Miracle-dz/UniFAR-FTUs huggingface dataset:
Preprocessing for Local Bianry Pattern Based Face Recognition

This paper studies the pre-processing methods on Local Binary Pattern (LBP) for face recognition. Three methods are well investigated, such as Gaussian smoothing, histogram equalization and Sobel operator. The extensive experiments on FERET database show that the best recognition rate increase is achieved by combination of histogram equalization, Gaussian smoothing, and Sobel with LBP. The conclusion achieved in the paper is useful for real face recognition system.
A hierarchical text classification system for manufacturing knowledge management and retrieval

Intensive global competition is pushing manufacturing companies ever harder in their strife for constant profit. As the world evolves into a knowledge based economy, manufacturing companies are increasingly concerned about the acquisition, management and utilisation of advanced R&D information and knowledge from both internal organisations and external resources, like e-journals and digital libraries. This paper describes our recent research on a Knowledge Management and Retrieval system based on Hierarchical Text Classification scheme. This system organises the large volume of manufacturing related electronic documents according to the manufacturing knowledge taxonomy, then classifies and further routes the searching queries based on manufacturing concepts to the corresponding categories for documents retrieval. In this way, better performance of information retrieval is achieved as searching is directed under the guidance of the manufacturing knowledge.
JAGUAR: a fully pipelined VLSI architecture for JPEG image compression standard

In this paper, we describe a fully pipelined single chip VLSI architecture for implementing the JPEG baseline image compression standard. The architecture exploits the principles of pipelining and parallelism to the maximum extent in order to obtain high speed and throughput. The architecture for discrete cosine transform and the entropy encoder are based on efficient algorithms designed for high speed VLSI implementation. The entire architecture can be implemented on a single VLSI chip to yield a clock rate of about 100 MHz which would allow an input rate of 30 frames per second for 1024/spl times/1024 color images. >
Measuring campus portal effectiveness and the contributing factors

Purpose – The purpose of the paper is to evaluate the effectiveness or success of universities' portal implementation from the perspective of students as users. Adopting the model developed by Delone and McLean, portal effectiveness is defined as being composed of information quality, systems quality and service quality. In addition, the paper also seeks to investigate the influence of individual factors comprising attitudes towards the portal, personal innovativeness and web self‐efficacy on the effectiveness of the portal.Design/methodology/approach – The study adopted a survey research design with questionnaires being administered to 600 students as respondents. The cross‐sectional strategy for data collection resulted in 405 usable responses that were used for data analysis.Findings – The results show that IS effectiveness dimensions consisting of service quality and systems quality are significantly correlated with user satisfaction. In addition, the study also showed that of the three predictors inv.
DISTAL: Domain-speciﬁc Language for Implementing Distributed Algorithms

Distributed algorithms research focuses on interactions and communication between independent systems and processors in diverse scenarios. These algorithms are usually written as abstract pseudo-code, and turning them into compilable and runnable code is a complex and error prone task. This is in part due to the lack of expressiveness for representing the distributed algorithms abstractions in currently available tools and libraries. We present DISTAL, a domain-specific language for implementing distributed algorithms, as a library on top of Scala that allows the user to express and fully implement distributed algorithms in a high level, pseudo-code-like manner. Validated with a Paxos and its MultiPaxos variant along with a batching optimization, this library exhibits the capability of allowing a quickly implementation of these algorithms, while retaining their expected behavior and properties.
Collection Development Policies

In order to develop a collection and a collection development policy, data must be gathered and representatives of the library and community must be consulted. This is not something that can be accomplished in a short period of time—or alone. The greatest need in formulating a collection development policy is for ideas — these ideas must come from different people and different points of view. Even the smallest library must gather ideas from a number of people interested in keeping the library alive, vital, and a part of the community it serves.
Visually Mining Off‐line Data for Quality Improvement

Highly automated modern manufacturing processes are yielding large databases with records on hundreds of process variables and product characteristics. This large amount of information calls for new approaches to production process analysis. In this paper, we discuss why a data mining framework can be appropriate for this goal, and we propose a visual data mining strategy to mine large and high‐dimensional off‐line data sets. The strategy allows users to achieve a deeper process understanding through a set of linked interactive graphical devices, and is illustrated within an industrial process case study. Copyright © 2003 John Wiley & Sons, Ltd.
Nonprint Media and Technology Literacy Standards for Assessing Technology Integration

