Search results for: detecting unknown viruses

Authors: Shuo Li, Yannick Coffinier, Chann Lagadec, Fabrizio Cleri, Katsuhiko Nishiguchi, Akira Fujiwara, Soo Hyeon Kim, Nicolas Clément

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The need for single cell detection and analysis techniques has increased in the past decades because of the heterogeneity of individual living cells, which increases the complexity of the pathogenesis of malignant tumors. In the search for early cancer detection, high-precision medicine and therapy, the technologies most used today for sensitive detection of target analytes and monitoring the variation of these species are mainly including two types. One is based on the identification of molecular differences at the single-cell level, such as flow cytometry, fluorescence-activated cell sorting, next generation proteomics, lipidomic studies, another is based on capturing or detecting single tumor cells from fresh or fixed primary tumors and metastatic tissues, and rare circulating tumors cells (CTCs) from blood or bone marrow, for example, dielectrophoresis technique, microfluidic based microposts chip, electrochemical (EC) approach. Compared to other methods, EC sensors have the merits of easy operation, high sensitivity, and portability. However, despite various demonstrations of low limits of detection (LOD), including aptamer sensors, arrayed EC sensors for detecting single-cell have not been demonstrated. In this work, a new technique based on 20-nm-thick nanopillars array to support cells and keep them at ideal recognition distance for redox-labeled aptamers grafted on the surface. The key advantages of this technology are not only to suppress the false positive signal arising from the pressure exerted by all (including non-target) cells pushing on the aptamers by downward force but also to stabilize the aptamer at the ideal hairpin configuration thanks to a confinement effect. With the first implementation of this technique, a LOD of 13 cells (with5.4 μL of cell suspension) was estimated. In further, the nanosupported cell technology using redox-labeled aptasensors has been pushed forward and fully integrated into a single-cell electrochemical aptasensor array. To reach this goal, the LOD has been reduced by more than one order of magnitude by suppressing parasitic capacitive electrochemical signals by minimizing the sensor area and localizing the cells. Statistical analysis at the single-cell level is demonstrated for the recognition of cancer cells. The future of this technology is discussed, and the potential for scaling over millions of electrodes, thus pushing further integration at sub-cellular level, is highlighted. Despite several demonstrations of electrochemical devices with LOD of 1 cell/mL, the implementation of single-cell bioelectrochemical sensor arrays has remained elusive due to their challenging implementation at a large scale. Here, the introduced nanopillar array technology combined with redox-labeled aptamers targeting epithelial cell adhesion molecule (EpCAM) is perfectly suited for such implementation. Combining nanopillar arrays with microwells determined for single cell trapping directly on the sensor surface, single target cells are successfully detected and analyzed. This first implementation of a single-cell electrochemical aptasensor array based on Brownian-fluctuating redox species opens new opportunities for large-scale implementation and statistical analysis of early cancer diagnosis and cancer therapy in clinical settings.

Keywords: bioelectrochemistry, aptasensors, single-cell, nanopillars

Procedia PDF Downloads 92

Authors: Avinash Malladhi

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Forensic accounting is a specialized field that involves the application of accounting principles, investigative skills, and legal knowledge to detect and prevent fraud. With the rise of big data and technological advancements, artificial intelligence (AI) and machine learning (ML) algorithms have emerged as powerful tools for forensic accountants to enhance their fraud detection capabilities. In this paper, we review and analyze various AI/ML algorithms that are commonly used in forensic accounting, including supervised and unsupervised learning, deep learning, natural language processing Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Support Vector Machines (SVMs), Decision Trees, and Random Forests. We discuss their underlying principles, strengths, and limitations and provide empirical evidence from existing research studies demonstrating their effectiveness in detecting financial fraud. We also highlight potential ethical considerations and challenges associated with using AI/ML in forensic accounting. Furthermore, we highlight the benefits of these technologies in improving fraud detection and prevention in forensic accounting.

