Search results for: false testimony
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 412

Search results for: false testimony

322 Fault Prognostic and Prediction Based on the Importance Degree of Test Point

Authors: Junfeng Yan, Wenkui Hou

Abstract:

Prognostics and Health Management (PHM) is a technology to monitor the equipment status and predict impending faults. It is used to predict the potential fault and provide fault information and track trends of system degradation by capturing characteristics signals. So how to detect characteristics signals is very important. The select of test point plays a very important role in detecting characteristics signal. Traditionally, we use dependency model to select the test point containing the most detecting information. But, facing the large complicated system, the dependency model is not built so easily sometimes and the greater trouble is how to calculate the matrix. Rely on this premise, the paper provide a highly effective method to select test point without dependency model. Because signal flow model is a diagnosis model based on failure mode, which focuses on system’s failure mode and the dependency relationship between the test points and faults. In the signal flow model, a fault information can flow from the beginning to the end. According to the signal flow model, we can find out location and structure information of every test point and module. We break the signal flow model up into serial and parallel parts to obtain the final relationship function between the system’s testability or prediction metrics and test points. Further, through the partial derivatives operation, we can obtain every test point’s importance degree in determining the testability metrics, such as undetected rate, false alarm rate, untrusted rate. This contributes to installing the test point according to the real requirement and also provides a solid foundation for the Prognostics and Health Management. According to the real effect of the practical engineering application, the method is very efficient.

Keywords: false alarm rate, importance degree, signal flow model, undetected rate, untrusted rate

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321 Fusion of Finger Inner Knuckle Print and Hand Geometry Features to Enhance the Performance of Biometric Verification System

Authors: M. L. Anitha, K. A. Radhakrishna Rao

Abstract:

With the advent of modern computing technology, there is an increased demand for developing recognition systems that have the capability of verifying the identity of individuals. Recognition systems are required by several civilian and commercial applications for providing access to secured resources. Traditional recognition systems which are based on physical identities are not sufficiently reliable to satisfy the security requirements due to the use of several advances of forgery and identity impersonation methods. Recognizing individuals based on his/her unique physiological characteristics known as biometric traits is a reliable technique, since these traits are not transferable and they cannot be stolen or lost. Since the performance of biometric based recognition system depends on the particular trait that is utilized, the present work proposes a fusion approach which combines Inner knuckle print (IKP) trait of the middle, ring and index fingers with the geometrical features of hand. The hand image captured from a digital camera is preprocessed to find finger IKP as region of interest (ROI) and hand geometry features. Geometrical features are represented as the distances between different key points and IKP features are extracted by applying local binary pattern descriptor on the IKP ROI. The decision level AND fusion was adopted, which has shown improvement in performance of the combined scheme. The proposed approach is tested on the database collected at our institute. Proposed approach is of significance since both hand geometry and IKP features can be extracted from the palm region of the hand. The fusion of these features yields a false acceptance rate of 0.75%, false rejection rate of 0.86% for verification tests conducted, which is less when compared to the results obtained using individual traits. The results obtained confirm the usefulness of proposed approach and suitability of the selected features for developing biometric based recognition system based on features from palmar region of hand.

Keywords: biometrics, hand geometry features, inner knuckle print, recognition

Procedia PDF Downloads 192
320 A Human Factors Approach to Workload Optimization for On-Screen Review Tasks

Authors: Christina Kirsch, Adam Hatzigiannis

Abstract:

Rail operators and maintainers worldwide are increasingly replacing walking patrols in the rail corridor with mechanized track patrols -essentially data capture on trains- and on-screen reviews of track infrastructure in centralized review facilities. The benefit is that infrastructure workers are less exposed to the dangers of the rail corridor. The impact is a significant change in work design from walking track sections and direct observation in the real world to sedentary jobs in the review facility reviewing captured data on screens. Defects in rail infrastructure can have catastrophic consequences. Reviewer performance regarding accuracy and efficiency of reviews within the available time frame is essential to ensure safety and operational performance. Rail operators must optimize workload and resource loading to transition to on-screen reviews successfully. Therefore, they need to know what workload assessment methodologies will provide reliable and valid data to optimize resourcing for on-screen reviews. This paper compares objective workload measures, including track difficulty ratings and review distance covered per hour, and subjective workload assessments (NASA TLX) and analyses the link between workload and reviewer performance, including sensitivity, precision, and overall accuracy. An experimental study was completed with eight on-screen reviewers, including infrastructure workers and engineers, reviewing track sections with different levels of track difficulty over nine days. Each day the reviewers completed four 90-minute sessions of on-screen inspection of the track infrastructure. Data regarding the speed of review (km/ hour), detected defects, false negatives, and false positives were collected. Additionally, all reviewers completed a subjective workload assessment (NASA TLX) after each 90-minute session and a short employee engagement survey at the end of the study period that captured impacts on job satisfaction and motivation. The results showed that objective measures for tracking difficulty align with subjective mental demand, temporal demand, effort, and frustration in the NASA TLX. Interestingly, review speed correlated with subjective assessments of physical and temporal demand, but to mental demand. Subjective performance ratings correlated with all accuracy measures and review speed. The results showed that subjective NASA TLX workload assessments accurately reflect objective workload. The analysis of the impact of workload on performance showed that subjective mental demand correlated with high precision -accurately detected defects, not false positives. Conversely, high temporal demand was negatively correlated with sensitivity and the percentage of detected existing defects. Review speed was significantly correlated with false negatives. With an increase in review speed, accuracy declined. On the other hand, review speed correlated with subjective performance assessments. Reviewers thought their performance was higher when they reviewed the track sections faster, despite the decline in accuracy. The study results were used to optimize resourcing and ensure that reviewers had enough time to review the allocated track sections to improve defect detection rates in accordance with the efficiency-thoroughness trade-off. Overall, the study showed the importance of a multi-method approach to workload assessment and optimization, combining subjective workload assessments with objective workload and performance measures to ensure that recommendations for work system optimization are evidence-based and reliable.

