Relevant bibliographies by topics / AUTOMATIC EVALUATING

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  2. Dissertations / Theses
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Academic literature on the topic 'AUTOMATIC EVALUATING'

Author: Grafiati
Published: 11 September 2023

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Journal articles on the topic "AUTOMATIC EVALUATING"

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Fabbri, Alexander R., Wojciech Kryściński, Bryan McCann, Caiming Xiong, Richard Socher, and Dragomir Radev. "SummEval: Re-evaluating Summarization Evaluation." Transactions of the Association for Computational Linguistics 9 (2021): 391–409. http://dx.doi.org/10.1162/tacl_a_00373.

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Abstract The scarcity of comprehensive up-to-date studies on evaluation metrics for text summarization and the lack of consensus regarding evaluation protocols continue to inhibit progress. We address the existing shortcomings of summarization evaluation methods along five dimensions: 1) we re-evaluate 14 automatic evaluation metrics in a comprehensive and consistent fashion using neural summarization model outputs along with expert and crowd-sourced human annotations; 2) we consistently benchmark 23 recent summarization models using the aforementioned automatic evaluation metrics; 3) we assemble the largest collection of summaries generated by models trained on the CNN/DailyMail news dataset and share it in a unified format; 4) we implement and share a toolkit that provides an extensible and unified API for evaluating summarization models across a broad range of automatic metrics; and 5) we assemble and share the largest and most diverse, in terms of model types, collection of human judgments of model-generated summaries on the CNN/Daily Mail dataset annotated by both expert judges and crowd-source workers. We hope that this work will help promote a more complete evaluation protocol for text summarization as well as advance research in developing evaluation metrics that better correlate with human judgments.
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Liu, Zhixiang, Huan Liu, Yuanji Chen, Wenbo Zhang, Wei Song, Liping Zhou, Quanmiao Wei, and Jingxiang Xu. "Evaluating Airfoil Mesh Quality with Transformer." Aerospace 10, no. 2 (January 23, 2023): 110. http://dx.doi.org/10.3390/aerospace10020110.

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Mesh quality is a major factor affecting the structure of computational fluid dynamics (CFD) calculations. Traditional mesh quality evaluation is based on the geometric factors of the mesh cells and does not effectively take into account the defects caused by the integrity of the mesh. Ensuring the generated meshes are of sufficient quality for numerical simulation requires considerable intervention by CFD professionals. In this paper, a Transformer-based network for automatic mesh quality evaluation (Gridformer), which translates the mesh quality evaluation into an image classification problem, is proposed. By comparing different mesh features, we selected the three features that highly influence mesh quality, providing reliability and interpretability for feature extraction work. To validate the effectiveness of Gridformer, we conduct experiments on the NACA-Market dataset. The experimental results demonstrate that Gridformer can automatically identify mesh integrity quality defects and has advantages in computational efficiency and prediction accuracy compared to widely used neural networks. Furthermore, a complete workflow for automatic generation of high-quality meshes based on Gridformer was established to facilitate automated mesh generation. This workflow can produce a high-quality mesh with a low-quality mesh input through automatic evaluation and optimization cycles. The preliminary implementation of automated mesh generation proves the versatility of Gridformer.
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Shinar, David, Meir Meir, and Israel Ben-Shoham. "How Automatic Is Manual Gear Shifting?" Human Factors: The Journal of the Human Factors and Ergonomics Society 40, no. 4 (December 1998): 647–54. http://dx.doi.org/10.1518/001872098779649346.

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Manual gear shifting is often used as an example of an automated (vs. controlled) process in driving. The present study provided an empirical evaluation of this assumption by evaluating sign detection and recall performance of novice and experienced drivers driving manual shift and automatic transmission cars in a downtown area requiring frequent gear shifting. The results showed that manual gear shifting significantly impaired sign detection performance of novice drivers using manual gears compared with novice drivers using an automatic transmission, whereas no such differences existed between the two transmission types for experienced drivers. The results clearly demonstrate that manual gear shifting is a complex psychomotor skill that is not easily (or quickly) automated and that until it becomes automated, it is an attention-demanding task that may impair other monitoring aspects of driving performance. Actual or potential applications of this research include a reevaluation of the learning process in driving and the need for phased instruction in driving from automatic gears to manual gears.
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Sai, Ananya B., Akash Kumar Mohankumar, and Mitesh M. Khapra. "A Survey of Evaluation Metrics Used for NLG Systems." ACM Computing Surveys 55, no. 2 (March 31, 2023): 1–39. http://dx.doi.org/10.1145/3485766.

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In the last few years, a large number of automatic evaluation metrics have been proposed for evaluating Natural Language Generation (NLG) systems. The rapid development and adoption of such automatic evaluation metrics in a relatively short time has created the need for a survey of these metrics. In this survey, we (i) highlight the challenges in automatically evaluating NLG systems, (ii) propose a coherent taxonomy for organising existing evaluation metrics, (iii) briefly describe different existing metrics, and finally (iv) discuss studies criticising the use of automatic evaluation metrics. We then conclude the article highlighting promising future directions of research.
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Sungdo Moon, Byoungro So, and M. W. Hall. "Evaluating automatic parallelization in SUIF." IEEE Transactions on Parallel and Distributed Systems 11, no. 1 (2000): 36–49. http://dx.doi.org/10.1109/71.824639.