Keywords: AI, machine learning, forensic accounting & fraud detection, anti money laundering, Benford's law, fraud triangle theory

Procedia PDF Downloads 69

Authors: Rashini Maduka, C. R. Wijesinghe, A. R. Weerasinghe

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Drug-drug interactions (DDIs) can happen when two or more drugs are taken together. Today DDIs have become a serious health issue due to adverse drug effects. In vivo and in vitro methods for identifying DDIs are time-consuming and costly. Therefore, in-silico-based approaches are preferred in DDI identification. Most machine learning models for DDI prediction are used chemical and biological drug properties as features. However, some drug features are not available and costly to extract. Therefore, it is better to make automatic feature engineering. Furthermore, people who have diabetes already suffer from other diseases and take more than one medicine together. Then adverse drug effects may happen to diabetic patients and cause unpleasant reactions in the body. In this study, we present a model with a graph convolutional autoencoder and a graph decoder using a dataset from DrugBank version 5.1.3. The main objective of the model is to identify unknown interactions between antidiabetic drugs and the drugs taken by diabetic patients for other diseases. We considered automatic feature engineering and used Known DDIs only as the input for the model. Our model has achieved 0.86 in AUC and 0.86 in AP.

Keywords: drug-drug interaction prediction, graph embedding, graph convolutional networks, adverse drug effects

Procedia PDF Downloads 80

Authors: Myoung-Jin Lee, Sung-Jin Lee, Young-Kon Park, Jin-Wook Kim, Bo-Kyoung Kim, Song-Hun Chong, Sun-Il Kim

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Currently, sinkholes may occur due to natural or unknown causes. When the sinkhole is an instantaneous phenomenon, most accidents occur because of significant damage. Thus, methods of monitoring are being actively researched, such that the impact of the accident can be mitigated. A sinkhole can severely affect and wreak havoc in community-based facilities such as a city railway construction. Therefore, the development of a laser / scanning system and an image-based tunnel is one method of pre-monitoring that it stops the accidents. The laser scanning is being used but this has shortcomings as it involves the development of expensive equipment. A laser / videobased scanning tunnel is being developed at Korea Railroad Research Institute. This is designed to automatically operate the railway. The purpose of the scanning is to obtain an image of the city such as of railway structures (stations, tunnel). At the railway structures, it has developed 3D laser scanning that can find a micro-crack can not be distinguished by the eye. An additional aim is to develop technology to monitor the status of the railway structure without the need for expensive post-processing of 3D laser scanning equipment, by developing corresponding software.

Keywords: 3D laser scanning, sinkhole, tunnel, city railway construction

Procedia PDF Downloads 416

Authors: Marina Franulovic, Robert Basan, Bozidar Krizan

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Constitutive modelling of material behaviour is becoming increasingly important in prediction of possible failures in highly loaded engineering components, and consequently, optimization of their design. In order to account for large number of phenomena that occur in the material during operation, such as kinematic hardening effect in low cycle fatigue behaviour of steels, complex nonlinear material models are used ever more frequently, despite of the complexity of determination of their parameters. As a method for the determination of these parameters, genetic algorithm is good choice because of its capability to provide very good approximation of the solution in systems with large number of unknown variables. For the application of genetic algorithm to parameter identification, inverse analysis must be primarily defined. It is used as a tool to fine-tune calculated stress-strain values with experimental ones. In order to choose proper objective function for inverse analysis among already existent and newly developed functions, the research is performed to investigate its influence on material behaviour modelling.

Keywords: genetic algorithm, kinematic hardening, material model, objective function

Procedia PDF Downloads 312

Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: autonomous surveillance, Bayesian reasoning, decision support, interventions, patterns of life, predictive analytics, predictive insights

Procedia PDF Downloads 102

Authors: Maram Saleh

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Knowledge has become an essential resource in today’s economy and become the most important asset of maintaining competition advantage in organizations. The importance of knowledge has made organizations to manage their knowledge assets and resources through all multiple knowledge management stages such as: Knowledge Creation, knowledge storage, knowledge sharing and knowledge use. Researches on data mining are continues growing over recent years on both business and educational fields. Data mining is one of the most important steps of the knowledge discovery in databases process aiming to extract implicit, unknown but useful knowledge and it is considered as significant subfield in knowledge management. Data miming have the great potential to help organizations to focus on extracting the most important information on their data warehouses. Data mining tools and techniques can predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. This review paper explores the applications of data mining techniques in supporting knowledge management process as an effective knowledge discovery technique. In this paper, we identify the relationship between data mining and knowledge management, and then focus on introducing some application of date mining techniques in knowledge management for some real life domains.

