Miracle-dz/UniFAR-FTUs huggingface dataset:
Reliable Resource Provision Policy for Cloud Computing

Cloud computing has become a hot topic,researchers proposed various resource sharing technique and resource provision technique.However,very limited literatures pay attentions to the reliability of dynamically provided resources.This paper proposes failure rules aware node resource provision policies for heterogeneous services consolidated in cloud computing infrastructure,and evaluates the proposed policy with simulation approach,i.e.,implements a simulator of heterogeneous service consolidation platform,which take characteristics of heterogeneous services(both characteristics of resource utility and failure rules),into consideration,and uses two production traces to synthesize inputs.In order to evaluate wide ranges of failure rules,this paper proposes a multi-dimension failure modeling framework,i.e.,adapt various factors about failure distribution involving temporal and spatial factors to study the proposed policy's capability.The results of evaluation indicate that the proposed resource provision policy is effective for providing robust nodes for heterogeneous services,i.e.,the policy can mask more potential node reboot failures from services and leave less chances of unplanned failures,e.g.,service failure or node reboot,compared with baseline fault re-provided policy.In addition,the policy is able to mask non-uniformly distribution among resource's reliability system wide.Meanwhile,the policy involves no negative impact on service performance and on node's resource utility,compared with baseline policy.Evaluation with failure rules about temporal and spatial factors indicates that the policy is useful for could computing environment.
What do students think about group work in business education? An investigation into the benefits, challenges, and student-suggested solutions

ABSTRACT The authors sought to gain insight on how students view group learning and development as part of their business education experience. Specifically, the authors categorize benefits and challenges using S. A. Wheelan's (2005) integrated model of group development. Additionally, they investigate (from the students' perspective) best practices that instructors can implement to improve students' group work experience. As group work is critical in business classrooms, the authors suggest instructors should focus more on the earlier stages of group development by assigning groups based on students' strengths and weaknesses, offering a better introduction to groups, and assigning more group-related time or meetings during class.
Minimum-Cost Cloud Storage Service Across Multiple Cloud Providers

Many Cloud Service Providers (CSPs) provide data storage services with datacenters distributed worldwide. These datacenters provide different Get/Put latencies and unit prices for resource utilization and reservation. Thus, when selecting different CSPs' datacenters, cloud customers of globally distributed applications (e.g., online social networks) face two challenges: (i) how to allocate data to worldwide datacenters to satisfy application SLO (service level objective) requirements including both data retrieval latency and availability, and (ii) how to allocate data and reserve resources in datacenters belonging to different CSPs to minimize the payment cost. To handle these challenges, we first model the cost minimization problem under SLO constraints using integer programming. Due to its NP-hardness, we then introduce our heuristic solution, including a dominant-cost based data allocation algorithm and an optimal resource reservation algorithm. We finally introduce an infrastructure to enable the conduction of the algorithms. Our trace-driven experiments on a supercomputing cluster and on real clouds (i.e., Amazon S3, Windows Azure Storage and Google Cloud Storage) show the effectiveness of our algorithms for SLO guaranteed services and customer cost minimization.
Study of a new central compact object: The neutron star in the supernova remnant G15.9+0.2

We present our study of the central point source CXOU J181852.0−150213 in the young Galactic supernova remnant (SNR) G15.9+0.2 based on the recent ~90 ks Chandra observations. The point source was discovered in 2005 in shorter Chandra observations and was hypothesized to be a neutron star associated with the SNR. Our X-ray spectral analysis strongly supports the hypothesis of a thermally emitting neutron star associated with G15.9+0.2. We conclude that the object belongs to the class of young cooling low-magnetized neutron stars referred to as central compact objects (CCOs). We modeled the spectrum of the neutron star with a blackbody spectral function and with our hydrogen and carbon neutron star atmosphere models, assuming that the radiation is uniformly emitted by the entire stellar surface. Under this assumption, only the carbon atmosphere models yield a distance that is compatible with a source located in the Galaxy. In this respect, CXOU J181852.0−150213 is similar to two other well-studied CCOs, the neutron stars in Cas A and in HESS J1731−347, for which carbon atmosphere models were used to reconcile their emission with the known or estimated distances.
Design and research of voltage tunable bandpass filters

This paper studies how to realize an voltage tunable bandpass filters by means of transmission line with loaded capacitors. The design technique of filter based on design criteria is provided, and design scheme of microstrip line combline filters is discussed in details. In the end, some methods that may analyse and improve filters when tuned and calibrated are presented.
One of semi-supervised classification algorithm named Co-S3OM based on cooperative training

