Miracle-dz/UniFAR-FTUs huggingface dataset:
The Mechanisms of Information Communication on Construction Sites

Construction sites are information intensive environments. Various construction personnel in the field need large amounts of information ranging from proj- ect design drawings to personal diaries to support their ongoing works. The emergence of Mobile Computing (MC) has the potential to improve information management on construction sites and enlarge the boundary of information systems from site offices to actual work sites. Before the implementation of mobile computing for information man- agement on construction sites, the context in which construction personnel retrieve and transfer construction information should be investigated. This paper describes a survey that is aimed at investigating the current mechanism of information retrieval and trans- fer on construction sites. Following a description of the research method and the research process, this paper discusses survey findings from the following aspects: the nature of information, sources and destinations of information transfer, mediums of information communication, approaches of information access and collection on work sites, and the users' perception of mobile computing. The paper concludes with a brief discussion on how the findings can be used in future research.
A New Normalized-Cut Image Segmentation Algorithm Based on Watershed Transform

In this paper an improved image segmentation algorithm based on watershed transform is presented. Firstly the normalized cut method and watershed transform are explained and analyzed. Secondly the idea of the improved algorithm and the main formula are explained. We consider the area and perimeter when we merge adjacent regions. We define a new weight value and discuss the value of the parameterαandβ. Finally the experiment result is presented. The new algorithm reduces the nodes and the computational demand of the common normalized cut technique.
Optimal Energy Management Strategy for Parallel Scheduling

Large-scale data streams processing is now fundamental to many data processing applications. There is growing focus on manipulating Large-sca le data streams on GPUs in order to improve the data throughput. Hence, there is a need to investigate the parallel scheduling strategy at the task level for the Large-scale data stream s processing, and to support them efficiently. We propose two different parallel scheduling strategies to handle massive data stream s in real time. Additionally, massive data stream s processing on GPUs is energy-consumed computation task. So we consider the power efficiency as an important factor to the parallel strategies. We present an approximation method to quantify the power efficiency for massive data streams during the computing phase. Finally, we test and compare the two parallel scheduling strategies on a large quantity of synthetic and real stream datas. The simulation experiments and compuatation results in practice both prove the accuracy of analysis on performance and power efficiency.
Interaction between power converter and control-PWM and sampling issues

The control section of power electronics equipment interacts with the power section though pulse width modulation (PWM) on the output and through A/D converter(s) on the input side. The most important presently used sampling and PWM methods are presented in the paper. The influence of different sampling and PWM methods on quality of control and on the power losses is analyzed.
On the feasibility of ASR in extreme noise using the PARAT earplug communication terminal

This paper presents recognition results for a novel microphone solution for ASR in adverse acoustic environments. PARAT is an intelligent hearing protector and communication terminal implemented as a lightweight earplug. The inner microphone in PARAT captures the speech signal behind a seal in the auditory canal, thus impeding contamination from external noise sources. Experiments on a stereo speech database contaminated with noise show that the PARAT microphone compares favourably with a high-quality noise-cancelling close-talking microphone.
Predictive coding for document layout characterization

We propose a new approach to document image layout extraction using rapid feature analysis, preclassification and predictive coding. First, a set of layout features is used to render the image profile information. The knowledge base is utilized to rule these early regions into layout labels. The regions found are given a classification tag and a degree of membership into background, text, picture and line drawing classes. A predictive coding method is used with the preclassification information to increase the confidence of each label, and to integrate the regional domain and the labels into a uniform class without any shape assumption. We have tested our technique using three different databases that comprise over 1000 document images. The results show a high degree of confidence in region separation and extraction. The main benefits include robust classification shape independency and rapid computation.
OS/2 cleanroom environment: a progress report on a cleanroom tools development project

CASE tools to support the cleanroom software development process are being developed for the OS/2 and Presentation Manager environment following the SAA and CUA standards. The paper presents a brief description of the tools, and reports the metrics from design, functional verification and statistical certification testing of the first seven increments of the project. <<ETX>>
The Research of Face Verification Based on Perceptron Algorithm

