Search results for: one-shot object detection

Authors: Fatemeh Nokhodchi Bonab

Abstract:

Bioinformatics, in its broad sense, involves application of computer processes to solve biological problems. A wide range of computational tools are needed to effectively and efficiently process large amounts of data being generated as a result of recent technological innovations in biology and medicine. A number of computational tools have been developed or adapted to deal with the experimental riches of complex and multivariate data and transition from data collection to information or knowledge. These bioinformatics tools are being evaluated and applied in various medical areas including early detection, risk assessment, classification, and prognosis of cancer. The goal of these efforts is to develop and identify bioinformatics methods with optimal sensitivity, specificity, and predictive capabilities. The recent flood of data from genome sequences and functional genomics has given rise to new field, bioinformatics, which combines elements of biology and computer science. Bioinformatics is conceptualizing biology in terms of macromolecules (in the sense of physical-chemistry) and then applying "informatics" techniques (derived from disciplines such as applied maths, computer science, and statistics) to understand and organize the information associated with these molecules, on a large-scale. Here we propose a definition for this new field and review some of the research that is being pursued, particularly in relation to transcriptional regulatory systems.

Keywords: methods, applications, transcriptional regulatory systems, techniques

Procedia PDF Downloads 127

Authors: Oktia Woro Kasmini Handayani, Sri Ratna Rahayu, Efa Nugroho, Bertakalswa Hermawati

Abstract:

The double burden of nutrition problem must be faced by Indonesia as developing country. The implemented program did not improve the nutritional status, therefore need to consider to utilize local potential. The objective of this research was to find out the effectivity of magnification model of early detect through local potential utilization in urban region, Semarang, Central Java, Indonesia. The research used an experimental design with the quantitative-qualitative approach. The population was all toddlers under five within the research region, sample determination by purposive sampling, as many as 216 toddlers. Quantitative data analysis used effectively criteria by Sugiono. Qualitative data was analyzed using NVivo. The optimization of local potential in the effort of nutrition status improvement shows number of nutrition case found was increased 225% (very effective), number of cases treated was increased 175% (very effective), number of cases counselled was increased 200% (effective), and number of cases that have improvement increase 75% (effective). The local potential need to be utilized in the effort of nutrition program improvement one of it is through the community empowerment, particularly health care and health high education institution as partner.

Keywords: early detection, nutrition status, local potential, health cadre

Procedia PDF Downloads 275

Authors: Komal Ghafoor, Tauqir Ahmad, Murtaza Hanif, Hira Zaheer

Abstract:

Assistive technology has been developed to support visually impaired people in their social interactions. Conversation assistive technology is designed to enhance communication skills, facilitate social interaction, and improve the quality of life of visually impaired individuals. This technology includes speech recognition, text-to-speech features, and other communication devices that enable users to communicate with others in real time. The technology uses natural language processing and machine learning algorithms to analyze spoken language and provide appropriate responses. It also includes features such as voice commands and audio feedback to provide users with a more immersive experience. These technologies have been shown to increase the confidence and independence of visually impaired individuals in social situations and have the potential to improve their social skills and relationships with others. Overall, conversation-assistive technology is a promising tool for empowering visually impaired people and improving their social interactions. One of the key benefits of conversation-assistive technology is that it allows visually impaired individuals to overcome communication barriers that they may face in social situations. It can help them to communicate more effectively with friends, family, and colleagues, as well as strangers in public spaces. By providing a more seamless and natural way to communicate, this technology can help to reduce feelings of isolation and improve overall quality of life. The main objective of this research is to give blind users the capability to move around in unfamiliar environments through a user-friendly device by face, object, and activity recognition system. This model evaluates the accuracy of activity recognition. This device captures the front view of the blind, detects the objects, recognizes the activities, and answers the blind query. It is implemented using the front view of the camera. The local dataset is collected that includes different 1st-person human activities. The results obtained are the identification of the activities that the VGG-16 model was trained on, where Hugging, Shaking Hands, Talking, Walking, Waving video, etc.

Keywords: dataset, visually impaired person, natural language process, human activity recognition

Procedia PDF Downloads 58

Authors: Ludivine Gueho, Sylvain Fleury, Eric Jamet

Abstract:

Driver distraction is known to be a major contributing factor of car accidents. Since many years, constructors have been designing embedded technologies to face this problem and reduce distraction. Being able to predict user acceptance would further be helpful in the development process to build appropriate systems. The present research aims at modelling the acceptability of a specific system, an innovative personalized and contextualized embedded radio, through an online survey of 202 people in France that assessed the psychological variables determining intentions to use the system. The questionnaire instantiated the dimensions of the extended version of the UTAUT acceptability model. Because of the specific features of the system assessed, we added 4 dimensions: perceived security, anxiety, trust and privacy concerns. Results showed that hedonic motivation, i.e., the fun or pleasure derived from using a technology, and performance expectancy, i.e., the degree to which individuals believe that the characteristics of the system meet their needs, are the most important dimensions in determining behavioral intentions about the innovative radio. To a lesser extent, social influence, i.e., the degree to which individuals think they can use the system while respecting their social group’s norms and while giving a positive image of themselves, had an effect on behavioral intentions. Moreover, trust, that is, the positive belief about the perceived reliability of, dependability of, and confidence in a person, object or process, had a significant effect, mediated by performance expectancy. In an applicative way, the present research reveals that, to be accepted, in-car embedded new technology has to address individual needs, for instance by facilitating the driving activity or by providing useful information. If it shows hedonic qualities by being entertaining, pretty or comfortable, this may improve the intentions to use it. Therefore, it is clearly important to include reflection about user experience in the design process. Finally, the users have to be reassured on the system’s reliability. For example, improving the transparency of the system by providing information about the system functioning, could improve trust. These results bring some highlights on determinant of acceptance of an in-vehicle technology and are useful for constructors to design acceptable systems.