Keywords: automation, efficiency-thoroughness trade-off, human factors, job design, NASA TLX, performance optimization, subjective workload assessment, workload analysis

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319 Biopotential of Introduced False Indigo and Albizia’s Weevils in Host Plant Control and Duration of Its Development Stages in Southern Regions of Panonian Basin

Authors: Renata Gagić-Serdar, Miroslava Markovic, Ljubinko Rakonjac, Aleksandar Lučić

Abstract:

The paper present the results of the entomological experimental studies of the biological, ecological, and (bionomic) insect performances, such as seasonal adaptation of introduced monophagous false indigo and albizias weevil’s Acanthoscelides pallidipennis Motschulsky. and Bruchidius terrenus (Sharp), Coleoptera: Chrysomelidae: Bruchinae, to phenological phases of aggressive invasive host plant Amorpha fruticosa L. and Albizia julibrissin (Fabales: Fabaceae) on the territory of Republic of Serbia with special attention on assessing and monitoring of new formed and detected inter species relations between autochthons parasite wasps from fauna (Hymenoptera: Chalcidoidea) and herbaceous seed weevil beetle. During 15 years (2006-2021), on approximately 30 localities, data analyses were done for observed experimental host plants from samples with statistical significance. Status of genera from families Hymenoptera: Chalcidoidea.: Pteromalidae and Eulophidae, after intensive investigations, has been trophicly identified. Recorded seed pest species of A. fruticosa or A. julibrissin (Fabales: Fabaceae) was introduced in Serbia and planted as ornamental trees, they also were put undergo different kinds of laboratory and field research tests during this period in a goal of collecting data about lasting each of develop stage of their seed beetles. Field generations in different stages were also monitored by continuous infested seed collecting and its disection. Established host plant-seed predator linkage was observed in correlation with different environment parameters, especially water level fluctuations in bank corridor formation stands and riparian cultures.

Keywords: amorpha, albizia, chalcidoid wasp, invasiveness, weevils

Procedia PDF Downloads 64
318 Fact-checking and Political Polarization in an Emerging Democracy

Authors: Eric Agyekum, Dominic Asitanga

Abstract:

Ghana is widely considered asa beacon of democracy in sub-Saharan Africa. With a relatively free media, the country was ranked30thin the world and third in Africaon the 2021 Press Freedom Index. Despite the democratic gains, itis one of the most politically polarized nations in the world. Ghana’spolitical division is evident in the current hunglegislature, where each of the two dominant political parties has 137 members, with an independent member occupying the remaining one seat. Misinformation and fake newsthrive in systems with acuteideological and political differences(Imelda et al, 2021; Azzimonti&Fernandes, 2018; Spohr, 2017) and Ghana is no exception. The information disorder problem has been exacerbatedby the COVID-19 pandemic, with its attendant conspiracy theories and speculations, making it difficult for the media and fact-checking organizations to verifyall claims and flag false information. In Ghana, fact-checking agencies like Ghana Fact, Dubawa Ghana, and some mainstream news media organizations have been fact-checking political claims, COVID-19 conspiracy theories, and many others. However, it is not clear if the audience consumeand attach prominence to these fact-checked stories or even visit the websites of the fact-checking agencies to read the content. Nekmat (2020) opine that though the literature on fact-checking suggest that fact-checked stories can alter readers’ beliefs, very few studies have investigated the patronage and the potential of fact-checks to deter users from sharing false news with others, particularly on social media. In response to Nekmat, this study has been initiated to examine the perception and attitude of the audience in Ghana towards fact-checks. Anchored on the principles of the nudge theory, this study will investigate how fact-checked stories alters readers’ behavioural patterns. A survey will be conducted to collect data from sampled members of the Ghanaian society.

Keywords: fact-checking, information disorder, nudge theory, political polarization

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317 Multicenter Evaluation of the ACCESS Anti-HCV Assay on the DxI 9000 ACCESS Immunoassay Analyzer, for the Detection of Hepatitis C Virus Antibody

Authors: Dan W. Rhodes, Juliane Hey, Magali Karagueuzian, Florianne Martinez, Yael Sandowski, Vanessa Roulet, Mahmoud Badawi, Mohammed-Amine Chakir, Valérie Simon, Jérémie Gautier, Françoise Le Boulaire, Catherine Coignard, Claire Vincent, Sandrine Greaume, Isabelle Voisin

Abstract:

