improve the highway network resilience. Moreover, the deployment of inspection and repair teams should match each other, and the network resilience will not be improved once the unilateral increase in inspection teams or repair teams exceeds a certain level. This study contributes to both knowledge and practice. First, the developed mathematical model makes it possible for capturing the impact of real-time inspection-repair interactions on inspection routing and repair scheduling and efficiently deriving optimal EIR and ERS on a large and complex highway network. Moreover, this study contributes to the organizational dimension of highway network resilience by providing optimal strategies for highway bridge management. With the decision support tool, disaster managers are able to identify the most critical bridges for disaster management and make decisions on proper inspection and repair strategies to improve highway network resilience.

Keywords: disaster management, emergency bridge inspection and repair, highway network, resilience, uncertainty

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Authors: Natalia Wojarnik

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The paper aims to present the analysis of a Reddit confessions corpus. The interpretation focuses on the use of emotional language, in particular emotive verbs, in the context of personal pronouns. The analysis of the linguistic properties answers the question of what the Reddit users confess about and who is the subject of confessions. The study reveals that the specific language patterns used in Reddit confessions reflect the language of depression and the language used by patients during different stages of their psychotherapy sessions. The paper concludes that Reddit users are more willing to confess about their own experiences, not rarely very private and intimate, extensively using the first person singular pronoun I. It indicates that the Reddit users use the language of depression and the language used by psychotherapy patients. The language they use is very emotionally impacted and includes many emotive verbs such as want, feel, need, hate, love. This finding in Reddit confessions correlates with the extensive use of stative affective verbs in the first stages of the psychotherapy sessions. Lastly, the paper refers to the positive and negative lexicon and helps determine how online posts can serve as a depression detector and “talking cure” for the users.

Keywords: confessions, emotional language, emotive verbs, pronouns, first person pronoun, language of depression, depression detection, psychotherapy language

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Authors: C. N. Vanitha, M. Usha

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In a real world scenario, the viability of the sensor networks has been proved by standardizing the technologies. Wireless sensor networks are vulnerable to both electronic and physical security breaches because of their deployment in remote, distributed, and inaccessible locations. The compromised sensor nodes send malicious data to the base station, and thus, the total network effectiveness will possibly be compromised. To detect and seclude the Route modifiers, a neural network based Pattern Learning predictor (PLP) is presented. This algorithm senses data at any node on present and previous patterns obtained from the en-route nodes. The eminence of any node is upgraded by their predicted and reported patterns. This paper propounds a solution not only to detect the route modifiers, but also to seclude the malevolent nodes from the network. The simulation result proves the effective performance of the network by the presented methodology in terms of energy level, routing and various network conditions.

Keywords: neural networks, pattern learning, security, wireless sensor networks

Procedia PDF Downloads 408

Authors: J. Al-Dmour, A. Sagahyroon, A. Al-Ali, S. Abusnana

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Radio Frequency Based Identification Systems have emerged as one of the possible valuable solutions that can be utilized in healthcare systems. Nowadays, RFID tags are available with built-in human vital signs sensors such as Body Temperature, Blood Pressure, Heart Rate, Blood Sugar level and Oxygen Saturation in Blood. This work proposes the design, implementation, and testing of an integrated mobile RFID-based health care system. The system consists of a wireless mobile vital signs data acquisition unit (RFID-DAQ) integrated with a fuzzy-logic–based software algorithm to monitor and assess patients conditions. The system is implemented and tested in ‘Rashid Center for Diabetes and Research’, Ajman, UAE. System testing results are compared with the Modified Early Warning System (MEWS) that is currently used in practice. We demonstrate that the proposed and implemented system exhibits an accuracy level that is comparable and sometimes better than the widely adopted MEWS system.

Keywords: healthcare, fuzzy logic, MEWS, RFID

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Authors: Rahmat Purwoko, Bambang Riyanto Trilaksono

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This paper gives comparison of INS/GNSS architecture namely Loosely Coupled and Tightly Coupled using Hardware in the Loop Simulation in Guided Missile RKX-200 rocket model. INS/GNSS Tightly Coupled architecture requires pseudo-range, pseudo-range rate, and position and velocity of each satellite in constellation from GPS (Global Positioning System) measurement. The Loosely Coupled architecture use estimated position and velocity from GNSS receiver. INS/GNSS architecture also requires angular rate and specific force measurement from IMU (Inertial Measurement Unit). Loosely Coupled arhitecture designed using 15 states Kalman Filter and Tightly Coupled designed using 17 states Kalman Filter. Integration algorithm calculation using ECEF frame. Navigation System implemented Zedboard All Programmable SoC.

