Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing the Presence and Severity of Constipation with Plain Radiographs in Constipated Palliative Care Patients.

BACKGROUND Palliative care guidelines recommend plain radiographs to assess constipation based on the presumption that visible fecal shadowing represents stool retention. Despite this, using plain radiographs in this way is not well validated. OBJECTIVES This work's main aim was to compare clinicians' reports of fecal loading on radiographs. This study also compares clinicians' assessments with radio-opaque marker transit studies and patients' self-reported constipation symptoms. METHODS This study was conducted in a sample of 30 constipated palliative care patients taking laxatives who had all undergone colon transit studies and contemporaneous assessment of constipation symptoms with the Patient Assessment of Constipation Symptom (PAC-SYM) questionnaire. Four separate clinicians independently reported their opinions of fecal loading using a previously developed fecal loading scale. Participant details were summarized and pair-wise inter-rater agreement among all four raters were examined using the Bland-Altman approach. For the comparisons of the clinician-assigned fecal loading score between the radiographic assessment of the normal and slow colon transit time, the nonparametric approach of Mann-Whitney U tests were applied. Spearman's correlation analyses were employed to investigate the association between the clinician-assigned fecal loading score and the patient self-reported PAC-SYM score. RESULTS The results of this study are very similar to other studies conducted in functional constipation, highlighting systematic disagreement between observers. Further poor correlations were noted between fecal loading scores and colon transit times and with patient self-reported symptoms. CONCLUSION These results, when considered with other work in chronic constipation, question the ongoing use of radiographs in the diagnosis of constipation.
Extraction of semantic features of histological images for content-based retrieval of images

This paper presents an approach for automatically assign histologically meaningful labels to tissue slide images. This approach is implemented as part of a larger system, I- Browse, which combines iconic and semantic content for intelligent image browsing. Our approach partitioned an input image into a number of subimages. A set of texture features based on Gabor filterings and color histogram which capture the visual characteristics of each of the subimages were computed. These image feature measurements then form the input to a pattern classifier which gives an initial coarse label assignment to subimages based on a hierarchical clustering of these image features. To facilitate supervised training of the classifier, a knowledge elicitation tool was developed which allows a histopathologist to assign histological terms to a sample of sub-images obtained from digitized tissue imags. The initial labels and their spatial distribution were then analyzed by a semantic analyzer with the help of a knowledge base which contains prior knowledge of the expected visual appearance of histological images of an organ. The label assigned to the subimages were successive refined through a process of relevant feedback.
Learned dictionaries for sparse image representation: properties and results

Sparse representation of images using learned dictionaries have been shown to work well for applications like image denoising, impainting, image compression, etc. In this paper dictionary properties are reviewed from a theoretical approach, and experimental results for learned dictionaries are presented. The main dictionary properties are the upper and lower frame (dictionary) bounds, and (mutual) coherence properties based on the angle between dictionary atoms. Both ℓ0 sparsity and ℓ1 sparsity are considered by using a matching pursuit method, order recursive matching Pursuit (ORMP), and a basis pursuit method, i.e. LARS or Lasso. For dictionary learning the following methods are considered: Iterative least squares (ILS-DLA or MOD), recursive least squares (RLS-DLA), K-SVD and online dictionary learning (ODL). Finally, it is shown how these properties relate to an image compression example.
Generalized preemption models for single-machine dynamic scheduling problems

In the extensive scheduling literature, job preemption, if allowed, implies that the processing of a partly completed job is temporarily halted and later resumed at the same point. However, little attention has been given to problems where job preemption is allowed under the condition that either some startup time delay must be incurred or some fraction of work must be repeated if preemption occurs. We generalize the notion of job preemption by using models representing these conditions. The models are applied to studying the dynamic single-machine scheduling problems of minimizing total flow time, and of minimizing maximum lateness, subject to arbitrary and unknown job ready dates. On-line optimal dispatching rules, which consider only available – as opposed to look-ahead – information, are developed. These rules determine, on arrival or completion of each job, which available job should next be processed by the machine. A special case of our models, the preempt-repeat scenario, where preempted jobs must be totally repeated, is suggested as heuristic for the equivalent non-preemptive static problem where all ready dates are known and given. A computational study is performed to determine the potential benefits of reducing startup time delays or work repetition fractions in the context of continuous improvement of manufacturing systems.
Technology Acceptance Model: A Survey of Literature

The technology acceptance model has been a theory that is most widely used to explain an individualâ€™s acceptance of an information system. This study has reviewed numerous literatures available in this area. The different studies in this area were evaluated to understand the modifications that were done on this model. The paper then tries to provide an insight on future trends in the technology acceptance model.
Massive Open Online Courses (MOOCs) and Their Impact on Academic Library Services: Exploring the Issues and Challenges