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Gonzalez-Rodriguez, Joaquin. "Evaluating Automatic Speaker Recognition systems: An overview of the NIST Speaker Recognition Evaluations (1996-2014)." Loquens 1, no. 1 (June 30, 2014): e007. http://dx.doi.org/10.3989/loquens.2014.007.

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Oña, Edwin, Patricia Sánchez-Herrera, Alicia Cuesta-Gómez, Santiago Martinez, Alberto Jardón, and Carlos Balaguer. "Automatic Outcome in Manual Dexterity Assessment Using Colour Segmentation and Nearest Neighbour Classifier." Sensors 18, no. 9 (August 31, 2018): 2876. http://dx.doi.org/10.3390/s18092876.

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Objective assessment of motor function is an important component to evaluating the effectiveness of a rehabilitation process. Such assessments are carried out by clinicians using traditional tests and scales. The Box and Blocks Test (BBT) is one such scale, focusing on manual dexterity evaluation. The score is the maximum number of cubes that a person is able to displace during a time window. In a previous paper, an automated version of the Box and Blocks Test using a Microsoft Kinect sensor was presented, and referred to as the Automated Box and Blocks Test (ABBT). In this paper, the feasibility of ABBT as an automated tool for manual dexterity assessment is discussed. An algorithm, based on image segmentation in CIELab colour space and the Nearest Neighbour (NN) rule, was developed to improve the reliability of automatic cube counting. A pilot study was conducted to assess the hand motor function in people with Parkinson’s disease (PD). Three functional assessments were carried out. The success rate in automatic cube counting was studied by comparing the manual (BBT) and the automatic (ABBT) methods. The additional information provided by the ABBT was analysed to discuss its clinical significance. The results show a high correlation between manual (BBT) and automatic (ABBT) scoring. The lowest average success rate in cube counting for ABBT was 92%. Additionally, the ABBT acquires extra information from the cubes’ displacement, such as the average velocity and the time instants in which the cube was detected. The analysis of this information can be related to indicators of health status (coordination and dexterity). The results showed that the ABBT is a useful tool for automating the assessment of unilateral gross manual dexterity, and provides additional information about the user’s performance.
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White, Hannah, Joshua Penney, Andy Gibson, Anita Szakay, and Felicity Cox. "Evaluating automatic creaky voice detection methods." Journal of the Acoustical Society of America 152, no. 3 (September 2022): 1476–86. http://dx.doi.org/10.1121/10.0013888.

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There is growing interest in research on the non-modal voice quality, creaky voice; however, its identification often relies on time-consuming manual annotation, leading to a recent focus on automatic creak detection methods. Various automatic methods have been proposed, which rely on varying types and combinations of acoustic cues for creak detection. In this paper, we compare the performance of three automatic tools, the AntiMode method, the Creak Detector algorithm, and the Roughness algorithm, against manual annotation of creak using data from 80 Australian English speakers. We explore the possibility that tools used in combination may yield more accurate creak detection than individual tools used alone. Based on method comparisons, we present options for researchers, including an “out-of-the-box” approach, which supports combining automatic tools, and propose additional steps to further improve creak detection. We found restricting analysis to sonorant segments significantly improves automatic creak detection, and tools performed consistently better on female speech than male speech. Findings support previous work showing detection may be optimised by performing a creak probability threshold sweep on a subset of data prior to applying the Creak Detector algorithm on new datasets. Results provide promising solutions for advancing efficient large-scale research on creaky voice.
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Bernstein, Jared, and Elizabeth Rosenfeld. "Evaluating automatic speech-to-speech interpreting." Journal of the Acoustical Society of America 132, no. 3 (September 2012): 2079. http://dx.doi.org/10.1121/1.4755669.

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van Diepen, Merel, and Philip Hans Franses. "Evaluating chi-squared automatic interaction detection." Information Systems 31, no. 8 (December 2006): 814–31. http://dx.doi.org/10.1016/j.is.2005.03.002.

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Dissertations / Theses on the topic "AUTOMATIC EVALUATING"

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PENG, SISI. "Evaluating Automatic Model Selection." Thesis, Uppsala universitet, Statistiska institutionen, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-154449.

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In this paper, we briefly describe the automatic model selection which is provided by Autometrics in the PcGive program. The modeler only needs to specify the initial model and the significance level at which to reduce the model. Then, the algorithm does the rest. The properties of Autometrics are discussed. We also explain its background concepts and try to see whether the model selected by the Autometrics can perform well. For a given data set, we use Autometrics to find a “new” model, and then compare the “new” model with a previously selected one by another modeler. It is an interesting issue to see whether Autometrics can also find models which fit better to the given data. As an illustration, we choose three examples. It is true that Autometrics is labor saving and always gives us a parsimonious model. It is really an invaluable instrument for social science. But, we still need more examples to strongly support the idea that Autometrics can find a model which fits the data better, just a few examples in this paper is far from enough.
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Doe, Hope L. "Evaluating the Effects of Automatic Speech Recognition Word Accuracy." Thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/36956.

