Search results for: hate speech detection

Authors: M. Y. Lee, D. H. Shin, S. H. Park, W.C. Ham, S.K. Ko, C. G. Song

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Photoacoustic Tomography (PAT) is a promising medical imaging modality that combines optical imaging contrast with the spatial resolution of ultrasound imaging. It can also distinguish the changes in biological features. But, real-time PAT system should be confirmed due to photoacoustic effect for tissue. Thus, we have developed a real-time PAT system using a custom-developed data acquisition board and ultrasound linear probe. To evaluate performance of our system, phantom test was performed. As a result of those experiments, the system showed satisfactory performance and its usefulness has been confirmed. We monitored the degradation of inflammation which induced on the rat’s kidney using real-time PAT.

Keywords: photoacoustic tomography, inflammation detection, rat, kidney, contrast agent, ultrasound

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Authors: Sadeq Al Yaari, Ayman Al Yaari, Adham Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Sajedah Al Yaari

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Background & Objectives: Audio-visual aids and computer-assisted language instruction (CALI) effects are strong in teaching language components (sound system, grammatical structures and vocabulary) to students of special needs. To explore the effects of the audio-visual aids and CALI in teaching sound system to this class of students by speech language therapists (SLTs), an experiment has been undertaken to evaluate their performance during their study of the sound system course. Methods: Forty students (males and females) of special needs at al-Malādh school for teaching students of special needs in Dhamar (Yemen) range between 8 and 18 years old underwent this experimental study while they were studying language sound system course. Pre-and-posttests have been administered at the begging and end of the semester. Students' treatment was compared to a similar group (control group) of the same number under the same environment. Whereas the first group was taught using audio-visual aids and CALI, the second was not. Students' performances were linguistically and statistically evaluated. Results & conclusions: Compared with the control group, the treatment group showed significantly higher scores in the posttest (72.32% vs. 31%). Compared with females, males scored higher marks (1421 vs. 1472). Thus, we should take the audio-visual aids and CALI into consideration in teaching sound system to students of special needs.

Keywords: language components, sound system, audio-visual aids, CALI, students, special needs, SLTs

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Authors: M. Jebali, M. Jemni

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This work is the part of vision based hand gesture recognition system for Natural Human Computer Interface. Hand tracking and segmentation are the primary steps for any hand gesture recognition system. The aim of this paper is to develop robust and efficient hand segmentation algorithm such as an input to another system which attempt to bring the HCI performance nearby the human-human interaction, by modeling an intelligent sign language recognition system based on prediction in the context of dialogue between the system (avatar) and the interlocutor. For the purpose of hand segmentation, an overcoming occlusion approach has been proposed for superior results for detection of hand from an image.

Keywords: HCI, sign language recognition, object tracking, hand segmentation

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Authors: Tannistha Dasgupta

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This study explores the aspects of second language (L2) spoken fluency that are related to L2 linguistic knowledge and processing skill. It draws on Levelt’s ‘blueprint’ of the L2 speaker which discusses the cognitive issues underlying the act of speaking. However, L2 speaking assessments have largely neglected the underlying mechanism involved in language production; emphasis is given on the relationship between subjective ratings of L2 speech sample and objectively measured aspects of fluency. Hence, in this study, the relation between L2 linguistic knowledge and processing skill i.e. Cognitive Fluency (CF), and objectively measurable aspects of L2 spoken fluency i.e. Utterance Fluency (UF) is examined. The participants of the study are L2 learners of English, studying at high school level in Hyderabad, India. 50 participants with intermediate level of proficiency in English performed several lexical retrieval tasks and attention-shifting tasks to measure CF, and 8 oral tasks to measure UF. Each aspect of UF (speed, pause, and repair) were measured against the scores of CF to find out those aspects of UF which are reliable indicators of CF. Quantitative analysis of the data shows that among the three aspects of UF; speed is the best predictor of CF, and pause is weakly related to CF. The study suggests that including the speed aspect of UF could make L2 fluency assessment more reliable, valid, and objective. Thus, incorporating the assessment of psycholinguistic mechanisms into L2 spoken fluency testing, could result in fairer evaluation.

