Miracle-dz/UniFAR-FTUs huggingface dataset:
An Object Position And Orientation Ic With Embedded Imager

A CMOS VLSI chip that determines the position and orientation of an object against a dark background is described. The chip operates in a continuous-time analog fashion, with a response time as short as 200 mu s and power consumption under 50 mW. A self-contained phototransistor array acquires the image directly, and the output is a set of eight currents from which the position and orientation can be found. The output can be sampled at up to 5000 frames/s, and there is a greatly reduced analog-digital (A-D) conversion requirement (per frame) for real-time interfacing with a digital system. Orientation is determined to within +or-2 degrees or better for moderately sized and sufficiently elongated objects. Chip dimensions are 7900 mu m*9200 mu m. >
The statistics of discrete-event simulation

as tracing the elements of a typical experiment from inception through analysis, defining statistical problems encountered and relating them to the formal body of stdtistical theory. The problems described are inherent in all stochastic system simulation models. An experimental design’s ability. to reveal useful insights into a system depends to a great extent on how well these problems are solved. Failure to deal with them may cause errors in interpreting observed associations between system input and output. One common error is the underestimation of the statistical reliability of system response measurements; this error is caused by failure to account for autocorrelation in system response time-series generated by a simulation model. Another frequent source of error is the assumption that random numbers generated within a simulation model are independent, when in fact the method of ran-
Mindtools for teacher communities: a European perspective

Abstract Programmes for teacher training should train (aspiring) teachers to be able to make use of information and communications technology as mindtools. Mindtools are not pieces of specialised software that‘teach’ a subject, but computer programs and applications that facilitate meaningful professional thinking and working. Teachers can use these programs and applications to engage their students in critical thinking and to help further their own professional development. In the latter case mindtools can be applied for cooperation (between teachers, teacher educators and student teachers) and collaboration (with other teachers, experts, designers, etc. on pedagogical projects). In this article we focus on electronic networking technologies (conversation tools) as mindtools in communities of practice for teacher professional development. Examples of good practice from teacher training institutions in Europe illustrate how to prepare (aspirant) teachers for working with mindtools that enhance teacher professional development
Optimal control and scheduling in a multiclass queueing network: results and conjectures

Dynamic scheduling and control in queuing networks are addressed. A two-station queuing network with two types of jobs is studied. Type 1 jobs visit stations, 1 and 2 in sequence, and type 2 jobs visit station 1 only. The problem is to control the (external) arrival processes and the service processes, as well as to schedule the server at station 1 among the two types of jobs. The objective is to minimize a discounted cost function over an infinite time horizon. The approach is based on stochastic intensity representation of point processes. The problem is divided into several cases, each corresponding to a certain parameter range. Optimal control and scheduling are derived for some cases. For the other cases, conjectures for the optimality of certain simple threshold policies are presented. <<ETX>>
Interactive Supercomputing with PPMatlab

This paper describes MITMatlab, a system that enables users of supercomputers or networked PCs to work on large data sets within Matlab transparently. MITMatlab is based on the Parallel Problems Server (PPServer), a standalone "linear algebra server" that provides a mechanism for running distributed memory algorithms on large data sets. The PPServer and MITMatlab enable high-performance interactive supercomputing. With such a tool, researchers can now use Matlab as more than a prototyping tool for experimenting with small problems. Instead, MITMatlab makes is possible to visualize and operate interactively on large data sets. This has implications not only in supercomputing, but for Artificial Intelligence applicatons such as Machine Learning, Information Retrieval and Image Processing.
A Self-Organizing Random Array Communications Relay

A sparse random array with self-organizing properties is proposed as a communications relay. The relay consists of N randomly deployed, low-power transmit/receive elements with capabilities for phasing their retransmissions to arrive coherently at the ultimate destination. Signal-to-noise ratio results for conventional modulation schemes corrupted with additive noise are given, together with possible system block diagrams. It is concluded that, in spite of the complexity, practical systems can be built with extremely low electromagnetic radiation densities with point-to-point characteristics at least as good as with conventional systems employing high power relays. The novel characteristics make the proposed system particularly suitable for tactical military communication, and variants thereof may find application in urban communication.
“Technostress” A literature survey on the effect of information technology on library users

