Miracle-dz/UniFAR-FTUs huggingface dataset:
Incorporating visual attention models into video quality metrics

A recent development in the area of image and video quality consists of trying to incorporate aspects of visual attention in the design of visual quality metrics, mostly using the assumption that visual distortions appearing in less salient areas might be less visible and, therefore, less annoying. This research area is still in its infancy and results obtained by different groups are not yet conclusive. Among the works that have reported some improvement, most use subjective saliency maps, i.e. saliency maps generated from eye-tracking data obtained experimentally. Besides, most works address the image quality problem, not focusing on how to incorporate visual attention into video signals. In this work, we investigate the benefits of incorporating saliency maps obtained with visual attention. In particular, we compare the performance of four full-reference video quality metrics with their modified versions, which had saliency maps incorporated to the algorithm. For comparison proposes, we have used a database of subjective salience maps.
Digital Perspective Correction For Cylindrical Holographic Stereograms

This paper discusses digital perspective correction in the multiplex hologram,also known as Cross hologram or white light cylindrical holographic stereogram. It presents digital analogues of previously reported optical methods, and demonstrates the digital implementation of Benton's method. It introduces a non-linear remapping of the input views to compensate for a non-uniform color viewing position. Simulation results are included on the relative accuracy of different algorithms. Digital correction can be applied to both real and artificial objects such as computed tomography (CT) data.
Embodied Interfaces for Interactive Percussion Instruction

For decades, the application of technology to percussion curricula has been substantially hindered by the limitations of conventional input devices. With the need for specialized percussion instruction at an all-time high, investigation of this domain can open the doors to an entirely new educational approach for percussion. This research frames the foundation of an embodied approach to percussion instruction manifested in a system called Percussive. Through the use of body-scale interactions, percussion students can connect with pedagogical tools at the most fundamental level—leveraging muscle memory, kinesthetics, and embodiment to present engaging and dynamic instructional sessions. The major contribution of this work is the exploration of how a system which uses motion-sensing to replicate the experiential qualities of drumming can be applied to existing pedagogues. Techniques for building a system which recognizes drumming input are discussed, as well as the system’s application to a successful contemporary instructional model. In addition to the specific results that are presented, it is felt that the collective wisdom provided by the discussion of the methodology throughout this thesis provides valuable insight for others in the same area of research.
Non-Intrusive Electric Appliances Load Monitoring System-Experiment for Real Household-

This paper presents applying results of four estimation algorithms of non-intrusive monitoring system for real household. We conclude that all algorithms have practicable ability. 1) support vector machine(SVM): SVM was used to estimate ON/OFF states for fluorescent and refrigerator. SVM has the performance equivalent to best performance of sigmoid function networks(SFN). However, SVM has high estimating ability constantly. 2) RBF networks(RBFN): RBFN was used to estimate power consumption for air conditioner. RBFN has the performance equivalent to best performance of SFN. However, RBFN has high estimating ability constantly. 3) step change detection method(SCD): SCD was used to estimate ON/OFF states and power consumption for IH cooking range. SCD does not need the necessary learning process for SFN and has higher estimating ability than SFN. 4) spectrum reference method(SRM): SRM was used to estimate working conditions for rice cocker and washing machine. SRM is able to estimate these working conditions that cannot be estimated by earlier methods.
Using data clustering to improve cleaning performance for flash memory

Flash memory offers attractive features for storage of data, such as non‐volatility, shock resistance, fast access speed, and low power consumption. However, it requires erasing before it can be overwritten. The erase operations are slow and consume comparatively a great deal of power. Furthermore, flash memory can only be erased a limited number of times. To overcome hardware limitations, we use the non‐in‐place update mechanism that requires a cleaner to reclaim space occupied by obsolete data. To improve cleaning performance and prolong flash memory lifetime, we propose a new data reorganization method. By this method, data in flash memory are dynamically classified and clustered together according to their accessing frequencies. Experimental results show that this clustering technique significantly improved the cleaning performance for a variety of cleaning algorithms. The number of erase operations performed is greatly reduced and flash memory lifetime is prolonged. Even wearing is ensured as well. Copyright © 1999 John Wiley & Sons, Ltd.
On the Network Characteristics of the Google’s Suggest Service

