Miracle-dz/UniFAR-FTUs huggingface dataset:
Critical Review of Time-Dependent Shortest Path Algorithms: A Multimodal Trip Planner Perspective

Abstract A multimodal trip planner that produces optimal journeys involving both public transport and private vehicle legs has to solve a number of shortest path problems, both on the road network and the public transport network. The algorithms that are used to solve these shortest path problems have been researched since the late 1950s. However, in order to provide accurate journey plans that can be trusted by the user, the variability of travel times caused by traffic congestion must be taken into consideration. This requires the use of more sophisticated time-dependent shortest path algorithms, which have only been researched in depth over the last two decades, from the mid-1990s. This paper will review and compare nine algorithms that have been proposed in the literature, discussing the advantages and disadvantages of each algorithm on the basis of five important criteria that must be considered when choosing one or more of them to implement in a multimodal trip planner.
A Survey on Query Suggestion 1

Query suggestion attracts great concern recently. It is crucial for capturing frequently asked questions in question-answering system and most popular topics in search engine. Besides these, is also used in advertising retrieval systems, e-commerce system for advertising push to get more profits. The paper gives a general review of query suggestion methods. On the whole, all the methods can be grouped into two categories: session based methods and click-through based methods. Adjacency based query suggestion, co-occurrence based query suggestion, query-flow graph based query suggestion, clustering based query suggestion, and bipartite graph based query suggestion are presented respectively in detail. Furthermore, how to evaluate the performance of query suggestion is denoted. Finally the important related issues of the area in further research are discussed.
Interlingua for Multilingual Machine Translation

I n machine translation systems, an intermediate representation is necessary to express the result of sentence analysis. This represents syntactic structure or semantic structure of an input sentence given as a character string. The syntactic structure is normally represented is a tree and semantic structure as a network. In transfer system, t h e intermediate representation of syntactic structure is usually t h e same as analyzed structure of input sentences. When the intermediate representation r e f l e c t s the syntactic structure of a source language, syntactic structure transfer from a source language to a target language is necessary to translate. Implementation cost for the transformation becomes enormous if we develop a multilingual translation system with such an approach. The intermediate representation of interlingua approach is called interlingua. It is the semantic expression of a sentence, how concepts expressed by each word of a sentence relate each other, and what role they play. When we develop the multilingual machine translation systems of interlingua approach, this approach has two important merits. The first merit is that the development of a machine translation system for a language can be localized. To develop dictionaries and grammar rules for analysis and generation of a language requires well-trained native speaker only for an interlingua. An analysis system and a generation system of an interlingua system can completely separated each other by the interface of interlingua. Therefore the development of an analysis system and generation system can be developed independently from those of the other language. Accordingly, those who develop an analysis system and a generation system only need to know the language and the interlingua. The second merit is that knowledge necessary for machine translation systems can be u t i l i z e d in common. To understand the sentence written in the natural language
Managing Information Overload in Distributed Computing Environment

The rapid growth and improved accessibility to Internet has presented users with huge amount and variety of information. From communication programs for instant messaging and email, the technology is now become powerful and reliable to support freely networked business relationships. However, the web is causing information overload and it is becoming difficult to focus on specific information. People are unable to attend the huge volume of information presented to them. The paper provides a review of nature and causes of information overload and explores various solutions to the problem. In this paper, we have identified various sources of information which may cause information overload problem to a user in distributed computing environment. We also suggest techniques to measure the amount of information overload in specific situations. Finally, we have presented the method of using the information effectively for making business decisions
A Model Driven Development Method for Interactive Information Visualization

Wide-Spread deployment for interactive information visualization is difficult. Non-Specialist users need a general development method and a toolkit to support the generic data structures suited to tree, network and multi-dimensional data, special visualization techniques and interaction techniques, and well-known generic information tasks. This paper presents a model driven development method for interactive information visualization. First, an interactive information visualization interface model (IIVM) is proposed. Then, the development method for interactive information visualization based on IIVM is presented. The Daisy toolkit is introduced, which includes Daisy model builder, Daisy IIV generator and runtime framework with Daisy library. Finally, an application example is given. Experimental results show that Daisy can provide a general solution for development for interactive information visualization.
A Graph-based Word Sense Disambiguation Using Collocation

Word sense disambiguation (WSD) is an essential part of Natural Language Processing (NLP) task to identify the senses of words in context. A new WSD approach based on collocation is proposed in this paper. In this approach, collocation is used to characterize the senses of words and the graph connectivity is measured by using various meanings which exist in the WordNet, when no collocation exists among the words.
Radiometric detection of direct-sequence spread spectrum signals with interference excision using the wavelet transform