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Automatic Speech Recognition (ASR) research has been primarily focused towards large-scale systems and industry, while other areas that require attention are often over-looked by researchers. For this reason, this research looked at automatic speech recognition at the consumer level. Many individual consumers will purchase and use automatic software recognition for a different purpose than that of the military or commercial industries, such as telecommunications. Consumers who purchase the software for personal use will mainly use ASR for dictation of correspondences and documents. Two ASR dictation software packages were used to conduct the study. The research examined the relationships between (1) speech recognition software training and word accuracy, (2) error-correction time by the user and word accuracy, and (3) correspondence type and word accuracy. The correspondences evaluated were those that resemble Personal, Business, and Technical Correspondences. Word accuracy was assessed after initial system training, five minutes of error-correction time, and ten minutes of error-correction time.

Results indicated that word recognition accuracy achieved does affect user satisfaction. It was also found that with increased error-correction time, word accuracy results improved. Additionally, the results found that Personal Correspondence achieved the highest mean word accuracy rate for both systems and that Dragon Systems achieved the highest mean word accuracy recognition for the Correspondences explored in this research. Results were discussed in terms of subjective and objective measures, advantages and disadvantages of speech input, and design recommendations were provided.
Master of Science

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Nguyen, Christofer. "Priority automation engineering : Evaluating a tool for automatic code generation and configuration of PLC-Applications." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-85797.

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This research explores the Automation Interface created by Beckhoff through introducinga compiler solution. Today machine builders have to be able to build machinesor plants in different sizes and provide many variations of the machine orplant types. Automatic code generation can be used in the aspect to reuse code thathas been tested and is configurable to match the desired functionality. Additionally,the use of a pre-existing API could potentially result in less engineering resourceswasted in developing automatic code generation. This thesis aims to evaluate theAutomation Interface (AI) tool created by Beckhoff. This is accomplished throughmeans of incorporating the API functions into a compiler solution. The solution isdesigned to export the information required through an XML-file to generate PLCapplications.The generated PLC-code will be in Structured Text. In order to createa functional PLC-application, the construction of software requirements and testcases are established. The solution is then validated by means of generating a dataloggerto illustrate the usage. The exploratory research revealed both the benefitsand cons of using AI to a compiler solution. The evaluation indicated that the AutomationInterface can reduce engineering effort to produce a compiler solution, butthe learning curve of understanding the underlying components that work with theAPI required a great deal of effort.
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Vatn, Niklas, and Julia Byström. "Evaluating automatic colour equalization to preprocess dermoscopic images for classification using a CNN." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302502.

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Skin cancer is one of the most prevalent types of cancer and diagnosing of skin lesions are mostly done by visual inspection by a doctor. Lately, computer- aided diagnosis (CAD) has gained popularity and previous studies have with great results utilized a convolutional neural network (CNN) to classify dermoscopic images of different benign and malignant skin lesions. While other studies using CAD tools have investigated the effects of using preprocessing methods on image data before using them in diagnosis classification. Therefore our thesis aims to investigate if preprocessing dermoscopic images of skin lesions before training a CNN in classifying them will improve the accuracy of classification The investigation was conducted by training a CNN on the multi-class problem of classifying dermoscopic images of four different skin lesions. Melanoma and basal cell carcinoma which are malignant and benign keratosis-like lesions and melanocytic nevi which are benign. The dermoscopic images were preprocessed using automatic colour equalization (ACE). The ACE preprocessing was applied to the entire dataset five times each time with different levels of its slope parameter, the contrast tuner of the algorithm. These five datasets together with a dataset not preprocessed with ACE was used to train a CNN model. After 50 epochs of training, the CNN was evaluated on the accuracy of prediction as well as precision, recall and specificity of the four classes. The result indicates that preprocessing images using ACE did not improve the classification accuracy of skin lesions. Additionally, the result suggests that no class is affected more with ACE preprocessing than the others. To further investigate if preprocessing will improve the accuracy of classification the effects of ACE on a different CNN should be conducted. Additionally, if further investigation on the effects of image preprocessing for skin lesion classification is to be conducted, hair removal could be interesting to look into.
Hudcancer är en av de vanligaste typerna av cancer och diagnostisering av hudåkommor utförs primärt genom visuell inspektion av en läkare. På senare tid har computer-aided diagnosis (CAD) blivit vanligare och tidigare studier har med bra resultat använt convolutional neural network (CNN) för att klassificera dermatoskopiska bilder av olika god- och elakartade hudåkommor. Andra studier med CAD-verktyg har undersökt effekterna av att använda förbehandling på bilddata innan den används vid diagnos. Däremot har lite forskning fokuserat på effekten av förbehandling på experiment som använder CNN. Därför är syftet med vår studie att undersöka om förbehandling av dermatoskopiska bilder av hudåkommor innan ett CNN tränas i klassificering kan förbättra klassificeringens noggrannhet. Undersökningen genomfördes genom att träna ett CNN på att klassificera dermatoskopiska bilder av fyra olika hudåkommor. Malignt melanom och basalcellscancer som är elakartade och seborroiska keratoser och melanocytiska nevi som är godartade. De dermatoskopiska bilderna förbehandlades med automatisk algoritmen automatic colour equalization (ACE).ACE-förbehandlingen applicerades på hela datasetet fem gånger, varje gång med olika nivåer på algoritmens kontrastförstärkare. Dessa fem datamängder och en datamängd som inte förbehandlats med ACE användes för att träna olika CNN-modeller. Efter 50 epoker utvärderades modellen med avseende på noggrannhet samt precision, sensitivitet och specificitet hos de fyra klasserna. Resultatet indikerar att förbehandling av bilder med ACE inte förbättrar klassificeringsnoggrannheten för hudåkommor. Dessutom antyder resultatet att ingen klass påverkas mer med ACE-förbehandling än de andra. För att ytterligare undersöka om förbehandling kan förbättra klassificeringens noggrannhet bör effekterna av ACE på andra CNN-modeller genomföras. Om ytterligare undersökningar av effekterna av bildförbehandling för klassificering av hudskador ska genomföras, kan hårborttagning vara intressant att undersöka.
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Gilbert, Michael Stephen. "A Small-Perturbation Automatic-Differentiation (SPAD) Method for Evaluating Uncertainty in Computational Electromagnetics." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1354742230.