This paper investigates application- and transport-level characteristics of Google's interactive Suggest service by analyzing a passively captured packet trace from a campus network. In particular, we study the number of HTTP GET requests involved in user search queries, the inter-request times, the number of HTTP GET requests per TCP connection, the number of keyword suggestions that Google's Suggest service to users, and how often users utilize these suggestions in enhancing their search queries. Our findings indicate, for example, that nearly 40% of Google search queries involve five or more HTTP GET requests. For 36% of these requests, Google returns no suggestions, and 57% of the time users do not utilize returned suggestions. Furthermore, we find that some HTTP characteristics such as inter-request generation time for interactive search application are different from that of traditional Web applications. These results confirm the findings of other studies that examined interactive applications and reported that such applications are more aggressive than traditional Web applications.
HEPDOOP: High-Energy Physics Analysis using Hadoop

We perform a LHC data analysis workflow using tools and data formats that are commonly used in the "Big Data" community outside High Energy Physics (HEP). These include Apache Avro for serialisation to binary files, Pig and Hadoop for mass data processing and Python Scikit-Learn for multi-variate analysis. Comparison is made with the same analysis performed with current HEP tools in ROOT.
Human Interactions With a Robot That Recognizes Differences Between Fields of View

It is likely that in the near future, human-symbiotic robots will share people's living spaces. Since there are many objects that can cause visual occlusion in these environments, situations in which a robot cannot see an object due to occlusion whereas a user can, and vice versa, will often occur. In such situations, ideally the human-symbiotic robot should be able to interact with the user while taking into consideration the differences between their fields of view. We anticipate that such a “considerate” robot will be friendlier and provide more pleasant interactions with users. In this paper, we aim to test this anticipation. First, we propose a robot that can estimate a user's and its own fields of view and thus behave appropriately due to being aware of the difference between their perceptions. The robot estimates the orientation of the user's head and the structure of its surrounding environment using a stereo camera. By combining these results, it can inform itself of the user's and its own fields of view: that is, what they can see and what they cannot see. Next, we carry out experimental subjective evaluations of the impressions that people gain during interaction with the proposed robot. Participants who observe the interactions are asked to subjectively evaluate their impressions of the robot's behaviors. The experimental results show that the proposed robot, which can guess what the user can see and understand the differences between their different viewpoints, is perceived as more “companionable. ” This ability is likely to be one of the basic requirements for achieving interactions that people interpret as “friendly” with robots and other intelligent systems.
A finite volume model on unstructured meshes and application in computing two dimensional flows

Some methods in approximation of fluxes between adjacent cells have been proposed in context of the finite volume technique on unstructured meshes. A shallow water model has been developed for testing the proposed methods. The third order Adams-Bashforth scheme is used in integrating the governing equations. A filter is designed to remove spurious waves. The model is tested on unstructured triangular meshes with some examples in literature. Tóm tắt. Bài báo tr̀ınh bày mô. t số kỹ thuâ. t xấp xı’ thông lu.o. ng giũ. a các nốt trên lu. ́o.i phi cấu trúc trong kỹ thuâ. t thê’ t́ıch hũ. u ha.n. Các phu.o. ng pháp này du.o. c thu. ’ nghiê. m vào mô. t mô h̀ınh nu. ́o.c nông hai chiè̂u trên lu. ́o.i tam giác phi cấu trúc. Mô h̀ınh này su. ’ du.ng so. dồ t́ıch phân thò. i gian Adams-Bashforth bâ. c ba. Mô. t bô. lo.c cũng du.o. c du.a vào mô h̀ınh nhà̆m loa.i bo’ các sóng nhiẽ̂u sinh ra trong quá tr̀ınh t́ıch phân. Các bài toán mẫu sẽ du.o. c su. ’ du.ng nhằm kiê’m tra kỹ năng mô pho’ng cu’a mô h̀ınh.
Increasing the performance of MAP (multi-angled parallelism) erosion-dilation for feature extraction through unary/binary operations