Keywords: attention-shifting, cognitive fluency, lexical retrieval, utterance fluency

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Authors: Emily Purdom, Rachel Robinson

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As the number of students worldwide requiring speech-language therapy, occupational therapy and mental health services during their school day increases, innovation is becoming progressively more important to meet the demand. Telepractice can be used to reach a greater number of students requiring specialized therapy while maintaining the highest quality of care. It can be provided in a way that is not only effective but ultimately more convenient for student, teacher and therapist without the added burden of travel. Teletherapy eradicates many hurdles to traditional on-site service delivery and helps to solve the pervasive shortage of certified professionals. Because location is no longer a barrier to specialized education plans for students with disabilities when teletherapy is conducted, there are many advantages that can be deployed. Increased frequency of engagement is possible along with students receiving specialized care from a clinician that may not be in their direct area. Educational teams, including parents, can work together more easily and engage in face-to-face, student-centered collaboration through videoconference. Practical strategies will be provided for connecting students with qualified therapists without the typical in-person dynamic. In most cases, better therapy outcomes are going to be achieved when treatment is most convenient for the student and educator. This workshop will promote discussion in the field of education to increase advocacy for remote service delivery. It will serve as a resource for those wanting to expand their knowledge of options for students with special needs afforded through innovation.

Keywords: education technology, innovation, student support services, telepractice

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Authors: Tshegofatso Rambau, Tonderai Muchenje

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Zero-day attacks (ZDA) are increasing day by day; there are many vulnerabilities in systems and software that date back decades. Companies keep discovering vulnerabilities in their systems and software and work to release patches and updates. A zero-day vulnerability is a software fault that is not widely known and is unknown to the vendor; attackers work very quickly to exploit these vulnerabilities. These are major security threats with a high success rate because businesses lack the essential safeguards to detect and prevent them. This study focuses on the factors and techniques that can help us detect zero-day attacks. There are various methods and techniques for detecting vulnerabilities. Various companies like edges can offer penetration testing and smart vulnerability management solutions. We will undertake literature studies on zero-day attacks and detection methods, as well as modeling approaches and simulations, as part of the study process.

Keywords: zero-day attacks, exploitation, vulnerabilities

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Authors: Sundus Ayyaz, Saad Rehman, Usman Qamar

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Software Architecture is the basic structure of software that states the development and advancement of a software system. Software architecture is also considered as a significant tool for the construction of high quality software systems. A clean design leads to the control, value and beauty of software resulting in its longer life while a bad design is the cause of architectural erosion where a software evolution completely fails. This paper discusses the occurrence of software architecture erosion and presents a set of methods for the detection, declaration and prevention of architecture erosion. The causes and symptoms of architecture erosion are observed with the examples of prescriptive and descriptive architectures and the practices used to stop this erosion are also discussed by considering different types of software erosion and their affects. Consequently finding and devising the most suitable approach for fighting software architecture erosion and in some way reducing its affect is evaluated and tested on different scenarios.

Keywords: software architecture, architecture erosion, prescriptive architecture, descriptive architecture

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Authors: Akankunda Veronicah Karuhanga

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Dementia is an age mental disorder that makes victims lose normal functionality that needs delicate attention. It has been technically defined as a clinical syndrome that presents a number of difficulties in speech and other cognitive functions that change someone’s behaviors and can also cause impairments in activities of daily living, not forgetting a range of neurological disorders that bring memory loss and cognitive impairment. Family members are the primary healthcare givers and therefore, the way how they handle the situation in its early stages determines future deterioration syndromes like total memory loss. Unfortunately, most family members are ignorant about this condition and in most cases, the patients are brought to our facilities when their condition was already mismanaged by family members and we thus cannot do much. For example, incontinence can be managed at early stages through potty training or toilet scheduling before resorting to 24/7 diapers which are also not good. Professional Elderly care should be understood and practiced as an extension of homes, not a dumping place for people considered “abnormal” on account of ignorance. Immediate relatives should therefore be sensitized concerning the normalcy of dementia in the context of old age so that they can be understanding and supportive of dementia patients rather than discriminating against them as present-day lepers. There is a need to skill home-based caregivers on how to handle dementia in its early stages. Unless this is done, many of our elderly homes shall be filled with patients who should have been treated and supported from their homes. This skilling of home-based caregivers is a vital intervention because until elderly care is appreciated as a human moral obligation, many transactional rehabilitation centers will crop up and this shall be one of the worst moral decadences of our times.

