Search results for: automatic recording

Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

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Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and ECG-based systems are unquestionably the best choice due to their appealing inherent characteristics. The CNNs are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the calibre of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest FAR of 0.04 percent and the highest FRR of 5%, the best performing network achieved an identification accuracy of 99.94 percent. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, Dense Networks, Identification Rate, Train/Test split ratio

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Authors: Olivia Borgue, Massimo Panarotto, Ola Isaksson

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This article presents a neural networks-based strategy for reducing the need for support structures when designing for additive manufacturing (AM). Additive manufacturing is a relatively new and immature industrial technology, and the information to make confident decisions when designing for AM is limited. This lack of information impacts especially the early stages of engineering design, for instance, it is difficult to actively consider the support structures needed for manufacturing a part. This difficulty is related to the challenge of designing a product geometry accounting for customer requirements, manufacturing constraints and minimization of support structure. The approach presented in this article proposes an automatized geometry modification technique for reducing the use of the support structures while designing for AM. This strategy starts with a neural network-based strategy for shape recognition to achieve product classification, using an STL file of the product as input. Based on the classification, an automatic part geometry modification based on MATLAB© is implemented. At the end of the process, the strategy presents different geometry modification alternatives depending on the type of product to be designed. The geometry alternatives are then evaluated adopting a QFD-like decision support tool.

Keywords: additive manufacturing, engineering design, geometry modification optimization, neural networks

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Authors: A. Elsehemy, M. Abdeen , T. Nazmy

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Since the appearance of the Semantic web, many semantic search techniques and models were proposed to exploit the information in ontology to enhance the traditional keyword-based search. Many advances were made in languages such as English, German, French and Spanish. However, other languages such as Arabic are not fully supported yet. In this paper we present a framework for ontology based information retrieval for Arabic language. Our system consists of four main modules, namely query parser, indexer, search and a ranking module. Our approach includes building a semantic index by linking ontology concepts to documents, including an annotation weight for each link, to be used in ranking the results. We also augmented the framework with an automatic document categorizer, which enhances the overall document ranking. We have built three Arabic domain ontologies: Sports, Economic and Politics as example for the Arabic language. We built a knowledge base that consists of 79 classes and more than 1456 instances. The system is evaluated using the precision and recall metrics. We have done many retrieval operations on a sample of 40,316 documents with a size 320 MB of pure text. The results show that the semantic search enhanced with text classification gives better performance results than the system without classification.

Keywords: Arabic text classification, ontology based retrieval, Arabic semantic web, information retrieval, Arabic ontology

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Authors: Bel G Raggad

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An e-Learning setting is a distributed computing environment where information resources can be connected to any public network. Public networks are very unsecure which can compromise the reliability of an e-Learning environment. This study is only concerned with the intrusion detection aspect of e-Learning security and how incident responses are planned. The literature reported great advances in intrusion detection system (ids) but neglected to study an important ids weakness: suspected events are detected but an intrusion is not determined because it is not defined in ids databases. We propose an incident response generator (DIRG) that produces incident responses when the working ids system suspects an event that does not correspond to a known intrusion. Data involved in intrusion detection when ample uncertainty is present is often not suitable to formal statistical models including Bayesian. We instead adopt Dempster and Shafer theory to process intrusion data for the unknown event. The DIRG engine transforms data into a belief structure using incident scenarios deduced by the security administrator. Belief values associated with various incident scenarios are then derived and evaluated to choose the most appropriate scenario for which an automatic incident response is generated. This article provides a numerical example demonstrating the working of the DIRG system.

Keywords: decision support system, distributed computing, e-Learning security, incident response, intrusion detection, security risk, statefull inspection

Procedia PDF Downloads 433

Authors: R. Tlili Yaakoubi, H.Nakouri, O. Blanpain, S. Lallahem

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The current tools for real time management of sewer systems are based on two software tools: the software of weather forecast and the software of hydraulic simulation. The use of the first ones is an important cause of imprecision and uncertainty, the use of the second requires temporal important steps of decision because of their need in times of calculation. This way of proceeding fact that the obtained results are generally different from those waited. The major idea of this project is to change the basic paradigm by approaching the problem by the "automatic" face rather than by that "hydrology". The objective is to make possible the realization of a large number of simulations at very short times (a few seconds) allowing to take place weather forecasts by using directly the real time meditative pluviometric data. The aim is to reach a system where the decision-making is realized from reliable data and where the correction of the error is permanent. A first model of control laws was realized and tested with different return-period rainfalls. The gains obtained in rejecting volume vary from 19 to 100 %. The development of a new algorithm was then used to optimize calculation time and thus to overcome the subsequent combinatorial problem in our first approach. Finally, this new algorithm was tested with 16- year-rainfall series. The obtained gains are 40 % of total volume rejected to the natural environment and of 65 % in the number of discharges.

