Miracle-dz/UniFAR-FTUs huggingface dataset:
Properties of Associative Memory Model with the β-th-order Synaptic Decay

Many associative memory models with synaptic decay such as the forgetting model and the zero-order decay model have been proposed and studied so far. The previous studies showed the relation between the storage capacity C and the synaptic decay coefficient α in each synaptic decay model. However, with the exceptions of a few studies, they did not compare the network retrieval performance between different synaptic decay models. We formulate the associative memory model with the β-th-order synaptic decay as an extension of the zero-order decay model. The parameter β denotes the synaptic decay order or the degree of the synaptic decay term, which enables us to compare the retrieval performance between different synaptic decay models. Using numerical simulations, we investigate the relation between the synaptic decay coefficient α and the storage capacity C of the network by varying the synaptic decay order β. The results show that the properties of the synaptic decay model are constant for a large decay order β. Moreover, we search the minimum β to avoid overloading and the optimal β to maximize the network retrieval performance. The minimum integer value of β to avoid overloading is −1. The optimal integer value of β to maximize the network retrieval performance is 1, i.e., the degree of the forgetting model, and the suboptimal integer β is 0, i.e., that of the zero-order synaptic decay model.
Computer simulation and measurement of error vector magnitude (EVM) and adjacent-channel power ratio (ACPR) for digital wireless communication RF power amplifiers

Computer simulation and measurement of the error vector magnitude (EVM) and the adjacent channel power ratio (ACPR) of a 2.4 GHz MMIC power amplifier (PA) for digital wireless communications is presented. A computer simulation based on the /spl pi//4-DQPSK modulation with square-root raised cosine (SRRC) filter is established for this study. Using digital signal processing techniques and a time-domain approach, we can accurately predict the EVM and the ACPR related to the input power. The nonlinear effects of the MMIC PA are modeled as traditional nonlinearity parameters, such as 1-dB gain compression point or third-order intercept point IP3, by which the EVM and ACPR are simulated. A standard NADC modulated signal from a HP ESG-D signal generator is applied to the MMIC PA and the output signal analyzed by a HP 89410A vector signal analyzer. The measured results agree well with the simulation curves. This shows that the computer program by Matlab is useful to RF/microwave system engineers in the design of power amplifiers for digital wireless communications.
Gossip: The Architecture of SpreadPlots

A spreadplot is a visualization that simultaneously shows several different views of a dataset or model. The individual views can be dynamic, can support high-interaction direct manipulation, and can be algebraically linked with each other, possibly via an underlying statistical model. Thus, when a data analyst changes the information shown in one view of a statistical model, the changes can be processed by the model and instantly represented in the other views. Spreadplots simplify the analyst's task when many different plots are relevant to the analysis at hand, as is the case in regression analysis, where there are many plots that can be used for model building and diagnosis. On the other hand, the development of a visualization involving many dynamic, highly interactive, directly manipulable graphics is not a trivial task. This article discusses a software architecture which simplifies the spreadplot developer's task. The architecture addresses the two main problems in constructing a spreadplot, simplifying the layout of the plots and structuring the communication between them.
Key Technologies of Speech Services in the Internet Era

With the popularity of mobile devices, the communication mode based on speech is increasing obviously. The cognitive load of speech interaction is small, and will not always arouse the user's attention, at the same time, it needs a small physical space, but has great amount of interaction information and high interaction efficiency. The challenge Internet speech information service is facing is speech interaction. This paper analyzes four key technologies: the user behavior modeling of speech service in Internet era, multi-channel perception technology in speech interaction, speech information service platform architecture, and visual analysis of speech information. It also presents the development and application prospect of speech interaction.
Engaging student interpreters in vocabulary building: Web search with computer workbench

Abstract This paper investigates the usefulness of Web portals in a workbench for assisting student interpreters in the search for and collection of vocabulary. The experiment involved a class of fifteen English as a Foreign Language (EFL) student interpreters, who were required to equip themselves with the appropriate English vocabulary to handle an interpreting task they had been assigned. The subjects were given the same topic for vocabulary building in two stages – one stage without and the other stage with the use of the workbench. They were not allowed to repeat vocabulary items in the two stages. They documented their experience in vocabulary preparation in the first stage, and provided think-aloud protocols for the second stage. They also completed a questionnaire and submitted two portfolios. The vocabulary portfolios compiled during the two stages were then compared. The results indicate that, with the use of the workbench, the subjects were more efficient in performing the task of building vocabulary by searching for the required vocabulary, and were able to build a vocabulary portfolio that was larger in size and richer in variety. The data also reveal that most students make use of Web portals that have a specific focus, rather than general search engines. The findings provide important information to support the use of the workbench as a tool for training EFL student interpreters in vocabulary building, and also show that guided Web portals are essential for users who need to perform Web-based language learning activities to achieve efficient search results.
A monolithic analog video comb filter in a 1.2 mu m CMOS