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Skoglund, Martin. "Evaluating SLAM algorithms for Autonomous Helicopters." Thesis, Linköping University, Department of Electrical Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-12282.

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Navigation with unmanned aerial vehicles (UAVs) requires good knowledge of the current position and other states. A UAV navigation system often uses GPS and inertial sensors in a state estimation solution. If the GPS signal is lost or corrupted state estimation must still be possible and this is where simultaneous localization and mapping (SLAM) provides a solution. SLAM considers the problem of incrementally building a consistent map of a previously unknown environment and simultaneously localize itself within this map, thus a solution does not require position from the GPS receiver.

This thesis presents a visual feature based SLAM solution using a low resolution video camera, a low-cost inertial measurement unit (IMU) and a barometric pressure sensor. State estimation in made with a extended information filter (EIF) where sparseness in the information matrix is enforced with an approximation.

An implementation is evaluated on real flight data and compared to a EKF-SLAM solution. Results show that both solutions provide similar estimates but the EIF is over-confident. The sparse structure is exploited, possibly not fully, making the solution nearly linear in time and storage requirements are linear in the number of features which enables evaluation for a longer period of time.

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Breakiron, Daniel Aubrey. "Evaluating the Integration of Online, Interactive Tutorials into a Data Structures and Algorithms Course." Thesis, Virginia Tech, 2013. http://hdl.handle.net/10919/23107.

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OpenDSA is a collection of open source tutorials for teaching data structures and algorithms. It was created with the goals of visualizing complex, abstract topics; increasing the amount of practice material available to students; and providing immediate feedback and incremental assessment. In this thesis, I first describe aspects of the OpenDSA architecture relevant to collecting user interaction data. I then present an analysis of the interaction log data gathered from three classes during Spring 2013. The analysis focuses on determining the time distribution of student activity, determining the time required for assignment completion, and exploring \credit-seeking" behaviors and behavior related to non-required exercises. We identified clusters of students based on when they completed exercises, verified the reliability of estimated time requirements for exercises, provided evidence that a majority of students do not read the text, discovered a measurement that could be used to identify exercises that require additional development, and found evidence that students complete exercises after obtaining credit. Furthermore, we determined that slideshow usage was fairly high (even when credit was not ordered), and skipping to the end of slideshows was more common when credit was offered but also occurred when it was not.
Master of Science
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Ivarsson, Anton, and Jacob Stachowicz. "Evaluating machine learning methods for detecting sleep arousal." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259996.