Keywords: Data Mining, Knowledge management, Knowledge discovery, Knowledge creation.

Procedia PDF Downloads 189

Authors: Marina Borgert Moraes, Wesley Francisco, Filipe Vargas, Gilmar Patrocínio Thim

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In recent years, carbon nanotubes (CNT) and graphene oxide (GO), especially the functionalized ones, have been added to epoxy resin in order to increase the mechanical, electrical and thermal properties of nanocomposites. However, it's still unknown how the presence of these nanoparticles influences the curing process and the final mechanical properties as well. In this work, kinetic and mechanical properties of the nanocomposites were analyzed, where the kinetic process was followed by DSC and the mechanical properties by DMA. Initially, CNT was annealed at high temperature (1800 °C) under vacuum atmosphere, followed by a chemical treatment using acids and ethylenediamine. GO was synthesized through chemical route, washed clean, dried and ground to #200. The presence of functional groups on CNT and GO surface was confirmed by XPS spectra and FT-IR. Then, epoxy resin, nanoparticles and acetone were mixed by sonication in order to obtain the composites. DSC analyses were performed on samples with different curing cycles (1h 80°C + 2h 120°C; 3h 80°C + 2h 120°C; 5h 80°C) and samples with different times at constant temperature (120°C). Results showed that the kinetic process and the mechanical strength are very dependent on the presence of graphene and functionalized-CNT in the nanocomposites.

Keywords: carbon nanotube, epoxy resin, Graphene oxide, nanocomposite

Procedia PDF Downloads 300

Authors: Hao Cheng, Zhiwu Wang, Guozheng Yan, Pingping Jiang, Shijia Qin, Shuai Kuang

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Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.

Keywords: AFI, edge detection, adaptive threshold, morphological processing, OV6930, FPGA

Procedia PDF Downloads 208

Authors: E. Sobhani-Tehrani, K. Khorasani, N. Meskin

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This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems. Unlike most FD techniques, the proposed solution simultaneously accomplishes fault detection, isolation, and identification (FDII) within a unified diagnostic module. At the core of this solution is a bank of adaptive neural parameter estimators (NPE) associated with a set of single-parameter fault models. The NPEs continuously estimate unknown fault parameters (FP) that are indicators of faults in the system. Two NPE structures including series-parallel and parallel are developed with their exclusive set of desirable attributes. The parallel scheme is extremely robust to measurement noise and possesses a simpler, yet more solid, fault isolation logic. On the contrary, the series-parallel scheme displays short FD delays and is robust to closed-loop system transients due to changes in control commands. Finally, a fault tolerant observer (FTO) is designed to extend the capability of the NPEs to systems with partial-state measurement.

Keywords: hybrid fault diagnosis, dynamic neural networks, nonlinear systems, fault tolerant observer

Procedia PDF Downloads 375

Authors: Fangtian Fan, Zhaoguo Liu, Yin Lu

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Early recurrence (ER) (< 1 year) after liver resection is one of the most important factors that impacts the prognosis of patients with hepatocellular carcinoma (HCC). However, the molecular mechanisms and predictive indexes of ER after curative resection remain largely unknown. The present study aimed to exploit the role of EGFR signaling in EMT and early recurrence of HCC after curative resection and elucidate the molecular mechanisms. Our results showed that nuclear beta-catenin / PKM2 was a independent predictor of early recurrence after curative resection in EGFR-overexpressed HCC. Mechanistic investigation indicated that nuclear accumulation of beta-catenin and PKM2 induced by EGFR signal promoted HCC cell invasion and proliferation, which were required for early recurrence of HCC. These effects were mediated by PI3K/AKT and ERK pathways rather than the canonical Wnt signaling. In conclusions, EGFR signal induced-nuclear translocation of beta-catenin and PKM2 promotes HCC malignancy and indicates early recurrence after curative resection.