In order to improve the classification effectiveness of semi-supervised classification,this paper designed a semi-supervised classification algorithm based on SOM neural network and collaborative training. It divided the limited labeled samples into three equal training sets and respectively used supervised SOM algorithm to train the three single classifier. It mined the implicit information of unlabeled samples by voting together through three single classifier to expand the number of labeled samples,extend a single classifier training set and generate the final classifier. Finally,experiment results conduct on UCI data set show that Co-S3OM has a higher labeling rate and classification rate.
Warm and dense stellar matter under strong magnetic fields

We investigate the effects of strong magnetic fields on the equation of state of warm stellar matter as it may occur in a protoneutron star. Both neutrino-free and neutrino-trapped matter at a fixed entropy per baryon are analyzed. A relativistic mean-field nuclear model, including the possibility of hyperon formation, is considered. A density-dependent magnetic field with a magnitude of 10{sup 15} G at the surface and not more than 3x10{sup 18} G at the center is considered. The magnetic field gives rise to a neutrino suppression, mainly at low densities, in matter with trapped neutrinos. It is shown that a hybrid protoneutron star will not evolve into a low-mass black hole if the magnetic field is strong enough and the magnetic field does not decay. However, the decay of the magnetic field after cooling may give rise to the formation of a low-mass black hole.
Catalytic Asymmetric Carbon−Carbon Bond Formations: Their Evolution from Biocatalysis to Organocatalysis over the Millennium

Illustrative discussion is made in chronological order on six select catalysts for asymmetric carbon−carbon bond formations that are scalable and are reported to be potentially scalable: (1) thiamine diphosphate (TPP)-bound pyruvate decarboxylase (PDC) used in the industrial production of (R)-l-phenyl acetyl carbinol (PAC; 5); (2) bimetallic Lewis acid−Bronsted base catalyst (9) for asymmetric Michael addition of dialkyl malonates; (3) Lewis acid−Lewis base catalyst (11) for asymmetric cyanosilylation of aryl alkyl ketones; (4) a chiral Schiff base chelated titanium(IV) alkoxide catalyst (32) for asymmetric addition of diketene to aldehydes; (5) 2-deoxyribose-5-phosphate aldolase (DERA) used in the preparation of (3R,5S)-6-chloro-2,4,6-trideoxy-erythro-hexose in its lactol form (50) from acetaldehyde (43)/chloroacetaldehyde (47) (2:1); and (6) chiral C2-symmetric quaternary ammonium bromides, such as 63 of an N-spiro type, for asymmetric alkylation of Schiff bases of glycine and α-substituted glycine der.
Joint pricing of multiple types of rooms in hotel under customer choices

This paper studies the joint optimal pricing problem when the demands for multiple types of rooms depend on the manager’s pricing strategies.First,we present an idea that all room types are classified by whether their demands have interactive impacts.Second,under the assumption of customers staying at the hotel only for a single night,we describe the dynamic pricing process of the hotel manager with a stochastic and dynamic model,and describe the customer’s choice behavior with a Nested Logit(NL) discrete choice model.We also design an algorithm to solve the optimal price strategy.Experimental results show that,compared to cases that do not consider the influence of pricing strategies among different types of rooms,the model that consider the interactive impacts of demands between different types of rooms can achieve more benefit,higher expectation of room occupancy rate and lower average room price.
Silicon Photonics Design: From Devices to Systems