This article suggests a set of cumulative standards for assessing the use of nonprint media and electronic technologies in elementary, middle, and high school classrooms. The proposed standards are culled from existing standards created for educational technologies, information literacy, and the English language arts, and are offered as a starting point for thinking about expanding our notions of literacy and literacy instruction in the schools. Most importantly, from this perspective, the standards are categorized as addressing three types of literacies—basic skills, critical literacies, and construction skills—to encourage teachers to incorporate all three when integrating technology use in teaching and learning.
An Animation Video Resource Conversion System Based on Supercomputers

The rapid development of mobile internet has brought new opportunities to the development of the animation industry, but the network traffic bottlenecks animation video promotion. Based on the super-computing resources, using the Python language, adopting FFMpeg, OpenCV, HEVC and PyGTK technologies, we designed and implemented an animation video resource conversion system to solve the traffic bottleneck in this paper. The conversion system provides HEVC parallel conversion, video serial conversion, video frames extraction and video playback functions, effectively promoted the promotion of animation products distribution.
Information Behavior and Japanese Students: How Can an Understanding of the Research Process Lead to Better Information Literacy?

Academic librarians are striving to better serve international students as this emerging population grows on university campuses. Past studies of international students generally focus on linguistic and cultural differences in relation to information literacy skills development. However, it is necessary to go beyond these factors to better serve the population. By using a framework based in information behavior research, the present study investigates the factors that mediate students' behavior and information literacy skills. Practical recommendations based on the findings of an in-depth qualitative study of students' research process are provided.
A multi-task neural network approach to speech recognition

Improving the speaker-independent generalization exhibited by neural network approaches to phoneme identification is an area of continuing interest to speech recognition researchers. The author reports research exploring the combined impact of multiple task constraints and differing speech input representations on network generalization. The multiple tasks required of the networks are based on a psychological model of speech perception. Using 12 American vowels to train and test the networks, the differing input representations are motivated by current theories of vowel perception and human audition. Network results compare favorably to baseline performance results established by a K-nearest neighbor classification and the classification performance of human listeners on the same task. These results are also extremely good when compared to performance reported by other researchers. <<ETX>>
Motion sensitive clothing

Pervasive systems have a vast potential to provide novel assistive solutions, in particular in personalized health and sports applications. Recent research has been directed to develop smart monitoring garments with integrated sensors and processing functionalities to address these fields. It was found that clothing is an ideal platform for sensing and recognizing activities in natural out-of-lab settings. This paper discusses approaches to activity monitoring using smart garments and introduces the smart shirt (SMASH), a prototyping platform for quick exploration of options and challenges in development of convenient sensing garments. We discuss the primary challenge to obtain casual fitting cloths that can robustly identify activities at the same time.
Auditory Display: Sonification, Audification, And Auditory Interfaces

Foreword (Albert Bregman) An Introduction to Auditory Display (Gregory Kramer) Delivery of Information Through Sound (James A. Ballas) Perceptual Principles in Sound Grouping (Sheila M. Williams) Spatial Sound and Sonification (Elizabeth M. Wenzel) Pattern and Reference in Auditory Display (Robin Bargar) Environments for Exploring Auditory Representations of Multidimensional Data (Stuart Smith, Ronald M. Pickett, and Marian G. Williams) Some Organizing Principles for Representing Data with Sound (Gregory Kramer) Sound Synthesis Algorithms for Auditory Data Representations (Carla Scaletti) Sonnet: Audio-Enhanced Monitoring and Debugging (David H. Jameson) A Framework for Sonification Design (Tara M. Madhyastha and Daniel A. Reed) Synchronization of Visual and Aural Parallel Program Performance Data (Jay Alan Jackson and Joan M. Francioni) Sonifying the Body Electric: Superiority of an Auditory over a Visual Display in a Complex, Multivariate System (W. Tecumeseh Fitch and Gregory Kramer) Auditory Display of Computational Fluid Dynamics Data (Kevin McCabe and Akil Rangwalla) Musical Structures in Data from Chaotic Attractors (Gottfried Mayer-Kress, Robin Bargar, and Insook Choi) Listening to the Earth Sing (Chris Hayward) Multivariate Data Mappings (Sara Bly).
Setswana sports terms: a genre analysis

Genre studies in Setswana are rare, particularly those which study genre on the basis of lexical distinctiveness. Such studies have however been attempted in other languages (cf. Stamatatos et al., 2000; Xiao and McEnery, 2005). The paper proposes a genre analysis of the sports domain of Setswana. It implements a computational and statistical methodology of retrieving sports terms from a Setswana sub-corpus of a large Setswana corpus. The proposed approach is preferred since it is unbiased and measures real language as used by speakers of the language. It uses frequency and keyword analysis to generate words which are typical and definitive of the sports genre. The strategy has been used before extensively in the study of a variety of Setswana genres (see Otlogetswe, 2007). Finally, the article demonstrates that such retrieved texts could be useful in a variety of applications, amongst these being, genre studies, lexicography and other data retrieval applications.
Enhancing Collaborative Filtering Recommendation by Utilizing Improved Ant Colony Optimization Algorithm