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Sleep arousal is a phenomenon that affects the sleep of a large amount of people. The process of predicting and classifying arousal events is done manually with the aid of certified technologists, although some research has been done on automation using Artificial Neural Networks (ANN). This study explored how a Support Vector Machine performed(SVM) compared to an ANN on this task. Polysomnography (PSG) is a sort of sleep study which produces the data that is used in classifying sleep disorders. The PSG-data used in this thesis consists of 13 wave forms sampled at or resampled at 200Hz. There were samples from 994 patients totalling approximately 6.98 1010 data points, processing this amount of data is time consuming and presents a challenge. 2000 points of each signal was used in the construction of the data set used for the models. Extracted features included: Median, Max, Min, Skewness, Kurtosis, Power of EEG-band frequencies and more. Recursive feature elimination was used in order to select the best amount of extracted features. The extracted data set was used to train two ”out of the box” classifiers and due to memory issues the testing had to be split in four batches. When taking the mean of the four tests, the SVM scored ROC AUC of 0,575 and the ANN 0.569 respectively. As the difference in the two results was very modest it was not possible to conclude that either model was better suited for the task at hand. It could however be concluded that SVM can perform as well as ANN on PSG-data. More work has to bee done on feature extraction, feature selection and the tuning of the models for PSG-data to conclude anything else. Future thesis work could include research questions as ”Which features performs best for a SVM in the prediction of Sleep arousals on PSG-data” or ”What feature selection technique performs best for a SVM in the prediction of Sleep arousals on PSG-data”, etc.
Sömnstörningar är en samling hälsotillstånd som påverkar sömnkvaliteten hos en stor mängd människor. Ett exempel på en sömnstörning är sömnapne. Detektion av dessa händelser är idag en manuell uppgift utförd av certifierade teknologer, det har dock på senare tid gjorts studier som visar att Artificella Neurala Nätverk (ANN) klarar att detektera händelserna med stor träffsäkerhet. Denna studie undersöker hur väl en Support Vector Machine (SVM) kan detektera dessa händelser jämfört med en ANN. Datat som används för att klassificera sömnstörningar kommer från en typ av sömnstudie kallad polysomnografi (PSG). Den PSG-data som används i denna avhandling består av 13 vågformer där 12 spelats in i 200Hz och en rekonstruerats till 200Hz. Datan som används i denna avhandling innehåller inspelningar från 994 patienter, vilket ger totalt ungefär·6.98 1010 datapunkter. Att behandla en så stor mängd data var en utmaning. 2000 punkter från vare vågform användes vid konstruktionen av det dataset som användes för modellerna. De attribut som extraherades innehöll bland annat: Median, Max, Min, Skewness, Kurtosis, amplitud av EEG-bandfrekvenser m.m. Metoden Recursive Feature Elimination användes för att välja den optimala antalet av de bästa attributen. Det extraherade datasetet användes sedan för att träna två standard-konfigurerade modeller, en SVM och en ANN. På grund av en begräning av arbetsminne så var vi tvungna att dela upp träningen och testandet i fyra segment. Medelvärdet av de fyra testen blev en ROC AUC på 0,575 för en SVM, respektive 0,569 för ANN. Eftersom skillnaden i de två resultaten var väldigt marginella kunde vi inte dra slutsatsen att endera modellen var bättre lämpad för uppgiften till hands. Vi kan dock dra slutsatsen att en SVM kan prestera lika väl som ANN på PSG-data utan konfiguration. Mer arbete krävs inom extraheringen av attributen, attribut-eliminationen och justering av modellerna. Framtida avhandlingar skulle kunna göras med frågeställningarna: “Vilka attributer fungerar bäst för en SVM inom detektionen av sömnstörningar på PSG-data” eller ”Vilken teknik för attribut-elimination fungerar bäst för en SVM inom detektionen av sömnstörningar på PSG-data”, med mera.
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LUNDIN, FORSSÉN WILLIAM. "Automatic Grading System in Microsoft .NETFramework : Evaluating the performance of different programming languages on the Microsoft.NET platform." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-155892.

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A common challenge for software consulting companies is recruiting the right people. In the software industry, the recruitment process usually involves several steps before a contract is signed; a single job interviewis rarely enough. Thus, the interview tends to involve some test to make sure that the job applicant is qualified. The testing procedure is usually part of the interview or conducted at the same occasion. Interviewing applicants who are not qualified for the position is a waste of time. This waste can be minimized by only interviewing qualified applicants. In the software industry, qualifications are commonly asserted by letting an applicant solve programming problems. This process can be automated using an Automatic Grader. Such systems already exist on some universities today and are used extensively invarious programming courses and also in programming contests.This thesis explains how such a system can be built using only Microsoft.NET Framework while still supporting multiple languages. The thesis also evaluates this system with regard to execution speed and memory consumption in an attempt to find a scaling factor between the different programming languages since the same implementation of a specific algorithm in different languages should be graded equally. The supported languages are C#, Java and Python. Java support is enabled through the use of a Java byte code to Common Intermediate Language(.NET bytecode) compiler called IKVM. Python is supported through the use of Iron Python.The results showed that C# and Java performed almost equally interms of execution speed and memory usage, with Java being slightly behind. As a compensation for Javas slower execution speed a scaling factor was calculated. The average of this scaling factor was 1.29.Python had greater performance and memory issues than the other twoand no scaling factor could be obtained for this language using the data present in this thesis. Future work involves implementing additional language support and improving the system with usability in mind.
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Lu, Ming. "System Dynamics Model for Testing and Evaluating Automatic Headway Control Models for Trucks Operating on Rural Highways." Diss., This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-01292008-113749/.

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Books on the topic "AUTOMATIC EVALUATING"

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Evaluating control systems reliability: Techniques and applications. Research Triangle Park, N.C: Instrument Society of America, 1992.

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John, Karat, ed. Designing and evaluating usable technology in industrial research: Three case studies. [San Rafael, Calif.]: Morgan & Claypool, 2010.