One of the most important properties of direct-sequence spread spectrum signals (DSSS) is their low probability of intercept. Determination of the presence of such signals can be performed by radiometer-based intercept receivers that detect the signal's presence by measuring received power. However, conventional intercept receivers often fail when they operate in the presence of narrow-band interference because of their inability to differentiate between jammer and DSSS signal energy. An intercept receiver which employs wavelet transform domain-based excision is described. The receiver detects BPSK DSSS signals in the presence of narrow-band interference by employing adaptive interference rejection techniques to suppress the interference before measuring power. The improvement in the system performance over that of conventional radiometric detection only is shown by presenting numerical simulation results in the form of receiver operating characteristics. Performance is also compared to that for intercept receivers that use FFT-based excision systems techniques. <<ETX>>
A study on online learner profile for supporting personalized learning

Digital learning as a popular learning approach has received increasing attention in modern education. The learner profile in online learning plays a critical role in supporting personalized learning. This article uses an information flow-based approach to build the learner profile for supporting personalized learning. The learner profile includes the individual profile to capture the personal features and the community profile to capture the social features in online learning environment.
Empirical Investigation on Certain Anonymization Strategies for Preserving Privacy of Social Network Data

In recent years, the rapid growth of web applications developed the need for private data to be published. Most of the social network data necessitates the data to be available for easy access and conversion of data to graph structure to re-identify sensitive labels of individuals became an impeccable issue. In this paper, we have made a detailed surveyed about the existing techniques that preserve the sensitive data in social network. It is observed that preserving the graph structure and label re-identification by adding some noise nodes to the graph makes significant change in degree is inferred from existing techniques. The anonymization methods for preservation of the private sensitive data based on cluster based approach and graph modification approaches are studied in detail.
An Improved Harmony Search Algorithm for Constrained Multi-Objective Optimization Problems

An improved harmony search algorithm for constrained multi-objective optimization problems is proposed in this paper. Inspired by Particle Swarm Optimization, an inductor particle is introduced to speed up the convergence rate of the CMOHS. Two populations are adopted to increase the opportunity of finding the optimal solutions. Numerical experiments are divided into two parts: the first one compares the CMOHS with NSGA-II, and the other one compares the CMOHS with the algorithm without the inductor individual. The results show that the CMOHS is more effective than NSGA-II, and the induction mechanism improved the convergence and diversity of the algorithm.
Ultra-low power digital front-end for single lead ECG acquisition integrated with a time-to-digital converter

A low power single lead electrocardiogram front-end acquisition system in 0.18 μm CMOS operating at 0.5 V is presented here. The analogue blocks in low noise amplifier (LNA), filters and passive elements that perform amplification and DC offset cancellation are replaced by a moving average voltage to time converter (MA-VTC) to get amplification and anti-aliasing in the time domain. A digital feedback algorithm is used to cancel out the DC offset. The front-end structure is designed in the sub-threshold region of MOS to reduce the power consumption in the circuit. The proposed architecture consumes 50 nW of power with a gain of 670 μs/V. The output of the front-end is fed to an all digital time-to-digital converter (TDC) that operates in the near threshold region with a resolution of 586.4 ps and 32.5 μW power consumption.
Evolution of digital signal processing based spacecraft computing solutions

Increasing information processing needs and data complexity of space exploration has motivated the constant development of higher speed DSP processor modules. These changes and the need to maximize the science data gathered and returned from satellite instruments has led to the development of a line of space qualified, DSP based spacecraft computers (DSP modules) at Southwest Research Institute. The DSP module family (SC-DSP) established at Southwest Research Institute (SwRI) forms an integral part of SwRI's SC-9, VME based, command and data handling systems. Included in the SC-DSP line are the space proven TMS320C30 based, SC-7 module, several module variants of the RTX2010 processor, and a radiation tolerant version of the Analog Devices 21020 in the newest SC-21020 DSP module. SwRI'S newest module (SC-21020) was developed to provide data handling functionality, while maintaining support for critical spacecraft control functions. The SC-21020 spacecraft computer utilizes these features coupled with high performance radiation hardened memories and the space proven VME bus.
Distributed processing of reliability index assessment and reliability-based network reconfiguration in power distribution systems