Keywords: beta-catenin, early recurrence, hepatocellular carcinoma, malignancy, PKM2

Procedia PDF Downloads 342

Authors: K. Thiagarajan, K. Saranya, A. Veeraiah, B. Sudha

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This paper presents a novel algorithm for secure, reliable and flexible transmission of big data in two hop wireless networks using cooperative jamming scheme. Two hop wireless networks consist of source, relay and destination nodes. Big data has to transmit from source to relay and from relay to destination by deploying security in physical layer. Cooperative jamming scheme determines transmission of big data in more secure manner by protecting it from eavesdroppers and malicious nodes of unknown location. The novel algorithm that ensures secure and energy balance transmission of big data, includes selection of data transmitting region, segmenting the selected region, determining probability ratio for each node (capture node, non-capture and eavesdropper node) in every segment, evaluating the probability using binary based evaluation. If it is secure transmission resume with the two- hop transmission of big data, otherwise prevent the attackers by cooperative jamming scheme and transmit the data in two-hop transmission.

Keywords: big data, two-hop transmission, physical layer wireless security, cooperative jamming, energy balance

Procedia PDF Downloads 467

Authors: Siddharth Satishchandran, Brian Khumalo

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Humans are able to derive semantic content from syntactic and pragmatic sources. Multimodal evidence from signaling theory, which examines communication between individuals within and across species, suggests that non-human primates possess similar syntactic and pragmatic capabilities. However, the extent remains unknown because primate pragmatics are relatively under-examined. Our paper reviews research within communication theory amongst non-human primates to understand current theoretical trends. We examine evidence for primate pragmatic capacities through observational, experimental, and theoretical work on gestures. Given fragmented theoretical perspectives, we provide a unified framework of communication for future research that contextualizes the available research under code biology. To achieve this, we rely on biological semiotics (biosemiotics), the philosophy of biology investigating prelinguistic meaning-making as a function of signs and codes. We close by discussing areas of potential research for studying gestural pragmatics amongst non-human primates, particularly chimpanzees (Pan troglodytes), Diana monkeys (Cercopithecus diana), and other potential candidates.

Keywords: pragmatics, non-human primates, gestural communication, biological semiotics

Procedia PDF Downloads 14

Authors: Eid Alharbi, Yaser Miaji

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The quality level for fresh fruits is very important for the fruit industries. In presents study, an automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic conveyer belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950nm region the online sorting system was constructed.

Keywords: mechatronics, NIR, fruit quality, spectroscopic technology, mechatronic design

Procedia PDF Downloads 378

Authors: Soumaya Mrabet, Imen Akkari, Amira Atig, Elhem Ben Jazia

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Introduction: Autoimmune hepatitis (AIH) is a chronic inflammatory liver disease of unknown cause. Concomitant autoimmune disorders have been described in 30–50% of patients with AIH. The aim of our study is to determine the prevalence and the type of autoimmune disorders associated with AIH. Material and Methods: It is a retrospective study over a period of 16 years (2000-2015) including all patients followed for AIH. The diagnosis of AHI was based on the criteria of the revised International AIH group scoring system (IAIHG). Results: Twenty-for patients (21 women and 3 men) followed for AIH were collected. The mean age was 39 years (17-65 years). Among these patients, 11 patients(45.8%) had at least one autoimmune disease associated to AIH. These diseases were Hashimoto's thyroiditis (n = 5), Gougerot Sjogren syndrome (n=5), Primary biliary cirrhosis (n=2), Primitive sclerosant Cholangitis (n=1), Addison disease (n = 1) and systemic sclerosis (n=1). Patients were treated with corticosteroids alone or with azathioprine associated to the specific treatment of associated diseases with complete remission of AIH in 90% of cases and clinical improvement of other diseases. Conclusion: In our study, the prevalence of autoimmune diseases in AIH patients was 45.8%. These diseases were dominated by autoimmune thyroiditis and Gougerot Sjogren syndrome. The investigation of autoimmune diseases in autoimmune hepatitis must be systematic because of their frequency and the importance of adequate management.

