Miracle-dz/UniFAR-FTUs huggingface dataset:
Demodulation Reference Signal Design and Channel Estimation for LTE-Advanced Uplink

The merits of 3GPP long term evolution (LTE), such as high spectral efficiency, very low latency, support of variable bandwidth, simple architecture, etc, make it the most competitive candidate for the next generation mobile communications standard. In the first release of LTE, only single transmit antenna is supported in the uplink due to its simplicity and acceptable performance. However, in order to keep its current leading position, LTE needs further evolvement (known as LTE-Advanced (LTE-A)) to provide better performance, including a higher uplink spectrum efficiency. Therefore, multiple transmit antennas must be supported in the LTE-A uplink and one important issue is the uplink demodulation reference signal (DMRS) design, which will influence uplink channel estimation accuracy and eventually determine uplink reliability and throughput. In this study we first briefly review the current status of DMRS in LTE uplink and then different DMRS enhancement schemes are investigated for LTE-A uplink multiple-input multiple-output (MIMO) transmission. Also, two-dimensional channel estimation algorithms are provided to realize accurate uplink channel estimation. With computer simulations, the performances of several candidate LTE-A uplink DMRS design schemes are evaluated and compared. Finally some basic conclusions are provided together with the latest standardization progress.
Gate All Around Metal Oxide Field Transistor: Surface Potential Calculation Method including Doping and Interface Trap Charge and the Effect of Interface Trap Charge on Subthreshold Slope

An explicit surface potential calculation method of gate-all-around MOSFET (GAAMOSFET) devices which takes into account both interface trap charge and varying doping levels is presented. The results of the method are extensively verified by numerical simulation. Results from the model are used to find qualitative and quantitative effect of interface trap charge on subthreshold slope (SS) of GAAMOSFET devices. Further, design constraints of GAAMOSFET devices with emphasis on the effect of interface trap charge on device SS performance are investigated.
Automatic generation of data-flow analyzers : a tool for building optimizers

Modern compilers generate good code by performing global optimizations. Unlike other functions of the compiler such as parsing and code generation which examine only one statement or one basic block at a time, optimizers examine large parts of a program and coordinate changes in widely separated parts of a program. Thus optimizers use more complex data structures and consume more time. To generate the best code, optimizers perform not one global transformation, but many in concert. These transformations can interact in unforeseen ways. This dissertation concerns the building of optimizers that are modular and extensible. It espouses an optimizer architecture, first proposed by Kildall, in which each phase is based on a data-flow analysis (DFA) of the program and on an optimization function that transforms the program. To support the architecture, a set of abstractions--flow values, flow functions, path simplification rules, action routines--is provided. A tool called Sharlit turns a DFA specification consisting of these abstraction into a solver for a DFA problem. At the heart of Sharlit is an algorithm called path simplification, an extension of Tarjan's fast path algorithm. Path simplification unifies several powerful DFA solution techniques. By using path simplification rules, compilers writers can construct a wide range of data-flow analyzers, from simple iterative ones, to solvers that use local analysis, interval analysis, or sparse data-flow evaluation. Sharlit frees compiler writers from the details of how these various solution techniques. The compiler writer can view the program representation as a simple flow graph in which each instruction is a node. Data structures to represent basic blocks and other regions are automatically generated. Sharlit promotes modularity by making it possible to build more complex data-flow analyzers from simpler ones. Sharlit promotes extensibility because it is easier to add new flow functions and path simplification rules that represent new kinds of instructions to existing analyzers. A complete optimizer has been built using Sharlit. Measurements showed that this optimizer can compete in code quality with commercial optimizing compilers.
Automatic Recognition Of Facial Expressions In Color Spaces: A Survey

Since the early ninetees, automatic facial expression analysis has become an active research area that finds potential applications in areas such as more engaging human–computer interfaces, talking heads, image retrieval and human emotion analysis. Facial expressions reflect not only emotions, but other mental activities, social interaction and physiological signals. There have been several advances in the past few years in the areas of face detection and tracking, feature extraction mechanisms and the techniques used for expression classification. This paper is a survey of some of the published works since 2001 till date. In this survey, the most prominent automatic facial expression analysis methods and systems presented in the literature are discussed. Facial motion and deformation extraction approaches as well as classification methods are discussed with respect to issues such as face normalization, facial expression dynamics and intensity and also with regard to their robustness. The paper also has a special mention on the 3D facial expression databases.
News Analytics: Framework, Techniques and Metrics

