Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Path Computation Approach for Road Networks Based on Hierarchical Communities

Abstract The problem of efficient path computation arises in several applications such as intelligent transportation and network routing. Although various algorithms exist for computing shortest paths, their heavy precomputation/storage costs and/or query costs hinder their application to real-time routing. By detecting hierarchical community structure in road networks, we develop a community-based hierarchical graph model that supports efficient path computation on large road networks. We then propose a new hierarchical routing algorithm that can significantly reduce the search space over the conventional algorithms with acceptable loss of accuracy. Finally, we evaluate our approach experimentally using a large, real-world road network to show the gain in performance.
HUMAN FACTOR CONSIDERATIONS IN TRAFFIC FLOW THEORY

THE MANY TRAFFIC FLOW THEORY FORMULATIONS THAT HAVE BEEN OFFERED HAVE STIMULATED MUCH FUNDAMENTAL THINKING ON IMPORTANT PHASES OF TRAFFIC FLOW THEORY. A NUMBER OF DIFFERENT FORMULATIONS BASED MAINLY ON MATHEMATICAL AND PHYSICAL RELATIONSHIPS HAVE BEEN PROPOSED BUT NONE SEEMS AS YET TO BE GREATLY SUPERIOR TO ANOTHER. HUMAN FACTOR CONSIDERATIONS HAVE BEEN RECOGNIZED IN SOME BUT ACCORDED A MINOR ROLE IN MOST. THE PRESENT PAPER PROPOSES CERTAIN RELATIONSHIPS BASED ON EXPERIMENTAL INFORMATION FROM PREVIOUS EXPERIMENTAL STUDIES OF TRAFFIC FLOW BY THE INVESTIGATOR. MATHEMATICAL RELATIONSHIPS DEVELOPED FROM THESE ARE OFFERED AS IMPORTANT FOR TRAFFIC FLOW THEORY. DISCONTINUITIES IN CERTAIN PREVIOUS DATA MAY BE EXPLAINABLE ON THE BASIS OF THESE HUMAN FACTOR VARIABLES. /AUTHOR/
Joint scheduling and power control for wireless ad-hoc networks

In this paper we introduce power control as a solution to the multiple access problem in contention-based wireless ad-hoc networks. The motivation for this study is two fold, limiting multi-user interference to increase single-hop throughput, and reducing power consumption to increase battery life. We focus on next neighbor transmissions where nodes are required to send information packets to their respective receivers subject to a constraint on the signal-to-interference-and-noise ratio. The multiple access problem is solved via two alternating phases, namely scheduling and power control. The scheduling algorithm is essential to coordinate the transmissions of independent users in order to eliminate strong interference (e.g. self-interference) that can not be overcome by power control. On the other hand, power control is executed in a distributed fashion to determine the admissible power vector, if one exists, that can be used by the scheduled users to satisfy their single-hop transmission requirements. This is done for two types of networks, namely TDMA and TDMA/CDMA wireless ad-hoc networks.
Rate-adaptive H.264 for TCP/IP networks

Rate-Adaptive H.264 for TCP/IP Networks. (May 2006) Praveen Kota, B.Tech., Pondicherry University, Pondicherry Chair of Advisory Committee: Dr. Zixiang Xiong While there has always been a tremendous demand for streaming video over TCP/IP networks, the nature of the application still presents some challenging issues. These applications that transmit multimedia data over best-effort networks like the Internet must cope with the changing network behavior; specifically, the source encoder rate should be controlled based on feedback from a channel estimator that probes the network periodically. First, one such Multimedia Streaming TCP-Friendly Protocol (MSTFP) is considered, which iteratively integrates forward estimation of network status with feedback control to closely track the varying network characteristics. Second, a network-adaptive embedded bit stream is generated using a ρ -domain rate controller. The conceptual elegance of this ρ -domain framework stems from the fact that the coding bit rate ) (R is approximately linear in the percentage of zeros among the quantized spatial transform coefficients ) (ρ , as opposed to the more traditional, complex and highly nonlinear ) ( Q R − characterization. Though the ρ -model has been successfully implemented on a few other video codecs, its application to the emerging video coding standard H.264 is considered. The extensive experimental results show that the ρ -model outperforms the current rate control algorithm for H.264, with a more
Android malware detection based on permissions

In this paper, we propose a permission-based malware detection framework for Android platform. The proposed framework uses PCA(Principal Component Analysis) algorithm for features selection after permissions extracted, and applies SVM(support vector machine) methods to classify the collected data as benign or malicious in the process of detection. The simulation experimental results suggest that this proposed detection framework is effective in detecting unknown malware, and compared with traditional antivirus software, it can detect unknown malware effectively and immediately without updating the newest malware sample library in time. It also illustrates that using permissions features alone with machine learning methods can achieve good detection result.
A Study on the Effective Approaches to Big Data Planning