Keywords: automation, optimization, paradigm, RTC

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Authors: Poonam Malik, Ravi Bhushan

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This work describes a very efficient approach for synthesis of activated ester of (S)-naproxen which was characterized by UV, IR, ¹HNMR, elemental analysis and polarimetric studies. It was used as a C-N bond forming chiral derivatizing reagent for further synthesis of diastereomeric amides of (RS)-salbutamol (a β₂ agonist that belongs to the group β-adrenolytic and is marketed as racamate) under microwave irradiation. The diastereomeric pair was separated by achiral phase HPLC, using mobile phase in gradient mode containing methanol and aqueous triethylaminephosphate (TEAP); separation conditions were optimized with respect to pH, flow rate, and buffer concentration and the method of separation was validated as per International Council for Harmonisation (ICH) guidelines. The reagent proved to be very effective for on-line sensitive detection of the diastereomers with very low limit of detection (LOD) values of 0.69 and 0.57 ng mL⁻¹ for diastereomeric derivatives of (S)- and (R)-salbutamol, respectively. The retention times were greatly reduced (2.7 min) with less consumption of organic solvents and large (α) as compared to literature reports. Besides, the diastereomeric derivatives were separated and isolated by preparative HPLC; these were characterized and were used as standard reference samples for recording ¹HNMR and IR spectra for determining absolute configuration and elution order; it ensured the success of diastereomeric synthesis and established the reliability of enantioseparation and eliminated the requirement of pure enantiomer of the analyte which is generally not available. The newly developed reagent can suitably be applied to several other amino group containing compounds either from organic syntheses or pharmaceutical industries because the presence of (S)-Npx as a strong chromophore would allow sensitive detection.This work is significant not only in the area of enantioseparation and determination of absolute configuration of diastereomeric derivatives but also in the area of developing new chiral derivatizing reagents (CDRs).

Keywords: chiral derivatizing reagent, naproxen, salbutamol, synthesis

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Authors: Bing Li, Zhi Li, Yilong Yang

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Web classification can promote the quality of service discovery and management in the service repository. It is widely used to locate developers desired services. Although traditional classification methods based on supervised learning models can achieve classification tasks, developers need to manually mark web services, and the quality of these tags may not be enough to establish an accurate classifier for service classification. With the doubling of the number of web services, the manual tagging method has become unrealistic. In recent years, the attention mechanism has made remarkable progress in the field of deep learning, and its huge potential has been fully demonstrated in various fields. This paper designs a multi-head attention graph convolutional network (MHAGCN) service classification method, which can assign different weights to the neighborhood nodes without complicated matrix operations or relying on understanding the entire graph structure. The framework combines the advantages of the attention mechanism and graph convolutional neural network. It can classify web services through automatic feature extraction. The comprehensive experimental results on a real dataset not only show the superior performance of the proposed model over the existing models but also demonstrate its potentially good interpretability for graph analysis.

Keywords: attention mechanism, graph convolutional network, interpretability, service classification, service discovery

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Authors: M. Moslehpour, S. Khorsandi

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Due to shortage in IPv4 addresses, transition to IPv6 has gained significant momentum in recent years. Like Address Resolution Protocol (ARP) in IPv4, Neighbor Discovery Protocol (NDP) provides some functions like address resolution in IPv6. Besides functionality of NDP, it is vulnerable to some attacks. To mitigate these attacks, Internet Protocol Security (IPsec) was introduced, but it was not efficient due to its limitation. Therefore, SEND protocol is proposed to automatic protection of auto-configuration process. It is secure neighbor discovery and address resolution process. To defend against threats on NDP’s integrity and identity, Cryptographically Generated Address (CGA) and asymmetric cryptography are used by SEND. Besides advantages of SEND, its disadvantages like the computation process of CGA algorithm and sequentially of CGA generation algorithm are considerable. In this paper, we parallel this process between network resources in order to improve it. In addition, we compare the CGA generation time in self-computing and distributed-computing process. We focus on the impact of the malicious nodes on the CGA generation time in the network. According to the result, although malicious nodes participate in the generation process, CGA generation time is less than when it is computed in a one-way. By Trust Management System, detecting and insulating malicious nodes is easier.

Keywords: NDP, IPsec, SEND, CGA, modifier, malicious node, self-computing, distributed-computing

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Authors: Mian Huang, Chi Ma, Junyu Lin, William Lu