News analysis is defined as the measurement of the various qualitative and quantitative attributes of textual news stories. Some of these attributes are: sentiment, relevance, and novelty. Expressing news stories as numbers permits the manipulation of everyday information in a mathematical and statistical way. (Wikipedia). In this article, I provide a framework for news analytics techniques used in finance. I first discuss various news analytic methods and software, and then provide a set of metrics that may be used to assess the performance of analytics. Various directions for this field are discussed through the exposition.
Report on the application of statistical techniques to the analysis of computer codes

Two types of sampling plans are presented as alternatives to simple random sampling in Monte Carlo studies. These plans are shown to be improvements over simple random sampling with respect to the variance of a class of estimators which includes the sample mean and the sample cumulative distribution function. The partial rank correlation coefficient is presented as a measure of sensitivity. Examples and test cases are included. 14 figures, 5 tables.
RASIONALISASI PERSPEKTIF FILM LAYAR LEBAR BERADAPTASI KARYA SASTRA

Film as one of super important visual media is currently growing in Indonesia. Films will only be meaningful if it meets with the audience. Indonesia's willingness to watch the movie becomes very important. According to the survey the majority of wide screen film lovers , films adapted from literary works such as novels. This research is qualitative research in the field of literary studies and concentrate on the educational value of social psychology. Based on the analysis , it can be concluded that moviegoers are more interested in the film because of adopting novel storyline that often make a good impression, especially on their personality. Literary works such as novels able to be taught and enjoyed also by the presence of the film that this requirement will be educational value. Compared with the films that did not adopt a literary work, lovers of literature are sometimes not more interested in movies with some reason considered quite rational. Differences in the way the story and imagination commercial terms was seen as reducing the spirit of a literary work's title.
Small corpus studies and ELT : theory and practice

1. Preface (by Sinclair, John McH.) 2. Introduction (by Ghadessy, Mohsen) 3. Section I: Corpus analysis: from large to small 4. 1. Large corpora, small corpora, and the learning of "language" (by Beaugrande, Robert de) 5. Section II: Tools for small corpus analysis 6. 2. Using small corpora to investigate learner needs: Two vocabulary research tools (by Nation, Paul) 7. 3. Comparing corpora and identifying key words, collocations, and frequency distributions through the Word Smith Tools suite of computer programs (by Scott, Mike) 8. Section III: Analysing and teaching language variation in genres through small corpora 9. 4. Concordancing as a tool in course design (by Flowerdew, John) 10. 5. Using a small corpus to obtain data for teaching a genre (by Henry, Alex) 11. 6. Small corpora and language variation: Reflexivity across genres (by Bondi, Marina) 12. 7. Investigating and teaching genres using the World Wide Web (by Ooi, Vincent B.Y.) 13. Section IV: Small corpora and the investigation of English structure 14. 8. Classroom use of a systemic functional small learner corpus (by Ragan, Peter H.) 15. 9. Specialised corpus, local and functional grammars (by Barnbrook, Geoff) 16. Section V: Using parallel corpora as a source of classroom data 17. 10. Collecting, aligning and analysing parallel corpora (by Lawson, Ann) 18. 11. Corpus, comparison, culture: Doing the same things differently in different cultures (by Thompson, Geoff) 19. 12. Small corpora and translation: Comparing thematic organization in two languages (by Ghadessy, Mohsen) 20. Section VI: Using learner corpora in ELT 21. 13. The exploitation of small learner corpora in EAP materials design (by Flowerdew, Lynne) 22. 14. Small corpora and teaching writing (by Tribble, Christopher) 23. Name index 24. Subject index
Information retrieval: on-line

This text treats current developments in the design, operation and evaluation of information retrieval systems operating in an on-line, realtime, time-shared, interactive mode. Look for coverage of--characteristics and advantages of on-line systems; equipment; searching techniques; description of existing systems; operating experience; evaluation of on-line systems; indexing and cataloging on-line; on-line support to personal files; and human factors aspects of on-line retrieval systems.
An architecture for rapid retrieval of structured information using speech with application to spoken address recognition

We describe an iterative recognition strategy that can be used to improve vastly the performance of a speech recognition system when the speech pertains to structured information that can be looked up in a database. The framework that we present is designed to extract specific fields of interest from the speech signal during each iteration, query a database using these fields, and thereby construct the hypothesis space for searching during the next iteration. The architecture has been found to be significantly useful in applications such as spoken address recognition where a proof of concept and a demonstration system had been developed. We also present results on a small test set to compare the performance of the described system with the more common baseline approach.
Outlier Detection for Different Applications: Review

