Search results for: network diagnostic tool

Authors: Nanditha Rajamani, Anirudhaa R. Rao, Divya Sriram

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One of the greatest difficulties in treating patients with pain is the highly subjective nature of pain sensation. The measurement of pain intensity is primarily dependent on the patient’s report, often with little physical evidence to provide objective corroboration. This is also complicated by the fact that there are only few and expensive existing technologies (Functional Magnetic Resonance Imaging-fMRI). The need is thus clear and urgent for a reliable, non-invasive, non-painful, objective, readily adoptable, and coefficient diagnostic platform that provides additional diagnostic information to supplement its current regime with more information to assist doctors in diagnosing these patients. Thus, our idea of developing a pain detector was conceived to take a step further the detection and diagnosis of chronic and acute pain.

Keywords: pain sensor, microwave radiometery, pain sensation, fMRI

Procedia PDF Downloads 425

Authors: Fabiano Araujo Soares, Sauro Emerick Salomoni, Joao Paulo Lima da Silva, Igor Luiz Moura, Adson Ferreira da Rocha

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This paper presents a tool developed in the Matlab platform. It was developed to simplify the analysis of surface electromyography signals (S-EMG) in a way accessible to users that are not familiarized with signal processing procedures. The tool receives data by commands in window fields and generates results as graphics and excel tables. The underlying math of each S-EMG estimator is presented. Setup window and result graphics are presented. The tool was presented to four non-engineer users and all of them managed to appropriately use it after a 5 minutes instruction period.

Keywords: S-EMG estimators, electromyography, surface electromyography, ARV, RMS, MDF, MNF, CV

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Authors: Ali Alshumrani, Nathan Clarke, Bogdan Ghite, Stavros Shiaeles

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Digital forensics has become an essential tool in the investigation of cyber and computer-assisted crime. Arguably, given the prevalence of technology and the subsequent digital footprints that exist, it could have a significant role across almost all crimes. However, the variety of technology platforms (such as computers, mobiles, Closed-Circuit Television (CCTV), Internet of Things (IoT), databases, drones, cloud computing services), heterogeneity and volume of data, forensic tool capability, and the investigative cost make investigations both technically challenging and prohibitively expensive. Forensic tools also tend to be siloed into specific technologies, e.g., File System Forensic Analysis Tools (FS-FAT) and Network Forensic Analysis Tools (N-FAT), and a good deal of data sources has little to no specialist forensic tools. Increasingly it also becomes essential to compare and correlate evidence across data sources and to do so in an efficient and effective manner enabling an investigator to answer high-level questions of the data in a timely manner without having to trawl through data and perform the correlation manually. This paper proposes a Unified Forensic Analysis Tool (U-FAT), which aims to establish a common language for electronic information and permit multi-source forensic analysis. Core to this approach is the identification and development of forensic analyses that automate complex data correlations, enabling investigators to investigate cases more efficiently. The paper presents a systematic analysis of major crime categories and identifies what forensic analyses could be used. For example, in a child abduction, an investigation team might have evidence from a range of sources including computing devices (mobile phone, PC), CCTV (potentially a large number), ISP records, and mobile network cell tower data, in addition to third party databases such as the National Sex Offender registry and tax records, with the desire to auto-correlate and across sources and visualize in a cognitively effective manner. U-FAT provides a holistic, flexible, and extensible approach to providing digital forensics in technology, application, and data-agnostic manner, providing powerful and automated forensic analysis.

Keywords: digital forensics, evidence correlation, heterogeneous data, forensics tool

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Authors: Tariq A. El Shheibia, Halima Mohamed Belhamad

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This paper is considered securing data based on multi-path protocol (SDMP) in mobile ad hoc network utilizing OPNET simulator modular 14.5, including the AODV routing protocol at the network as based multi-path algorithm for message security in MANETs. The main idea of this work is to present a way that is able to detect the attacker inside the MANETs. The detection for this attacker will be performed by adding some effective parameters to the network.

Keywords: MANET, AODV, malicious node, OPNET

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Authors: Sofia Baldelli, Aman More

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Milk curd obstruction is commonly reported as being misdiagnosed for NEC, and they predominantly mimic each other in clinical presentation, including abdominal distension, vomiting, constipation, feeding intolerance and frank or occult blood PR. Using the case of a pre-term neonate misdiagnosed with necrotising enterocolitis when in fact, they had milk curd obstruction, we compare the two diagnoses and why they are hard to differentiate, the risk factors for clinicians to consider and the different management options. The main diagnostic tool for these conditions remains the plain radiograph and here we present the original radiograph of the neonate and discuss the classical radiological features of both diagnoses. We conclude that further imaging techniques such as ultrasound might be used to improve diagnosis when X-ray is inconclusive.