In recent years, as the need of counter terrorism and security, countries have increased investment in the security field and human identification is the core issue of security. This paper use Perceptron Algorithm Method to verify human face with the ORL face database. The results show that when no fresh face appears, the accuracy rate is 99.67% and decreases to 98.14% with fresh face. Later, its performance in reality is tested by importing a new class from the camera. The result is 7 (of 10) photos is verified correctly and 3(of 10) can not judge (no wrong verified).
Intelligent Information Agents: Agent-Based Information Discovery and Management on the Internet

From the Publisher: This book is the first systematic state-of-the-art survey of intelligent information agents. Eighteen chapters that provide comprehensive coverage of the relevant issues are organized into four parts: cooperative information systems and agents, rational information agents and electronic commerce, adaptive information agents, and mobile information agents and security. Leading authorities and experts in the field offer chapters coherently and concisely written. In addition, the volume editor has provided an introductory survey chapter, highly motivating introductions to each of the four parts, and a comprehensive bibliography with more than 700 entries.
A new 5-parameter MOS transistors mismatch model

A new 5-parameter MOS transistor mismatch model is introduced capable of predicting transistor mismatch with very high accuracy for ohmic and saturation strong inversion regions, including short channel transistors. The new model is based on splitting the contribution of the mobility degradation parameter mismatch into two components, and modulating them as the transistor transitions from ohmic to saturation regions. The model is tested for a wide range of transistor sizes (30), and shows excellent precision, never reported before for such a wide range of transistor sizes, including short channel transistors.
On the effectiveness of various techniques of searching in 3D mesh objects in databases

The article compares some algorithm for object comparison, that can be used for searching 3D objects in database. There are tested: basic D2, TH, and EGI algorithms. The algorithms use histograms as descriptors of 3D shape. The techniques were tested using cultural heritage objects and objects from Shape Princeton Benchmark. Additional test use the same object represented with different accuracy. The tests give us conclusions about the restricted usefulness of the algorithms and suggest the important parameters for searching in database.
Link Adaptation for Video Transmission over COFDM based WLANs

Wireless Local Area Networks (WLANs) such as IEEE 802.11a/g and Hiperlan/2 operate in numerous transmission modes, each providing different throughputs and reliability levels. Link Adaptation algorithms proposed in the literature ([1], [2], and [3]) maximise data throughput based on channel conditions and assume that only error-free packets may be passed on to the higher layer. For multimedia applications such as video transmission, completely error-free communication is not essential, especially if robust video compression techniques are applied. In such scenarios, better decoded video quality might be obtained with a video stream transmitted at a higher bit-rate but with some degree of transmission error, rather than an error free video stream at a lower bit-rate. In this paper, we present a link adaptation scheme that improves the Quality of Service (QoS) for video transmission in terms of the overall received video quality, rather than by maximising error-free throughput. Simulation results using the H.263+ video compression standard over IEEE 802.11a are presented.
Effects of Technology Immersion on Teachers' Growth in Technology Competency, Ideology, and Practices

In the study of the Technology Immersion model, high-need middle schools were “immersed” in technology by providing laptops for each teacher and student, instructional and learning resources, professional development, and technical and pedagogical support. This article reports third-year findings for the teacher component of the theory-driven evaluation. Using hierarchical linear modeling (HLM) to analyze longitudinal survey data, we found that Technology Immersion has a statistically significant effect on teachers' growth rate for technology knowledge and skills, ideological affiliations with technology integration and learner-centered instruction, and the frequency of class activities involving technology. Treatment teachers' technical proficiency and their school's innovative culture, ongoing professional development, and parent/community support predicted teachers' higher classroom immersion. The authors discuss the viability of the Technology Immersion model and implications for technology integration in classrooms.
FrameNet as a resource for paraphrase research

Theoretically as well as empirically, paraphrase is a pivotal concept in many academic and nonacademic fields. And yet, its investigation has made very slow progress, due mainly to the lack of a framework that is versatile enough to deal with the nebulous nature of paraphrase in use. This paper demonstrates how the mechanisms of FrameNet can be utilized as a resource for systematic and coherent research into paraphrase. The semantic framework it provides, including detailed frame descriptions, frame-to-frame relations, and the recording of syntactic information, allows one to see in more principled ways why some set of sentences can be considered paraphrases of each other.
Oral Competency of ESL Technical Students in Workplace Internships.