Background: Beckman Coulter, Inc. (BEC) has recently developed a fully automated second-generation anti-HCV test on a new immunoassay platform. The objective of this multicenter study conducted in Europe was to evaluate the performance of the ACCESS anti-HCV assay on the recently CE-marked DxI 9000 ACCESS Immunoassay Analyzer as an aid in the diagnosis of HCV (Hepatitis C Virus) infection and as a screening test for blood and plasma donors. Methods: The clinical specificity of the ACCESS anti-HCV assay was determined using HCV antibody-negative samples from blood donors and hospitalized patients. Sample antibody status was determined by a CE-marked anti-HCV assay (Abbott ARCHITECTTM anti-HCV assay or Abbott PRISM HCV assay) with an additional confirmation method (Immunoblot testing with INNO-LIATM HCV Score - Fujirebio), if necessary, according to pre-determined testing algorithms. The clinical sensitivity was determined using known HCV antibody-positive samples, identified positive by Immunoblot testing with INNO-LIATM HCV Score - Fujirebio. HCV RNA PCR or genotyping was available on all Immunoblot positive samples for further characterization. The false initial reactive rate was determined on fresh samples from blood donors and hospitalized patients. Thirty (30) commercially available seroconversion panels were tested to assess the sensitivity for early detection of HCV infection. The study was conducted from November 2019 to March 2022. Three (3) external sites and one (1) internal site participated. Results: Clinical specificity (95% CI) was 99.7% (99.6 – 99.8%) on 5852 blood donors and 99.0% (98.4 – 99.4%) on 1527 hospitalized patient samples. There were 15 discrepant samples (positive on ACCESS anti-HCV assay and negative on both ARCHITECT and Immunoblot) observed with hospitalized patient samples, and of note, additional HCV RNA PCR results showed five (5) samples had positive HCV RNA PCR results despite the absence of HCV antibody detection by ARCHITECT and Immunoblot, suggesting a better sensitivity of the ACCESS anti-HCV assay with these five samples compared to the ARCHITECT and Immunoblot anti-HCV assays. Clinical sensitivity (95% CI) on 510 well-characterized, known HCV antibody-positive samples was 100.0% (99.3 – 100.0%), including 353 samples with known HCV genotypes (1 to 6). The overall false initial reactive rate (95% CI) on 6630 patient samples was 0.02% (0.00 – 0.09%). Results obtained on 30 seroconversion panels demonstrated that the ACCESS anti-HCV assay had equivalent sensitivity performances, with an average bleed difference since the first reactive bleed below one (1), compared to the ARCHITECTTM anti-HCV assay. Conclusion: The newly developed ACCESS anti-HCV assay from BEC for use on the DxI 9000 ACCESS Immunoassay Analyzer demonstrated high clinical sensitivity and specificity, equivalent to currently marketed anti-HCV assays, as well as a low false initial reactive rate.

Keywords: DxI 9000 ACCESS Immunoassay Analyzer, HCV, HCV antibody, Hepatitis C virus, immunoassay

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316 Jointly Optimal Statistical Process Control and Maintenance Policy for Deteriorating Processes

Authors: Lucas Paganin, Viliam Makis

Abstract:

With the advent of globalization, the market competition has become a major issue for most companies. One of the main strategies to overcome this situation is the quality improvement of the product at a lower cost to meet customers’ expectations. In order to achieve the desired quality of products, it is important to control the process to meet the specifications, and to implement the optimal maintenance policy for the machines and the production lines. Thus, the overall objective is to reduce process variation and the production and maintenance costs. In this paper, an integrated model involving Statistical Process Control (SPC) and maintenance is developed to achieve this goal. Therefore, the main focus of this paper is to develop the jointly optimal maintenance and statistical process control policy minimizing the total long run expected average cost per unit time. In our model, the production process can go out of control due to either the deterioration of equipment or other assignable causes. The equipment is also subject to failures in any of the operating states due to deterioration and aging. Hence, the process mean is controlled by an Xbar control chart using equidistant sampling epochs. We assume that the machine inspection epochs are the times when the control chart signals an out-of-control condition, considering both true and false alarms. At these times, the production process will be stopped, and an investigation will be conducted not only to determine whether it is a true or false alarm, but also to identify the causes of the true alarm, whether it was caused by the change in the machine setting, by other assignable causes, or by both. If the system is out of control, the proper actions will be taken to bring it back to the in-control state. At these epochs, a maintenance action can be taken, which can be no action, or preventive replacement of the unit. When the equipment is in the failure state, a corrective maintenance action is performed, which can be minimal repair or replacement of the machine and the process is brought to the in-control state. SMDP framework is used to formulate and solve the joint control problem. Numerical example is developed to demonstrate the effectiveness of the control policy.

Keywords: maintenance, semi-Markov decision process, statistical process control, Xbar control chart

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315 Artificial Neural Networks and Hidden Markov Model in Landslides Prediction

Authors: C. S. Subhashini, H. L. Premaratne

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Landslides are the most recurrent and prominent disaster in Sri Lanka. Sri Lanka has been subjected to a number of extreme landslide disasters that resulted in a significant loss of life, material damage, and distress. It is required to explore a solution towards preparedness and mitigation to reduce recurrent losses associated with landslides. Artificial Neural Networks (ANNs) and Hidden Markov Model (HMMs) are now widely used in many computer applications spanning multiple domains. This research examines the effectiveness of using Artificial Neural Networks and Hidden Markov Model in landslides predictions and the possibility of applying the modern technology to predict landslides in a prominent geographical area in Sri Lanka. A thorough survey was conducted with the participation of resource persons from several national universities in Sri Lanka to identify and rank the influencing factors for landslides. A landslide database was created using existing topographic; soil, drainage, land cover maps and historical data. The landslide related factors which include external factors (Rainfall and Number of Previous Occurrences) and internal factors (Soil Material, Geology, Land Use, Curvature, Soil Texture, Slope, Aspect, Soil Drainage, and Soil Effective Thickness) are extracted from the landslide database. These factors are used to recognize the possibility to occur landslides by using an ANN and HMM. The model acquires the relationship between the factors of landslide and its hazard index during the training session. These models with landslide related factors as the inputs will be trained to predict three classes namely, ‘landslide occurs’, ‘landslide does not occur’ and ‘landslide likely to occur’. Once trained, the models will be able to predict the most likely class for the prevailing data. Finally compared two models with regards to prediction accuracy, False Acceptance Rates and False Rejection rates and This research indicates that the Artificial Neural Network could be used as a strong decision support system to predict landslides efficiently and effectively than Hidden Markov Model.

