Search results for: automated testing tool

Authors: Rong-Terng Juang

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Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: autonomous vehicle, data compression, remote monitoring, controller area networks (CAN), Lidar

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Authors: A. Degale Desta, Tamirat Kebamo

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Background: Recent advances in computer vision and pattern recognition have significantly improved activity recognition through video analysis, particularly with the application of Deep Convolutional Neural Networks (CNNs). One-stage detectors now enable efficient video-based recognition by simultaneously predicting object categories and locations. Such advancements are highly relevant in educational settings where CCTV surveillance could automatically monitor academic activities, enhancing security and classroom management. However, current datasets and recognition systems lack the specific focus on campus environments necessary for practical application in these settings.Objective: This study aims to address this gap by developing a dataset and testing an automated activity recognition system specifically tailored for educational campuses. The EthioCAD dataset was created to capture various classroom activities and teacher-student interactions, facilitating reliable recognition of academic activities using deep learning models. Method: EthioCAD, a novel video-based dataset, was created with a design science research approach to encompass teacher-student interactions across three domains and 18 distinct classroom activities. Using the Roboflow AI framework, the data was processed, with 4.224 KB of frames and 33.485 MB of images managed for frame extraction, labeling, and organization. The Ultralytics YOLOv8 model was then implemented within Google Colab to evaluate the dataset’s effectiveness, achieving high mean Average Precision (mAP) scores. Results: The YOLOv8 model demonstrated robust activity recognition within campus-like settings, achieving an mAP50 of 90.2% and an mAP50-95 of 78.6%. These results highlight the potential of EthioCAD, combined with YOLOv8, to provide reliable detection and classification of classroom activities, supporting automated surveillance needs on educational campuses. Discussion: The high performance of YOLOv8 on the EthioCAD dataset suggests that automated activity recognition for surveillance is feasible within educational environments. This system addresses current limitations in campus-specific data and tools, offering a tailored solution for academic monitoring that could enhance the effectiveness of CCTV systems in these settings. Conclusion: The EthioCAD dataset, alongside the YOLOv8 model, provides a promising framework for automated campus activity recognition. This approach lays the groundwork for future advancements in CCTV-based educational surveillance systems, enabling more refined and reliable monitoring of classroom activities.

Keywords: deep CNN, EthioCAD, deep learning, YOLOv8, activity recognition

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Authors: Doru Anastasiu Popescu, Raducanu Dragos Ionut

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In this paper the presentation of a tool which measures the similarity between two websites is made. The websites are compound only from webpages created with HTML. The tool uses three ways of calculating the similarity between two websites based on certain results already published. The first way compares all the webpages within a website, the second way compares a webpage with all the pages within the second website and the third way compares two webpages. Java programming language and technologies such as spring, Jsoup, log4j were used for the implementation of the tool.

Keywords: Java, Jsoup, HTM, spring

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Authors: Irbulat Utepbergenov, Lyazzat Issabekova, Shara Toybayeva

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This article discusses quality management using the bread baking process as an example. The baking process must be strictly controlled and repeatable. Automation and monitoring of quality management systems can help. After baking bread, quality control of the finished product should be carried out. This may include an evaluation of appearance, weight, texture, and flavor. It is important to continuously work to improve processes and products based on data and feedback from the quality management system. A method and model of automated quality management and an intelligent automated management system based on intelligent technologies are proposed, which allow to automate the processes of QMS implementation and support and improve the validity, efficiency, and effectiveness of management decisions by automating a number of functions of decision makers and staff. This project is supported by the grant of the Ministry of Education and Science of the Republic of Kazakhstan (Zhas Galym project No. AR 13268939 Research and development of digital technologies to ensure consistency of the carriers of normative documents of the quality management system).