Purpose – The purpose of the present paper is to review the impact of information technologies on users of libraries and to understand the problems encountered in their information technology (IT) usage by reference to the concept of “technostress”, the inability to cope with the new computer technologies in a healthy or positive manner.Design/methodology/approach – A literature review was undertaken to further our understanding of the influence of IT based services on the users of libraries.Findings – The paper provides a literature derived set of information about library users who initially find it difficult to cope with the new technology and experience anxiety (termed “IT anxiety”, “technostress” or alternatively “technophobia”). This is bound to affect their adoption of IT technologies negatively. They may eventually begin to avoid contact with computers. Since this avoidance strategy is highly impractical in the modern IT dependent world, the various causes of technostress must be analysed, so that.
The Analysis of the Ontology-based K-Means Clustering Algorithm

In view of research findings made from home and abroad on clustering algorithm and the traditional partition clustering method K-means algorithm, this paper first analyses the advantages and disadvantages of this algorithm and then combines it with ontologybased data set to establish a semantic web model. It then tries to improve the existing clustering algorithm in various constraint conditions to demonstrate that the improved algorithm has better efficiency and accuracy under semantic web. Keywords-component; Ontology; Semantic Web; Data; Kmeans Algorithm
Digital Divides and Social Network Sites: Which Students Participate in Social Media?

Social network sites (SNSs) like Myspace and Facebook are now popular online communities with large teenage user populations. Teens use these technologies to interact, play, explore, and learn in significant ways. As scholars become interested in studying these new online communities, I contribute to the emerging conversation by re-examining questions about the digital divide. This study utilizes a nationally representative survey from the Pew Internet & American Life Project to investigate whether access and participation divides persist in teens' use of SNSs. I use binary logistic regression to examine the relationship between social, demographic, and technology variables with youth participation in social network sites. The results suggest that traditional divide indicators such as Internet access or parent education are not significant predictors of SNS use. Youth appear to find a way to get connected. Deeper understanding of the social and cultural factors related to participation in social technologies is needed for youth populations.
Library instruction and information literacy 2010

Purpose – The purpose of this paper is to provide a selected bibliography of recent resources on library instruction and information literacy.Design/methodology/approach – The paper introduces and annotates periodical articles, monographs, and audiovisual material examining library instruction and information literacy.Findings – Information about each source is provided. The paper discusses the characteristics of current scholarship, and describes sources that contain unique scholarly contributions and quality reproductions.Originality/value – The information in the paper may be used by librarians and interested parties as a quick reference to literature on library instruction and information literacy.
Scaling up multi-camera tracking for real-world deployment

A user-assisted multi-camera tracking system employing several key novel methodologies has previously been shown to be highly effective in assisting human users in tracking targets of interest through industry-standard i-LIDS multi-camera benchmark data.1 A prototype system was developed in order to test and evaluate the effectiveness of this approach. In this paper, we develop this system further in order to improve tracking accuracy and further facilitate scalability to arbitrary numbers of camera views across much larger spatial areas and different locations. Specifically, we describe the following three areas of improvement: (1) dynamic learning mechanisms apply user feedback in adapting internal models to improve performance over time; (2) modular design and hardware acceleration techniques are explored with a view to real-time performance, extensive configurability to leverage available hardware and scalability to larger datasets; and (3) re-design of the user interface for deployment as a secure asynchronous remote web-based service. We conduct an extensive evaluation of the system in terms of: (1) tracking performance; and (2) the speed of the system in computation and in usage over a network. We use a newly collected real-world dataset significantly more challenging than i-LIDS, which comprises six cameras covering two London Underground stations. We show that: (1) dynamic learning is effective; (2) the user-assisted paradigm retains its effectiveness with this significantly more challenging dataset; (3) large-scale deployment and real-time computation is feasible due to linear scalability; (4) context-aware user search strategies and external non-visual information can aid search convergence; and (5) storage and querying of meta-data is a bottleneck to be overcome.
Particle swarm optimization-based sub-pixel mapping for remote-sensing imagery

