Miracle-dz/UniFAR-FTUs huggingface dataset:
Scheduling Over Nonstationary Wireless Channels With Finite Rate Sets

We consider a wireless basestation transmitting high-speed data to multiple mobile users in a cell. The channel conditions between the basestation and the users are time-varying and user-dependent. Our objective is to design a scheduler that determines which user to schedule at each time step. Previous work on this problem has typically assumed that the channel conditions are governed by a stationary stochastic process. In this setting, a popular algorithm known as Max-Weight has been shown to have good performance. However, the stationarity assumption is not always reasonable. In this paper, we study a more general worst-case model in which the channel conditions are governed by an adversary and are not necessarily stationary. In this model, we show that the nonstationarities can cause Max-Weight to have extremely poor performance. In particular, even if the set of possible transmission rates is finite, as in the CDMA 1xEV-DO system, Max-Weight can produce queue sizes that are exponential in the number of users. On the positive side, we describe a set of tracking algorithms that aim to track the performance of a schedule maintained by the adversary. For one of these tracking algorithms, the queue sizes are only quadratic. We discuss a number of practical issues associated with the tracking algorithms. We also illustrate the performance of Max-Weight and the tracking algorithms using simulation
A Multi-query Strategy forContent-based Image Retrieval

Content-Based Image Retrieval (CBIR) leads a central role in the multimedia database. The traditional CBIR is often established on single-query image method. However, multi-query has been applied to capture information more precisely in CBIR. There are many applications are interesting on the multi-query. For example, a registered 3D-trademark has different angles images for recognition. A stereo image is constituted by two images from different viewpoint. A set of images helps to represent the scene or trademark. Multi-query strategy will be a suitable mechanism for the retrieval relevant 3D-trademark or stereo image in CBIR. Each image in multi-query has its visual representation in user's respect and major low-level features. How to integrate multi-query properly in the query processing is an important issue. This study proposes Multi-Query Image Retrieval (MQIR) to support multi-query and low-level feature integration. The relevant images are selected based on user's query preference in multi-query. Experimental results present that the proposed approach is more accurate to improve retrieval performance and provides better retrieval results. The proposed multi-query approach was provided to help the query processing in CBIR system.
Combined principal component preprocessing and n‐tuple neural networks for improved classification

We present a combined principal component analysis/neural network scheme for classification. The data used to illustrate the method consist of spectral fluorescence recordings from seven different production facilities, and the task is to relate an unknown sample to one of these seven factories. The data are first preprocessed by performing an individual principal component analysis on each of the seven groups of data. The components found are then used for classifying the data, but instead of making a single multiclass classifier, we follow the ideas of turning a multiclass problem into a number of two‐class problems. For each possible pair of classes we further apply a transformation to the calculated principal components in order to increase the separation between the classes. Finally we apply the so‐called n‐tuple neural network to the transformed data in order to give the classification system non‐linear capabilities, and all derived two‐class models are combined to facilitate multiclass classification. Validation results show that the combined scheme is superior to the individual methods. Copyright © 2000 John Wiley & Sons, Ltd.
Open, web-based internationalization and localization tools

As many software applications have moved from a desktop software deployment model to a Software-as-a-Service (SaaS) model so we have seen tool vendors in the language service industry move to a SaaS model, e.g., for web-based Computer Assisted Translation (CAT) tools. However, many of these offerings fail to take full advantage of the Open Web Platform, i.e., the rich set of web browser-based APIs linked to HTML5. We examine the interoperability landscape that developers of web-based translation tools can benefit from, and in particular the potential offered by the open metadata defined in the W3C’s (World Wide Web Consortium) recent Internationalization Tag Set v2.0 Recommendation. We examine how this can be used in conjunction with the XML Localisation Interchange File Format (XLIFF) standardized by OASIS to exchange translation jobs between servers and Javascript-based CAT tools running in the web browser. We also explore how such open metadata can support activities in the multilingual web processing chain before and after translation.
Use of Differential Scanning Calorimetry (DSC) to Study the Thermodynamics of DNA-Based Interactions and Nucleic Acid-Based Therapeutics