Keywords: automated control system, quality management, efficiency evaluation, bakery oven, intelligent system

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Authors: Chia-Yen Lee, Hao-Jen Wang, Jhih-Hao Lai

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In recent years, infrared (IR) imaging has been considered as a potential tool to assess the efficacy of chemotherapy and early detection of breast cancer. Regions of tumor growth with high metabolic rate and angiogenesis phenomenon lead to the high temperatures. Observation of differences between the heat maps in long term is useful to help assess the growth of breast cancer cells and detect breast cancer earlier, wherein the multi-time infrared image alignment technology is a necessary step. Representative feature points detection and matching are essential steps toward the good performance of image registration and quantitative analysis. However, there is no clear boundary on the infrared images and the subject's posture are different for each shot. It cannot adhesive markers on a body surface for a very long period, and it is hard to find anatomic fiducial markers on a body surface. In other words, it’s difficult to detect and match features in an IR sequence images. In this study, automated feature detection and matching algorithms with two type of automatic feature points (i.e., vascular branch points and modified Harris corner) are developed respectively. The preliminary results show that the proposed method could identify the representative feature points on the IR breast images successfully of 98% accuracy and the matching results of 93% accuracy.

Keywords: Harris corner, infrared image, feature detection, registration, matching

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Authors: Nikhil Verma, Akshay Kant Mishra, Rishabh Rastogi, Bikarama Prasad Yadav

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Emerging fire incidents are the protuberant contributor out turning into life loss, property damage and importantly firefighters. It insinuates that a firefighting and rescue operation of the existing equipment or apparatus and their proficiency is limited, particularly in annihilating firefighting environments. The proposed methodology will help in developing a technology which can be useful in minimizing the risks and losses due to fire. In this paper, design and development of combat mini vehicle comprising of multi-purpose nozzle system is proposed which can target diverse fires simultaneously at distinct time and location. Basically, the system is semi-automated type protection system which can be manoeuvred by controller. Designing of robust vehicle based on semi-automated protection type system is consummated using SolidWorks platform. Concept of developing a robust vehicle will help to fight fires in multiple directions reducing the time required to douse multiple fires.

Keywords: fire douse vehicle, multiple fires, multi-purpose nozzle, semi-automated system

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Authors: Reyhaneh Soltanshah, Hamid R. Zarandi

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In order to be more efficient in industries that are related to computer systems, software testing is necessary despite spending time and money. In the embedded system software test, complete knowledge of the embedded system architecture is necessary to avoid significant costs and damages. Software tests increase the price of the final product. The aim of this article is to provide a method to reduce time and cost in tests based on program structure. First, a complete review of eleven white box test methods based on ISO/IEC/IEEE 29119 2015 and 2021 versions has been done. The proposed algorithm is designed using two versions of the 29119 standards, and some white-box testing methods that are expensive or have little coverage have been removed. On each of the functions, white box test methods were applied according to the 29119 standard and then the proposed algorithm was implemented on the functions. To speed up the implementation of the proposed method, the Unity framework has been used with some changes. Unity framework can be used in embedded software testing due to its open source and ability to implement white box test methods. The test items obtained from these two approaches were evaluated using a mathematical ratio, which in various software mining reduced between 50% and 80% of the test cost and reached the desired result with the minimum number of test items.

Keywords: embedded software, reduce costs, software testing, white-box testing

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Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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Authors: Keaghan Brown

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The prioritization of drug resistance mutations impacting protein folding or protein-drug and protein-DNA interactions within macromolecular systems is critical to the success of treatment regimens. With a continual increase in computational tools to assess these impacts, the need for scalability and reproducibility became an essential component of computational analysis and experimental research. Here it introduce a bioinformatics pipeline that combines several structural analysis tools in a simplified workflow, by optimizing the present computational hardware and software to automatically ease the flow of data transformations. Utilizing preestablished software tools, it was possible to develop a pipeline with a set of pre-defined functions that will automate mutation introduction into the HIV-1 Integrase protein structure, calculate the gain and loss of polar interactions and calculate the change in energy of protein fold. Additionally, an automated molecular dynamics analysis was implemented which reduces the constant need for user input and output management. The resulting pipeline, Automated Mutation Introduction and Analysis (AMIA) is an open source set of scripts designed to introduce and analyse the effects of mutations on the static protein structure as well as the results of the multi-conformational states from molecular dynamic simulations. The workflow allows the user to visualize all outputs in a user friendly manner thereby successfully enabling the prioritization of variant systems for experimental validation.

