Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on Data Mining Based on Apriori Algorithm

With the availability of inexpensive storage and the progress in data collection tools, many organizations have created large databases of business and scientific data, which create an imminent need and great opportunities for mining interesting knowledge from data.Mining association rules is an important topic in the data mining research. In the paper, research mining frequent itemsets algorithm based on recognizable matrix and mining association rules algorithm based on improved measure system, the above method is used to mine association rules to the students’ data table under Visual FoxPro 6.0.
An Integrated CMOS Instrumentation Amplifier with Improved CMRR

An instrumentation amplifier is described, which is based on the classical current-balancing technique that ensures this type of circuit achieves high immunity to common-mode signals. In the particular case of the circuit herein described, a CMRR of 110 dB was attained, thanks specially to improving the current mirror that balances the current between the input and the output stages of the amplifier. Prototypes of the circuit were fabricated in 0.6 /spl mu/m CMOS using MPW (multi-project wafer) services and were fully characterized.
Why failure rates observe Zipf's law in operational software

The author proposes a model showing how software developers, when attempting to produce software of a given reliability level with a minimum of resources, create software whose fault content observes Phillip's and Zipf's laws. He also proposes a software reliability model based on Zipf's law that fits Adam's reliability data on nine software systems with an average correlation coefficient of 0.986. He concludes that software, when and only when optimally developed, displays operational reliability patterns conforming to Zipf's law. >
Clique-Based Reputation System in Self-Organizing Internet-Based Virtual Computing Environment

By borrowing the construction and evolution mechanisms of the social groups, a reputation system based on groups of autonomic elements (AE) is proposed, which is called clique-based reputation system (CRS). With the combination of the clique-based reputation evaluation and reputation inspired clique evolution, CRS makes the reputation model more realistic on evaluation of the characteristic of AE behaviors and better convergent properties. Meanwhile, the node cluster results from the clique evolution make a foundation for the differential service for AE based on reputation, incentivize them to take corporative behaviors, and provide reliable services.
Metaphors as an Unconventional Reflective Approach in Architectural Design

Metaphors affect the way designers think, perceive, conceptualize and organize their knowledge. The vague character of metaphors allows for capturing the essence of a problem under different perspectives. In the design domain, this cognitive strategy can help to reflect on a problem situation and restructure it anew. This is particularly relevant in design problem-solving which by definition is ill-structured. Empirical research dealing with the use of metaphors as a supportive design tool was carried out. The investigation enabled an insight into the way metaphors helped students, and into the knowledge gained from the application of this tool in design problem-solving. Moreover, it was possible to identify what were the most frequent difficulties found during the process, and what could be the role of metaphorical thinking in future design tasks. Metaphors are proposed as an alternative reflective approach and as an educational tool for the development of design skills.
A Method of Handling Missing Data in the Context of Learning Bayesian Network Structure

Under the background of learning Bayesian network structure, we proposed a new method based on the KNN algorithm and dynamic Gibbs sampling to fill in the missing data, which is mainly used to solve the problem of how to learn the Bayesian network structure better with missing data sets. The experiments based on Asia Network show that, this method can restore the original data very well, which will make it available to use some Bayesian network structure learning algorithm only based on complete data. This method will expand the scope and improve the effect of Bayesian networks application.
Finite element analysis of different contact bearing couples for human hip prosthesis

The main concern limiting the long-run success of the total hip replacement is the limited service life. The success of the implant is mainly depends upon the proper material selection and design of the prosthesis. The present work is to develop the two dimensional finite element model of acetabular component to investigate the maximum von Mises stress, contact pressure, contact radius and mean contact pressure to yield strength ratio developed for the different material combinations. The different bearing couple considered for the analysis are metal in contact with plastic, metal on metal, metal on ceramic, ceramic on plastic, ceramic on metal and ceramic on ceramic combinations. The result reveals that the combination with the metal in contact with plastic i.e. cobalt chromium femoral head paired with UHMWPE cup reduces von Mises stress by 90%, contact pressure by 91% and additionally provides thrice the contact area in comparison with other combinations. The finite element results are validated with the experimental data’s and found to be in close correlation between them.
The Analysis of Research Frontier and Hot Topics about User Behavior in Network Community Based on Mapping Knowledge Domain

By using mapping knowledge domain, this paper analyzes the literature from 2005 to 2013 of user behavior in network community, the results show that with the development of the Internet and the maturity of the social media, the research in this field is increasing. Now, the papers mainly focus on the study of the user behavior, virtual community and online community, and the chief methods are structural equation model and social network analysis, also, they have a deep analyze on trust as an influence factor. First, to have an overall understanding of the research situation, this paper analyzes three aspects as follow: the information of the papers, the author of the papers and the research institutions, second, it focuses on the research frontier and the cited references.
Two dynamic performance tuning methods for portable parallel programs

