Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Method for Content Consistency and Efficient Full-text Search for P2P Content Sharing Systems

A problem associated with current P2P (peer-to-peer) systems is that the consistency between copied contents is not guaranteed. Additionally, the limitation of fulltext search capability in most of the popular P2P systems hinders the scalability of P2P-based content sharing systems. We proposed a new P2P content sharing system in which the consistency of contents in the network is maintained after updates or modifications have been made to the contents. Links to the downloaded contents are maintained on a server. As a result, the updates and modifications to the contents can be instantly detected and hence get reflected in future P2P downloads. Natural language processing including morphological analysis is performed distributedly by the P2P clients and the update of the inverted index on the server is conducted concurrently to provide an efficient full-text search. The scheme and a preliminary experimental result have been mentioned
General Self-Efficacy: More Development Needed

Self-efficacy (1, 2) has been proposed as a unifying mechanism underlying all behavior change. Bandura's seminal writings on self-efficacy have stimulated many empirical studies and much comment. Shelton (4) recently presented a model of "general self-efficaz' that is based on Bandura's work as well as some of ours (5, 6) and of Tipton and Wort ngton (7). For Shelton, general self-efficacy is a personality trait related to but distinct from specific efficacy expectancies for specific behaviors. Shelton's model describes how general self-efficacy expectancies influence specific self-efficacy expectancies for specific behaviors and how successful behavioral performances, attributed to the self, augment both specific and general self-efficacy expectancies while unsuccessful performances, at~ributed to the self, detract from both general and specific self-efficacy expectancies. Shelton's roposals regarding general self-efficacy are generally reasonable though no empirical evidence 8 r the proposals i s$ r~sen~ed . Nonetheless, some aspects of her model merit cr1tlc31 comment. First, the sharp utmctlon Shelton (4, p. 989) drew between our descri tion oi gneral self-efficacy expectancies and Bandura's (1) original conceptualization of self-eflcacy I S 1101 accurate. Bandura (1, p. 194) stated chat self-efficacy expectancies vary in generality. Personal efficacy expectancies reflect a continuum from very specific to quite general. We focused on one end of the continuum while Bnndura generally wrote about the other. However, Bandura (2, p. 143) described rather general self-efficacy expectancies that contribute to social . change. Shelton (4, p. 990) correctly identified the importance of attribtion of successful and unsuccessful performances to personal ability and effort in determining self-efficacy ex ectancies. Individual differences in attributional style are major determinants of individual difLrences in self-efficacy expectancies (1, 6). Shelton neither discussed factors that contribute to individual differences in attributional style, e.g., Rotter's locus of control, nor made recommendations for ways to alter personal attributional style. Given the key role of attributional style in determining fnona l efficacy expectancies, reater attention to this would strengthen Shelton's model. Fina y, Bandura (1. 2) emphasizer8 the interaction of self-efficacy expectancies and outcome ex ectancies in determuling behavior. There is empirical evidence (3) that outcome expectancies in/uence the strenglh of self-efficacy ex ectancies. Shelton's model makes no mention of the influence of outcome expectancies on segefficacy expectancies and behavior. While Shelton (4) sought to synthesae prior work in her model of general self-efficacy, a broader model reflecting these comments and supported by empirical studies would be welcome.
A converter topology for high current density drive applications

In the area of marine industry, there is a large interest in converters for high power density. Increasing power above 8MW; pf 0.8; 3, 3kV in Medium Voltage Drive leds to either increase voltage or associate drives in parallel. Both solutions consist in doubling the number of components to reach the same power density that means drives with higher footprints and expensive solutions. This paper presents how a 3-level converter structure which was developed to double switching frequency is able to switch 50% more current, offering a very power dense medium voltage drive to industry.
Changing Local Political Leadership: The New Zealand Mayor in Contemporary Local Governance

Recent local elections have drawn attention to local political leadership in New Zealand. This article situates local political leadership in the context of recent theorising about typologies of local government and also in the context of changing styles of political leadership. The requirements of leadership are evolving as the role of local government and government more generally has been shaped by new public management and in particular the increasing emphasis on joined-up government and partnerships. The emergence of systems of local governance where political activities extend beyond the institution of ‘local government’ to encompass nongovernmental institutions and networks of institutional actors highlights the need for a more facilitative style of local political leadership. As well as the need to manage relationships with these networks, local political leadership and representative democracy more generally cannot be viewed in isolation from citizen participation and community involvement, and, indeed, these are now complementary aspects of local governance. This article examines recent literature on local political leadership and presents findings from a recent research project which examined leadership styles and the interface between leadership and community involvement.
Spatial and Temporal Charging Infrastructure Planning Using Discrete Event Simulation