Outlier Detection is a Data Mining Application. Outlier contains noisy data which is researched in various domains. The various techniques are already being researched that is more generic. We surveyed on various techniques and applications of outlier detection that provides a novel approach that is more useful for the beginners. The proposed approach helps to clean data at university level in less time with great accuracy. This survey includes the existing outlier techniques and applications where the noisy data exists. Our paper defines critical review on various techniques used in different applications of outlier detection that are to be researched further and they gives a particular type of knowledge based data i.e. more useful in research activities. So where the Anomalies is present it will be detected through outlier detection techniques and monitored accordingly.
Clinical characteristics and prognosis of patients with left ventricular thrombus in East China

Background Left ventricular thrombus (LVT) is a serious complication in patients with left ventricular dysfunction. However, there is still a paucity of data on treatments and prognosis of patients with LVT. This study aims to evaluate the clinical characteristics of patients with LVT and to determine the impact of LVT on the incidence of major adverse cardiovascular events (MACEs) and all-cause mortality. Methods From January 2010 to January 2020, 237 patients diagnosed with LVT at The Second Affiliated Hospital Zhejiang University School of Medicine in East China were retrospectively included. Clinical characteristics, treatments, MACEs, and bleeding events [thrombolysis in myocardial infarction (TIMI) I and II] were collected. MACE is determined as the composite of all-cause mortality, ischemic stroke, acute myocardial infarction (MI), and acute peripheral artery emboli. Results The all-cause mortality rate was 28.3% (89.6% due to cardiovascular death), ischemic stroke 8.4%, MI 3%, peripheral artery emboli 1.7%, and bleeding events (TIMI I and II) 7.6% were found during a median follow-up of 736 days. Total LVT regression occurred in 152 patients (64.1%). Atrial fibrillation [hazard ratio (HR), 3.049; 95% confidence interval (95% CI) 1.264–7.355; p = 0.013], moderate and severe renal function injuries (HR, 2.097; 95% CI, 1.027–4.281; p = 0.042), and left ventricular ejection fraction (LVEF) ≤ 50% (HR, 2.243; 95% CI 1.090–4.615; p = 0.028) were independent risk factors for MACE, whereas the use of β-blocker (HR, 0.397; 95% CI 0.210–0.753; p = 0.005) was its protective factor. Age (HR, 1.021; 95% CI 1.002–1.040; p = 0.031), previous caronary artery bypass grafting (CABG; HR, 4.634; 95% CI 2.042–10.517; p < 0.001), LVEF ≤ 50% (HR, 3.714; 95% CI 1.664–8.290; p = 0.001), and large thrombus area (HR, 1.071; 95% CI 1.019–1.126; p = 0.007) were independent risk factors for increasing all-cause mortality, whereas the use of β-blocker (HR, 0.410; 95% CI 0.237–0.708; p = 0.001) was protective factor. Conclusion This study showed that atrial fibrillation, moderate and severe renal dysfunction, and LVEF ≤ 50% were independent risk factors for MACE; age, previous CABG, LVEF ≤ 50%, and large thrombus area were independent risk factors for all-cause mortality. It was found that the use of β-blockers could improve the prognosis of patient with LVT for the first time. It is recommended that clinicians could be more active in applying patient with LVT with anticoagulants.
Sentiment Classification based on Latent Dirichlet Allocation

Opinion miningrefers to the use of natural language processing, text analysis and computational linguistics to identify and extract the subjective information. Opinion Mining has become an indispensible part of online reviews which is in the present scenario.In the field of information retrieval, a various kinds of probabilistic topic modeling techniques have been used to analyze contents present in a document. A topic model is a generative technique for document. All topic models share the idea that documents are having mixture of topics, and the topic is a probability distribution over words. Recently topic modeling techniques have been used to identify the meaningful review aspects, but existing topic models like Latent Dirichlet Markov Allocation (LDMA), hierarchical aspect sentiment model (HASM) do not identify aspect specific opinion words and also not suitable for shared features. In the proposed system, movie review dataset is collected from the IMDB database and is preprocessed. TF-IDF is calculated for the preprocessed data and result is given to LDA model which is then used to discover both the aspects and aspect specific opinion words. After that CHI value has been determined, SVM classifier is used to classify the topics preferable to each and every document.
Transient Analysis of lossy transmission lines (TOPLine)