We present two dynamic performance tuning methods for portable parallel programs on various parallel computers. In parallel programs the affinity between parallel algorithms and the architecture of the target parallel computer is very important. In this paper we focus on the parallelism in view of the number of micro-tasks which are processing units in parallel programs. The presented methods estimate the optimal number of micro-tasks before the parallel processing is invoked. Furthermore, they shorten the execution time of the parallel program so that it is close to the optimal execution time. The estimation is based on the result of pre-executions of the program for different sizes of the data to be processed on a target parallel computer. One tuning method uses nearest-neighbor interpolation and the other uses spline interpolation for the estimation. We tested these tuning methods using a parallel square-matrix multiplication program written in Dataparallel C on three different parallel computers; a Paragon, an iPSC/2, and an nCUBE/2. In these experiments, the method using nearest-neighbor interpolation brought the execution time closer to the optimum than did the method using spline interpolation. The nearest-neighbor interpolation method yielded average execution times, which are given in terms of the optimal execution time, of 1.01 for the Paragon, 1.005 for the iPSC/2, and 1.052 for the nCUBE/2. <<ETX>>
Access Control Based on File View

Constructing the tree type logic structure of a file and introducing the view mechanism of database system into the file system, the hierarchical structure of view files is created. Different files ( view files ) are provided to different users according to their levels or interests by mapping layer by layer with beginning of the minimum access unit (the logic block). It can solve the problem of the discrepancy of users views.
The journey from formal learning to performance support

Twenty years have passed since Gloria Gery first introduced performance support (PS). Rather than sending employees through hours, day or weeks of upfront training, Gery argued that we could instead provide them with “individualized on-line access to the full range of.systems to permit job performance” (Gery, 1991, p.21). This intervention opened up the possibility of providing real-time support to employees were performing their job rather than sending them to formal learning events disconnected from the work. Fortunately for us, this pipe dream is now possible -more than ever before.
Programmable analog vector-matrix multipliers

A VLSI-compatible approach for vector-matrix multipliers consisting of a two-dimensional array of analog multiplier circuits with the weight matrix values capacitively stored as analog voltages is described. The performances of several MOSFET analog multiplier circuits, including the triode, differential pair, Gilbert, and modified Gilbert multiplier circuits, are evaluated. The weight retention characteristics of the capacitive storage approach are evaluated as a function of temperature with effective weight decay rates of 30 and 0.6 mV/s at room temperature measured for the single- and double-capacitor storage arrangements, respectively. The design approach for a 32*32 programmable vector-matrix multiplier circuit with an analog serial-to-parallel multiplexer for the input vector and an analog parallel-to-serial multiplexer for the output vector is described. An architecture for cascading the 32*32 vector-matrix multiplier circuits to implement multilevel artificial neural networks is described. >
Modelling for a Federated Peer-to-Peer MMOG Architecture

Abstract In this paper we propose a methodology, in which analytical models are presented so as to abstract the characteristics of massive multiplayer online games (MMOGs). By using these models, the system performance can be evaluated in terms of two performance metrics: (i) the cost of resources consumed by a targeted game system during its game-play; (ii) the system delay and consistency loss rate. Specifically, we can investigate the impact of various factors, such as game types, the number of players, the intensity of players or NPCs interaction, the number of regions in a game-world, avatar region-transition rate and network configuration, on the system performance. In this study, a number of resource-cost functions are also defined, which map the system resource consumed to the cost during a game-play. In addition, an approach for evaluating the system delay and consistency loss is proposed. We choose the federated peer-to-peer architecture as a target for this study, because it is a typical and potential architecture proposed recently and attracting more attention. Finally, we demonstrate numerical examples for the system performance evaluation.
Automatic segmentation of training set for facial feature detection

In conventional image-based feature detection a time consuming pre-processing step is required to manually segment the training features from the unsegmented face images. We present a novel method of using automatically segmented facial image data for facial feature detection. A quality measure is defined to identify those image data from a large training set that are better to describe the feature. The best quality subset is then extracted and used to train the feature detector. The detection performance obtained by the automatically segmented data set after refinement is almost as high as that obtained by the feature detector trained by a manually segmented set.
Using Prosody to Predict the End of Sentences in English and French: Normal and Brain-damaged Subjects