Keywords: autoimmune diseases, autoimmune hepatitis, autoimmune thyroiditis, gougerot sjogren syndrome

Procedia PDF Downloads 245

Authors: R. Majidzadeh Heravi, M. Sankian, H. Kermanshahi, M. R. Nassiri, A. Heravi Moussavi, S. A. Lari, A. R. Varasteh

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The use of probiotics engineered to express specific enzymes has been the subject of considerable attention in poultry industry because of increased nutrient availability and reduced cost of enzyme supplementation. Phytase enzyme is commonly added to poultry feed to improve digestibility and availability of phosphorus from plant sources. To construct a probiotic with potential of phytate degradation, phytase gene (appA) from E. coli was cloned and transformed into two probiotic bacteria Lactobacillus salivarius and Lactococcus lactis. L. salivarous showed plasmid instability, unable to express the gene. The expression of appA gene in L. lactis was analyzed by detecting specific RNA and zymography assay. Phytase enzyme was isolated from cellular extracts of recombinant L. lactis, showing a 46 kDa band upon the SDS-PAGE analysis. Zymogram also confirmed the phytase activity of the 46 kDa band corresponding to the enzyme. An enzyme activity of 4.9U/ml was obtained in cell extracts of L. lactis. The growth of native and recombinant L. lactis was similar in the presence of two concentrations of ox bile.

Keywords: Lactobacillus salivarus, Lactococcuslactis, recombinant, phytase, poultry

Procedia PDF Downloads 471

Authors: Marina Borgert Moraes, Gilmar Patrocinio Thim

Abstract:

It is still unknown how the presence of nanoparticles such as graphene oxide (GO) or carbon nanotubes (CNT) influence the curing process and the final mechanical properties as well. In this work, kinetic and mechanical properties of the nanocomposites were analyzed, where the kinetic process was followed by DSC and the mechanical properties by DMA as well as mechanical tests. Initially, CNT was annealed at high temperature (1800 °C) under vacuum atmosphere, followed by a chemical treatment using acids and ethylenediamine. GO was synthesized through chemical route, washed clean, dried and ground to #200. The presence of functional groups on CNT and GO surface was confirmed by XPS spectra and FT-IR. Then, nanoparticles and acetone were mixed by sonication in order to obtain the composites. DSC analyses were performed on samples with different curing cycles (1h 80 °C + 2h 120 °C; 3h 80 °C + 2h 120 °C; 5h 80 °C) and samples with different times at constant temperature (120 °C). Mechanical tests were performed according to ASTM D638 and D790. Results showed that the kinetic process and the mechanical strength are very dependent on the presence of graphene and functionalized-CNT in the nanocomposites, and the GO reinforced samples had a slightly bigger improvement compared to functionalized CNT.

Keywords: carbon nanotube, epoxy resin, graphene oxide, nanocomposite

Procedia PDF Downloads 247

Authors: Yavuz Yardım

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The most important criteria for structural engineering is the structure’s ability to carry intended loads safely. The key element of this ability is mathematical modeling of really loadings situation into a simple loads input to use in structure analysis and design. Amongst many different types of loads, the most challenging load is earthquake load. It is possible magnitude is unclear and timing is unknown. Therefore the concept of intended loads and safety have been built on experience of previous earthquake impact on the structures. Understanding and developing these concepts is achieved by investigating performance of the structures after real earthquakes. Damage after an earthquake provide results of thousands of full-scale structure test under a real seismic load. Thus, Earthquakes reveille all the weakness, mistakes and deficiencies of analysis, design rules and practice. This study deals with lesson learnt from earthquake recoded last two decades in Turkey. Results of investigation after several earthquakes exposes many deficiencies in structural detailing, inappropriate design, wrong architecture layout, and mainly mistake in construction practice.

Keywords: earthquake, seismic assessment, RC buildings, building performance

Procedia PDF Downloads 245

Authors: Rei-Heng Cheng, Wen-Pinn Fang

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A wireless sensor network (WSN) is composed by a large number of sensors and one or a few base stations, where the sensor is responsible for detecting specific event information, which is sent back to the base station(s). However, how to save electricity consumption to extend the network lifetime is a problem that cannot be ignored in the wireless sensor networks. Since the sensor network is used to monitor a region or specific events, how the information can be reliably sent back to the base station is surly important. Network coding technique is often used to enhance the reliability of the network transmission. When a node needs to send out M data packets, it encodes these data with redundant data and sends out totally M + R packets. If the receiver can get any M packets out from these M + R packets, it can decode and get the original M data packets. To transmit redundant packets will certainly result in the excess energy consumption. This paper will explore relationship between the quality of wireless transmission and the number of redundant packets. Hopefully, each sensor can overhear the nearby transmissions, learn the wireless transmission quality around it, and dynamically determine the number of redundant packets used in network coding.