Part I. Silicon Photonics - Introduction: 1. Fabless Silicon Photonics: 1.1 Introduction 1.2 Silicon photonics - the next fabless semiconductor industry 1.3 Applications 1.4 Technical challenges and the state of the art 1.5 Opportunities 2. Modelling and Design Approaches: 2.1 Optical Waveguide Mode Solver 2.2 Wave Propagation 2.3 Optoelectronic models 2.4 Microwave Modelling 2.5 Thermal Modelling 2.6 Photonic Circuit Modelling 2.7 Physical Layout 2.8 Software Tools Integration Part II. Silicon Photonics - Passive Components: 3. Optical Materials and Waveguides: 3.1 Silicon-on-Insulator 3.2 Waveguides 3.3 Bent waveguides 3.4 Code Listings 3.5 Problems 4. Fundamental Building Blocks: 4.1 Directional couplers 4.2 Y-Branch 4.3 Mach-Zehnder Interferometer 4.4 Ring resonators 4.5 Waveguide Bragg Grating Filters 4.6 Code Listings 4.7 Problems 5. Optical I/O: 5.1 The challenge of optical coupling to silicon photonic chips 5.2 Grating Coupler 5.3 Edge Coupler 5.4 Polarization 5.5 Code Listings 5.6 Problems Part III. Silicon Photonics - Active Components: 6. Modulators: 6.1 Plasma Dispersion E 6.2 PN Junction Phase Shifter 6.3 Micro-ring Modulators 6.4 Forward-biased PIN Junction 6.5 Active Tuning 6.6 Thermo-Optic Switch 6.7 Code Listings 6.8 Problems 7. Detectors: 7.1 Performance Parameters 7.2 Fabrication 7.3 Types of detectors 7.4 Design Considerations 7.5 Detector modelling 7.5.2 Electronic Simulations 7.6 Code Listings 7.7 Problems 8. Lasers: 8.1 External Lasers 8.2 Laser Modelling 8.3 Co-Packaging 8.4 Hybrid Silicon Lasers 8.5 Monolithic Lasers 8.6 Alternative Light Sources 8.7 Problems Part IV. Silicon Photonics - System Design: 9. Photonic Circuit Modelling: 9.1 Need for photonic circuit modelling 9.2 Components for System Design 9.3 Compact Models 9.4 Directional Coupler - Compact Model 9.5 Ring Modulator - Circuit Model 9.6 Grating Coupler - S Parameters 9.7 Code Listings 10. Tools and Techniques: 10.1 Process Design Kit (PDK) 10.2 Mask Layout 11. Fabrication: 11.1 Fabrication Non-Uniformity 11.2 Problems 12. Testing and Packaging: 12.1 Electrical and Optical Interfacing 12.2 Automated Optical Probe Stations 12.3 Design for Test 13. Silicon Photonic System Example: 13.1 Wavelength Division Multiplexed Transmitter.
Research on High Speed Parallel Blind Equalization Algorithm

Abstract. The paper presents an efficient high speed parallel blind equalization algorithm suitable for multi-mode signals in wireless communication system. The parallel algorithm combines the idea of coordinate transformation on the basis of the classical CMA. It converts a multi-mode signals into a constant-mode signal, so that the system error can be more toward zero. We also give a detailed implementation structure of the parallel blind equalization algorithm. The simulation results show that the proposed parallel blind equalization algorithm has excellent performance for modulated multi-mode signals, and the mean square error (MSE) value of the proposed algorithm is smaller than the classic CMA about 10dB.
Design and Realization of Embedded Fog-degraded Image Contrast Enhancement System

An embedded high speed image enhancement processing system on high performance DSP TMS320C6418 and FPGA is designed,and a color image enhancement algorithm is presented. Firstly,the color image is transformed from RGB to HIS. Then,histogram equalization enhancement is adopted in the brightness image. Finally,the color image is transformed from RGB to HIS. Experimental results with real images show that the system can improve the contrast of the fog-degraded image,effectively enhance the color image,and the running time of the program is shorter,which can meet the project.
Syntax A Generative Introduction

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Reconfiguration of flight control systems for actuator failures

We consider the problem of designing fault tolerant control for transient failures in the flight control system caused by harsh electromagnetic environments. We examine principles of fault tolerant design, and discuss integrated local supervisory control of these systems. As an example, we present a sample design of a control mixer to achieve fault tolerance in the event of failures in the actuators.
Model Based Sparse Feature Extraction for Biomedical Signal Classification

This article focuses on model based sparse feature extraction of biomedical signals for classification problems, which stems from sparse representation in modern signal processing. In the presented work, a novel approach based on sparse principal component analysis (SPCA) is proposed to extract signal features. This method involves partitioning signals and utilizing SPCA to select only a limited number of signal segments in order to construct signal principal components during the training stage. For signal classification purposes, a set of regression models based on sparse principal components of the selected training signal segments is constructed. Within this approach, model residuals are estimated and used as signal features for classification. The applications of the proposed approach are demonstrated by using both the synthetic data and real EEG signals. The high classification accuracy results suggest that the proposed methods may be useful for automatic event detection using long-term observational signals. keywords : Sparse Principal Component Analysis, Sparse Feature Extraction, Signal Classification, Long-term Signals
Token Based Trust Computation in VANET

In vehicular ad hoc network or VANET, the safety related messages broadcast by vehicles is used by other vehicles to make critical decisions. This may trap a vehicle taking wrong decision with dire consequences and authenticated vehicles or malicious vehicles may also broadcast wrong messages. This necessitates those messages of vehicles to be trusted after authentication process of vehicles, especially in the absence of centralized authority. In this paper, token based trust computation based on network connectivity duration of vehicles in VANET is proposed. The proposed technique is based on travelling time association among vehicles or network connectivity of vehicle at the time of driving on the road. We present simulations of the proposed technique that verify its correctness and reliability in the presence of infrastructure and absence of infrastructure. Results show that the efficacy of the proposed scheme and makes it viable for secure and lightweight trusted communication in a VANET.
Niederreiter Cascade Combination Cryptosystem Based on the Double Public Keys

