Manual Marking Research Articles

Stereo image matching for facial feature measurement to aid in fetal alcohol syndrome screening

The facial phenotype associated with fetal alcohol syndrome is identified through the measurement of facial distances and their comparison to population norms. As an alternative to time-consuming direct manual measurements, stereo photogrammetry has been used to obtain the required facial measurements from stereo digital photographs. While stereo photogrammetric measurement is faster, it requires manual marking of relevant facial landmarks on digital images. We present an algorithm that automatically finds matched feature points on the second of a pair of stereo images, after manual marking of the first. Standard image processing tools are used for preprocessing. Matching is based on a simple exhaustive search in an image window, with the sum of squared differences of the pixel intensities in the two images as the objective function. Eye measurements, namely palpebral fissure length, interpupillary distance, inner canthal distance and outer canthal distance, as well as distances that can be used to approximate the circularity of the upper lip, were obtained using the manual method of marking both images, and the method of automatic marking of the second image. Comparison revealed mean differences less than 1 mm.

Dataset of manually measured QT intervals in the electrocardiogram

BackgroundThe QT interval and the QT dispersion are currently a subject of considerable interest. Cardiac repolarization delay is known to favor the development of arrhythmias. The QT dispersion, defined as the difference between the longest and the shortest QT intervals or as the standard deviation of the QT duration in the 12-lead ECG is assumed to be reliable predictor of cardiovascular mortality.The seventh annual PhysioNet/Computers in Cardiology Challenge, 2006 addresses a question of high clinical interest: Can the QT interval be measured by fully automated methods with accuracy acceptable for clinical evaluations?MethodThe PTB Diagnostic ECG Database was given to 4 cardiologists and 1 biomedical engineer for manual marking of QRS onsets and T-wave ends in 458 recordings. Each recording consisted of one selected beat in lead II, chosen visually to have minimum baseline shift, noise, and artifact.In cases where no T wave could be observed or its amplitude was very small, the referees were instructed to mark a 'group-T-wave end' taking into consideration leads with better manifested T wave.A modified Delphi approach was used, which included up to three rounds of measurements to obtain results closer to the median.ResultsA total amount of 2*5*548 Q-onsets and T-wave ends were manually marked during round 1. To obtain closer to the median results, 8.58 % of Q-onsets and 3.21 % of the T-wave ends had to be reviewed during round 2, and 1.50 % Q-onsets and 1.17 % T-wave ends in round 3.The mean and standard deviation of the differences between the values of the referees and the median after round 3 were 2.43 ± 0.96 ms for the Q-onset, and 7.43 ± 3.44 ms for the T-wave end.ConclusionA fully accessible, on the Internet, dataset of manually measured Q-onsets and T-wave ends was created and presented in additional file: 1 (Table 4) with this article. Thus, an available standard can be used for the development of automated methods for the detection of Q-onsets, T-wave ends and for QT interval measurements.

Locality phase prediction

As computer memory hierarchy becomes adaptive, its performance increasingly depends on forecasting the dynamic program locality. This paper presents a method that predicts the locality phases of a program by a combination of locality profiling and run-time prediction. By profiling a training input, it identifies locality phases by sifting through all accesses to all data elements using variable-distance sampling, wavelet filtering, and optimal phase partitioning. It then constructs a phase hierarchy through grammar compression. Finally, it inserts phase markers into the program using binary rewriting. When the instrumented program runs, it uses the first few executions of a phase to predict all its later executions.Compared with existing methods based on program code and execution intervals, locality phase prediction is unique because it uses locality profiles, and it marks phase boundaries in program code. The second half of the paper presents a comprehensive evaluation. It measures the accuracy and the coverage of the new technique and compares it with best known run-time methods. It measures its benefit in adaptive cache resizing and memory remapping. Finally, it compares the automatic analysis with manual phase marking. The results show that locality phase prediction is well suited for identifying large, recurring phases in complex programs.

Locality phase prediction

As computer memory hierarchy becomes adaptive, its performance increasingly depends on forecasting the dynamic program locality. This paper presents a method that predicts the locality phases of a program by a combination of locality profiling and run-time prediction. By profiling a training input, it identifies locality phases by sifting through all accesses to all data elements using variable-distance sampling, wavelet filtering, and optimal phase partitioning. It then constructs a phase hierarchy through grammar compression. Finally, it inserts phase markers into the program using binary rewriting. When the instrumented program runs, it uses the first few executions of a phase to predict all its later executions.Compared with existing methods based on program code and execution intervals, locality phase prediction is unique because it uses locality profiles, and it marks phase boundaries in program code. The second half of the paper presents a comprehensive evaluation. It measures the accuracy and the coverage of the new technique and compares it with best known run-time methods. It measures its benefit in adaptive cache resizing and memory remapping. Finally, it compares the automatic analysis with manual phase marking. The results show that locality phase prediction is well suited for identifying large, recurring phases in complex programs.

