Search results for: preposition error detection

Authors: Peifei Zhu, Zisheng Li, Yasuki Kakishita, Mayumi Suzuki, Tomoaki Chono

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Segmentation of left ventricle (LV) from cardiac ultrasound images provides a quantitative functional analysis of the heart to diagnose disease. Active Shape Model (ASM) is a widely used approach for LV segmentation but suffers from the drawback that initialization of the shape model is not sufficiently close to the target, especially when dealing with abnormal shapes in disease. In this work, a two-step framework is proposed to improve the accuracy and speed of the model-based segmentation. Firstly, a robust and efficient detector based on Hough forest is proposed to localize cardiac feature points, and such points are used to predict the initial fitting of the LV shape model. Secondly, to achieve more accurate and detailed segmentation, ASM is applied to further fit the LV shape model to the cardiac ultrasound image. The performance of the proposed method is evaluated on a dataset of 800 cardiac ultrasound images that are mostly of abnormal shapes. The proposed method is compared to several combinations of ASM and existing initialization methods. The experiment results demonstrate that the accuracy of feature point detection for initialization was improved by 40% compared to the existing methods. Moreover, the proposed method significantly reduces the number of necessary ASM fitting loops, thus speeding up the whole segmentation process. Therefore, the proposed method is able to achieve more accurate and efficient segmentation results and is applicable to unusual shapes of heart with cardiac diseases, such as left atrial enlargement.

Keywords: hough forest, active shape model, segmentation, cardiac left ventricle

Procedia PDF Downloads 333

Authors: Catalina Albornoz, Giacomo Barbieri

Abstract:

Crop monitoring has shown to reduce vulnerability to spreading plagues and pathologies in crops. Remote sensing with Unmanned Aerial Vehicles (UAVs) has made crop monitoring more precise, cost-efficient and accessible. Nowadays, remote monitoring involves calculating maps of vegetation indices by using different software that takes either Truecolor (RGB) or multispectral images as an input. These maps are then used to segment the crop into management zones. Finally, knowing the spectral signature of a crop (the reflected radiation as a function of wavelength) can be used as an input for decision-making and crop characterization. The calculation of vegetation indices using software such as Pix4D has high precision for monoculture plantations. However, this paper shows that using this software on mixed crops may lead to errors resulting in an incorrect segmentation of the field. Within this work, authors propose to filter all the elements different from the main crop before the calculation of vegetation indices and the spectral signature. A filter based on the Sobel method for border detection is used for filtering a coffee crop. Results show that segmentation into management zones changes with respect to the traditional situation in which a filter is not applied. In particular, it is shown how the values of the spectral signature change in up to 17% per spectral band. Future work will quantify the benefits of filtering through the comparison between in situ measurements and the calculated vegetation indices obtained through remote sensing.

Keywords: coffee, filtering, mixed crop, precision agriculture, remote sensing, spectral signature

Procedia PDF Downloads 380

Authors: Muhammad Fiaz Qamar, Ahmad Faraz, Muhammad Arfan Zaman, Kazim Ali, Waleed Akram

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Babesiosis is reflected as the most important disease of cattle that are transmitted by arthropods. In Pakistan, its prevalence is up to 29% in the cattle and buffalo population in different regions. Cattle show a long lasting and durable immunity by giving an infection of B.bovis, B. bigemina, or Babesiadivergens. this is used in cattle to immunize them in a few countries as anti-babesiosis vaccine. Development of frozen vaccine allows for complete testing after production of each batch, However, once thawed, its reduced its shelf life, frozen vaccines are more difficult to transport as well as expensive to produce as compared to chilled vaccine. The contamination of blood derived vaccine has the potential risk that makes pre-production and post-production quality control necessary. For the trail master seed production of whole blood frozen bivalent Babesia(Babesiabovis and Babesiabigemina), 100 blood samples of Babesial positive suspected cattle was taken and processed for separation microscopic detection and rectification by PCR. Vaccine passages were done to reduce the parasitaemiasis in live calves. After 8 passages, parasitemia of Babesia reduced from 80% to 15%. Infected donor calf’s blood was taken by jugular cannulation by using preservative free lithium heparin as an anticoagulant (5 International Units IU heparin/ml blood). In lab, parasite containing blood was mixed in equal volumes with 3 M glycerol in PBS supplemented with 5 mM glucose (final concentration of glycerol 1.5 M) at 37°C. The mixture was then equilibrized at 37°C for 30 minutes and were dispensed in required containers (e.g., 5 ml cryovials).

Keywords: distribution, babesia, primer sequences, PCV

Procedia PDF Downloads 96

Authors: Cam Nguyen

Abstract:

Rapid, accurate, and safe sensing and imaging of physical quantities or structures finds many applications and is of significant interest to society. Sensing and imaging using radio-frequency (RF) techniques, particularly, has gone through significant development and subsequently established itself as a unique territory in the sensing world. RF sensing and imaging has played a critical role in providing us many sensing and imaging abilities beyond our human capabilities, benefiting both civilian and military applications - for example, from sensing abnormal conditions underneath some structures’ surfaces to detection and classification of concealed items, hidden activities, and buried objects. We present the developments of several sensing and imaging systems implementing RF technologies like ultra-wide band (UWB), synthetic-pulse, and interferometry. These systems are fabricated completely using RF integrated circuits. The UWB impulse system operates over multiple pulse durations from 450 to 1170 ps with 5.5-GHz RF bandwidth. It performs well through tests of various samples, demonstrating its usefulness for subsurface sensing. The synthetic-pulse system operating from 0.6 to 5.6 GHz can assess accurately subsurface structures. The synthetic-pulse system operating from 29.72-37.7 GHz demonstrates abilities for various surface and near-surface sensing such as profile mapping, liquid-level monitoring, and anti-personnel mine locating. The interferometric system operating at 35.6 GHz demonstrates its multi-functional capability for measurement of displacements and slow velocities. These RF sensors are attractive and useful for various surface and subsurface sensing applications. This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.

