Miracle-dz/UniFAR-FTUs huggingface dataset:
Lightweight target classification for wireless multimedia sensor networks

Visual target classification is one of the challenging tasks in resource-constrained wireless sensor networks. This article presents binary and multicast animal classification techniques, which use rule-based decision tree, for wireless multimedia sensor networks. In order to reduce the computational complexity on the sensor nodes, the expensive training phase is carried out by a high-power base station. Then, the best IF-THEN rules are extracted from the decision tree classifier and stored in the sensor nodes before being deployed. This would decrease the learning phase time and the energy consumption, while attaining high classification accuracy. Experimental results demonstrated that the proposed classification model can effectively perform visual target classification in wireless multimedia sensor networks.
Self-organising Modelling as a Part of Simulation Process

At present GMDH algorithms give us an explicit model description (equations, rules, patterns) of complex ill-defined systems in the case of very short and noisy data samples. Therefore this is a necessary supplement to simulation methodology. Self-organising modelling and in special the GMDH approach is suitable and valuable as a part of the whole simulation process, which is demonstrated in macroeconomic simulation. More than this the paper will give an overview about the sources of traditional GMDH and about further development of self-organising modelling, which is implemented in "KnowledgeMiner".
A complete OCR system for continuous Bengali characters

This paper is concerned with a complete optical character recognition (OCR) system for Bengali character. Recognition is done for both isolated and continuous printed multi font Bengali characters. Preprocessing steps includes segmentation in various levels, noise removal and scaling. Freeman chain code has been calculated from scaled character which is further processed to obtain a discriminating set of feature vectors for the recognizer. The unknown samples are classified using feed forward neural network based recognition scheme. It has been found from experimental results that success rate is approximately 98% for isolated characters and 96% for continuous character.
Interaction Representation and Application of Flash Animation in Webpage Design

The application of Flash animation in website design becomes more popular because it is more attractive and infective than static pages. Functions of Flash, status in quo and characteristics of webpage design are analyzed in this paper; how to present and apply the interaction of Flash animation in webpage design better is promoted via three aspects including functional design of guide, smart application of transparent Flash in Banner ads images and the application of pure Flash making websites.
Fuzzy neural network and fuzzy expert system for load forecasting

A hybrid neural network fuzzy expert system is developed to forecast short-term electric load accurately. The fuzzy membership values of the load and other weather variables are the inputs to the neural network, and the output comprises the membership values of the predicted load. An adaptive fuzzy correction scheme is used to forecast the final load by using a fuzzy rule base and fuzzy inference mechanism. Extensive studies have been performed for all seasons, and a few examples are presented in the paper, including average, peak and hourly load forecasts.
Toward Evaluating Software According to Principles of Learning and Teaching

Sixteen software packages designed for classroom use were evaluated against nineteen criteria based on principles of effective teaching and learning. The programs were randomly selected from a software library containing over 1,100 items representing all grade levels and a variety of subject-matter areas, software types (tutorials, simulations, etc.), and publishers. Generally speaking, the programs were rated high with regard to 1) presenting material in appropriate steps or blocks, 2) consistency between program and stated objectives, 3) providing appropriate examples, and 4) opportunities for independent practice. The programs were rated low with regard to 1) informing students of instructional goal, 2) determining if students have necessary prior knowledge, 3) reviewing prerequisite knowledge, 4) reteaching information not known, 5) providing anticipatory set, and 6) providing for closure. Differences in ratings were obtained between subject-matter areas and program types, but these differences are difficult to interpret. These findings are discussed in terms of their implications for the development of effective instructional software and its use in the classroom.
A Parallel Algorithm for Contact in a Finite Element Hydrocode

A parallel algorithm is developed for contact/impact of multiple three dimensional bodies undergoing large deformation. As time progresses the relative positions of contact between the multiple bodies changes as collision and sliding occurs. The parallel algorithm is capable of tracking these changes and enforcing an impenetrability constraint and momentum transfer across the surfaces in contact. Portions of the various surfaces of the bodies are assigned to the processors of a distributed-memory parallel machine in an arbitrary fashion, known as the primary decomposition. A secondary, dynamic decomposition is utilized to bring opposing sections of the contacting surfaces together on the same processors, so that opposing forces may be balanced and the resultant deformation of the bodies calculated. The secondary decomposition is accomplished and updated using only local communication with a limited subset of neighbor processors. Each processor represents both a domain of the primary decomposition and a domain of the secondary, or contact, decomposition. Thus each processor has four sets of neighbor processors: (a) those processors which represent regions adjacent to it in the primary decomposition, (b) those processors which represent regions adjacent to it in the contact decomposition, (c) those processors which send it the data from which it constructsmore » its contact domain, and (d) those processors to which it sends its primary domain data, from which they construct their contact domains. The latter three of these neighbor sets change dynamically as the simulation progresses. By constraining all communication to these sets of neighbors, all global communication, with its attendant nonscalable performance, is avoided. A set of tests are provided to measure the degree of scalability achieved by this algorithm on up to 1024 processors. Issues related to the operating system of the test platform which lead to some degradation of the results are analyzed. This algorithm has been implemented as the contact capability of the ALE3D multiphysics code, and is currently in production use. « less
Hierarchical spatial clustering in multi-hop wireless sensor networks