Locality phase prediction

As computer memory hierarchy becomes adaptive, its performance increasingly depends on forecasting the dynamic program locality. This paper presents a method that predicts the locality phases of a program by a combination of locality profiling and run-time prediction. By profiling a training input, it identifies locality phases by sifting through all accesses to all data elements using variable-distance sampling, wavelet filtering, and optimal phase partitioning. It then constructs a phase hierarchy through grammar compression. Finally, it inserts phase markers into the program using binary rewriting. When the instrumented program runs, it uses the first few executions of a phase to predict all its later executions.Compared with existing methods based on program code and execution intervals, locality phase prediction is unique because it uses locality profiles, and it marks phase boundaries in program code. The second half of the paper presents a comprehensive evaluation. It measures the accuracy and the coverage of the new technique and compares it with best known run-time methods. It measures its benefit in adaptive cache resizing and memory remapping. Finally, it compares the automatic analysis with manual phase marking. The results show that locality phase prediction is well suited for identifying large, recurring phases in complex programs.

Evaluating an image analysis system for mapping white clover pastures

We have developed an image analysis system for mapping white clover pastures. The information from digital colour photographs is processed by software (Trifolium.exe) specially designed for the purpose. The software estimates the coverage of clover, weeds and bare ground, and the unidentified remainder of the total area is regarded as covered by grass. To evaluate the reliability of the estimates of clover content, the clover on paper printouts of non-processed images were marked manually and analysed by a photo scanner and commercially available software. The outputs from Trifolium.exe and the estimates from scanned manual markings were highly correlated (r 2=0.81). A sensitivity test was conducted to quantify the impact of changes of six user-adjustable parameters of Trifolium.exe. The software output of clover coverage was sensitive for changes in three, soil coverage for changes in one, and weed coverage for changes in all parameters. The fact that the digital image acquisition and analysis produce nearly continuous and exactly positioned data, implies further that it is a very appropriate tool for analyses of spatial dynamics in grass-clover pastures.

Interrogative Constructions in Signed Languages: Crosslinguistic Perspectives

This article reports on results from a broad crosslinguistic study based on data from thirty-five signed languages around the world. The study is the first of its kind, and the typological generalizations presented here cover the domain of interrogative structures as they appear across a wide range of geographically and genetically distinct signed languages. Manual and nonmanual ways of marking basic types of questions in signed languages are investigated. As a result, it becomes clear that the range of crosslinguistic variation is extensive for some subparameters, such as the structure of question-word paradigms, while other parameters, such as the use of nonmanual expressions in questions, show more similarities across signed languages. Finally, it is instructive to compare the findings from signed language typology to relevant data from spoken languages at a more abstract, crossmodality level.

Automated Tracking of Facial Features in Patients with Facial Neuromuscular Dysfunction

Facial neuromuscular dysfunction severely impacts adaptive and expressive behavior and emotional health. Appropriate treatment is aided by quantitative and efficient assessment of facial motion impairment. We validated a newly developed method of quantifying facial motion, automated face analysis (AFA), by comparing it with an established manual marking method, the Maximal Static Response Assay (MSRA). In the AFA, motion of facial features is tracked automatically by computer vision without the need for placement of physical markers or restrictions of rigid head motion. Nine patients (seven women and two men) with a mean age of 39.3 years and various facial nerve disorders (five with Bell's palsy, three with trauma, and one with tumor resection) participated. The patients were videotaped while performing voluntary facial action tasks (brow raise, eye closure, and smile). For comparison with MSRA, physical markers were placed on facial landmarks. Image sequences were digitized into 640 x 480 x 24-bit pixel arrays at 30 frames per second (1 pixel congruent with0.3 mm). As defined for the MSRA, the coordinates of the center of each marker were manually recorded in the initial and final digitized frames, which correspond to repose and maximal response. For the AFA, these points were tracked automatically in the image sequence. Pearson correlation coefficients were used to evaluate consistency of measurement between manual (the MSRA) and automated (the AFA) tracking methods, and paired t tests were used to assess the mean difference between methods for feature tracking. Feature measures were highly consistent between methods, Pearson's r = 0.96 or higher, p < 0.001 for each of the action tasks. The mean differences between the methods were small; the mean error between methods was comparable to the error within the manual method (less than 1 pixel). The AFA demonstrated strong concurrent validity with the MSRA for pixel-wise displacement. Tracking was fully automated and provided motion vectors, which may be useful in guiding surgical and rehabilitative approaches to restoring facial function in patients with facial neuromuscular disorders.