The switch from gasoline-powered vehicles to electric vehicles (EVs) is an important step to reduce greenhouse gas emissions. To this end, many European countries announced EV stock targets, e.g., Germany aims to have one million EVs on the roads by 2020. To achieve these goals and to handle the range limitation of EVs, a widespread publicly accessible charging infrastructure is needed. This paper provides a dynamic spatial and temporal simulation model for the building of charging infrastructure on a municipality scale. We evaluate empirical data about the timely utilization of different charging stations in the German federal state of Bavaria. This data is used to derive empirical models for the start time and duration of charging events as well as the popularity of charging stations. We develop a lightweight discrete event simulation model which can be used to investigate different expansion strategies, e.g., based on the load of charging stations or the number of successful and failed charging attempts. We show the applicability of our model using the German federal state of Bavaria as a use case.
Evolution of Learning Rules for Hard Learning Problems

Recent experiments with a genetic-based encoding schema are presented as a potentially useful tool in discovering learning rules by means of evolution. The representation strategy is similar to that used in genetic programming(GP) but it employs only a xed set of functions to solve a variety of problems. In this paper, three Monk's and parity problems are tested. The results indicate the usefulness of the encoding schema in discovering learning rules for hard learning problems. The problems and future research directions are discussed within the context of GP practices.
Discourse Analysis: Ronald Reagan’s Evil Empire Speech

Language can be a powerful tool to convince others and make them cooperative. Cialdini (2007) has worked out several principles along which it is possible to analyze discourses in terms of their persuasiveness. Others also have contributed with tools to analyzing discourses such as Fairclough (2003). These tools are used to analyze the “Evil Empire Speech” of the US President Ronald Reagan that he held at the National Association of Evangelicals, 1983, in Orlando Florida. His historical speech was aimed at convincing the nation about the righteousness of his nuclear policy. He partly rewrote the already prepared script and included the “evil empire” part. The analysis supports that his speech was an exceptionally effective one. Reagan made his speech an example of the following principles of persuasiveness such as reciprocity, authority, commitment, liking, scarcity and social proof. He wanted support for belligerent intentions from a faithful community, which was already problematic, but he got the audience on his side through emphasizing his similarities with them, his own faithfulness, the presentation of strong examples and balancing humor and seriousness. Additionally, he introduced the striking metaphor “evil empire”, which stuck to the peoples’ minds and had an impact on them. He also appealed to the people through implicitly distinguishing the evil from the ones who were not evil—the US citizens. Thus, he made the American people feel better, to ensure them that they do the right thing when following him. He ranked religious people above him when he was joking about clergy men and politicians. To reinforce his authority, he borrowed the authority of various respected men through citing them. He improved his position and the power of his arguments using the philosophical wisdom of others.
Integrated speaker-adaptive speech synthesis

Enabling speech synthesis systems to rapidly adapt to sound like a particular speaker is an essential attribute for building personalised systems. For deep-learning based approaches, this is difficult as these networks use a highly distributed representation. It is not simple to interpret the model parameters, which complicates the adaptation process. To address this problem, speaker characteristics can be encapsulated in fixed-length speaker-specific Identity Vectors (iVectors), which are appended to the input of the synthesis network. Altering the iVector changes the nature of the synthesised speech. The challenge is to derive an optimal iVector for each speaker that encodes all the speaker attributes required for the synthesis system. The standard approach involves two separate stages: estimation of the iVectors for the training data; and training the synthesis network. This paper proposes an integrated training scheme for speaker adaptive speech synthesis. For the iVector extraction, an attention based mechanism, which is a function of the context labels, is used to combine the data from the target speaker. This attention mechanism, as well as nature of the features being merged, are optimised at the same time as the synthesis network parameters. This should yield an iVector-like speaker representation that is optimal for use with the synthesis system. The system is evaluated on the Voice Bank corpus. The resulting system automatically provides a sensible attention sequence and shows improved performance from the standard approach.
Traffic sign recognition using hybrid features descriptor and artificial neural network classifier