Keywords: automated workflow, variant prioritization, drug resistance, HIV Integrase

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Authors: Nafiseh Mirabdolhosseini, Jerry Zhou, Vincent Ho

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The dramatic global rise in acid reflux has also led to oesophageal adenocarcinoma (OAC) becoming the fastest-growing cancer in developed countries. While gastroscopy with biopsy is used to diagnose OAC patients, this labour-intensive and expensive process is not suitable for population screening. This study aims to design, develop, and implement a minimally invasive system to capture optical data of the distal oesophagus for rapid screening of potential abnormalities. To develop the system and understand user requirements, a user-centric approach was employed by utilising co-design strategies. Target users’ segments were identified, and 38 patients and 14 health providers were interviewed. Next, the technical requirements were developed based on consultations with the industry. A minimally invasive optical system was designed and developed considering patient comfort. This system consists of the sensing catheter, controller unit, and analysis program. Its procedure only takes 10 minutes to perform and does not require cleaning afterward since it has a single-use catheter. A prototype system was evaluated for safety and efficacy for both laboratory and clinical performance. This prototype performed successfully when submerged in simulated gastric fluid without showing evidence of erosion after 24 hours. The system effectively recorded a video of the mid-distal oesophagus of a healthy volunteer (34-year-old male). The recorded images were used to develop an automated program to identify abnormalities in the distal oesophagus. Further data from a larger clinical study will be used to train the automated program. This system allows for quick visual assessment of the lower oesophagus in primary care settings and can serve as a screening tool for oesophageal adenocarcinoma. In addition, this system is able to be coupled with 24hr ambulatory pH monitoring to better correlate oesophageal physiological changes with reflux symptoms. It also can provide additional information on lower oesophageal sphincter functions such as opening times and bolus retention.

Keywords: endoscopy, MedTech, oesophageal adenocarcinoma, optical system, screening tool

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Authors: Cristian Păuna

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After the widespread release of electronic trading, automated trading systems have become a significant part of the business intelligence system of any modern financial investment company. An important part of the trades is made completely automatically today by computers using mathematical algorithms. The trading decisions are taken almost instantly by logical models and the orders are sent by low-latency automatic systems. This paper will present a real-time price prediction methodology designed especially for algorithmic trading. Based on the price cyclicality function, the methodology revealed will generate price cyclicality bands to predict the optimal levels for the entries and exits. In order to automate the trading decisions, the cyclicality bands will generate automated trading signals. We have found that the model can be used with good results to predict the changes in market behavior. Using these predictions, the model can automatically adapt the trading signals in real-time to maximize the trading results. The paper will reveal the methodology to optimize and implement this model in automated trading systems. After tests, it is proved that this methodology can be applied with good efficiency in different timeframes. Real trading results will be also displayed and analyzed in order to qualify the methodology and to compare it with other models. As a conclusion, it was found that the price prediction model using the price cyclicality function is a reliable trading methodology for algorithmic trading in the financial market.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, price prediction

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Authors: Goutam Dubey, Varun Dutta

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In the present study, rotary-electro discharge machining of EN31 tool steel has been carried out using a pure copper electrode. Various response variables such as Material Removal Rate (MRR), Tool Wear Rate (TWR), and Machining Rate (MR) have been studied against the selected process variables. The selected process variables were peak current (I), voltage (V), duty cycle, and electrode rotation (N). EN31 Tool Steel is hardened, high carbon steel which increases its hardness and reduces its machinability. Reduced machinability means it not economical to use conventional methods to machine EN31 Tool Steel. So, non-conventional methods play an important role in machining of such materials.

