Miracle-dz/UniFAR-FTUs huggingface dataset:
Resistance changes of SnO/sub 2/ thin films suitable for microelectronic gas sensors

A simple method for the separate estimation of the electrical sheet resistivity (/spl rho//sub s/) and the contact resistivity (/spl rho//sub c/) is developed. The influence of an oxygen annealing on /spl rho//sub s/ and /spl rho//sub c/ of thin SnO/sub 2/ layers with W/Al, Cr/Al and Ti/Al contacts is investigated as an illustration of the method. The method is applicable for evaluation of very high resistivity layers, because "potential" measurements are not needed.
Modern Applied Biostatistical Methods Using S-Plus

From the Publisher: Modern Applied Biostatistical Methods Using S-Plus is unlike other statistical texts, which usually deal either with theory or with applications. It integrates the two elements into a single presentation of theoretical background, data, interpretation, graphics, and implementation. This all-around approach will be particularly helpful to students in various biostatistics and advanced epidemiology courses, and will interest all researchers involved in biomedical data analysis.
Medical image segmentation using improved active contour model

In this paper, an algorithm for the semiautomatic segmentation of medical image series is proposed by combining the live wire algorithm and the active contour model. Firstly the accurate segmented results of one or more slices in a medical image series are obtained by the livewire algorithm and the watershed transform. Based on the segmentation of previous slices, the computer will segment the nearby slice using the modified active contour model automatically. To make full use of the correlative information between contiguous slices, we introduce a gray-scale model to the boundary points of the active contour model to record the local region characters of the desired object in the segmented slice and scale model. Moreover we introduce the active region concept of the snake to improve the segmentation accuracy. Experiment shows that our algorithm can obtain the boundary of the desired object from a series of medical images quickly and reliably with only little user intervention.
Improving partial stripe write performance in RAID level 5

Redundant Array of Independent Disks (RAID) is now the most efficient way to solve the bottleneck problem between CPU and storage devices. In RAID 5, for the write operation, disk array controller first reads the old data from the disks which the new data will write into and the old parity information. Then, it calculates the new parity information using the old data, the new data and the old parity information to get the new parity. At last, disk array controller writes the new data and the new parity information altogether into the corresponding disks in the array. Thus, in order to write the new data into the disk array, it should perform the two extra read operations and one extra write operation compared with RAID 0. Hence, improving the stripe write operation is the key factor in improving the write performance of RAID 5. The basic idea is the reduce the stripe read/write operations to as few as possible. This paper discusses the different situations of stripe write operation in RAID 5, and proposes an adaptive control algorithm to improve the partial stripe write performance. The basic idea is to reduce the stripe read/write operation as much as possible.
Arabic/Latin and Machine-printed/Handwritten Word Discrimination using HOG-based Shape Descriptor

In this paper, we present an approach for Arabic and Latin script and its type identification based on Histogram of Oriented Gradients (HOG) descriptors. HOGs are first applied at word level based on writing orientation analysis. Then, they are extended to word image partitions to capture fine and discriminative details. Pyramid HOG are also used to study their effects on different observation levels of the image. Finally, co-occurrence matrices of HOG are performed to consider spatial information between pairs of pixels which is not taken into account in basic HOG. A genetic algorithm is applied to select the potential informative features combinations which maximizes the classification accuracy. The output is a relatively short descriptor that provides an effective input to a Bayes-based classifier. Experimental results on a set of words, extracted from standard databases, show that our identification system is robust and provides good word script and type identification: 99.07% of words are correctly classified.
Real-time recognition of road traffic sign in motion image based on genetic algorithm

In this paper, a new technology based on the genetic algorithm and new image filter for recognizing road traffic sign from motion image captured by a CCD camera in a car was developed. In order to realize a real-time position recognition, the step genetic algorithm with search region limits and image filter (denoted by SVF) were proposed. The genetic algorithm with search region limits was employed to detect the position and size of traffic signs in real-time as well as SVF was employed to extract specified colors. The feasibility and validity of the proposed scheme are demonstrated through road driving experiments.
Technology-assisted sheltered instruction: instructional streaming video in an EFL multi-purpose computer course