Keywords: energy consumption, network coding, transmission reliability, wireless sensor networks

Procedia PDF Downloads 373

Authors: Yu. I. Pigolkin, M. A. Garcia Corro

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Age determination of unknown dead bodies in forensic personal identification is a complicated process which involves the application of numerous methods and techniques. Skeletal remains are less exposed to influences of environmental factors. In order to enhance the accuracy of forensic age estimation additional properties of bones correlating with age are required to be revealed. Material and Methods: Dimensional examination of the sella turcica was carried out on cadavers with the cranium opened by a circular vibrating saw. The sample consisted of a total of 90 Russian subjects, ranging in age from two months and 87 years. Results: The tendency of dimensional variations throughout life was detected. There were no observed gender differences in the morphometry of the sella turcica. The shared use of the sella turcica depth and length values revealed the possibility to categorize an examined sample in a certain age period. Conclusions: Based on the results of existing methods of age determination, the morphometry of the sella turcica can be an additional characteristic, amplifying the received values, and accordingly, increasing the accuracy of forensic biological age diagnosis.

Keywords: age–related changes in bone structures, forensic personal identification, sella turcica morphometry, body identification

Procedia PDF Downloads 255

Authors: V. Ramu Reddy, Parijat Deshpande, Ranjan Dasgupta

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This paper presents different methodology for an acoustic source sensing and localization in an unknown environment. The developed methodology includes an acoustic based sensing and localization system, a converging target localization based on the recursive direction of arrival (DOA) error minimization, and a regressive obstacle avoidance function. Our method is able to augment the existing proven localization techniques and improve results incrementally by utilizing robot locomotion and is capable of converging to a position estimate with greater accuracy using fewer measurements. The results also evinced the DOA error minimization at each iteration, improvement in time for reaching the destination and the efficiency of this target localization method as gradually converging to the real target position. Initially, the system is tested using Kinect mounted on turntable with DOA markings which serve as a ground truth and then our approach is validated using a FireBird VI (FBVI) mobile robot on which Kinect is used to obtain bearing information.

Keywords: acoustic source localization, acoustic sensing, recursive direction of arrival, robot locomotion

Procedia PDF Downloads 477

Authors: Annisa Ulfah Pristya, Andi Setiawan

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Indonesia placed in sixth rank total Acute Respiratory Infection (ARI) patient in the world and Riau as one of the province with the highest number of people with respiratory infection in Indonesia reached 37 thousand people. Usually society using a mask as prevention action. Unfortunately the commercial mouth mask only can work maximum for 4 hours and the pores are too large to filter out microorganisms and viruses carried by infectious droplets nucleated 1-5 μm. On the other hand, Indonesia is rich with Titanium dioxide (TiO2) and purple sweet potato anthocyanin pigment. Therefore, offered Bio-nano-mask which is a antimicrobial and antiviral mouth mask with Nano-TiO2 coating and purple sweet potato anthocyanins utilization as an effective solution to high ARI patients in Riau, which has the advantage of the mask surface can’t be attached by infectious droplets, self-cleaning and have anthocyanins biosensors that give visual response can be understood easily by the general public in the form of a mask color change from blue/purple to pink when acid levels increase. Acid level is an indicator of microorganisms accumulation in the mouth and surrounding areas. Bio-nano mask making process begins with the preparation (design, Nano-TiO2 liquid preparation, anthocyanins biosensors manufacture) and then superimposing the Nano-TiO2 on the outer surface of spunbond color using a sprayer, then superimposing anthocyanins biosensors film on the Meltdown surface, making bio nano-mask and it pack. Bio-nano mask has the advantage is effectively preventing pathogenic microorganisms and infectious droplets and has accumulated indicator microorganisms that color changes which easily observed by the common people though.