Keywords: electric discharge machining, EDM, tool steel, tool wear rate, optimization techniques

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Authors: C. Salis, D. Zedda, M. F. Wilson

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The IDEA project was conceived for teachers who are interested in enhancing their capacity to effectively implement the use of specific technologies in their teaching practice. Participating teachers are coached and supported as they explore technologies applied to the educational context. They access tools such as the technological platform developed by our team. Among the platform functionalities, teachers access an instructional systems design (ISD) tool (learning designer) that was adapted to the needs of our project. The tool is accessible from computers or mobile devices and used in association with other technologies to create new, meaningful learning environments. The objective of an instructional systems design is to guarantee the quality and effectiveness of education and to enhance learning. This goal involves both teachers who want to become more efficient in transferring knowledge or skills and students as the final recipient of their teaching. The use of Blooms’s taxonomy enables teachers to classify the learning objectives into levels of complexity and specificity, thus making it possible to highlight the kind of knowledge teachers would like their students to reach. The fact that the instructional design features can be visualized through the IDEA platform is a guarantee for those who are looking for specific educational materials to be used in their lessons. Despite the benefits offered, a number of teachers are reluctant to use ISD because the preparatory work of having to thoroughly analyze the teaching/learning objectives, the planning of learning material, assessment activities, etc., is long and felt to be time-consuming. This drawback is minimized using a learning designer, as the tool facilitates to reuse of the didactic contents having a clear view of the processes of analysis, planning, and production of educational or testing materials uploaded on our platform. In this paper, we shall present the feedback of the teachers who used our tool in their didactic.

Keywords: educational benefits, educational quality, educational technology, ISD tool

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Authors: Bouwer Kleynhans

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The built environment is responsible for about 40% of the world’s energy consumption and generates one third of global carbon dioxide emissions. The Green Building Council of South Africa’s (GBCSA) current rating tools are all for new buildings. By far the largest portion of buildings exist stock and therefore the need to develop a certification tool for existing buildings. Direct energy measurement comprises 27% of the total available points in this tool. The aim of this paper is to describe the development process of a green star certification tool for existing buildings in South Africa with specific emphasis on the energy measurement criteria. Successful implementation of this tool within the property market will ensure a reduced carbon footprint of buildings.

Keywords: certification tool, development process, energy consumption, green buildings

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Authors: Hatim Laalej, Jon Stammers

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In machining, monitoring of tool wear is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Currently, the task of monitoring the wear on the cutting tool is carried out by the operator who performs manual inspections of the cutting tool, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from loss of productivity. The cutting tool consumable costs may also be higher than necessary when tools are changed before the end of their useful life. Furthermore, damage can be caused to the workpiece when tools are not changed soon enough leading to a significant increase in the costs of manufacturing. The present study is concerned with the development of break sensor printed on the flank surface of poly-crystalline diamond (PCD) cutting to perform on-line condition monitoring of the cutting tool used to machine Titanium Ti-6al-4v bar. The results clearly show that there is a strong correlation between the break sensor measurements and the amount of wear in the cutting tool. These findings are significant in that they help the user/operator of the machine tool to determine the condition of the cutting tool without the need of performing manual inspection, thereby reducing the manufacturing costs such as the machine down time.

Keywords: machining, manufacturing, tool wear, signal processing

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Authors: Yusuf Nugroho Doyo Yekti, Budi Praptono, Fransiskus Tatas Dwi Atmaji

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There is no ergonomic prototype testing method for manual material handling yet. This study has been carried out to demonstrate the comprehensive ergonomic assessment. The ergonomic assessment is important to improve safety of products and to ensure usefulness of the product. The prototype testing is conducted by involving few intended users and ordinary people. In this study, there are four operators who participated in several tests. Also, there are 30 ordinary people who joined the usability test. All the ordinary people never do material handling activity nor use material handling device. The methods used in the tests are Rapid Entire Body Assessment (REBA), Recommended Weight Limit (RWL), and Cardiovascular Load (%CVL) other than usability test and questionnaire. The proposed testing methods cover comprehensive ergonomic aspects, i.e. physical aspect, mental aspect, emotional aspects of human.