Content-based instruction (CBI) has been widely adopted for decades. However, existing CBI models cannot always be effectively put into practice, especially for learners of lower English proficiency in English as a foreign language (EFL) context. This study examined an animation design course adopting CBI to promote reading abilities of English majors at a technology university in Taiwan. CBI usually adds challenges in cognitive and linguistic learning, especially for English majors in computer courses. Different from other CBI courses, this course dealt with multiple situations: multi-approaches (CBI and task-based instruction); multi-skills (Flash animation software skills- various animation effects; language skills-computer vocabulary and reading comprehension); multi-level learners (various English language proficiency levels – mostly low proficiency level; computer abilities; learning styles), and a large class taught by one instructor. Simply employing CBI cannot solve such complex problems. Therefore, instructional streaming video was applied as a learner-directed scaffold and a technological facilitator. A control group and an experimental group comprised 117 and 121 English majors taking this course for one semester respectively. Both groups were taught with English materials but the later were additionally provided with instructional streaming video (ISV). Qualitative and quantitative data were collected from classroom observations, interviews, exams, and semester-end questionnaires from both groups to examine whether ISV facilitated instructor teaching and student learning. Results show that the experimental group significantly performed better in reading comprehension, reading speed, acceptance, attention, and exams, as well as easing teaching difficulties. Drawn upon empirical results, a technology-assisted sheltered model was generated for EFL multi-purpose courses.
Batch-to-batch model-based iterative optimisation control for a batch polymerisation reactor

A batch-to-batch model-based iterative optimisation control strategy for a batch polymerisation reactor is proposed. Because the reference sequences for product quality variables during a batch are usually difficult to be set reasonably and the interest usually lies in the end-of-batch product quality, a modified quadratic objective function is introduced to track the desired qualities at the end-point of a batch. Predictions of recurrent neural network models are modified using the prediction errors in the previous runs. Because model errors are gradually reduced from batch to batch, the control trajectory gradually approaches to the optimal control policy. The proposed scheme is illustrated on a simulated batch polymerisation reactor.
Integrating Globality and Locality for Robust Representation Based Classification

The representation based classification method (RBCM) has shown huge potential for face recognition since it first emerged. Linear regression classification (LRC) method and collaborative representation classification (CRC) method are two well-known RBCMs. LRC and CRC exploit training samples of each class and all the training samples to represent the testing sample, respectively, and subsequently conduct classification on the basis of the representation residual. LRC method can be viewed as a “locality representation” method because it just uses the training samples of each class to represent the testing sample and it cannot embody the effectiveness of the “globality representation. ” On the contrary, it seems that CRC method cannot own the benefit of locality of the general RBCM. Thus we propose to integrate CRC and LRC to perform more robust representation based classification. The experimental results on benchmark face databases substantially demonstrate that the proposed method achieves high classification accuracy.
Lossless compression of mammographic images with region‐based predictor selection

One of the main tools for early diagnosis of breast cancer is digital mammography. These images require large storage space and are difficult to be transmitted over communication links. In this paper we propose a context‐based method for lossless compression of these images. Some modifications are performed to customize the activity level classification model (ALCM) predictor to work best in mammograms. The function of the modified predictor changes for different main regions of these images. Also, best qualities of two other predictors are exploited and the results of the fittest predictor are selected adaptively for the prediction of a pixel. Moreover, context modeling is used for a better categorization of the prediction errors. The proposed algorithm was tested using images from a well‐known database and the results were compared with two standard compression methods of lossless mode of JPEG2000 and JPEG‐LS. The proposed method was proved to produce better compression results than those of the standard algorithms. © 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
A cross sectional assessment of health status instruments in patients with rheumatoid arthritis participating in a clinical trial

Objective. To (1) validate the Short-Form Health Survey (SF-36) as a generic functional health status measure in patients with rheumatoid arthritis (RA): and (2) assess correlations between the SF-36 and other outcome measures used in the Minocycline in Rheumatoid Arthritis (MIRA) Trial. Methods. We conducted a cross sectional analysis of the final visit outcome measures from the 48 week, multicenter, placebo controlled, double blind MIRA trial. Multitrait scaling analyses assessed convergent and discriminant validity and internal consistency reliability of the SF-36 in the study patients. Responses to comparable items on the SF-36 and modified Health Assessment Questionnaire (M-HAQ) regarding physical functioning were compared and questions from both instruments were also compared to other RA outcome measures. Results. In patients with RA, the SF-36 had high internal consistency and reliability, high discriminant and high convergent validity. Moderate correlations were observed (r = -0.46 to -0,61, p < 0.01 in each case) for comparable items on the SF-36 and M-HAQ regarding dressing, walking, and bending. Joint tenderness score correlations with items on the M-HAQ and SF-36, and joint tenderness score correlations with the SF-36 scales were higher than for joint swelling scores. Physician and patient global assessments were most highly correlated (r = 0.58 and 0.66. p < 0.01, respectively) with the SF-36 bodily pain item. Conclusion. The SF-36 is a valid instrument for this RA population. The SF-36 correlates with the M-HAQ and the physician and patient global assessments. The usefulness of the SF-36 in measuring change in RA clinical trials requires testing in longitudinal studies.
Modeling and analysis of electrostatic force for robot handling of fabric materials