Keywords: milk curd obstruction, Necrotising Enterocolitis, radiology, pediatric surgery

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Authors: Rei-Heng Cheng, Wen-Pinn Fang

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

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

Procedia PDF Downloads 365

Authors: M. Pappa, C. Efstathiou, G. Livanos, P. Xidas, D. Vakondios, E. Maravelakis, M. Zervakis, A. Antoniadis

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The choice of cutting tools in manufacturing processes is an essential parameter on which the required manufacturing time, the consumed energy and the cost effort all depend. If the number of tool changing times could be minimized or even eliminated by using a single convex tool providing multiple profiles, then a significant benefit of time and energy saving, as well as tool cost, would be achieved. A typical machine contains a variety of tools in order to deal with different curvatures and material removal rates. In order to minimize the required cutting tool changes, Actively Deformable micro-Cutters (ADmC) will be developed. The design of the Actively Deformable micro-Cutters will be based on the same cutting technique and mounting method as that in typical cutters.

Keywords: deformable cutters, cutting tool, milling, turning, manufacturing

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Authors: Wang Xue, Fan Liwei

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The trust and use of social network platforms by users are instrumental factors that contribute to the platform’s sustainable development. Studying the influential factors of the use of social network platforms is beneficial for developing and maintaining a large user base. This study constructed an extended unified theory of acceptance and use of technology (UTAUT2) moderating model with perceived privacy risks to analyze the factors affecting the trust and use of social network platforms. 444 participants completed our 35 surveys, and we verified the survey results by structural equation model. Empirical results reveal the influencing factors that affect the trust and use of social network platforms, and the extended UTAUT2 model with perceived privacy risks increases the applicability of UTAUT2 in social network scenarios. Social networking platforms can increase their use rate by increasing the economics, functionality, entertainment, and privacy security of the platform.

Keywords: perceived privacy risk, social network, trust, use, UTAUT2 model

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Authors: Hamid Rostami Jaz, Kamran Ameri Siahooei

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Up to now different methods have been used to forecast the index returns and the index rate. Artificial intelligence and artificial neural networks have been one of the methods of index returns forecasting. This study attempts to carry out a comparative study on the performance of different Radial Base Neural Network and Feed-Forward Perceptron Neural Network to forecast investment returns on the index. To achieve this goal, the return on investment in Tehran Stock Exchange index is evaluated and the performance of Radial Base Neural Network and Feed-Forward Perceptron Neural Network are compared. Neural networks performance test is applied based on the least square error in two approaches of in-sample and out-of-sample. The research results show the superiority of the radial base neural network in the in-sample approach and the superiority of perceptron neural network in the out-of-sample approach.

Keywords: exchange index, forecasting, perceptron neural network, Tehran stock exchange

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Authors: A. Shebani, C. Pislaru

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Wear of materials is an everyday experience and has been observed and studied for long time. The prediction of wear is a fundamental problem in the industrial field, mainly correlated to the planning of maintenance interventions and economy. Pin-on-disc test is the most common test which is used to study the wear behaviour. In this paper, the pin-on-disc (AEROTECH UNIDEX 11) is used for the investigation of the effects of normal load and hardness of material on the wear under dry and sliding conditions. In the pin-on-disc rig, two specimens were used; one, a pin which is made of steel with a tip, is positioned perpendicular to the disc, where the disc is made of aluminium. The pin wear and disc wear were measured by using the following instruments: The Talysurf instrument, a digital microscope, and the alicona instrument; where the Talysurf profilometer was used to measure the pin/disc wear scar depth, and the alicona was used to measure the volume loss for pin and disc. After that, the Archard model, American Society for Testing and Materials model (ASTM), and neural network model were used for pin/disc wear modelling and the simulation results are implemented by using the Matlab program. This paper focuses on how the alicona can be considered as a powerful tool for wear measurements and how the neural network is an effective algorithm for wear estimation.