Parallel and distributed processing has been broadly applied to scientific and engineering computing, including various aspects of power system analysis. This paper first presents a distributed processing approach of reliability index assessment (RIA) for distribution systems. Then, this paper proposes a balanced task partition approach to achieve better efficiency. Next, the distributed processing of RIA is applied to reliability-based network reconfiguration (NR), which employs an algorithm combining local search and simulated annealing to optimize system reliability. Testing results are presented to demonstrate the speeded execution of RIA and NR with distributed processing.
Efficient channel borrowing strategy for multimedia wireless networks

An efficient resource sharing strategy is proposed for multimedia wireless networks in this paper. Assume the channel resource in a wireless system is partitioned into two sets, one for voice calls and one for video calls. In the proposed channel borrowing strategy, voice calls can borrow channels from those allocated to video calls temporarily when all voice channels are busy. A threshold type decision policy is designed such that the channel borrowing request will be granted only if the QoS requirement on video call blocking will not be violated during the duration of channel lending. An analytical model is constructed for evaluating the performance of the channel borrowing strategy in a simplified wireless system and verified by computer simulations. We found that the proposed channel borrowing scheme can significantly reduce the voice call blocking probability while the increase in video call blocking probability is insignificant.
Document classification intelligent system in complex organizations

The objective of the paper is to describe an "intelligent" mechanism proposed for the task of document classification in a complex organization as a part of the so-called "Contextual Communication", module developed in the ESPRIT III Project no. 8749 entitled ORCHESTRA. The task carried out by this system is similar to that carried out in a Post Office: classification and distribution. We focus on a module that realizes tasks of determination of addressees when the information of the document is insufficiently explicit. We describe the sub module called "generic contexts" within the classification module in charge of this task.
A Study on Effective Compression Method using the Diffusion on Luminance for Each Macroblock Luminance Histogram

H.264/AVC is an authoritative international video coding standard, which shows improved code and efficiency than the existing video standards. Above all, the parameter block mode of H.264/AVC contributes much to high compression efficiency. However, as the occasion demands, users tend to pass while overlooking the part that can produce a little higher compression efficiency. We, taking notice of this point, are designed to bring in much higher compression efficiency by gathering up the overlooked parts. This paper suggests the algorithm that produces efficient performance improvement by using the histogram of luminance in the pixel unit (macroblock) of respective prediction block and applying specific thresholds. The experimental results prove that this algorithm proposed by this paper increases the compression efficiency of the existing H.264/AVC algorithm by 0.4% without any increase in the whole encoding time and peak signal to noise ratio(PSNR).
Item Signature Study: Report on the Characteristics of Reading Texts and Items from Calibration 3

Introduction 1 Purpose of the Study . 1 Goals of the Study.2 Methodology . 2 Findings.4 Characteristics of Reading Texts . 4 Characteristics of Assessment Items.5 Level of Agreement . 7 Summary of Findings.8 Characteristics of the Reading Texts . 8 Characteristics of Assessment Items.9 Level of Agreement . 9 Recommendations for Future Studies . 9 References 9
Parallel 3D Fast Wavelet Transform comparison on CPUs and GPUs

We present in this paper several implementations of the 3D Fast Wavelet Transform (3D-FWT) on multicore CPUs and manycore GPUs. On the GPU side, we focus on CUDA and OpenCL programming to develop methods for an efficient mapping on manycores. On multicore CPUs, OpenMP and Pthreads are used as counterparts to maximize parallelism, and renowned techniques like tiling and blocking are exploited to optimize the use of memory. We evaluate these proposals and make a comparison between a new Fermi Tesla C2050 and an Intel Core 2 QuadQ6700. Speedups of the CUDA version are the best results, improving the execution times on CPU, ranging from 5.3x to 7.4x for different image sizes, and up to 81 times faster when communications are neglected. Meanwhile, OpenCL obtains solid gains which range from 2x factors on small frame sizes to 3x factors on larger ones.
Visual intonation in two sign languages*

In a detailed comparison of the intonational systems of two unrelated languages, Israeli Sign Language and American Sign Language, we show certain similarities as well as differences in the distribution of several articulations of different parts of the face and motions of the head. Differences between the two languages are explained on the basis of pragmatic notions related to information structure, such as accessibility and contingency, providing novel evidence that the system is inherently intonational, and only indirectly related to syntax. The study also identifies specific ways in which the physical modality in which language is expressed influences intonational structure.
Large Scale IT Projects: Study and Analysis of Failures and Winning Factors