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S, Aden Teresa, Bevelheimer Susan J, and Construction Engineering Research Laboratories (U.S.), eds. Evaluation of automatic aqueous parts washers. Champaign, IL: US Army Corps of Engineers, Construction Engineering Research Laboratories, 1997.

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K, Gomard Carsten, and Sestoft Peter, eds. Partial evaluation and automatic program generation. New York: Prentice Hall, 1993.

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Ivory, Melody Y. Automated Web Site Evaluation. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-0375-8.

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Skimmons, Brian E. Automated performance evaluation technique. Monterey, Calif: Naval Postgraduate School, 1992.

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R, Kaplunov D., ed. Razvitie mekhanizat͡s︡ii prokhodcheskikh i ochistnykh rabot na podzemnykh rudnikakh. Moskva: IPKON AN SSSR, 1989.

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Yeoh, Swee Mei. Automated maintainability quality evaluation system. Birmingham: University of Birmingham, 1986.

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Kim, David S. Technology evaluation for implementation of VMT based revenue collection systems: Final report. Salem, OR: Oregon Dept. of Transportation, Research Group, 2002.

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Tinker, Amanda Jayne. Automatic abstracting: A review and an empirical evaluation. Loughborough: Loughborough University, 1997.

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Book chapters on the topic "AUTOMATIC EVALUATING"

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Torres-Moreno, Juan-Manuel. "Evaluating Document Summaries." In Automatic Text Summarization, 243–73. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781119004752.ch8.

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Bouix, Sylvain, Lida Ungar, Chandlee C. Dickey, Robert W. McCarley, and Martha E. Shenton. "Evaluating Automatic Brain Tissue Classifiers." In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004, 1038–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30136-3_127.

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Korkontzelos, Ioannis, Ioannis P. Klapaftis, and Suresh Manandhar. "Reviewing and Evaluating Automatic Term Recognition Techniques." In Advances in Natural Language Processing, 248–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-85287-2_24.

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Schlachter, Jason, David Van Brackle, Luis Asencios Reynoso, James Starz, and Nathanael Chambers. "Evaluating Automatic Learning of Structure for Event Extraction." In Advances in Intelligent Systems and Computing, 145–58. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41636-6_12.

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Liddy, Elizabeth D., Jiangping Chen, Christina M. Finneran, Anne R. Diekema, Sarah C. Harwell, and Ozgur Yilmazel. "Generating and Evaluating Automatic Metadata for Educational Resources." In Research and Advanced Technology for Digital Libraries, 513–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11551362_60.

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O'Toole, Alice, and P. Jonathon Phillips. "Evaluating Automatic Face Recognition Systems with Human Benchmarks." In Forensic Facial Identification, 263–83. Chichester, UK: John Wiley & Sons, Ltd, 2015. http://dx.doi.org/10.1002/9781118469538.ch11.

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Athanasakos, Konstantinos, Vassilios Stathopoulos, and Joemon M. Jose. "A Framework for Evaluating Automatic Image Annotation Algorithms." In Lecture Notes in Computer Science, 217–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12275-0_21.

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Caparrós-Laiz, Camilo, José Antonio García-Díaz, and Rafael Valencia-García. "Evaluating Extractive Automatic Text Summarization Techniques in Spanish." In Communications in Computer and Information Science, 79–92. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88262-4_6.

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Campr, Michal, and Karel Ježek. "Comparing Semantic Models for Evaluating Automatic Document Summarization." In Text, Speech, and Dialogue, 252–60. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24033-6_29.

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Nasr Azadani, Mozhgan, and Nasser Ghadiri. "Evaluating Different Similarity Measures for Automatic Biomedical Text Summarization." In Advances in Intelligent Systems and Computing, 305–14. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76348-4_30.

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Conference papers on the topic "AUTOMATIC EVALUATING"

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Martins, Antonio S., and Ronaldo A. L. Goncalves. "Implementing and Evaluating Automatic Checkpointing." In 2007 IEEE International Parallel and Distributed Processing Symposium. IEEE, 2007. http://dx.doi.org/10.1109/ipdps.2007.370557.

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Tong, Sibo, Nanxin Chen, Yanmin Qian, and Kai Yu. "Evaluating vad for automatic speech recognition." In 2014 12th International Conference on Signal Processing (ICSP 2014). IEEE, 2014. http://dx.doi.org/10.1109/icosp.2014.7015406.

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Henderson, Tim A. D., Andy Podgurski, and Yigit Kucuk. "Evaluating Automatic Fault Localization Using Markov Processes." In 2019 IEEE 19th International Working Conference on Source Code Analysis and Manipulation (SCAM). IEEE, 2019. http://dx.doi.org/10.1109/scam.2019.00021.

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Mayer-Patel, Ketan, and Wesley Miaw. "Evaluating the effectiveness of automatic PVR management." In Electronic Imaging 2004, edited by Minerva M. Yeung, Rainer W. Lienhart, and Chung-Sheng Li. SPIE, 2003. http://dx.doi.org/10.1117/12.527252.