Keywords: dementia, family, Alzheimers, relevancy

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Authors: R. Sanchez-Salcedo, N. H. Voelcker

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Currently, low breast milk production in women is one of the leading health complications in infants. Recently, It has been demonstrated that exclusive breastfeeding, especially up to a minimum of 6 months, significantly reduces respiratory and gastrointestinal infections, which are the main causes of death in infants. However, the current data shows that a high percentage of women stop breastfeeding their children because they perceive an inadequate supply of milk, and only 45% of children are breastfeeding under 6 months. It is, therefore, clear the necessity to design and develop a biosensor that is sensitive and selective enough to identify and validate a panel of milk biomarkers that allow the early diagnosis of this condition. In this context, electrochemical biosensors could be a powerful tool for assessing all the requirements in terms of reliability, selectivity, sensitivity, cost efficiency and potential for multiplex detection. Moreover, they are suitable for the development of POC devices and wearable sensors. In this work, we report the development of two types of sensing platforms towards several biomarkers, including miRNAs and hormones present in breast milk and dysregulated in this pathological condition. The first type of sensing platform consists of an enzymatic sensor for the detection of lactose, one of the main components in milk. In this design, we used gold surface as an electrochemical transducer due to the several advantages, such as the variety of strategies available for its rapid and efficient functionalization with bioreceptors or capture molecules. For the second type of sensing platform, nanoporous silicon film (pSi) was chosen as the electrode material for the design of DNA sensors and aptasensors targeting miRNAs and hormones, respectively. pSi matrix offers a large superficial area with an abundance of active sites for the immobilization of bioreceptors and tunable characteristics, which increase the selectivity and specificity, making it an ideal alternative material. The analytical performance of the designed biosensors was not only characterized in buffer but also validated in minimally treated breastmilk samples. We have demonstrated the potential of an electrochemical transducer on pSi and gold surface for monitoring clinically relevant biomarkers associated with the heightened risk of low milk production in women. This approach, in which the nanofabrication techniques and the functionalization methods were optimized to increase the efficacy of the biosensor highly provided a foundation for further research and development of targeted diagnosis strategies.

Keywords: biosensors, electrochemistry, early diagnosis, clinical markers, miRNAs

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Authors: Kangkang Wu, Kaizhi Wang, Zhijun Yuan

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This paper deals with a mini radar system aimed at detecting small targets at the low latitude. The radar operates at Ku-band in the frequency modulated continuous wave (FMCW) mode with two receiving channels. The radar system has the characteristics of compactness, mobility, and low power consumption. This paper focuses on the implementation of the radar system, and the Block least mean square (Block LMS) algorithm is applied to minimize the fortuitous distortion. It is validated from a series of experiments that the track of the unmanned aerial vehicle (UAV) can be easily distinguished with the radar system.

Keywords: unmanned aerial vehicle (UAV), interference, Block Least Mean Square (Block LMS) Algorithm, Frequency Modulated Continuous Wave (FMCW)

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Authors: Prabhakar Sathujoda

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Vibration analysis of a misaligned rotor coupling bearing system has been carried out while decelerating through its critical speed. The finite element method (FEM) is used to model the rotor system and simulate flexural vibrations. A flexible coupling with a frictionless joint is considered in the present work. The continuous wavelet transform is used to extract the misalignment features from the simulated time response. Subcritical speeds at one-half, one-third, and one-fourth the critical speed have appeared in the wavelet transformed vibration response of a misaligned rotor coupling bearing system. These features are also verified through a parametric study.

Keywords: Continuous Wavelet Transform, Flexible Coupling, Rotor System, Sub Critical Speed

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Authors: Desouky Abd El Haleem, Sahar Zaki

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This work was conducted to develop a one-step multiplex PCR system for rapid, sensitive, and specific detection of three different bacterial pathogens, Escherichia coli, Pseudomonas aeruginosa, and Salmonella spp, directly in wastewater without prior isolation on selective media. As a molecular confirmatory test after isolation of the pathogens by classical microbiological methods, PCR-RFLP of their amplified 16S rDNA genes was performed. It was observed that the developed protocols have significance impact in the ability to detect sensitively, rapidly and specifically the three pathogens directly in water within short-time, represents a considerable advancement over more time-consuming and less-sensitive methods for identification and characterization of these kinds of pathogens.

Keywords: multiplex PCR, bacterial pathogens, Escherichia coli, Pseudomonas aeruginosa, Salmonella spp.