Keywords: kalman filter, loosely coupled, navigation system, tightly coupled

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Authors: Isil Gazioglu, Abdulselam Ertas

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Aflatoxins (AFs) are secondary toxic metabolites of Aspergillus flavus and A. parasiticus. AFs can be absorbed through the skin. Potent carcinogens like AFs should be completely absent from cosmetics, this can be achieved by careful quality control of the raw plant materials. Regulatory limits for aflatoxins have been established in many countries, and reliable testing methodology is needed to implement and enforce the regulatory limits. In this study, ten medicinal plant samples (Bundelia tournefortti, Capsella bursa-pastoris, Carduus tenuiflorus, Cardaria draba, Malva neglecta, Malvella sharardiana, Melissa officinalis, Sideritis libanotica, Stakys thirkei, Thymus nummularius) were investigated for aflatoxin (AF) contaminations by employing an HPLC assay for the determination of AFB1, B2, G1 and G2. The samples were extracted with 70% (v/v) methanol in water before further cleaned up with an immunoaffinity column and followed by the detection of AFs by using an electrochemically post-column derivatization with Kobra-Cell and fluorescence detector. The extraction procedure was optimized in order to obtain the best recovery. The method was successfully carried out with all medicinal plant samples. The results revealed that five (50%) of samples were contaminated with AFs. The association between particular samples and the AF contaminated could not be determined due to the low frequency of positive samples.

Keywords: aflatoxin B1, HPLC-FLD, KOBRA-Cell, mycotoxin

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Authors: Md. Baki Billah, Suraiya Parveen, Shuvra Kanti Dey

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Bangladesh is earning a lot of foreign currency by exporting shrimp, but this industry is facing a tremendous problem due to the infection of white spot syndrome virus (WSSV). This study was undermined to develop rapid detection method of WSSV. A total of shrimp samples 240 collected from the 12 shrimp farms of different coastal regions (Satkhira, Khulna, and Bagerhat) were analyzed by conventional PCR using VP28 and VP664 gene-specific primers. In satkhira, Bagerhat and Khulna 39, 41 and 29 samples were found WSSV positive respectively. Real-time PCR using 71-bp amplicon for VP664 gene correlated well with conventional PCR data. The prevalence rates of WSSV among the collected 240 samples were Satkhira 38%, Khulna 47% and Bagerhat 50%. Molecular analysis of the VP28 gene sequences of WSSV revealed that Bangladeshi strains phylogenetically affiliated to the strains belong to India. This work concluded that WSSV infections are widely distributed in the coastal regions cultured shrimp in Bangladesh. Physico-chemical parameters were within the range of fish culture.

Keywords: coastal regions of Bangladesh, PCR, shrimp, white spot syndrome virus

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Authors: Xiuying Wang, Changliang Li, Bo Xu

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A fixed-length feature vector is required for many machine learning algorithms in NLP field. Word embeddings have been very successful at learning lexical information. However, they cannot capture the compositional meaning of sentences, which prevents them from a deeper understanding of language. In this paper, we introduce a novel hierarchical tree long short-term memory (HTLSTM) model that learns vector representations for sentences of arbitrary syntactic type and length. We propose to split one sentence into three hierarchies: short phrase, long phrase and full sentence level. The HTLSTM model gives our algorithm the potential to fully consider the hierarchical information and long-term dependencies of language. We design the experiments on both English and Chinese corpus to evaluate our model on sentiment analysis task. And the results show that our model outperforms several existing state of the art approaches significantly.

Keywords: deep learning, hierarchical tree long short-term memory, sentence representation, sentiment analysis

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Authors: Shih-Wen Hsiao, Chu-Hsuan Lee, Rong-Qi Chen

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When it comes to last, it is regarded as the critical foundation of shoe design and development. Not only the last relates to the comfort of shoes wearing but also it aids the production of shoe styling and manufacturing. In order to enhance the efficiency and application of last development, a computer aided methodology for customized last form designs is proposed in this study. The reverse engineering is mainly applied to the process of scanning for the last form. Then the minimum energy is used for the revision of surface continuity, the surface of the last is reconstructed with the feature curves of the scanned last. When the surface of a last is reconstructed, based on the foundation of the proposed last form reconstruction module, the weighted arithmetic mean method is applied to the calculation on the shape morphing which differs from the grading for the control mesh of last, and the algorithm of subdivision is used to create the surface of last mesh, thus the feet-fitting 3D last form of different sizes is generated from its original form feature with functions remained. Finally, the practicability of the proposed methodology is verified through later case studies.