Keywords: wear modelling, Archard Model, ASTM Model, Neural Networks Model, Pin-on-disc Test, Talysurf, digital microscope, Alicona

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Authors: Yichao Lv, Minmin Cai, Yanqiang Tao, Xinyuan Zou, Chao Zhang, Xiangping Liu

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Objective: This study aims to explore the network structure of personality traits and mental health and identify key factors for effective intervention strategies. Methods: All participants (N = 6,067; 3,368 females) underwent the Eysenck Personality Scale (EPQ) to measure personality traits and the Symptom Self-rating Scale (SCL-90) to measure psychiatric symptoms. Using the mean value of the SCL-90 total score plus one standard deviation as the cutoff, 854 participants (14.08%; 528 females) were categorized as individuals exhibiting potential psychological symptoms and were included in the follow-up network analysis. The structure and bridge centrality of the network for dimensions of EPQ and SCL-90 were estimated. Results: Between the EPQ and SCL-90, psychoticism (P), extraversion (E), and neuroticism (N) showed the strongest positive correlations with somatization (Som), interpersonal sensitivity (IS), and hostility (Hos), respectively. Extraversion (E), somatization (Som), and anxiety (Anx) were identified as the most important bridge factors influencing the overall network. Conclusions: This study explored the network structure and complex connections between mental health and personality traits from a network perspective, providing potential targets for intervening in adolescent personality traits and mental health.

Keywords: EPQ, SCL-90, Chinese adolescents, network analysis

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Authors: Iting Chiang, Cheng-Yu Wei, Chin-Teng Kuo, Po-Sheng Hsu, Yo-Lun Yang, Yung-Chang Kang, Chien-Chon Chen, Chih-Yuan Chen

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In recent years, it is reported that microalloying of nitrogen atoms within traditional Cr-Mo-V hot work tool steels can achieve better high temperature mechanical properties, which thus leads to such metallurgical approach widely utilized in the several commercial advanced hot work tool steels. Although the performance of hot work tool steel can be improved better by alloy composition design strategy, the influence of processing parameters on the mechanical property, especially on the service life of hot work tool steel, is still not fully understood yet. A longer service life of hot work tool steel can decrease the manufacturing cost effectively and thus become a research hot spot. According to several previous studies, it is generally acknowledged the service life of hot work tool steels can be increased effectively as the steels possessing higher hardness and toughness due to the formation and propagation of microcracks within the steel can be inhibited effectively. Therefore, in the present research, the designed experiments are primarily to explore the synergistic effect of nitrogen content and austenitization conditioning on the mechanical properties of hot work tool steels has been conducted and analyzed. No matter the nitrogen content, the results indicated the hardness of hot work tool steels increased as the austenitization treatment executed at higher temperature. On the other hand, an optimum toughness of hot work tool steel can be achieved as the austenitization treatment performed at a suitable temperature range. The possible explanation of such metallurgical phenomenon has been also proposed and analyzed in the present research.

Keywords: hot work tool steel, Cr-Mo-V, toughness, hardness, TEM

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Authors: Xinyan Zhang, Zhipeng Tan, Shan Fan

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The first layer of defense against data loss is the backup data. This paper implements an agent-based network backup system used the backup, server-storage and server-backup agent these tripartite construction, and we realize the snapshot and hierarchical index in the NSBS. It realizes the control command and data flow separation, balances the system load, thereby improving the efficiency of the system backup and recovery. The test results show the agent-based network backup system can effectively improve the task-based concurrency, reasonably allocate network bandwidth, the system backup performance loss costs smaller and improves data recovery efficiency by 20%.

Keywords: agent, network backup system, three architecture model, NSBS

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Authors: Ebenezer Obaloluwa Olaniyi

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In this paper, an intelligent system has been designed to grade apple based on either its defective or healthy for production in food processing. This paper is segmented into two different phase. In the first phase, the image processing techniques were employed to extract the necessary features required in the apple. These techniques include grayscale conversion, segmentation where a threshold value is chosen to separate the foreground of the images from the background. Then edge detection was also employed to bring out the features in the images. These extracted features were then fed into the neural network in the second phase of the paper. The second phase is a classification phase where neural network employed to classify the defective apple from the healthy apple. In this phase, the network was trained with back propagation and tested with feed forward network. The recognition rate obtained from our system shows that our system is more accurate and faster as compared with previous work.