ABSTRACT The Federal Bureau of Investigation (FBI) embarked on developing a case management software project titled “The Virtual Case File (VCF)” in 2000 to facilitate the FBI agents in progress in active investigations and connects them with each other. But FBI ultimately discarded the project in April 2005. This study demonstrates why the project titled “Virtual Case File” failed and analyses the reasons behind this failure. This meticulous analysis thoroughly examines the VCF project and suggests a few effective pointers to identify a dwindling IT project. This analytical study also explores the exclusivity of this project failure. This study discusses about a few effective suggestions that could have saved this huge IT project failure and future large IT projects. A dedicated chapter in this paper explains the possible winning factors for an IT project success. Finally, a selective chronology of the over-hyped VCF project has been illustrated in the final part of this paper.
A Low Order System Frequency ResponseModel for Large Power System and AdaptiveLoad Shedding

Now a days electrical system becomes very much large and Power demand will be increasing more and more. To satisfy the power demand nonconventional sources are incorporated in the field of electrical power generation and the system becomes Inter connected. Large power system disturbances sometimes causes interconnected system to become separated into some islands and it has either surplus of generation or load. If generation is more than it can be controlled by controlling the speed of speed governors connected with the generating station will result into change in frequency. This paper includes the derivation of simple low order system frequency response (SFR) model that can be used for estimating the frequency behaviour of the interconnected power system to sudden load disturbances. The SFR model is the simplify model to analyse system dynamics.
Report of NEWS 2009 Machine Transliteration Shared Task

This report documents the details of the Machine Transliteration Shared Task conducted as a part of the Named Entities Workshop (NEWS), an ACL-IJCNLP 2009 workshop. The shared task features machine transliteration of proper names from English to a set of languages. This shared task has witnessed enthusiastic participation of 31 teams from all over the world, with diversity of participation for a given system and wide coverage for a given language pair (more than a dozen participants per language pair). Diverse transliteration methodologies are represented adequately in the shared task for a given language pair, thus underscoring the fact that the workshop may truly indicate the state of the art in machine transliteration in these language pairs. We measure and report 6 performance metrics on the submitted results. We believe that the shared task has successfully achieved the following objectives: (i) bringing together the community of researchers in the area of Machine Transliteration to focus on various research avenues, (ii) Calibrating systems on common corpora, using common metrics, thus creating a reasonable baseline for the state-of-the-art of transliteration systems, and (iii) providing a quantitative basis for meaningful comparison and analysis between various algorithmic approaches used in machine transliteration. We believe that the results of this shared task would uncover a host of interesting research problems, giving impetus to research in this significant research area.
Conversation Code-switching in Class with Chinese as Foreign Language

This study focused on the function, forms, and frequency of conversation code-switching used by bilinguals in the class with Chinese as foreign language. Qualitative questionnaire and quantitative conversation audio data were collected and analyzed among 56 teachers and 315 overseas students as participants in the study. The questionnaire and data conversation analysis showed both teachers and students were free to use their L1 or L2 according to their own needs and desires, which meant code-switching was not as directly related to the target language proficiency as expected. Instead, it could be a strategy for successful class communication to repair trouble source in listening, understanding or expressing. In some cases, code-switching could be a turn mark to initiate a new turn or remind other participants to be attentive to catch the utterance at the possible transition relevant space (TRS). It also found code-switching between L2 and L1 possibly meant some trouble source initiated repair in understanding, expression or interaction especially in foreign language class conversation. Finally, neither teacher nor students meant to prefer L1 or L2, they preferred to switch to the appropriate language in sequence organization to make sure the class interaction could be carry on smoothly.
Time-frequency coherence analysis of nonstationary random processes

The coherence function is extended to nonstationary random processes through the introduction and investigation of a coherence operator and time-frequency (TF) coherence functions. For underspread nonstationary processes, it is shown that TF coherence functions are a meaningful tool for nonstationary coherence analysis and that they provide approximate TF formulations of the coherence operator.
IMPROVING PERFORMANCE AND SECURING DATA IN MANET WITH AES

Mobile ad-hoc network is wireless network composed of different nodes communicate with each other without having to establish infrastructure. The security of such network is a major concern. To improve the security of such network and to improve the efficiency of Adhoc on demand distance vector routing protocol technique proposed here is SMDNA (Securing MANET Data using Node Authentication) that combines the features of Symmetric and asymmetric cryptographic algorithms and digital signature. This protocol design provides the integrity, confidentiality, non repudiation and authentication with the help of AES, and digital signature. It shows better results in terms of end to end delay and throughput on varying number of nodes. This method also applied on other algorithms IDEA,DES. The results shows better performance with AES algorithm.