Miracle-dz/UniFAR-FTUs huggingface dataset:
An Integrated Approach to Automated Synthesis, Simulation and Optimization of Energy and Signal-Based Design Concepts

Computers have the capability to support human de- signers in a variety of tasks including releasing the human designer from routine tasks via design automation as well as sparking and supporting innovation and creativity. To sup- port the concept phase effectively, a wide range of possible concepts, which are quantitatively evaluated, should be con- sidered to enable designers to explore the solution space and choose advantageous concepts. To enable automated solu- tion space exploration and evaluation, this research presents a method that uses automated model transformations based on a graph-based object-oriented knowledge representation. The approach combines previous research with automated generation of variable assignments for generated concepts and optimization using simulated annealing. The variable assignments are generated by automatically setting up and solving constraint satisfaction problems and evaluated us- ing automatically generated simulation models. The main contributions of this research are an integrated and fully automated approach starting with task definition and end- ing with a solution space of optimized product concepts and generic model transformations that enable automated use of Boolean satisfiability, constraint satisfaction and bond graph-based simulation methods. The method is validated on the case studies of automotive powertrains.
The Human Resource Development Strategies on Information TechnologySemi-Professionals Adoption of the Local Government

The technology acceptance model (TAM) has been applied in different contexts to investigate a wide range of information technologies (ITs), and a cumulative tradition has already been developed in this stream of research. Nevertheless, it was still needed to be empirically investigated for government organizations in order to make sure that different sample profiles would not have a negative effect on the findings. The objective of this research was to develop and test an integrated model of human resource management strategies in local government. The members of matrix structured team were semi-professionals on IT and were organized from different departments for introducing IT using. We discussed the work ability and working willingness as the independent variables and test the moderating effects of personal characteristics on the attitude of IT adoption. Forty-eight team members filled questionnaire. The empirical results based on moderated multiple regression (MMR) modeling approach to provide preliminary evidence supportive of the hypotheses advanced. Specifically, the IT experience and the work ability have interactive effect with adoption attitude. The results indicate that the IT experience plays a strategic role for adoption of IT. Finally, the implications for introducing IT to the local government are presented.
Control of interior permanent magnet synchronous motor drives over a wide speed range

A set of control strategies were developed to improve the performance,efficiency and reliability of the interior permanent magnet synchronous motor(IPMSM) drives for a wide range of speeds.Rotor flux oriented vector control with a model reference adaptive system(MRAS) based rotor position/speed estimation was used as the basic control strategy for the IPMSM drive.A maximum torque per ampere(MTPA) control strategy was used to minimize the motor current magnitude during low speed operation.Over-modulation method was used to improve the voltage transfer ratio of the pulse width modulation(PWM) inverter and the output torque capability of the IPMSM during high speed operation,with flux weakening control for high speed stable operation of the IPMSM drive.Phase current reconstruction for over-modulation was used to improve the high speed IPMSM operation.The issue of seamless switching from MTPA during low speed operation to conventional field-weakening control during high speed operation was also discussed.Simulations and tests demonstrate the feasibility and effectiveness of these control strategies for high performance operation of IPMSM drives over a wide speed range.
Error automation moodeling of coordinate measuring machine based on multi-body system kinematics theory

The principles of error modeling for complexity machines such as coordin ate measuring ma-chines(CMM)are studied and analyzed based on the multi -body system(MBS)kinematics theory.And in addition the error automation modeling processes of them are introduced.An FXYZ vertical CMM taken as an example,its error modeling processes are expatiated,and its volumetric error moldel expression are given a lso.It is shown that the proposed method solves universality problems of machin e error modeling commendably in therory analysis and practicality a pplication and it provides a perfectly good error modeling method for pre ci-sion analysis,error compensation a nd so on.
A New Graph Clustering Algorithm for Chinese Noun Phrase Coreference Resolution

Coreference resolution plays an important role in natural language processing.Facing the fact that the Chinese training corpus for coreference resolution is heavily lacking,this paper presents a new unsupervised clustering algorithm for noun phrase coreference resolution.In this approach,the problem of coreference resolution is firstly converted as a graph clustering problem,and then an objective function called the modularity function,which allows automatic selection of the number of clusters,is selected for graph clustering.The proposed algorithm does not make pairwise coreference decisions independently of each other.The experimental results on the Chinese ACE training corpus demonstrate that the proposed method is a feasible unsupervised algorithm for noun phrase coreference resolution.
A Security System Design of Digital Signature Based on PKI

