Miracle-dz/UniFAR-FTUs huggingface dataset:
A new computing method for extracting contiguous phraseological sequences from academic text corpora

This study aims to develop a new computing method for extracting contiguous phraseological sequences (PSs) of various lengths from academic text corpora by measuring internal associations of n-grams. We construct a new normalizing algorithm of probability-weighted average for refining the MI measure and enhancing precision in extracting PSs from corpora. This computing method is applied to the data in a medium-sized text corpus of academic English. Results indicate that the resultant new MI measure can provide statistics which better reveal internal associations within an n-gram, regardless of size. Lexico-grammatical sequences extracted with this method are more complete and less arbitrary in terms of grammar and semantics. The method can be applied to treating a variety of linguistic phenomenon, ranging from well-established phrases to likely phrasal entities, thus having potentially practical applications in corpus-based studies of phraseology and natural language processing.
A High Speed Low Power Adder in Multi Output Domino Logic

Speed and power is the major constraint in modern digital design. We have to design the high speed, l ess number of transistor as a prime consideration. The low power c arry look ahead adder using static CMOS transmission gate logic that overcomes the limitation of series connected pass t ransistors in the carry propagation path. In this approach it is required to find the longest critical paths in the multi-bit ad ders and then shortening the path to reduce the total critical pa th delay. The design simulation on microwind layout tool shows the worst-case delay in ns and total power consumption in microwatt range.
Fast Feature-Based Template Matching, Based on Efficient Keypoint Extraction

In order to improve the performance of feature-based template matching techniques, several research papers have been published. Real-time applications require the computational complexity of keypoint matching algorithms to be as low as possible. In this paper, we propose a method to improve the keypoint detection stage of feature-based template matching algorithms. Our experiment results show that the proposed method outperforms keypoint matching techniques in terms of speed, keypoint stability and repeatability.
Static Analysis of Run-Time Inter-Core Interferences for Concurrent Programs in Shared Cache Multicore Architectures

Worst-Case Execution Time (WCET) is crucial in real-time systems and is very challenging in multicore processors due to the possible runtime inter-thread interferences caused by shared resources. This paper proposes a novel approach to analyze runtime inter-core interferences for consecutive or inconsecutive concurrent programs. Our approach can reasonably estimate runtime inter-core interferences in shared cache by introducing lifetime and instruction fetching timing relations analysis into address mapping method. Compared with the method based on lifetime alone, our proposed approach efficiently improves the tightness of WCET estimation.
A Heuristic Method for Channel Allocation and Scheduling in an OFDMA System

In this letter, a heuristic channel allocation and scheduling scheme is proposed. By comparing the size of the alternative‐factor assessment, which is obtained by simple calculation, we can easily find the most appropriate channel for each user for overall throughput enhancement. Numerical results show that the downlink throughput of the proposed scheme is higher than that of proportional fairness and is almost the same as that of the maximum C/I scheme, while user fairness remains better than that of the maximum C/I scheme.
Integration of Cloud resources in the LHCb Distributed Computing

This contribution describes how Cloud resources have been integrated in the LHCb Distributed Computing. LHCb is using its specific Dirac extension (LHCbDirac) as an interware for its Distributed Computing. So far, it was seamlessly integrating Grid resources and Computer clusters. The cloud extension of DIRAC (VMDIRAC) allows the integration of Cloud computing infrastructures. It is able to interact with multiple types of infrastructures in commercial and institutional clouds, supported by multiple interfaces (Amazon EC2, OpenNebula, OpenStack and CloudStack) – instantiates, monitors and manages Virtual Machines running on this aggregation of Cloud resources. Moreover, specifications for institutional Cloud resources proposed by Worldwide LHC Computing Grid (WLCG), mainly by the High Energy Physics Unix Information Exchange (HEPiX) group, have been taken into account. Several initiatives and computing resource providers in the eScience environment have already deployed IaaS in production during 2013. Keeping this on mind, pros and cons of a cloud based infrasctructure have been studied in contrast with the current setup. As a result, this work addresses four different use cases which represent a major improvement on several levels of our infrastructure. We describe the solution implemented by LHCb for the contextualisation of the VMs based on the idea of Cloud Site. We report on operational experience of using in production several institutional Cloud resources that are thus becoming integral part of the LHCb Distributed Computing resources. Furthermore, we describe as well the gradual migration of our Service Infrastructure towards a fully distributed architecture following the Service as a Service (SaaS) model.
Improving the extrapolation capability of neural networks