Keywords: 3D last design, customization, reverse engineering, weighted morphing, shape blending

Procedia PDF Downloads 342

Authors: Misrak Assefa

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The Amharic language is the second most widely spoken Semitic language in the world. There are several new overloaded on the web. Searching some useful documents from the web on a specific topic, which is written in the Amharic language, is a challenging task. Hence, document categorization is required for managing and filtering important information. In the classification of Amharic text news, there is still a gap in the domain of information that needs to be launch. This study attempts to design an automatic Amharic news classification using a supervised learning mechanism on four un-touch classes. To achieve this research, 4,182 news articles were used. Naive Bayes (NB) and Decision tree (j48) algorithms were used to classify the given Amharic dataset. In this paper, k-fold cross-validation is used to estimate the accuracy of the classifier. As a result, it shows those algorithms can be applicable in Amharic news categorization. The best average accuracy result is achieved by j48 decision tree and naïve Bayes is 95.2345 %, and 94.6245 % respectively using three categories. This research indicated that a typical decision tree algorithm is more applicable to Amharic news categorization.

Keywords: text categorization, supervised machine learning, naive Bayes, decision tree

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Authors: Sandhya Baskaran, Hari Kumar Nagabushanam

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Sarcasm sentiment recognition is an area of natural language processing that is being probed into in the recent times. Even with the advancements in NLP, typical translations of words, sentences in its context fail to provide the exact information on a sentiment or emotion of a user. For example, if something bad happens, the statement ‘That's just what I need, great! Terrific!’ is expressed in a sarcastic tone which could be misread as a positive sign by any text-based analyzer. In this paper, we are presenting a unique real time ‘word with its tone’ spotting technique which would provide the sentiment analysis for a tone or pitch of a voice in combination with the words being expressed. This hybrid approach increases the probability for identification of special sentiment like sarcasm much closer to the real world than by mining text or speech individually. The system uses a tone analyzer such as YIN-FFT which extracts pitch segment-wise that would be used in parallel with a speech recognition system. The clustered data is classified for sentiments and sarcasm score for each of it determined. Our Simulations demonstrates the improvement in f-measure of around 12% compared to existing detection techniques with increased precision and recall.

Keywords: sarcasm recognition, tone-word spotting, natural language processing, pitch analyzer

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Authors: Daniel C. Bonzo

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Practical considerations lead to the use of unit of analysis within subjects, e.g., bleeding episodes or treatment-related adverse events, in rare disease settings. This is coupled with data augmentation techniques such as extrapolation to enlarge the subject base. In general, one can think about extrapolation of data as extending information and conclusions from one estimand to another estimand. This approach induces hierarchichal clustered data with varying cluster sizes. Extrapolation of clinical trial data is being accepted increasingly by regulatory agencies as a means of generating data in diverse situations during drug development process. Under certain circumstances, data can be extrapolated to a different population, a different but related indication, and different but similar product. We consider here the problem of estimation (point and interval) using a mixed-models approach under an extrapolation. It is proposed that estimators (point and interval) be constructed using weighting schemes for the clusters, e.g., equally weighted and with weights proportional to cluster size. Simulated data generated under varying scenarios are then used to evaluate the performance of this approach. In conclusion, the evaluation result showed that the approach is a useful means for improving statistical inference in rare disease settings and thus aids not only signal detection but risk-benefit evaluation as well.

Keywords: clustered data, estimand, extrapolation, mixed model

Procedia PDF Downloads 140

Authors: Antonio Boggia, Luisa Paolotti, Gianluca Massei, Lucia Rocchi, Elaine Pace, Maria Attard

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The aim of this paper is to present a methodology and a computer model for sustainability assessment based on the integration of Multi-criteria Decision Analysis (MCDA) with a Geographic Information System (GIS). It presents the result of a study for the implementation of a model for measuring sustainability to address the policy actions for the improvement of sustainability at territory level. The aim is to rank areas in order to understand the specific technical and/or financial support that is required to develop sustainable growth. Assessing sustainable development is a multidimensional problem: economic, social and environmental aspects have to be taken into account at the same time. The tool for a multidimensional representation is a proper set of indicators. The set of indicators must be integrated into a model, that is an assessment methodology, to be used for measuring sustainability. The model, developed by the Environmental Laboratory of the University of Perugia, is called GeoUmbriaSUIT. It is a calculation procedure developed as a plugin working in the open-source GIS software QuantumGIS. The multi-criteria method used within GeoUmbriaSUIT is the algorithm TOPSIS (Technique for Order Preference by Similarity to Ideal Design), which defines a ranking based on the distance from the worst point and the closeness to an ideal point, for each of the criteria used. For the sustainability assessment procedure, GeoUmbriaSUIT uses a geographic vector file where the graphic data represent the study area and the single evaluation units within it (the alternatives, e.g. the regions of a country, or the municipalities of a region), while the alphanumeric data (attribute table), describe the environmental, economic and social aspects related to the evaluation units by means of a set of indicators (criteria). The use of the algorithm available in the plugin allows to treat individually the indicators representing the three dimensions of sustainability, and to compute three different indices: environmental index, economic index and social index. The graphic output of the model allows for an integrated assessment of the three dimensions, avoiding aggregation. The presence of separate indices and graphic output make GeoUmbriaSUIT a readable and transparent tool, since it doesn’t produce an aggregate index of sustainability as final result of the calculations, which is often cryptic and difficult to interpret. In addition, it is possible to develop a “back analysis”, able to explain the positions obtained by the alternatives in the ranking, based on the criteria used. The case study presented is an assessment of the level of sustainability in the six regions of Malta, an island state in the middle of the Mediterranean Sea and the southernmost member of the European Union. The results show that the integration of MCDA-GIS is an adequate approach for sustainability assessment. In particular, the implemented model is able to provide easy to understand results. This is a very important condition for a sound decision support tool, since most of the time decision makers are not experts and need understandable output. In addition, the evaluation path is traceable and transparent.