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Introduction: Bone health attracts more attention recently and an intelligent question and answer (QA) chatbot for osteoporosis is helpful for science popularization. With Generative Pretrained Transformer (GPT) technology developing, we build an osteoporosis corpus dataset and then fine-tune LLaMA, a famous open-source GPT foundation large language model(LLM), on our self-constructed osteoporosis corpus. Evaluated by clinical orthopedic experts, our fine-tuned model outperforms vanilla LLaMA on osteoporosis QA task in Chinese. Three-dimensional quantitative computed tomography (QCT) measured bone mineral density (BMD) is considered as more accurate than DXA for BMD measurement in recent years. We develop an automatic Phantom-less QCT(PL-QCT) that is more efficient for BMD measurement since no need of an external phantom for calibration. Combined with LLM on osteoporosis, our PL-QCT provides efficient and accurate BMD measurement for our chatbot users. Material and Methods: We build an osteoporosis corpus containing about 30,000 Chinese literatures whose titles are related to osteoporosis. The whole process is done automatically, including crawling literatures in .pdf format, localizing text/figure/table region by layout segmentation algorithm and recognizing text by OCR algorithm. We train our model by continuous pre-training with Low-rank Adaptation (LoRA, rank=10) technology to adapt LLaMA-7B model to osteoporosis domain, whose basic principle is to mask the next word in the text and make the model predict that word. The loss function is defined as cross-entropy between the predicted and ground-truth word. Experiment is implemented on single NVIDIA A800 GPU for 15 days. Our automatic PL-QCT BMD measurement adopt AI-associated region-of-interest (ROI) generation algorithm for localizing vertebrae-parallel cylinder in cancellous bone. Due to no phantom for BMD calibration, we calculate ROI BMD by CT-BMD of personal muscle and fat. Results & Discussion: Clinical orthopaedic experts are invited to design 5 osteoporosis questions in Chinese, evaluating performance of vanilla LLaMA and our fine-tuned model. Our model outperforms LLaMA on over 80% of these questions, understanding ‘Expert Consensus on Osteoporosis’, ‘QCT for osteoporosis diagnosis’ and ‘Effect of age on osteoporosis’. Detailed results are shown in appendix. Future work may be done by training a larger LLM on the whole orthopaedics with more high-quality domain data, or a multi-modal GPT combining and understanding X-ray and medical text for orthopaedic computer-aided-diagnosis. However, GPT model gives unexpected outputs sometimes, such as repetitive text or seemingly normal but wrong answer (called ‘hallucination’). Even though GPT give correct answers, it cannot be considered as valid clinical diagnoses instead of clinical doctors. The PL-QCT BMD system provided by Bone’s QCT(Bone’s Technology(Shenzhen) Limited) achieves 0.1448mg/cm2(spine) and 0.0002 mg/cm2(hip) mean absolute error(MAE) and linear correlation coefficient R2=0.9970(spine) and R2=0.9991(hip)(compared to QCT-Pro(Mindways)) on 155 patients in three-center clinical trial in Guangzhou, China. Conclusion: This study builds a Chinese osteoporosis corpus and develops a fine-tuned and domain-adapted LLM as well as a PL-QCT BMD measurement system. Our fine-tuned GPT model shows better capability than LLaMA model on most testing questions on osteoporosis. Combined with our PL-QCT BMD system, we are looking forward to providing science popularization and early morning screening for potential osteoporotic patients.

Keywords: GPT, phantom-less QCT, large language model, osteoporosis

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Authors: T. Radu, R. Sreenivas, H. Albuflasa, A. Mustafa Khan, W. Aloqab

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The Kingdom of Bahrain, a small island country in the Gulf region, is experiencing fast economic growth resulting in a sharp increase in population and greater than ever amounts of waste being produced. However, waste management in the country is still very basic, with landfilling being the most popular option. Recycling is still a scarce practice, with small recycling businesses and initiatives emerging in recent years. This scenario is typical for other countries in the region, with similar amounts of per capita waste being produced. In this paper, we are reviewing current waste management practices in Bahrain by collecting data published by the Government and various authors, and by visiting the country’s only landfill site, Askar. In addition, we have performed a survey of the residents to learn more about the awareness and attitudes towards sustainable waste management strategies. A review of the available data on waste management indicates that the Askar landfill site is nearing its capacity. The site uses open tipping as the method of disposal. The highest percentage of disposed waste comes from the building sector (38.4%), followed by domestic (27.5%) and commercial waste (17.9%). Disposal monitoring and recording are often based on estimates of weight and without proper characterization/classification of received waste. Besides, there is a need for assessment of the environmental impact of the site with systematic monitoring of pollutants in the area and their potential spreading to the surrounding land, groundwater, and air. The results of the survey indicate low awareness of what happens with the collected waste in the country. However, the respondents have shown support for future waste reduction and recycling initiatives. This implies that the education of local communities would be very beneficial for such governmental initiatives, securing greater participation. Raising awareness of issues surrounding recycling and waste management and systematic effort to divert waste from landfills are the first steps towards securing sustainable waste management in the Kingdom of Bahrain.

Keywords: landfill, municipal solid waste, survey, waste management

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Authors: Chia-Hui Chen, Chien-Kuo Wang

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Background: Full field digital mammography (FFDM) is widely used in diagnosis of breast cancer. Digital breast tomosynthesis (DBT) has recently been introduced into the clinic and is being used for screening for breast cancer in the general population. Hence, the radiation dose delivered to the patients involved in an imaging protocol is of utmost concern. Aim: To compare the surface radiation dose (ESD) of digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) by using breast phantoms. Method: We analyzed the average entrance surface dose (ESD) of FFDM and DBT by using breast phantoms. Optically Stimulated luminescent Dosimeters (OSLD) were placed in a tissue-equivalent Breast phantom at difference sites of interest. Absorbed dose measurements were obtained after digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) exposures. Results: An automatic exposure control (AEC) is proposed for surface dose measurement during DBT and FFDM. The mean ESD values for DBT and FFDM were 6.37 mGy and 3.51mGy, respectively. Using of OSLD measured for surface dose during DBT and FFDM. There were 19.87 mGy and 11.36 mGy, respectively. The surface exposure dose of DBT could possibly be increased by two times with FFDM. Conclusion: The radiation dose from DBT was higher than that of FFDM and the difference in dose between AEC and OSLD measurements at phantom surface.