Abstract Big data analysis is a means of organizational problem solving. For an effective problem solving, approaches to problem solving should take into account the factors such as characteristics of problem, types and availability of data, data analytic capability, and technical capability. In this article we propose three approaches: logical top-down, data driven bottom-up, and prototyping for overcoming undefined problem circumstances. In particular we look into the relationship of creative problem solving with the bottom-up approach. Based on the organizational data governance and data analytic capability, we also derive strategic issues concerning the sourcing of big data analysis. Key Words : Big data planning, Data Convergence, Top-down approach, Bottom-up approach, Prototyping approach,Data governance * The research was supported by the 2014 Hannam University Research Fund.Received 5 November 2014, Revised 8 December 2014Accepted 20 January 2015Corresponding Author: Kyoo-Sung Noh (SunMoon University)Email: ksnoh@sunmoon.ac. krⒸ The Society of Digital Policy & Management. All rights reserved. This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is ISSN: 1738-1916 properly cited.
Analysis of and feedback on phonetic features in pronunciation training with a virtual teacher

Pronunciation errors may be caused by several different deviations from the target, such as voicing, intonation, insertions or deletions of segments, or that the articulators are placed incorrectly. Computer-animated pronunciation teachers could potentially provide important assistance on correcting all these types of deviations, but they have an additional benefit for articulatory errors. By making parts of the face transparent, they can show the correct position and shape of the tongue and provide audiovisual feedback on how to change erroneous articulations. Such a scenario however requires firstly that the learner's current articulation can be estimated with precision and secondly that the learner is able to imitate the articulatory changes suggested in the audiovisual feedback. This article discusses both these aspects, with one experiment on estimating the important articulatory features from a speaker through acoustic-to-articulatory inversion and one user test with a virtual pronunciation teacher, in which the articulatory changes made by seven learners who receive audiovisual feedback are monitored using ultrasound imaging.
Multi-swarm particle swarm optimiser with Cauchy mutation for dynamic optimisation problems

Many real-world problems are dynamic, requiring an optimisation algorithm which is able to continuously track a changing optimum over time. In this paper, we present a new variant of particle swarm optimisation (PSO) specifically designed to work well in dynamic environments. The main idea is to divide the population of particles into a set of interacting swarms. These swarms interact locally by dynamic regrouping and dispersing. Cauchy mutation is applied to the global best particle when the swarm detects the environment of the change. The dynamic function [proposed by Morrison and De Jong (1999)] is used to test the performance of the proposed algorithm. The numerical experimental results are compared with other variant PSO from the literature, showing that the proposed algorithm is an excellent alternative to track dynamically changing optima.
Radial basis function networks for speaker recognition

A speaker recognition system, using a modified form of feedforward neural network based on radial basis functions (RBFs), is presented. Each person to be recognized has his/her own neural model which is trained to recognise spectral feature vectors representative of his/her speech. Experimental results on a 40-speaker database indicate that the modified neural approach significantly outperforms both a standard multilayer perceptron and a vector quantization based system. The best performance for 4 digit test utterances is obtained from an RBF network with 384 RBF nodes in the hidden layer, given an 8% true talker rejection rate for a fixed 1% imposter acceptance rate. Additional advantages include a substantial reduction in training time over an MLP approach, and the ability to readily interpret the resulting model. <<ETX>>
Black-Hole and Wormhole Attack in Routing Protocol AODV in MANET

Mobile ad hoc network (MANET) is a self-configuring network that is formed automatically via wireless links by a collection of mobile nodes without the help of a fixed infrastructure or centralized management. The mobile nodes allow communication among the nodes outside the wireless transmission range by hop to hop and the forward packets to each other. Due to dynamic infrastructure-less nature and lack of centralized monitoring points, the ad hoc networks are vulnerable to attacks. The network performance and reliability is break by attacks on ad hoc network routing protocols. AODV is a important on-demand reactive routing protocol for mobile ad hoc networks. There is no any security provision against a “Black Hole” and “Wormhole” attacks in existing AODV protocol. Black hole nodes are those malicious nodes that conform to forward packet to destination. But they do not forward packet intentionally to the destination node. The black hole nodes degrade the performance of network eventually by participating in the network actively. The propose watchdog mechanism detect the black hole nodes in a MANET. This method first detects a black hole attack in the network and then provide a new route to this node. In this, the performance of original AODV and modified AODV in the presence of multiple black hole nodes is find out on the basis of throughput and packet delivery ratio. In a wormhole attack, intruders tunnel the data from one end of the network to the other, leading distant network nodes to trust they are neighbors’ and making them communicate through the wormhole link.
60 GHz Amplifier Employing Slow-wave Transmission Lines in 65-nm CMOS