In the 1950’s, the research findings of James Watson, Francis Crick, Rosalind Franklin, and Maurice Wilkins led to the discovery of the deoxyribonucleic acid (DNA) double-helix conformation [1,2]. With DNA at their core, many nucleic acid based assays are used in pharmaceutical, biochemistry, biotechnology, molecular biology, target-based drug design, and other DNA-based technologies [3-7]. In addition, DNA is the molecular target of numerous anti-tumor drugs, anti-viral drugs, and several anti-bacterial agents [8-10]. Historically there have been several approaches in developing some pharmacological and therapeutic agents that interfere with DNA synthesis [8,11]. Since the therapeutic effects of many DNA-binding interactions correlate with thermodynamic profiles of the resulting complexes, elucidation of thermodynamic parameters of such interactions are important in nucleic acid-based therapeutics [12,13]. Differential Scanning Calorimetry (DSC), which provides unique complementary information for nucleic acids, modified nucleic acids, and nucleic acid-ligand interactions, is a powerful method in obtaining thermodynamic parameters. DSC is a direct, model-independent measurement tool that complements, structural and bonding information obtained by various physicochemical methods [13-15]. This review is designed to give the reader a greater understanding of the applications of DSC in DNA-based therapeutics. While this review focuses on calorimetry studies of DNA-based complexes, DSC applications in RNAs have been reviewed elsewhere [16-18].
Classifying Sentiment Based on LDA Model

Online reviews as a new textual domain offer a unique proposition for sentiment analysis. Their short document length suggests any sentiment they contain is compact and explicit. Although supersized methods have obtained good results, a large amount of corpus should be trained beforehand. Recently, topic models have been introduced for the simultaneous analysis for sentiment in the document. However, the LDA model makes the assumption that, given the parameters the words in the document are all independent. It obviously isnt the case. The words in the document express the sentiment of the author. This paper proposes a model to solve the problem. We assume that the sentiments are related to the topic in the documents. A sentiment layer is added to the LDA model to improve it. Experimental result in the dataset demonstrates the advantage of the proposed model.
A fast supervised-learning algorithm for large, multilayered neural networks

A method for training multilayered neural networks that uses genetic-algorithm techniques is discussed. Tests show that this method, called GenLearn, is significantly faster than methods that use the generalized delta rule (GDR). GenLearn also has the advantage that, unlike the GDR, it can escape local minima in its search of weight space. In a feedforward, three-layered neural net, the search for an appropriate first-layer weight matrix can be thought of as a search for powerful internal representations of the input data. GenLearn, in searching for the most fit hidden neurons, searches for a globally-optimal internal representation. The hidden neurons that are least fit do not survive and are replaced. Thus, GenLearn is based on survival of fittest hidden neurons. The biggest advantage of the GenLearn procedure over the GDR in training three-layered neural nets is that it scales up to large neural networks much better. <<ETX>>
Web-Assisted Courses for Business Education: An Examination of Two Sections of Principles of Marketing

This research investigates student responses to two technologically different teaching methods for two sections of a Principles of Marketing course. A traditional method of teaching using lectures, in-class discussions, assignments, and exams is compared to a “Web-assisted” method in which 7 of the 14 class sessions met asynchronously online. Overall, students were more satisfied with the traditional course, preferred the traditional format, and felt the course was more effective in developing their skills and course knowledge. In addition, students in the traditional class felt that the course helped them develop their skills, including team building, critical thinking, oral and written communications, global perspective, and social interaction. Student performance on a comprehensive final exam was not, however, significantly different between the two sections. Implications for those considering such hybrid courses are provided for both faculty and administration.
An Improved Method for Design of Recursive Digital Filters Using Optimization

Abstract With the increased capability of today′s personal computers (PC) and software packages, it often is advantageous to formulate engineering problems in such a way as to take full advantage of these resources. In this paper a new approach to recursive filter design is presented which takes advantage of a popular spreadsheet program and a simple formulation of an optimization problem. No code must be written other than the formula definitions in a spreadsheet. Explicit derivatives are not needed and full interaction with the optimization process is possible, including graphical information. Results are given for an eighth-order filter and these are compared to previously published designs.
Pyramid multiresolution classifier for online large vocabulary Chinese character recognition

A pyramid classifier is proposed for large vocabulary Chinese characters, which at first uses low resolution features to roughly classify the input character, and then used higher resolution features to make finer classification stage by stage. In addition to the rule- based preclassification, there are three stages to achieve recognition. The number of candidate categories is reduced step by step. We use one thousand categories of Chinese characters for experiments. Simulation results show that this classifier can recognize the input character with 93.1% and 90% accuracy on the training set and the test set respectively.
Anatomical-Functional Correlative Analysis Of The Human Brain Using Three Dimensional Imaging Systems