In wireless sensor networks, the resource-limited sensor nodes collect and transmit sensing readings to Sink node collaboratively in multi-hop manner to conserve energy. For more energy-efficient data collection, we consider the problem of spatial clustering, which aims to group the strong correlated sensor nodes into the same cluster for rotatively reporting representative data later, and propose a hierarchical spatial clustering algorithm named as HSC. Specifically, with similarity measure on both magnitude and trend of sensing readings, HSC groups the similar sensor nodes in distributed and hierarchical manner by exploiting a pre-built data collection tree, which dispenses HSC from the extra requirements, such as global network topology and strict time synchronization, during clustering. Extensive simulation results show that HSC performs superiorly on clustering quality when compared with the alternative algorithms. Furthermore, approximate data collection scheme combined with HSC can reduce much more communication overhead while incurring modest data error than with other algorithms. In general, HSC possesses comprehensive advantage on the aspects of both clustering quality and approximation performance.
A New Digital Coherent Demodulator

A coherent demodulator is described which is particularly well suited to digital implementation. Its important features are that no low-pass filter is required to eliminate double-frequency terms and that the passband signal need be sampled at only twice the highest frequency of the baseband signal, rather than at twice the highest frequency of the passband signal. A demodulator of this type will be useful in those systems that do not require passband digital signal processing for other purposes.
An incremental basic unit level QP determination algorithm for H.264/AVC rate control

In this paper, we propose an incremental-based basic unit (BU) level quantization parameter (QP) determination algorithm for H.264/AVC rate control. Unlike traditional BU level QP computation in existing rate control schemes, the proposed algorithm does not perform target bit allocation and predict coding complexities. Instead, it exploits bit increment to directly determine QP for a BU, aiming at reducing the variations of encoding bits used among BUs within a frame and improve subjective visual quality. To better handle buffer fullness and reduce buffer overflow/ underflow, we explore an enhanced Proportional-Integral-Derivative buffer controller. In addition, the algorithm can also effectively intra-code all frames in a video sequence and has low computational complexity making it suitable for real-time applications. Our experimental results demonstrate that, the proposed algorithm outperforms the rate control algorithm JVT-W042, adopted in the recent H.264/AVC reference model JM13.2, by achieving accurate rate regulation, reducing frame skipping, decreasing quality fluctuation, and improving coding quality up to 1 dB.
Development and operation of the Traffic Alert and Collision Avoidance System (TCAS)

The authors describe the development of the Traffic Alert and Collision Avoidance System (TCAS), provide a description of the TCAS II system operation, offer results of operational evaluations conducted in cooperation with Piedmont, United, and Northwest Airlines, and outline the status and progress of the TCAS implementation. In recent years, the TCAS effort has focused on concepts that make use of the radar transponders carried by aircraft for ground air traffic control purposes. A transponder-based collision avoidance system can provide immediate protection against the vast population of aircraft already equipped with either the current Air Traffic Control Radar Beacon System (ATCRBS) transponder or the new Mode S transponder. The TCAS concept encompasses a range of capabilities, including TCAS I, which provides traffic advisories (bearing, range, and relative altitude) to assist the pilot in visually acquiring the threat aircraft; TCAS II, which provides traffic and resolution advisories (recommended escape maneuvers) in the vertical plane; and TCAS III, which provides traffic and resolution advisories in both the vertical and horizontal planes. >
Dynamic bandwidth allocation for an MPEG-2 multiencoder video system

An efficient algorithm for dynamically multiplexing MPEG2 encoded video sources is presented. Sources are grouped into classes regarding different combined levels of spatial detail and amount of movement. Simulations were performed using different associations of sources belonging to distinct classes, different bit rates and GOP structures. The implications associated to a real implementation are analyzed and a modular architecture is proposed. Simulation results are presented and discussed, showing that sequences with higher spatial detail and motion are those which exhibit the higher quality improvements. These results are almost not affected by the non alignment, at GOP level, between video sequences.
Current criticalities and innovation perspectives in flash memory design automation