Keywords: RF sensors, radars, surface sensing, subsurface sensing

Procedia PDF Downloads 307

Authors: Silvia Arrate, Waldo Salud, Eloy París

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The wear of cutting tools is one of the most decisive elements when planning tunneling works, programming the maintenance stops and saving the optimum stock of spare parts during the evolution of the excavation. Being able to predict the behavior of cutting tools can give a very competitive advantage in terms of costs and excavation performance, optimized to the needs of the TBM itself. The incredible evolution of data science in recent years gives the option to implement it at the time of analyzing the key and most critical parameters related to machinery with the purpose of knowing how the cutting head is performing in front of the excavated ground. Taking this as a case study, Metro Line 3 of Guadalajara in Mexico will develop the feasibility of using Specific Energy versus data science applied over parameters of Torque, Penetration, and Contact Force, among others, to predict the behavior and status of cutting tools. The results obtained through both techniques are analyzed and verified in the function of the wear and the field situations observed in the excavation in order to determine its effectiveness regarding its predictive capacity. In conclusion, the possibilities and improvements offered by the application of digital tools and the programming of calculation algorithms for the analysis of wear of cutting head elements compared to purely empirical methods allow early detection of possible damage to cutting tools, which is reflected in optimization of excavation performance and a significant improvement in costs and deadlines.

Keywords: cutting tools, data science, prediction, TBM, wear

Procedia PDF Downloads 41

Authors: Tolulope Allo, Mofoluwake P. Ajayi, Adenike E. Idowu, Emmanuel O. Amoo, Fadeke Esther Olu-Owolabi

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Breast cancer which was more prevalent in Europe and America in the past is gradually being mirrored across the world today with greater economic burden on low and middle income countries (LMCs). Breast cancer is the most common cancer among women globally and current studies have shown that a woman dies with the diagnosis of breast cancer every thirteen minutes. The economic cost of breast cancer is overwhelming particularly for developing economies. While it causes billion of dollar in losses of national income, it pushes millions of people below poverty line. This study examined the economic burden of breast cancer on Nigerian women, its impacts on their standard of living and its effects on Nigeria’s socio economic development. The study adopts a qualitative research approach using the in-depth interview technique to elicit valuable information from respondents with cancer experience from the Southern part of Nigeria. Respondents constituted women in their reproductive age (15-49 years) that have experienced and survived cancer and also those that are currently receiving treatment. Excerpts from the interviews revealed that the cost of treatment is one of the major factors contributing to the late presentation of breast cancer incidences among women as many of them could not afford to pay for their own treatment. The study also revealed that many women prefer to explore other options such as herbal treatments and spiritual consultations which is less expensive and affordable. The study therefore concludes that breast cancer diagnosis and treatment should be subsidized by the government in order to facilitate easy access and affordability thereby promoting early detection and reducing the economic burden of treatment on women.

Keywords: breast cancer, development, economic burden, women

Procedia PDF Downloads 352

Authors: Michael Anton Kraus, Miriam Schuster, Geralt Siebert, Jens Schneider

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Polymers increasingly gained interest in construction materials over the last years in civil engineering applications. As polymeric materials typically show time- and temperature dependent material behavior, which is accounted for in the context of the theory of linear viscoelasticity. Within the context of this paper, the authors show, that some polymeric interlayers for laminated glass can not be considered as thermorheologically simple as they do not follow a simple TTSP, thus a methodology of identifying the thermorheologically complex constitutive bahavioir is needed. ‘Dynamical-Mechanical-Thermal-Analysis’ (DMTA) in tensile and shear mode as well as ‘Differential Scanning Caliometry’ (DSC) tests are carried out on the interlayer material ‘Ethylene-vinyl acetate’ (EVA). A navoel Bayesian framework for the Master Curving Process as well as the detection and parameter identification of the TTSPs along with their associated Prony-series is derived and applied to the EVA material data. To our best knowledge, this is the first time, an uncertainty quantification of the Prony-series in a Bayesian context is shown. Within this paper, we could successfully apply the derived Bayesian methodology to the EVA material data to gather meaningful Master Curves and TTSPs. Uncertainties occurring in this process can be well quantified. We found, that EVA needs two TTSPs with two associated Generalized Maxwell Models. As the methodology is kept general, the derived framework could be also applied to other thermorheologically complex polymers for parameter identification purposes.

Keywords: bayesian parameter identification, generalized Maxwell model, linear viscoelasticity, thermorheological complex

Procedia PDF Downloads 259

Authors: Jean Berger, Nassirou Lo, Martin Noel

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Perfectly suited for natural or man-made emergency and disaster management situations such as flood, earthquakes, tornadoes, or tsunami, multi-target search path planning for a team of rescue agents is known to be computationally hard, and most techniques developed so far come short to successfully estimate optimality gap. A novel mixed-integer linear programming (MIP) formulation is proposed to optimally solve the multi-target multi-agent discrete search and rescue (SAR) path planning problem. Aimed at maximizing cumulative probability of successful target detection, it captures anticipated feedback information associated with possible observation outcomes resulting from projected path execution, while modeling agent discrete actions over all possible moving directions. Problem modeling further takes advantage of network representation to encompass decision variables, expedite compact constraint specification, and lead to substantial problem-solving speed-up. The proposed MIP approach uses CPLEX optimization machinery, efficiently computing near-optimal solutions for practical size problems, while giving a robust upper bound obtained from Lagrangean integrality constraint relaxation. Should eventually a target be positively detected during plan execution, a new problem instance would simply be reformulated from the current state, and then solved over the next decision cycle. A computational experiment shows the feasibility and the value of the proposed approach.