A fully integrated, sampled-data, analog three-line (2H) Y/C (luminance/chrominance) separator for high-performance NTSC decoding is described. This function requires two 910-tap delay elements, implemented in fully differential, sequentially addressed, charge-based switched-capacitor analog RAM cells. Efforts to minimize cell size and complexity result in the use of a single-switch cell. The prototype Y/C separator, realized in 1.2- mu m CMOS, has an effective SNR of 51 dB and an active area of 11.7 mm/sup 2/, while dissipating less than 170 mW. In this prototype, less than 20% of the total area is consumed by storage capacitors, indicating that this approach will be competitive with scaled technologies. <<ETX>>
Processes of knowledge construction in the classroom mediated by technological convergence: reflections of this emerging scenario

It is remarkable the outbreak in the educational context, of the phenomenon we call technological convergence, in short, characterized by a proliferation and coexistence of mobile cyberinstruments (netbooks, tablets, etc.) and constant flow of information. In this sense, the aim of this paper is to discuss changes in knowledge building processes in the classroom environment, in the context of higher education, mediated by technological convergence. To this end, we developed an exploratory and qualitative research whose investigated object was a postgraduate course. The instruments used to conduct experiments were participant observation, semistructured interviewing and literature review; for the analysis, we used content analysis and triangulation between the cited instruments. The research, with special emphasis on multidisciplinary attentional mechanisms, allowed us to identify and assess relevant aspects of the studied scenario, revealing that the convergence can help to accelerate processes of (collaborative) knowledge building but also raise difficulties.
A study in Tabu Search Algorithm to Solve a Special Vehicle Routing Problem

In this paper, a kind of special vehicle routing problem based on reality-- vehicle routing problem with facultative demands is presented. The attributes of the problem and the optimization target are described. The mathematical model of the problem is set up. To solve the problem, A meta-heuristic approach called tobu search (TS) is put forward. The neighborhood structure and the parameters of TS algorithm are designed respectively. The proposed algorithm is successfully applied to a case and the result indicates the TS algorithm is practicable and valid.
Terrain-referenced Underwater Navigation using Rao-Blackwellized Particle Filter

: Navigation is a crucial capability for all types of manned or unmanned vehicles. However, vehicle navigation in underwater environments still remains a challenging problem since GPS signals for position fixes are not available in the water. Terrain-referenced underwater navigation is an alternative navigation technique that utilizes geometric information of the subsea terrain to correct drift errors due to dead-reckoning or inertial navigation. Terrain-referenced navigation requires the description of an undulating terrain surface as a mathematical function or table, which often leads to a highly nonlinear estimation problem. Recently, PFs (Particle Filters), which do not require any restrictive assumptions about the system dynamics and uncertainty distributions, have been widely used for nonlinear filtering applications. However, PF has considerable computational requirements which used to limit its applicability to problems of relatively low state dimensions. This study proposes the use of a Rao-Blackwellized particle filter that is computationally more efficient than the standard PF for terrain-referenced underwater navigation involving a moderate number of states, and its performance is compared with that of the extended Kalman filter algorithm. The validity and feasibility of the proposed algorithm is demonstrated through numerical simulations.
An Image Processing System For Automatic Retina Diagnosis

We are developing a system designed around an IBM PC-AT to perform automatic diagnosis of diseases from images of the retina. The system includes hardware for color image capture and display. We are developing software for performing image enhancement, image analysis, pattern recognition and artificial intelligence. The design goal of the system is to automatically segment a digitized photograph of the retina into its normal and abnormal structures, identifying these objects by various features such as color, size, shape, texture, orientation, etc., and ultimately to provide a list of possible diagnoses with varying degrees of probability. We will discuss algorithms used to identify markedly different objects and to distinguish between those objects which appear very similar to the trained eye. Implementation of these algorithms, which are typically applied to areas such as remote sensing, terrain mapping and robotics, has been very successful when applied to color images of the retina.
Iterative Learning Control: A Comparison Study