In an earlier study (Grosjean, 1983), it was found that listeners of English were surprisingly accurate at predicting the temporal end of a sentence when only given the part up to the “potentially last word”, that is a noun before an optional prepositional phrase of varying lengths. The present study investigated this phenomenon in four experiments. The first two experiments examined the prediction capabilities of listeners when presented with the whole sentence in segments of increasing duration and when presented with the potentially last word only. The results indicate that to be able to use prosody to predict the end of sentences correctly, subjects must have reached a point in thesentence where neither syntax nor semantics can contribute to the prediction process. The third experiment investigated whether the results obtained with English can be replicated in French, a language with a very different prosodic structure. It was found that unlike their English counterparts, French listeners were unablet.
The Relationship Between Word And Bit Level Systolic Arrays As Applied To Matrix X Matrix Multiplication

The mapping of matrix x matrix multiplication on to both word and bit level systolic arrays has been investigated. It has been found that well defined word and bit level data flow constraints must be satisified within such circuits. An efficient and highly regular bit level array has been generated by exploiting the basic compatibilities in data flow symmetries at each level of the problem. A detailed description of the circuit which emerges is given and some details relating to its practical implementation are discussed.
Quasi-parallel network applications in real-time distribution management system

In modern distribution management systems (DMSs), the real-time calculation of the network's state plays an important role for the operation of the network. High sophisticated algorithms for the estimation and calculation of the system's state like distribution system state estimation (DSSE), distribution system power and short circuit calculations (DSPF and SCC), voltage var control (VVC) and others must operate in a real-time environment, supplying subsequently running functions with reliable input data. Closed-loop requirements also increase the requirements concerning performance, availability and robustness. In this paper, an implementation of the sequence control of different DMS-network applications is presented. This proposed real-time scheduler takes advantage of CPU-cores inside of a modern computer system: by passing subtasks to different CPU-cores, the overall performance is significantly increased. The scheduling process is analysed in detail taking the nature of a distribution system into consideration. The presentation is finalised with a report about the gain of performance for the state estimation process.
Performance analysis of blind digital signal copy algorithms

We have recently proposed a blind approach for separating multiple co-channel digital signals received at an antenna array. This approach exploits the finite alphabet property of digital signals to simultaneously estimate the array response and symbol sequence for each signal. Previously Talwar et al. (1993-1994) presented two efficient algorithms for computing the estimates: iterative least-squares with projection (ILSP) and iterative least-squares with enumeration (ILSE). In this paper, we focus on the performance analysis of these algorithms. We derive the probability of error for both algorithms assuming that the array responses are known. In scenarios where the parameters allow convergence to signal estimates with low error rates, simulation results show that the performance of blind algorithms is virtually the same as predicted by the analysis. <<ETX>>
REVISITANDO AS HEURÍSTICAS DE AVALIAÇÃO DE NIELSEN PARA ANÁLISE DE USABILIDADE EM JOGOS DE TABULEIRO NÃO VIRTUAIS

As heuristicas de Nielsen foram originalmente propostas e desenvolvidas para avaliacao de usabilidade em interfaces de sistemas computacionais. Este trabalho propoe uma analise e redesenho das heuristicas de Nielsen de forma a especializa-las para emprego na avaliacao de jogos de tabuleiros nao virtuais. As heuristicas foram redesenhadas a partir de levantamento bibliografico, consideracoes e modelos gerados sobre as regras encontradas em cada jogo testado, alem da analise heuristica das interfaces existentes nesses jogos atraves de metodo de inspecao utilizando as heuristicas de Nielsen. O objetivo do trabalho visa atraves desse levantamento, gerar uma base onde seja possivel expor a aplicabilidade de tais heuristicas especializadas em ambientes nao computacionais e que elas possam ser aplicadas em jogos de tabuleiro distintos dos analisados inicialmente.
The Optimal Design of Junctionless Transistors with Double-Gate Structure for reducing the Effect of Band-to-Band Tunneling

The effect of band-to-band tunneling (BTBT) leads to an obvious increase of the leakage current of junctionless (JL) transistors in the OFF state. In this paper, we propose an effective method to decline the influence of BTBT with the example of ntype double gate (DG) JL metal-oxide-semiconductor field-effect transistors (MOSFETs). The leakage current is restrained by changing the geometrical shape and the physical dimension of the gate of the device. The optimal design of the JL MOSFET is indicated for reducing the effect of BTBT through simulation and analysis.
Video processing on a flexible heterogeneous architecture