Keywords: search path planning, search and rescue, multi-agent, mixed-integer linear programming, optimization

Procedia PDF Downloads 366

Authors: Breanna Macumber, Victor A. Huayamave, Emir A. Vela, Wangdo Kim, Tamara T. Chamber, Esteban Centeno

Abstract:

Spina bifida is a type of neural tube defect that affects the nervous system and can lead to problems such as total leg paralysis. Treatment requires physical therapy and rehabilitation. Robotic exoskeletons have been used for rehabilitation to train muscle movement and assist in injury recovery; however, current models focus on the adult populations and not on the infant population. The proposed framework aims to couple a musculoskeletal infant model with a robotic exoskeleton using vacuum-powered artificial muscles to provide rehabilitation to infants affected by spina bifida. The study that drove the input values for the robotic exoskeleton used motion capture technology to collect data from the spontaneous kicking movement of a 2.4-month-old infant lying supine. OpenSim was used to develop the musculoskeletal model, and Inverse kinematics was used to estimate hip joint angles. A total of 4 kicks (A, B, C, D) were selected, and the selection was based on range, transient response, and stable response. Kicks had at least 5° of range of motion with a smooth transient response and a stable period. The robotic exoskeleton used a Vacuum-Powered Artificial Muscle (VPAM) the structure comprised of cells that were clipped in a collapsed state and unclipped when desired to simulate infant’s age. The artificial muscle works with vacuum pressure. When air is removed, the muscle contracts and when air is added, the muscle relaxes. Bench testing was performed using a 6-month-old infant mannequin. The previously developed exoskeleton worked really well with controlled ranges of motion and frequencies, which are typical of rehabilitation protocols for infants suffering with spina bifida. However, the random kicking motion in this study contained high frequency kicks and was not able to accurately replicate all the investigated kicks. Kick 'A' had a greater error when compared to the other kicks. This study has the potential to advance the infant rehabilitation field.

Keywords: musculoskeletal modeling, soft robotics, rehabilitation, pediatrics

Procedia PDF Downloads 106

Authors: Mayesha Tahsin, A.S. Mollah

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Recently, a 1.5x1.5 inch NaI(Tl) detector based gamma-ray spectroscopy system has been installed in the laboratory of the Nuclear Science and Engineering Department of the Military Institute of Science and Technology for radioactivity detection purposes. The newly installed NaI(Tl) detector has a circular lead shield of 22 mm width. An important consideration of any gamma-ray spectroscopy is the minimization of natural background radiation not originating from the radioactive sample that is being measured. Natural background gamma-ray radiation comes from naturally occurring or man-made radionuclides in the environment or from cosmic sources. Moreover, the main problem with this system is that it is not suitable for measurements of radioactivity with a large sample container like Petridish or Marinelli beaker geometry. When any laboratory installs a new detector or/and new shield, it “must” first carry out quality and performance tests for the detector and shield. This paper describes a new portable shielding system with lead that can reduce the background radiation. Intensity of gamma radiation after passing the shielding will be calculated using shielding equation I=Ioe-µx where Io is initial intensity of the gamma source, I is intensity after passing through the shield, µ is linear attenuation coefficient of the shielding material, and x is the thickness of the shielding material. The height and width of the shielding will be selected in order to accommodate the large sample container. The detector will be surrounded by a 4π-geometry low activity lead shield. An additional 1.5 mm thick shield of tin and 1 mm thick shield of copper covering the inner part of the lead shielding will be added in order to remove the presence of characteristic X-rays from the lead shield.

Keywords: shield, NaI (Tl) detector, gamma radiation, intensity, linear attenuation coefficient

Procedia PDF Downloads 145

Authors: Joseph Gear, Yue Xu, Ernest Foo, Praveen Gauravaran, Zahra Jadidi, Leonie Simpson

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Deep learning methods have been seeing an increasing application to the long-standing security research goal of automatic vulnerability detection for source code. Attention, however, must still be paid to the task of producing vector representations for source code (code embeddings) as input for these deep learning models. Graphical representations of code, most predominantly Abstract Syntax Trees and Code Property Graphs, have received some use in this task of late; however, for very large graphs representing very large code snip- pets, learning becomes prohibitively computationally expensive. This expense may be reduced by intelligently pruning this input to only vulnerability-relevant information; however, little research in this area has been performed. Additionally, most existing work comprehends code based solely on the structure of the graph at the expense of the information contained by the node in the graph. This paper proposes Semantic-enhanced Code Embedding for Vulnerability Discovery (SCEVD), a deep learning model which uses semantic-based feature selection for its vulnerability classification model. It uses information from the nodes as well as the structure of the code graph in order to select features which are most indicative of the presence or absence of vulnerabilities. This model is implemented and experimentally tested using the SARD Juliet vulnerability test suite to determine its efficacy. It is able to improve on existing code graph feature selection methods, as demonstrated by its improved ability to discover vulnerabilities.

Keywords: code representation, deep learning, source code semantics, vulnerability discovery

Procedia PDF Downloads 148

Authors: Yasser A. Ahmed, Juleen M Dickson, Evan S. Krystofiak, Julie A. Oliver

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Cancer cells urgently need folate to support their rapid division. Folate receptors (FR) are over-expressed on a wide range of tumor cells, including breast cancer cells. FR are distributed over the entire surface of cancer cells, but are polarized to the apical surface of normal cells. Targeting of cancer cells using specific surface molecules such as folate receptors may be one of the strategies used to kill cancer cells without hurting the neighing normal cells. The aim of the current study was to try a method of SEM detecting FR in a murine breast cancer cell model (4T1 cells) using secondary antibody conjugated to gold or gold-coated magnetite nanoparticles. 4T1 cells were suspended in RPMI medium witth FR antibody and incubated with secondary antibody for fluorescence microscopy. The cells were cultured on 30mm Thermanox coverslips for 18 hours, labeled with FR antibody then incubated with secondary antibody conjugated to gold or gold-coated magnetite nanoparticles and processed to scanning electron microscopy (SEM) analysis. The fluorescence microscopy study showed strong punctate FR expression on 4T1 cell membrane. With SEM, the labeling with gold or gold-coated magnetite conjugates showed a similar pattern. Specific labeling occurred in nanoparticle clusters, which are clearly visualized in backscattered electron images. The 4T1 tumor cell model may be useful for the development of FR-targeted tumor therapy using gold-coated magnetite nano-particles.