Iterative Learning Control (ILC) is a technique of tracking control aiming at improving tracking performance for systems that work in a repetitive mode. ILC is a simple and effective control and can progressively reduce tracking errors and improve system performance from iteration to iteration. In this paper, we first classify the ILC schemes into three categories: offline learning scheme, online learning scheme, and online-offline learning scheme. In each scheme, P-type, D-type, PD-type, and switching gain learning control are discussed. The corresponding convergence conditions for each type of ILCs are presented. Then, different ILCs are applied to control a general nonlinear system with noise and disturbance. After that, various ILC schemes are tested under different test conditions to compare the effectiveness and robustness. It is demonstrated that the online-offline type ILCs can obtain the best tracking performance, and the switching gain learning control can provide the fastest convergence speed.Copyright © 2010 by ASME
A heuristic for combining fuzzy results in multimedia databases

This paper deals with the issue of combining fuzzy results obtained from two individual systems in multimedia query processing. Consider a query such as retrieve images similar to I1 by color AND with associated text flower. Suppose we have a color subsystem which can return a sorted list of images based on similarity with I1 and a text subsystem which can return a sorted list of images based on similarity with flower. Our task is to combine these two results. In other words, we need to evaluate the fuzzy combining function AND, giving a sorted list of the images.Fagin has proved that the probabilistic complexity of the problem is almost linear (Fagin 1996), and our multi-step algorithm (Nepal & M. V. Ramakrishna 1999) is an optimal uniform algorithm (Fagin, Lotem & Naor 2001). In view of this inherent limitation, we investigated a non-uniform heuristic approach. In this paper, we discuss the problems of processing such queries, also referred to as aggregation queires in multimedia databases. The experimental results presented show that our "minimum depth first search" heuristic approach out-performs other uniform algorithms in general and by over 90% when the distribution of similarity values is not uniform.
Non-Linear Predictive Models for Intra-Day Foreign Exchange Trading

Artificial neural networks were used to search for non-linear relations in high- frequency foreign exchange time series. Three years 1985-7 tick-by-tick bid prices for the Swiss franc to the US dollar exchange rate were used in this study as training data to specify predictive models for intra-day trading, which was then tested on the same exchange rate time series in the following year 1988. A simple trading rule was adopted to evaluate the models, which showed statistically significant trading profit under moderate transaction costs. In contrast, a standard linear model did not produce profit with the same training and test data and under the same trading rule and transaction cost assumption. This provides evidence for the non-linear nature of the foreign exchange time series under study.
Early Appraisals of Electronic Voting

With the recent troubles in U.S. elections, there has been a nationwide push to update voting systems. States and localities are investing heavily in electronic voting systems, many of which use a touch screen. These systems offer the promise of faster and more accurate voting; however, the current reality is that they have some shortcomings in terms of voter usability. This study examines issues related to the usability of electronic voting systems and reports on a series of usability studies that involved expert review, close observation, a field test, and an exit poll to learn voters’responses to a new voting system. Our analysis shows these systems work well; however, they have some shortcomings including some that have raised concerns among a minority of voters.
Building up Ontologies with Many Properties from Japanese Wikipedia

Here is discussed how to build up ontologies with many properties from Japanese Wikipedia. The ontologies include is-a relationship (rdfs:subClassOf), class-instance relationship (rdf:type) and synonym relation (skos:altLabel) moreover it includes property relations and types. Property relations are triples, property domain (rdfs:domain) and property range (rdfs:range). Property types are object (owl:ObjectProperty), data (owl:DatatypeProperty), symmetric (owl:SymmetricProperty), transitive (owl:TransitiveProperty), functional (owl:FunctionalProperty) and inverse functional (owl:InverseFunctionalProperty). Experimental case studies show us that the built Japanese Wikipedia Ontology goes better than DBpedia from utility when we use, such as Hub of Linked Data, especially in Japan.
Developing a TRIZ-Based Systematic Method to Inspire Individual Student’s Interest and to Solve Problem for Engineering Innovation Education

TRIZ has been developed over six decades and attracted a great deal of interest in industry and education. It can provide a systematic approach to analyze problems where innovation is needed and to provide strategies and methods to solve the problem. It consists of many tools such as 40 inventive principles and the matrix of contradictions, laws of technical system evolution, substance-field analysis, ARIZ (algorithm of inventive problems solving). In this paper, we focused on engineering innovative education and developed a TRIZ-based systematic method applied to inspire individual student’s interest and learning motivation based on their life experience and capability. The process of this method includes analysis of individual student’s interest and expertise, requirement analysis, confirmation of problem direction, problem definition, selection of TRIZ tools, generation of solutions, evaluation of solutions. A case study including an integrated application with mechanical, electrical and information techniques was illustrated for the method and process. The authors expects this research could provide a reference for engineering innovation education and the method proposed in this paper is general in form to be applied for the other disciplines.
Knowledge-based artificial neural network and the application of it in understanding remotely sensed images