Keywords: full-field digital mammography, digital breast tomosynthesis, optically stimulated luminescent dosimeters, surface dose

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Authors: Diana Pombo, Maria Loaiza, Mauricio Quijano, Alberto Cadena, Juan Pablo Tello

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In this paper, we present a semi-automatic tool for calculating ejection fraction from an echocardiographic video signal which is derived from a database in DICOM format, of Clinica de la Costa - Barranquilla. Described in this paper are each of the steps and methods used to find the respective calculation that includes acquisition and formation of the test samples, processing and finally the calculation of the parameters to obtain the ejection fraction. Two imaging segmentation methods were compared following a methodological framework that is similar only in the initial stages of processing (process of filtering and image enhancement) and differ in the end when algorithms are implemented (Active Contour and Region Growing Algorithms). The results were compared with the measurements obtained by two different medical specialists in cardiology who calculated the ejection fraction of the study samples using the traditional method, which consists of drawing the region of interest directly from the computer using echocardiography equipment and a simple equation to calculate the desired value. The results showed that if the quality of video samples are good (i.e., after the pre-processing there is evidence of an improvement in the contrast), the values provided by the tool are substantially close to those reported by physicians; also the correlation between physicians does not vary significantly.

Keywords: echocardiography, DICOM, processing, segmentation, EDV, ESV, ejection fraction

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Authors: Gheida J. Shahrour, Martin J. Russell

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The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to their culture. We arranged each group into pairs and each pair communicated with each other about different topics. A state-of-art recognition system is applied to the problems of person, culture, and topic recognition. We borrowed modeling, classification, and normalization techniques from speech recognition. We used Gaussian Mixture Modeling (GMM) as the main technique for building our three systems, obtaining 77.78%, 55.47%, and 39.06% from the person, culture, and topic recognition systems respectively. In addition, we combined the above GMM systems with Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and 40.63% accuracy for person, culture, and topic recognition respectively. Although direct comparison among these three recognition systems is difficult, it seems that our person recognition system performs best for both GMM and GMM-SVM, suggesting that inter-subject differences (i.e. subject’s personality traits) are a major source of variation. When removing these traits from culture and topic recognition systems using the Nuisance Attribute Projection (NAP) and the Intersession Variability Compensation (ISVC) techniques, we obtained 73.44% and 46.09% accuracy from culture and topic recognition systems respectively.

Keywords: person recognition, topic recognition, culture recognition, 3D body movement signals, variability compensation

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Authors: Y. Melis, E. Apicella, E. Dozio, L. Mendolicchio

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Introduction: Feeding and Eating Disorders (FED) represent the psychiatric pathology with the highest mortality rate and one of the major disorders with the highest psychiatric and clinical comorbidity. The vagus nerve represents one of the main components of the sympathetic and parasympathetic nervous system and is involved in important neurophysiological functions. In FED, there is a spectrum of symptoms which with TaVNS (Transcutaneous Auricular Vagus Nerve Stimulation) therapy, is possible to have a therapeutic efficacy. Materials and Methods: Sample subjects are composed of 15 female subjects aged > 18 ± 51. Admitted to a psychiatry community having been diagnosed according to DSM-5: anorexia nervosa (AN) (N= 9), bulimia nervosa (BN) (N= 5), binge eating disorder (BED) (N= 1). The protocol included 9 weeks of Ta-VNS stimulation at a frequency of 1.5-3.5 mA for 4 hours per day. The variables detected are the following: Heart Rate Variability (HRV), Hamilton Depression Rating Scale (HAMD-HDRS-17), Body Mass Index (BMI), Beck Anxiety Index (BAI). Results: Data analysis showed statistically significant differences between recording times (p > 0.05) in HAM-D (t0 = 18.28 ± 5.31; t4 = 9.14 ± 7.15), in BAI (t0 = 24.7 ± 10.99; t4 = 13.8 ± 7.0). The reported values show how during (T0-T4) the treatment there is a decay of the degree in the depressive state, in the state of anxiety, and an improvement in the value of BMI. In particular, the BMI in the AN-BN sub-sample had a minimum gain of 5% and a maximum of 11%. The analysis of HRV did not show a clear change among subjects, thus confirming the discordance of the activity of the sympathetic and parasympathetic nervous system in FED. Conclusions: Although the sample does not possess a relevant value to determine long-term efficacy of Ta-VNS or on a larger population, this study reports how the application of neuro-stimulation in FED may become a further approach therapeutic. Indeed, substantial improvements are highlighted in the results and confirmed hypotheses proposed by the study.