Keywords: acceptability, innovative embedded radio, structural equation, user-centric evaluation, UTAUT

Procedia PDF Downloads 269

Authors: Tewelde Gebreslassie Gebreanenia, Frie Ayalew Yimam, Seada Hussen Adem

Abstract:

Patient safety and quality of care are essential goals of health care delivery, but they are often compromised by human errors, system failures, or resource constraints. In a variety of healthcare contexts, artificial intelligence (AI), a quickly developing field, can provide fresh approaches to enhancing patient safety and treatment quality. Artificial Intelligence (AI) has the potential to decrease errors and enhance patient outcomes by carrying out tasks that would typically require human intelligence. These tasks include the detection and prevention of adverse events, monitoring and warning patients and clinicians about changes in vital signs, symptoms, or risks, offering individualized and evidence-based recommendations for diagnosis, treatment, or prevention, and assessing and enhancing the effectiveness of health care systems and services. This study examines the state-of-the-art and potential future applications of AI-based technologies for enhancing patient safety and care quality, as well as the opportunities and problems they present for patients, policymakers, researchers, and healthcare providers. In order to ensure the safe, efficient, and responsible application of AI in healthcare, the paper also addresses the ethical, legal, social, and technical challenges that must be addressed and regulated.

Keywords: artificial intelligence, health care, human intelligence, patient safty, quality of care

Procedia PDF Downloads 78

Authors: Reza Ferdousi, Reza Safdari, Yadollah Omidi

Abstract:

Drug-drug interactions (DDIs) are main cause of the adverse drug reactions and nature of the functional and molecular complexity of drugs behavior in human body make them hard to prevent and treat. With the aid of new technologies derived from mathematical and computational science the DDIs problems can be addressed with minimum cost and efforts. Market basket analysis is known as powerful method to identify co-occurrence of thing to discover patterns and frequency of the elements. In this research, we used market basket analysis to identify important bio-elements in DDIs occurrence. For this, we collected all known DDIs from DrugBank. The obtained data were analyzed by market basket analysis method. We investigated all drug-enzyme, drug-carrier, drug-transporter and drug-target associations. To determine the importance of the extracted bio-elements, extracted rules were evaluated in terms of confidence and support. Market basket analysis of the over 45,000 known DDIs reveals more than 300 important rules that can be used to identify DDIs, CYP 450 family were the most frequent shared bio-elements. We applied extracted rules over 2,000,000 unknown drug pairs that lead to discovery of more than 200,000 potential DDIs. Analysis of the underlying reason behind the DDI phenomena can help to predict and prevent DDI occurrence. Ranking of the extracted rules based on strangeness of them can be a supportive tool to predict the outcome of an unknown DDI.

Keywords: drug-drug interaction, market basket analysis, rule discovery, important bio-elements

Procedia PDF Downloads 309

Authors: Nisha Gaur, K.Narasimhulu, Pydi Setty Yelamarthy

Abstract:

Persistent organic pollutants (POPs) have become a great concern due to their toxicity, transformation and bioaccumulation property. Therefore, this review highlights the types, sources, classification health hazards and mobility of organochlorine pesticides, industrial chemicals and their by-products. Moreover, with the signing of Aarhus and Stockholm convention on POPs there is an increased demand to identify and characterise such chemicals from industries and environment which are toxic in nature or to existing biota. Due to long life, persistent nature they enter into body through food and transfer to all tropic levels of ecological unit. In addition, POPs are lipophilic in nature and accumulate in lipid-containing tissues and organs which further indicates the adverse symptoms after the threshold limit. Though, several potential enzymes are reported from various categories of microorganism and their interaction with POPs may break down the complex compounds either through biodegradation, biostimulation or bioaugmentation process, however technological advancement and human activities have also indicated to explore the possibilities for the role of genetically modified organisms and metagenomics and metabolomics. Though many studies have been done to develop low cost, effective and reliable method for detection, determination and removal of ultra-trace concentration of persistent organic pollutants (POPs) but due to insufficient knowledge and non-feasibility of technique, the safe management of POPs is still a global challenge.

Keywords: persistent organic pollutants, bioaccumulation, biostimulation, microbial remediation

Procedia PDF Downloads 299

Authors: Hui Zhang, Sherif Beskhyroun

Abstract:

Structural Health monitoring systems (SHM) are commonly used to identify and assess structural damage. In terms of damage detection, SHM needs to periodically collect data from sensors placed in the structure as damage-sensitive features. This includes abnormal changes caused by the strain field and abnormal symptoms of the structure, such as damage and deterioration. Currently, deploying sensors on a large scale in a building structure is a challenge. In this study, a highly stretchable strain sensors are used in this study to collect data sets of strain generated on the surface of full-size reinforced concrete (RC) frames under extreme cyclic load application. This sensing sheet can be switched freely between the test bending strain and the axial strain to achieve two different configurations. On this basis, the deep neural network prediction model of the frame beam and frame column is established. The training results show that the method can accurately predict the strain value and has good generalization ability. The two deep neural network prediction models will also be deployed in the SHM system in the future as part of the intelligent strain sensor system.