Keywords: GIS, multi-criteria analysis, sustainability assessment, sustainable development

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Authors: Hsin-Yang Wang, K. M. A. Salam, Ying-Jia Lin, Daniel Tan, Tzu-Hsuan Chou, Hung-Yu Kao

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Detecting user intent from natural language expression has a wide variety of use cases in different natural language processing applications. Recently few-shot training has a spike of usage on commercial domains. Due to the lack of significant sample features, the downstream task performance has been limited or leads to an unstable result across different domains. As a state-of-the-art method, the pre-trained BERT model gathering the sentence-level information from a large text corpus shows improvement on several NLP benchmarks. In this research, we are proposing a method to change multi-class classification tasks into binary classification tasks, then use the confidence score to rank the results. As a language model, BERT performs well on sequence data. In our experiment, we change the objective from predicting labels into finding the relations between words in sequence data. Our proposed method achieved 71.0% accuracy in the internal intent detection dataset and 63.9% accuracy in the HuffPost dataset. Acknowledgment: This work was supported by NCKU-B109-K003, which is the collaboration between National Cheng Kung University, Taiwan, and SoftBank Corp., Tokyo.

Keywords: OSML, BERT, text classification, one shot

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Authors: Li Long, Thomas Ortlepp

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A theoretical model for the optimization of thermopile sensor performance is developed for thermoelectric-based infrared radiation detection. It is shown that the performance of polycrystalline silicon film thermopile sensor can be optimized according to the thermoelectric quality factor, sensor layer structure factor, and sensor layout geometrical form factor. Based on the properties of electrons, phonons, grain boundaries, and their interactions, the thermoelectric quality factor of polycrystalline silicon is analyzed with the relaxation time approximation of the Boltzmann transport equation. The model includes the effect of grain structure, grain boundary trap properties, and doping concentration. The layer structure factor is analyzed with respect to the infrared absorption coefficient. The optimization of layout design is characterized by the form factor, which is calculated for different sensor designs. A double-layer polycrystalline silicon thermopile infrared sensor on a suspended membrane has been designed and fabricated with a CMOS-compatible process. The theoretical approach is confirmed by measurement results.

Keywords: polycrystalline silicon, relaxation time approximation, specific detectivity, thermal conductivity, thermopile infrared sensor

