Miracle-dz/UniFAR-FTUs huggingface dataset:
Network Coordinates-Based Request Routing Approach to Improve Multimedia Content Delivery

In order to solve the problem of large-scale multimedia content delivery, we present Multimedia Content Delivery Network (MM-CDN). For providing multimedia services with high quality in MM-CDN, the traditional request routing approaches in CDN face two key challenges, namely performance and cost. To balance the tradeoff between performance and cost in MM-CDN, we propose an improved request routing approach. First, based on the idea of network coordinates, the computation and transfer costs of different server clusters are computed depending on the network and server status change. Then, all the server clusters are reorganized in the coordinate space. Finally, user requests can be adaptively redirected to the server clusters with minimum cost without sacrificing performance. Computational results show that the effectiveness of our approach with acceptable time performance.
Multicast routing and wavelength assignment in WDM networks: a bin packing approach

We address the problem of multicast routing and wavelength assignment (MClowbarRWA) in wavelength-routed WDM optical networks. Multicast requests are facilitated in WDM networks by setting up so-called light trees and assigning wavelengths to them. Objectives of the MClowbarRWA problem include minimizing the number of distinct wavelengths used to establish a set of multicast requests and minimizing the cost of the corresponding light trees. This cost can represent the physical length, delay, or actual cost of a tree. Applications that require quality of service (QoS) multicasting can impose additional constraints on light trees, such as a bounded end-to-end delay. Proposed are heuristic algorithms based on bin packing methods for the general MClowbarRWA problem, which is NP complete. These algorithms can consider unicast, multicast, and broadcast requests with or without QoS demands. Computational tests indicate that these algorithms are efficient, particularly for dense networks.
Ferment in Business Education: E-Commerce Master's Programs

Abstract Business schools are developing strategies to prepare students for the new digital economy. In this study, the authors investigated recently launched master's programs in e-commerce by reviewing the curriculum and course descriptions of 67 programs that had Web listings of their programs. Findings suggest that the programs offered more nontechnical e-commerce courses than courses focusing on e-commerce technology. The authors explored the debate between those who believe e-commerce is a new discipline requiring its own degree programs and those who would weave e-commerce content into existing functional area courses.
Performance of soft-output space-time equalization for EGPRS

The use of antenna arrays can help to combat cochannel interference (CCI) in wireless cellular systems. In interference-limited scenarios, spatio-temporal filtering techniques based on a deterministic least-square (LS) approach may be competitive with respect to trellis based algorithms, because of the difficulties of accurately modelling the space-time characteristics of CCI. We consider the impact on the receiver performance of the quality of the reliability information on the coded bits, computed at the output of the deterministic space-time equalizer. Simulation results are provided for an EGPRS receiver employing linear and decision-feedback training-based filtering techniques.
Who Solved the Secretary Problem

In Martin Gardner's Mathematical Games column in the February 1960 issue of Scientific American, there appeared a simple problem that has come to be known today as the Secretary Problem, or the Marriage Problem. It has since been taken up and developed by many eminent probabilists and statisticians and has been extended and generalized in many different directions so that now one can say that it constitutes a "field" within mathematics-probability-optimization. The object of this article is partly historical (to give a fresh view of the origins of the problem, touching upon Cayley and Kepler), partly review of the field (listing the subfields of recent interest), partly serious (to answer the question posed in the title), and partly entertainment. The contents of this paper were first given as the Allen T. Craig lecture at the University of Iowa, 1988.
On-Line Signature Verification Utilizing 3-Axis Force Features Extraction Based on DWT

Automatic on-line signature verification is an intriguing intellectual challenge with wide attention and practical applications. We examined the validation of the new dynamic features for on-line signature verification, which extracted from 3-axis forces of pen-tip to writing tablet with application of discrete wavelet transform (DWT). The force signals were decomposed into sub-band signals by DWT and individual features were extracted as locations of modulus maximum in detail and the values of the wavelet transform at the corresponding location. Verification was achieved by using dynamic time warping (DTW) and total decision was done by combining multiple thresholds. Experimental results indicate the effectiveness of the dynamic features for on-line signature verification described in this paper.
Decision making process via binary decision diagram