Keywords: strain sensing sheets, deep neural networks, strain measurement, SHM system, RC frames

Procedia PDF Downloads 99

Authors: Jakob Krause

Abstract:

Past Financial Crisis has shown that contemporary risk management models provide an unjustified sense of security and fail miserably in situations in which they are needed the most. In this paper, we start from the assumption that risk is a notion that changes over time and therefore past data points only have limited explanatory power for the current situation. Our objective is to derive the optimal amount of representative information by optimizing between the two adverse forces of estimator convergence, incentivizing us to use as much data as possible, and the aforementioned non-representativeness doing the opposite. In this endeavor, the cornerstone assumption of having access to identically distributed random variables is weakened and substituted by the assumption that the law of the data generating process changes over time. Hence, in this paper, we give a quantitative theory on how to perform statistical analysis in non-ergodic systems. As an application, we discuss the impact of a paragraph in the last iteration of proposals by the Basel Committee on Banking Regulation. We start from the premise that the severity of assumptions should correspond to the robustness of the system they describe. Hence, in the formal description of physical systems, the level of assumptions can be much higher. It follows that every concept that is carried over from the natural sciences to economics must be checked for its plausibility in the new surroundings. Most of the probability theory has been developed for the analysis of physical systems and is based on the independent and identically distributed (i.i.d.) assumption. In Economics both parts of the i.i.d. assumption are inappropriate. However, only dependence has, so far, been weakened to a sufficient degree. In this paper, an appropriate class of non-stationary processes is used, and their law is tied to a formal object measuring representativeness. Subsequently, that data set is identified that on average minimizes the estimation error stemming from both, insufficient and non-representative, data. Applications are far reaching in a variety of fields. In the paper itself, we apply the results in order to analyze a paragraph in the Basel 3 framework on banking regulation with severe implications on financial stability. Beyond the realm of finance, other potential applications include the reproducibility crisis in the social sciences (but not in the natural sciences) and modeling limited understanding and learning behavior in economics.

Keywords: banking regulation, non-ergodicity, risk management, semimartingale modeling

Procedia PDF Downloads 148

Authors: Rômulo Eustáquio Martins de Souza, Paulo Alexandre Rodrigues de Vasconcelos Figueiredo

Abstract:

In recent years, there has been a surge in interest in applying artificial intelligence techniques, particularly machine learning algorithms. Machine learning is a data-analysis technique that automates the creation of analytical models, making it especially useful for designing complex situations. As a result, this technology aids in reducing human intervention while producing accurate results. This methodology is also extensively used in aerospace engineering since this is a field that encompasses several high-complexity operations, such as rocket propulsion. Rocket propulsion is a high-risk operation in which engine failure could result in the loss of life. As a result, it is critical to use computational methods capable of precisely representing the spacecraft's analytical model to guarantee its security and operation. Thus, this paper describes the use of machine learning algorithms for rocket propulsion to aid the realization that this technique is an efficient way to deal with challenging and restrictive aerospace engineering activities. The paper focuses on three machine-learning-aided rocket propulsion applications: set-point control of an expander-bleed rocket engine, supersonic retro-propulsion of a small-scale rocket, and leak detection and isolation on rocket engine data. This paper describes the data-driven methods used for each implementation in depth and presents the obtained results.

Keywords: data analysis, modeling, machine learning, aerospace, rocket propulsion

Procedia PDF Downloads 115

Authors: Mohamed Moustafa, Medhat Abdallah, Ramy Magdy, Ahmed Abdrabou, Mohamed Badr

Abstract:

The scribe box under study dates back to the old kingdom. It was excavated by the Italian expedition in Qena (1935-1937). The box consists of 2pieces, the lid and the body. The inner side of the lid is decorated with ancient Egyptian inscriptions written with a black pigment. The box was made using several panels assembled together by wooden dowels and secured with plant ropes. The entire box is covered with a red pigment. This study aims to use analytical techniques in order to identify and have deep understanding for the box components. Moreover, the authors were significantly interested in using infrared reflectance transmission imaging (RTI-IR) to improve the hidden inscriptions on the lid. The identification of wood species included in this study. The visual observation and assessment were done to understand the condition of this box. 3Ddimensions and 2D programs were used to illustrate wood joints techniques. Optical microscopy (OM), X-ray diffraction (XRD), X-ray fluorescence portable (XRF) and Fourier Transform Infrared spectroscopy (FTIR) were used in this study in order to identify wood species, remains of insects bodies, red pigment, fibers plant and previous conservation adhesives, also RTI-IR technique was very effective to improve hidden inscriptions. The analysis results proved that wooden panels and dowels were identified as Acacia nilotica, wooden rail was Salix sp. the insects were identified as Lasioderma serricorne and Gibbium psylloids, the red pigment was Hematite, while the fiber plants were linen, previous adhesive was identified as cellulose nitrates. The historical study for the inscriptions proved that it’s a Hieratic writings of a funerary Text. After its transportation from the Egyptian museum storage to the wood conservation laboratory of the Grand Egyptian museum –conservation center (GEM-CC), conservation techniques were applied with high accuracy in order to restore the object including cleaning , consolidating of friable pigments and writings, removal of previous adhesive and reassembly, finally the conservation process that were applied were extremely effective for this box which became ready for display or storage in the grand Egyptian museum.