Keywords: cancer cell, nanoparticles, cell culture, SEM

Procedia PDF Downloads 728

Authors: E. Bennion, A. Acharya, S. Barnes, D. Ferrell, S. Luckett-Cole, G. Mower, J. Nelson, Y. Nguyen

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Objective: This study aimed to evaluate the validity of a firearm injury query in the Early Notification of Community-based Epidemics syndromic surveillance system. Syndromic surveillance data are used at the Utah Department of Health for early detection of and rapid response to unusually high rates of violence and injury, among other health outcomes. The query of interest was defined by the Centers for Disease Control and Prevention and used chief complaint and discharge diagnosis codes to capture initial emergency department encounters for firearm injury of all intents. Design: Two epidemiologists manually reviewed electronic health records of emergency department visits captured by the query from April-May 2020, compared results, and sent conflicting determinations to two arbiters. Results: Of the 85 unique records captured, 67 were deemed probable, 19 were ruled out, and two were undetermined, resulting in a positive predictive value of 75.3%. Common reasons for false positives included non-initial encounters and misleading keywords. Conclusion: Improving the validity of syndromic surveillance data would better inform outbreak response decisions made by state and local health departments. The firearm injury definition could be refined to exclude non-initial encounters by negating words such as “last month,” “last week,” and “aftercare”; and to exclude non-firearm injury by negating words such as “pellet gun,” “air gun,” “nail gun,” “bullet bike,” and “exit wound” when a firearm is not mentioned.

Keywords: evaluation, health information system, firearm injury, syndromic surveillance

Procedia PDF Downloads 163

Authors: Jae Ni Jang, Young Uk Kim

Abstract:

Background: Chat Generative Pre-training Transformer-3 (ChatGPT; San Francisco, California, Open Artificial Intelligence) is an artificial intelligence chatbot based on a large language model designed to generate human-like text. As the usage of ChatGPT is increasing among less knowledgeable patients, medical students, and anesthesia and pain medicine residents or trainees, we aimed to evaluate the accuracy of ChatGPT-3 responses to questions about the American Society of Anesthesiologists (ASA) classification based on patients’ underlying diseases and assess the quality of the generated responses. Methods: A total of 47 questions were submitted to ChatGPT using textual prompts. The questions were designed for ChatGPT-3 to provide answers regarding ASA classification in response to common underlying diseases frequently observed in adult patients. In addition, we created 18 questions regarding the ASA classification for pediatric patients and pregnant women. The accuracy of ChatGPT’s responses was evaluated by cross-referencing with Miller’s Anesthesia, Morgan & Mikhail’s Clinical Anesthesiology, and the American Society of Anesthesiologists’ ASA Physical Status Classification System (2020). Results: Out of the 47 questions pertaining to adults, ChatGPT -3 provided correct answers for only 23, resulting in an accuracy rate of 48.9%. Furthermore, the responses provided by ChatGPT-3 regarding children and pregnant women were mostly inaccurate, as indicated by a 28% accuracy rate (5 out of 18). Conclusions: ChatGPT provided correct responses to questions relevant to the daily clinical routine of anesthesiologists in approximately half of the cases, while the remaining responses contained errors. Therefore, caution is advised when using ChatGPT to retrieve anesthesia-related information. Although ChatGPT may not yet be suitable for clinical settings, we anticipate significant improvements in ChatGPT and other large language models in the near future. Regular assessments of ChatGPT's ASA classification accuracy are essential due to the evolving nature of ChatGPT as an artificial intelligence entity. This is especially important because ChatGPT has a clinically unacceptable rate of error and hallucination, particularly in pediatric patients and pregnant women. The methodology established in this study may be used to continue evaluating ChatGPT.

Keywords: American Society of Anesthesiologists, artificial intelligence, Chat Generative Pre-training Transformer-3, ChatGPT

Procedia PDF Downloads 37

Authors: V. Mentl, V. Koula, P. Mazal, J. Volák

Abstract:

Nowadays, the acoustic emission is a widely recognized method of material damage investigation, mainly in cases of cracks initiation and growth observation and evaluation. This is highly important in structures, e.g. pressure vessels, large steam turbine rotors etc., applied both in classic and nuclear power plants. Nevertheless, the acoustic emission signals must be correlated with the real crack progress to be able to evaluate the cracks and their growth by this non-destructive technique alone in real situations and to reach reliable results when the assessment of the structures' safety and reliability is performed and also when the remaining lifetime should be evaluated. The main aim of this study was to propose a methodology for evaluation of the early manifestations of the fatigue cracks and their growth and thus to quantify the material damage by acoustic emission parameters. Specimens made of several steels used in the power producing industry were subjected to fatigue loading in the low- and high-cycle regimes. This study presents results of the crack growth rate measurement obtained by the classic compliance change method and the acoustic emission signal analysis. The experiments were realized in cooperation between laboratories of Brno University of Technology and West Bohemia University in Pilsen within the solution of the project of the Czech Ministry of Industry and Commerce: "A diagnostic complex for the detection of pressure media and material defects in pressure components of nuclear and classic power plants" and the project “New Technologies for Mechanical Engineering”.

Keywords: fatigue, crack growth rate, acoustic emission, material damage

Procedia PDF Downloads 367

Authors: Ratih Fitria Putri, Josaphat Tetuko Sri Sumantyo, Hiroaki Kuze

Abstract:

Jakarta Metropolitan City is located on the northwest coast of West Java province with geographical location between 106º33’ 00”-107º00’00”E longitude and 5º48’30”-6º24’00”S latitude. Jakarta urban area has been suffered from land subsidence in several land use type as trading, industry and settlement area. Land subsidence hazard is one of the consequences of urban development in Jakarta. This hazard is caused by intensive human activities in groundwater extraction and land use mismanagement. Geologically, the Jakarta urban area is mostly dominated by alluvium fan sediment. The objectives of this research are to make an analysis of Jakarta urban land use type on land subsidence zone areas. The process of producing safer land use and settlements of the land subsidence areas are very important. Spatial distributions of land subsidence detection are necessary tool for land use management planning. For this purpose, Differential Synthetic Aperture Radar Interferometry (DInSAR) method is used. The DInSAR is complementary to ground-based methods such as leveling and global positioning system (GPS) measurements, yielding information in a wide coverage area even when the area is inaccessible. The data were fine tuned by using X-Band image satellite data from 2010 to 2013 and land use mapping data. Our analysis of land use type that land subsidence movement occurred on the northern part Jakarta Metropolitan City varying from 7.5 to 17.5 cm/year as industry and settlement land use type areas.