Keywords: landslides, influencing factors, neural network model, hidden markov model

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314 Adaptive CFAR Analysis for Non-Gaussian Distribution

Authors: Bouchemha Amel, Chachoui Takieddine, H. Maalem

Abstract:

Automatic detection of targets in a modern communication system RADAR is based primarily on the concept of adaptive CFAR detector. To have an effective detection, we must minimize the influence of disturbances due to the clutter. The detection algorithm adapts the CFAR detection threshold which is proportional to the average power of the clutter, maintaining a constant probability of false alarm. In this article, we analyze the performance of two variants of adaptive algorithms CA-CFAR and OS-CFAR and we compare the thresholds of these detectors in the marine environment (no-Gaussian) with a Weibull distribution.

Keywords: CFAR, threshold, clutter, distribution, Weibull, detection

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313 An Automatic Large Classroom Attendance Conceptual Model Using Face Counting

Authors: Sirajdin Olagoke Adeshina, Haidi Ibrahim, Akeem Salawu

Abstract:

large lecture theatres cannot be covered by a single camera but rather by a multicamera setup because of their size, shape, and seating arrangements. Although, classroom capture is achievable through a single camera. Therefore, a design and implementation of a multicamera setup for a large lecture hall were considered. Researchers have shown emphasis on the impact of class attendance taken on the academic performance of students. However, the traditional method of carrying out this exercise is below standard, especially for large lecture theatres, because of the student population, the time required, sophistication, exhaustiveness, and manipulative influence. An automated large classroom attendance system is, therefore, imperative. The common approach in this system is face detection and recognition, where known student faces are captured and stored for recognition purposes. This approach will require constant face database updates due to constant changes in the facial features. Alternatively, face counting can be performed by cropping the localized faces on the video or image into a folder and then count them. This research aims to develop a face localization-based approach to detect student faces in classroom images captured using a multicamera setup. A selected Haar-like feature cascade face detector trained with an asymmetric goal to minimize the False Rejection Rate (FRR) relative to the False Acceptance Rate (FAR) was applied on Raspberry Pi 4B. A relationship between the two factors (FRR and FAR) was established using a constant (λ) as a trade-off between the two factors for automatic adjustment during training. An evaluation of the proposed approach and the conventional AdaBoost on classroom datasets shows an improvement of 8% TPR (output result of low FRR) and 7% minimization of the FRR. The average learning speed of the proposed approach was improved with 1.19s execution time per image compared to 2.38s of the improved AdaBoost. Consequently, the proposed approach achieved 97% TPR with an overhead constraint time of 22.9s compared to 46.7s of the improved Adaboost when evaluated on images obtained from a large lecture hall (DK5) USM.

Keywords: automatic attendance, face detection, haar-like cascade, manual attendance

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312 Filipino And Malaysian Travel Bloggers: Adverbial Intensifiers Used in Blog Description

Authors: Arvin Ludovice

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The modern way of communicating and connecting people has been in its easiest forms nowadays, one of it is blog. Blogs, nowadays, are truly relevant in informing people of different as aspects, interests, and fields through these blogs. The evidentiality and testimony of collective people are easily been accessed. However, the description of blog in the making is persuading people, choice of language is one—adverbial intensifiers. Measuring the language on a scale of its intensity subdue the intensity per se. The present study determines, scrutinizes and analyses the adverbial intensifiers used in Filipino and Malaysian. The corpus consists of 30 top travel blogs written by Filipinos and 30 top travel blogs written by Malaysian for a total of 60 travel blogs. The application AntConc was utilized to tag the necessary intensifiers. A frequency distribution of the scores is used to identify the most common intensifiers used by travel bloggers from the Philippines and Malaysia. The scale or degree of intensifier is taken from Quirk Degree of Intensifiers as the basis for the functions of intensifiers. The result found that Malaysian travel blogs are more expressive with the use of the adverbial intensifiers vis-à-vis Filipino travel bloggers, consequently, ranking of the intensifiers, boosters are most used one in expressing and utilizing the language choice a more. The conclusion states that Malaysian travel bloggers are of using the functionality of the adverbial intensifiers. The distinction on the pedagogical implications are hereunto stated as well to deepen and give its significant and importance in language teaching.

Keywords: adverbial intensifiers, blogs, Filipino and Malaysian blogs, AntConc

Procedia PDF Downloads 157
311 DEEPMOTILE: Motility Analysis of Human Spermatozoa Using Deep Learning in Sri Lankan Population

Authors: Chamika Chiran Perera, Dananjaya Perera, Chirath Dasanayake, Banuka Athuraliya

Abstract:

Male infertility is a major problem in the world, and it is a neglected and sensitive health issue in Sri Lanka. It can be determined by analyzing human semen samples. Sperm motility is one of many factors that can evaluate male’s fertility potential. In Sri Lanka, this analysis is performed manually. Manual methods are time consuming and depend on the person, but they are reliable and it can depend on the expert. Machine learning and deep learning technologies are currently being investigated to automate the spermatozoa motility analysis, and these methods are unreliable. These automatic methods tend to produce false positive results and false detection. Current automatic methods support different techniques, and some of them are very expensive. Due to the geographical variance in spermatozoa characteristics, current automatic methods are not reliable for motility analysis in Sri Lanka. The suggested system, DeepMotile, is to explore a method to analyze motility of human spermatozoa automatically and present it to the andrology laboratories to overcome current issues. DeepMotile is a novel deep learning method for analyzing spermatozoa motility parameters in the Sri Lankan population. To implement the current approach, Sri Lanka patient data were collected anonymously as a dataset, and glass slides were used as a low-cost technique to analyze semen samples. Current problem was identified as microscopic object detection and tackling the problem. YOLOv5 was customized and used as the object detector, and it achieved 94 % mAP (mean average precision), 86% Precision, and 90% Recall with the gathered dataset. StrongSORT was used as the object tracker, and it was validated with andrology experts due to the unavailability of annotated ground truth data. Furthermore, this research has identified many potential ways for further investigation, and andrology experts can use this system to analyze motility parameters with realistic accuracy.