Procedia PDF Downloads 149

Authors: Dan Kanmegne

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Africa will become the most populated continent by the end of the century, with around 4 billion inhabitants. Food security and climate changes will become continental issues since agricultural practices depend on climate but also contribute to global emissions and land degradation. Agroforestry has been identified as a cost-efficient and reliable strategy to address these two issues. It is defined as the integrated management of trees and crops/animals in the same land unit. Agroforestry provides benefits in terms of goods (fruits, medicine, wood, etc.) and services (windbreaks, fertility, etc.), and is acknowledged to have a great potential for carbon sequestration; therefore it can be integrated into reduction mechanisms of carbon emissions. Particularly in sub-Saharan Africa, the constraint stands in the lack of information about both areas under agroforestry and the characterization (composition, structure, and management) of each agroforestry system at the country level. This study describes and quantifies “what is where?”, earliest to the quantification of carbon stock in different systems. Remote sensing (RS) is the most efficient approach to map such a dynamic technology as agroforestry since it gives relatively adequate and consistent information over a large area at nearly no cost. RS data fulfill the good practice guidelines of the Intergovernmental Panel On Climate Change (IPCC) that is to be used in carbon estimation. Satellite data are getting more and more accessible, and the archives are growing exponentially. To retrieve useful information to support decision-making out of this large amount of data, satellite data needs to be organized so to ensure fast processing, quick accessibility, and ease of use. A new solution is a data cube, which can be understood as a multi-dimensional stack (space, time, data type) of spatially aligned pixels and used for efficient access and analysis. A data cube for Burkina Faso has been set up from the cooperation project between the international service provider WASCAL and Germany, which provides an accessible exploitation architecture of multi-temporal satellite data. The aim of this study is to map and characterize agroforestry systems using the Burkina Faso earth observation data cube. The approach in its initial stage is based on an unsupervised image classification of a normalized difference vegetation index (NDVI) time series from 2010 to 2018, to stratify the country based on the vegetation. Fifteen strata were identified, and four samples per location were randomly assigned to define the sampling units. For safety reasons, the northern part will not be part of the fieldwork. A total of 52 locations will be visited by the end of the dry season in February-March 2020. The field campaigns will consist of identifying and describing different agroforestry systems and qualitative interviews. A multi-temporal supervised image classification will be done with a random forest algorithm, and the field data will be used for both training the algorithm and accuracy assessment. The expected outputs are (i) map(s) of agroforestry dynamics, (ii) characteristics of different systems (main species, management, area, etc.); (iii) assessment report of Burkina Faso data cube.

Keywords: agroforestry systems, Burkina Faso, earth observation data cube, multi-temporal image classification

Procedia PDF Downloads 152

Authors: Olukayode Bamgbose, Feyisola Agboola, Adewale M. Taiwo, Olanrewaju Olujimi Oluwole Terebo, Azeez Soyingbe, Akeem Bamgbade

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The present study evaluated the contents and health risk assessment of metals determined in milk and milk product samples collected from the Abeokuta market. Forty-five milk and milk product (yoghurt) samples were digested and analysed for selected metals using Atomic Absorption Spectrophotometric method. Health risk assessment was evaluated for hazard quotient (HQ), hazard index (HI), and cancer risk (CR). Data were subjected to descriptive and inferential statistics. The concentrations of Zn, which ranged from 3.24±0.59 to 4.35±0.59 mg/kg, were the highest in the samples. Cr and Cd were measured below the detection limit of the analytical instrument, while the Pb level was higher than the Codex Alimentarius Commission value of 0.02 mg/kg, indicating unsafe for consumption. However, the HQ of Pb and other metals in milk and milk product samples was less than 1.0, thereby establishing no adverse health effects for Pb and other metals. The distribution pattern of metals in milk and milk product samples followed the decreasing order of Zn > Fe > Ni > Co > Cu > Mn > Pb > Cd/Cr. The CR levels of meals were also less than the permissible limit of 1.0 x 10-4, establishing no possible development of cancer. Keywords: adverse effects, cancer, metals, milk, milk product, the permissible limit.

Keywords: adverse effects, cancer, metals, milk, milk product, permissible limit

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Authors: H. Feza Carlak, N. G. Gencer

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To increase the temperature contrast in thermal images, the characteristics of the electrical conductivity and thermal imaging modalities can be combined. In this experimental study, it is objected to observe whether the temperature contrast created by the tumor tissue can be improved just due to the current application within medical safety limits. Various thermal breast phantoms are developed to simulate the female breast tissue. In vitro experiments are implemented using a thermal infrared camera in a controlled manner. Since experiments are implemented in vitro, there is no metabolic heat generation and blood perfusion. Only the effects and results of the electrical stimulation are investigated. Experimental study is implemented with two-dimensional models. Temperature contrasts due to the tumor tissues are obtained. Cancerous tissue is determined using the difference and ratio of healthy and tumor images. 1 cm diameter single tumor tissue causes almost 40 °mC temperature contrast on the thermal-breast phantom. Electrode artifacts are reduced by taking the difference and ratio of background (healthy) and tumor images. Ratio of healthy and tumor images show that temperature contrast is increased by the current application.

Keywords: medical diagnostic imaging, breast phantom, active thermography, breast cancer detection

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Authors: Mayank Gupta, Siba Prasad Samal, Vasu Kakkirala