A three-stage V-band amplifier implemented in 65-nm baseline CMOS technology is presented in this paper. Slow-wave coplanar waveguides are used for matching and interconnects to study the benefits of using this line type in amplifier design. Measured power gain, noise figure and 1 dB output compression point at 60 GHz are 13 dB, 6.3 dB and +4 dBm, respectively. The amplifier has 19.6 GHz of 3 dB bandwidth, thus covering entirely the unlicenced band around 60-GHz. The performance is achieved with a 1.2 V supply and 45 mA DC-current consumption.
Quantitative Calculation of Vibration Source Contributions of Submarines Based on Independent Component Analysis

Vibration noise control is of great significance to submarines. Vibration and noise source analysis methods that are commonly used only analyze the sources of vibration and noise, but sources contributions of submarine equipments are not calculated quantitatively. The basic model of blind source separation (BSS) and an improved fixed-point algorithm based on independent component analysis (ICA) are introduced, and the performance of BSS is improved by means of clustering evaluation. A new method to calculate the source contributions quantitatively based on the improved algorithm and priori information is proposed. The performances of BSS methods based on different separation criteria are compared in the simulations, and the result of sources contributions is analyzed. The new method is applied in quantitative calculation of vibration source contributions of a scaled submarine model, and the comparative result shows that it has high calculation accuracy. The conclusions provide a reliable evidence for the active control of vibration noise.
Technology Portfolio Assessments Using a Modified Genetic Algorithm Approach

A metallized layer is formed by active metal solder on the surface of a ceramic base material to be joined to a terminal electrode, and metal solder is interposed between the metallized layer and the electrode terminal to join the ceramic heater and the electrode terminal. The joined structure obtained provides for a higher reliability of the joining strength between the terminal joining portion of the heater and the electrode terminal, which prolongs the life of the heater.
Synthesis of the H-I-J Tricyclic Fragment of Ciguatoxin, a Marine Polyether Toxin

: During the course of our synthetic studies on ciguatoxin, synthesis of H-I-J tricyclic fragment has been stereoselectively achieved starting from a D -glucal derivative. The key steps are So-nogashira coupling reaction and cobalt complex-mediated oxocane cyclization.
Category Development Based on Semantic Principles

Category systems extracted from textual material are an important part of the scientific process and qualitative analysis but are frequently developed on an ad-hoc basis. Their development can be improved by a stronger reliance on linguistic and semantic principles. Tracing and recapitulating the development of semantic principles from the 1950s to the 1990s in linguistics and text analysis show how the principled use of information from lexical resources can facilitate the development and analysis of category systems. These principles are demonstrated in examining the category systems of Minnesota Contextual Content Analysis, a technique for analyzing textual material from sentences, answers to open-ended questions on questionnaires, expository texts, and verbatim transcripts. These principles are then extended to show how to abstract category assignments for this type of textual material. The discussion identifies computerized systems and data resources used in the application of these principles.
Cartographic Interaction Primitives: Framework and Synthesis

Abstract A cartographic interaction primitive is a basic unit of interactivity that is combined with other primitives in sequence when using interactive maps. The construction of a taxonomy of these basic interaction primitives is considered the ‘grand challenge of interaction’, as such taxonomies provide a consistent lexicon for describing map-based interaction strategies and interface designs, inform the design of scientific experiments to investigate the nature of cartographic interaction, and ultimately lead to design and use guidelines for interactive maps. The purpose of this research is not to offer a new framework of interaction primitives—as there are many in existence—but to organize and synthesize extant strategies for parsing interaction within Cartography and the related fields of Human–Computer Interaction, Information Visualisation, and Visual Analytics into a logical framework. Norman’s stages of action model provides a useful foundation for conceptualizing interaction primitives, with organisation of extant taxonomies by the model resulting in three dominant approaches for parsing interaction: (1) an objective-based approach, compartmentalizing cartographic interaction according to the kinds of tasks the user may wish to complete with a cartographic interface; (2) an operator-based approach, compartmentalizing cartographic interaction according to the unique cartographic interfaces that make manipulation of a cartographic representation possible; and (3) an operand-based approach, compartmentalizing cartographic interaction according to characteristics of the digital/virtual object with which the user is interacting. Extant interaction primitive taxonomies representative of each of these three approaches are treated in turn, synthesizing key themes within each approach and identifying important concordances and discordances across the associated taxonomies.
Analysis and Optimization of Resource Control in High-Speed Railway Wireless Networks