Firms require to optimize any decisions taken for increasing their competitiveness. Each decision will depend of a large number of causes. The relations between the causes and the decisions are effected by the decision making process. An approach to finding the best solution to each logistical or organizational problem is to identify the main causes which are involved for the best decision. A qualitative and a quantitative analysis to facilitate the decision making process is carried out in this paper employing logical decision trees together with binary decision diagrams. This paper presents a novel comparison between different ranking methods applied to several case studies of logical decision trees. The ranking methods considered in this paper are ‘Level’, ‘AND’ and the topological heuristic methods Top-Down-Left-Right, Depth-First-Search and Breath-First-Search. Importance measures have been used for ranking the basic events of the logical decision trees according to their contribution to the top event in order to establish the main causes and, therefore, to determine the critical causes. The importance measures methods employed in this paper are: Fussell–Vesely, Birnbaum and criticality. Finally, an analysis of these importance measures is performed that is based on a comparative study of the different methods for setting the importance measures in order to determine the differences between them.
Study on a New Modeling Method of Equipment Support Base on Ontology

In this paper, it studies the Ontology construction ofequipment support system with the Ontology construction technology. In the buildingprocess, the “Seven Step Method” has been improved, and it puts forward a new method suitable for the equipment support system. Then analyze the equipment support system in detail with system analysis method to build Ontology. Through the study, it aims at building up a sharing and reusing conceptual model.
Automatic language recognition using acoustic features

Two language recognition algorithms are proposed and some experimental results are described. While many studies have been done concerning the speech recognition problem, few studies have addressed the language recognition task. The speech data used contains 20 languages: 16 sentences uttered twice by 4 males and 4 females. The duration of each sentence is about 8 seconds. The first algorithm is based on the standard vector quantization (VQ) technique. Every language is characterized by its own VQ codebook. The second algorithm is based on a single universal (common) VQ codebook for all languages, and its occurrence probability histograms. Every language is characterized by a histogram. The experiment results show that the recognition rates for the first and second algorithms were 65% and 80%, respectively, each using just 8 sentences of unknown speech (about 64 seconds). <<ETX>>
A sharpness measure on automatically selected edge segments

We address the problem of image quality assessment for natural images, focusing on No Reference (NR) assessment methods for sharpness. The metrics proposed in the literature are based on edge pixel measures that significantly suffer the presence of noise. In this work we present an automatic method that selects edge segments, making it possible to evaluate sharpness on more reliable data. To reduce the noise influence, we also propose a new sharpness metric for natural images.
JVM-based Techniques for Improving Java Observability

Observability measures the support of computer systems to accurately capture, analyze, and present (collectively observe) the internal information about the systems. Observ-ability frameworks play important roles for program understanding, troubleshooting, performance diagnosis, and optimizations. However, traditional solutions are either expensive or coarse-grained, consequently compromising their utility in accommodating today's increasingly complex software systems. New solutions are emerging for VM-based languages due to the full control language VMs have over program executions. Existing such solutions, nonetheless, still lack flexibility, have high overhead, or provide limited context information for developing powerful dynamic analyses. In this thesis, we present a VM-based infrastructure, called marker tracing framework (MTF), to address the deficiencies in the existing solutions for providing better observability for VM-based languages. MTF serves as a solid foundation for implementing fine-grained low-overhead program instrumentation. Specifically, MTF allows analysis clients to: 1) define custom events with rich semantics ; 2) specify precisely the program locations where the events should trigger; and 3) adaptively enable/disable the instrumentation at runtime. In addition, MTF-based analysis clients are more powerful by having access to all information available to the VM. To demonstrate the utility and effectiveness of MTF, we present two analysis clients: 1) dynamic typestate analysis with adaptive online program analysis (AOPA); and 2) selective probabilistic calling context analysis (SPCC). In addition, we evaluate the runtime performance of MTF and the typestate client with the DaCapo benchmarks. The results show that: 1) MTF has acceptable runtime overhead when tracing moderate numbers of marker events; and 2) AOPA is highly effective in reducing the event frequency for the dynamic typestate analysis; and 3) language VMs can be exploited to offer greater observability. iv Acknowledgement I am deeply grateful to Witawas Srisa-an for supporting and mentoring me throughout my master studies. Dr. Srisa-an has provided invaluable technical expertise and feedback in all projects we have taken. Dr. Srisa-an kindly accepted me into his group and guided me enter the field of computer system research. He is always enthusiastic and positive about research ideas and projects, and teaches me research and writing skills. It has been a great honor and pleasure for me to conduct research under his supervision. I am also indeted to Matthew Dwyer, co-advisor of my master project. I am thankful to his guidance, support and encouragement. Dr. Dwyer not only originated the ideas in this research, but also offered invaluable expertises and insights. My research has …
2‐(4‐Bromo­phen­yl)‐5,7‐dimeth­yl[1,3]oxazolo[3,2‐a]pyrimidin‐4‐ium perchlorate