In recent years, an increasing number of university students in Canada speak a home language other than English, which can put added pressure on the kinds of linguistic, cultural, and academic support they may require in their tertiary education and in the workplace. Indeed, communication difficulties can surface in the workplace for students during internship placements. This article discusses the challenges that ESL engineering students have and the strategies they use to acquire oral competency while on their internship placements. The students in this study participated in a sixteen-month internship in a research and development unit of a software company. Findings reveal that learning technical language was the main priority. However, challenges revolved around conversational aspects of communication that required the ability to use and understand colloquial language, idioms, and slang, as well as to recognize cultural practices in face-to-face and computer-mediated interactions. Pedagogical implications for English for Specific Purposes (ESP) programs are dis
The Eye of the Frog: Questions of Space in Films Using Digital Processes

This article maps initial cinematic terrains produced through digital processes. Composited shots, multiple screens, and new transition strategies shift viewers’ understanding of spatial relations, reconfigure shot boundaries, and construct “semantic clusters” combining different types of information. Digital processes recreate older cinematic styles, and resituate production culturally, economically, and institutionally.
Design and simulation of high frame frequency CMOS camera image acquisition system

For the requirement of high frame in supervision and control for instruments in compartment and record of missiles lunching outside the compartment of a fighter, a high frame CMOS image acquisition system based on the FPGA is designed. High speed CMOS image sensor LUPA-300 is used in this system. Xilinx's FPGA is used as timing and readout of the image sensor and image transmission controlling. FIFO generated by FPGA using Verilog HDL (Hardware Description Language) achieves high-speed image data buffering. Camera Link interface is used to communicate with the image acquisition card of the host computer. The Experiments of the system show the frame can reach 249.6 fps in a format of 640 * 480 with the clock of 80 MHz.
Task assignment under uncertainty: stochastic programming and robust optimisation approaches

The assignment of tasks to teams is a challenging combinatorial optimisation problem. The uncertainty in the tasks’ execution processes further complicates the assignment decisions. This study investigates a variant of the typical assignment problem, in which each task can be divided into two parts, one is deterministic and the other is uncertain with respect to their workloads. From the stochastic perspective, this paper proposes both a stochastic programming model that can cope with arbitrary probability distributions of tasks’ random workload requirements, and a robust optimisation model that is applicable to situations in which limited information about probability distributions is available. An example of its application in the software project management is given. Some numerical experiments are also performed to validate the effectiveness of the proposed models and the relationships between the two models.
The processing of German word stress: evidence for the prosodic hierarchy*

The present paper explores whether the metrical foot is necessary for the description of prosodic systems. To this end, we present empirical findings on the perception of German word stress using event-related brain potentials as the dependent measure. A manipulation of the main stress position within three-syllable words revealed differential brain responses, which (a) correlated with the reorganisation of syllables into feet in stress violations, and (b) differed in strength depending on syllable weight. The experiments therefore provide evidence that the processing of word stress not only involves lexical information about stress positions, but also (quantity-sensitive) information about metrical structures, in particular feet and syllables.
Foundations of Process-Aware Information Systems

Over the past decade, the ubiquity of business processes and their need for ongoing management in the same manner as other corporate assets has been recognized through the establishment of a dedicated research area: Business Process Management (or BPM). There are a wide range of potential software technologies on which a BPM o®ering can be founded. Although there is signi¯cant variation between these alternatives, they all share one common factor { their execution occurs on the basis of a business process model { and consequently, this ¯eld of technologies can be termed Process-Aware Information Systems (or PAIS). This thesis develops a conceptual foundation for PAIS based on the results of a detailed examination of contemporary o®erings including work°ow and case han- dling systems, business process modelling languages and web service composition languages. This foundation is based on 126 patterns that identify recurrent core constructs in the control-°ow, data and resource perspectives of PAIS. These patterns have been used to evaluate some of the leading systems and business process modelling languages. It also proposes a generic graphical language for de¯ning exception handling strategies that span these perspectives. On the basis of these insights, a comprehensive reference language { newYAWL { is developed for business process modelling and enactment. This language is formally de¯ned and an abstract syntax and operational semantics are provided for it. An assessment of its capabilities is provided through a comprehensive patterns-based analysis which allows direct comparison of its functionality with other PAIS. newYAWL serves as a reference language and many of the ideas embodied within it are also applicable to existing languages and systems. The ultimate goal of both the patterns and newYAWL is to improve the support and applicability of PAIS.
Identifying and Tracking Major Events Using Geo-Social Networks