Keywords: scribe box, hieratic, 3D program, Acacia nilotica, XRD, cellulose nitrate, conservation

Procedia PDF Downloads 271

Authors: Jihene Bettaieb, Kaouther Ayouni, Ghassen Kharroubi, Rym Mallekh, Walid Hammemi, Afif Ben Salah, Henda Triki

Abstract:

In Tunisia, the hepatitis A virus (HAV) represents a public health concern. Due to the progress in sanitation and socio-economic conditions, the epidemiology of HAV has shown dynamic changes over the past years. This study aimed to investigate the current seroprevalence of HAV antibodies (anti-HAV) among the residents of Thala, a rural setting in central-west Tunisia, to determine the age-specific seroprevalence for HAV infection and co-infection with hepatitis C and B virus. A total of 1379 subjects (mean age: 25.0 ± 17.3 years, 555 males/ 824 females) were recruited between January and June 2014. The study population included 95 individuals previously known as hepatitis C positive. Serum samples were collected and screened for the detection of IgG anti-HAV, HBsAg, and HBcAb by the Elisa Test. The overall anti- HAV seroprevalence was about 84.7%. There was no statistically significant difference between males and females. On the 1379 tested individual, 219 were positive for HBcAb, and 67 were positive for HBsAg. IgG anti- HAV were positive in 80.6% of HBsAg-positive patients (54 out of 67), 81.3% of HBcAb-positive patients (178 out of 219), and in 95.8% of HCV-positive patients (91 out of 95). HBV infection and HCV infection were statistically associated with a greater risk of positive anti-HAV antibody (p < 0.001). Our study revealed that Thala represents an intermediate endemicity level and that the introduction of vaccination against HAV in this region is recommended, especially for the hepatitis B or C infected person seronegative for HAV.

Keywords: coinfection, hepatitis A, seroprevalence, Tunisia

Procedia PDF Downloads 151

Authors: F. Kashanian, M. M. Masoudi, A. Akbari, A. Shamloo, M. R. Zand, S. S. Salehi

Abstract:

Nano-sized materials present new opportunities in biology and medicine and they are used as biomedical tools for investigation, separation of molecules and cells. To achieve more effective cancer therapy, it is essential to select cancer cells exactly. This research suggests that using the antibody-functionalized nontoxic Arginine-doped magnetic nanoparticles (A-MNPs), has been prosperous in detection, capture, and magnetic separation of circulating tumor cells (CTCs) in tumor tissue. In this study, A-MNPs were synthesized via a simple precipitation reaction and directly immobilized Ep-CAM EBA-1 antibodies over superparamagnetic A-MNPs for Mucin BCA-225 in breast cancer cell. The samples were characterized by vibrating sample magnetometer (VSM), FT-IR spectroscopy, Tunneling Electron Microscopy (TEM) and Scanning Electron Microscopy (SEM). These antibody-functionalized nontoxic A-MNPs were used to capture breast cancer cell. Through employing a strong permanent magnet, the magnetic separation was achieved within a few seconds. Antibody-Conjugated nontoxic Arginine-doped Fe₃O₄ nanoparticles have the potential for the future study to capture CTCs which are released from tumor tissue and for drug delivery, and these results demonstrate that the antibody-conjugated A-MNPs can be used in magnetic hyperthermia techniques for cancer treatment.

Keywords: tumor tissue, antibody, magnetic nanoparticle, CTCs capturing

Procedia PDF Downloads 360

Authors: Youn Young Shim, Ji Hye Kim, Jae Youl Cho, Martin JT Reaney

Abstract:

Flaxseed (Linumusitatissimum L.) is gaining popularity in the food industry as a superfood due to its health-promoting properties. Linusorbs (LOs, a.k.a. Cyclolinopeptide) are bioactive compounds present in flaxseed exhibiting potential health effects. The study focused on the effects of processing and storage on the stability of flaxseed-derived LOs added to various bakery products. The flaxseed meal fortified gluten-free (GF) bakery bread was prepared, and the changes of LOs during the bread-making process (meal, fortified flour, dough, and bread) and storage (0, 1, 2, and 4 weeks) at different temperatures (−18 °C, 4 °C, and 22−23 °C) were analyzed by high-performance liquid chromatography-diode array detection. The total oxidative LOs and LO1OB2 were almost kept stable in flaxseed meals at storage temperatures of 22−23 °C, −18 °C, and 4 °C for up to four weeks. Processing steps during GF-bread production resulted in the oxidation of LOs. Interestingly, no LOs were detected in the dough sample; however, LOs appeared when the dough was stored at −18 °C for one week, suggesting that freezing destroyed the sticky structure of the dough and resulted in the release of LOs. The final product, flaxseed meal fortified bread, could be stored for up to four weeks at −18 °C and 4 °C, and for one week at 22−23 °C. All these results suggested that LOs may change during processing and storage and that flaxseed flour-fortified bread should be stored at low temperatures to preserve effective LOs components.

Keywords: linum usitatissimum L., flaxseed, linusorb, stability, gluten-free, peptides, cyclolinopeptide

Procedia PDF Downloads 179

Authors: A. Ghodbane, M. Saad, J. F. Boland, C. Thibeault

Abstract:

Historically, actuators’ redundancy was used to deal with faults occurring suddenly in flight systems. This technique was generally expensive, time consuming and involves increased weight and space in the system. Therefore, nowadays, the on-line fault diagnosis of actuators and accommodation plays a major role in the design of avionic systems. These approaches, known as Fault Tolerant Flight Control systems (FTFCs) are able to adapt to such sudden faults while keeping avionics systems lighter and less expensive. In this paper, a (FTFC) system based on the Geometric Approach and a Reconfigurable Flight Control (RFC) are presented. The Geometric approach is used for cosmic ray fault reconstruction, while Sliding Mode Control (SMC) based on Lyapunov stability theory is designed for the reconfiguration of the controller in order to compensate the fault effect. Matlab®/Simulink® simulations are performed to illustrate the effectiveness and robustness of the proposed flight control system against actuators’ faulty signal caused by cosmic rays. The results demonstrate the successful real-time implementation of the proposed FTFC system on a non-linear 6 DOF aircraft model.