Keywords: ergonomic, manual material handling, prototype testing, assessment

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Authors: Finda A. Mahardika, Niken Aristyawati, Retno W. Damayanti

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Improvement technology needed to increase productivity of home industry that make herbal medicine is ginger washer tool. To solve this case, the writers develop existing technologies to create a tool that serves as a wash of ginger. This washer uses pedal tools to help the brush washer move. This tool is expected to produce ginger with good quality. In addition, this tool is also expected to be able to save time as well as water used when conducting the process of leaching. This tool is based on the size of the anthropometri people of Indonesia for the results of an ergonomic. The activities carried out by conducting a study of theory, experiment based on existing theories and make modifications based on the results obtained.

Keywords: ginger, ginger washer, technology, pedal

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Authors: Kamna Solanki, Yudhvir Singh, Sandeep Dalal

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Software testing is a time and cost intensive process. A scrutiny of the code and rigorous testing is required to identify and rectify the putative bugs. The process of bug identification and its consequent correction is continuous in nature and often some of the bugs are removed after the software has been launched in the market. This process of code validation of the altered software during the maintenance phase is termed as Regression testing. Regression testing ubiquitously considers resource constraints; therefore, the deduction of an appropriate set of test cases, from the ensemble of the entire gamut of test cases, is a critical issue for regression test planning. This paper presents a novel method for designing a suitable prioritization process to optimize fault detection rate and performance of regression test on predefined constraints. The proposed method for test case prioritization m-ACO alters the food source selection criteria of natural ants and is basically a modified version of Ant Colony Optimization (ACO). The proposed m-ACO approach has been coded in 'Perl' language and results are validated using three examples by computation of Average Percentage of Faults Detected (APFD) metric.

Keywords: regression testing, software testing, test case prioritization, test suite optimization

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Authors: Thomai Voulgari, Vasilis Vasilopoulos, Antonis Skamnakis

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The aim of this study is to investigate the effect of the European election campaigns (May 23-26, 2019) on Twitter achieving with artificial intelligence tools such as troll factories and automated inauthentic accounts. Our research focuses on the last European Parliamentary elections that took place between 23 and 26 May 2019 specifically in Italy, Greece, Germany and France. It is difficult to estimate how many Twitter users are actually bots (Echeverría, 2017). Detection for fake accounts is becoming even more complicated as AI bots are made more advanced. A political bot can be programmed to post comments on a Twitter account for a political candidate, target journalists with manipulated content or engage with politicians and artificially increase their impact and popularity. We analyze variables related to 1) the scope of activity of automated bots accounts and 2) degree of coherence and 3) degree of interaction taking into account different factors, such as the type of content of Twitter messages and their intentions, as well as the spreading to the general public. For this purpose, we collected large volumes of Twitter accounts of party leaders and MEP candidates between 10th of May and 26th of July based on content analysis of tweets based on hashtags while using an innovative network analysis tool known as MediaWatch.io (https://mediawatch.io/). According to our findings, one of the highest percentage (64.6%) of automated “bot” accounts during 2019 European election campaigns was in Greece. In general terms, political bots aim to proliferation of misinformation on social media. Targeting voters is a way that it can be achieved contribute to social media manipulation. We found that political parties and individual politicians create and promote purposeful content on Twitter using algorithmic tools. Based on this analysis, online political advertising play an important role to the process of spreading misinformation during elections campaigns. Overall, inauthentic accounts and social media algorithms are being used to manipulate political behavior and public opinion.

Keywords: artificial intelligence tools, human-bot interactions, political manipulation, social networking, troll factories

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Authors: Kuniaki Kudo, Raviraj Solanki, Kaushal Patel, Yash Virani