Collaborative filtering (CF) is the most widely used and successful personalized recommendation technology in web usage mining. The traditional collaborative filtering algorithm based on user static evaluation of the item's neighbour to predict changes of the users’ interests, however, the user’s interest will make a difference over time. Taking the dynamic changes the user’s interest into account in the process, this paper presents a dynamic collaborative filtering recommendation method based on improved ant colony algorithm (EACF). Improved ant colony algorithm takes into account the user access time and access frequency, which can be more representative of the true interests of users. When generating the recommendation, this method not only takes into account the item’s score, but also will take into account intensity of “interest pheromone” on each item. Experimental results show that the EACF can significantly improve the prediction accuracy of the recommendation system compared with traditional CF.
Improved Signal Processing Techniques for Color Television Broadcasting

A new technique for image enhancement permits both vertical and horizontal equalization of an encoded NTSC signal without the generation of black-and-white overshoots and without the use of clippers in the main signal path. A phantom channel is used to improve the long-term drift characteristics of the equalizer. Level dependent equalization and crispening are also employed to permit a maximum of equalization with a minimum introduction of noise. A companion masking amplifier employs low-pass filters in the masking channel to permit optimum live camera, pre-gamma masking without the introduction of noise. When used together these two units produce considerable subjective improvement in the broadcast color signal.
Efficient Indexing RDF Query Algorithm for Big Data

With the rapid development of information technology, data grows explosionly, how to deal with the large scale data become more and more important. Based on the characteristics of RDF data, we propose to compress RDF data. We construct an index structure called PAR-Tree Index, then base on the MapReduce parallel computing framework and the PAR-Tree Index to execute the query. Experimental results show that the algorithm can improve the efficiency of large data query.
Optimized Corporate Defense Programs: A 5 Step Roadmap

This paper begins by comparing the concept of defense in both the sporting and corporate worlds. It then identifies the critical components which constitute an organization’s program for self-defense, namely governance, risk, compliance, intelligence, security, resilience, controls and assurance. The idea of introducing a formal corporate defense program which integrates all of these critical components is then examined. The paper concludes by stating the business case for adopting a 5 step roadmap in relation to a formal corporate defense program and highlights how organizations can only expect to derive positive returns on their already significant investment in this area, once they arrive at step 3 and beyond. The paper stresses that in relation to corporate defense activities during an economic downturn, successful organizations need to be optimizing value while minimizing overhead and redundancy, and suggests that this 5 step roadmap can offer guidance on how to achieve this objective.
Coin Identification Based on Fusion Multiple Algorithms

With the extensive use of coins in the financial sector, it is necessary to develop an effective real-time method of identification. This paper presents a coin identification algorithm based on multiple algorithms fusioned and verifies the effectiveness of the algorithm in the simulation environment of Matlab. Through experimental analysis, the accuracy of the algorithm is high, and is not easily effected by external environmental factors.
Adaptive Tree Encoding of Speech at 8000 Bits/s with a Frequency-Weighted Error Criterion

The multipath tree-encoding of speech at 8 kbits/s is investigated. Tree coding proceeds along the lines of Anderson, et al, but at this lower bit rate, frequency weighting of the error process and adaptation of the coding process are found to be beneficial. Coding results for a stationary speech-like source are found to agree well with rate-distortion theoretic ideas, and when applied to speech, tree coding at 8000 bits/s yielded frequency-weighted SNR's of 15-20 dB.
An adaptive silence deletion algorithm for compression of telephone speech

The ever-increasing volume of speech generated for transmission and storage motivates a continuing search for an improved cost-effective means to effectively compress speech. Earlier work by various researchers has resulted in various compression algorithms. Of particular interest to us are those waveform compression techniques utilizing the principle of silence deletion developed by Gan (1988) and by Rose (1991) which was implemented on good quality speech signals. We further modify, optimize and evaluate these waveform compression algorithms, and test their viability and performance on noisy speech from actual telephone circuits. The results show that up to 50% compression of continuous speech is achievable at an acceptable level of playback quality.
Numerical Wind Tunnel (NWT) and CFD research at National Aerospace Laboratory