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The internet world and its priorities have changed considerably in the last decade. Browsing on smart phones has increased manifold and is set to explode much more. Users spent considerable time browsing different websites, that gives a great deal of insight into user’s preferences. Instead of plain information classifying different aspects of browsing like Bookmarks, History, and Download Manager into useful categories would improve and enhance the user’s experience. Most of the classification solutions are server side that involves maintaining server and other heavy resources. It has security constraints and maybe misses on contextual data during classification. On device, classification solves many such problems, but the challenge is to achieve accuracy on classification with resource constraints. This on device classification can be much more useful in personalization, reducing dependency on cloud connectivity and better privacy/security. This approach provides more relevant results as compared to current standalone solutions because it uses content rendered by browser which is customized by the content provider based on user’s profile. This paper proposes a Naive Bayes based lightweight classification engine targeted for a resource constraint devices. Our solution integrates with Web Browser that in turn triggers classification algorithm. Whenever a user browses a webpage, this solution extracts DOM Tree data from the browser’s rendering engine. This DOM data is a dynamic, contextual and secure data that can’t be replicated. This proposal extracts different features of the webpage that runs on an algorithm to classify into multiple categories. Naive Bayes based engine is chosen in this solution for its inherent advantages in using limited resources compared to other classification algorithms like Support Vector Machine, Neural Networks, etc. Naive Bayes classification requires small memory footprint and less computation suitable for smartphone environment. This solution has a feature to partition the model into multiple chunks that in turn will facilitate less usage of memory instead of loading a complete model. Classification of the webpages done through integrated engine is faster, more relevant and energy efficient than other standalone on device solution. This classification engine has been tested on Samsung Z3 Tizen hardware. The Engine is integrated into Tizen Browser that uses Chromium Rendering Engine. For this solution, extensive dataset is sourced from dmoztools.net and cleaned. This cleaned dataset has 227.5K webpages which are divided into 8 generic categories ('education', 'games', 'health', 'entertainment', 'news', 'shopping', 'sports', 'travel'). Our browser integrated solution has resulted in 15% less memory usage (due to partition method) and 24% less power consumption in comparison with standalone solution. This solution considered 70% of the dataset for training the data model and the rest 30% dataset for testing. An average accuracy of ~96.3% is achieved across the above mentioned 8 categories. This engine can be further extended for suggesting Dynamic tags and using the classification for differential uses cases to enhance browsing experience.

Keywords: chromium, lightweight engine, mobile computing, Naive Bayes, Tizen, web browser, webpage classification

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Authors: P. D. Pastuszak

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The present work is devoted to thermographic studies of curved composite panels (unidirectional GFRP) with subsurface defects. Various artificial defects, created by inserting PTFE stripe between individual layers of a laminate during manufacturing stage are studied. The analysis is conducted both with the use finite element method and experiments. To simulate transient heat transfer in 3D model with embedded various defect sizes, the ANSYS package is used. Pulsed Thermography combined with optical excitation source provides good results for flat surfaces. Composite structures are mostly used in complex components, e.g., pipes, corners and stiffeners. Local decrease of mechanical properties in these regions can have significant influence on strength decrease of the entire structure. Application of active procedures of thermography to defect detection and evaluation in this type of elements seems to be more appropriate that other NDT techniques. Nevertheless, there are various uncertainties connected with correct interpretation of acquired data. In this paper, important factors concerning Infrared Thermography measurements of curved surfaces in the form of cylindrical panels are considered. In addition, temperature effects on the surface resulting from complex geometry and embedded and real defect are also presented.

Keywords: active thermography, composite, curved structures, defects

Procedia PDF Downloads 323

Authors: Eunseop Yeom

Abstract:

Platelets can be activated by the surrounding blood flows where a blood vessel is narrowed as a result of atherosclerosis. Numerous studies have been conducted to identify the relation between platelets activation and thrombus formation. To measure platelet adhesion, this study proposes an image analysis technique. Blood samples are delivered in the microfluidic channel, and then platelets are activated by a stenotic micro-channel with 90% severity. By applying proposed correlation mapping, which visualizes decorrelation of the streaming blood flow, the area of adhered platelets (APlatelet) was estimated without labeling platelets. In order to evaluate the performance of correlation mapping on the detection of platelet adhesion, the effect of tile size was investigated by calculating 2D correlation coefficients with binary images obtained by manual labeling and the correlation mapping method with different sizes of the square tile ranging from 3 to 50 pixels. The maximum 2D correlation coefficient is observed with the optimum tile size of 5×5 pixels. As the area of the platelet adhesion increases, the platelets plug the channel and there is only a small amount of blood flows. This image analysis could provide new insights for better understanding of the interactions between platelet aggregation and blood flows in various physiological conditions.