Keywords: image processing, neural network, apple, intelligent system

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Authors: Oyebade K. Oyedotun

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The cardiotocogram is a technical recording of the heartbeat rate and uterine contractions of a fetus during pregnancy. During pregnancy, several complications can occur to both the mother and the fetus; hence it is very crucial that medical experts are able to find technical means to check the healthiness of the mother and especially the fetus. It is very important that the fetus develops as expected in stages during the pregnancy period; however, the task of monitoring the health status of the fetus is not that which is easily achieved as the fetus is not wholly physically available to medical experts for inspection. Hence, doctors have to resort to some other tests that can give an indication of the status of the fetus. One of such diagnostic test is to obtain cardiotocograms of the fetus. From the analysis of the cardiotocograms, medical experts can determine the status of the fetus, and therefore necessary medical interventions. Generally, medical experts classify examined cardiotocograms into ‘normal’, ‘suspect’, or ‘pathological’. This work presents an artificial neural network based decision support system which can filter cardiotocograms data, producing the corresponding statuses of the fetuses. The capability of artificial neural network to explore the cardiotocogram data and learn features that distinguish one class from the others has been exploited in this research. In this research, feedforward and radial basis neural networks were trained on a publicly available database to classify the processed cardiotocogram data into one of the three classes: ‘normal’, ‘suspect’, or ‘pathological’. Classification accuracies of 87.8% and 89.2% were achieved during the test phase of the trained network for the feedforward and radial basis neural networks respectively. It is the hope that while the system described in this work may not be a complete replacement for a medical expert in fetus status evaluation, it can significantly reinforce the confidence in medical diagnosis reached by experts.

Keywords: decision support, cardiotocogram, classification, neural networks

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Authors: Ji-Hoon Hong, Dong-Hee Kim, Nam-Uk Kim, Tai-Myoung Chung

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Smartphone users are increasing rapidly. Accordingly, many companies are running BYOD (Bring Your Own Device: Policies to bring private-smartphones to the company) policy to increase work efficiency. However, smartphones are always under the threat of malware, thus the company network that is connected smartphone is exposed to serious risks. Most smartphone malware detection techniques are to perform an independent detection (perform the detection of a single target application). In this paper, we analyzed a variety of intrusion detection techniques. Based on the results of analysis propose an agent using the network IDS.

Keywords: android malware detection, software-defined network, interaction environment, android malware detection, software-defined network, interaction environment

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Authors: Alireza Alesaadi

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Reliability analysis is a powerful method for determining the weak points of the electrical networks. In designing of electrical network, it is tried to design the most reliable network with minimal system shutting down, but it is usually associated with increasing the cost. In this paper, using adaptive genetic algorithm, a method was presented that provides the most reliable system with a certain economical cost. Finally, the proposed method is applied to a sample network and results will be analyzed.

Keywords: reliability, adaptive genetic algorithm, electrical network, communication engineering

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Authors: Hala Shaari, Nuredin Ahmed

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Teaching computer programming is recognized to be difficult and a real challenge. The biggest problem faced by novice programmers is their lack of understanding of basic programming concepts. A visualized learning tool was developed and used by volunteered first-year students for two semesters. The purposes of this paper are firstly, to emphasize factors which directly affect the performance of our students negatively. Secondly, to examine whether the proposed tool would improve their performance and learning progression. The results of adopting this tool were conducted using a pre-survey and post-survey questionnaire. As a result, students who used the learning tool showed better performance in their programming subject.

Keywords: factors, novice, programming, visualization

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Authors: Katherine Carl Payne, Moshe Dror

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The problem of minimum cost routing has been extensively explored in a variety of contexts. While there is a prevalence of routing applications based on least distance, time, and related attributes, exertion-based routing has remained relatively unexplored. In particular, the network structures traditionally used to construct minimum cost paths are not suited to representing exertion or finding paths of least exertion based on road gradient. In this paper, we introduce a topographical network or “topograph” that enables minimum cost routing based on the exertion metric on each arc in a given road network as it is related to changes in road gradient. We describe an algorithm for topograph construction and present the implementation of the topograph on a road network of the state of California with ~22 million nodes.