Keywords: feeding and eating disorders, neurostimulation, anxiety disorders, depression

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Authors: Dilshad Ali Mohammed, Ziyad Nayef Shamsulddin Aldoski, Millet Salim Mohammed

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The increase in levels of traffic congestion along urban signalized arterials needs efficient traffic management. The application of traffic signal coordination can improve the traffic operation and safety for a series of signalized intersection along the arterials. The objective of this study is to evaluate the benefits achievable through actuated traffic signal coordination and make a comparison in control delay against the same signalized intersection in case of being isolated. To accomplish this purpose, a series of eight signalized intersections located on two major arterials in Duhok City was chosen for conducting the study. Traffic data (traffic volumes, link and approach speeds, and passenger car equivalent) were collected at peak hours. Various methods had been used for collecting data such as video recording technique, moving vehicle method and manual methods. Geometric and signalization data were also collected for the purpose of the study. The coupling index had been calculated to check the coordination attainability, and then time space diagrams were constructed representing one-way coordination for the intersections on Barzani and Zakho Streets, and others represented two-way coordination for the intersections on Zakho Street with accepted progression bandwidth efficiency. The results of this study show great progression bandwidth of 54 seconds for east direction coordination and 17 seconds for west direction coordination on Barzani Street under suggested controlled speed of 60 kph agreeable with the present data. For Zakho Street, the progression bandwidth is 19 seconds for east direction coordination and 18 seconds for west direction coordination under suggested controlled speed of 40 kph. The results show that traffic signal coordination had led to high reduction in intersection control delays on both arterials.

Keywords: bandwidth, congestion, coordination, traffic, signals, streets

Procedia PDF Downloads 300

Authors: Joud Basyouni, Rama Zagzoog, Mashael Al Faleh, Jana Alireza

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AI is changing many fields and speeding up tasks that used to take a long time. It used to take too long to edit photos. However, many AI-powered apps make photo editing, automatic effects, and animations much easier than other manual editing apps with no AI. The mobile app Photoleap edits photos and creates digital art using AI. Editing photos with text prompts is also becoming a standard these days with the help of apps like Photoleap. Now, users can change backgrounds, add animations, turn text into images, and create scenes with AI. This project report discusses the photo editing app's history and popularity. Photoleap resembles Photoshop, Canva, Photos, and Pixlr. The report includes survey questions to assess Photoleap user satisfaction. The report describes Photoleap's features and functions with screenshots. Photoleap uses AI well. Charts and graphs show Photoleap user ratings and comments from the survey. This project found that most Photoleap users liked how well it worked, was made, and was easy to use. People liked changing photos and adding backgrounds. Users can create stunning photo animations. A few users dislike the app's animations, AI art, and photo effects. The project report discusses the app's pros and cons and offers improvements.

Keywords: artificial intelligence, photoleap, images, background, photo editing

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Authors: Andrii Biloshchytskyi, Serik Omirbayev, Alexandr Neftissov, Sapar Toxanov, Svitlana Biloshchytska, Adil Faizullin

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Kazakhstan has adopted a carbon neutrality strategy until 2060. In accordance with this strategy, it is necessary to introduce various tools to maintain the environmental safety of the environment. The use of IoT, in combination with the characteristics and requirements of Kazakhstan's environmental legislation, makes it possible to develop a modern environmental monitoring system. The article proposes a solution for developing an example of an automated system for the continuous collection of data on the concentration of pollutants in the atmosphere based on an open architecture. The Audino-based device acts as a microcontroller. It should be noted that the transmission of measured values is carried out via an open wireless communication protocol. The architecture of the system, which was used to build a prototype based on sensors, an Arduino microcontroller, and a wireless data transmission module, is presented. The selection of elementary components may change depending on the requirements of the system; the introduction of new units is limited by the number of ports. The openness of solutions allows you to change the configuration depending on the conditions. The advantages of the solutions are openness, low cost, versatility and mobility. However, there is no comparison of the working processes of the proposed solution with traditional ones.

Keywords: environmental monitoring, greenhouse gases emissions, environmental pollution, Industry 4.0, IoT, microcontroller, automated monitoring system.

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Authors: Jorge Anibal Restrepo Morales, Sonia Martín Gómez

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A model based on a logical framework was developed to quantify SMEs' internationalization capacity. To do so, linguistic variables, such as human talent, infrastructure, innovation strategies, FTAs, marketing strategies, finance, etc. were integrated. It is argued that a company’s management of international markets depends on internal factors, especially capabilities and resources available. This study considers internal factors as the biggest business challenge because they force companies to develop an adequate set of capabilities. At this stage, importance and strategic relevance have to be defined in order to build competitive advantages. A fuzzy inference system is proposed to model the resources, skills, and capabilities that determine the success of internationalization. Data: 157 linguistic variables were used. These variables were defined by international trade entrepreneurs, experts, consultants, and researchers. Using expert judgment, the variables were condensed into18 factors that explain SMEs’ export capacity. The proposed model is applied by means of a case study of the textile and clothing cluster in Medellin, Colombia. In the model implementation, a general index of 28.2 was obtained for internationalization capabilities. The result confirms that the sector’s current capabilities and resources are not sufficient for a successful integration into the international market. The model specifies the factors and variables, which need to be worked on in order to improve export capability. In the case of textile companies, the lack of a continuous recording of information stands out. Likewise, there are very few studies directed towards developing long-term plans, and., there is little consistency in exports criteria. This method emerges as an innovative management tool linked to internal organizational spheres and their different abilities.