Keywords: platelet activation, correlation coefficient, image analysis, shear rate

Procedia PDF Downloads 338

Authors: J. van Soest, B. Bruneel, J. Smit, N. Williams, P. Swiegers

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Selenium (Se) is an essential trace mineral involved in reducing oxidative stress, enhancing immune status, improving reproduction, and regulating growth. During finishing period, selenium supplementation can be applied to improve meat quality. Dietary selenium can be provided in inorganic or organic forms. Specifically, L-selenomethionine (organic selenium) allows for selenium storage in animal protein which supports the animal during periods of high oxidative stress. The objective of this study was to investigate the effects of synthetically produced, single amino acid, L-selenomethionine (Excential Selenium 4000, Orffa Additives BV) on production parameters, health status, and meat quality of Bonsmara bull calves. 24 calves, 7 months of age, completed a 60-day initial growing period at a commercial feedlot, after which they were transported to research station Rumen-8 (Bethlehem, South-Africa). After a ten-day adaptation period, the bulls were allocated to a control (n=12) or treatment (n=12) group. Each group was divided over 3 pens based on weight. Both groups received Total Mixed Ration supplemented with 5.25 mg Se/head per day. The control group was supplemented with sodium selenite as Se source, whilst the treatment group was supplemented with L-selenomethionine (Excential Selenium 4000, Orffa Additives BV). Animals were limited to 10 kg feed intake per head per day to ensure similar Se intake. Treatment period lasted 1.5 months. A beta-adrenergic agonist was included in the feed for the last 30 days. During the treatment period, average daily gain, average daily feed intake, and feed conversion ratio were recorded. Blood parameters were measured at day 1, day 25, and before slaughter (day 47). After slaughter, carcass weight, dressing percentage, grading, and meat quality (pH, tenderness, colour, odour, purge, proximate analyses, acid detergent fibre, and neutral detergent fibre) were determined. No differences between groups were found in performance. A higher number of animals with cortisol levels below detection limit (27.6 nmol/l) was recorded for the treatment group. Other blood parameters showed no differences. No differences were found regarding carcass weight and dressing percentage. Important parameters of meat quality were significantly improved in the treatment group: instrumental tenderness at 14 days ageing was 2.8 and 3.4 for treatment and control respectively (P=0.010), and a 0.5% decrease in purge (of fresh samples) was shown, 1.5% and 2.0% for treatment group and control respectively (p=0.029). Besides, pH was shown to be numerically reduced in the treatment group. In summary, supplementation with L-selenomethionine as selenium source improved meat quality compared to sodium selenite. Lower instrumental tenderness (Warner Bratzler Shear Force, WBSF) was recorded for the treatment group. This indicates less tough meat and highest consumer satisfaction. Regarding purge, control was just below 2.0%, an important threshold for consumer acceptation. Treatment group scored 0.5% lower for purge than control, indicating higher consumer satisfaction. The lower pH in the treatment group could be an indication of higher glycogen reserves in muscle which could contribute to a reduced risk of Dark Firm Dry carcasses. More animals showed cortisol levels below detection limit in the treatment group, indicating lower levels of stress when animals receive L-selenomethionine.

Keywords: calves, meat quality, nutrition, selenium

Procedia PDF Downloads 188

Authors: Nizar Karim Uribe-Orihuela, Fernando Brambila-Paz, Ivette Caldelas, Rodrigo Montufar-Chaveznava

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In this paper, we present the advances corresponding to the implementation of a strategy to visualize geographical data using a Software Development Kit (SDK) for video games. We use multispectral images from Landsat 7 platform and Laser Imaging Detection and Ranging (LIDAR) data from The National Institute of Geography and Statistics of Mexican (INEGI). We select a place of interest to visualize from Landsat platform and make some processing to the image (rotations, atmospheric correction and enhancement). The resulting image will be our gray scale color-map to fusion with the LIDAR data, which was selected using the same coordinates than in Landsat. The LIDAR data is translated to 8-bit raw data. Both images are fused in a software developed using Unity (an SDK employed for video games). The resulting image is then displayed and can be explored moving around. The idea is the software could be used for students of geology and geophysics at the Engineering School of the National University of Mexico. They will download the software and images corresponding to a geological place of interest to a smartphone and could virtually visit and explore the site with a virtual reality visor such as Google cardboard.

Keywords: virtual reality, interactive technologies, geographical data visualization, video games technologies, educational material

Procedia PDF Downloads 249

Authors: E. Irankhah, M. Zarif, E. Mazrooei Rad, K. Ghandehari

Abstract:

Alzheimer's prevalence is on the rise, and the disease comes with problems like cessation of treatment, high cost of treatment, and the lack of early detection methods. The pathology of this disease causes the formation of protein deposits in the brain of patients called plaque amyloid. Generally, the diagnosis of this disease is done by performing tests such as a cerebrospinal fluid, CT scan, MRI, and spinal cord fluid testing, or mental testing tests and eye tracing tests. In this paper, we tried to use the Medial Temporal Atrophy (MTA) method and the Leave One Out (LOO) cycle to extract the statistical properties of the three Fz, Pz, and Cz channels of ERP signals for early diagnosis of this disease. In the process of CT scan images, the accuracy of the results is 81% for the healthy person and 88% for the severe patient. After the process of ERP signaling, the accuracy of the results for a healthy person in the delta band in the Cz channel is 81% and in the alpha band the Pz channel is 90%. In the results obtained from the signal processing, the results of the severe patient in the delta band of the Cz channel were 89% and in the alpha band Pz channel 92%.