This paper firstly briefed the basic concepts of N public key cryptosystem, RS code and QC-LDPC code, and then put forward the cascade cryptosystem with the RS code being the outer code and QC-LDPC code being the internal code. At last, the writer analyzed in detail the security and performance of the N cryptosystem based on double public key, and thus proved its better security and performance than the traditional public key cryptosystem based on error correcting code. In addition, it is also endowed with higher practicability in complex environment.
An Approach of Fast Object Description for Image Segmentation

A new approach of object description after image segmentation to obtain objects’ feature is introduced. It reduce the numbers of image scanning to 1 time and combine equivalent label in image scanning. All objects’ feature can be obtained in the time of scanning finishing. The corresponding label information is update when a new pixel is scanned. All equivalent labels are combined as soon as possible when label is updating. No more time is needed after pixel scan finished. The flow of this approach is listed step by step with particular description. A complex example is analyzed with picture. Correctness and performance of this approach is proved with all possible instances are illuminated.
Recent Advances in Face Recognition

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Context Dependent Word Error Detection and Correction

Context dependent word errors in English texts are errors in which one is incorrectly substituted by another word without spelling mistake.This paper mainly discusses how to detect this type of errors.We prospose to extract the context festers by a method that firstly extract features of syntax and semantics from the word context,and then select the festures by the Document Frequency and the Information Gain to do feature selection.Further,we model the detecting task as a classification using the Winnow algorithm.With five-across validation among 61groups of confusion sets,the average precision and recall are 96%,79.47%,respectively.
Discrete-Time Signal Pro-cessing

For senior/graduate-level courses in Discrete-Time Signal Processing. THE definitive, authoritative text on DSP -- ideal for those with an introductory-level knowledge of signals and systems. Written by prominent, DSP pioneers, it provides thorough treatment of the fundamental theorems and properties of discrete-time linear systems, filtering, sampling, and discrete-time Fourier Analysis. By focusing on the general and universal concepts in discrete-time signal processing, it remains vital and relevant to the new challenges arising in the field --without limiting itself to specific technologies with relatively short life spans.
Spectral Efficient Opportunistic Relay Selection Policies for Next Generation Mobile Systems

This book chapter presents various relay selection policies based on spectral efficient techniques for the next generation mobile systems. Successive opportunistic relaying (SOR) that leverages the half-duplex constraint of conventional relays through concurrent transmissions is described, while proposing techniques to reduce the effect of inter-relay interference (IRI). An extension of SOR is defined for the case of out-of-band relaying, when additional spectrum bands are available and in networks with buffer-aided relays. Moreover, the use of full-duplex (FD) relays is outlined, in view of the effect of loop-interference (LI) from the relay’s output to its input and, also, the power reduction is presented. As networks with multiple relays suffer from increased coordination overhead, a reduced Channel State Information (CSI) policy is proposed. For every policy, performance evaluation is provided in terms of outage probability, average throughput, power reduction and switching rate. Finally, open problems in spectral-efficient opportunistic relay selection policies are discussed.
Advanced and robust control of grid connected converters

A typical application for parallel connected converters is in multi megawatt wind turbine systems. Manipulating the interleaving angle between the Pulse Width Modulated (PWM) carrier waves of each converter can result in reduced grid and DC link current ripple, thus the passive components from the DC link and grid filter can be minimized. In previous studies the optimization of the interleaving angle for either the grid current Total Harmonic Distortion (THD) or the DC link current ripple has been made. In this study a compromise is made in order to maintain a THD of the grid current in a level that complies with the standards, while in the DC link the current ripple is reduced. The dependency of the grid current THD and the DC link current ripple on the interleaving angle were determined by simulations. The results were also validated on a hardware setup.
Study of error modeling in kinematic calibration of parallel manipulators

Error modeling is the foundation of a kinematic calibration which is a main approach to assure the accuracy of parallel manipulators. This article investigates the influence of error model on the kinematic calibration of parallel manipulators. Based on the coupling analysis between error parameters, an identifiability index for evaluating the error model is proposed. Taking a 3PRS parallel manipulator as an example, three error models with different values of identifiability index are given. With the same parameter identification, measurement, and compensation method, the computer simulations and prototype experiments of the kinematic calibration with each error model are performed. The simulation and experiment results show that the kinematic calibration using the error model with a bigger value of identifiability index can lead to a better accuracy of the manipulator. Then, an approach of error modeling is proposed to obtain a bigger value of identifiability index. The study of this article is useful for error modeling in kinematic calibration of other parallel manipulators.