Keywords: business strategy, exports, internationalization, fuzzy set methods

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Authors: Young Kwon Yang, Bo Rang Park, Hyo Eun Lee, Tea Won Kim, Eun Ji Choi, Jin Chul Park

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To develop an artificial intelligence based automatic ventilation system, recent research trends were analyzed and analyzed. This research method is as follows. In the field of architecture and window technology, the use of artificial intelligence, the existing study of machine learning model and the theoretical review of the literature were carried out. This paper collected journals such as Journal of Energy and Buildings, Journal of Renewable and Sustainable Energy Reviews, and articles published on Web-sites. The following keywords were searched for articles from 2000 to 2016. We searched for the above keywords mainly in the title, keyword, and abstract. As a result, the global artificial intelligence market is expected to grow at a CAGR of 14.0% from USD127bn in 2015 to USD165bn in 2017. Start-up investments in artificial intelligence increased from the US $ 45 million in 2010 to the US $ 310 million in 2015, and the number of investments increased from 6 to 54. Although AI is making efforts to advance to advanced countries, the level of technology is still in its infant stage. Especially in the field of architecture, artificial intelligence (AI) is very rare. Based on the data of this study, it is expected that the application of artificial intelligence and the application of architectural field will be revitalized through the activation of artificial intelligence in the field of architecture and window.

Keywords: artificial intelligence, window, fine dust, thermal comfort, ventilation system

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Authors: Winncy Du, Jeremy Nguyen, Harpinder Dhillon, Reinardus Justin Halim, Clayton Haske, Trent Hughes, Marissa Ortiz, Rozy Saini

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Stroke often causes death or cerebro-vascular (CV) brain damage. Most patients with CV brain damage lost their motor control on their limbs. This paper focuses on developing a reliable, safe, and non-invasive EEG-based robot-assistant stroke rehabilitation system to help stroke survivors to rapidly restore their motor control functions for their limbs. An electroencephalogram (EEG) recording device (EPOC Headset) and was used to detect a patient’s brain activities. The EEG signals were then processed, classified, and interpreted to the motion intentions, and then converted to a series of robot motion commands. A six-axis articulated robot (AdeptSix 300) was employed to provide the intended motions based on these commends. To ensure the EEG device, the computer, and the robot can communicate to each other, an Arduino microcontroller is used to physically execute the programming codes to a series output pins’ status (HIGH or LOW). Then these “hardware” commends were sent to a 24 V relay to trigger the robot’s motion. A lookup table for various motion intensions and the associated EEG signal patterns were created (through training) and installed in the microcontroller. Thus, the motion intention can be direct determined by comparing the EEG patterns obtaibed from the patient with the look-up table’s EEG patterns; and the corresponding motion commends are sent to the robot to provide the intended motion without going through feature extraction and interpretation each time (a time-consuming process). For safety sake, an extender was designed and attached to the robot’s end effector to ensure the patient is beyond the robot’s workspace. The gripper is also designed to hold the patient’s limb. The test results of this rehabilitation system show that it can accurately interpret the patient’s motion intension and move the patient’s arm to the intended position.

Keywords: brain waves, EEG sensor, motion control, robot-assistant stroke rehabilitation

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Authors: Yousif Mohamed Y. Abdallah

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This is an experimental study deals with detection, measurement and analysis of the periodic physiological organ motion during external beam radiotherapy; to improve the accuracy of the radiation field placement, and to reduce the exposure of healthy tissue during radiation treatments. The importance of this study is to detect the maximum path of the mobile structures during radiotherapy delivery, to define the planning target volume (PTV) and irradiated volume during both inspiration and expiration period and to verify the target volume. In addition to its role to highlight the importance of the application of Intense Guided Radiotherapy (IGRT) methods in the field of radiotherapy. The results showed (body contour was equally (3.17 + 0.23 mm), for left lung displacement reading (2.56 + 0.99 mm) and right lung is (2.42 + 0.77 mm) which the radiation oncologist to take suitable countermeasures in case of significant errors. In addition, the use of the image registration technique for automatic position control is predicted potential motion. The motion ranged between 2.13 mm and 12.2 mm (low and high). In conclusion, individualized assessment of tumor mobility can improve the accuracy of target areas definition in patients undergo Sterostatic RT for stage I, II and III lung cancer (NSCLC). Definition of the target volume based on a single CT scan with a margin of 10 mm is clearly inappropriate.

Keywords: respiratory motion, external beam radiotherapy, image processing, lung

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Authors: Rabaa Tlili Yaakoubi, Hind Nakouri, Olivier Blanpain

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The current tools for real time management of sewer systems are based on two software tools: the software of weather forecast and the software of hydraulic simulation. The use of the first ones is an important cause of imprecision and uncertainty, the use of the second requires temporal important steps of decision because of their need in times of calculation. This way of proceeding fact that the obtained results are generally different from those waited. The major idea of the CARDIO project is to change the basic paradigm by approaching the problem by the "automatic" face rather than by that "hydrology". The objective is to make possible the realization of a large number of simulations at very short times (a few seconds) allowing to take place weather forecasts by using directly the real time meditative pluviometric data. The aim is to reach a system where the decision-making is realized from reliable data and where the correction of the error is permanent. A first model of control laws was realized and tested with different return-period rainfalls. The gains obtained in rejecting volume vary from 40 to 100%. The development of a new algorithm was then used to optimize calculation time and thus to overcome the subsequent combinatorial problem in our first approach. Finally, this new algorithm was tested with 16- year-rainfall series. The obtained gains are 60% of total volume rejected to the natural environment and of 80 % in the number of discharges.