Mixed pixels are widely existent in remote-sensing imagery. Although the proportion occupied by each class in mixed pixels can be determined by spectral unmixing, the spatial distribution of classes remains unknown. Sub-pixel mapping (SPM) addresses this problem and a sub-pixel/pixel spatial attraction model (SPSAM) has been introduced to realize SPM. However, this algorithm fails to adequately consider the correlation between sub-pixels. Consequently, the SPM results created by SPSAM are noisy and the accuracy is limited. In this article, a method based on particle swarm optimization is proposed as post-processing on the SPM results obtained with SPSAM. It searches the most likely spatial distribution of classes in each coarse pixel to improve the SPSAM. Experimental results show that the proposed method can provide higher accuracy and reduce the noise in the results created by SPSAM. When compared with the available modified pixel-swapping algorithm, the proposed method often yields higher accuracy results.
A user friendly decision support system for dealing stocks using neural network

A user friendly decision support system for dealing stocks has been developed. Parameters in the neural network consisting of 15 input units, 2 hidden layers, and 2 output units are trained by the hybrid algorithm which combines the modified backpropagation method with the random optimization method. It is shown by several simulation results that the proposed decision support system is quite helpful for dealing stocks.
Human-agent interaction in a target identification task

Due to the complex and dynamic nature of our world it is increasingly common for decisions to be made in teams rather than by individuals. Team members must exchange and fuse information and resources from a variety of sources to make effective decisions. While the variety of information and resources brought together by a team may be needed for complex, real-time decision making, members must be able to communicate and interpret one another's communications to realize these benefits. In natural settings which are plagued by unreliable data and data sources, the difficulty of improving reliability through aggregation of data increases with available resources. Effective teams must develop a shared task language, shared perceptions of the task, and knowledge of one another and of the reliability of each other's communications to derive full value from pooled resources. While our understanding of the informational dynamics of human teams remains incomplete, even less is known about teams combining human and software agents.
Improvement mean shift-based image segmentation approach for automatic agriculture vehicle

Mean Shift algorithm, a statistic iterative procedure, is robust when applied to farmland image segmentation. It can effectively overcome the influence of shadow, weeds or illumination changes, etc. However, the Mean Shift procedure has relatively high time complexity and can not meet the requirements of real-time processing. Based on pyramid algorithm, we can obtain a low resolution representation of the images being processed. Then, run Mean shift algorithm on a set of seed points that selected in the low resolution image. Through this method, the time consumption is significantly lower than the original Mean Shift Procedure. The objects in farmland images are large and there are only two major types of structure in it, so the examination accuracy of proposed method is changed little. At the same time based on spatial structure and color distribution of farmland image, Mean Shift Kernel radius in the spatial and range domain is selected. In addition, according to different seasons, crops show different colors. In this case, the equations which convert color image into a grayscale image are discussed.
Automatic detection and quantitative analysis of cells in the mouse primary motor cortex

Neuronal cells play very important role on metabolism regulation and mechanism control, so cell number is a fundamental determinant of brain function. Combined suitable cell-labeling approaches with recently proposed three-dimensional optical imaging techniques, whole mouse brain coronal sections can be acquired with 1-μm voxel resolution. We have developed a completely automatic pipeline to perform cell centroids detection, and provided three-dimensional quantitative information of cells in the primary motor cortex of C57BL/6 mouse. It involves four principal steps: i) preprocessing; ii) image binarization; iii) cell centroids extraction and contour segmentation; iv) laminar density estimation. Investigations on the presented method reveal promising detection accuracy in terms of recall and precision, with average recall rate 92.1% and average precision rate 86.2%. We also analyze laminar density distribution of cells from pial surface to corpus callosum from the output vectorizations of detected cell centroids in mouse primary motor cortex, and find significant cellular density distribution variations in different layers. This automatic cell centroids detection approach will be beneficial for fast cell-counting and accurate density estimation, as time-consuming and error-prone manual identification is avoided.
Tekstdekking, Tekstbegrip En Woordselectie Voor Het Vreemde-Talenonderwijs

This article deals with an alternative approach to the problem of the selection of words in foreign language teaching at higher levels. Since frequency as a selection criterion is inadequate beyond the first 2.500 words, it is argued that the question as to how many and which words can only be answered on the basis of quantitative data on the relationship between lexical coverage and text comprehen-sion. Only after establishing what coverage goes with what level of comprehension will it be possible to come forward with valid suggestions concerning the number of words required for reading authentic L2 texts. As to which words, it is argued that these should be selected from a corpus of 10.000 words (beyond the first 2.500) to be constructed on the basis of a combination of selection criteria such as frequency, valency etc. Knowledge of any 5.000 words from this corpus (combined with the first 2.500) will yield such a dense coverage (at least 95%) of general L2 texts that the meaning of any remaining unknown words can be deduced via contextual clues utilisation.To substantiate this claim the results of some experimental investigations of the relationship between coverage and text comprehension are reported.
Consensus control for multi-agent systems with double-integrator dynamics and time delays