Neural networks can be used as an effective system identification tool in that they can model the vast majority of nonlinear systems to any arbitrary degree of accuracy. However, a fundamental disadvantage of neural networks is their inability to incorporate effectively first-principles models' information into their training so that their predictive capability is improved. This study proposes to use information obtained from a first principles model to impart a sense of extrapolation capability to the neural network model. This is accomplished by modifying the objective function to include an additional term that is the difference between the time rate of change of the error between the best first principles model estimate of the process and the neural network prediction. The performance of a feedforward neural network model that uses this modified objective function is demonstrated on a chaotic process and compared to the conventional feedforward network trained on the usual objective function.
Healthy Twin: A Twin-Family Study of Korea — Protocols and Current Status

Abstract ‘Healthy Twin’ is a twin family study extension of the existing Korean Twin-Family Register. Healthy Twin recruits adult like-sex twins over the age of 30 and their adult family members. Healthy Twin protocols are primarily tailored to the study of the quantitative trait loci of complex traits as well as to the role of environment in the etiology of complex diseases. A full-length survey is underway, including questionnaires, health examinations and the collection of biological specimens. So far, 820 individuals (169 twin pairs and their families) have participated in the survey and 1068 individual twins (608 twin pairs) have replied to the mailed zygosity questionnaire as of July 2006. The first phase (2005–2006) of Healthy Twin will recruit 1550 individuals (including about 380 twin pairs), and the second phase a proposed 1500 to 2500 additional participants. We report study protocols and zygosity and the distribution of family size of the study participants.
Characteristic Analysis on UAV-MIMO Channel Based on Normalized Correlation Matrix

Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication.
The impact of developing Open Educational Resources (OERs) on novice OER developers

We focus on the experiences and attitudes of a small group of academics, new to the concept of OER, who developed open resources for the first time as part of a UK funded project, CPD4HE . This work was located within an on-going national OER programme, which has stimulated development of resources and research into related issues such as motivators and barriers, usage and impact. Analysis of texts generated during the development process revealed that the novice OER developers engaged particularly with licensing and IPR issues, the nature of their audience and some technical challenges, as well as with the practicalities of project participation. The texts also illustrate collaborative and community-building aspects of OER development; teacher-developers supported one another with encouragement and feedback on resources, and participants established links with sector-wide networks in Open Education. Post-project 'professional conversations' between four of the academics suggest that the OER experience has raised awareness of open practices and that educational values, academic identity, authorship and approaches to IPR were key elements in a description of their experiences and their attitudes towards open education. Findings provide tentative support for suggestions in the literature about the transformative potential of creating open educational resources. Keywords: OER, Open Education, innovation, collaboration, academic practice, impact, academic values, academic identity, workplace writing, teaching
The role of guided induction in paper-based data-driven learning

Abstract This study examines the role of guided induction as an instructional approach in paper-based data-driven learning (DDL) in the context of an ESL grammar course during an intensive English program at an American public university. Specifically, it examines whether corpus-informed grammar instruction is more effective through inductive, data-driven learning or through traditional deductive instruction. In the study, 49 participants completed two weeks of ESL grammar instruction on the passive voice in English. The learners participated in one of three instructional treatments: a data-driven learning treatment, a deductive instructional treatment using corpus-informed teaching materials, and a deductive instructional treatment using traditional (i.e., non-corpus-informed) materials. Results from pre-test, post-test, and delayed post-test indicated that the DDL group significantly improved their grammar ability with the passive voice, while the other two treatment groups did not show significant gains. The findings from this study suggest that in this learning context there are measurable benefits to teaching ESL grammar inductively using paper-based DDL.
N-Benzylindole-2,3-dione (N-benzylisatin)

The title mol­ecule, C15H11NO2, is non-planar, the dihedral angle between the isatin group and the phenyl ring being 87.08 (5)°. The crystal structure is stabilized by C–H⋯O hydrogen bonding inter­actions.
Analysis of security attacks in AODV