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This research mainly concerns optimizing UI test automation for large-scale web applications. The test target application is the HHAexchange homecare management WEB application that seamlessly connects providers, state Medicaid programs, managed care organizations (MCOs), and caregivers through one platform with large-scale functionalities. This study focuses on user interface automation testing for the WEB application. The quality assurance team must execute many manual users interface test cases in the development process to confirm no regression bugs. The team automated 346 test cases; the UI automation test execution time was over 17 hours. The business requirement was reducing the execution time to release high-quality products quickly, and the quality assurance automation team modernized the test automation framework to optimize the execution time. The base of the WEB UI automation test environment is Selenium, and the test code is written in Python. Adopting a compilation language to write test code leads to an inefficient flow when introducing scalability into a traditional test automation environment. In order to efficiently introduce scalability into Test Automation, a scripting language was adopted. The scalability implementation is mainly implemented with AWS's serverless technology, an elastic container service. The definition of scalability here is the ability to automatically set up computers to test automation and increase or decrease the number of computers running those tests. This means the scalable mechanism can help test cases run parallelly. Then test execution time is dramatically decreased. Also, introducing scalable test automation is for more than just reducing test execution time. There is a possibility that some challenging bugs are detected by introducing scalable test automation, such as race conditions, Etc. since test cases can be executed at same timing. If API and Unit tests are implemented, the test strategies can be adopted more efficiently for this scalability testing. However, in WEB applications, as a practical matter, API and Unit testing cannot cover 100% functional testing since they do not reach front-end codes. This study applied a scalable UI automation testing strategy to the large-scale homecare management system. It confirmed the optimization of the test case execution time and the detection of a challenging bug. This study first describes the detailed architecture of the scalable test automation environment, then describes the actual performance reduction time and an example of challenging issue detection.

Keywords: aws, elastic container service, scalability, serverless, ui automation test

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Authors: Satyanarayana Kosaraju, Venu Gopal Anne, Sateesh Nagari

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In this paper, the effect of cutting speed, feedrate and rake angle in tool geometry on cutting forces and temperature generated on the tool tip in turning were investigated. The data used for the investigation derived from experiments conducted on precision lathe according to the full factorial design to observe the effect of each factor level on the process performance. During the tests, depth of cut were kept constant and each test was conducted with a sharp coated tool insert. Ti-6Al-4V was used as the workpiece material. The effects of cutting parameters and tool geometry on cutting forces and tool tip temperature were analyzed. The main cutting force was observed to have a decreasing trend and temperature found to be increasing trend as the rake angle increased.

Keywords: cutting force, tool tip temperature, rake angle, machining

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Authors: W. Wen, G. Jackson, S. Maskill, D. G. McCartney, W. Sun

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CoNiCrAlY alloys have been widely used as bond coats for thermal barrier coating (TBC) systems because of low cost, improved control of composition, and the feasibility to tailor the coatings microstructures. Coatings are in general very thin structures, and therefore it is impossible to characterize the mechanical responses of the materials via conventional mechanical testing methods. Due to this reason, miniature specimen testing methods, such as the small punch test technique, have been developed. This paper presents some of the recent research in evaluating the mechanical properties of the CoNiCrAlY coatings at room and high temperatures, through the use of small punch testing and the developed miniature specimen tensile testing, applicable to a range of temperature, to investigate the elastic-plastic and creep behavior as well as ductile-brittle transition temperature (DBTT) behavior. An inverse procedure was developed to derive the mechanical properties from such tests for the coating materials. A two-layer specimen test method is also described. The key findings include: 1) the temperature-dependent coating properties can be accurately determined by the miniature tensile testing within a wide range of temperature; 2) consistent DBTTs can be identified by both the SPT and miniature tensile tests (~ 650 °C); and 3) the FE SPT modelling has shown good capability of simulating the early local cracking. In general, the temperature-dependent material behaviors of the CoNiCrAlY coating has been effectively characterized using miniature specimen testing and inverse method.

Keywords: NiCoCrAlY coatings, mechanical properties, DBTT, miniature specimen testing

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Authors: John Lorenzo Bautista, Yoon-Joong Kim

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This paper presents the development of a Filipino speech recognition tool using the HTK System. The system was trained from a subset of the Filipino Speech Corpus developed by the DSP Laboratory of the University of the Philippines-Diliman. The speech corpus was both used in training and testing the system by estimating the parameters for phonetic HMM-based (Hidden-Markov Model) acoustic models. Experiments on different mixture-weights were incorporated in the study. The phoneme-level word-based recognition of a 5-state HMM resulted in an average accuracy rate of 80.13 for a single-Gaussian mixture model, 81.13 after implementing a phoneme-alignment, and 87.19 for the increased Gaussian-mixture weight model. The highest accuracy rate of 88.70% was obtained from a 5-state model with 6 Gaussian mixtures.