Electrostatic force has received considerable interest in recent years for handling small objects in microsystems and microengineering applications, but little work has been carried out to study its use in handling large-size objects. This paper discusses the principles of a robotic electrostatic gripping device for the handling of large-size fabric plies. A theory is derived to describe the dynamic behavior of the charging/discharging processes of the gripping surface. Mathematical equations are developed to relate the dynamic performance of the gripping force to the device's design parameters and the properties of materials being handled. An automated experimental process is employed to validate the theory. The theoretical modeling and analysis of the gripping force has allowed optimization of the gripper's design parameters for practical materials handling applications. The design and construction of an electrostatic gripper for fabric handling in aerospace applications are discussed.
Preventing Buffer Overflows with Binary Rewriting

Title of thesis: PREVENTING BUFFER OVERFLOWS WITH BINARY REWRITING Padraig O’Sullivan, Master of Science, 2010 Thesis directed by: Professor Rajeev Barua Department of Electrical and Computer Engineering Professor Angelos Keromytis Department of Computer Science, Columbia University Buffer overflows are the single largest cause of security attacks in recent times. Attacks based on this vulnerability have been the subject of extensive research and a significant number of defenses have been proposed for dealing with attacks of this nature. However, despite this extensive research, buffer overflows continue to be exploited due to the fact that many defenses proposed in prior research provide only partial coverage and attackers have adopted to exploit problems that are not well defended. The fact that many legacy binaries are still deployed in production environments also contributes to the success of buffer overflow attacks since most, if not all, buffer overflow defenses are source level defenses which require an application to be re-compiled. For many legacy applications, this may not be possible since the source code may no longer be available. In this thesis, we present an implementation of a defense mechanism for defending against various attack forms due to buffer overflows using binary rewriting. We study various attacks that happen in the real world and present techniques that can be employed within a binary rewriter to protect a binary from these attacks. Binary rewriting is a nascent field and little research has been done regarding the applications of binary rewriting. In particular, there is great potential for applications of binary rewriting in software security. With a binary rewriter, a vulnerable application can be immediately secured without the need for access to it’s source code which allows legacy binaries to be secured. Also, numerous attacks on application software assume that application binaries are laid out in certain ways or have certain characteristics. Our defense scheme implemented using binary rewriting technology can prevent many of these attacks. We demonstrate the effectiveness of our scheme in preventing many different attack forms based on buffer overflows on both synthetic benchmarks and real-world attacks. PREVENTING BUFFER OVERFLOWS WITH BINARY REWRITING by Padraig O’Sullivan Thesis submitted to the Faculty of the Graduate School of the University of Maryland, College Park in partial fulfillment of the requirements for the degree of Master of Science 2010 Advisory Committee: Professor Rajeev Barua, Chair/Advisor Dr. Peter Petrov Dr. Gang Qu c © Copyright by Padraig O’Sullivan 2010
Pheromone based transportation scheduling system for the multi-vehicle routing problem

We propose a novel and fast method, named "pheromone based transportation scheduling system" (PBTS), to obtain feasible solution for the multi-vehicle routing problem. It is a method inspired by a communication mechanism of living organisms such as ants and bees which communicate with each other and organize the cluster using pheromones. In PBTS, each transportation agent autonomously and independently searches its own route as the partial solution of the vehicle routing problem, where the imitated pheromone is effectively used to dissolve the duplications of customers between routes of agents. Computer simulations show that the PBTS can generate good solutions comparably to the one generated by a genetic algorithm in shorter time.
From ISBD(S) to ISBD(CR)

Abstract The development and maintenance of the various ISBDs, international standards that play a major role in universal bibliographic control, are the responsibility of the Standing Committee of the IFLA Section on Cataloguing. ISBD(S) has just been revised to take into account new developments in the production and dissemination of serial-type publications and is now known as ISBD(CR)-International Standard Bibliographic Description for Serials and Other Continuing Resources. Major changes to the standard were made in connection with revisions to both the Anglo-American Cataloguing Rules and the ISSN Manual. These international standards for the descriptive cataloguing of serials and integrating resources have been harmonized to a great extent, thus facilitating access to these publications in all formats.
The research of the police GIS spatial data classification technology based on rough set

In this paper, the methods of spatial data classification which is based on the rough sets theory are studied. Using rough set methods one can simplify enormous irregular geographic information system (GIS) data. By using the trial data of cars, we can easily find out the places where cars often give an alarm or traffic jams often happen. With these information, the police can learn where criminals often appear or accidents often happen. It is thus useful for them to concentrate their force.
TUMOR SEGMENTATION FROM PET/CT IMAGES USING LEVEL SETS METHOD