Keywords: computer vision, deep learning, convolutional neural networks, multi-target tracking, microscopic object detection and tracking, male infertility detection, motility analysis of human spermatozoa

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310 Energy Consumption and Economic Growth: Testimony of Selected Sub-Saharan Africa Countries

Authors: Alfred Quarcoo

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The main purpose of this paper is to examine the causal relationship between energy consumption and economic growth in Sub-Saharan Africa using panel data techniques. An annual data on energy consumption and Economic Growth (proxied by real gross domestic product per capita) spanning from 1990 to 2016 from the World bank index database was used. The results of the Augmented Dickey–Fuller unit root test shows that the series for all countries are not stationary at levels. However, the log of economic growth in Benin and Congo become stationary after taking the differences of the data, and log of energy consumption become stationary for all countries and Log of economic growth in Kenya and Zimbabwe were found to be stationary after taking the second differences of the panel series. The findings of the Johansen cointegration test demonstrate that the variables Log of Energy Consumption and Log of economic growth are not co-integrated for the cases of Kenya and Zimbabwe, so no long-run relationship between the variables were established in any country. The Granger causality test indicates that there is a unidirectional causality running from energy use to economic growth in Kenya and no causal linkage between Energy consumption and economic growth in Benin, Congo and Zimbabwe.

Keywords: Cointegration, Granger Causality, Sub-Sahara Africa, World Bank Development Indicators

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309 False Assumptions Made in Cybersecurity Curriculum: K-12

Authors: Nathaniel Evans, Jessica Boersma, Kenneth Kass

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With technology and STEM fields growing every day, there is a significant projected shortfall in qualified cybersecurity workers. As such, it is essential to develop a cybersecurity curriculum that builds skills and cultivates interest in cybersecurity early on. With new jobs being created every day and an already significant gap in the job market, it is vital that educators are pro-active in introducing a cybersecurity curriculum where students are able to learn new skills and engage in an age-appropriate cyber curriculum. Within this growing world of cybersecurity, students should engage in age-appropriate technology and cybersecurity curriculum, starting with elementary school (k-5), extending through high school, and ultimately into college. Such practice will provide students with the confidence, skills, and, ultimately, the opportunity to work in the burgeoning information security field. This paper examines educational methods, pedagogical practices, current cybersecurity curricula, and other educational resources and conducts analysis for false assumptions and developmental appropriateness. It also examines and identifies common mistakes with current cyber curriculum and lessons and discuss strategies for improvement. Throughout the lessons that were reviewed, many common mistakes continued to pop up. These mistakes included age appropriateness, technology resources that were available, and consistency of student’s skill levels. Many of these lessons were written for the wrong grade levels. The ones written for the elementary level all had activities that assumed that every student in the class could read at grade level and also had background knowledge of the cyber activity at hand, which is not always the case. Another major mistake was that these lessons assumed that all schools had any kind of technology resource available to them. Some schools are 1:1, and others are only allotted three computers in their classroom where the students have to share. While coming up with a cyber-curriculum, it has to be kept in mind that not all schools are the same, not every classroom is the same. There are many students who are not reading at their grade level or have not had exposure to the digital world. We need to start slow and ease children into the cyber world. Once they have a better understanding, it will be easier to move forward with these lessons and get the students engaged. With a better understanding of common mistakes that are being made, a more robust curriculum and lessons can be created that no only spark a student’s interest in this much-needed career field but encourage learning while keeping our students safe from cyber-attacks.

Keywords: assumptions, cybersecurity, k-12, teacher

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308 SOTM: A New Cooperation Based Trust Management System for VANET

Authors: Amel Ltifi, Ahmed Zouinkhi, Mohamed Salim Bouhlel

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Security and trust management in Vehicular Ad-hoc NETworks (VANET) is a crucial research domain which is the scope of many researches and domains. Although, the majority of the proposed trust management systems for VANET are based on specific road infrastructure, which may not be present in all the roads. Therefore, road security should be managed by vehicles themselves. In this paper, we propose a new Self Organized Trust Management system (SOTM). This system has the responsibility to cut with the spread of false warnings in the network through four principal components: cooperation, trust management, communication and security.

Keywords: ative vehicle, cooperation, trust management, VANET

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307 South African Breast Cancer Mutation Spectrum: Pitfalls to Copy Number Variation Detection Using Internationally Designed Multiplex Ligation-Dependent Probe Amplification and Next Generation Sequencing Panels

Authors: Jaco Oosthuizen, Nerina C. Van Der Merwe

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The National Health Laboratory Services in Bloemfontien has been the diagnostic testing facility for 1830 patients for familial breast cancer since 1997. From the cohort, 540 were comprehensively screened using High-Resolution Melting Analysis or Next Generation Sequencing for the presence of point mutations and/or indels. Approximately 90% of these patients stil remain undiagnosed as they are BRCA1/2 negative. Multiplex ligation-dependent probe amplification was initially added to screen for copy number variation detection, but with the introduction of next generation sequencing in 2017, was substituted and is currently used as a confirmation assay. The aim was to investigate the viability of utilizing internationally designed copy number variation detection assays based on mostly European/Caucasian genomic data for use within a South African context. The multiplex ligation-dependent probe amplification technique is based on the hybridization and subsequent ligation of multiple probes to a targeted exon. The ligated probes are amplified using conventional polymerase chain reaction, followed by fragment analysis by means of capillary electrophoresis. The experimental design of the assay was performed according to the guidelines of MRC-Holland. For BRCA1 (P002-D1) and BRCA2 (P045-B3), both multiplex assays were validated, and results were confirmed using a secondary probe set for each gene. The next generation sequencing technique is based on target amplification via multiplex polymerase chain reaction, where after the amplicons are sequenced parallel on a semiconductor chip. Amplified read counts are visualized as relative copy numbers to determine the median of the absolute values of all pairwise differences. Various experimental parameters such as DNA quality, quantity, and signal intensity or read depth were verified using positive and negative patients previously tested internationally. DNA quality and quantity proved to be the critical factors during the verification of both assays. The quantity influenced the relative copy number frequency directly whereas the quality of the DNA and its salt concentration influenced denaturation consistency in both assays. Multiplex ligation-dependent probe amplification produced false positives due to ligation failure when ligation was inhibited due to a variant present within the ligation site. Next generation sequencing produced false positives due to read dropout when primer sequences did not meet optimal multiplex binding kinetics due to population variants in the primer binding site. The analytical sensitivity and specificity for the South African population have been proven. Verification resulted in repeatable reactions with regards to the detection of relative copy number differences. Both multiplex ligation-dependent probe amplification and next generation sequencing multiplex panels need to be optimized to accommodate South African polymorphisms present within the genetically diverse ethnic groups to reduce the false copy number variation positive rate and increase performance efficiency.