Keywords: Filipino language, Hidden Markov Model, HTK system, speech recognition

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Authors: Cherry Oo, Hnin Min Oo

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Software bug localization is one of the most costly tasks in program repair technique. Therefore, there is a high claim for automated bug localization techniques that can monitor programmers to the locations of bugs, with slight human arbitration. Spectrum-based bug localization aims to help software developers to discover bugs rapidly by investigating abstractions of the program traces to make a ranking list of most possible buggy modules. Using the Apache Commons Math library project, we study the diagnostic accuracy using our spectrum-based bug localization metric. Our outcomes show that the greater performance of a specific similarity coefficient, used to inspect the program spectra, is mostly effective on localizing of single line bugs.

Keywords: software testing, bug localization, program spectra, bug

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Authors: Karlygash Adamova

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This article is focused on the KazTest as one of the most important high-stakes tests and the key tool in Kazakh language assessment. The research will also include the brief introduction to the language policy in Kazakhstan. Particularly, it is going to be changed significantly and turn from bilingualism (Kazakh, Russian) to multilingual policy (three languages - Kazakh, Russian, English). Therefore, the current status of the abovementioned languages will be described. Due to the various educational reforms in the country, the language evaluation system should also be improved and moderated. The research will present the most significant test of Kazakhstan – the KazTest, which is aimed to evaluate the Kazakh language proficiency. Assessment is an ongoing process that encompasses a wide area of knowledge upon the productive performance of the learners. Test is widely defined as a standardized or standard method of research, testing, diagnostics, verification, etc. The two most important characteristics of any test, as the main element of the assessment - validity and reliability - will also be described in this paper. Therefore, the preparation and design of the test, which is assumed to be an indicator of knowledge, and it is highly important to take into account all these properties.

Keywords: multilingualism, language assessment, testing, language policy

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Authors: Devanjan Bhattacharya, Jitka Komarkova

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The research describes the implementation of a novel and stand-alone system for dynamic hazard warning. The system uses all existing infrastructure already in place like mobile networks, a laptop/PC and the small installation software. The geospatial dataset are the maps of a region which are again frugal. Hence there is no need to invest and it reaches everyone with a mobile. A novel architecture of hazard assessment and warning introduced where major technologies in ICT interfaced to give a unique WebGIS based dynamic real time geohazard warning communication system. A never before architecture introduced for integrating WebGIS with telecommunication technology. Existing technologies interfaced in a novel architectural design to address a neglected domain in a way never done before–through dynamically updatable WebGIS based warning communication. The work publishes new architecture and novelty in addressing hazard warning techniques in sustainable way and user friendly manner. Coupling of hazard zonation and hazard warning procedures into a single system has been shown. Generalized architecture for deciphering a range of geo-hazards has been developed. Hence the developmental work presented here can be summarized as the development of internet-SMS based automated geo-hazard warning communication system; integrating a warning communication system with a hazard evaluation system; interfacing different open-source technologies towards design and development of a warning system; modularization of different technologies towards development of a warning communication system; automated data creation, transformation and dissemination over different interfaces. The architecture of the developed warning system has been functionally automated as well as generalized enough that can be used for any hazard and setup requirement has been kept to a minimum.

Keywords: geospatial, web-based GIS, geohazard, warning system

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Authors: Qing K. Zhu

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Very Large Scale Integration (VLSI) design becomes very complex due to the continuous integration of millions of gates in one chip based on Moore’s law. Designers have encountered numerous report files during design iterations using timing and noise analysis tools. This paper presented our work using data mining techniques combined with HTML tables to extract and represent critical timing/noise data. When we apply this data-mining tool in real applications, the running speed is important. The software employs table look-up techniques in the programming for the reasonable running speed based on performance testing results. We added several advanced features for the application in one industry chip design.