The title compound, C14H12BrN2O+·ClO4−, was synthesized from the parent 2-amino­oxazole and acetyl­acetone and characterized by 1H NMR and single-crystal X-ray diffraction. The bromo­phenyl fragment and the essentially planar nine-membered bicyclic system form a dihedral angle of 10.50 (11)°.
Modular reinforcement learning with adaptive networks

A modular reinforcement learning system (modular RL) with adaptive networks was proposed for applying the reinforcement learning into control tasks with numerous inputs. It is composed of several control modules and a selection module. All its modules are calculated by using the incremental normalised Gaussian networks (INGnet). The modular RL (INGnet) showed a better learning ability in all three control tasks performed in this study than the modular reinforcement learning whose all modules are calculated by CMAC [modular RL (CMAC)]. It showed a better or similar learning ability to the reinforcement learning using INGnet [RL (INGnet)]. From the simulation results obtained in this study, the modular RL (INGnet) is considered to have a better learning ability in the control tasks with a large number of inputs (8–10) than the modular RL (CMAC) and the RL (INGnet).
Simulation of queueing systems with many stations and of queueing networks using copulas

In this paper we will generate queueing systems with c stations where the inter-arrival time and the c service times depend through a c+1 copula C. We will consider two models: first when the customer does not know the order of service times for the free service channels (he/she chooses the service channel randomly), and the second when he/she knows this order (he/she chooses the fastest free service channel). The marginals can be exponential, Erlang or hyper-exponential.
Construction of panoramic image mosaics based on affine transform and graph cut

Image-based rendering has been a popular technique to simulate a visually rich telepresence and virtual reality experience. The construction of panoramic image mosaics is an indispensable step in image-based rendering systems like QuickTime VR and Surround Video. The conventional methods for creating panoramic image mosaics with regular photographic or video images use geometrical feature points and optimization to the overlapped areas of the two consecutive images, and then align and mosaic the corresponding areas using the blending or stitching algorithm. This paper introduces a novel and efficient method to build panoramic image mosaics. The proposed method divides the overlapped areas of the consecutive images into several sub-areas. The feature point, whose gradient value of intensity is the maximum in the sub-area can be found easily. After selecting these feature points, we warp the images using an affine transformation based on point set matching. Then the graph cut algorithm is used to build the seamless image mosaic which makes the overlapped areas containing no visible ghosting or blurred details. It is shown by the experiments that the new method can obtain mosaics of high quality and reduce the computing time.
A predictive algorithm for current controlled voltage source inverter

The basic idea of a predictive algorithm discussed in the paper is illustrated with help of the space vector method. Inverter switchings occur in a time instant predicted and are synchronised with a sampling wave. While a successive vector is acting, the current error vector is anticipated and the vector expected is selected. Its operational time is calculated as a multiple of sampling periods. Useful expressions facilitating indispensable calculations are presented as well as a condition of precision application of zero voltage vectors. <<ETX>>
Soft combining for hybrid ARQ

A soft combining approach utilising symbol-by-symbol maximum a posteriori probability decoding is proposed for hybrid automatic repeat request schemes. In comparison to an existing soft combining approach, significant reductions in post-decoding bit error rate can be obtained without sacrificing the throughput efficiency. This is achieved with the proposed method by accumulating the signal-to-noise ratio at the channel output on each additional retransmission, for use in calculating extrinsic log-likelihood ratios on subsequent decoding attempts.
Zero forcing and minimum mean-square-error equalization for multiuser detection in code-division multiple-access channels

In code-division multiple-access (CDMA) systems transmitting over time-varying multipath channels, both intersymbol interference (ISI) and multiple-access interference (MAI) arise. The conventional suboptimum receiver consisting of a bank of matched filters is often inefficient because interference is treated as noise. The optimum multiuser detector is too complex to be implemented at present. Four suboptimum detection techniques based on zero forcing (ZF) and minimum mean-square-error (MMSE) equalization with and without decision feedback (DF) are presented and compared. They combat both ISI and MAI. The computational complexity of all four equalizers is essentially the same. All four equalizers are independent of the size of the data symbol alphabet. It is shown that the performance of the MMSE equalizers is better than that of the corresponding ZF equalizers. Furthermore, the performance of the equalizers with DF is better than that of the corresponding equalizers without DF. The impairing effect of error propagation on the equalizers with DF is reduced by channel sorting.
A Moving Object Detection Algorithm Based on Joint Gradient

Intelligent video retrieval is a prominent problem in police video investigation. In this paperwe propose a moving object detection algorithm which is based on jointing the Time gradient and theSingle-frame gradient of a video. Firstly, the concept of the joint gradient was discussed. Secondly,the algorithm steps and related descriptions were listed. The algorithm has been tested in a typicalvideo database. Finally, the experimental results and discussions were given at the end of the article.The results showed that this algorithm has good performance both in accuracy and robustness. Also,it has a fast execution speed. It is expected to be further used in police video investigation.
Adaptive data fusion