Quantitative interpretation of functional images (PET or SPECT) is hampered by poor spatial resolution, low counting statistics and, for many tracers, low contrast between different brain structures of interest. Further, normal tracer distributions can be severely distorted by such gross pathologies as stroke, tumor and dementia. Hence, the complementary anatomical information provided by CT or MRI is essential for accurate and reproducible regional analysis of functional data. We have developed methods for the three-dimensional integration and simultaneous display of image volumes from MRI and PET. PET data was collected from an older Therascan 3-slice scanner with 12 mm resolution and a 15-slice Scanditronix PC-2048 system having 5-6 mm resolution in each dimension. MRI data was obtained from a Philips 1.5 Tesla Gyroscan scanner. The image volumes were loaded into a PIXAR 3-D image computer for simultaneous display. A general algorithm for finding the optimal transformation between two ensembles of equivalent points was implemented and investigated through simulation studies. Using a locally-developed 3-D image/graphics analysis package, equivalent points in the two image volumes were identified, either manually or via an adjustable computerized volume-of-interest (VOI) atlas. The MRI data were then re-sampled along planes parallel to the PET planes and the two volumes overlaid using opacity-weighted composition. Arbitrary oblique planes through the two volumes were obtained in interactive sessions.
The effects of memory latency and fine-grain parallelism on Astronautics ZS-1 performance

The performance of the Astronautics ZS-1, a decoupled access/execute (DAE) processor, is examined. The CPU is composed of two subsystems: an access processor, which handles address generation and fixed-point operations; and an execute processor, which handles floating-point operations. These two systems communicate through a network of queues and operate in a fairly decoupled manner. This architecture exhibits a form of fine-grain parallelism, called slip, that improves performance. Some performance bounds for the ZS-1 are developed. A simple count of resource usage is sufficient to establish a good upper bound on performance for most vector loops. A dependence graph is used to form another bound that is particularly useful for nonvector loops. This two-bound model accounts for compiler characteristics, such as loop unrolling, and for hardware characteristics, such as memory latency. This model is applied to the first 12 Livermore loops and compared to simulation results for a variety of memory systems. This comparison indicates how well the ZS-1 tolerates increased memory latency as a function of slip and provides insights regarding application codes, architectures, and compiler capabilities. <<ETX>>
A Novel Task Scheduling Approach for Reducing Energy Consumption of MapReduce Cluster

ABSTRACT In recent years, data processing technologies like MapReduce in cloud computing have been widely used. However, the problem of high energy consumption (EC) is an obstacle for further development of cloud computing. We believe that EC could be reduced not only by hardware reinforcement but also by software improvement, especially, by energy-aware task scheduling. In this paper, the Best resources assignment model (Bram) is proposed. On this basis, a scheduling approach, concerning resource usage of nodes and different kinds of resource intensive tasks running on them, is proposed to avoid resource idleness, and then reduce energy consumption. The experimental results show that the new method could reduce the energy consumption of MapReduce cluster.
Development of Reading and Spelling Finnish From Preschool to Grade 1 and Grade 2

This study had two aims: first, to investigate how emerging reading and spelling are interlinked when children move up from preschool to primary school and, second, to examine the antecedents of these skills. The study is part of the Jyvaskyla Entrance into Primary School Study in which 196 children 5 to 6 years of age were followed up every half a year during their transition from preschool to Grade 1 and Grade 2. The results show, first, that reading skills at the end of preschool and Grade 1 predicted subsequent spelling skills and, second, that the level of spelling skills at the beginning of preschool predicted the level of reading skills at the end of the preschool year and at the end of Grade 1. These results suggest that emerging reading and spelling form a recursive developmental pattern. The results show further that phonological awareness predicts reading and spelling in preschool, whereas letter knowledge contributes to both skills during Grade 1.
Short Text Classification Based on Improved ITC

The long text classification has got great achievements, but short text classification still needs to be perfected. In this paper, at first, we describe why we select the ITC feature selection algorithm not the conventional TFIDF and the superiority of the ITC compared with the TFIDF, then we conclude the flaws of the conventional ITC algorithm, and then we present an improved ITC feature selection algorithm based on the characteristics of short text classification while combining the concepts of the Documents Distribution Entropy with the Position Distribution Weight. The improved ITC algorithm conforms to the actual situation of the short text classification. The experimental results show that the performance based on the new algorithm was much better than that based on the traditional TFIDF and ITC.
VLSI design of lossless frame recompression using multi-orientation prediction

Pursuing an experience of high-end visual quality drives human to demand a higher display resolution and a higher frame rate. Hence, a lot of powerful coding tools are aggregated together in emerging video coding standards to improve coding efficiency. This also makes video coding standards suffer from two design challenges: heavy computation and tremendous memory bandwidth. The first issue can be properly solved by a careful hardware architecture design with advanced semiconductor processes. Nevertheless, the second one becomes a critical design bottleneck for a modern video coding system. In this article, a lossless frame recompression using multi-orientation prediction technique is proposed to overcome this bottleneck. This work is realised into a silicon chip with the technology of TSMC 0.18 µm CMOS process. Its encoding capability can reach full-HD (1920 × 1080)@48 fps. The chip power consumption is 17.31 mW@100 MHz. Core area and chip area are 0.83 × 0.83 mm2 and 1.20 × 1.20 mm2, respectively. Experiment results demonstrate that this work exhibits an outstanding performance on lossless compression ratio with a competitive hardware performance.
Causal Process “Observation”: Oxymoron or (Fine) Old Wine