Keywords: topograph, RPE, routing, GIS

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Authors: Surabhi Agrawal Kohli, Sunita Gupta, Esha Khanuja, Parul Garg, P. Gupta

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Background: Adenomyosis is a common gynaecological condition that affects the menstruating women. Uterine enlargement, dysmenorrhoea, and menorrhagia are regarded as the cardinal clinical symptoms of adenomyosis. Classically it was thought, compared with ultrasonography, when adenomyosis is suspected, MRI enables more accurate diagnosis of the disease. Materials and Methods: 172 subjects were enrolled after an informed consent that had complaints of HMB, dyspareunia, dysmenorrhea, and chronic pelvic pain. Detailed history of the enrolled subjects was taken, followed by a clinical examination. These patients were then subjected to TVS where myometrial echo texture, presence of myometrial cysts, blurring of endomyometrial junction was noted. MRI was followed which noted the presence of junctional zone thickness and myometrial cysts. After hysterectomy, histopathological diagnosis was obtained. Results: 78 participants were analysed. The mean age was 44.2 years. 43.5% had parity of 4 or more. heavy menstrual bleeding (HMB) was present in 97.8% and dysmenorrhea in 93.48 % of HPE positive patient. Transvaginal sonography (TVS) and MRI had a sensitivity of 89.13% and 80.43%, specificity of 90.62% and 84.37%, positive likelihood ratio of 9.51 and 5.15, negative likelihood ratio of 0.12 and 0.23, positive predictive value of 93.18% and 88.1%, negative predictive value of 85.29% and 75% and a diagnostic accuracy of 89.74% and 82.5%. Comparison of sensitivity (p=0.289) and specificity (p=0.625) showed no statistically significant difference between TVS and MRI. Conclusion: Prevalence of 30.23%. HMB with dysmenorrhoea and chronic pelvic pain helps in diagnosis. TVS (Endomyometrial junction blurring) is both sensitive and specific in diagnosing adenomyosis without need for additional diagnostic tool. Both TVS and MRI are equally efficient, however because of certain additional advantages of TVS over MRI, it may be used as the first choice of imaging. MRI may be used additionally in difficult cases as well as in patients with existing co-pathologies.

Keywords: adenomyosis, heavy menstrual bleeding, MRI, TVS

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Authors: Ebrahim Panah, Muhammad Yasir Babar

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Thanks to the development of online technology and social networks, people are able to communicate as well as learn. WhatsApp is a popular social network which is growingly gaining popularity. This app can be used for communication as well as education. It can be used for instructor-learner, learner-learner, and learner-content interactions; however, very little knowledge is available on these potentials of WhatsApp. The current study was undertaken to investigate university students’ perceptions of WhatsApp used as a tool for instructor-learner dialogue, learner-content dialogue, and learner-learner dialogue. The study adopted a survey approach and distributed the questionnaire developed by Google Forms to 54 (11 males and 43 females) university students. The obtained data were analyzed using SPSS version 20. The result of data analysis indicates that students have positive attitudes towards WhatsApp as a tool for Instructor-Learner Dialogue: it easy to reach the lecturer (4.07), the instructor gives me valuable feedback on my assignment (4.02), the instructor is supportive during course discussion and offers continuous support with the class (4.00). Learner-Content Dialogue: WhatsApp allows me to academically engage with lecturers anytime, anywhere (4.00), it helps to send graphics such as pictures or charts directly to the students (3.98), it also provides out of class, extra learning materials and homework (3.96), and Learner-Learner Dialogue: WhatsApp is a good tool for sharing knowledge with others (4.09), WhatsApp allows me to academically engage with peers anytime, anywhere (4.07), and we can interact with others through the use of group discussion (4.02). It was also found that there are significant positive correlations between students’ perceptions of Instructor-Learner Dialogue (ILD), Learner-Content Dialogue (LCD), Learner-Learner Dialogue (LLD) and WhatsApp Application in classroom. The findings of the study have implications for lectures, policy makers and curriculum developers.

Keywords: instructor-learner dialogue, learners-contents dialogue, learner-learner dialogue, whatsapp application

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Authors: Sukriti Sabharwal, Sonali Bhattar, Shikhar Saxena