The multiangled parallelism (MAP) concept, which defines directional operations with directional elements, is discussed. To achieve the MAP operation, a parallel architecture in which MAP operations are summarized as single or cyclic, unary or binary, logical operations is proposed. The hardware design is simulated using an existing image processor. It is demonstrated that geometric figures can be extracted from a topographical map by first extracting the core features and then expanding it gradually. <<ETX>>
Classification of RNA secondary structure

In presented paper the algorithms to to assign the RNA molecule to the appropriate category is presented. The new computer program was implemented in thin client architecture. The classification using different machine learning algorithms were performed on data retrieved from the database storing RNA secondary structures and on secondary structures calculated by prediction algorithms. We carried out the studies to compare the effectiveness and speed of the implemented algorithms.
Statistical Analysis of Circular Data

Preface 1. The purpose of the book 2. Survey of contents 3. How to use the book 4. Notation, terminology and conventions 5. Acknowledgements Part I. Introduction: Part II. Descriptive Methods: 2.1. Introduction 2.2. Data display 2.3. Simple summary quantities 2.4. Modifications for axial data Part III. Models: 3.1. Introduction 3.2. Notation trigonometric moments 3.3. Probability distributions on the circle Part IV. Analysis of a Single Sample of Data: 4.1. Introduction 4.2. Exploratory analysis 4.3. Testing a sample of unit vectors for uniformity 4.4. Nonparametric methods for unimodal data 4.5. Statistical analysis of a random sample of unit vectors from a von Mises distribution 4.6. Statistical analysis of a random sample of unit vectors from a multimodal distribution 4.7. Other topics Part V. Analysis of Two or More Samples, and of Other Experimental Layouts: 5.1. Introduction 5.2. Exploratory analysis 5.3. Nonparametric methods for analysing two or more samples of unimodal data 5.4. Analysis of two or more samples from von Mises distributions 5.5. Analysis of data from more complicated experimental designs Part VI. Correlation and Regression: 6.1. Introduction 6.2. Linear-circular association and circular-linear association 6.3. Circular-circular association 6.4. Regression models for a circular response variable Part VII. Analysis of Data with Temporal or Spatial Structure: 7.1. Introduction 7.2. Analysis of temporal data 7.3. Spatial analysis Part VIII. Some Modern Statistical Techniques for Testing and Estimation: 8.1. Introduction 8.2. Bootstrap methods for confidence intervals and hypothesis tests: general description 8.3. Bootstrap methods for circular data: confidence regions for the mean direction 8.4. Bootstrap methods for circular data: hypothesis tests for mean directions 8.5. Randomisation, or permutation, tests Appendix A. Tables Appendix B. Data sets References Index.
Selectivity in Reduction of Natural Furanoheliangolides with Stryker′s Reagent.

Natural sesquiterpene lactones (I) and (IV), and the ether derivatives (VII) and (X) are chemoselectively reduced through a biomimetic pathway affording eremantholides (II) and (V), and the corresponding derivatives (VIII) and (XI).
Joint motion monitoring by accelerometers set at both near sides around the joint

In this paper we examined a joint motion monitoring method utilizing accelerometers to monitor upper limb motion in daily activities. In this method two accelerometers are set at both near sides around the joint. The difference of these sensor outputs depends on the joint angle because centrifugal and turning acceleration occurring in the rotation around the joint can be neglected. We confirmed the validity of this method in the measurement of elbow and shoulder motion.
A monolithic miniaturized programmable implant for neuromuscular stimulation