The issue of how qualitative and quantitative information can be used together is critical. Brady, Collier, and Seawright (BCS) have argued that “causal process observations” can be adjoined to “data set observations. ” This implies that qualitative methods can be used to add information to quantitative data sets. In a symposium in Political Analysis, I argued that such qualitative information cannot be adjoined in any meaningful way to quantitative data sets. In that symposium, the original authors offered several defenses, but, in the end, BCS can be seen as recommending good, but hopefully standard, research design practices that are normally thought of as central in the quantitative arena. It is good that BCS remind us that no amount of fancy statistics can save a bad research design.
A Comparative Study Between Free and Immobilized Enzyme onto Porous Chitosan Beads

The search for an inexpensive support has motivated our group to undertake this work dealing with the use of chitosan as matrix for immobilizing lipase. In addition to its low cost, chitosan has several advantages for use as a support, including its lack of toxicity and chemical reactivity, allowing easy fixation of enzymes. In this article, we describe the immobilization of Candida rugosa lipase onto porous chitosan beads for the enzymatic hydrolysis of olive oil. The binding of the lipase onto the support was performed by physical adsorption using hexane as the dispersion medium. A comparative study between free and immobilized lipase was conducted in terms of pH, temperature, and thermal stability. A slightly lower value for optimum pH (6.0) was found for the immobilized form in comparison with that attained for the soluble lipase (7.0). The optimum reaction temperature shifted from 37°C for the free lipase to 50°C for the chitosan lipase. The patterns of heat stability indicated that the immobilization process tends to stabilize the enzyme. The half-life of the soluble free lipase at 55°C was equal to 0.71 h (K d = 0.98 h ‐1 ), whereas for the immobilized lipase it was 1.10 h (K d = 0.63 h ‐1 ). Kinetics was tested at 37°C following the hydrolysis of olive oil and obeys the MichaelisMenten type of rate equation. The K m was 0.15 mM and the V max was 51 μmol/ (min·mg), which were lower than for free lipase, suggesting that the apparent affinity toward the substrate changes and that the activity of the immobilized lipase decreases during the course of immobilization. Index Entries: Lipase; immobilization; chitosan; physical adsorption; characterization; hydrolysis.
Robust restoration of microwave brightness contrasts from the DMSP SSM/I data

A technique tolerant to an inexactness of the antenna pattern form is developed for resampling microwave radiometer data on the base of robust principles of statistical estimation. Two types of algorithms are considered: a single-channel algorithm and an interchannel algorithm to resample low frequency channel data taking into account a higher frequency channel. The performance of the algorithms is demonstrated by results of DMSP SSM/I data processing.
DSP-based indirect-current-controlled STATCOM. Part 1: Evaluation of current control techniques

DSP-based implementation of a 3-phase static compensator (STATCOM) is presented. The closed-loop control scheme of the compensator is based on fuzzy logic. The hardware module of an IGBT-based PWM current-controlled voltage-source-inverter (PWM-CC-VSI) is taken as a STATCOM. Two different types of current control techniques, namely, direct and indirect current control are designed for the compensator. The experimental tests on the compensator are carried out with both techniques. The STATCOM is tested as an active filter (AF) to select the most promising technique for the current control.
Automatically Collect the Adjectives and Calculate their Sentiment Intensity in the Sentiment Analysis

In order to automatically expand high quality polarity adjectives as much as possible by using the WordNet, three types of query strings are used in this study. Among them, the third type of query string is the most important. Besides ‘synonym’ and ‘antonym’ relations, we also use ‘similar to’ and ‘also see’ relations of the WordNet. In fact, the last two relations are more important than the first two ones. With the help of the newly proposed method, we can calculate the sentiment intensity of those expanded adjectives exactly. Abundant experiments demonstrate that our improved POAE algorithm is very effective in expanding and ranking adjective seed list in the sentiment analysis.
Discovering closed frequent patterns in moving trajectory database

The increasing availability of tracking devices bring larger amounts of trajectories representing people's moving location histories. In this paper, we aimed to mine closed frequent patterns in moving trajectory database. Such closed frequent patterns can help us to understand general mobile behaviors in compact representation. In this work, we first presented a conception of spatiotemporal region of interesting (STROI) to capture the attribute of moving trajectory in spatial and temporal dimensions. Second, based on the set of STROIs distributing in given geospatial region, we transformed trajectory data into STROI element sequence data at different time slice with respect to corresponding STROIs. Third, we modified the closed sequence pattern mining algorithm CloSpan to adapt to closed moving trajectory pattern discovery. Finally, the approaches are then validated by a range of synthetic data sets to evaluate the usefulness and efficiency.