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Introduction: COVID-19 molecular diagnostic laboratory is the cornerstone of the COVID-19 disease diagnosis as the patient’s treatment and management protocol depend on the molecular results. For this purpose, it is extremely important that the laboratory conducting these results adheres to the quality management processes to increase the accuracy and validity of the reports generated. We started our own molecular diagnostic setup at the onset of the pandemic. Therefore, we conducted this study to generate our quality management data to help us in improving on our weak points. Materials and Methods: A total of 14561 samples were evaluated by the retrospective observational method. The quality variables analysed were classified into pre-analytical, analytical, and post-analytical variables, and the results were presented in percentages. Results: Among the pre-analytical variables, sample leaking was the most common cause of the rejection of samples (134/14561, 0.92%), followed by non-generation of SRF ID (76/14561, 0.52%) and non-compliance to triple packaging (44/14561, 0.3%). The other pre-analytical aspects assessed were incomplete patient identification (17/14561, 0.11%), insufficient quantity of samples (12/14561, 0.08%), missing forms/samples (7/14561, 0.04%), samples in the wrong vials/empty VTM tubes (5/14561, 0.03%) and LIMS entry not done (2/14561, 0.01%). We are unable to obtain internal quality control in 0.37% of samples (55/14561). We also experienced two incidences of cross-contamination among the samples resulting in false-positive results. Among the post-analytical factors, a total of 0.07% of samples (11/14561) could not be dispatched within the stipulated time frame. Conclusion: Adherence to quality control processes is foremost for the smooth running of any diagnostic laboratory, especially the ones involved in critical reporting. Not only do the indicators help in keeping in check the laboratory parameters but they also allow comparison with other laboratories.

Keywords: laboratory quality management, COVID-19, molecular diagnostics, healthcare

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Authors: Ella Tyuryumina, Alexey Neznanov

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This study is an attempt to obtain reliable data on the natural history of breast cancer growth. We analyze the opportunities for using classical mathematical models (exponential and logistic tumor growth models, Gompertz and von Bertalanffy tumor growth models) to try to describe growth of the primary tumor and the secondary distant metastases of human breast cancer. The research aim is to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoMPaS and corresponding software. We are interested in: 1) modelling the whole natural history of the primary tumor and the secondary distant metastases; 2) developing adequate and precise CoMPaS which reflects relations between the primary tumor and the secondary distant metastases; 3) analyzing the CoMPaS scope of application; 4) implementing the model as a software tool. The foundation of the CoMPaS is the exponential tumor growth model, which is described by determinate nonlinear and linear equations. The CoMPaS corresponds to TNM classification. It allows to calculate different growth periods of the primary tumor and the secondary distant metastases: 1) ‘non-visible period’ for the primary tumor; 2) ‘non-visible period’ for the secondary distant metastases; 3) ‘visible period’ for the secondary distant metastases. The CoMPaS is validated on clinical data of 10-years and 15-years survival depending on the tumor stage and diameter of the primary tumor. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer growth models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. The CoMPaS model and predictive software: a) fit to clinical trials data; b) detect different growth periods of the primary tumor and the secondary distant metastases; c) make forecast of the period of the secondary distant metastases appearance; d) have higher average prediction accuracy than the other tools; e) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoMPaS: the number of doublings for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases. The CoMPaS enables, for the first time, to predict ‘whole natural history’ of the primary tumor and the secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on the primary tumor sizes. Summarizing: a) CoMPaS describes correctly the primary tumor growth of IA, IIA, IIB, IIIB (T1-4N0M0) stages without metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and inception of the secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, metastases in lymph nodes, primary tumor, survival

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Authors: Mustafa Kemal Bilici, Memduh Kurtulmuş, İlyas Kartal, Ahmet İrfan Yükler

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Friction stir welding is a solid-state joining process that has gained acceptable progress in recent years. This method which was first used for welding of aluminum and its alloys is now employed for welding of other materials such as polymers and composites. The aim of the present work is to investigate the mechanical properties of butt joints produced by friction stir welding (FSW) in high density polyethylene sheets of 4 mm thickness. The effects of critical welding parameters and tool design have affected on mechanical properties, weld surface and macrostructure of friction stir welded polyethylene. Experiments were performed at tool rotational speeds of 600, 900, 1200 and 1500 r/min and traverse speeds of 30, 45 and 60 mm/min, tool diameters (d) of 4, 5, 6 mm and tool shoulder diameters (D) 20, 25, 30 mm. A strength value of 80 % of the base material was achieved at the isolated optimum welding condition. According to the tool design, the welding parameters and the mechanical properties changed to a great extent. The highest tensile strength was achieved at low feed rates, high tool rotation speeds and shoulder diameters/pin diameters ratio.