Keywords: actuators’ faults, fault detection and diagnosis, fault tolerant flight control, sliding mode control, geometric approach for fault reconstruction, Lyapunov stability

Procedia PDF Downloads 418

Authors: Shaik Ayesha Fathima, Shaik Noor Jahan, Duvvada Rajeswara Rao

Abstract:

Earth's environment and its evolution can be seen through satellite images in near real-time. Through satellite imagery, remote sensing data provide crucial information that can be used for a variety of applications, including image fusion, change detection, land cover classification, agriculture, mining, disaster mitigation, and monitoring climate change. The objective of this project is to propose a method for classifying satellite images according to multiple predefined land cover classes. The proposed approach involves collecting data in image format. The data is then pre-processed using data pre-processing techniques. The processed data is fed into the proposed algorithm and the obtained result is analyzed. Some of the algorithms used in satellite imagery classification are U-Net, Random Forest, Deep Labv3, CNN, ANN, Resnet etc. In this project, we are using the DeepLabv3 (Atrous convolution) algorithm for land cover classification. The dataset used is the deep globe land cover classification dataset. DeepLabv3 is a semantic segmentation system that uses atrous convolution to capture multi-scale context by adopting multiple atrous rates in cascade or in parallel to determine the scale of segments.

Keywords: area calculation, atrous convolution, deep globe land cover classification, deepLabv3, land cover classification, resnet 50

Procedia PDF Downloads 139

Authors: Rania A. R. Soudan, Easter Joury

Abstract:

Introduction: Psoriasis is a common chronic dermatologic disease. It may affect the mucous membranes. The presence of oral mucosal lesions has been a subject of controversy. The aim: To determine possible association between oral mucosal lesions and psoriasis, and to correlate the same with different types of psoriasis and severity of the disease. Materials and Methods: The oral mucosa was clinically examined in 100 randomly selected Syrian psoriatic patients presented to the Dermatological Diseases Hospital in Damascus University, Syria (February 2009 - December 2010), and in 100 matched controls. PASI index was used to evaluate the disease severity. Chi-square and Student t-test were used to compare differences between groups. Results: Oral mucosal lesions were observed in 72% of the psoriasis cases, while 46% of the control group’s subjects had oral lesions. Fissured tongue, geographic tongue, and red lesions were detected in 36%, 25%, and 7% of the examined psoriatics, respectively. These lesions were significantly more frequent in the psoriatics than in the controls. A correlation was found between furred tongue and the age of the psoriasis patients. However, an association was observed for fissured tongue, furred tongue with the severity of the disease, and for fissured tongue, white lesions, cheilitis with nail involvement. However, no correlation with the psoriasis types was recorded. Conclusion: Some oral mucosal lesions were associated with psoriasis, so these lesions may be considered as oral manifestations of this disease, and should be taken into account in new studies as possible predictors or markers of this dermatitis. Further studies are recommended to confirm these oral manifestations.

Keywords: psoriasis, tongue, mucosa, lesions

Procedia PDF Downloads 292

Authors: Libor Zachoval, Daire O Broin, Oisin Cawley

Abstract:

E-learning platforms, such as Blackboard have two major shortcomings: limited data capture as a result of the limitations of SCORM (Shareable Content Object Reference Model), and lack of incorporation of Artificial Intelligence (AI) and machine learning algorithms which could lead to better course adaptations. With the recent development of Experience Application Programming Interface (xAPI), a large amount of additional types of data can be captured and that opens a window of possibilities from which online education can benefit. In a corporate setting, where companies invest billions on the learning and development of their employees, some learner behaviours can be troublesome for they can hinder the knowledge development of a learner. Behaviours that hinder the knowledge development also raise ambiguity about learner’s knowledge mastery, specifically those related to gaming the system. Furthermore, a company receives little benefit from their investment if employees are passing courses without possessing the required knowledge and potential compliance risks may arise. Using xAPI and rules derived from a state-of-the-art review, we identified three learner behaviours, primarily related to guessing, in a corporate compliance course. The identified behaviours are: trying each option for a question, specifically for multiple-choice questions; selecting a single option for all the questions on the test; and continuously repeating tests upon failing as opposed to going over the learning material. These behaviours were detected on learners who repeated the test at least 4 times before passing the course. These findings suggest that gauging the mastery of a learner from multiple-choice questions test scores alone is a naive approach. Thus, next steps will consider the incorporation of additional data points, knowledge estimation models to model knowledge mastery of a learner more accurately, and analysis of the data for correlations between knowledge development and identified learner behaviours. Additional work could explore how learner behaviours could be utilised to make changes to a course. For example, course content may require modifications (certain sections of learning material may be shown to not be helpful to many learners to master the learning outcomes aimed at) or course design (such as the type and duration of feedback).

Keywords: artificial intelligence, corporate e-learning environment, knowledge maintenance, xAPI

Procedia PDF Downloads 121

Authors: Nivon P. Alejandra, Valencia P. L. Rodrigo, Vivanco V. Martin, Morita A. Adelina

Abstract:

Technological innovation is fundamental to reach and maintain the levels of competitiveness of agricultural producers, the detection of actors, their activities, resources and capacities of an innovation system is needed for the development of technological packages that adapt to each type of crops, local circumstances and characteristics of the producer. The growing development of the viticulture and wine sector in Mexico prospects an increase in its national market participation for 2020, this is the reason to consider it a fertile field for the technological packages adoption that promote Precision Agriculture (PA) in a harmonic and sustainable development. A viability inspection of technological packages adoption by viticulture and wine sector is made following the methodology proposed by SAGARPA in 2015 and the World Bank in 2008: the history, actors, strengths and opportunities are analyzed in this particular agroindustrial sector, also its technological innovation system is inspected in order to improve technological capacities and innovation networks taking into account local and regional resources. PA and technological packages adoption can help improving the conditions and quality of the grape for winemaking: increasing the wine's storage potential and its nutraceutical nature. The assertive diagnosis in vineyard opportunity areas will help the management of the crop by applying natural treatments at the right time in the right place.