Keywords: VLSI design, data mining, big data, HTML forms, web, VLSI, EDA, timing, noise

Procedia PDF Downloads 254

Authors: Pradeep Joshi, Prashant Dhiman, Shiv Dayal Dhakad

Abstract:

Inconel 718 is a family if Nickel-Chromium based Superalloy; it has very high oxidation and corrosion resistance. Inconel 718 is widely being used in aerospace, engine, turbine etc. due to its high mechanical strength and creep resistance. Being widely used, its machining should be easy but in real its machining is very difficult, especially by using traditional machining methods. It becomes easy to machine only by using non Traditional machining such as EDM. During EDM machining there is wear of both tool and workpiece, the tool wear is undesired because it changes tool shape, geometry. To reduce the tool wear rate (TWR) cryogenic treatment is performed on tool before the machining operation. The machining performances of the process are to be evaluated in terms of MRR, TWR which are functions of Discharge current, Pulse on-time, Pulse Off-time.

Keywords: EDM, cyrogenic, TWR, MRR

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Authors: Wing Kam Fung, Kexin Yu

Abstract:

Child trafficking has been a serious problem in modern China. The Chinese government has established a national anti-trafficking DNA database to help reunite missing children with their families. The database collects DNA information from missing children's parents, trafficked and homeless children, then conducts paternity tests to find matched pairs. This paper considers the matching accuracy in such cases by looking into the exclusion probability in paternity testing. First, the situation of child trafficking in China is introduced. Next, derivations of the exclusion probability for both one-parent and two-parents cases are given, followed by extension to allow for 1 or 2 mutations. The accuracy of paternity testing of child trafficking cases is then assessed using the exclusion probabilities and available data. Finally, the number of loci that should be used to ensure a correct match is investigated.

Keywords: child trafficking, DNA database, exclusion probability, paternity testing

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Authors: Ali Ashtiani, Hamid Shirazi

Abstract:

This paper reviews the status of existing practice and research related to measuring pavement cracking and using crack density as a pavement surface evaluation protocol. Crack density for pavement evaluation is currently not widely used within the airport community and its use by the highway community is limited. However, surface cracking is a distress that is closely monitored by airport staff and significantly influences the development of maintenance, rehabilitation and reconstruction plans for airport pavements. Therefore crack density has the potential to become an important indicator of pavement condition if the type, severity and extent of surface cracking can be accurately measured. A pavement distress survey is an essential component of any pavement assessment. Manual crack surveying has been widely used for decades to measure pavement performance. However, the accuracy and precision of manual surveys can vary depending upon the surveyor and performing surveys may disrupt normal operations. Given the variability of manual surveys, this method has shown inconsistencies in distress classification and measurement. This can potentially impact the planning for pavement maintenance, rehabilitation and reconstruction and the associated funding strategies. A substantial effort has been devoted for the past 20 years to reduce the human intervention and the error associated with it by moving toward automated distress collection methods. The automated methods refer to the systems that identify, classify and quantify pavement distresses through processes that require no or very minimal human intervention. This principally involves the use of a digital recognition software to analyze and characterize pavement distresses. The lack of established protocols for measurement and classification of pavement cracks captured using digital images is a challenge to developing a reliable automated system for distress assessment. Variations in types and severity of distresses, different pavement surface textures and colors and presence of pavement joints and edges all complicate automated image processing and crack measurement and classification. This paper summarizes the commercially available systems and technologies for automated pavement distress evaluation. A comprehensive automated pavement distress survey involves collection, interpretation, and processing of the surface images to identify the type, quantity and severity of the surface distresses. The outputs can be used to quantitatively calculate the crack density. The systems for automated distress survey using digital images reviewed in this paper can assist the airport industry in the development of a pavement evaluation protocol based on crack density. Analysis of automated distress survey data can lead to a crack density index. This index can be used as a means of assessing pavement condition and to predict pavement performance. This can be used by airport owners to determine the type of pavement maintenance and rehabilitation in a more consistent way.

Keywords: airport pavement management, crack density, pavement evaluation, pavement management

Procedia PDF Downloads 185