Keywords: friction stir welding, mechanical properties, polyethylene, high density polyethylene, tool design

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Authors: Majid Arvan, Peyman Beygi, Sina Rokhsati

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In-time detection of fire in buildings is of great importance. Employing intelligent methods in data processing in fire detection systems leads to a significant reduction of fire damage at lowest cost. In this paper, the raw data obtained from the fire detection sensor networks in buildings is processed by using intelligent methods based on neural networks and the likelihood of fire happening is predicted. In order to enhance the quality of system, the noise in the sensor data is reduced by analyzing wavelets and applying SVD technique. Meanwhile, the proposed neural network is trained using particle swarm optimization (PSO). In the simulation work, the data is collected from sensor network inside the room and applied to the proposed network. Then the outputs are compared with conventional MLP network. The simulation results represent the superiority of the proposed method over the conventional one.

Keywords: intelligent fire detection, neural network, particle swarm optimization, fire sensor network

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Authors: Gherbi Khadidja

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In the Mediterranean region, water resources are limited and very unevenly distributed in space and time. The main objective of this project is the development of a wireless network for the management of water resources in northern Algeria, the Mitidja plain, which helps farmers to irrigate in the most optimized way and solve the problem of water shortage in the region. Therefore, we will develop an aid tool that can modernize and replace some traditional techniques, according to the real needs of the crops and according to the soil conditions as well as the climatic conditions (soil moisture, precipitation, characteristics of the unsaturated zone), These data are collected in real-time by sensors and analyzed by an algorithm and displayed on a mobile application and the website. The results are essential information and alerts with recommendations for action to farmers to ensure the sustainability of the agricultural sector under water shortage conditions. In the first part: We want to set up a wireless sensor network, for precise management of water resources, by presenting another type of equipment that allows us to measure the water content of the soil, such as the Watermark probe connected to the sensor via the acquisition card and an Arduino Uno, which allows collecting the captured data and then program them transmitted via a GSM module that will send these data to a web site and store them in a database for a later study. In a second part: We want to display the results on a website or a mobile application using the database to remotely manage our smart irrigation system, which allows the farmer to use this technology and offers the possibility to the growers to access remotely via wireless communication to see the field conditions and the irrigation operation, at home or at the office. The tool to be developed will be based on satellite imagery as regards land use and soil moisture. These tools will make it possible to follow the evolution of the needs of the cultures in time, but also to time, and also to predict the impact on water resources. According to the references consulted, if such a tool is used, it can reduce irrigation volumes by up to up to 40%, which represents more than 100 million m3 of savings per year for the Mitidja. This volume is equivalent to a medium-size dam.

Keywords: optimal irrigation, soil moisture, smart irrigation, water management

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Authors: Ruairi J. McMillan

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Introduction: This critical analysis aims to ascertain how well neuroanatomical aetiologies are communicated within 20 case reports of aphasia. Neuroanatomical visualisations based on dissected brain specimens were produced and combined with white matter tract and vascular taxonomies of function in order to address the most consistently underreported features found within the aphasic case study reports. Together, these approaches are intended to integrate aphasiological knowledge from the past 20 years with aphasiological diagnostics, and to act as prototypal resources for both researchers and clinical professionals. The medico-legal precedent for aphasia diagnostics under Canadian, US and UK case law and the neuroimaging/neurological diagnostics relative to the functional capacity of aphasic patients are discussed in relation to the major findings of the literary analysis, neuroimaging protocols in clinical use today, and the neuroanatomical aetiologies of different aphasias. Basic Methodology: Literature searches of relevant scientific databases (e.g, OVID medline) were carried out using search terms such as aphasia case study (year) & stroke induced aphasia case study. A series of 7 diagnostic reporting criteria were formulated, and the resulting case studies were scored / 7 alongside clinical stroke criteria. In order to focus on the diagnostic assessment of the patient’s condition, only the case report proper (not the discussion) was used to quantify results. Statistical testing established if specific reporting criteria were associated with higher overall scores and potentially inferable increases in quality of reporting. Statistical testing of whether criteria scores were associated with an unclear/adjusted diagnosis were also tested, as well as the probability of a given criterion deviating from an expected estimate. Major Findings: The quantitative analysis of neuroanatomically driven diagnostics in case studies of aphasia revealed particularly low scores in the connection of neuroanatomical functions to aphasiological assessment (10%), and in the inclusion of white matter tracts within neuroimaging or assessment diagnostics (30%). Case studies which included clinical mention of white matter tracts within the report itself were distributed among higher scoring cases, as were case studies which (as clinically indicated) related the affected vascular region to the brain parenchyma of the language network. Concluding Statement: These findings indicate that certain neuroanatomical functions are integrated less often within the patient report than others, despite a precedent for well-integrated neuroanatomical aphasiology also being found among the case studies sampled, and despite these functions being clinically essential in diagnostic neuroimaging and aphasiological assessment. Therefore, ultimately the integration and specificity of aetiological neuroanatomy may contribute positively to the capacity and autonomy of aphasic patients as well as their clinicians. The integration of a full aetiological neuroanatomy within the reporting of aphasias may improve patient outcomes and sustain autonomy in the event of medico-ethical investigation.