The Artificial Neural Network (ANN) is an intelligent computer system bases on the empirical learning of the human being. Knowledge-Based Artificial Neural Networks (KBANN) effectively combines the knowledge learnt from theory with that of learnt from examples. This efficient combination of theory and data may result in efficient learning system. And the method of building a KBANN solves the problem that how to design the structure of the neural network. According to the way of building a KBANN, interpreting system of Remotely-Sensed images can be built.
Interactive Recognition of Hand-drawn Circuit Diagrams

When designing electronic circuits, engineers frequently make hand-drawn sketches of circuits. These are then captured with a computerised design. This study aims to create an alternative to the common schematic capture process through the use of an interactive pen-based interface to the capturing software. Sketches are interpreted through a process of vectorising the user’s strokes into primitive shapes, extracting information on intersections between primitives and using a naive Bayesian classifier to identify symbol components. Various alternative approaches were also considered. It is concluded that it is feasible to use a pen-based interface and underlying recognition engine to capture circuit diagrams. It is hoped that this would provide an attractive early design environment for the engineer and enhance productivity.
Preparing Preservice Teachers to Implement Performance Assessment and Technology through Electronic Portfolios

Abstract This qualitative study considers the use of electronic portfolios in teacher education and evaluates responses from 26 preservice teachers (PSTs). The PSTs used presentation software and multimedia to recreate two instructional units they had taught to elementary school children. Following completion of each unit, PSTs responded to open-ended questions in which they evaluated the electronic portfolio assignment. The PSTs rated the assignment positively (7.51 on a 10-point scale). Evaluations disclosed several advantages, including opportunities to learn about educational technology and new ways to organize and present ideas. Some PSTs complained of time and equipment problems. Overall, the electronic portfolio assignment educated the preservice teachers in computer-based technology and provided faculty with a performance-based assessment of teaching development.
How potential users of music search and retrieval systems describe the semantic quality of music

A large-scale study was set up aiming at the clarification of the influence of demographic and musical background on the semantic description of music. Our model for rating high-level music qualities distinguishes between affective/ emotive, structural and kinaesthetic descriptors. The focus was on the understanding of the most important attributes of music in view of the development of efficient search and retrieval systems. We emphasized who the users of such systems are and how they describe their favorite music. Particular interest went to inter-subjective similarities among listeners. The results from our study suggest that gender, age, musical expertise, active musicianship, broadness of taste and familiarity with the music have an influence on the semantic description of music.
Mastering Cloud Computing: Foundations and Applications Programming

Mastering Cloud Computing is designed for undergraduate students learning to develop cloud computing applications. Tomorrow's applications won't live on a single computer but will be deployed from and reside on a virtual server, accessible anywhere, any time. Tomorrow's application developers need to understand the requirements of building apps for these virtual systems, including concurrent programming, high-performance computing, and data-intensive systems. The book introduces the principles of distributed and parallel computing underlying cloud architectures and specifically focuses on virtualization, thread programming, task programming, and map-reduce programming. There are examples demonstrating all of these and more, with exercises and labs throughout. Explains how to make design choices and tradeoffs to consider when building applications to run in a virtual cloud environment Real-world case studies include scientific, business, and energy-efficiency considerations Table of Contents 1. Introduction 2. Principles of Parallel and Distributed Computing 3. Virtualization 4. Cloud Computing Architecture 5. Aneka: Cloud application platform 6. Concurrent Computing: Thread programming 7. High-Throughput Computing: Task Programming 8. Data Intensive Computing: Map-Reduce Programming 9. Cloud Platforms in Industry 10. Cloud Applications 11. Advanced Topics in Cloud Computing
Multiframe image and video super-resolution algorithm with inaccurate motion registration errors rejection

Super-resolution (SR) is a technique to obtain a higher resolution image (frame) by fusing multiple low-resolution (LR) images (frames) of the same scene. In a typical super-resolution algorithm, image registration is one of the most affective steps. The diffculty of this step results in the fact that most of the existing SR algorithms can not cope with local motions because image registration in general assumes global motion. Moreover, modeling SR noise including image registration error has great influence on the performance of the SR algorithms. In this paper, we report that Laplacian distribution assumption is good selection for global and slow motions that can be easily registered, while for fast motion sequences that contain multi-moving objects, Gaussian distribution is better for error modeling. Based on these results, we propose a cost function with weighted L2-norm considering the SR noise model where the weights are generated from the error of registration and penalize parts that are inaccurately registered. These weights serve to reject the outlier image regions. Both the objective and subjective results demonstrate that the proposed algorithm gives better results for slow and fast motion sequences.