In the framework of detection, diagnostic and treatment planning of tumors, the Positron Emission Tomography (PET) examination coupled with a Computed Tomography (CT) have become recently the most efficient technique. Manual segmentation of regions of interest (ROI) could be time consuming and this is necessary to obtain information about patient pathology. The aim of our study is to propose an automatic solution to this problem. This paper presents an approach of tumor segmentation based on a level set method. One critical step, the algorithm stopping, is automatic. The results obtained by the proposed method dealing with PET-CT images are encouraging.
Automatic Panorama Recognition and Stitching Based on Graph Structure

An automatic panorama recognition and stitching method based on graph structure was proposed to solve the multiple images recognition and matching problem. With multiple unordered images of user input, the method can automatically finding overlapping portion between images, and stitch them. First, the MOPS feature points were detected from the input images, and using kd-tree nearest neighbor search to perform fast feature matching between images. The motion model between any two images can be established by RANSAC algorithm based on the correspondence of feature points, and robust verification by a probabilistic algorithm. The automatic recognition of multiple panoramic images problem can be solved by building undirected connected graph corresponding to image matching relationship. Finally, a recursive algorithm was used to do depth-first traversal of the established undirected connected graphs, and multi-band blending algorithm was used to eliminate stitching seam. The experiments showed that multiple unordered images can be matched and recognized automatically, and panoramas can also be stitched automatically and seamlessly. Keywords-feature detection; feature matching; image recognition; image matching; image stitching
Interferometric synthetic aperture radar terrain elevation mapping from multiple observations

All prior interferometric SAR imaging experiments to date dealt with pairwise processing. Simultaneous image collections from two antenna systems or two-pass single antenna collections are processed as interferometric pairs to extract corresponding pixel by pixel phase differences which encode terrain elevation height. The phase differences are wrapped values which must be unwrapped and scaled to yield terrain height. We propose two major classes of techniques that hold promise for robust multibaseline (multiple pair) interferometric SAR terrain elevation mapping. The first builds on the capability of a recently published method for robust weighted and unweighted least-squares phase unwrapping, while the second attacks the problem directly in a maximum likelihood (ML) formulation. We will provide several examples (actual and simulated SAR imagery) that illustrate the advantages and disadvantages of each method. <<ETX>>
C-B4-02: Enhancing the Quality and Efficiency of Obstructive Sleep Apnea Screening Using Health Information Technology: Results of a Geisinger Clinic Pilot Study

Background Health information technology (HIT) can improve the screening and delivery of care to patients with chronic illnesses. To date there are no published data describing the use of HIT for screening patients with obstructive sleep apnea (OSA), a prevalent under-diagnosed chronic condition representing a substantial and growing socio-economic burden. Geisinger Clinic is a physician-led, multi-specialty group practice in rural Central Pennsylvania with integrated electronic medical records. Aim We sought to determine whether HIT could be used to identify OSA amongst patients at risk for the disease through the use of a simple questionnaire and a physician approved referral protocol. Methods Using an internet-based portal through which patients can review their Electronic Health Record (EHR), schedule appointments, and receive communication, patients with a body mass index (BMI) >40 and without a diagnosis or prior evaluation for sleep apnea were invited to complete the “STOP” questionnaire, a self-administered validated screening tool consisting of 4 “yes/no” questions; “yes” answers to 2 questions identify individuals at high risk of having OSA. Patients who screened positive were then contacted to schedule a sleep medicine evaluation. Results Electronic invitations were sent to 2,283 eligible patients to take the questionnaire; 279 (12%) completed and submitted their responses. Based on their answers, 122/279 (44%) were identified as being at high risk for having OSA and recommended to undergo evaluation in the sleep clinic. To date, 104/122 patients (85%) were offered an appointment with a sleep specialist; the remaining 18 (15%) are waiting scheduling. Of those offered a clinic appointment, 41/104 (40%) have undergone a sleep medicine evaluation, 38/104 (36%) are waiting to be scheduled, and 25/104 (24%) cancelled or did not keep their appointment. Of the evaluated patients, 38/41 (93%) were diagnosed with OSA, 2/41(5%) had negative sleep studies, and 1/41(2%) are awaiting polysomnographic evaluation. The positive predictive value of the STOP questionnaire among patients who underwent polysomnography was 95%. Conclusions This pilot study suggests that utilizing an internet-based patient portal via the EHR can identify patients at high risk of OSA and facilitate their ultimate evaluation and diagnosis through the administration of a simple questionnaire.