In this study, mathematical modelling and analysis for consensus problems will be conducted for a group of autonomous mobile agents with double-integrator dynamics and time-varying interconnection delays. To solve the problems, distributed control scheme for each agent will be proposed first. Then the consensus stability of the multi-agent system is obtained for the problem, where the dynamics of each agent is second-order with time-varying interconnection delays. In the convergence analysis, both fixed and switched interconnection topologies of the considered multi-agent system are investigated. Finally, some numerical examples are presented to validate the consensus algorithms.
Java Intermediate Bytecode

Java is a programming language loosely related to C++. Java originated in a project to produce a software development environment for small distributed embedded systems. Programs needed to be small, fast, “safe” and portable. These needs led to a design that is rather different from standard practice. In particular, the form of compiled programs is machine independent bytecodes. But we needed to manipulate programs in ways usually associated with higher level, more abstract intermediate representations. This lets us build systems that are safer, less fragile, more portable, and yet show little performance penalty while still being simple.
Comparison of Satellite- and Ground-Based Measurements of Total Ozone Content

Results of international experiments for the validation of measurements of total ozone content (TOC) by the GOME instrument are reviewed and compared with measurements made with independent surface measurements from Dobson and Brewer spectrophotometers and the M-124 ozonometer. The results of numerous comparisons of on-line GOME TOC data with data from ground-based measurements by the Russian ozone monitoring network during 1996-2000 reveal that the GOME data systematically understate TOC (by 4-9%), also noticeable in comparison with data from simultaneous TOMS measurements.
Study on Factors of College Student's Network Service Time Based on Bayesian Networks

Due to the uncertainty of the factors that influence the network service time and other characters of college student, Bayesian Network is used to model this kind of system. Different algorithms are used for learning Bayesian Networks in order to compare several models. It is suggested that researchers can use Bayesian Networks to explore the potential relationship between variables of complex social problems. The result indicates that learning target and family closeness degree are the key variables which influenced college students network service time. Origin of student and family economy didnt influence college students network service time directly. Schools and community should strengthen the education of college students life planning and communication with parents.
Exploring kansei in multimedia information

With information technologies being increasingly involved in areas such as (online) shopping, entertainment or advertisement, computer systems are bound to be able to process Kansei information, i.e. information relevant to users' sensibilities. Rather than modelling the biology of users' sensibilities, we suggest a functional approach by modelling the translation process between different modalities of expression of a same Kansei concept. We hypothesise that this translation process can be grounded into the categorization of users' perception, i.e. the extraction of structures in the multimedia information. Because this translation process is intrinsically variable, we propose a computational agent, called K-Agent, able to learn categories in its visual perception and interactively evolve a translation language. The K-Agent consists of three main modules: a multi-feature image processing unit, a learning kernel that iteratively constructs the translation language, and a feedback interpreter system which incorporates self-supervision and user feedback to structurally tune the learning kernel. The concept of K-Agent has been evaluated in a real-world application involving user Kansei, more specifically, the filtering of images against a given user Kansei impression. Our experimental results demonstrate the feasibility of the concept as well as a superior performance compared to manually filtering the output of existing search engines.
Survey of buffer management policies for delay tolerant networks

Delay tolerant networks (DTN) are a class of networks that are a subset of the traditional mobile ad-hoc networks. It differs from mobile ad hoc networks (MANETs) in the sense that it can withstand high delays in delivering data because of frequent network partitions, limited bandwidth and storage constraints persisting in such networks. Owing to these inherent characteristics of the delay tolerant networks improving delivery ratio in such networks depends on two main factors-use of routing strategy and a good buffer management policy. Many routing protocols have been proposed in the literature for DTN. Buffer management is a very important factor in DTN because of the very limited buffer space available in DTN nodes. Although a scheduling policy in DTN determines which message has to be forwarded first, the dropping policy decides which messages are to be dropped in case of buffer overflow. This Letter presents a survey of the existing buffer management policies proposed for DTN and discusses the pros and cons of these approaches. The buffer management techniques have been classified on the basis of information used by them whether they are based on local information of messages available at the node or global information of all the messages in the network.