Video Processing algorithms, and in particular those found in high-end television receivers, often have challenging demands for system resources. Therefore, most often, dedicated IC solutions are proposed to meet both the system and economic constraints. However as the functional requirements increase and as more diversity in terms of application support is required, dedicated solutions become less economic attractive, and hence a more heterogeneous architecture becomes more economic. In this paper, we present an architecture that is suited to run multiple very demanding video processing applications in real-time for consumer market applications.
Adaptive MIMO decision feedback equalization for receivers in time-varying channels

In an attempt to reduce the computational complexity of the vertical Bell Labs layered space time (V-BLAST) processing for time-varying channels, an efficient adaptive receiver is developed based on the generalized decision feedback equalizer (GDFE) architecture. This receiver updates the filter weight vectors using a recursive least squares (RLS)-based time- and order-update algorithm. In time-varying channels, the proposed adaptive technique can be considerably simpler to implement than the V-BLAST processor with the channel tracking, yet its performance is almost comparable to that of the latter.
Green Synthesis of Silver Nanoparticles using Aqueous Plant Extracts and its Application as Optical Sensor

Metal nanoparticles have received a lot of attention in the recent decades due to their unique ability to alter optical, electrical, biological properties.1–5 Nanoparticles are also interesting because of their huge increase in surface area and a surge in conductivity compared to their metal counterparts. Moreover, metal nanoparticles also show surface plasmon resonance. These properties make them useful to many applications such as bio-sensing, imaging, drug delivery, HIV treatment, Cancer treatment, optical spectroscopy and Surface Enhanced Raman scattering (SERS). 2–4
Density-induced oversampling for highly imbalanced datasets

The problem of highly imbalanced datasets with only sparse data of the minority class in the context of two class classification is investigated. A novel synthetic data oversampling technique is proposed which utilizes estimations of the probability density distribution in the feature space. First, a Gaussian mixture model (GMM) from the data of the well-sampled majority class is generated and with its help a new GMM is approximated by Bayesian adaptation using the sparse minority class data. Random synthetic data is generated from the adapted GMM and an additional assignment rule assigns this data to either the minority class or else discards it. The obtained synthetic data is employed in combination with the available original data to train a support vector machine classifier. The examined application in this paper is optical on-line process monitoring of laser brazing with only rare sporadic occurring defects. Experiments with different amounts of minority class data samples and comparisons to other methods show that this approach performs very well for highly imbalanced datasets.
The Prospects of Layered Alumino-silicates in the Synthesis of Nano-Excipients for Controlled Release Systems

Over the past six decades, there has been a growing need for designing controlled release formulations of drugs and agrochemicals in order to attain an extended therapeutic effect of various active ingredients, improve patient convenience, maintain steady state of active ingredients-target site interaction, optimize release kinetics, reduce side effects as well as improve the way in which the active ingredients are delivered into the targeted organ. On account of that, researchers in the course of time have developed three generations of controlled release systems (CRSs) namely, first generation which consist of basics of controlled release systems; second generation which consist of smart delivery systems; and third generation which consist of modulated delivery systems. In view of challenges emanating from CRS usage such as difficulties in retrieving active ingredients upon hypersensitivity, decreased systemic availability as well as poor in vitro-in vivo correlation, the need to further the design of CRSs using nano-excipients set-in. Consequently, opportunities aiming at synthesizing effective nano-based-excipients of active ingredients using in situ polymerization, graft polymerization, copolymerization and intercalation emerged. With regard to intercalation technique, application of 2:1 layered nano materials as nano-excipients has been a success leaving behind a question of what limits the application of 1:1 layered nano materials as nano-excipients in CRS industry. This paper therefore, intends to provide an overview of progress made in the application of 1:1 layered nano-materials as nano-excipients by using first generation intercalation compounds technically called intermediate intercalation agents.
Research of Data Mining Algorithm Based on the Intrusion Prevention System

With the rapid development of network, the security problem of network becomes an issue which has been paid more and more attentions to. Among so many methods of intrusion prevention, data mining is a very effective one. The FP-growth algorithm is the most widely used algorithm for mining frequent item-sets, which is also an algorithm for mining association rules without candidate set. However, the FP-growth algorithm needs large memory when mining large database,and its running speed is slow. In order to overcome these problems, based on the FP-growth algorithm, this paper proposed an optimized algorithm. This paper compared the new algorithm with the previous one based on intrusion prevention model for campus network by experiments. Based on Experiments, we can draw the conclusion that, mining association rules by using the improved FP-growth algorithm can effectively detect the users’ behavior pattern, historical pattern and the current model to calculate the similarity of users, and provides the possibility to accurately judge the user behavior.