Transient Analysis of lossy transmission lines (TOPLine) / Canavero F.G. ; Giachino C. ; Grivet Talocia S. ; Maio I.A. ; Stievano I.S. ELETTRONICO. (2004), pp. 1-2. ((Intervento presentato al convegno XX Riunione Annuale del Gruppo Nazionale di Coordinamento di Elettrotecnica (ET2004) tenutosi a Salerno, Italy nel June 16-19, 2004. Original Transient Analysis of lossy transmission lines (TOPLine)
Development and validation of accelerometer-based activity classification algorithms for older adults: A machine learning approach

Purposes: 1) To compare activity type recognition rates of random forest and support vector machine algorithms trained on laboratory (RFLab and SVMLab) versus free-living accelerometer data (SVMFL and RFFL) in free-living older adults, 2) to examine the correlation between locomotion speed predicted by an algorithm developed in Study 1 (RFspeed) and speed in the 400 m walk test. Methods: Fifteen participants from Study 1 wore three ActiGraph GT3X+ activity monitors (dominant hip, wrist, and ankle) in freeliving conditions and were directly observed for 2-3 h. The RFLab and SVMLab algorithms were applied to hip, wrist, and ankle accelerometer data for classification of activity type in 20 s intervals. Free-living accelerometer data were used to train SVMFL and RFFL algorithms for classification of activity type. Direct observation data were used to compute percent correct classification for activity type by the different algorithms. The best algorithm was used to predict locomotion time and the RFspeed algorithm was applied to predict locomotion speed. A Pearson product-moment correlation was used to determine the association of predicted with actual locomotion speed (400 m walk speed). Results: Overall classification accuracy using 20 s intervals for the lab-based algorithms was between 49% (wrist) to 55% (ankle) for the SVMLab algorithms, and 49% (wrist) to 54% (ankle) for RFLab algorithms. Overall classification accuracy of SVMFL and RFFL algorithms ranged from 58% (wrist) to 69% (ankle) and from 61% (wrist) to 66% (hip and ankle), respectively. Using 30 s intervals improved classification accuracy up to 71%
The High Performance Fortran Handbook

From the Publisher: High Performance Fortran (HPF) is a set of extensions to Fortran expressing parallel execution at a relatively high level. For the thousands of scientists, engineers, and others who wish to take advantage of the power of both vector and parallel supercomputers, five of the principal authors of HPF have teamed up here to write a tutorial for the language. There is an increasing need for a common parallel Fortran that can serve as a programming interface with the new parallel machines that are appearing on the market. While HPF does not solve all the problems of parallel programming, it does provide a portable, high-level expression for data- parallel algorithms that brings the convenience of sequential Fortran a step closer to today's complex parallel machines.
Review and Analysis of Multifarious Spatial Domain Steganography Techniques

-Steganography is fetching attraction because of rapid growth & use of internet as a communication medium. A steganography is a technique of invisible or secret communication. In steganography the secret message can be hidden into a cover_media which results in the stego_media, so that no one can realize its subsistence except the sender & receiver. There are various medium used as a cover such as image, audio, video, protocol, DNA etc. But image is mostly used as a cover media. There are several type and techniques of steganography, each having its own confines and rewards. In this paper we have explicated & analyzed the different spatial domain steganography techniques.
Visual analysis of high DOF articulated objects with application to hand tracking

Measurement of human hand and body motion is an important task for applications ranging from athletic performance analysis to advanced user interfaces. Commercial human motion sensors are invasive, requiring the user to wear gloves or targets. This thesis addresses noninvasive real-time 3D tracking of human motion using sequences of ordinary video images. Other computer vision systems have demonstrated real-time tracking of a single rigid object in six degrees-of-freedom (DOFs). Articulated objects like the hand present challenges to existing rigid-body tracking algorithms: a large number of DOFs (27 for the hand), nonlinear kinematic constraints, and complex self-occlusion effects. This thesis presents a novel local tracking framework based on explicit kinematic models that overcomes these obstacles. Kinematic models from robotics are used in this work to represent skeletal constraints and predict self-occlusions, which occur when one link of the object obscures the view of another. In local tracking, images are acquired at a high sampling rate and the linearized kinematic model is used to estimate the small motions between successive frames. Self-occlusion is modeled by a set of overlapping templates which are ordered by their visibility to the camera. This layered representation is constructed automatically from the kinematic model and used to constrain image interpretation. This thesis presents new experimental results for vision-based hand tracking. A real-time tracking system called DigitEyes was developed and tested in two experiments. First, a hand was tracked using a 27 DOF model and two cameras. Second, hand tracking with a single camera provided the input for a 3D mouse user-interface. Self-occluding hand motion was tracked off-line in a third experiment. These results illustrate the effectiveness of explicit kinematic models in constraining the interpretation of hand intensity images and analyzing self-occluding motion.