This passage presents a security system design of digital signature based on PKI . Algorithm improvement can be found in graphs and tables. It applies the symmetric algorithm and one-way hash functions to guarantee the security of the private key, and also applies asymmetric algorithm and technology of digital signature to guarantee their validity and confirmability. The author’s conclusion has certain economic efficiency and the social efficiency to do with the development of a nation.
An Overview on Signature File Techniques

An important question in information retrieval is how to create a database index which can be searched efficiently for the data one seeks. Today, one or more of the following four techniques have been frequently used: full text searching, B-trees, inversion and the signature file. Full text searching imposes no space overhead, but requires long response time. In contrast, B-trees, inversion and the signature file work quickly, but need a large intermediary representation structure (index), which provides direct links to relevant data. In this paper, we concentrate on the techniques of signature files and discuss different construction approaches of a signature file. The signature technique cannot only be used in document databases, but also in relational and object-oriented databases. In a document database, a set of semistructured (XML) documents is stored and the queries related to keywords are frequently evaluated. To speed up the evaluation of such queries, we can construct signatures for words and superimpose them to establish signatures for document blocks, which can be used to cut off non-relevant documents as early as possible when evaluating a query. Especially, such a method can be extended to handle the socalled containment queries, for which not only the key words, but also the hierarchical structure of a document has to be considered. We can also handle queries issued to a relational or an objectoriented database using the signature technique by establishing signatures for attribute values, tuples, as well as tables and classes.
Novel Time Domain MIMO Equalization Algorithm for High Frequency Spectrum

In this paper,a novel time domain MIMO equalization algorithm is proposed with respect to the high-frequency domain,which is referring to the detection algorithm of V-BLAST system.The new algorithm is based on the special structure of decision feedback equalization,the coefficients of which is obtained by channel estimation.With layered equalization,the earlier recovered transmit signals can be used for the interference cancellation of next layer equalization.The results of simulation show that the proposed algorithm can provide better symbol error rate with a relatively low calculation complexity.
Data Warehouse and Data Mining Overview

with the development of information technology and database technology,the appearance of the concept of data warehouse(Data Warehouse,DW) and data mining(Data Mining,DM),in the era of big data,has the vital significance to the study of. In this paper,both the interpretation and definition,relationship,use of technology,elaborates common problems are elaborated.
Representation of Arc with C-Béier Curve

Representation of a circular arc plays an important role in CAD. However, the existing methods are not friendly to designers. In this paper, a series of methods are presented to construct the circular arc with C-Beier curves. In order to compare with the old methods, so-called characteristic ratio is proposed. As a consequence, the C-Beier curves with degree higher are better than the lower. Specially, the quintic C-Beier curve can construct the whole circle.
A Coding Strategy of H.264 Based on High-definition Display of Target Region

H.264 is the latest video coding standard,and it adopts many new technologies such as intra prediction,integer cosine transform,multiple reference pictures for motion estimation,context adaptive entropy coding and so on,these methods largely improve the coding efficiency.Under real-time and low bit rate conditions,remote digital video monitoring system based on H.264 needs to be improved.In this paper,an inter-frame subtraction combining with background subtraction is used to detect the target region.To achieve the purpose of high-definition of target region under low bit rate,an optimized rate control scheme is proposed.The whole coding system is realized on TMS320DM642.The design originates from the co-operation project with some scientific research unit.The corresponding production will be used for wireless real-time video coding transmission system on unmanned aircraft.The research has important practical significance.
Role-Based Access Control Model and its Implementation in Operating System

Since Role-based access control shows great advantage in meeting the security need in large-scale, enterprise-wide system, RBAC becomes the hot topic in access control research area. Researchers have proposed several RBAC models, which include the famous RBAC96 model. However, these frameworks are sometimes hard for system developers to understand because the models defined are too abstract or focus on application-oriented solutions. In this paper, a new model (OSRBAOis discussed, which is the improved model to RBAC3 model in RBAC96 model family. Compared with RBAC3 model, OSRBAC model is more concrete and easilier to understand. At the end, this paper describes the implementation of OSRBAC model in RedFlag Secure Operating System (RFSOS).
A Moving Object Tracking Method Based on Active Contour Models