2012 was a year of rapid change for education with the advent of MOOCs—Massive Open Online Courses—available for the world to use to learn for free. But what does this mean for the role of the librarian? How has the landscape in education changed, and what are the issues and challenges that librarians now face? This article reviews the position of libraries in the emergence of MOOCs and the role that a librarian could undertake within the research, production, and presentation of MOOCs.
Taming Textual Data: The Contribution of Corpus Linguistics to Computer-Aided Text Analysis

Corpus linguistics studies real-life language use on the basis of a text corpus, drawing on both quantitative and qualitative text analysis techniques. This article seeks to bridge the gap between the social sciences and linguistics by introducing the techniques of corpus linguistics to the field of computer-aided text analysis. The article first discusses the differences between corpus linguistics and computer-aided text analysis, which is divided into computer-aided content analysis and computer-aided interpretive textual analysis. It then outlines the techniques of corpus linguistics for exploring textual data. In an exemplary analysis of letters to shareholders, the article demonstrates how these techniques can be applied to compare letters to shareholders from two different years. The article concludes with a discussion of the strengths and limitations of corpus linguistics for management and organization studies.
Area-efficient CMOS charge pumps for LCD drivers

Area-efficient 4/spl times/ charge pumps based on the cross-coupled structure that uses the V/sub dd/-2V/sub dd/ outputs alternately to reduce the number of power devices and capacitors are presented. Compared with conventional designs, our best design can save two power transistors, one capacitor, and two level shift circuits. An integrated 4/spl times/ charge pump is then designed to deliver 100 /spl mu/A at 9 V using a 0.8-/spl mu/m AMS high-voltage CMOS process. The topology can be extended to 2n/spl times/ charge pumps, and a 6/spl times/ charge pump is also fabricated and tested to demonstrate the validity of the extension.
The Research of Generation Algorithm of Frequent Itemsets in High-Dimensional Data

In the mining of association rules, the generation of frequent itemsets is a key factor that influence the efficiency and performance of the algorithm. With the increase of data dimension, it is obvious that the traditional association rules mining algorithm can’t meet the demand of high dimensional data mining. On the basis of Apriori algorithm, we put forward Split Mtrix _Apriori algorithm in this paper. By generating the Boolean matrix of the database, Split Mtrix _Apriori algorithm decreased the times of scanning database when generating the frequent itemsets. With adopting grouping processing strategy in the Boolean matrix, the algorithm can still keep high efficiency in dealing with high-dimensional data.So Split Mtrix _Apriori improved the efficiency of association rule mining significantly.
Hydro-thermal power flow scheduling accounting for head variations

Variable head hydro-thermal optimal power flow in an electric power system is considered. As the hydro generation is energy limited, a dynamic optimization problem involving the daily scheduling of the system is encountered. This dynamic optimal power flow problem requires solving a large-scale set of nonlinear simultaneous equations. The computational implementation was based on a Newton-Raphson's iterative procedure, with a special initial guess, and sparsity-based matrix manipulations to obtain improved convergence properties. The algorithm was tested with test systems that are smaller than those encountered in practice. Computational results and CPU times required are given to illustrate the impact of including head variations in the model. The effects of head variation, volume of water, and power demand are listed. >
Modeling and simulation of blanket chemical vapor deposition of WSix from WF6/Si2H6

The reaction mechanism of blanket chemical vapor deposition of WSix from WF6/Si2H6 mixture was modeled based on the data of a tubular reactor. In this reaction, film deposition is initiated by radical chain reaction and the silicon concentration in the film can be increased easily. The model is as follows. During radical chain reaction, reaction between WF6 and Si2H6 takes place, Si-rich intermediary product with Si/W = 2 is formed and reaction between the product and Si2H6 causes an increase of Si concentration. The Si concentration profile in the film in the reactor could be simulated by using the reaction speed constant as a fitting parameter and the validity of this model was confirmed. The activation energy of this reaction was 23.5 kJ/mol. Using this model, the Si concentration in the film formed in the substrate-heating-type reactor could be predicted.
Bayesian Software Reliability Prediction Based on Yamada Delayed S-Shaped Model

Software Reliability Growth Models (SRGMs) provide techniques to predict future failure behavior from known characteristics of the software testing work. However, in some cases, software developers did not have sufficient historical data to estimate the corresponding reliability and the expected testing cost, especially for a newly developed software project, and thus the results obtained from analytical models may not be reliable. In such situations, Bayesian analysis is a reasonable approach to additionally take expert's opinions into account for better decision making. In this paper, we utilized Yamada Delayed S-shaped Model with Bayesian analysis in predicting software reliability and expected testing costs to determine an optimal release time for software systems. Besides, the failure process of software are assumed to be drawn from a non-homogeneous Poisson process (NHPP), and the parameters of the proposed model are assumed to be mutually independent and Gamma distributed. Finally, a numerical example is given to verify the effectiveness of the proposed approach, and the sensitive and risk analyses are performed in light of the numerical example.
Parallel force/position control of a novel biomechatronic hand prosthesis