Keywords: RTC, paradigm, optimization, automation

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Authors: Malinwo Estone Ayikpa

Abstract:

Electric power systems are likely to operate with minimum losses and voltage meeting international standards. This is made possible generally by control actions provide by automatic voltage regulators, capacitors and transformers with on-load tap changer (OLTC). With the development of photovoltaic (PV) systems technology, their integration on distribution networks has increased over the last years to the extent of replacing the above mentioned techniques. The conventional analysis and simulation tools used for electrical networks are no longer able to take into account control actions necessary for studying distributed PV generation impact. This paper presents an unbalanced optimal power flow (OPF) model that minimizes losses with association of active power generation and reactive power control of single-phase and three-phase PV systems. Reactive power can be generated or absorbed using the available capacity and the adjustable power factor of the inverter. The unbalance OPF is formulated by current balance equations and solved by primal-dual interior point method. Several simulation cases have been carried out varying the size and location of PV systems and the results show a detailed view of the impact of PV distributed generation on distribution systems.

Keywords: distribution system, loss, photovoltaic generation, primal-dual interior point method

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Authors: Jia-Sin Li, Ying-Fang Wang, Cheing-Tong Yan

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In this study, an integrated approach of Google Spreadsheet and QR code which is free internet resources was used to improve the inspection procedure. The mobile phone Application（App）was also designed to combine with a web page to create an automatic checklist in order to provide a new integrated information of inspection management system. By means of client-server model, the client App is developed for Android mobile OS and the back end is a web server. It can set up App accounts including authorized data and store some checklist documents in the website. The checklist document URL could generate QR code first and then print and paste on the machine. The user can scan the QR code by the app and filled the checklist in the factory. In the meanwhile, the checklist data will send to the server, it not only save the filled data but also executes the related functions and charts. On the other hand, it also enables auditors and supervisors to facilitate the prevention and response to hazards, as well as immediate report data checks. Finally, statistics and professional analysis are performed using inspection records and other relevant data to not only improve the reliability, integrity of inspection operations and equipment loss control, but also increase plant safety and personnel performance. Therefore, it suggested that the traditional paper-based inspection method could be replaced by the APP which promotes the promotion of industrial security and reduces human error.

Keywords: checklist, Google spreadsheet, APP, self-inspection

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Authors: Yehya Rasool, Mohit Agrawal

Abstract:

The site characterization and site response analysis are the crucial steps for reliable seismic microzonation of an area. So, the basic parameters involved in these fundamental steps are required to be chosen properly in order to efficiently characterize the vulnerable sites of the study region. In this study, efforts are made to delineate the variations in the physical parameter of the soil for the summer and monsoon seasons of the year (2021) by using Horizontal-to-Vertical Spectral Ratios (HVSRs) recorded at five sites of the Indian Institute of Technology (Indian School of Mines), Dhanbad, Jharkhand, India. The data recording at each site was done in such a way that less amount of anthropogenic noise was recorded at each site. The analysis has been done for five seismic parameters like predominant frequency, H/V ratio, the phase velocity of Rayleigh waves, shear wave velocity (Vs), compressional wave velocity (Vp), and Poisson’s ratio for both the seasons of the year. From the results, it is observed that these parameters majorly vary drastically for the upper layers of soil, which in turn may affect the amplification ratios and probability of exceedance obtained from seismic hazard studies. The HVSR peak comes out to be higher in monsoon, with a shift in predominant frequency as compared to the summer season of the year 2021. Also, the drastic reduction in shear wave velocity (up to ~10 m) of approximately 7%-15% is also perceived during the monsoon period with a slight decrease in compressional wave velocity. Generally, the increase in the Poisson ratios is found to have higher values during monsoon in comparison to the summer period. Our study may be very beneficial to various agricultural and geotechnical engineering projects.

Keywords: HVSR, shear wave velocity profile, Poisson ratio, microtremor data

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Authors: Ming-Jong Tsai, T. M. Wu, R. C. Chu

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The purpose of this study is to develop an Advanced linear calibration Technique for air flow sensing by using CTA-based Hot wire Anemometry. It contains a host PC with Human Machine Interface, a wind tunnel, a wind speed controller, an automatic data acquisition module, and nonlinear calibration model. To improve the fitting error by using single fitting polynomial, this study proposes a Multiple three-order Polynomial Fitting Method (MPFM) for fitting the non-linear output of a CTA-based Hot wire Anemometry. The CTA-based anemometer with built-in fitting parameters is installed in the wind tunnel, and the wind speed is controlled by the PC-based controller. The Hot-Wire anemometer's thermistor resistance change is converted into a voltage signal or temperature differences, and then sent to the PC through a DAQ card. After completion measurements of original signal, the Multiple polynomial mathematical coefficients can be automatically calculated, and then sent into the micro-processor in the Hot-Wire anemometer. Finally, the corrected Hot-Wire anemometer is verified for the linearity, the repeatability, error percentage, and the system outputs quality control reports.