Keywords: land use analysis, land subsidence mapping, urban area, X-band satellite image

Procedia PDF Downloads 269

Authors: Breanna Macumber, Victor A. Huayamave, Emir A. Vela, Wangdo Kim, Tamara T. Chamber, Esteban Centeno

Abstract:

Spina bifida is a type of neural tube defect that affects the nervous system and can lead to problems such as total leg paralysis. Treatment requires physical therapy and rehabilitation. Robotic exoskeletons have been used for rehabilitation to train muscle movement and assist in injury recovery; however, current models focus on the adult populations and not on the infant population. The proposed framework aims to couple a musculoskeletal infant model with a robotic exoskeleton using vacuum-powered artificial muscles to provide rehabilitation to infants affected by spina bifida. The study that drove the input values for the robotic exoskeleton used motion capture technology to collect data from the spontaneous kicking movement of a 2.4-month-old infant lying supine. OpenSim was used to develop the musculoskeletal model, and Inverse kinematics was used to estimate hip joint angles. A total of 4 kicks (A, B, C, D) were selected, and the selection was based on range, transient response, and stable response. Kicks had at least 5° of range of motion with a smooth transient response and a stable period. The robotic exoskeleton used a Vacuum-Powered Artificial Muscle (VPAM) the structure comprised of cells that were clipped in a collapsed state and unclipped when desired to simulate infant’s age. The artificial muscle works with vacuum pressure. When air is removed, the muscle contracts and when air is added, the muscle relaxes. Bench testing was performed using a 6-month-old infant mannequin. The previously developed exoskeleton worked really well with controlled ranges of motion and frequencies, which are typical of rehabilitation protocols for infants suffering with spina bifida. However, the random kicking motion in this study contained high frequency kicks and was not able to accurately replicate all the investigated kicks. Kick 'A' had a greater error when compared to the other kicks. This study has the potential to advance the infant rehabilitation field.

Keywords: musculoskeletal modeling, soft robotics, rehabilitation, pediatrics

Procedia PDF Downloads 71

Authors: Mar Cañada Soriano, Rafael Royo-Pastor, Carolina Aparicio-Fernández, Jose-Luis Vivancos

Abstract:

The lack of insulation, along with the existence of air leakages, constitute a meaningful impact on the energy performance of buildings. Both of them lead to increases in the energy demand through additional heating and/or cooling loads. Additionally, they cause thermal discomfort. In order to quantify these uncontrolled air currents, pressurization and depressurization tests can be performed. Among them, the Blower Door test is a standardized procedure to determine the airtightness of a space which characterizes the rate of air leakages through the envelope surface, calculating to this purpose an air flow rate indicator. In this sense, the low-energy buildings complying with the Passive House design criteria are required to achieve high levels of airtightness. Due to the invisible nature of air leakages, additional tools are often considered to identify where the infiltrations take place. Among them, the infrared thermography entails a valuable technique to this purpose since it enables their detection. The aim of this study is to assess the airtightness of a typical Mediterranean dwelling house located in the Valencian orchad (Spain) restored under the Passive House standard using to this purpose the blower-door test. Moreover, the building energy performance modelling tools TRNSYS (TRaNsient System Simulation program) and TRNFlow (TRaNsient Flow) have been used to determine its energy performance, and the infiltrations’ identification was carried out by means of infrared thermography. The low levels of infiltrations obtained suggest that this house may comply with the Passive House standard.

Keywords: airtightness, blower door, trnflow, infrared thermography

Procedia PDF Downloads 113

Authors: Lydia Booney Jyrwa, Rabindra Nath Bhuyan

Abstract:

Chocolate Mahseer (Neolissochilus hexagonolepis) is one of the Mahseer species inhabiting the North-eastern region of India and is a native species to the state of Meghalaya since it can adapt and grow well under the agro climatic conditions of the region. The natural population of this fish has been declining over the years from this part of the country. The natural population of this fish has been declining over the years from this part of the country. The fish is considered as one of the endangered species of the Mahseer group, which is having tremendous scope for culture, sports and tourism. But non-availability of quality seed is a hindrance for the culture of this fish. Thus induced breeding of the fish by hormonal administration with pituitary gland and synthetic hormones is the only reliable method to procure the pure seed of the fish. Chocolate Mahseer was successfully bred at the Hatchery Complex, St. Anthony’s College, Shillong, Meghalaya by using pituitary extract and synthetic hormone viz. ovaprim, ovatide and gonopro-FH. The dose standardized is @ 4mg/kg body weight to both male and female as 1st dose and @ 7.9 mg/kg body weight only to female as 2nd dose for pituitary extract and single dose @ 0.8 ml/kg body weight to female and @ 0.3 ml/kg body weight to male of both ovaprim and ovatide, while a single dose @ 0.9 ml/kg body weight to female and @ 0.3 ml/kg body weight to male of gonopro-FH. The doses are standardized after a series of trial and error experiment performed. The fecundity of the fish was 3500 eggs/ kg body weight. The final hatching percentage achieved was 60%. The survival rate of hatchling was 50% up to fry stage. The use of synthetic hormone and positive response of the fish to the hormone will go in long way for production of quality seed of the fish which in turn help in culture of the species as the fish can be a very good candidate species for the culture in the state. This study will also help in the ranching of the fish in the natural habitat leading to conservation of the species. However, the study should be continued further for the large scale production of seeds.