An adaptive algorithm for multi-sensor/data fusion is developed. The algorithm can be employed in an uncertain sensed environment using imperfect sensors. Assuming little prior information about the sensed environment and the sensors, the algorithm adaptively adjusts the weights for the best fusion of inaccurate information provided by the multiple sensors. The algorithm is general, computationally efficient, and very suitable for dynamic sensor fusion. The effectiveness of the algorithm is demonstrated by an example. <<ETX>>
Clustering techniques and their applications in engineering

Abstract Clustering is an important data exploration technique with many applications in different areas of engineering, including engineering design, manufacturing system design, quality assurance, production planning and process planning, modelling, monitoring, and control. The clustering problem has been addressed by researchers from many disciplines. However, efforts to perform effective and efficient clustering on large data sets only started in recent years with the emergence of data mining. The current paper presents an overview of clustering algorithms from a data mining perspective. Attention is paid to techniques of scaling up these algorithms to handle large data sets. The paper also describes a number of engineering applications to illustrate the potential of clustering algorithms as a tool for handling complex real-world problems.
Dynamic retransmission limit scheme in MAC layer for routing in multihop ad hoc networks

We consider a wireless ad hoc network with random access channel. We present a model that takes into account topology, routing, random access in MAC layer, and forwarding probability. In this paper, we focus on drawing benefit from the interaction of the MAC (governed by IEEE 802.11 or slotted Aloha) and routing by defining a new cross-layer scheme for routing based on the limit number of retransmission. By adjusting dynamically and judiciously this parameter in a saturated network, we have realized that both stability of forwarding queues and average throughput are significantly improved in linear networks with symmetric traffic: a gain of 100% can be reached. While in asymmetric topology network with asymmetric traffic, we achieve a better average delay (resp., throughput) for each connection without changing the average throughput (resp., delay). In addition, we show the efficiency of our new scheme in case of multimedia applications with delay constraint. A detailed performance study is presented using analytical and simulation evaluation.
Research of Real-Time Data Presentation of Cloud Monitoring Based on Highcharts

Based on industry, agriculture and rail transit to the data in real-time monitoring tasks, this paper proposes a new cloudmonitoring method, it mainly studies the real-time data presentation.This article uses the graphical component of Highcharts and the dataextraction technology of JQuery, it can present efficient real-time data to managers, it can also make managers learn quickly the shape of the data and the possibility of adverse conditions.
Extension of the ICP algorithm to non-rigid intensity-based registration of 3D volumes

Presents a new registration and gain correction algorithm for 3D medical images. It is intensity based. The basic idea is to represent the images by 4D points (x/sub j/, y/sub j/, z/sub j/, i/sub j/) and to define a global energy function based on this representation. For minimization, the authors propose a technique which does not require to compute the derivatives of this criterion with respect to the parameters. It can be understood as an extension of the Iterative Closest Point algorithm (P. Besl and N. McKay, 1992; Z. Zhang, 1992) or as an application of the formalism proposed by L. Cohen (Use of auxiliary variables in computer vision problems. In Proceedings of the Fifth International Conference on Computer Vision (ICCV '95), Boston, June 1995). Two parameters allow one to have a coarse to fine strategy both for resolution and deformation. The authors' technique presents the advantage to minimize a well defined global criterion to deal with various classes of transformations (for example rigid, affine and volume spline), to be simple to implement and to be efficient in practice. Results on real brain and heart 3D images are presented to demonstrate the validity of the authors' approach.
Distributed real-time processing using GNU/Linux/libré software and COTS hardware

This dissertation's research aims at studying the viability of using both low cost consumer Commodity Off The Self (COTS)PCs and libn~software in implementing a distributed real-time system modeled on a real-world engineering problem. Debugging and developing a modular satellite system is both time consuming and complex, to this end the SUNSATteam has envisioned the Interactive Test System that would be a dual mode simulator/monitoring system. It is this system that requires a real-time back-end and is used as a real world problem model to implement. The implementation was accomplished by researching the available parallel processing software and real-time extensions to GNU/Linux and choosing the appropriate solutions based on the needs of the model. A monitoring system was also implemented, for system verification, using freely available system monitoring utilities. The model was successfully implemented and verified with a global synchronization of < 10ms. It was shown that GNU/Linux and libn~ software is both mature enough and appropriate in solving a real world distributed real-time problem. ii Stellenbosch University http://scholar.sun.ac.za