In recent years, several technological advancements have changed the lives of millions throughout the globe. These include broadband Internet wireless access, advanced mobile platforms and smartphones including accurate global positioning system capabilities, and the introduction of social networks. The fusion of these technological advances led to the massive adoption of mobile platform-operated social networking applications and unleashed new real-time and on-site social information. The ability to generate content anywhere and anytime leads to a detectable projection of real-life events on geo-social networks (GSN). For example, in preparation for a rally, the geo-social activity may precede the actual event, allowing predictive capabilities. Alternatively, in a natural event such as a wildfire, early content generated in the proximity of the event may allow early identification of the event and the assessment of its physical boundaries. In this article, we propose to use the massive and rapidly accumulating information communicated within GSN to identify and track major events and present a proof of concept. We discuss means and methods to retrieve relevant information from the networks, through a set of adequate spatial, temporal, and textual filters. Our preliminary empirical results corroborate our assumptions and show that major events may have detectable “abnormal” impact on GSN activities, which allows prompt identification and real-time tracking. Our approach is expected to pave the way to the development of real-time systems and algorithms for early identification and geographical tracking of major events.
An Overview of Collaborative Filtering Recommendation Algorithm

Recommendation algorithm is the most core and key point in recommender systems, and plays a decisive role in type and performance evaluation. At present collaborative filtering recommendation not only is the most widely useful and successful recommend technology, but also is a promotion for the study of the whole recommender systems. The research on the recommender systems is coming into a focus and critical problem at home and abroad. Firstly, the latest development and research in the collaborative filtering recommendation algorithm are introduced. Secondly, the primary idea and difficulties faced with the algorithm are explained in detail. Some classical solutions are used to deal with the problems such as data sparseness, cold start and augmentability. Thirdly, the particular evaluation method of the algorithm is put forward and the developments of collaborative filtering algorithm are prospected.
Stress-Sensors with High-Sensitivity Using the Combined Meandering-Patterns

In this work, the combined meandering-pattern stress-sensors were presented in order to achieve the high sensitivity of stress sensors. Compared to the previous works, which have been using the single meandering-pattern stress-sensors, the sensitivity was approximately observed to increase by 30%~70%. Also, in this paper, more simple and convenient stress-measurement method was presented.
From Cellular Automata to Urban Models: New Principles for Model Development and Implementation

Integration with geographic information systems (GIS) has helped move cellular automata (CA)-based urban and regional models from the realm of instructive metaphors to that of potentially useful qualitative forecasting tools. Such models can now be fully interactive for exploratory purposes and they can be based on actual data. New problems, however, arise as the formal integrity of the original CA framework is lost through successive relaxations of the assumptions and as the resulting complicated models become increasingly difficult to implement and understand. In this paper I propose that the theoretical problem can find a satisfactory answer in the notion of proximal space and the practical one can be handled successfully within the formalism of geo-algebra, a mathematical expression of proximal space which builds a bridge between GIS data and operations, on the one hand, and traditional robust classes of urban and regional models, on the other.
The Evaluation of Ontology Matching versus Text

Lately, the ontologies have become more and more complex, and they are used in different domains. Some of the ontologies are domain independent; some are specific to a domain. In the case of text processing and information retrieval, it is important to identify the corresponding ontology to a specific text. If the ontology is of a great scale, only a part of it may be reflected in the natural language text. This article presents metrics which evaluate the degree in which an ontology matches a natural language text, from word counting metrics to text entailment based metrics.
Foundations and Technological Landscape of Cloud Computing

The cloud computing paradigm has brought the benefits of utility computing to a global scale. It has gained paramount attention in recent years. Companies are seriously considering to adopt this new paradigm and expecting to receive significant benefits. In fact, the concept of cloud computing is not a revolution in terms of technology; it has been established based on the solid ground of virtualization, distributed system, and web services. To comprehend cloud computing, its foundations and technological landscape need to be adequately understood. This paper provides a comprehensive review on the building blocks of cloud computing and relevant technological aspects. It focuses on four key areas including architecture, virtualization, data management, and security issues.