Keywords: chocolate mahseer, induced breeding, pituitary extract, synthetic hormone

Procedia PDF Downloads 233

Authors: Ágota Ábrahám, Md Nurul Islam, Karimane Zeghbib, Gábor Kemenesi, Sazeda Akter

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Collecting palm sap as a food source is an everyday practice in some parts of the world. However, the consumption of palm juice has been associated with regular infections and epidemics in parts of Bangladesh. This is attributed to fruit-eating bats and other vertebrates or invertebrates native to the area, contaminating the food with their body secretions during the collection process. The frequent intake of palm juice, whether as a processed food product or in its unprocessed form, is a common phenomenon in large areas. The range of pathogens suitable for human infection resulting from this practice is not yet fully understood. Additionally, the high sugar content of the liquid makes it an ideal culture medium for certain bacteria, which can easily propagate and potentially harm consumers. Rapid diagnostics, especially in remote locations, could mitigate health risks associated with palm juice consumption. The primary objective of this research is the rapid genomic detection and risk assessment of bacteria that may cause infections in humans through the consumption of palm juice. Utilizing state-of-the-art third-generation Nanopore metagenomic sequencing technology based on 16S rRNA, and identified bacteria primarily involved in fermenting processes. The swift metagenomic analysis, coupled with the widespread availability and portability of Nanopore products (including real-time analysis options), proves advantageous for detecting harmful pathogens in food sources without relying on extensive industry resources and testing.

Keywords: raw date palm sap, NGS, metabarcoding, food safety

Procedia PDF Downloads 44

Authors: Yanping Liao, Congcong He, Ruigang Zhao

Abstract:

The application of magnetocardiography signals to detect cardiac electrical function is a new technology developed in recent years. The magnetocardiography signal is detected with Superconducting Quantum Interference Devices (SQUID) and has considerable advantages over electrocardiography (ECG). It is difficult to extract Magnetocardiography (MCG) signal which is buried in the noise, which is a critical issue to be resolved in cardiac monitoring system and MCG applications. In order to remove the severe background noise, the Total Variation (TV) regularization method is proposed to denoise MCG signal. The approach transforms the denoising problem into a minimization optimization problem and the Majorization-minimization algorithm is applied to iteratively solve the minimization problem. However, traditional TV regularization method tends to cause step effect and lacks constraint adaptability. In this paper, an improved TV regularization method for denoising MCG signal is proposed to improve the denoising precision. The improvement of this method is mainly divided into three parts. First, high-order TV is applied to reduce the step effect, and the corresponding second derivative matrix is used to substitute the first order. Then, the positions of the non-zero elements in the second order derivative matrix are determined based on the peak positions that are detected by the detection window. Finally, adaptive constraint parameters are defined to eliminate noises and preserve signal peak characteristics. Theoretical analysis and experimental results show that this algorithm can effectively improve the output signal-to-noise ratio and has superior performance.

Keywords: constraint parameters, derivative matrix, magnetocardiography, regular term, total variation

Procedia PDF Downloads 146

Authors: A. Flammini, R. Morbidelli, C. Saltalippi

Abstract:

The increase of air surface temperature at global scale is a fact, with values around 0.85 ºC since the late nineteen century, as well as a significant change in main features of rainfall regime. Nevertheless, the detected climatic changes are not equally distributed all over the world, but exhibit specific characteristics in different regions. Therefore, studying the evolution of climatic indices in different geographical areas with a prefixed standard approach becomes very useful in order to analyze the existence of climatic trend and compare results. In this work, a methodology to investigate the climatic change and its effects on a wide set of climatic indices is proposed and applied at regional scale in the case study of a Mediterranean area, Umbria region in Italy. From data of the available temperature stations, nine temperature indices have been obtained and the existence of trends has been checked by applying the non-parametric Mann-Kendall test, while the non-parametric Pettitt test and the parametric Standard Normal Homogeneity Test (SNHT) have been applied to detect the presence of break points. In addition, aimed to characterize the rainfall regime, data from 11 rainfall stations have been used and a trend analysis has been performed on cumulative annual rainfall depth, daily rainfall, rainy days, and dry periods length. The results show a general increase in any temperature indices, even if with a trend pattern dependent of indices and stations, and a general decrease of cumulative annual rainfall and average daily rainfall, with a time rainfall distribution over the year different from the past.

Keywords: climatic change, temperature, rainfall regime, trend analysis

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Authors: J. Pazourek, K. Šmejkal, P. Kollár, J. Rajchard, J. Šinko, Z. Balounová, E. Vlková, H. Salmonová

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Pectinatella magnifica (Leidy, 1851) is an invasive freshwater animal that lives in colonies. A colony of Pectinatella magnifica (a gelatinous blob) can be up to several feet in diameter large and under favorable conditions it exhibits an extreme growth rate. Recently European countries around rivers of Elbe, Oder, Danube, Rhine and Vltava have confirmed invasion of Pectinatella magnifica, including freshwater reservoirs in South Bohemia (Czech Republic). Our project (Czech Science Foundation, GAČR P503/12/0337) is focused onto biology and chemistry of Pectinatella magnifica. We monitor the organism occurrence in selected South Bohemia ponds and sandpits during the last years, collecting information about physical properties of surrounding water, and sampling the colonies for various analyses (classification, maps of secondary metabolites, toxicity tests). Because the gelatinous matrix is during the colony lifetime also a host for algae, bacteria and cyanobacteria (co-habitants), in this contribution, we also applied a high performance liquid chromatography (HPLC) method for determination of potentially present cyanobacterial toxins (microcystin-LR, microcystin-RR, nodularin). Results from the last 3-year monitoring show that these toxins are under limit of detection (LOD), so that they do not represent a danger yet. The final goal of our study is to assess toxicity risks related to fresh water resources invaded by Pectinatella magnifica, and to understand the process of invasion, which can enable to control it.