Keywords: anthocyanins, ARI, nano-TiO2 liquid, self cleaning

Procedia PDF Downloads 543

Authors: Insaf Bellamine, Hamid Tairi

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Detecting moving objects in sequences is an essential step for video analysis. This paper mainly contributes to the Color Space-Time Interest Points (CSTIP) extraction and detection. We propose a new method for detection of moving objects. Two main steps compose the proposed method. First, we suggest to apply the algorithm of the detection of Color Space-Time Interest Points (CSTIP) on both components of the Color Structure-Texture Image Decomposition which is based on a Partial Differential Equation (PDE): a color geometric structure component and a color texture component. A descriptor is associated to each of these points. In a second stage, we address the problem of grouping the points (CSTIP) into clusters. Experiments and comparison to other motion detection methods on challenging sequences show the performance of the proposed method and its utility for video analysis. Experimental results are obtained from very different types of videos, namely sport videos and animation movies.

Keywords: Color Space-Time Interest Points (CSTIP), Color Structure-Texture Image Decomposition, Motion Detection, clustering

Procedia PDF Downloads 361

Authors: Divya Agarwal, Pushpendra S. Bharti

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Autonomous mobile robots (AMR) are expected as smart tools for operations in every automation industry. Path planning and obstacle avoidance is the backbone of AMR as robots have to reach their goal location avoiding obstacles while traversing through optimized path defined according to some criteria such as distance, time or energy. Path planning can be classified into global and local path planning where environmental information is known and unknown/partially known, respectively. A number of sensors are used for data collection. A number of algorithms such as artificial potential field (APF), rapidly exploring random trees (RRT), bidirectional RRT, Fuzzy approach, Purepursuit, A* algorithm, vector field histogram (VFH) and modified local path planning algorithm, etc. have been used in the last three decades for path planning and obstacle avoidance for AMR. This paper makes an attempt to review some of the path planning and obstacle avoidance algorithms used in the field of AMR. The review includes comparative analysis of simulation and mathematical computations of path planning and obstacle avoidance algorithms using MATLAB 2018a. From the review, it could be concluded that different algorithms may complete the same task (i.e. with a different set of instructions) in less or more time, space, effort, etc.

Keywords: path planning, obstacle avoidance, autonomous mobile robots, algorithms

Procedia PDF Downloads 216

Authors: Yu-Lin Shen, Ming-Kuen Chang

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In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electro Magnetic Acoustic Transducer Testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length.. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, NDT, artificial defect, ultrasonic testing

Procedia PDF Downloads 449

Authors: Sara Pereira-Nogueira, Tim Worbs, Marc Permanyer-Bosser, Reinhold Förster

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While the entry mechanism of lymphocytes into the lymph node via the blood are well described, it is still largely unknown how cells enter lymph nodes that arrive via afferent lymphatics. In order to address this, our group has established a micro-injection technique in mice through which cells are delivered directly into the lymphatic vessel immediately afferent to the popliteal lymph node. Injected cells can then be tracked via multi-colour fluorescence or 2-photon microscopy, and their localization can be analysed within the popliteal or downstream lymph nodes by immunohistology. Since naïve B cells express the chemokine receptor CXCR5 we intra-lymphatically co-injected B cells derived from wildtype and Cxcr5-deficient mice. While CXCR5 does not play a role in guiding B cells out of the subcapsular sinus, it affects their positioning within the lymph node parenchyma, since CXCR5-deficient B cells are impaired in migrating into the B cell follicle. The knowledge obtained by studying B-cell migration may prove beneficial in clinical settings regarding tumor metastasis or autoimmune diseases.

Keywords: afferent lymphatics, B cell migration, chemokine, intra-lymphatic injection

Procedia PDF Downloads 244

Authors: D. Leibman, D. Wolf, A. Gal-On

Abstract:

Viral diseases of tomato crops result in heavy yield losses and may even jeopardize the production of these crops. Classical tomato breeding for disease resistance against Tomato yellow leaf curl virus (TYLCV), leads to partial resistance associated with a number of recessive genes. To author’s best knowledge Pepino mosaic virus (PepMV) genetic resistance is not yet available. The generation of viral resistance by means of genetic engineering was reported and implemented for many crops, including tomato. Transgenic resistance against viruses is based, in most cases, on Post Transcriptional Gene Silencing (PTGS), an endogenous mechanism which destroys the virus genome. In this work, we developed immunity against PepMV and TYLCV in a tomato based on a PTGS mechanism. Tomato plants were transformed with a hairpin-construct-expressed transgene-derived double-strand-RNA (tr-dsRNA). In the case of PepMV, the binary construct harbored three consecutive fragments of the replicase gene from three different PepMV strains (Italian, Spanish and American), to provide resistance against a range of virus strains. In the case of TYLCV, the binary vector included three consecutive fragments of the IR, V2 and C2 viral genes constructed in a hairpin configuration. Selected transgenic lines (T0) showed a high accumulation of transgene siRNA of 21-24 bases, and T1 transgenic lines showed complete immunity to PepMV and TYLCV. Graft inoculation displayed immunity of the transgenic scion against PepMV and TYLCV. The study presents the engineering of resistance in tomato against two serious diseases, which will help in the production of high-quality tomato. However, unfortunately, these resistant plants have not been implemented due to public ignorance and opposition against breeding by genetic engineering.