With reference to technological, architectural, and market considerations, the specific areas of design methodology and automation in flash memory design are analyzed in this paper. For each of the activities identified as critical, we show the design process key constraints and specifications, which drive the change in methodology, tools, and flows. We go through a brief survey of the solutions adopted in the recent past as well as the new emerging areas of intervention. The analysis covers: 1) design methodology, floorplanning, full-custom layout design and Rtl2Layout automation integration; 2) analog-digital mixed full-chip simulation and architectural exploration; 3) statistical analog circuital simulation; 4) mixed-signal design to test approaches; and 5) IC and package design integration.
A Rule Based Approach for Automatic Annotation of a Hindi Tree- bank

The paper describes an approach to automatically annotate a Hindi Treebank using Paninian dependency framework. The annotator is a rule based system and the rules use certain syntactic cues available in a sentence. This automated annotation scheme aims at facilitating manual annotation by reducing time and effort of manual annotators. Also, the aim of automatic annotation, among other things, is to increase the efficiency of a broad coverage constraint based Hindi parser. We also evaluate this tool and show its accuracy and coverage.
Lightweight Recovery from Kernel Failures Using Phase-based Reboot

: Although operating systems (OSes) are crucial to achieving high availability of computer systems, modern OSes are far from bug-free. Rebooting the OS is simple, powerful, and sometimes the only remedy for kernel failures. Once we accept reboot-based recovery as a fact of life, we should try to ensure that the downtime caused by reboots is as short as possible. This paper presents “phase-based” reboots that shorten the downtime caused by reboot-based recovery. The key idea is to divide a boot sequence into phases . The phase-based reboot reuses a system state in the previous boot if the next boot reproduces the same state. A prototype of the phase-based reboot was implemented on Xen 3.4. 1 running para-virtualized Linux 2.6. 18. Experiments with the prototype show that it successfully recovered from kernel transient failures inserted by a fault injector, and its downtime was 34.3% to 93.6% shorter than that of the normal reboot-based recovery.
Arnold Transform Based Image Scrambling Method

With the development of information security, the traditional image encryption algorithm has been far from to ensuring the security of images in the transmission process. This paper presents a new image encryption algorithm, which can improve the security of image during transmission more effectively. The traditional scrambling algorithm based on Arnold transformation only applies to the square area, which is a big limitation. Focus on this, a multi-region algorithm for image scrambling encryption model is proposed, which splits the non-square image to multiple square regions, and scrambles each region. Experimental results show that the new algorithm improves the image security effectively to avoid deciphering, and it also can restore the image as same as the original image almost, which reaches to the purposes of image safe and reliable transmission.
Prediction of Mental Workload in Single and Multiple Tasks Environments

This research aimed to develop and validate a practical framework for predicting mental workload in both single- and multitask environments with particular consideration of individual factors. To describe mental workload more precisely and completely, a framework for mental workload measures, containing instantaneous workload, average workload, accumulated workload, peak workload, and overall workload was proposed. To model individual factors, 2 new variables (effective workload and ineffective workload) were introduced to conceptually model task- and individual-generated workloads. Under the conceptual model, the operational models for predicting human mental workload for human-computer interaction tasks were developed. The model used a multidimensional approach and allowed the quantification of different aspects of load. Two experimental studies were conducted to validate the proposed model. The results revealed that (a) the framework, which consisted of average workload, accumulated workload, and insta.
A model and framework of self-adaptive spatial information multi-grid

Based on the fundamental theory of spatial information multi-grid (SIMG), a four-layer model to construct a Self-adaptive Spatial Information Multi-grid (SSIMG) is put forward, which includes 4 layers, i.e. the basic grid layer, the multi-level subdivided grid layer, the visualization grid layer and the bottom cell grid layer. In the next part, the framework to construct Self-adaptive Spatial Information Multi-grid is discussed. Firstly, the globe is divided into Multi-grid and coded to construct a SIMG; Secondly, the detailed feature can be acquired to build a grid database or extracted from traditional database; thirdly, threshold of dynamic grid subdivision can be determined, and a SSIMG can be constructed According to the threshold. The validity of SSIMG has been verified in case study at the last of this paper.
Trend-Based Time Series Prediction Algorithm

According to the resources performance and status information provided by grid monitoring system, this paper adopts a trend-based time series prediction algorithm to predict short-term performance of the resources. Experiments show that the improved mixed trend-based prediction algorithm tracks the trend of data changes by giving more weight, simultaneously takes the different situations of data increases and decreases into account, so the improved algorithm is superior to the pre-improved and it improves the accuracy of the prediction effectively.
LS-SVMlab Toolbox User's Guide version 1.7