An ad hoc network is a collection of mobile devices that communicate in a self-organized way using wireless network interfaces without neither centralized administration nor fixed infrastructure. In such a network, nodes must cooperate with each other so as to extend their transmission range to reach distant nodes. This cooperation requires a specific ad hoc routing protocol to establish and maintain routes between nodes. Ad hoc routing protocols are based on mutual trust between collaborating nodes and suppose a correct behavior. As a result, these networks are particularly vulnerable to various security threats. , and therefore, security is a more significant issue than infrastructure-based wireless networks. In this paper, we present security analysis of the Ad hoc On-demand Distance Vector (AODV) routing protocol to identify all possible security threats that can target its algorithm, such as resources depletion, blackhole, wormhole and rushing attacks. Keywords—MANET; AODV; security attacks; malicious node;
A feature-based regression algorithm for cold-start recommendation

Recommender systems are widely used to help user select relevant online information. A key challenge of recommender systems is to provide high-quality recommendations for cold-start users or cold-start items. We propose a feature-based regression algorithm with baseline estimates to cope with three types of cold-start problems: cold-start system, cold-start users, and cold-start items. We consider all available information of users and items to solve the cold-start problems and take into account the user and item effects that exist in collaborative filtering systems. Compared to some existing algorithms, our algorithm is effective on the 100 k MovieLens data-set for cold-start recommendation.
Simulation for the current density distribution in a contact spot

Contact components have been used widely for switches, relays, and connectors. Although they have a simple structure, they are very reliable, having low resistance at on-time and high resistance at off-time, and are relatively immune against external noise. As a result, there has been a constant increase in demand for such components. However, because the contact surface may get contaminated, oxidized, or damaged over a long period of time or just through many cycles of usage, they may fail in conduction. Thus, very little information is available as to the relation between the surface state and the conductive phenomenon. The electric conductivity has been studied in conjunction with the surface state using a finite element method. A current density distribution inside a contact spot was calculated. As a result, when the resistivity of the contact spot is small, the current was found not to distribute uniformly throughout the spot area but increases at the corners of the spot when the spot shape is square. This means that the electric conductivity is proportional to the circumference length of the spot. On the other hand, as the resistivity of the spot increases, the current density at corners and circumferential regions decreases gradually and finally becomes uniform in its distribution over the entire spot region. In this case, the electric conductivity is shown schematically and quantitatively to be proportional to the area.
Error behaviour in differential phase-shifting algorithms

Differential Phase-Shifting Algorithms (DPSAs) recover directly the phase difference encoded in two patterns being unnecessary the previous calculation and subtraction of each individual optical phase by means of well-known highly efficient and accurate Phase-Shifting Algorithms (PSAs). In spite of their interesting metrological applications, there are almost no published studies about the possible error-compensating methods in DPSAs, so it is necessary to investigate the tools to eliminate or minimize the inevitable effect of the principal errors on the measurement process. In previous works we have linearized and numerically simulated phase shifting errors and the presence of harmonics on the signal of several families of DPSAs obtaining analytical phase error expressions. In this paper we present an analysis of propagation errors for several DPSAs families considering, in a similar way than in PSAs, the frequency shifting property of the employed arctan function. A Fizeau phase-shifting interferometer is employed to verify the main characteristics of the analysed DPSAs families.
Processing along the way: forwarding vs. coding

We consider a source that transmits to a receiver by routing the information packets over a communication network and examine rate benefits that finite complexity processing at the intermediate nodes may offer. We show that the processing capabilities of the intermediate nodes affect not only the end-to-end achievable rate, but also the optimal routing strategy. For example, there exist network configurations where the maximal throughput is achieved only by coding across independent information streams.
Performance analysis of application response measurement (ARM) version 2.0 measurement agent software implementations

Effective distributed application performance management infrastructures are based upon the collection and management of key performance metrics including resource utilization, workload and service measurements. Without application oriented transaction service measurements, the viability and long term usability of the client/server paradigm for mission critical applications is in question. The Application Response Measurement (ARM) Application Programming Interface (API) addresses this requirement by enabling the measurement of transaction level metrics, notably response time, for distributed applications through application code instrumentation. Version 2.0 of the ARM API includes the ability to measure and correlate response time components on different processors (i.e., clients and sewers). ARM Agents encompass the software components responsible for interception and processing of the ARM API calls including support for response time measurement, collection and communication. This paper introduces alternatives for several important design aspects of ARM agent software that are not specified in the ARM standards documents. In particular, we consider the architecture of ARM Agent software, correlator generation and communication, and ARM data storage. We propose, implement and analyze the performance of several alternative designs. This work provides an assessment of ARM instrumentation impact on application response times as well as insights into the design issues involved. We first provide a general overview of the ARM 2.0 API and features. We then consider alternative ARM agent software designs. Next, we present measurements results for several design implementations that shed light on the overhead involved with instrumentation and the developed designs. Finally, we present conclusions and a description of future work.
Display of Molecular Dynamics Simulation Results by MXDORTO with Web Browser. Interactive and Simple Display Program with GUI.