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Authors: Harris Niavis, Dimitra Politaki

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The manufacturing industry was collecting vast amounts of data for monitoring product quality thanks to the advances in the ICT sector and dedicated IoT infrastructure is deployed to track and trace the production line. However, industries have not yet managed to unleash the full potential of these data due to defective data collection methods and untrusted data storage and sharing. Blockchain is gaining increasing ground as a key technology enabler for Industry 4.0 and the smart manufacturing domain, as it enables the secure storage and exchange of data between stakeholders. On the other hand, AI techniques are more and more used to detect anomalies in batch and time-series data that enable the identification of unusual behaviors. The proposed scheme is based on smart contracts to enable automation and transparency in the data exchange, coupled with anomaly detection algorithms to enable reliable data ingestion in the system. Before sensor measurements are fed to the blockchain component and the smart contracts, the anomaly detection mechanism uniquely combines artificial intelligence models to effectively detect unusual values such as outliers and extreme deviations in data coming from them. Specifically, Autoregressive integrated moving average, Long short-term memory (LSTM) and Dense-based autoencoders, as well as Generative adversarial networks (GAN) models, are used to detect both point and collective anomalies. Towards the goal of preserving the privacy of industries' information, the smart contracts employ techniques to ensure that only anonymized pointers to the actual data are stored on the ledger while sensitive information remains off-chain. In the same spirit, blockchain technology guarantees the security of the data storage through strong cryptography as well as the integrity of the data through the decentralization of the network and the execution of the smart contracts by the majority of the blockchain network actors. The blockchain component of the Data Traceability Software is based on the Hyperledger Fabric framework, which lays the ground for the deployment of smart contracts and APIs to expose the functionality to the end-users. The results of this work demonstrate that such a system can increase the quality of the end-products and the trustworthiness of the monitoring process in the smart manufacturing domain. The proposed AI-enabled data traceability software can be employed by industries to accurately trace and verify records about quality through the entire production chain and take advantage of the multitude of monitoring records in their databases.

Keywords: blockchain, data quality, industry4.0, product quality

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Authors: Srinivas Bathini, Duraichelvan Raju, Simona Badilescu, Muthukumaran Packirisamy

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A bio-sensing method, based on the plasmonic property of gold nano-islands, has been developed for detection of exosomes in a clinical setting. The position of the gold plasmon band in the UV-Visible spectrum depends on the size and shape of gold nanoparticles as well as on the surrounding environment. By adsorbing various chemical entities, or binding them, the gold plasmon band will shift toward longer wavelengths and the shift is proportional to the concentration. Exosomes transport cargoes of molecules and genetic materials to proximal and distal cells. Presently, the standard method for their isolation and quantification from body fluids is by ultracentrifugation, not a practical method to be implemented in a clinical setting. Thus, a versatile and cutting-edge platform is required to selectively detect and isolate exosomes for further analysis at clinical level. The new sensing protocol, instead of antibodies, makes use of a specially synthesized polypeptide (Vn96), to capture and quantify the exosomes from different media, by binding the heat shock proteins from exosomes. The protocol has been established and optimized by using a glass substrate, in order to facilitate the next stage, namely the transfer of the protocol to a microfluidic environment. After each step of the protocol, the UV-Vis spectrum was recorded and the position of gold Localized Surface Plasmon Resonance (LSPR) band was measured. The sensing process was modelled, taking into account the characteristics of the nano-island structure, prepared by thermal convection and annealing. The optimal molar ratios of the most important chemical entities, involved in the detection of exosomes were calculated as well. Indeed, it was found that the results of the sensing process depend on the two major steps: the molar ratios of streptavidin to biotin-PEG-Vn96 and, the final step, the capture of exosomes by the biotin-PEG-Vn96 complex. The microfluidic device designed for sensing of exosomes consists of a glass substrate, sealed by a PDMS layer that contains the channel and a collecting chamber. In the device, the solutions of linker, cross-linker, etc., are pumped over the gold nano-islands and an Ocean Optics spectrometer is used to measure the position of the Au plasmon band at each step of the sensing. The experiments have shown that the shift of the Au LSPR band is proportional to the concentration of exosomes and, thereby, exosomes can be accurately quantified. An important advantage of the method is the ability to discriminate between exosomes having different origins.

Keywords: exosomes, gold nano-islands, microfluidics, plasmonic biosensing

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Authors: Sharanya C. H., Pragathi M., Vathsala R. S., Theja K. V., Yashaswini S.

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Identifying counterfeit products have become increasingly important in the product manufacturing industries in recent decades. This current ongoing product issue of counterfeiting has an impact on company sales and profits. To address the aforementioned issue, a functional blockchain technology was implemented, which effectively prevents the product from being counterfeited. By utilizing the blockchain technology, consumers are no longer required to rely on third parties to determine the authenticity of the product being purchased. Blockchain is a distributed database that stores data records known as blocks and several databases known as chains across various networks. Counterfeit products are identified using a QR code reader, and the product's QR code is linked to the blockchain management system. It compares the unique code obtained from the customer to the stored unique code to determine whether or not the product is original.