Keywords: familial breast cancer, multiplex ligation-dependent probe amplification, next generation sequencing, South Africa

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306 Generating Links That Are Both Quasi-Alternating and Almost Alternating

Authors: Hamid Abchir, Mohammed Sabak2

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We construct an infinite family of links which are both almost alternating and quasi-alternating from a given either almost alternating diagram representing a quasi-alternating link, or connected and reduced alternating tangle diagram. To do that we use what we call a dealternator extension which consists in replacing the dealternator by a rational tangle extending it. We note that all non-alternating and quasi-alternating Montesinos links can be obtained in that way. We check that all the obtained quasi-alternating links satisfy Conjecture 3.1 of Qazaqzeh et al. (JKTR 22 (6), 2013), that is the crossing number of a quasi-alternating link is less than or equal to its determinant. We also prove that the converse of Theorem 3.3 of Qazaqzeh et al. (JKTR 24 (1), 2015) is false.

Keywords: quasi-alternating links, almost alternating links, tangles, determinants

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305 Narrating 1968: Felipe Cazals’ Canoa (1976) and Images of Massacre

Authors: Nancy Elizabeth Naranjo Garcia

Abstract:

Canoa (1976) by Felipe Cazals is a film that exposes the consequences of power that the Mexican State exercised over the 1968 student movement. The film, in this particular way, approaches the Tlatelolco Massacre from a point of view that takes into consideration the events that led up to it. Nonetheless, the reference to the political tension in Canoa remains ambiguous. Thus, the cinematographic representation refers to an event that leaves space for reflection, and as a consequence leaves evidence of an image that signals the notion of survival as Georges Didi-Huberman points out. In addition to denouncing the oppressive force by the Mexican State, the images in Canoa also emphasize what did not happen in Tlatelolco and its condensation with the student activists. To observe the images that Canoa offers in a new light, this work proposes further exploration with the following questions; How do the images in Canoa narrate? How are the images inserted in the film? In this fashion, a more profound comprehension of the objective and the essence of the images becomes feasible. As a result, it is possible to analyze the images of Canoa with the real killing at San Miguel Canoa in literature. The film visualizes a testimony of the event that once seemed unimaginable, an image that anticipates and structures the proceeding event. Therefore, this study takes a second look at how Canoa considers not only the killing at San Miguel Canoa and the Tlatlelolco Massacre, but goes further on contextualize an unimaginable image.

Keywords: cinematographic representation, student movement, Tlatelolco Massacre, unimaginable image

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304 ¹⁸F-FDG PET/CT Impact on Staging of Pancreatic Cancer

Authors: Jiri Kysucan, Dusan Klos, Katherine Vomackova, Pavel Koranda, Martin Lovecek, Cestmir Neoral, Roman Havlik

Abstract:

Aim: The prognosis of patients with pancreatic cancer is poor. The median of survival after establishing diagnosis is 3-11 months without surgical treatment, 13-20 months with surgical treatment depending on the disease stage, 5-year survival is less than 5%. Radical surgical resection remains the only hope of curing the disease. Early diagnosis with valid establishment of tumor resectability is, therefore, the most important aim for patients with pancreatic cancer. The aim of the work is to evaluate the contribution and define the role of 18F-FDG PET/CT in preoperative staging. Material and Methods: In 195 patients (103 males, 92 females, median age 66,7 years, 32-88 years) with a suspect pancreatic lesion, as part of the standard preoperative staging, in addition to standard examination methods (ultrasonography, contrast spiral CT, endoscopic ultrasonography, endoscopic ultrasonographic biopsy), a hybrid 18F-FDG PET/CT was performed. All PET/CT findings were subsequently compared with standard staging (CT, EUS, EUS FNA), with peroperative findings and definitive histology in the operated patients as reference standards. Interpretation defined the extent of the tumor according to TNM classification. Limitations of resectability were local advancement (T4) and presence of distant metastases (M1). Results: PET/CT was performed in a total of 195 patients with a suspect pancreatic lesion. In 153 patients, pancreatic carcinoma was confirmed and of these patients, 72 were not indicated for radical surgical procedure due to local inoperability or generalization of the disease. The sensitivity of PET/CT in detecting the primary lesion was 92.2%, specificity was 90.5%. A false negative finding in 12 patients, a false positive finding was seen in 4 cases, positive predictive value (PPV) 97.2%, negative predictive value (NPV) 76,0%. In evaluating regional lymph nodes, sensitivity was 51.9%, specificity 58.3%, PPV 58,3%, NPV 51.9%. In detecting distant metastases, PET/CT reached a sensitivity of 82.8%, specificity was 97.8%, PPV 96.9%, NPV 87.0%. PET/CT found distant metastases in 12 patients, which were not detected by standard methods. In 15 patients (15.6%) with potentially radically resectable findings, the procedure was contraindicated based on PET/CT findings and the treatment strategy was changed. Conclusion: PET/CT is a highly sensitive and specific method useful in preoperative staging of pancreatic cancer. It improves the selection of patients for radical surgical procedures, who can benefit from it and decreases the number of incorrectly indicated operations.