Presents a new implantable microstimulator system for neuromuscular stimulation. The implantable circuitry is externally controlled and powered by a single encoded radio frequency carrier and may have up to 16 independently controlled bipolar channels. The implant system is adaptable to the patient's needs and to future development in stimulation algorithms, without changing the implant. The microstimulator is able to generate a wide range of stimulation patterns including selective stimulation waveforms. An optical telemetry link transmits the state of patient to the external controller. The chip has been designed for structural testability and uses circuit techniques to reduce power consumption and insure long-term stability. The implantable system can be used to any neuromuscular applications. If is intended to restore normal bladder functions (retention and incontinence) to spinal cord injured (SCI) patients.
A New Probabilistic Dependency Parsing Model for Head-Final, Free Word Order Languages

SUMMARY We propose a dependency parsing model for head-final, variable word order languages. Based on the observation that each word has its own preference for its modifying distance and the preferred distance varies according to surrounding context of the word, we define a parsing model that can reflect the preference. The experimental result shows that the parser based on our model outperforms other parsers in terms of precision and
Marginalised behaviour: digital annotations, spatial encoding and the implications for reading comprehension

Within large scale educational assessment agencies in the UK, there has been a shift towards assessors marking digitally scanned copies rather than the original paper scripts that were traditionally used. This project uses extended essay examination scripts to consider whether the mode in which an essay is read potentially influences the judgements made about it, employing qualitative and quantitative data‐gathering approaches to focus on the annotation practices of readers who are assessing extended essays, and to explore whether this might be affected by mode. The project also gathers evidence about the spatial encoding ability of these readers to suggest that mode‐related influences on annotation might influence the ability of readers to comprehend fully the material being read. Examiners had less spatial awareness about the location of script features on screen than on paper; however, annotating on screen might link to both the provision of appropriate annotations and the relative ease with which these are deployed whilst reading. There was also evidence that on‐screen annotation could contribute to the development of good mental representations of texts on screen.
Chinese New Word Identification Using N-Gram and PPM Models

New word identification is one of the difficult problems of the Chinese information processing. This paper presents a new method to identify new words. First of all, the text is segmented using N-Gram; then PPM is used to identify the new words which are in the text; finally, the new identified words are added to update the dictionary using LRU. Compared with three well-known word segmentation systems, the experimental results show that this method can improve the precision and recall rate of new word identification to a certain extent.
A comparison of part of speech taggers in the task of changing to a new domain

Part-of-speech tagging in real-world applications is performed on text in domains which are different from the publicly available large training data sets. The two most successful part-of-speech taggers are trained on the Wall Street Journal corpus, a corpus of millions of words. We compare their performance on a test set from a different domain-astronomy-from documents that are available on the World Wide Web. The Maximum Entropy Part of Speech Tagger (MXPOST) and the Transformation-Based Learning Tagger are well-known and widely used in language research and development systems. The two taggers were tested in several modes: (1) after training on the Wall Street Journal corpus only, (2) after training on only a small body of text from our astronomy domain, (3) with and without an auxiliary lexicon derived from many astronomy-related Web documents, and (4) after incremental training-that is, having been trained on the Wall Street Journal, with additional training from the specific domain. One conclusion from the experiment is that different taggers exhibit different biases when trained on the same data.
Medical image compression using cubic spline interpolation with bit-plane compensation

In this paper, a modified medical image compression algorithm using cubic spline interpolation (CSI) is presented for telemedicine applications. The CSI is developed in order to subsample image data with minimal distortion and to achieve compression. It has been shown in literatures that the CSI can be combined with the JPEG algorithms to develop a modified JPEG codec, which obtains a higher compression ratio and a better quality of reconstructed image than the standard JPEG. However, this modified JPEG codec will lose some high-frequency components of medical images during compression process. To minimize the drawback arose from loss of these high-frequency components, this paper further makes use of bit-plane compensation to the modified JPEG codec. The bit-plane compensation algorithm used in this paper is modified from JBIG2 standard. Experimental results show that the proposed scheme can increase 20~30% compression ratio of original JPEG medical data compression system with similar visual quality. This system can reduce the loading of telecommunication networks and is quite suitable for low bit-rate telemedicine applications.
Robust detection of facial features by generalized symmetry