Keywords: blockchain, ethereum, QR code

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Authors: Muhammad Irfan

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The rise of radicalization within Islam has spawned a new era of global terror. The battlefield Successes of ISIS and the Taliban are fuelled by an ideological war waged, largely and successfully, in the media arena. This research will examine how Islamic extremist groups are using media modalities and populist narratives to influence migrant Muslim populations in Europe towards extremism. In 2014, ISIS shocked the world in exporting horrifically graphic forms of violence on social media. Their Muslim support base was largely disgusted and reviled. In response, they reconfigured their narrative by introducing populist 'hooks', astutely portraying the Muslim populous as oppressed and exploited by unjust, corrupt autocratic regimes and Western power structures. Within this crucible of real and perceived oppression, hundreds of thousands of the most desperate, vulnerable and abused migrants left their homelands, risking their lives in the hope of finding peace, justice, and prosperity in Europe. Instead, many encountered social stigmatization, detention and/or discrimination for being illegal migrants, for lacking resources and for simply being Muslim. This research will examine how Islamic extremist groups are exploiting the disenfranchisement of these migrant populations and using populist messaging on social media to influence them towards violent extremism. ISIS, in particular, formulates specific encoded messages for newly-arriving Muslims in Europe, preying upon their vulnerability. Violence is posited, as a populist response, to the tyranny of European oppression. This research will analyze the factors and indicators which propel Muslim migrants along the spectrum from resilience to violence extremism. Expected outcomes are identification of factors which influence vulnerability towards violent extremism; an early-warning detection framework; predictive analysis models; and de-radicalization frameworks. This research will provide valuable tools (practical and policy level) for European governments, security stakeholders, communities, policy-makers, and educators; it is anticipated to contribute to a de-escalation of Islamic extremism globally.

Keywords: populism, radicalization, de-radicalization, social media, ISIS, Taliban, shariah, jihad, Islam, Europe, political communication, terrorism, migrants, refugees, extremism, global terror, predictive analysis, early warning detection, models, strategic communication, populist narratives, Islamic extremism

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Authors: Cristina Fernandez, Felix Amparano, John Tumberger, Stephani Stancil, Sarah Hampl, Brooke Sweeney, Amy R. Beck, Helena H Laroche, Jared Tucker, Eileen Chaves, Sara Gould, Matthew Lindquist, Lora Edwards, Renee Arensberg, Meredith Dreyer, Jazmine Cedeno, Alleen Cummins, Jennifer Lisondra, Katie Cox, Kelsey Dean, Rachel Perera, Nicholas A. Clark

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Background: Adolescents with obesity are at higher risk of disordered eating than the general population. Detection of eating disorders (ED) is difficult. Screening questionnaires may aid in early detection of ED. Our team’s prior efforts focused on increasing ED screening rates to ≥90% using a validated 10-question adolescent binge eating disorder screening questionnaire (ADO-BED). This aim was achieved. We then aimed to improve treatment plan initiation of patients ≥12 years of age who screen positive for BED within our WMC from 33% to 70% within 12 months. Methods: Our WMC is within a tertiary-care, free-standing children’s hospital. A3, an improvement framework, was used. A multidisciplinary team (physicians, nurses, registered dietitians, psychologists, and exercise physiologists) was created. The outcome measure was documentation of treatment plan initiation of those who screen positive (goal 70%). The process measure was ADO-BED screening rate of WMC patients (goal ≥90%). Plan-Do-Study-Act (PDSA) cycle 1 included provider education on current literature and treatment plan initiation based upon ADO-BED responses. PDSA 2 involved increasing documentation of treatment plan and retrain process to providers. Pre-defined treatment plans were: 1) repeat screen in 3-6 months, 2) resources provided only, or 3) comprehensive multidisciplinary weight management team evaluation. Run charts monitored impact over time. Results: Within 9 months, 166 patients were seen in WMC. Process measure showed sustained performance above goal (mean 98%). Outcome measure showed special cause improvement from mean of 33% to 100% (n=31). Of treatment plans provided, 45% received Plan 1, 4% Plan 2, and 46% Plan 3. Conclusion: Through a multidisciplinary improvement team approach, we maintained sustained ADO-BED screening performance, and, prior to our 12-month timeline, achieved our project aim. Our efforts may serve as a model for other multidisciplinary WMCs. Next steps may include expanding project scope to other WM programs.