Commercially available prosthetic hands are basically simple grippers having one or two degrees of freedom, which barely restore the capability of the thumb-index pinch. The development of novel prosthetic hands based on a "biomechatronic" design attempts at increasing the dexterity while keeping the same dimension and weight of a traditional prosthetic device. This paper concerns with the study of a particular kind of grasp task performed by the hand: a cylindrical grasp of a cylindrical object. On the basis of a previous grasp analysis, a parallel force/position control is developed that ensures stability of the grasp. Simulation results are discussed to validate the proposed controller in a number of case studies.
A Recognition Algorithm for M-QAM Based on Amplitude Distribution

An automatic recognition algorithm for M-QAM based on the amplitude distribution is proposed. This algorithm uses the normalized amplitude distribution to achieve automatic recognition for M-QAM signals, and enhances the correct recognition rate through the nonlinear amplification. Compared with the recognition algorithm based on amplitude moment, this algorithm does not need those prior conditions, such as carrier frequency offset, code element rate, amplitude factor and so on. The simulation confirmed that, when SNR≥16dB the correct recognition rate of this algorithm is greater than 90%.
Materialised view selection using differential evolution

A data warehouse is designed for answering analytical queries. These queries are usually long, complex and ad hoc in nature and their response time is high when processed against an exponentially growing data warehouse. Materialising views has been found to be an effective tool for reducing this response time. All views cannot be materialised on account of resource constraints. Further, optimal view selection is shown to be an NP-complete problem. This necessitates selection of an appropriate set of views, from amongst all possible views that reduce the query response time. Most of the view selection algorithms are greedy or evolutionary. In this paper, a differential evolution view selection algorithm (DEVSA) that selects the Top-K views from a multi-dimensional lattice is proposed. Further, it is shown that DEVSA when compared to the greedy, genetic and memetic-based view selection algorithms selects comparatively better quality views for higher dimensional datasets.
Approches théoriques en codage vidéo robuste multi-terminal.

In this thesis, new robust video compression techniques are proposed for multi-terminal coding. We first compare four video multiple description coding schemes based on different time splitting patterns and temporal two- or three-band motion-compensated temporal filtering (MCTF). Then, the latter schemes are extended with systematic lossy description coding where the original sequence is separated into two sub-sequences, one being coded as in the latter schemes, and the other being coded with a Wyner-Ziv encoder. This amounts to having a systematic lossy Wyner-Ziv coding of every other frame of each description. This error control approach can be used as an alternative to Automatic Repeat Request (ARQ) or Forward Error Correction (FEC), i. E. The additional bitstream can be systematically sent to the decoder or can be requested, as in ARQ. When used as a FEC mechanism, the amount of redundancy is mostly controlled by the quantization of the Wyner-Ziv data. In this context, this approach leads to satisfactory rate-distortion performance at the side decoders, however suffers from high redundancy which penalizes the central description. To cope with this problem, the approach is then extended to the use of MCTF for the Wyner-Ziv frames, in which case only the low-frequency subbands are Wyner-Ziv encoded and sent in the descriptions. Next, we propose a multiple description coding scheme with side information at the receiver. It builds upon both multiple description coding principles and Slepian-Wolf coding principles. The input source is first quantized with a multiple description scalar quantizer (MDSQ) which introduces redundancy or correlation in the transmitted streams in order to take advantage of the path diversity. The resulting sequences of indexes are Slepian-Wolf encoded, that is separately encoded and jointly decoded. While the first step (MDSQ) plays the role of a channel code, the second one (Slepian-Wolf coding) plays the role of a source code, compressing the sequences of quantized indexes. In a second step, the cross-decoding of the two descriptions is proposed. This allows us to account for both the correlation with the side information as well as the correlation between the two descriptions. Then, we propose a way to improve the robustness of distributed video coding while keeping good rate-distortion performance by structuring the input sequence into groups of picture, each containing one key frame and one Wyner-Ziv frame. For each frame, two descriptions are generated by a MDSQ. This provides two balanced descriptions that contain partial information about every frame in the video input. At the central decoder, iterative decoding of the two Wyner-Ziv descriptions along with side information is performed. We study the influence of the cross-decoding and of the amount of redundancy on the performance.
Vision based auto inspection system for detecting scratches on the products