Keywords: technological packages, precision farming, sustainable development, innovation

Procedia PDF Downloads 198

Authors: Sundaresan Sivapatham, B. Prabhu

Abstract:

Cancer results from a multistage, multi-mechanism carcinogenesis process that involves mutagenic, cell death and epigenetic mechanisms, during the three distinguishable but closely allied stages: initiation, promotion, and progression. Chemoprevention is promising in the realm of cancer prevention and it has been shown to reduce the risk of development of carcinoma in highly susceptible individuals such as those with known genetic mutations or high level of risk factors. The present study is aimed at the need of early detection of bladder cancer in order to improve performance in the treatment of this disease. Consumption of certain natural products like DIM is associated with a reduction in cancer incidence in humans. The study showed the protective effects of Diindolylmethane in N-Butyl-N-(4-hydroxybutyl) nitrosamine treated rats. Results of the study had shown the changes in the tumor markers, biomarkers and histopathological alterations in experimental rats when compared to control rats. The protective effects of DIM were shown from the results of cell proliferation, apoptotic markers and histopathological findings when compared with experimental control animals. Hence, our results speculate that the tumor markers, apoptotic markers, histopathological changes and cell proliferation index measured as PCNA serves as an indicator suggestive of protective effects of DIM in BBN induced urinary bladder carcinogenesis.

Keywords: bladder cancer, N-Butyl-N-(4-hydroxybutyl) nitrosamine, diindolylmethane, histopathology

Procedia PDF Downloads 342

Authors: Charbel Aoun, Loic Lagadec

Abstract:

A Sensor Network (SN) is considered as an operation of two phases: (1) the observation/measuring, which means the accumulation of the gathered data at each sensor node; (2) transferring the collected data to some processing center (e.g., Fusion Servers) within the SN. Therefore, an underwater sensor network can be defined as a sensor network deployed underwater that monitors underwater activity. The deployed sensors, such as Hydrophones, are responsible for registering underwater activity and transferring it to more advanced components. The process of data exchange between the aforementioned components perfectly defines the Marine Observatory (MO) concept which provides information on ocean state, phenomena and processes. The first step towards the implementation of this concept is defining the environmental constraints and the required tools and components (Marine Cables, Smart Sensors, Data Fusion Server, etc). The logical and physical components that are used in these observatories perform some critical functions such as the localization of underwater moving objects. These functions can be orchestrated with other services (e.g. military or civilian reaction). In this paper, we present an extension to our MO meta-model that is used to generate a design tool (ArchiMO). We propose new constraints to be taken into consideration at design time. We illustrate our proposal with an example from the MO domain. Additionally, we generate the corresponding simulation code using our self-developed domain-specific model compiler. On the one hand, this illustrates our approach in relying on Enterprise Architecture (EA) framework that respects: multiple views, perspectives of stakeholders, and domain specificity. On the other hand, it helps reducing both complexity and time spent in design activity, while preventing from design modeling errors during porting this activity in the MO domain. As conclusion, this work aims to demonstrate that we can improve the design activity of complex system based on the use of MDE technologies and a domain-specific modeling language with the associated tooling. The major improvement is to provide an early validation step via models and simulation approach to consolidate the system design.

Keywords: smart sensors, data fusion, distributed fusion architecture, sensor networks, domain specific modeling language, enterprise architecture, underwater moving object, localization, marine observatory, NS-3, IMS

Procedia PDF Downloads 177

Authors: Mohammad Abdel Fattah Mohammad Kewisha

Abstract:

Microbial deterioration of ancient materials became one of the biggest problems facing the workers in the field of cultural heritage protection because the microbial deterioration of artifacts causes detrimental effects on the aesthetic value of the monuments due to colonization, whether they are made of inorganic materials such as stone or organic like wood, textiles, wall paintings, and paper. So, the early identification of the bacterial strains that caused deterioration is the most important point for the protection of monument objects. The present study focuses on the Bacillus spp. group, which was isolated from some biodeterioration monuments from different areas of Egypt. The investigated objects in this study were made from organic materials (cellulose), paper, textile, and wood. Isolated strains were identified up to the species level biochemically. Eleven bacterial isolates were obtained from collected samples. They were taken from different archaeological objects, four microbicides, cetrimonium bromide, sodium azide, tetraethyl ammonium bromide, and dichloroxylenol, at various concentrations ranging from 25 ppm to 500 ppm. They were screened for their antibacterial activity against the Bacillus spp. isolates, and detection of Minimum inhibitory concentration (MIC). It was also necessary to indicate the ideal Minimum inhibitory concentration for each strain for the purpose of biotreatment of the infected monuments with less damaging effect on monument materials.

Keywords: microbial deterioration, ancient materials, heritage protection, protection of monuments, biodeteriorative monuments

Procedia PDF Downloads 60

Authors: Shih-Fang Lo, Tzu-Wei Guo, Chih-Hsuan Lee

Abstract:

Tropical fisheries are vulnerable to the physical and biogeochemical oceanic changes associated with climate change. Warmer temperatures and extreme weather have beendamaging the abundance and growth patterns of aquatic organisms. In recent year, the shrinking of fish stock and labor shortage have increased the threat to global aquacultural production. Thus, building a climate-resilient and sustainable mechanism becomes an urgent, important task for global citizens. To tackle the problem, Taiwanese fishermen applies the artificial intelligence (AI) technology. In brief, the AI system (1) measures real-time water quality and chemical parameters infish ponds; (2) monitors fish stock through segmentation, detection, and classification; and (3) implements fishermen’sprevious experiences, perceptions, and real-life practices. Applying this system can stabilize the aquacultural production and potentially increase the labor force. Furthermore, this AI technology can build up a more resilient and sustainable system for the fishermen so that they can mitigate the influence of extreme weather while maintaining or even increasing their aquacultural production. In the future, when the AI system collected and analyzed more and more data, it can be applied to different regions of the world or even adapt to the future technological or societal changes, continuously providing the most relevant and useful information for fishermen in the world.