Keywords: obesity, pediatrics, clinic, eating disorder

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Authors: Shamatha Shetty, Sakshi Dhabadi, Prerana M., Indushree B.

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About 66% of firms claim that insider attacks are more likely to happen. The frequency of insider incidents has increased by 47% in the last two years. The goal of this work is to prevent dangerous employee behavior by using keyloggers and the Machine Learning (ML) model. Every keystroke that the user enters is recorded by the keylogging program, also known as keystroke logging. Keyloggers are used to stop improper use of the system. This enables us to collect all textual data, save it in a CSV file, and analyze it using an ML algorithm and the VirusTotal API. Many large companies use it to methodically monitor how their employees use computers, the internet, and email. We are utilizing the SVM algorithm and the VirusTotal API to improve overall efficiency and accuracy in identifying specific patterns and words to automate and offer the report for improved monitoring.

Keywords: cyber security, machine learning, cyclic process, email notification

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Authors: Rishabh Ambavanekar

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Expressive Aphasia (EA) is an oral disability, common among stroke victims, in which the Broca’s area of the brain is damaged, interfering with verbal communication abilities. EA currently has no technological solutions and its only current viable solutions are inefficient or only available to the affluent. This prompts the need for an affordable, innovative solution to facilitate recovery and assist in speech generation. This project proposes a novel concept: using a wearable low-cost electroencephalography (EEG) device-based brain-computer interface (BCI) to translate a user’s inner dialogue into words. A low-cost EEG device was developed and found to be 10 to 100 times less expensive than any current EEG device on the market. As part of the BCI, a machine learning (ML) model was developed and trained using the EEG data. Two stages of testing were conducted to analyze the effectiveness of the device: a proof-of-concept and a final solution test. The proof-of-concept test demonstrated an average accuracy of above 90% and the final solution test demonstrated an average accuracy of above 75%. These two successful tests were used as a basis to demonstrate the viability of BCI research in developing lower-cost verbal communication devices. Additionally, the device proved to not only enable users to verbally communicate but has the potential to also assist in accelerated recovery from the disorder.

Keywords: neurotechnology, brain-computer interface, neuroscience, human-machine interface, BCI, HMI, aphasia, verbal disability, stroke, low-cost, machine learning, ML, image recognition, EEG, signal analysis

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Authors: C. Slim

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Traditional techniques for analyzing time series are based on the notion of stationarity of phenomena under study, but in reality most economic and financial series do not verify this hypothesis, which implies the implementation of specific tools for the detection of such behavior. In this paper, we study nonstationary non-seasonal time series tests in a non-exhaustive manner. We formalize the problem of nonstationary processes with numerical simulations and take stock of their statistical characteristics. The theoretical aspects of some of the most common unit root tests will be discussed. We detail the specification of the tests, showing the advantages and disadvantages of each. The empirical study focuses on the application of these tests to the exchange rate (USD/TND) and the Consumer Price Index (CPI) in Tunisia, in order to compare the Power of these tests with the characteristics of the series.

Keywords: stationarity, unit root tests, economic time series, ADF tests

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Authors: Rade M. Ciric, Sasa Mandic

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Students of Higher Education Technical School of Professional Studies, in Novi Sad follow the subject Maintenance of electric power equipment at the Electrotechnical Department. This paper presents educational plan and program of the subject Maintenance of electric power equipment. The course deals with the problems of preventive and investing maintenance of transformer stations (TS), performing and maintenance of grounding of TS and pillars, as well as tracing and detection the location of the cables failure. There is a special elaborated subject concerning the safe work conditions for the electrician during network maintenance, as well as the basics of making and keeping technical documentation of the equipment.

Keywords: educational plan and program, electric power equipment, maintenance, technical documentation, safe work

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Authors: Ghazi Bouaziz, Abderrahim Derouiche, Damien Brulin, Hélène Pigot, Eric Campo

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Automatic ADL classification is a crucial part of ambient assisted living technologies. It allows to monitor the daily life of the elderly and to detect any changes in their behavior that could be related to health problem. But detection of ADLs is a challenge, especially because each person has his/her own rhythm for performing them. Therefore, we used a correlation matrix to extract custom rules that enable to detect ADLs, including eating activity. Data collected from 3 different individuals between 35 and 105 days allows the extraction of personalized eating patterns. The comparison of the results of the process of eating activity extracted from the correlation matrices with the declarative data collected during the survey shows an accuracy of 90%.