In many production systems, the products are inspected by human operators who observe faults with their naked eye while most of the other manufacturing activities are automated. However, manual inspection is slow and yields subjective results. To defeat this problem, image processing based visual control systems have been integrated to the production systems. The visual system performance depends on the robustness of the image processing techniques. Especially, the thresholding technique plays crucial role if you are inspecting scratches on the products. Since utilizing the constant threshold fails in many cases, we have proposed an adaptive thresholding technique based visual inspection system to detect production faults rapidly and efficiently without hampering the manufacturing process. The proposed visual system also includes rotation invariant properties, which is important to get high speed processing.
Nonlinear Kalman filtering of long-baseline, short-baseline, GPS, and depth measurements

Moving ship tomography measures acoustic travel times between transmitters moored above the ocean floor and hydrophones on a cable tethered to a ship. The authors consider a Kalman filter that determines the location of a subarray of the hydrophones near the end of the cable. A long-baseline tracking system, consisting of floating buoys and the ship, acoustically measured the slant range to each hydrophone. The range to orbiting satellites was measured with the Global Positioning System (GPS). A short-baseline acoustic system measured range and direction from the ship to a beacon on the cable, and to each buoy. Depths at various points near the hydrophones were measured using three different pressure sensors. The Kalman filter combines these primary measurements and some supporting measurements to form an estimate of the buoy and hydrophone locations. An iterated correction step is used to adjust for the nonlinearities and an outlier detection scheme to make the filter robust. <<ETX>>
Detection of Concealed Micro-Electronic Devices Using Clustering and Classification of RF Harmonics

This paper proposes an advanced detection scheme for concealed micro-electronic devices using clustering and classification of radio frequency harmonics in order to protect intellectual property rights. In general, if a radio wave with a specific fundamental frequency is propagated from the transmitter of a classifier to a concealed object, the second and the third harmonics will be returned as the radio wave is reflected. Using this principle, we exploit the fuzzy c-means clustering and the -nearest neighbor classification for detecting diverse concealed objects. Simulation results indicate that the proposed scheme can detect electronic devices and metal devices in various learning environments by efficient classification. Furthermore, the proposed scheme can be extended to accumulate learning data of diverse devices for more efficient detection of diverse concealed objects to protect intellectual property rights. Cite this work as: Kwangyul Kim, Jeonghwan Lim, SongKang Kim, Junkyung Cho, and Yoan Shin, "Detection of Concealed Micro-Electronic Devices Using Clustering and Classification of RF Harmonics," Transaction on Electrical and Electronic Circuits and Systems, Vol. 3(1), Pp. 1-5, May, 2013. References: [1] Korea Industrial Technology Association, “A study on the current status of overseas industrial security management and case studies of American companies,” Korea Small and Medium Business Administration R&D Report, Dec. 2009 (in Korean). [2] B. R. Barsumian, T. H. Jones, and C. A. Liter, “Surveillance device detection utilizing nonlinear junction detection and reflectometry,” US Patent #7,212,008, May 2007. [3] R. Xu and D. Wunsch, “Survey of clustering algorithms,” IEEE Trans. Neural Networks , vol. 16, no. 3, pp. 645-678, May 2005. [4] S. Theodoridis and K. Koutroumbas, An Introduction to Pattern Recognition: A MATLAB Approach , Ch. 1-2, pp. 1-78, Academic Press, 2010. [5] R. J. Hathaway and Y. Hu, “Density-weighted fuzzy - means clustering,” IEEE Trans. Fuzzy Syst. , vol. 17, no. 1, pp. 243-252, Feb. 2009. [6] N. Roussopoulos, S. Kelley, and F. Vincent, "Nearest neighbor queries," Proc. ACM SIGMOD 1995 , pp. 71–79, San Jose, USA, May 1995. [7] T. M. Cover and P. E. Hart, “Nearest neighbor pattern classification,” IEEE Trans. Info. Theory , vol. 13, no. 1, pp. 21-27, Jan. 1967.
Implementation and analysis of the decomposition-fusion ECCM technique

In a previous paper, the authors proposed a new general and systematic electronic counter-countermeasure (ECCM) technique called the Decomposition and Fusion (D&F) approach. This ECCM is implemented within the multiple target-tracking framework for protection against range- gate-pull-off (RGPO) and range false target ECM techniques. The original formulation left open the specific multiple target tracking framework. In this paper, we develop a specific implementation of the D&F technique and evaluate it within the Benchmark 2 Problem environment. Simulation results are presented showing the track-loss rejection capabilities and the track accuracy performance of the D&F technique.
The Craft of Prolog

Hacking your program is no substitute for understanding your problem. Prolog is different, but not that different. Elegance is not optional. These are the themes that unify Richard O'Keefe's very personal statement on how Prolog programs should be written. The emphasis in "The Craft of Prolog" is on using Prolog effectively. It presents a loose collection of topics that build on and elaborate concepts learning in a first course. These may be read in any order following the first chapter, "Basic Topics in Prolog, " which provides a basis for the rest of the material in the book.