MXDORTOによる分子動力学シミュレーションによって得られる物質の構造を３次元グラフィックスとしてパソコン上で表示するため，MXDORTOによって得られた原子配置データからVRMLファイルを生成するプログラムを作成した．生成されたVRMLファイルはWebブラウザーとプラグインソフトを利用することにより，精細な３次元グラフィックスとして表示され，様々に視点を変えて構造を観察することが可能であった．本プログラムはWindows上で動作し，GUIを備えていることから，広く利用しやすいものとなっている．
Fast three-dimensional phase-unwrapping algorithm based on sorting by reliability following a non-continuous path

In this paper, we propose a novel three-dimensional phase unwrapping algorithm that extends the “two-dimensional phase unwrapping algorithm based on sorting by reliability following a non-continuous path” into three dimensions. The proposed algorithm depends on a quality map to unwrap the more reliable voxels first and the less reliable ones last. It follows a non-continuous path to perform the unwrapping process. Computer simulation has demonstrated that the proposed algorithm is more suitable than its two dimensional counterpart when used to unwrap volumetric data.
The Minimalist Program

Noam Chomsky,The Minimalist Program. (Current Studies in Linguistics 28.) Cambridge, MA: MIT Press, 1995. Pp. 420. The Minimalist Program, by Noam Chomsky, is a collection of four articles, ‘The Theory of Principles and Parameters’ (written with Howard Lasnik, 13–127), ‘Some notes on Economy of Derivation and representation’ (129–166), ‘A Minimalist Program for linguistic theory’ (167–217), and ‘Categories and transformations’ (219–394). The first three articles have appeared elsewhere, and are reprinted here with minor revisions. The fourth was circulated in manuscript form earlier in 1995 and is commonly referred to as ‘Chapter four’. The volume opens with an ‘Introduction’ (1–11) and closes with a general bibliography and an index (395–420). The work collected here is based on material presented by Chomsky, and discussed by participating students, faculty, and visitors, in Chomsky's fall term lecture-seminars at MIT in the period of 1986 through 1994. For those who have ever wanted to attend these class lectures, but were never in the position to, this is a must read. The MIT Press is to be commended for having made this collection available in such an exemplary inexpensive volume.
A Prototype Selection Method for Synthetic Object Recognition Based on Structural Graph Model

At present, many popular methods for object recognition are based on regional visual feature vectors which ignore the global structure of the object, leading to the “semantic gap” between image content and its tag. Graph-based structural representation of an object can record regional visual features and global relationships between regions that compose the object. However, the computation complexity of graph comparing limits the application of graph model in object recognition. One method for improving the recognizing speed is to reduce the prototypes in concept space of specific object category. We presented a prototype selection method for sythetic object recognition based on structural graph model using greedy clustering and representative sample selection. Experiments are conducted on a 2-D CAD synthetic object database. And the results show that the prototype selection method reduces the time cost of object recognition greatly with an acceptable loss in accuracy.
Data-mining assisted structural optimization using the evolutionary algorithm and neural network

The use of evolutionary algorithms for global optimization has increased rapidly during the past several years. But evolutionary computations have a common drawback: they need a huge number of function evaluations. This makes them inadequate for structural optimization. To overcome this difficulty, the authors propose a method that integrates the evolutionary algorithm with data mining and approximate analysis to find the optimal solution in structural optimization. The approximate analysis is used to replace exact finite element analyses and the data mining is employed to identify feasible solutions. These combined efforts can reduce the computational time and search the feasible region intensively. As a result, the efficiency and quality of structural optimization using evolutionary algorithms will be increased. Some test problems show that the proposed method not only finds the global solution but is also less computationally demanding.