This paper considers a joint optimal design of admission control and resource allocation for multimedia services delivery in high-speed railway (HSR) wireless networks. A stochastic network optimization problem is formulated which aims at maximizing the system utility while stabilizing all transmission queues under the average power constraint. By introducing virtual queues, the original problem is equivalently transformed into a queue stability problem, which can be naturally decomposed into three separate subproblems: utility maximization, admission control, and resource allocation. A threshold-based admission control strategy is proposed for the admission control subproblem. And a distributed resource allocation scheme is developed for the mixed-integer resource allocation subproblem with guaranteed global optimality. Then a dynamic admission control and resource allocation algorithm is proposed, which is suitable for distributed implementation. Finally, the performance of the proposed algorithm is evaluated by theoretical analysis and numerical simulations under realistic conditions of HSR wireless networks.
A neural-network-based approach for routing in a packet switching network

The authors report on routing in the packet switching network through a neural approach. The results obtained from a comparison between the latter and a minimum path algorithm are on average very similar. Each communication node learns the optimal results of a centralized routing algorithm (the Dijkstra one). This global information allows the node to operate a distributed routing in the production phase, identifying the adjacent node to which a packet is to be passed. The behavior of the neural approach is discussed and compared with the classical one. <<ETX>>
Modeling Self-Selection Bias in Interactive-Communications Research

Interactive media use is a key issue in contemporary and future communication research. However, when users can interact with messages, new sources of variation emerge that make generalization difficult. This article introduces methods that communication researchers can use to increase the external validity of studies investigating the effects of interactivity versus noninteractivity. For this area of research, the article recommends the use of forced-interaction studies with random assignment to maximize internal validity, and free-interaction studies with self-selection bias modeling to maximize external validity. The article concludes with examples of self-selection bias modeling, using data from real studies, and a discussion of their implications for communication researchers.
File grafting in market research

We present a statistical methodology, which we call File grafting, to visualize information coming from two independent data sets. For this purpose it is necessary that both data sets share a certain group of variables defining a common space which act as a hinge between the two data sets. Moreover, certain conditions should be fulfilled to control the whole process and interpret the issued results. Finally, we apply this methodology to assess the efficiency of an advertizing campaign of a product, visualizing together the TV audience of the corresponding spots and its relative change in consumption. Copyright © 1999 John Wiley & Sons, Ltd.
Image Representations for Visual Learning

Computer vision researchers are developing new approaches to object recognition and detection that are based almost directly on images and avoid the use of intermediate three-dimensional models. Many of these techniques depend on a representation of images that induces a linear vector space structure and in principle requires dense feature correspondence. This image representation allows the use of learning techniques for the analysis of images (for computer vision) as well as for the synthesis of images (for computer graphics).
A High Performance Co-design of 26 nm 64 Gb MLC NAND Flash Memory using the Dedicated NAND Flash Controller

It is progressing as new advents and remarkable developments of mobile device every year. On the upper line reason, NAND FLASH large density memory demands which can be stored into portable devices have been dramatically increasing. Therefore, the cell size of the NAND Flash memory has been scaled down by merely 50% and has been doubling density each per year. [1] However, side effects have arisen the cell distribution and reliability characteristics related to coupling interference, channel disturbance, floating gate electron retention, write-erase cycling owing to shrinking around 20㎚ technology. Also, FLASH controller to manage shrink effect leads to speed and current issues. In this paper, It will be introduced to solve cycling, retention and fail bit problems of sub-deep micron shrink such as Virtual negative read used in moving read, randomization. The characteristics of retention, cycling and program performance have 3 K per 1 year and 12.7 MB/s respectively. And device size is 179.32 ㎟ (16.79 ㎜ × 10.68 ㎜) in 3 metal 26 ㎚ CMOS.
Ontology-based Why-Question Analysis Using Lexico-Syntactic Patterns

This research focuses on developing a method to analyze why-questions. Some previous researches on the why-question analysis usually used the morphological and the syntactical approach without considering the expected answer types. Moreover, they rarely involved domain ontology to capture the semantic or conceptualization of the content. Consequently, some semantic mismatches occurred and then resulting not appropriate answers. The proposed method considers the expected answer types and involves domain ontology. It adapts the simple, the bag-of-words like model, by using semantic entities (i.e., concepts/entities and relations) instead of words to represent a query. The proposed method expands the question by adding the additional semantic entities got by executing the constructed SPARQL query of the why-question over the domain ontology. The major contribution of this research is in developing an ontology-based why-question analysis method by considering the expected answer types. Some experiments have been conducted to evaluate each phase of the proposed method. The results show good performance for all performance measures used (i.e., precision, recall, undergeneration, and overgeneration). Furthermore, comparison against two baseline methods, the keyword-based ones (i.e., the term-based and the phrase-based method), shows that the proposed method obtained better performance results in terms of MRR and P@10 values.