This paper discusses the advantages and disadvantages of several representative active contour models(i.e.,Snakes). When traditional Snakes are used in moving object tracking applications,they often encounter some defects,and an automatic initialization algorithm is designed to overcome these problems.The eight-neighbor searching algorithm is replaced by the four-neighbor-alternating searching method to reduce the computing cost,and a practical moving object tracking method based on Snake is proposed.Experiments are made to demonstrate the feasibility of the presented method.
A supervoxel-based spectro-spatial approach for 3D urban point cloud labelling

ABSTRACT Three-dimensional (3D) point cloud labelling of airborne lidar (light detection and ranging) data has promising applications in urban city modelling. Automatic and efficient methods for semantic labelling of airborne urban point cloud data with multiple classes still remains a challenge. We propose a novel 3D object-based classification framework for labelling urban lidar point cloud using a computer vision technique, supervoxels. The supervoxel approach is promising for representing dense lidar point cloud in a compact manner for 3D segmentation and for improving the computational efficiency. Initially, supervoxels are generated by over-segmenting the coloured point cloud using the voxel-based cloud connectivity algorithm in the geometric space. The local connectivity established between supervoxels has been used to produce meaningful and realistic objects (segments). The segments are classified by different machine learning techniques based on several spectral and geometric features extracted from the segments. All the points within a labelled segment are assigned the same segment label. Furthermore, the effect of different feature vectors and varying point density on the classification accuracy has been studied. Results indicate an accurate labelling of points in realistic 3D space conforming to the boundaries of objects. An overall classification accuracy of is achieved by the proposed method. The labelled 3D points can be used directly for the reconstruction of buildings and other man-made objects.
Understanding Small Business Electronic Commerce Adoption: An Empirical Analysis

Several small businesses have adopted electronic commerce but a significant number have not. This paper identifies a discriminant function that can accurately predict adoption of electronic commerce in small businesses. Data for the study was collected through structured interviews with 62 top managers/CEOs of small businesses. Many factors were found to discriminate between adopters and non-adopters of electronic commerce. These included: enthusiasm of the top manager/CEO toward electronic commerce, compatibility of electronic commerce with the work of the company, relative advantage perceived from electronic commerce, and knowledge of the company's employees about computers.
Autonomic Joint Session Admission Control Using Reinforcement Learning

A reinforcement learning based joint session admission control(JOSAC) algorithm is proposed to realize the autonomic and distributed joint resource optimization between the heterogeneous radio access technologies(RAT) in a reconfigurable system.By introducing Q-learning into the admission control algorithm and adjusting the strength of the reinforcement signals for different types of sessions considering the inherent characteristics of different RATs,the characteristics of RATs is driven to absorb the suitable traffic for a proper service distribution.That will improve the efficiency of resource utilization.The simulation results show that,through the "trial-and-error" on-line learning process,overlapping RATs can converge to the optimized admission control policies that reduce the overall blocking probability and achieve lower handover dropping probability as well as higher revenue.
Reliable high-throughput FPGA interconnect using source-synchronous surfing and wave pipelining

FPGA clock frequencies are slow enough that only a fraction of the interconnect’s bandwidth is used. By exploiting this bandwidth, the transfer of large amounts of data can be greatly accelerated. Alternatively, it may also be possible to save area on fixed-bandwidth links by using on-chip serial signalling. For datapath-intensive designs which operate on words instead of bits, this can reduce wiring congestion as well. This thesis proposes relatively simple circuit-level modifications to FPGA interconnect to enable high-bandwidth communication. High-level area estimates indicate a potential interconnect area savings of 10 to 60% when serial links are used. Two interconnect pipelining techniques, wave pipelining and surfing, are adapted to FPGAs and compared against each other and against regular FPGA interconnect in terms of throughput, reliability, area, power, and latency. Source-synchronous signalling is used to achieve high data rates with simple receiver design. Statistical models for high-frequency power supply noise are developed and used to estimate the probability of error of wave pipelined and surfing links as a function of link length and operating speed. Surfing is generally found to be more reliable and less sensitive to noise than wave pipelining. Simulation results in a 65nm process demonstrate a throughput of 3Gbps per wire across a 50-stage, 25mm link.
Phenomenological Psychology: Theory, Research and Method

phenomenological psychology theory research and method is available in our book collection an online access to it is set as public so you can download it instantly. Our digital library hosts in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the phenomenological psychology theory research and method is universally compatible with any devices to read.
On-line sampling methods for discovering association rules