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Kilickaya, Mert, Aykut Erdem, Nazli Ikizler-Cinbis, and Erkut Erdem. "Re-evaluating Automatic Metrics for Image Captioning." In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers. Stroudsburg, PA, USA: Association for Computational Linguistics, 2017. http://dx.doi.org/10.18653/v1/e17-1019.

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Federico, Marcello, Yogesh Virkar, Robert Enyedi, and Roberto Barra-Chicote. "Evaluating and Optimizing Prosodic Alignment for Automatic Dubbing." In Interspeech 2020. ISCA: ISCA, 2020. http://dx.doi.org/10.21437/interspeech.2020-2983.

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Granada, Roger L., Renata Vieira, and Vera Lucia Strube de Lima. "Evaluating co-occurrence order for automatic thesaurus construction." In 2012 IEEE 13th International Conference on Information Reuse & Integration (IRI). IEEE, 2012. http://dx.doi.org/10.1109/iri.2012.6303046.

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Šajatović, Antonio, Maja Buljan, Jan Šnajder, and Bojana Dalbelo Bašić. "Evaluating Automatic Term Extraction Methods on Individual Documents." In Proceedings of the Joint Workshop on Multiword Expressions and WordNet (MWE-WN 2019). Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/w19-5118.

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Alham, Nasullah Khalid, Maozhen Li, Suhel Hammoud, and Hao Qi. "Evaluating Machine Learning Techniques for Automatic Image Annotations." In 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery. IEEE, 2009. http://dx.doi.org/10.1109/fskd.2009.531.

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Whetten, Ryan, and Casey Kennington. "Evaluating and Improving Automatic Speech Recognition using Severity." In The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks. Stroudsburg, PA, USA: Association for Computational Linguistics, 2023. http://dx.doi.org/10.18653/v1/2023.bionlp-1.6.

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Reports on the topic "AUTOMATIC EVALUATING"

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Mathew, Jijo K., Christopher M. Day, Howell Li, and Darcy M. Bullock. Curating Automatic Vehicle Location Data to Compare the Performance of Outlier Filtering Methods. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317435.

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Agencies use a variety of technologies and data providers to obtain travel time information. The best quality data can be obtained from second-by-second tracking of vehicles, but that data presents many challenges in terms of privacy, storage requirements and analysis. More frequently agencies collect or purchase segment travel time based upon some type of matching of vehicles between two spatially distributed points. Typical methods for that data collection involve license plate re-identification, Bluetooth, Wi-Fi, or some type of rolling DSRC identifier. One of the challenges in each of these sampling techniques is to employ filtering techniques to remove outliers associated with trip chaining, but not remove important features in the data associated with incidents or traffic congestion. This paper describes a curated data set that was developed from high-fidelity GPS trajectory data. The curated data contained 31,621 vehicle observations spanning 42 days; 2550 observations had travel times greater than 3 minutes more than normal. From this baseline data set, outliers were determined using GPS waypoints to determine if the vehicle left the route. Two performance measures were identified for evaluating three outlier-filtering algorithms by the proportion of true samples rejected and proportion of outliers correctly identified. The effectiveness of the three methods over 10-minute sampling windows was also evaluated. The curated data set has been archived in a digital repository and is available online for others to test outlier-filtering algorithms.
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Kress, Marin. Automatic Identification System (AIS) data case study : identifying unofficial mooring areas along the Upper Mississippi River. Engineer Research and Development Center (U.S.), May 2023. http://dx.doi.org/10.21079/11681/47081.

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This Dredging Operations and Technical Support (DOTS) program technical note presents the results of a study undertaken at the request of staff from the US Army Corps of Engineers (USACE) Rock Island District (MVR) as part of a larger effort examining the potential creation of seven new permanent mooring cells along the Upper Mississippi River in proximity to lock and dam (LD) locations selected by MVR. MVR staff were interested in evaluating vessel traffic and identifying unofficial mooring areas (i.e., waiting areas) in the vicinity of LD7, LD10, LD11, LD14, LD15, LD20, and LD22; they were also interested in travel times from those unofficial mooring areas to the destination lock. The search distance for unofficial mooring areas was limited to 20 miles from the lock, or the distance to the next closest lock if less than 20 miles, in the appropriate direction (i.e., upstream or downstream), as specified by MVR staff.
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El-Rayes, Khaled, and Ernest-John Ignacio. Evaluating the Benefits of Implementing Mobile Road Weather Information Sensors. Illinois Center for Transportation, February 2022. http://dx.doi.org/10.36501/0197-9191/22-004.