Keywords: PepMV, PTGS, TYLCV, tr-dsRNA

Procedia PDF Downloads 109

Authors: Khaled Missaoui, Amina Beldjazia, Rachid Gharzouli, Yamna Djellouli

Abstract:

Optical remote sensing makes use of visible, near infrared and short-wave infrared sensors to form images of the earth's surface by detecting the solar radiation reflected from targets on the ground. Different materials reflect and absorb differently at different wavelengths. Thus, the targets can be differentiated by their spectral reflectance signatures in the remotely sensed images. In this work, we are interested to study the distribution of vegetation in the massif forest of Boutaleb (North East of Algeria) which suffered between 1998 and 1999 very large fires. In this case, we use remote sensing with Landsat images from two dates (1984 and 2000) to see the results of these fires. Vegetation has a unique spectral signature which enables it to be distinguished readily from other types of land cover in an optical/near-infrared image. Normalized Difference Vegetation Index (NDVI) is calculated with ENVI 4.7 from Band 3 and 4. The results showed a very important floristic diversity in this forest. The comparison of NDVI from the two dates confirms that there is a decrease of the density of vegetation in this area due to repeated fires.

Keywords: remote sensing, boutaleb, diversity, forest

Procedia PDF Downloads 542

Authors: Akbar Farahani, Afsaneh Hassani, Peyman M. Farkhondeh

Abstract:

Human Resource Management as one of the core processes of the project-based companies, despite its key role in the success and competitive advantage, is relatively unknown. In the project-based companies, due to the accelerated movement of knowledge in the work activities and the temporary nature of the project, the need to develop mechanisms for achieving optimal management of this issues is very challenging. Approach to human resource management in these companies evolves with goals, strategies, and operational processes. Therefore, the need for appropriate tools to facilitate implementation of the optimized human resource management in the project is more than before,Which currently with the development of information technology and modern communication, appropriate to address the optimal approach for dynamic management of human resources in the project have been provided.This is done by using the referral system implemented in Mahab GCE that provides 1: the ability to use humans in projects without geographic limitation and 2:information on the activities and outcomes of referrals.Furthermore, by using this system, recording the lessons learned after any particular activity on projects,accessing quantitative information, procedures, documentation of learned practices that have been stored in the data base as well as using them in future projects is provided.

Keywords: human resource management, project base company, ERP, referrals system

Procedia PDF Downloads 459

Authors: Shih-Hao Chen, Chi-Wai Chow

Abstract:

Multiple-input and multiple-output (MIMO) scheme can extend the transmission capacity for the light-emitting-diode (LED) visible light communication (VLC) system. The MIMO VLC system using the popular mobile-phone camera as the optical receiver (Rx) to receive MIMO signal from n x n Red-Green-Blue (RGB) LED array is desirable. The key step of decoding the received RGB LED array signals is detecting the direction of received array signals. If the LED transmitter (Tx) is rotated, the signal may not be received correctly and cause an error in the received signal. In this work, we propose and demonstrate a novel hierarchical transmission scheme which can reduce the computation complexity of rotation detection in LED array VLC system. We use the n x n RGB LED array as the MIMO Tx. A novel two dimension Hadamard coding scheme is proposed and demonstrated. The detection correction rate is above 95% in the indoor usage distance. Experimental results confirm the feasibility of the proposed scheme.

Keywords: Visible Light Communication (VLC), Multiple-input and multiple-output (MIMO), Red-Green-Blue (RGB), Hadamard coding scheme

Procedia PDF Downloads 404