Keywords: aphasia, language network, functional neuroanatomy, aphasiological diagnostics, medico-legal ethics

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Authors: Ganfeng Yu, Yuefeng Ma, Shanliang Yang

Abstract:

The word discovery is a key problem in text information retrieval technology. Methods in new word discovery tend to be closely related to words because they generally obtain new word results by analyzing words. With the popularity of social networks, individual netizens and online self-media have generated various network texts for the convenience of online life, including network words that are far from standard Chinese expression. How detect network words is one of the important goals in the field of text information retrieval today. In this paper, we integrate the word embedding model and clustering methods to propose a network word discovery framework based on sentence semantic similarity (S³-NWD) to detect network words effectively from the corpus. This framework constructs sentence semantic vectors through a distributed representation model, uses the similarity of sentence semantic vectors to determine the semantic relationship between sentences, and finally realizes network word discovery by the meaning of semantic replacement between sentences. The experiment verifies that the framework not only completes the rapid discovery of network words but also realizes the standard word meaning of the discovery of network words, which reflects the effectiveness of our work.

Keywords: text information retrieval, natural language processing, new word discovery, information extraction

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Authors: Daniela Evtimovska, Ivana Srbinovska, Padraig O’Rourke

Abstract:

Kostal Macedonia has the challenge to mill a rigid-flex printed circuit board (PCB). The PCB elaborated in this paper is made of FR4 material covered with polyimide through the whole surface on the one side, including the tabs where PCBs need to be separated. After milling only 1.44 meters, the updraft routing tool isn’t effective and causes polyimide debris on all PCB cuts if it continues to mill with the same tool. Updraft routing tool is used for all another product in Kostal Macedonia, and it is changing after milling 60 meters. Changing the tool adds 80 seconds to the cycle time. One solution is using a laser-cut machine. Buying a laser-cut machine for cutting only one product doesn’t make financial sense. The focus is given to find an internal solution among the options under review to solve the issue with polyimide debris. In the paper, the design of the rigid-flex panel is described deeply. It is evaluated downdraft routing tool as a possible solution which could be used for the flex rigid panel as a specific product. It is done a comparison between updraft and down draft routing tools from a technical and financial aspect of view, taking into consideration the customer requirements for the rigid-flex PCB. The results show that using the downdraft routing tool is the best solution in this case. This tool is more expensive for 0.62 euros per piece than updraft. The downdraft routing tool needs to be changed after milling 43.44 meters in comparison with the updraft tool, which needs to be changed after milling only 1.44 meters. It is done analysis which actions should be taken in order further improvements and the possibility of maximum serving of downdraft routing tool.

Keywords: Kostal Macedonia, rigid flex PCB, polyimide, debris, milling process, up/down draft routing tool

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Authors: Sopheak Sorn, Kwok Yip Szeto

Abstract:

Reliability is one of the important measures of how well the system meets its design objective, and mathematically is the probability that a complex system will perform satisfactorily. When the system is described by a network of N components (nodes) and their L connection (links), the reliability of the system becomes a network design problem that is an NP-hard combinatorial optimization problem. In this paper, we address the network design problem for a random point set’s pattern in two dimensions. We make use of a Voronoi construction with each cell containing exactly one point in the point pattern and compute the reliability of the Voronoi’s dual, i.e. the Delaunay graph. We further investigate the communicability of the Delaunay network. We find that there is a positive correlation and a negative correlation between the homogeneity of a Delaunay's degree distribution with its reliability and its communicability respectively. Based on the correlations, we alter the communicability and the reliability by performing random edge flips, which preserve the number of links and nodes in the network but can increase the communicability in a Delaunay network at the cost of its reliability. This transformation is later used to optimize a Delaunay network with the optimum geometric mean between communicability and reliability. We also discuss the importance of the edge flips in the evolution of real soap froth in two dimensions.

Keywords: Communicability, Delaunay triangulation, Edge Flip, Reliability, Two dimensional network, Voronio

Procedia PDF Downloads 390