Keywords: cancer, PET/CT, staging, surgery

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303 Improved Skin Detection Using Colour Space and Texture

Authors: Medjram Sofiane, Babahenini Mohamed Chaouki, Mohamed Benali Yamina

Abstract:

Skin detection is an important task for computer vision systems. A good method for skin detection means a good and successful result of the system. The colour is a good descriptor that allows us to detect skin colour in the images, but because of lightings effects and objects that have a similar colour skin, skin detection becomes difficult. In this paper, we proposed a method using the YCbCr colour space for skin detection and lighting effects elimination, then we use the information of texture to eliminate the false regions detected by the YCbCr colour skin model.

Keywords: skin detection, YCbCr, GLCM, texture, human skin

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302 Architectural Heritage of Southern Portugal: Disruptive Practices and Sustainability Plans for its Preservation

Authors: Patrícia Alexandra Rodrigues Monteiro

Abstract:

The way modern societies relate with their architectural heritage has become increasingly difficult. This fact is clearer in historic centres of Portuguese peripheral cities or villages, constantly on the balance between its growth needs and the restrictions imposed by the policies for the built heritage preservation. Nowadays, gentrification phenomenon has levelled the differences between architecture, from north to south of the country, under false pretences of modernity and promises of better living conditions for local populations who inhabit historic centres. With this essay, we will address some of the main problems of southern Portugal’s historic centres, reflecting on the concept of sustainability which, also in this context, has acquired an unavoidable relevance.

Keywords: architecture, art, heritage, portugal

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301 A Method for Processing Unwanted Target Caused by Reflection in Secondary Surveillance Radar

Authors: Khanh D.Do, Loi V.Nguyen, Thanh N.Nguyen, Thang M.Nguyen, Vu T.Tran

Abstract:

Along with the development of Secondary surveillance radar (SSR) in air traffic surveillance systems, the Multipath phenomena has always been a noticeable problem. This following article discusses the geometrical aspect and power aspect of the Multipath interference caused by reflection in SSR and proposes a method to deal with these unwanted multipath targets (ghosts) by false-target position predicting and adaptive target suppressing. A field-experiment example is mentioned at the end of the article to demonstrate the efficiency of this measure.

Keywords: multipath, secondary surveillance radar, digital signal processing, reflection

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300 Capacity Optimization in Cooperative Cognitive Radio Networks

Authors: Mahdi Pirmoradian, Olayinka Adigun, Christos Politis

Abstract:

Cooperative spectrum sensing is a crucial challenge in cognitive radio networks. Cooperative sensing can increase the reliability of spectrum hole detection, optimize sensing time and reduce delay in cooperative networks. In this paper, an efficient central capacity optimization algorithm is proposed to minimize cooperative sensing time in a homogenous sensor network using OR decision rule subject to the detection and false alarm probabilities constraints. The evaluation results reveal significant improvement in the sensing time and normalized capacity of the cognitive sensors.

Keywords: cooperative networks, normalized capacity, sensing time

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299 On the Relationship between the Concepts of "[New] Social Democracy" and "Democratic Socialism"

Authors: Gintaras Mitrulevičius

Abstract:

This text, which is based on the conference report, seeks to briefly examine the relationship between the concepts of social democracy and democratic socialism, drawing attention to the essential aspects of its development and, in particular, discussing the contradictions in the relationship between these concepts in the modern period. In the preparation of this text, such research methods as historical, historical-comparative methods were used, as well as methods of analyzing, synthesizing, and generalizing texts. The history of the use of terms in social democracy and democratic socialism shows that these terms were used alternately and almost synonymously. At the end of the 20th century, traditional social democracy was transformed into the so-called "new social democracy." Many of the new social democrats do not consider themselves democratic socialists and avoid the historically characteristic identification of social democracy with democratic socialism. It has become quite popular to believe that social democracy is a separate ideology from democratic socialism. Or that it has become a variant of the ideology of liberalism. This is a testimony to the crisis of ideological self-awareness of social democracy. Since the beginning of the 21st century, social democracy has also experienced a growing crisis of electoral support. This, among other things, led to her slight shift to the left. In this context, some social democrats are once again talking about democratic socialism. The rise of the ideas of democratic socialism in the United States was catalyzed by Bernie Sanders. But the proponents of democratic socialism in the United States have different concepts of democratic socialism. In modern Europe, democratic socialism is also spoken of by leftists of non-social democratic origin, whose understanding is different from that of democratic socialism inherent in classical social democracy. Some political scientists also single out the concepts in question. Analysis of the problem shows that there are currently several concepts of democratic socialism on the spectrum of the political left, both social-democratic and non-social-democratic.

Keywords: democratic socializm, socializm, social democracy, new social democracy, political ideologies

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298 Automatic Segmentation of Lung Pleura Based On Curvature Analysis

Authors: Sasidhar B., Bhaskar Rao N., Ramesh Babu D. R., Ravi Shankar M.

Abstract:

Segmentation of lung pleura is a preprocessing step in Computer-Aided Diagnosis (CAD) which helps in reducing false positives in detection of lung cancer. The existing methods fail in extraction of lung regions with the nodules at the pleura of the lungs. In this paper, a new method is proposed which segments lung regions with nodules at the pleura of the lungs based on curvature analysis and morphological operators. The proposed algorithm is tested on 06 patient’s dataset which consists of 60 images of Lung Image Database Consortium (LIDC) and the results are found to be satisfactory with 98.3% average overlap measure (AΩ).