Locating facial features is crucial for various face recognition schemes. The authors suggest a robust facial feature detector based on a generalized symmetry interest operator. No special tuning is required if the face occupies 15-60% of the image. The operator was tested on a large face data base with a success rate of over 95%. <<ETX>>
Modeling of discrete event systems using finite state machines with parameters

Control theories for discrete event systems modeled as finite state machines have been well developed over the years in addressing various fundamental control issues. However, modeling in finite state machines has long suffered the potential problem of state explosion that renders it unsuitable for many practical applications. In this paper, we propose an approach that appends finite sets of parameters to finite state machines in modeling discrete event systems. We show with an example that many discrete event applications can then be represented efficiently in this approach and the state explosion problem can then been mitigated.
Cyclopalladated Ferrocenylimines: Efficient Catalysts for Homocoupling and Sonogashira Reaction of Terminal Alkynes.

Abstract A novel pathway for homocoupling of terminal alkynes has been described using cyclopalladated ferrocenylimine 1 or 2 /CuI as catalyst in the air. This catalytic system could tolerate several functional groups. The palladacycle 2 in the presence of n -Bu 4 NBr as an additive could be applied to Sonogashira cross-coupling reaction of aryl iodides, aryl bromides, and some activated aryl chlorides with terminal alkynes under amine- and copper-free conditions, mostly to give moderate to excellent yields.
Fuzzy talent selection with multicriteria and multilevel decision making

The basic concept of fuzzy majority is used in developing the new methods for multicriteria and multilevel decision making problems. The precedence ordering criterion can help us to derive a preference ordering relational matrix which indicates the relative important degrees of each candidate to the others. We apply these new conjunct methods to solve the one-layer decision tree multilayer decision making problem, and the extended multilevel decision tree. Simulation results from various selection examples are presented to verify the applicability of the proposed model to the real world problems.
A Novel Collaborative Optimization Algorithm for Solving TSP

For the premature convergence and initial pheromone distribution problem of the basic ACO algorithm, PSO algorithm and chaos optimizing strategy are introduced into the ant colony algorithm in order to propose a novel collaborative optimization (CPACO) algorithm based on the collaboration theory. The first, the CPACO algorithm divides the ant colony into several subgroups, and the parameters of the subgroup are regarded as the particles. Then these advantages of PSO algorithm and chaos optimization strategy are fully utilized to optimize these parameters of the ACO algorithm in order to obtain the optimal values of these parameters. And the pheromone exchange operation is introduced into the subgroup. In order to validate the performance of the CPACO algorithm, the TSP problems are selected in here. The simulation results show that the proposed CPACO algorithm has better optimization performance than the traditional ACO algorithm.
Fuzzy-neural control theory applied to task-oriented proactive seamless migration application

The task-oriented proactive seamless migration is one of difficult problems to be solved in pervasive computing paradigm. Apparently, this function of seamless mobility is suitable for mobile web-based application. But when seamless migration for computing task of application is realised on PC, laptop, or PDA, there are several difficult problems to be solved, such as how to supply the proactive/attentive service for web-based worker. In order to realise e-application based on proactive seamless migration, we design and improve relative fuzzy-neural control approaches. Generally, the network can be classified into two. One is that fuzzy logic reasoning is completed by fuzzy weight in neural system. The other is that the input data must be fuzzified in the first or second level, but not weight. We discuss and study the second sort fuzzification in this paper. For proactive decision, fusion method based on fuzzy-neural control can make web-based application system keep advantage of fuzzy logic system and remain adaptive optimum in proactive/attentive service. The correctness and validity of our new approach have been tested.