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State departments of transportation (DOTs) have traditionally utilized fixed road weather information sensors (RWIS) to improve road safety during inclement weather; enhance the management of labor, equipment, and materials for winter road maintenance; and reduce adverse environmental impacts from road maintenance activities. Despite the benefits of these fixed RWIS sites, their coverage and effectiveness are limited because of their stationary locations. To overcome these limitations, recent advances in mobile road weather information sensing technology and cellular communications have enabled the development of mobile RWIS that can be deployed on vehicles to expand the limited coverage of fixed RWIS networks. Combining mobile RWIS, fixed RWIS networks, automatic vehicle location, and maintenance decision support systems (MDSS) provide DOTs with accurate georeferenced road and weather information that can be used by DOTs to optimize winter road maintenance operations and deicer applications. This report presents the findings of a research project funded by the Illinois Department of Transportation to investigate the effectiveness of mobile RWIS and MDSS in improving winter maintenance operations. This project had the following three objectives. First, conduct a literature review to gather and analyze current practices and latest research studies on mobile RWIS and their use for collecting real-time winter roadway conditions to optimize winter maintenance operations. Second, perform interviews with other state DOTs to gather and analyze their experiences and best management practices for the deployment and use of mobile RWIS and MDSS. Third, develop recommendations for a pilot study to evaluate the deployment and performance of mobile RWIS and MDSS in order to determine their effectiveness, implementation requirements, software/technology needs, operational challenges, and life-cycle costs.
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DiJoseph, Patricia, Brian Tetreault, and Marin Kress. AIS data case Study : identifying AIS coverage gaps on the Ohio River in CY2018. Engineer Research and Development Center (U.S.), June 2021. http://dx.doi.org/10.21079/11681/40886.

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This Coastal and Hydraulics Engineering Technical Note (CHETN) describes a method for evaluating the received coverage from Automatic Identification System (AIS) shore sites and the availability of historic vessel position reports along the Ohio River. The network of AIS shoreside sites installed and operated by the US Army Corps of Engineers (USACE) and the US Coast Guard (USCG) receive information transmitted from vessels; however, reception of these transmissions is generally line-of-sight between the vessel and the AIS site antenna. Reception may also be affected by factors such as the quality of the transceiver installation aboard the vessel as well as the state of the equipment at the receiving site. Understanding how to define and quantify coverage gaps along the inland river system can inform research utilizing AIS data, provide information on the performance of the AIS network, and provide guidance for efforts to address identified coverage gaps
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Tetreault, Brian, Marin Kress, and Patricia DiJoseph. AIS data case study : evaluating reception of AIS position reports on the Missouri River by LOMA AIS sites in April and August 2020. Engineer Research and Development Center (U.S.), January 2022. http://dx.doi.org/10.21079/11681/42980.

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This Coastal and Hydraulics Engineering Technical Note (CHETN) describes a method for evaluating the received coverage from Automatic Identification System (AIS) shoreside sites along the Missouri River managed by the US Army Corps of Engineers (USACE) Lock Operations Management Application (LOMA), and presents the results of that analysis. The purpose is to identify AIS coverage gaps in the current system. Reception of AIS transmissions between shore-based transceivers and vessels is generally line-of-sight between the vessel and the AIS site antenna. However, signal reception may be affected by factors such as the distance and terrain between the vessel and the transceiver site, quality of the transceiver installation, state of the equipment either aboard the vessel or at the shore transceiver station, and atmospheric phenomena. Quantifying coverage gaps along the inland waterways system can inform research that uses AIS data, provide information on the performance of the AIS network, and provide guidance for efforts to address coverage gaps to improve navigation safety. In autumn 2020, severe shoaling was occurring on the Missouri River. As the shoals were identified, the Kansas City District requested the LOMA system transmit AIS Aid to Navigation (AtoN) to mark the shoals in several critical areas. However, vessel pilots sometimes reported that they were not receiving the AIS AtoN being transmitted. At the request of the Kansas City District, the US Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory (ERDC-CHL), conducted a coverage analysis using data collected from the LOMA AIS transceivers in the area to determine if there were coverage issues and their extent and to aid in determining the best means of addressing any coverage gaps.
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Bukreiev, Dmitriy, Pavlo Chornyi, Evgeniy Kupchak, and Andrey Sender. Features of the development of an automated educational and control complex for checking the quality of students. [б. в.], March 2021. http://dx.doi.org/10.31812/123456789/4426.

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The paper reveals the problematic features of developing an automated system for teaching students. The authors emphasize the need to study the specialized needs of the system before the development process and conduct an in-depth analysis of the needs of the modern educational process in order to identify the needs of the future product. In this paper authors develop a model of knowledge representation in the system and reveal the features of the mathematical apparatus for calculating and automating the processes of obtaining and evaluating students knowledge.
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TeGrotenhuis, Ward. Clothes Dryer Automatic Termination Evaluation. Office of Scientific and Technical Information (OSTI), October 2014. http://dx.doi.org/10.2172/1159793.

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TeGrotenhuis, Ward. Clothes Dryer Automatic Termination Sensor Evaluation. Office of Scientific and Technical Information (OSTI), October 2014. http://dx.doi.org/10.2172/1159794.

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Hanson, Michelle J., Teresa S. Aden, and Susan J. Bevelheimer. Evaluation of Automatic Aqueous Parts Washers. Fort Belvoir, VA: Defense Technical Information Center, December 1997. http://dx.doi.org/10.21236/ada336543.

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Lassahn, G. D., J. K. Partin, and J. R. Davidson. Automatic TLI recognition system evaluation using AMPS data. Office of Scientific and Technical Information (OSTI), March 1995. http://dx.doi.org/10.2172/130622.

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