Keywords: cyanobacteria, fresh water resources, Pectinatella magnifica invasion, toxicity monitoring

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Authors: Hossein Tavallali, Mohammad Ali Karimi, Gohar Deilamy-Rad

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The proposed method for speciation, preconcentration and determination of Fe(II) and Fe(III) in pharmaceutical products was developed using of alumina-coated magnetite nanoparticles (Fe₃O₄/Al₂O₃ NPs) as solid phase extraction (SPE) sorbent in magnetic mixed hemimicell solid phase extraction (MMHSPE) technique followed by flame atomic absorption spectrometry analysis. The procedure is based on complexation of Fe(II) with 1, 10-phenanthroline (OP) as complexing reagent for Fe(II) that immobilized on the modified Fe₃O₄/Al₂O₃ NPs. The extraction and concentration process for pharmaceutical sample was carried out in a single step by mixing the extraction solvent, magnetic adsorbents under ultrasonic action. Then, the adsorbents were isolated from the complicated matrix easily with an external magnetic field. Fe(III) ions determined after facility reduced to Fe(II) by added a proper reduction agent to sample solutions. Compared with traditional methods, the MMHSPE method simplified the operation procedure and reduced the analysis time. Various influencing parameters on the speciation and preconcentration of trace iron, such as pH, sample volume, amount of sorbent, type and concentration of eluent, were studied. Under the optimized operating conditions, the preconcentration factor of the modified nano magnetite for Fe(II) 167 sample was obtained. The detection limits and linear range of this method for iron were 1.0 and 9.0 - 175 ng.mL⁻¹, respectively. Also the relative standard deviation for five replicate determinations of 30.00 ng.mL^-1 Fe²⁺ was 2.3%.

Keywords: Alumina-Coated magnetite nanoparticles, Magnetic Mixed Hemimicell Solid-Phase Extraction, Fe(ΙΙ) and Fe(ΙΙΙ), pharmaceutical sample

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Authors: Elnaz Saeedi, Jamileh Abolaghasemi, Mohsen Nasiri Tousi, Saeedeh Khosravi

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Goals and Objectives: A typical analysis of survival data involves the modeling of time-to-event data, such as the time till death. A frailty model is a random effect model for time-to-event data, where the random effect has a multiplicative influence on the baseline hazard function. This article aims to investigate the use of gamma frailty model with concomitant variable in order to individualize the prognostic factors that influence the liver cirrhosis patients’ survival times. Methods: During the one-year study period (May 2008-May 2009), data have been used from the recorded information of patients with liver cirrhosis who were scheduled for liver transplantation and were followed up for at least seven years in Imam Khomeini Hospital in Iran. In order to determine the effective factors for cirrhotic patients’ survival in the presence of latent variables, the gamma frailty distribution has been applied. In this article, it was considering the parametric model, such as Exponential and Weibull distributions for survival time. Data analysis is performed using R software, and the error level of 0.05 was considered for all tests. Results: 305 patients with liver cirrhosis including 180 (59%) men and 125 (41%) women were studied. The age average of patients was 39.8 years. At the end of the study, 82 (26%) patients died, among them 48 (58%) were men and 34 (42%) women. The main cause of liver cirrhosis was found hepatitis 'B' with 23%, followed by cryptogenic with 22.6% were identified as the second factor. Generally, 7-year’s survival was 28.44 months, for dead patients and for censoring was 19.33 and 31.79 months, respectively. Using multi-parametric survival models of progressive and regressive, Exponential and Weibull models with regard to the gamma frailty distribution were fitted to the cirrhosis data. In both models, factors including, age, bilirubin serum, albumin serum, and encephalopathy had a significant effect on survival time of cirrhotic patients. Conclusion: To investigate the effective factors for the time of patients’ death with liver cirrhosis in the presence of latent variables, gamma frailty model with parametric distributions seems desirable.

Keywords: frailty model, latent variables, liver cirrhosis, parametric distribution

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Authors: Mohd Sabri Minhat, Nurul Adilla Mohd Subha

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The PUSPATI TRIGA Reactor (RTP), Malaysia reached its first criticality on June 28, 1982, with power capacity 1MW thermal. The Feedback Control Algorithm (FCA) which is conventional Proportional-Integral (PI) controller, was used for present power control method to control fission process in RTP. It is important to ensure the core power always stable and follows load tracking within acceptable steady-state error and minimum settling time to reach steady-state power. At this time, the system could be considered not well-posed with power tracking performance. However, there is still potential to improve current performance by developing next generation of a novel design nuclear core power control. In this paper, the dual-mode predictions which are proposed in modelling Optimal Model Predictive Control (OMPC), is presented in a state-space model to control the core power. The model for core power control was based on mathematical models of the reactor core, OMPC, and control rods selection algorithm. The mathematical models of the reactor core were based on neutronic models, thermal hydraulic models, and reactivity models. The dual-mode prediction in OMPC for transient and terminal modes was based on the implementation of a Linear Quadratic Regulator (LQR) in designing the core power control. The combination of dual-mode prediction and Lyapunov which deal with summations in cost function over an infinite horizon is intended to eliminate some of the fundamental weaknesses related to MPC. This paper shows the behaviour of OMPC to deal with tracking, regulation problem, disturbance rejection and caters for parameter uncertainty. The comparison of both tracking and regulating performance is analysed between the conventional controller and OMPC by numerical simulations. In conclusion, the proposed OMPC has shown significant performance in load tracking and regulating core power for nuclear reactor with guarantee stabilising in the closed-loop.