3-D sonographic volume measurement of the cerebral ventricular system: in vitro validation

This in vitro study evaluates the accuracy and observer dependency of a freehand three-dimensional (3-D) ultrasound system for measuring cerebral ventricular volume in infants. A sphere, a cylinder, and three cerebral ventricle phantoms were made of agarose and embedded in an echogenic matrix after measuring true volumes by water displacement. Volumes of the models were calculated by 3-D software after manual contour marking on ultrasound cross-sections. Mean ± SD sonographic volume was 94.6% ± 7.3% ( n = 130) of true volumes. Intraobserver variation ( n = 10) was 2.3%–5.3% for complete investigation (scanning and marking), and 1.8%–4.1% for marking alone. Difference of means ( n = 10) between two observers was 7.6% to 10.8% for complete investigation, and 0.6% to 1.6% for the marking process. We conclude that 3-D freehand ultrasonography may be useful for examining ventricle dilatation in infancy.

Effective electronic marking for on-line assessment

In response to the demands of increasing student numbers, the BOSS system for submission and assessment has been constructed to enable student programming assignments to be submitted and tested on-line. More recent developments of this system have been concerned with the addition of electronic marking facilities that incorporate both automated marking, resulting from the automated testing, and manual marking in a secure environment. This paper briefly reviews the system and describes in detail the electronic marksheets , their functionality, and their user-interface.

Quality control of rain data used for urban runoff systems

When improving software packages such as MOUSE and SAMBA for designing sewers and storage basins, and simulating overflows and flooding the quality of the input becomes important. The essential input to these modelling tools are the historical rain series. This paper presents the procedures for collection and quality control of rain data from a network of tipping bucket rain gauges in Denmark carried out by the Danish Meteorological Institute. During rain, the RIMCO gauge counts the number of tips (each of 0.2 mm of precipitation) every minute. The quality control of the rain data includes an automatic and a manual bit marking, where the automatic control basically is pointing out minutes with extreme intensities. In the manual control, the maximum intensities as well as the daily totals of precipitation are inspected, using weather charts, intensity plots and precipitation sums of nearby Hellmann gauges. Shortcomings and improvements of the quality control are discussed. Although, it is possible to improve the efficiency of the quality control, long term corrections will always be necessary.

Quality control of rain data used for urban runoff systems

When improving software packages such as MOUSE and SAMBA for designing sewers and storage basins, and simulating overflows and flooding the quality of the input becomes important The essential input to these modelling tools are the historical rain series. This paper presente the procedures for collection and quality control of rain data from a network of tipping bucket rain gauges in Denmark carried out by the Danish Meteorological Institute. During rain, the RIMCO gauge counts the number of tips (each of 0.2 mm of precipitation) every minute. The quality control of the rain data includes an automatic and a manual bit marking, where the automatic control basically is pointing out minutes with extreme intensities. In the manual control, the maximum intensities as well as the daily totals of precipitation are inspected, using weather charts, intensity plots and precipitation sums of nearby Hellmann gauges. Shortcomings and improvements of the quality control are discussed. Although, it is possible to improve the efficiency of the quality control, long term corrections will always be necessary.

Neural network approach to assist markings of syllabic nuclei for multi-language database

The manual marking of syllabic nuclei is not difficult for a trained person. For a large amount of speech data, it is time consuming, and human error can introduce inconsistencies. The problem becomes worse when the person is not familiar with the language. To provide an automatic procedure for reducing the marking time and eliminate human errors, an adhoc algorithm was developed to find syllabic nuclei using a set of acoustic features. The initial error rate is 15%. The overall time spent marking automatically and correcting errors manually, however, was less than hand-marking by itself. An improved machine learning approach using a backward-error-propagation multi-layered perceptron, with the same acoustic features as inputs, was applied to the training speech. The hand-corrected markings was used as the teacher. Testing on the training data showed only 3%–5% misalignment. The time required to verify markings has further been reduced. When the training extended to a database of 43 different languages, the marking errors dropped to 2%, less than the errors in the initial hand-markings. Finally, when the network is used to mark 7 h of a multi-language database, there is no significant increase in marking errors.

Assessment of student programming assignments in COBOL

In the teaching of computing subjects at tertiary level, student programming assignments are used for both learning and assessment. The manual marking of such an assignment by tutors is tedious and inconsistent. The use of a computerized system for this purpose reduces the tutor's workload while providing objective assessment of the students' work as well as timely feedback on their progress.

Adaptive probabilistic process for speech segmentation

A classical and as yet unsolved problem in speech research is that of segmenting running speech, either as an end in itself, or as a part of a segmentation and labeling task. This paper reports an adaptive process using a modification of the Viterbi algorithm, in which a simple Markov model is applied to running speech. This method is flexible as well as being computationally tractible. The results of the automatic process are compared with segmentation derived from careful manual marking.