Keywords: elderly monitoring, ADL identification, matrix correlation, meal-taking activity

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Authors: Vinai K. Singh

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In Neural Network-based Learning techniques, there are several models of Convolutional Networks. Whenever the methods are deployed with large datasets, only then can their applicability and appropriateness be determined. Clinical and pathological pictures of lobular carcinoma are thought to exhibit a large number of random formations and textures. Working with such pictures is a difficult problem in machine learning. Focusing on wet laboratories and following the outcomes, numerous studies have been published with fresh commentaries in the investigation. In this research, we provide a framework that can operate effectively on raw photos of various resolutions while easing the issues caused by the existence of patterns and texturing. The suggested approach produces very good findings that may be used to make decisions in the diagnosis of cancer.

Keywords: lobular carcinoma, convolutional neural networks (CNN), deep learning, histopathological imagery scans

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Authors: Nadhiya N. Subramony, Jenifer Vaughan, Lesley E. Scott

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In South Africa, the World Health Organisation estimated 454000 new cases of Mycobacterium tuberculosis (M.tb) infection (MTB) in 2015. Disseminated tuberculosis arises from the haematogenous spread and seeding of the bacilli in extrapulmonary sites. The gold standard for the detection of MTB in bone marrow is TB culture which has an average turnaround time of 6 weeks. Histological examinations of trephine biopsies to diagnose MTB also have a time delay owing mainly to the 5-7 day processing period prior to microscopic examination. Adding to the diagnostic delay is the non-specific nature of granulomatous inflammation which is the hallmark of MTB involvement of the bone marrow. A Ziehl-Neelson stain (which highlights acid-fast bacilli) is therefore mandatory to confirm the diagnosis but can take up to 3 days for processing and evaluation. Owing to this delay in diagnosis, many patients are lost to follow up or remain untreated whilst results are awaited, thus encouraging the spread of undiagnosed TB. The Xpert® MTB/RIF (Cepheid, Sunnyvale, CA) is the molecular test used in the South African national TB program as the initial diagnostic test for pulmonary TB. This study investigates the optimisation and performance of the Xpert® MTB/RIF on bone marrow aspirate specimens (BMA), a first since the introduction of the assay in the diagnosis of extrapulmonary TB. BMA received for immunophenotypic analysis as part of the investigation into disseminated MTB or in the evaluation of cytopenias in immunocompromised patients were used. Processing BMA on the Xpert® MTB/RIF was optimised to ensure bone marrow in EDTA and heparin did not inhibit the PCR reaction. Inactivated M.tb was spiked into the clinical bone marrow specimen and distilled water (as a control). A volume of 500mcl and an incubation time of 15 minutes with sample reagent were investigated as the processing protocol. A total of 135 BMA specimens had sufficient residual volume for Xpert® MTB/RIF testing however 22 specimens (16.3%) were not included in the final statistical analysis as an adequate trephine biopsy and/or TB culture was not available. Xpert® MTB/RIF testing was not affected by BMA material in the presence of heparin or EDTA, but the overall detection of MTB in BMA was low compared to histology and culture. Sensitivity of the Xpert® MTB/RIF compared to both histology and culture was 8.7% (95% confidence interval (CI): 1.07-28.04%) and sensitivity compared to histology only was 11.1% (95% CI: 1.38-34.7%). Specificity of the Xpert® MTB/RIF was 98.9% (95% CI: 93.9-99.7%). Although the Xpert® MTB/RIF generates a faster result than histology and TB culture and is less expensive than culture and drug susceptibility testing, the low sensitivity of the Xpert® MTB/RIF precludes its use for the diagnosis of MTB in bone marrow aspirate specimens and warrants alternative/additional testing to optimise the assay.

Keywords: bone marrow aspirate , extrapulmonary TB, low sensitivity, Xpert® MTB/RIF

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Authors: Nimisha Jadon, Rajeev Jain, Swati Sharma

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A chemically modified carbon paste sensor has been developed for the simultaneous determination of amlodipine (AML) and nebivolol (NBV). Carbon paste electrode (CPE) was fabricated by the addition of Gr/PANI-CeO2. Gr/PANI-CeO2/CPE has achieved excellent electrocatalytic activity and sensitivity. AML and NBV exhibited oxidation peaks at 0.70 and 0.90 V respectively on Gr/ PANI-CeO2/CPE. The linearity range of AML and NBV was 0.1 to 1.6 μgmL-1 in BR buffer (pH 8.0). The Limit of detection (LOD) was 20.0 ngmL-1 for AML and 30.0 ngmL-1 for NBV and limit of quantification (LOQ) was 80.0 ngmL-1 for AML and 100 ngmL-1 for NBV respectively. These analyses were also determined in pharmaceutical formulation and human serum and good recovery was obtained for the developed method.