Keywords: flow rate sensing, hot wire, constant temperature anemometry (CTA), linear calibration, multiple three-order polynomial fitting method (MPFM), temperature compensation

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Authors: Ali J. Ghandour, Houssam A. Krayem, Abedelkarim A. Jezzini

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High-resolution satellite images and remote sensing can provide global information in a fast way compared to traditional methods of data collection. Under such high resolution, a road is not a thin line anymore. Objects such as cars and trees are easily identifiable. Automatic vehicles enumeration can be considered one of the most important applications in traffic management. In this paper, autonomous vehicle detection and classification approach in highway environment is proposed. This approach consists mainly of three stages: (i) first, a set of preprocessing operations are applied including soil, vegetation, water suppression. (ii) Then, road networks detection and delineation is implemented using built-up area index, followed by several morphological operations. This step plays an important role in increasing the overall detection accuracy since vehicles candidates are objects contained within the road networks only. (iii) Multi-level Otsu segmentation is implemented in the last stage, resulting in vehicle detection and classification, where detected vehicles are classified into cars and trucks. Accuracy assessment analysis is conducted over different study areas to show the great efficiency of the proposed method, especially in highway environment.

Keywords: remote sensing, object identification, vehicle and road extraction, vehicle and road features-based classification

Procedia PDF Downloads 228

Authors: Nelson Andres, Meeko C. Masangcap, John Denver D. Catapang

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Balanga City as, the heart of Bataan, is a growing City and is now at its fast pace of development. The growth of commerce in the city results to an increase in commuters who travel back and forth through the city, leading to congestions. Consequently, queuing of vehicles along national roads and even in the highways of the city have become a regular occurrence. This common scenario of commuters flocking the city, private and public vehicles going bumper to bumper, especially during the rush hours, greatly affect the flow of traffic vehicles and is now a burden not only to the commuters but also to the government who is trying to address this dilemma. Seeing these terrible events, the implementation of an elevated Automated Guide-way transit is seen as a possible solution to help in the decongestion of the affected parts of Balanga City.In response to the problem, the researchers identify if it is feasible to have an elevated guide-way transit in the vicinity of Sapphire Street in Balanga City, Bataan. Specifically, the study aims to determine who will be the riders based on the demographic profile, where the trip can be generated and distributed, the time when volume of people usually peaks and the estimated volume of passengers. Statistical analysis is applied to the data gathered to find out if there is an important relationship between the demographic profile of the respondents and their preference of having an elevated railway transit in the City of Balanga.

Keywords: ridership, AGT, railway, elevated track

Procedia PDF Downloads 75

Authors: Prarabdh Tiwari, M. Vidya Sagar, K. Bhima Raju, Joy Choudhury, Subash Chandra, E. Nagaiah, Shakeel Ahmed

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Passive seismic, a wavefield interferometric imaging, low cost and rapid tool for subsurface investigation is used for various geotechnical purposes such as hydrocarbon exploration, seismic microzonation, etc. With the recent advancement, its application has also been extended to groundwater exploration by means of finding the bedrock depth. Council of Scientific & Industrial Research (CSIR)-National Geophysical Research Institute (NGRI) has experimented passive seismic studies along with electrical resistivity tomography for groundwater in hard rock (Choutuppal, Hyderabad). Passive Seismic with Electrical Resistivity (ERT) can give more clear 2-D subsurface image for Groundwater Exploration in Hard Rock area. Passive seismic data were collected using a Tromino, a three-component broadband seismometer, to measure background ambient noise and processed using GRILLA software. The passive seismic results are found corroborating with ERT (Electrical Resistivity Tomography) results. For data acquisition purpose, Tromino was kept over 30 locations consist recording of 20 minutes at each station. These location shows strong resonance frequency peak, suggesting good impedance contrast between different subsurface layers (ex. Mica rich Laminated layer, Weathered layer, granite, etc.) This paper presents signature of passive seismic for hard rock terrain. It has been found that passive seismic has potential application for formation characterization and can be used as an alternative tool for delineating litho-stratification in an urban condition where electrical and electromagnetic tools cannot be applied due to high cultural noise. In addition to its general application in combination with electrical and electromagnetic methods can improve the interpreted subsurface model.

Keywords: passive seismic, resonant frequency, Tromino, GRILLA

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Authors: Amit Verma, Pardeep Kaur

Abstract:

In software development organizations, Component based Software engineering (CBSE) is emerging paradigm for software development and gained wide acceptance as it often results in increase quality of software product within development time and budget. In component reusability, main challenges are the right component identification from large repositories at right time. The major objective of this work is to provide efficient algorithm for storage and effective retrieval of components using neural network and parameters based on user choice through clustering. This research paper aims to propose an algorithm that provides error free and automatic process (for retrieval of the components) while reuse of the component. In this algorithm, keywords (or components) are extracted from software document, after by applying k mean clustering algorithm. Then weights assigned to those keywords based on their frequency and after assigning weights, ANN predicts whether correct weight is assigned to keywords (or components) or not, otherwise it back propagates in to initial step (re-assign the weights). In last, store those all keywords into repositories for effective retrieval. Proposed algorithm is very effective in the error correction and detection with user base choice while choice of component for reusability for efficient retrieval is there.

Keywords: component based development, clustering, back propagation algorithm, keyword based retrieval

Procedia PDF Downloads 376