Keywords: Alzheimer's disease, image and signal processing, LOO cycle, medial temporal atrophy

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Authors: Simon B. N. Thompson

Abstract:

Cortisol is essential to the regulation of the immune system and yawning is a pathological symptom of multiple sclerosis (MS). Electromyography activity (EMG) in the jaw muscles typically rises when the muscles are moved and with yawning is highly correlated with cortisol levels in healthy people. Saliva samples from 59 participants were collected at the start and after yawning, or at the end of the presentation of yawning-provoking stimuli, in the absence of a yawn, together with EMG data and questionnaire data: Hospital Anxiety and Depression Scale, Yawning Susceptibility Scale, General Health Questionnaire, demographic, health details. Exclusion criteria: chronic fatigue, diabetes, fibromyalgia, heart condition, high blood pressure, hormone replacement therapy, multiple sclerosis, stroke. Significant differences were found between the saliva cortisol samples for the yawners, t (23) = -4.263, p = 0.000, as compared with the non-yawners between rest and post-stimuli, which was non-significant. Significant evidence was found to support the Thompson Cortisol Hypothesis suggesting that rises in cortisol levels are associated with yawning. Further research is exploring the use of cortisol as an early diagnostic tool for MS. Ethics approval granted and professional code of conduct, confidentiality, and safety issues are approved therein.

Keywords: cortisol, multiple sclerosis, yawning, thompson cortisol hypothesis

Procedia PDF Downloads 379

Authors: Raja Chinnappan, Huda Alanazi, Shanmugam Easwaramoorthi, Tanveer Mir, Balamurugan Kanagasabai, Ahmed Yaqinuddin, Sandhanasamy Devanesan, Mohamad S. AlSalhi

Abstract:

Serum albumin (SA) is a highly rich water-soluble protein in plasma. It is known to maintain the living organisms' health and help to maintain the proper liver function, kidney function, and plasma osmolality in the body. Low levels of serum albumin are an indication of liver failure and chronic hepatitis. Therefore, it is important to have a low-cost, accurate and rapid method. In this study, we designed a fluorescent probe, triphenylamine rhodanine-3-acetic acid (mRA), which triggers the fluorescence signal upon binding with serum albumin (SA). mRA is a bifunctional molecule with twisted intramolecular charge transfer (TICT)-induced emission characteristics. An aqueous solution of mRA has an insignificant fluorescence signal; however, when mRA binds to SA, it undergoes TICT and turns on the fluorescence emission. A SA dose-dependent fluorescence signal was performed, and the limit of detection was found to be less than ng/mL. The specific binding of SA was tested from the cross-reactivity study using similar structural or functional proteins.

Keywords: serum albumin, fluorescent sensing probe, liver diseases, twisted intramolecular charge transfer

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Authors: K. Ali, M. F. Qamar, M. A. Zaman, M. Younus, I. Khan, S. Ehtisham-ul-Haque, R. Tamkeen, M. I. Rashid, Q. Ali

Abstract:

This study centers on molecular identification of Haemonchus contortus and isolation of Benz-imidazoles (BZ) resistant strains. Different abattoirs’ of two geographic regions of Punjab (Pakistan) were frequently visited for the collection of worms. Out of 1500 (n=1500) samples that were morphologically confirmed as H. contortus, 30 worms were subjected to molecular procedures for isolation of resistant strains. Resistant worms (n=8) were further subjected to DNA gene sequencing. Bio edit sequence alignment editor software was used to detect the possible mutation, deletion, replacement of nucleotides. Genetic diversity was noticed and genetic variation existing in β-tubulin isotype 1 of the H. contortus population of small ruminants of different regions considered in this study. H. contortus showed three different type of genetic sequences. 75%, 37.5%, 25% and 12.5% of the studied samples showed 100% query cover and identity with isolates and clones of China, UK, Australia and other countries, respectively. Interestingly the neighbor countries such as India and Iran haven’t many similarities with the Pakistani isolates. Thus, it suggests that population density of same genetic makeup H. contortus is scattered worldwide rather than clustering in a single region.

Keywords: Haemonchus contortus, Benzimidazole resistant, β-tubulin-1 gene, abattoirs

Procedia PDF Downloads 179