Keywords: curvature analysis, image segmentation, morphological operators, thresholding

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297 Livonian Werewolves, 1500-1700s: A Sociological Assessment of Their Historical Significance and Origins through the Case of Old Thiess

Authors: Liu Jiaxin

Abstract:

This paper seeks to do an in-depth investigation on the phenomenon of Early Modern era (1500-1700s) Livonian werewolves. Noting their uniqueness in comparison to contemporaneous werewolves hailing from other geographic areas, the paper suggests that the Livonian werewolf is a metaphor for Livonian society at that time, one which was characterized by social turmoil and strict class hierarchy. This metaphor was utilized by different classes to establish their own interests in society, and thus the paper concludes that the werewolf is a mutable artifact whose value is contingent on its social context. This is demonstrated by the particular case of Old Thiess—a poor, elderly Livonian peasant who gave an unorthodox and anomalous testimony when accused of being a werewolf. In his court statement, it is shown how Thiess was, in fact, alluding to social tensions by lambasting the rich German elite and establishing the righteousness of the peasantry, of which he was a member. A close reading method was utilized on the trial transcript of Old Thiess with heavy reference to Carlo Ginzburg and Bruce Lincoln’s collaborative work Old Thiess, a Livonian werewolf: a classic case in comparative perspective. Through a contextual reading of Livonia’s social atmosphere, the paper draws connections between the content of the trial to wider societal disturbances happening at the time. The thesis—that the werewolf is a flexible metaphor for the social milieu—is further buttressed by numerous contemporaneous sources that had similar messages as Thiess’ transcript, which are discussed as well.

Keywords: early-modern baltic, Livonia, Old Thiess, social history, werewolves

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296 Balancing Aesthetics, Sustainability, and Safety in Handmade Fabric Face Masks: A Testimony of Creativity and Adaptability

Authors: Anne Mastamet-Mason, Oluwatosin Onakoya, Karla Tissiman

Abstract:

The COVID-19 pandemic that ravaged the world in 2020 brought about the need for handmade fabric face masks in South Africa and beyond. These masks showcased individuality and environmental responsibility and effectively aided our battle against the virus. These practical masks held significant meaning, representing human creativity, resilience, and commitment to sustainability in adversity. This paper examines how aesthetics, sustainability, and safety were achieved in the Handmade Fabric Face Masks. It analyses how their integration signified human agility and resilience to the pandemic while promoting dignity and environmental welfare. The research conducted a qualitative analysis to choose handmade fabric face masks and assess their aesthetic, sustainable, and safety features. The study involved interviewing a group of mask designers and users who evaluated the masks' efficacy in providing protection, aesthetics, and environmental sustainability. Although the designers demonstrated a high level of knowledge in the design aspects, the results indicated a need for more information regarding the functional safety measures and some environmental factors in mask selection and production. The mask analysis also revealed that the masks available in the market combined aesthetics and environmental protection but had limited safety measures. Despite the lack of balance of aesthetics, sustainability, and safety among the designers and the users of hand-fabric masks, functional aspects of fabrics and sustainability literacy are essential

Keywords: sustainable fashion, fabric mask, aesthetics, safety measures

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295 Modifying Assessment Modes in the Science Classroom as a Solution to Examination Malpractice

Authors: Catherine Omole

Abstract:

Examination malpractice includes acts that temper with collecting accurate results during the conduct of an examination, thereby giving undue advantage to a student over his colleagues. Even though examination malpractice has been a lingering problem, examinations may not be easy to do away with completely as it is an important feedback tool in the learning process with several other functions e.g for the purpose of selection, placement, certification and promotion. Examination malpractice has created a lot of problems such as a relying on a weak work force based on false assessment results. The question is why is this problem still persisting, despite measures that have been taken to curb this ugly trend over the years? This opinion paper has identified modifications that could help relieve the student of the examination stress and thus increase the student’s effort towards effective learning and discourage examination malpractice in the long run.

Keywords: assessment, examination malpractice, learning, science classroom

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294 OFDM Radar for Detecting a Rayleigh Fluctuating Target in Gaussian Noise

Authors: Mahboobeh Eghtesad, Reza Mohseni

Abstract:

We develop methods for detecting a target for orthogonal frequency division multiplexing (OFDM) based radars. As a preliminary step we introduce the target and Gaussian noise models in discrete–time form. Then, resorting to match filter (MF) we derive a detector for two different scenarios: a non-fluctuating target and a Rayleigh fluctuating target. It will be shown that a MF is not suitable for Rayleigh fluctuating targets. In this paper we propose a reduced-complexity method based on fast Fourier transfrom (FFT) for such a situation. The proposed method has better detection performance.

Keywords: constant false alarm rate (CFAR), match filter (MF), fast Fourier transform (FFT), OFDM radars, Rayleigh fluctuating target

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293 Advanced Machine Learning Algorithm for Credit Card Fraud Detection

Authors: Manpreet Kaur

Abstract:

When legitimate credit card users are mistakenly labelled as fraudulent in numerous financial delated applications, there are numerous ethical problems. The innovative machine learning approach we have suggested in this research outperforms the current models and shows how to model a data set for credit card fraud detection while minimizing false positives. As a result, we advise using random forests as the best machine learning method for predicting and identifying credit card transaction fraud. The majority of victims of these fraudulent transactions were discovered to be credit card users over the age of 60, with a higher percentage of fraudulent transactions taking place between the specific hours.

Keywords: automated fraud detection, isolation forest method, local outlier factor, ML algorithm, credit card

Procedia PDF Downloads 78