Keywords: amlodipine, nebivolol, square wave voltammetry, carbon paste electrode, simultaneous quantification

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Authors: Firas Gerges, Frank Y. Shih

Abstract:

Malignant melanoma, known simply as melanoma, is a type of skin cancer that appears as a mole on the skin. It is critical to detect this cancer at an early stage because it can spread across the body and may lead to the patient's death. When detected early, melanoma is curable. In this paper, we propose a deep learning model (convolutional neural networks) in order to automatically classify skin lesion images as malignant or benign. Images underwent certain pre-processing steps to diminish the effect of the normal skin region on the model. The result of the proposed model showed a significant improvement over previous work, achieving an accuracy of 97%.

Keywords: deep learning, skin cancer, image processing, melanoma

Procedia PDF Downloads 146

Authors: Ikechi Gilbert

Abstract:

Oral communication is the transmission of ideas or messages through the speech process. Acquiring competence in this area which, by its volatile nature, is prone to errors and inaccuracies would require the adoption of a well-suited teaching methodology. Efficient oral communication facilitates exchange of ideas and easy accomplishment of day-to-day tasks, by means of a demonstrated mastery of oral expression and the making of fine presentations to audiences or individuals while recognizing verbal signals and body language of others and interpreting them correctly. In Anglophone states such as Nigeria, Ghana, etc., the French language, for instance, is studied as a foreign language, being used majorly in teaching learners who have their own mother tongue different from French. The same applies to Francophone states where English is studied as a foreign language by people whose official language or mother tongue is different from English. The ideal approach would be to teach these languages in these environments through a pedagogical approach that properly takes care of the oral perspective for effective understanding and application by the learners. In this article, we are examining the communicative approach as a methodology for teaching oral communication in a foreign language. This method is a direct response to the communicative needs of the learner involving the use of appropriate materials and teaching techniques that meet those needs. It is also a vivid improvement to the traditional grammatical and audio-visual adaptations. Our contribution will focus on the pedagogical component of oral communication improvement, highlighting its merits and also proposing diverse techniques including aspects of information and communication technology that would assist the second language learner communicate better orally.

Keywords: communication, competence, methodology, pedagogical component

Procedia PDF Downloads 263

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

Abstract:

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

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

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Authors: Dêivisson Alves Anjos, Blenda Fonseca Aires Teles, Queitiane Castro Costa

Abstract:

Fire is one of the biggest dangers for factories, warehouses, mills, among other places, causing unimaginable damage, because besides the material damage also directly affects the lives of workers who are likely to suffer death or very serious consequences. This protection of the lives of these people should be taken seriously, always seeking safety. Thus investment in security and monitoring equipment must be high, so you can prevent or reduce the impacts of a possible fire. Our device, made in PIC micro controller monitors the temperature and the presence of gas in the environment, it sends the data via Bluetooth device to a developed in LabVIEW interface saves these data continuously and alert if the temperature exceeds the allowed or some gas is detected. Currently the device is in operation and can perform several tests, as well as use in different areas for which you need anti-fire protection.

Keywords: pic, bluetooth, fire, temperature, gas, LabVIEW

Procedia PDF Downloads 530

Authors: Moh Hanif Mubarok, Muhammad Rivai

Abstract:

The public's response to quality rice is very high. So it is necessary to set minimum standards in checking the quality of rice. Most rice quality measurements still use manual methods, which are prone to errors due to limited human vision and the subjectivity of testers. So, a gas detection system can be a solution that has high effectiveness and subjectivity for solving current problems. The use of gas sensors in testing rice quality must pay attention to several parameters. The parameters measured in this research are the percentage of rice water content, gas concentration, output voltage, and measurement time. Therefore, this research was carried out to identify carbon dioxide (CO₂), nitrous oxide (N₂O) and methane (CH₄) gases in rice quality using a series of gas sensors using the Neural Network method.

Keywords: carbon dioxide, dinitrogen oxide, methane, semiconductor gas sensor, neural network

Procedia PDF Downloads 45