Keywords: core power control, dual-mode prediction, load tracking, optimal model predictive control

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Authors: Dimiter M. Dimitrov, Abdullah Sadaawi

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The National Assessment for Schools (NAFS) in Saudi Arabia consists of standardized tests in Mathematics, Reading, and Science for school grade levels 3, 6, and 9. One main goal is to classify students into four categories of NAFS performance (minimal, basic, proficient, and advanced) by schools and the entire national sample. The NAFS scoring and equating is performed on a bounded scale (D-scale: ranging from 0 to 1) in the framework of the recently developed “D-scoring method of measurement.” The specificity of the NAFS measurement framework and data complexity presented both challenges and opportunities to (a) the estimation of score reliability for schools, (b) setting cut-scores for the classification of students into categories of performance, and (c) generating plausible values for distributions of student performance on the D-scale. The estimation of score reliability at the school level was performed in the framework of generalizability theory (GT), with students “nested” within schools and test items “nested” within test forms. The GT design was executed via a multilevel modeling syntax code in R. Cut-scores (on the D-scale) for the classification of students into performance categories was derived via a recently developed method of standard setting, referred to as “Response Vector for Mastery” (RVM) method. For each school, the classification of students into categories of NAFS performance was based on distributions of plausible values for the students’ scores on NAFS tests by grade level (3, 6, and 9) and subject (Mathematics, Reading, and Science). Plausible values (on the D-scale) for each individual student were generated via random selection from a statistical logit-normal distribution with parameters derived from the student’s D-score and its conditional standard error, SE(D). All procedures related to D-scoring, equating, generating plausible values, and classification of students into performance levels were executed via a computer program in R developed for the purpose of NAFS data analysis.

Keywords: large-scale assessment, reliability, generalizability theory, plausible values

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Authors: S. Ziaran, M. Musil, M. Cekan, O. Chlebo

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The paper analyzes the response of buildings and industrially structures on seismic waves (low frequency mechanical vibration) generated by blasting operations. The principles of seismic analysis can be applied for different kinds of excitation such as: earthquakes, wind, explosions, random excitation from local transportation, periodic excitation from large rotating and/or machines with reciprocating motion, metal forming processes such as forging, shearing and stamping, chemical reactions, construction and earth moving work, and other strong deterministic and random energy sources caused by human activities. The article deals with the response of seismic, low frequency, mechanical vibrations generated by nearby blasting operations on a residential home. The goal was to determine the fundamental natural frequencies of the measured structure; therefore it is important to determine the resonant frequencies to design a suitable modal damping. The article also analyzes the package of seismic waves generated by blasting (Primary waves – P-waves and Secondary waves S-waves) and investigated the transfer regions. For the detection of seismic waves resulting from an explosion, the Fast Fourier Transform (FFT) and modal analysis, in the frequency domain, is used and the signal was acquired and analyzed also in the time domain. In the conclusions the measured results of seismic waves caused by blasting in a nearby quarry and its effect on a nearby structure (house) is analyzed. The response on the house, including the fundamental natural frequency and possible fatigue damage is also assessed.

Keywords: building structure, seismic waves, spectral analysis, structural response

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Authors: Sabina-Adriana Floria, Marius Gavrilescu, Florin Leon, Silvia Curteanu, Costel Anton

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Neuroevolution is a subfield of artificial intelligence used to solve various problems in different application areas. Specifically, neuroevolution is a technique that applies biologically inspired methods to generate neural network architectures and optimize their parameters automatically. In this paper, we use different biologically inspired optimization algorithms in an ensemble strategy with the aim of training multilayer perceptron neural networks, resulting in regression models used to simulate the industrial chemical process of obtaining bricks from silicone-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. In addition, the initial conditions that were taken into account during the design and commissioning of the installation can change over time, which leads to the need to add new mixes to adjust the operating conditions for the desired purpose, e.g., material properties and energy saving. The present approach follows the study by simulation of a process of obtaining bricks from silicone-based materials, i.e., the modeling and optimization of the process. Optimization aims to determine the working conditions that minimize the emissions represented by nitrogen monoxide. We first use a search procedure to find the best values for the parameters of various biologically inspired optimization algorithms. Then, we propose an adaptive ensemble strategy that uses only a subset of the best algorithms identified in the search stage. The adaptive ensemble strategy combines the results of selected algorithms and automatically assigns more processing capacity to the more efficient algorithms. Their efficiency may also vary at different stages of the optimization process. In a given ensemble iteration, the most efficient algorithms aim to maintain good convergence, while the less efficient algorithms can improve population diversity. The proposed adaptive ensemble strategy outperforms the individual optimizers and the non-adaptive ensemble strategy in convergence speed, and the obtained results provide lower error values.

Keywords: optimization, biologically inspired algorithm, neuroevolution, ensembles, bricks, emission minimization

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Authors: Erwan Negre, Ewan J. O'Connor, Juha Toivonen

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The need for CO2 monitoring technologies grows simultaneously with the worldwide concerns regarding environmental challenges. To that purpose, we developed a compact coherent all-fiber ranged-resolved Differential Absorption Lidar (RR-DIAL). It has been designed along a tunable 2x1fiber optic switch set to a frequency of 1 Hz between two Distributed FeedBack (DFB) lasers emitting in the continuous-wave mode at 1571.41 nm (absorption line of CO2) and 1571.25 nm (CO2 absorption-free line), with linewidth and tuning range of respectively 1 MHz and 3 nm over operating wavelength. A three stages amplification through Erbium and Erbium-Ytterbium doped fibers coupled to a Radio Frequency (RF) driven Acousto-Optic Modulator (AOM) generates 100 ns pulses at a repetition rate from 10 to 30 kHz with a peak power up to 2.5 kW and a spatial resolution of 15 m, allowing fast and highly resolved CO2 profiles. The same afocal collection system is used for the output of the laser source and the backscattered light which is then directed to a circulator before being mixed with the local oscillator for heterodyne detection. Packaged in an easily transportable box which also includes a server and a Field Programmable Gate Array (FPGA) card for on-line data processing and storing, our setup allows an effective and quick deployment for versatile in-situ analysis, whether it be vertical atmospheric monitoring, large field mapping or sequestration site continuous oversight. Setup operation and results from initial field measurements will be discussed.

Keywords: CO2 profiles, coherent DIAL, in-situ atmospheric sensing, near infrared fiber source

Procedia PDF Downloads 125