Keywords: aquaculture, artificial intelligence (AI), real-time system, sustainable fishery

Procedia PDF Downloads 111

Authors: Anthony Proschka, Deepak Mishra, Merlyn Ramanan, Zurab Baratashvili

Abstract:

Small and medium-sized businesses receive over 160 billion invoices every year. Since these documents exhibit many subtle differences in layout and text, extracting structured fields such as sender name, amount, and VAT rate from them automatically is an open research question. In this paper, existing work in template-based document extraction is extended, and a system is devised that is able to reliably extract all required fields for up to 70% of all documents in the data set, more than any other previously reported method. The approaches are described for 1) detecting through visual features which template a given document belongs to, 2) automatically generating extraction rules for a given new template by composing regular expressions from multiple components, and 3) computing confidence scores that indicate the accuracy of the automatic extractions. The system can generate templates with as little as one training sample and only requires the ground truth field values instead of detailed annotations such as bounding boxes that are hard to obtain. The system is deployed and used inside a commercial accounting software.

Keywords: data mining, information retrieval, business, feature extraction, layout, business data processing, document handling, end-user trained information extraction, document archiving, scanned business documents, automated document processing, F1-measure, commercial accounting software

Procedia PDF Downloads 130

Authors: Bouaziz Amira, Zaatout Nawel

Abstract:

Background: Antimicrobial resistance is an urgent global health challenge in human and veterinary medicine, where migratory birds play a major role in the dissemination of multi-drug-resistant bacteria. The aim of this study was to screen for the presence of carbapenemase-producing Gram-negative bacteria (GNB) in the little egret (Egrettagarzetta) migratory bird stools in Algeria. Materials/Methods: In January 2014, 12 feacal samples were collected in Garaet El-Tarf, Oum El-Bouaghi city, Algeria. Samples were subjected to selective isolation of carbapenem-resistant GNB. Representative colonies were identified using the VITEK system. The obtained isolates were subjected to antibiotic susceptibility testing using the disc-diffusion method as well as carbapenemase production was verified by the modified Carba NP test. Results: In total, ten E. coli were obtained and were resistant to amoxicillin/clavulanic acid (100%), ertapenem (70%), cefoxitin (60%) cefotaxime (20%), cefepime (20%), ciprofloxacin (20%) and aztreonam (10%). The phenotypic detection results revealed that six out of the obtained strains were positive for the modified Carba NP test. Conclusion: The present study suggests that the little egret (Egretta garzetta) could be considered a reservoir of carbapenem-resistant Gram-negative bacteria.

Keywords: antimicrobial resistance, E. coli, Egretta garzetta, carbapenem resistance, dissemination

Procedia PDF Downloads 7

Authors: Kambiz Teimour Najad

Abstract:

The basic methodology of GPR involves the use of a transmitting antenna to send electromagnetic waves into the subsurface, which then bounce back to the surface and are detected by a receiving antenna. The transmitter and receiver antennas are typically placed on the ground surface and moved across the area of interest to create a profile of the subsurface. The GPR system consists of a control unit that powers the antennas and records the data, as well as a display unit that shows the results of the survey. The control unit sends a pulse of electromagnetic energy into the ground, which propagates through the soil or rock until it encounters a change in material or structure. When the electromagnetic wave encounters a buried object or structure, some of the energy is reflected back to the surface and detected by the receiving antenna. The GPR data is then processed using specialized software that analyzes the amplitude and travel time of the reflected waves. By interpreting the data, GPR can provide information on the depth, location, and nature of subsurface features and structures. GPR has several advantages over other geophysical survey methods, including its ability to provide high-resolution images of the subsurface and its non-invasive nature, which minimizes disruption to the site. However, the effectiveness of GPR depends on several factors, including the type of soil or rock, the depth of the features being investigated, and the frequency of the electromagnetic waves used. In environmental hazard assessments, GPR can be used to detect buried structures, such as underground storage tanks, pipelines, or utilities, which may pose a risk of contamination to the surrounding soil or groundwater. GPR can also be used to assess soil stability by identifying areas of subsurface voids or sinkholes, which can lead to the collapse of the surface. Additionally, GPR can be used to map the extent and movement of groundwater contamination, which is critical in designing effective remediation strategies. the methodology of GPR in environmental hazard assessments involves the use of electromagnetic waves to create high of the subsurface, which are then analyzed to provide information on the depth, location, and nature of subsurface features and structures. This information is critical in identifying and mitigating environmental hazards, and the non-invasive nature of GPR makes it a valuable tool in this field.

Keywords: GPR, hazard, landslide, rock fall, contamination

Procedia PDF Downloads 82

Authors: Mohammad Ali Karimi, Hossein Tavallali, Abdolhamid Hatefi-Mehrjardi

Abstract:

In this study, an electrochemical sensor based on gold nanoparticles (AuNPs) functionalized improved graphene (AuNPs-IGE) was fabricated for selective determination of L-dopa in the presence of ascorbic acid by a novel self-assembly method. The AuNP IGE modified carbon paste electrode (AuNPs-IGE/CPE) utilized for investigation of the electrochemical behavior of L-dopa in phosphate buffer solution. Compared to bare CPE, AuNPs-IGE/CPE shows novel properties towards the electrochemical redox of levodopa (L-dopa) in phosphate buffer solution at pH 4.0. The oxidation potential of L-dopa shows a significant decrease at the AuNPs-IGE/CPE. The oxidation current of L-dopa is higher than that of the unmodified CPE. AuNPs-IG/CPE shows excellent electrocatalytic activity for the oxidation of ascorbic acid (AA). Using differential pulse voltammetry (DPV) method, the oxidation current is well linear with L-dopa concentration in the range of 0.4–50 µmol L-1, with a detection limit of about 1.41 nmol L-1 (S/N = 3). Therefore, it was applied to measure L-dopa from real samples that recoveries are 94.6-106.2%. The proposed electrode can also effectively avoid the interference of ascorbic acid, making the proposed sensor suitable for the accurate determination of L-dopa in both pharmaceutical preparations and human body fluids.