We have added new functions to the toolbox and updated some of the existing commands with respect to the previous version v1.6. Because many readers are familiar with the layout of version 1.5 and version 1.6, we have tried to change it as little as possible. Here is a summary of the main changes: • The major difference with the previous version is the optimization routine used to find the minimum of the cross-validation score function. The tuning procedure consists out of two steps: 1) Coupled Simulated Annealing determines suitable tuning parameters and 2) a simplex method uses these previous values as starting values in order to perform a fine-tuning of the parameters. The major advantage is speed. The number of function evaluations needed to find optimal parameters reduces from ±200 in v1.6 to 50 in this version. • The construction of bias-corrected approximate 100(1 − α)% pointwise/simulataneous confidence and prediction intervals have been added to this version. • Some bug-fixes are performed in the function roc. The class do not need to be +1 or −1, but can also be 0 and 1. The conversion is automatically done. We have added new functions to the toolbox and updated some of the existing commands with respect to the previous version v1.5. Because many readers are familiar with the layout of version 1.5, we have tried to change it as little as possible. The major difference is the speed-up of several methods. Here is a summary of the main changes: Chapter/solver/function What's new 1. A birds eye on LS-SVMLab 2. LS-SVMLab toolbox examples Roadmap to LS-SVM; Addition of more regression and classification examples; Easier interface for multi-class classification; Changed implementation for robust LS-SVM. 3. Matlab functions Possibility of regression or classification using only one command! ; The function validate has been deleted; Faster (robust) training and (robust) model selection criteria are provided; In case of robust regression different weight functions are provided to be used with iteratively reweighted LS-SVM. 4. LS-SVM solver All CMEX and/or C files have been removed. The linear system is solved by using the Matlab command " backslash " (\).
CPFLOW: a practical tool for tracing power system steady-state stationary behavior due to load and generation variations

In this paper, a computer package called CPFLOW, which is a comprehensive tool for tracing power system steady-state stationary behavior due to parameter variations, is presented. The variations include general bus real and/or reactive loads, area real and/or reactive loads, or system-wide real and/or reactive loads, and real generation at P-V buses (e.g. determined by economic dispatch or participation factor). The main advantages of CPFLOW over repetitive power flow calculations are its computational speed and reliability as well as its wide applicability. A detailed description of the implementation regarding the predictor, corrector, step-size control and parameterizations employed in CPFLOW is presented. CPFLOW has comprehensive modeling capability and can handle power systems up to 12000 buses. For an illustrative purpose, CPFLOW is applied to a 3500-bus power system with a comprehensive set of operational limits and controls. >
Understanding Digitized Second Language Videotext

Despite the widespread use of digital video and, increasingly, multimedia in listening instruction throughout second language programs, little is known about how learners attend to dynamic visual elements in comprehension. A lack of research in how listeners engage with videotext retards the development of computer-based listening skills. This investigation seeks to describe what learners do when they attend to digital video media. In conjunction with Japanese language instructors, three authentic Japanese news broadcasts were recorded and digitized for computer display. Through a series of immediately retrospective verbal reports, 12 tertiary students of Japanese provided verbal reports as they attended to a front-to-back viewing of videotexts. Based on constructivist perspectives of comprehension, the study produced a seven-category framework regarding the comprehension of second language videotexts. The results of this investigation point out that visual elements work in a number of ways that go beyond merely ‘supporting’ verbal elements; they are better thought of as integral resources to comprehension whose influence shifts from primary to secondary importance as a Hlistener develops a mature understanding of the videotext.
Leadership, technology, and education: achieving a balance in new school leader thinking and behavior in preparation for twenty-first century global learning environments

Abstract Expectations for education are changing. The knowledge base of education is changing. Conceptions of how individual learning occurs are changing. The tools available to ‘do’ education are changing. The roles of teachers are changing. Understandings of what should be learned, who should be learning, how they learn, where they learn, and when they learn, are changing. So, in the face of this changing twenty-first century education it is not surprising that expecting school leaders to recreate their conceptions of appropriate leader behavior presents quite a challenge. This article explores the necessity of incorporating authentic global technology experiences in the preparation of school leaders and presents a description of the rationale and developmental stages of the Global Forum on School Leadership. Based on the existing practices of reflection and dialog found in the leader preparation program at Wichita State University in the United States, this Forum brings together leadership perspectives on common practices from a variety of global locations in an asynchronous, Internet-based discussion format. This learning experiment focused on incorporating a needed global orientation to leadership preparation following the September 11 and Bali tragedies, and emphasizes the use of appropriately selected technologies to achieve expanded course objectives at the same time as transforming the learning model traditionally employed in leader preparation programs