Association rule discovery is one of the prototypical problems in data mining. In this problem, the input database is assumed to be very large and most of the algorithms are designed to minimize the number of scans of the database. Enumerating association rules is usually an expensive task due to the size of the input database. A proposed approach for reducing the running time of this process is random sampling. Of course, any implementation of an algorithm that uses sampling must solve the problem of determining which sample size is appropriate. Previous research of sampling for association rule mining has approached this problem concluding that, in general, the theoretically obtained sample size bounds are far from what is observed in practice. In this paper, we try to reduce this gap between theory and practice. We propose two on-line sampling algorithms for association rule mining. Our algorithms maintain the same theoretical guarantees of previous approaches while using a much smaller number of transactions in most of the cases. In the experiments we report, this improvement is often by an order of magnitude.
Optimization of ODMRP and Simulation

ODMRP protocol is an on-demand multicast routing protocol in Ad hoc network.In order to improve the performance of it for Groups of different sizes,an optimized Ad Hoc multicast routing protocol is proposed,which is based on the concept of variable core.Two protocols are simulated in GloMoSim,and results show that the optimzed protocol has improvement to such performandce as distributing rate of the data and network validity,etc.So the optimization works efficiently,which is more suited for ad hoc network.
Research on Application of Density Distribution of Keywords in Biased Summarization

The study and implementation of biased summarization system is the basis of intelligent information service.The biased summarization can process the single document summarization and multi-document summarizations,so it is considered as a useful tool to meet users’ demands.The summarization approach is presented which is based on the density distribution of keywords.The conceptual expansion is applied to get more synonymies.The strategy of extracting sentences is discussed based on the density distribution of keywords.The summarization approach shows its high efficiency and high precision under the two evaluations,one is based on information retrieval(IR) and another is based on question answering(QA).
ONLINE INSTRUCTION AS LOCAL EDUCATION: CUNY'S ONLINE BACCALAUREATE

The City University of New York is taking a new, local approach to online instruction: offering an online baccalaureate for degree completers, designed for NYC students who have “stopped out” in good academic standing and need the “any time” flexibility of asynchronous learning to finish the degree. What is especially distinctive about this online program is its goal of access for local students, its core constituency and mission. Though CUNY is addressing a local problem, online access to higher education for local students may address nation-wide problems with rates of degree completion and progress towards completion. As more institutions provide online instruction, localness may well be the key to access and timely completion for local students, with time and not distance being the key obstacle it overcomes.
SECURING HEALTH CARE DATA IN COLLABORATIVE DATA PUBLISHING USING MAPREDUCE FRAMEWORK

Today publishing data on a web becomes need. Publishing such microdata can breach privacy of any individual. For analysis purpose researcher, medical practitioner required such health related data. Existing system used encryption algorithms for securing data. The data is stored on HDFS by encrypting and the user having key can only access that data by decrypting it. Big data is heterogeneous, distributed data where data is collected from different sources having different dimensions. In hospital patients data can be stored in different form such as audio, video, and in images. Big data having different characteristics like variety of data, its volume and velocity, this makes it different from other databases. Data privacy is one of the challenge in data mining with big data. Big data keeps growing continuously. In case of big data it is not efficient to encrypt large amount of data as it is time consuming. Existing provider aware algorithm has problem of data loss due to insider attack. K-anonymity and l- diversity are very popular algorithms for generalization and bucketization. They have some their own little limitations. In insider attack provider can infer the information of other user using his own records and with some background knowledge. To preserving the privacy of the user we need to use some method so that data privacy is preserve and at the same time increase the data utility. In the proposed system we focus to maintain the privacy for distributed data, and overcome the problems of M-privacy using new updated provider algorithm with a slicing technique. The main goal of paper is to publish an anonymized view of integrated data, which will be immune to attacks. We also use MR-Cube method which is used to compute large cube with non algebraic measures such as TOP-k, count.
Human ear recognition based on statistic features of local information

A new human ear recognition approach, based on statistic features of local information, is proposed. A human ear gray-scale image is divided into several sub-regions. The assorted features of each sub-regions are abstracted. Feature of sub-regions are joined in- to a feature vector to build human ear feature vector, thus gives a comprehensive description about the structure and local information of human ear images. The pattern classification is implemented by applying the nearest neighbor classifier. Three different feature extraction methods are adopted and USTB human ear database are applied to testing this algorithm. The experimental results show that the recognition rate is improved more than 30% compared with global information and the method based on statistics feature of local information is proved effective.