Keywords: gold nanoparticles, improved graphene, L-dopa, self-assembly

Procedia PDF Downloads 221

Authors: Youn Young Shim, Martin J. T. Reaney

Abstract:

Flaxseed meal is rich in water-soluble gums and, as such, can improve texture in gluten-free products. Flaxseed bioactive-antioxidant peptides, linusorbs (LOs, a.k.a. cyclolinopeptides), are a class of molecules that may contribute health-promoting effects. The effects of dough preparation, baking, and storage on flaxseed-derived LOs stability in doughs and baked products are un-known. Gluten-free (GF) bread dough and bread were prepared with flaxseed meal and the LO content was determined in the flaxseed meal, bread flour containing the flaxseed meal, bread dough, and bread. The LO contents during storage (0, 1, 2, and 4 weeks) at different temperatures (−18 °C, 4 °C, and 22−23 °C) were determined by high-performance liquid chromatog-raphy-diode array detection (HPLC-DAD). The content of oxidized LOs like [1–9-NαC],[1(Rs, Ss)-MetO]-linusorb B2 (LO14) were substantially constant in flaxseed meal and flour produced from flaxseed meal under all conditions for up to 4 weeks. However, during GF-bread production LOs decreased. Due to microbial contamination dough could not be stored at either 4 or 21°C, and bread could only be stored for one week at 21°C. Up to 4 weeks storage was possible for bread and dough at −18 °C and bread at 4 °C without the loss of LOs. The LOs change mostly from processing and less so from storage. The concentration of reduced LOs in flour and meal were much higher than measured in dough and bread. There was not a corre-sponding increase in oxidized LOs. The LOs in flaxseed meal-fortified bread were stable for products stored at low temperatures. This study is the first of the impact of baking conditions on LO content and quality.

Keywords: flaxseed, stability, gluten-free, antioxidant

Procedia PDF Downloads 88

Authors: Alia Ali, Azeem Taj, Muhammed Joher Amin, Farrukh Iqbal, Zafar Iqbal

Abstract:

Background: Hypertension is commonly found in patients with Diabetic Kidney Disease (DKD). Microalbuminuria is the first clinical sign of involvement of kidneys in patients with type 2 diabetes. Uncontrolled hypertension induces a higher risk of cardiovascular events, including death, increasing proteinuria and progression to kidney disease. Objectives: To determine the correlation between microalbuminuria and hypertension and their association with other risk factors in type 2 diabetic patients. Methods: One hundred and thirteen type 2 diabetic patients were screened for microalbuminuria and raised blood pressure, attending the diabetic clinic of Shaikh Zayed Hospital, Lahore, Pakistan. The study was conducted from November 2012 to June 2013. Results: Patients were divided into two groups. Group 1, those with normoalbuminuria (n=63) and Group 2, those having microalbuminuria (n=50). Group 2 patients showed higher blood pressure values as compared to Group 1. The results were statistically significant and showed poor glycemic control as a contributing risk factor. Conclusion: The study concluded that there is high frequency of hypertension among type 2 diabetics but still much higher among those having microalbuminuria. So, early recognition of renal dysfunction through detection of microalbuminuria and to start treatment without any delay will confer future protection from end-stage renal disease as well as hypertension and its complications in type 2 diabetic patients.

Keywords: hypertension, microalbuminuria, diabetic kidney disease, type 2 Diabetes mellitus

Procedia PDF Downloads 396

Authors: Moussa I. Mohamed, Turki, K. A. Al-Faraj, Abdullah A. Al-Arfaj, Ashgan M. Hessain

Abstract:

The objective of the present study is to detect the incidences of Salmonella enterica from different poultry farms located in Egypt on molecular basis. During the summer of 2012, a total of 1800 cloacal swabs were collected from poultry farms located I Cairo, Egypt to be subjected for isolation of Salmonella enteric. Moreover, a total of 300 samples of poultry and poultry products were collected from different retail establishment markets in Cairo, Egypt including, 150 local whole frozen chickens, 50 imported whole frozen chickens, 100 local chicken cut samples. The highest rate of isolation 8% was obtained from imported frozen chickens and local chicken cuts, followed by local frozen chickens 6.66% and finally rectal swabs from apparently health chickens 6.4 %. Salmonella Typhimurium and Salmonella Enteritidis were most frequent among the total Salmonella isolates. Multiplex-PCR for the rapid detection of Salmonella Typhimurium and Salmonella Enteritidis from field samples especially after pre-enrichment on Rappaport-Vassiliadis (RV) selective broth (PCR-RV), revealed the same positive samples. Therefore PCR-RV technique is rabid, time saving and applicable to detect Salmonella serovars directly from chicken samples. Moreover, detecting Salmonella Typhimurium and Salmonella Enteritidis by this assay was carried out within 2 days opposed to 5–6 d by the bacteriological and serological methods.

Keywords: Salmonella enterica, Salmonella typhimurium, Salmonella enteritidis enrichment, multiplex-PCR

Procedia PDF Downloads 374