The National Aerospace Laboratory (NAL) of Japan is the only national research institute for aerospace engineering and services in Japan. NAL is a pioneer of supercomputer development and utilization in Japan. Since 1993, NAL has developed the Numerical Wind Tunnel (NWT), consisting of 166 parallel-connected Fujitsu vector processors and has been providing substantial computational power resources to scientists and industries since 1993. This paper describes the background of NWT's development, its present status and computational fluid dynamics (CFD) research being carried out on NWT.
P‐47: Quiet Code: A Transition‐Minimized Code to Eliminate Inter‐Word Transition for an LCD‐Panel Module Interface

Quiet code not only minimizes intra‐word transition but also eliminates inter‐word transition for EMI reduction in LCD panel module interface. Combined with modulo reduction, it also avoids the extra bit of DPCM prediction error without any information loss, and it is estimated to gain 7‐dB EMI suppression with 1‐V predictor.
Influence of real-time queue capacity on system contents in Diffserv's expedited forwarding per-hop-behavior

This paper studies a single-server non-preemptive priority queue with two traffic classes in order to model Expedited Forwarding Per-Hop Behavior in the Differentiated Services (DiffServ) architecture. Generally, queueing models assume infinite queue capacity but in a DiffServ router the capacity for high priority traffic is typically small to prevent this traffic from monopolizing the output link and hence causing starvation of low-priority traffic. The presented model takes the exact (finite) high-priority queue capacity into account. Analytical formulas for the system content of each class are determined as well as the high-priority packet loss ratio. For each class, service of a packet takes a (different) general independent distribution. The issues this causes are resolved by using spectral decomposition. Numerical examples indicate the considerable impact of the finite capacity on system performance.
Performance analysis of high speed circuit switched data (HSCSD) over GSM

The paper presents a nonpreemptive priority queueing system model for voice and HSCSD service integration in GSM. The study is conducted using a multidimensional Markov chain. An HSCSD connection can be established if the number of available channels is between a minimum acceptable capacity, b, and a maximum required capacity, B. This leads to an effective service time for HSCSD calls, proportional to the bandwidth negotiated with the base station. Finite buffers are used for new and handoff requests to increase the total carried traffic, while maintaining the quality-of-service (QoS) requirements. The analysis can be applied when mean service times for voice and HSCSD calls are different. The key parameters which control the new data service performance are identified and adequate formulas are obtained. Especially, delays experienced by HSCSD calls are evaluated and compared to an optimal transmission operating at the maximum capacity.
Comparison of the design of a contoured-beam and an elliptical-beam satellite offset reflector antennas to cover the Taiwan island region for satellite communications

For the design of the satellite antenna for the future geostationary (GEO) satellite communication or DBS (direct broadcasting satellite) applications to serve the Taiwan Island region, it may be required to have a antenna beam which effectively covers the Taiwan region and reduces the antenna radiation level in the nearby area of mainland China. Two cases of the Ka-band (20 GHz) satellite antenna, a shaped offset reflector antenna to synthesize a contoured beam and an elliptical offset reflector antenna to generate an elliptical beam, have been studied. This paper presents the comparison and discussion of the antenna coverage performance of the two designs.
A Semi-Supervised Regression Algorithm Based on Co-Training with SVR - KNN

A semi-supervised regression algorithm based on co-training with the same type KNN required large amount of storage capacity and shown scarcely to improve the regression precision further after several iterations. This paper puts forward a kind of a semi-supervised regression algorithm based on co-training with SVR-KNN, which fully combined the advantages of SVR and KNN in a semi-supervised learning respectively, avoided the learning ability limitations of a single type of learning. Finally, comparative experiments of the semi-supervised regression algorithm based on co-training with SVR-KNN and the other two co-training algorithms with same type learners was conducted, the result shows that the algorithm proposed here works much better in improving regression precision and generalizing the regression model.
Digital libraries in the context of users' broader activities

Surprisingly little of the work on understanding information seeking and the design of digital libraries has taken much account of the background of the users or the context within which they are working. It has recently been noted (e.g., Kuhlthau, 2005) that there is little interaction between those who study information seeking and information retrieval. The challenge is arguably greater than this: there is additionally a need to understand how digital libraries (and related information sources) are used and also how such systems fit into people's broader work tasks. Without such an understanding, it is a matter of chance as to whether new systems that are developed actually meet the needs of their users or not. This JCDL workshop brought together researchers with an interest in designing digital libraries, and those who study information seeking and use in context, to exchange ideas and insights, and create new interaction possibilities.