Traffic Sign Recognition (TSR) system is a significant component of Intelligent Transport System (ITS) as traffic signs assist the drivers to drive more safely and efficiently. This paper represents a new approach for TSR system using hybrid features formed by two robust features descriptors, named Histogram Oriented Gradient(HOG) features and Speeded Up Robust Features(SURF) and artificial neural network (ANN) classifier. In the detection step, the region of interest (sign area) is segmented using color based thresholding algorithm, post processed to filter the unwanted region. Next robust features vector named Distance to Borders (DtBs) of the segmented blob is formed to verify the shape of the traffic sign. Finally the recognition of the traffic sign is implemented using ANN classifier upon the training of hybrid features descriptor. The proposed system simulated on offline road scene images shows a high classification rate in the recognition stage. The performance of the ANN model is illustrated in terms of cross entropy, confusion matrix and receiver operating characteristic (ROC) curves. In addition, the performance of hybrid feature descriptor is compared with recognition based on HOG and SURF descriptor respectively. Also, performances of some classifier such as Support Vector Machine (SVM), Decision Trees, Ensembles Learners (Adaboost) and K-Nearest Neighbor (KNN) classifier are assessed with ANN approach. The simulation results illustrates that recognition using hybrid feature descriptor outperforms in all classifier and the recognition accuracy of ANN is higher than classifier stated above.
EFFECTS OF NOVEL LONG LIFE ROUTING ALGORITHMS ON IEEE 802.16 THROUGHPUT IMPROVEMENT METHODS FOR VARIOUS VEHICULAR VELOCITIES

In this paper, effects of Fastest Path Routing, Ant-Colony Routing, Associativity Based Routing (ABR) and other novel proposed Associativity Based Long Life Routing algorithms, on novel proposed throughput improvement algorithm Most Congested Access First (MCAF), minimizing the packet loss ratio and improving the throughput of a multi-hop mobile WIMAX network are investigated for various vehicular velocities. The proposed Long Life Routing algorithms are shown to provide more throughput improvement for all vehicular velocities and provide longer life routes.
Religiosity and Spirituality Among Members of an African American Church Community: A Qualitative Analysis

This qualitative study explores how 21 African Americans, regular and active members in an African American Baptist church organization in the Midwest, define the terms religiosity and spirituality. The qualitative data were analyzed using a grounded theory methodology to determine the themes that were provided by the participants. This article will explore five recurring themes, including: (a) religiosity as external behaviors; (b) religiosity as internalized beliefs; (c) spirituality as acknowledging a “spiritual reality”; (d) spirituality as connectedness to God; and (e) interconnectedness of religiosity and spirituality. Narratives will be offered to support and illustrate each of these themes.
Adaptive bandwidth provisioning envelope based on discrete temporal network measurements

We propose an adaptive bandwidth provisioning mechanism based on packet-level measurements (done at discrete time intervals) without any assumption on the statistical property of the traffic. Our approach consists of two stages: traffic forecasting, followed by bandwidth estimation. For the first stage, we have developed a probability-hop forecasting algorithm (based on ARIMA model) to forecast traffic based on online traffic measurements in a temporal management information base framework. For the second stage, we present several bandwidth provisioning schemes that allocate or deallocate bandwidth depending on the traffic forecast generated by our forecasting algorithm. We have introduced an utility function (along with other measures) to evaluate the overall effectiveness of our bandwidth provisioning framework. Through the use of real-world data, we have found that our approach works well for highly fluctuating data
Self-governance and forest resources

Forest resources share attributes with many other resource systems that make difficult their governance and management in a sustainable, efficient, and equitable manner. While some ‘forests’ are small enough that fencing them or protecting their borders from intrusion is relatively easy, excluding beneficiaries from access and use of most forests is costly. The difficulty of exclusion creates the possibility that individuals who benefit from the use of a forest will not contribute to its long-term sustainability. For many uses of a forest, one person’s harvesting subtracts products that are not available to others. Thus, many aspects of forests can be considered as common-pool resources. Common-pool resources are characterized by difficulty of exclusion and generate finite quantities of resource units so that one person’s use subtracts from the quantity of resource available to others (E. Ostrom, Gardner and Walker 1994). The ecosystem services generated by forest resources – watershed protection, carbon sequestration, biodiversity enhancement, etc. – may be considered as externalities or as public goods. Ecosystem services are, however, closely tied to the sustainability of the forest stock, and are thus threatened by the same set of incentives that tempt users of an unregulated forest resource into a race to use up the timber and destroy the forest itself. Destruction or degradation of forest resources are most likely to occur in open access forests where those involved and/or external authorities have not established an effective governance regime to regulate the following: • Who is allowed to appropriate forest products; • The timing, quantity, location, and technology of appropriation; • Who is obligated to contribute resources to provide or maintain the forest; • How appropriation and obligation activities are to be monitored and enforced; • How conflicts over appropriation and obligation activities are to be resolved; and, • How the rules affecting the above will be changed over time with changes in the extent and composition of the forest and the strategies of participants. A self-governed forest resource is one where actors, who are major appropriators from the forest, are involved over time in making and adapting rules within collective-choice arenas regarding the inclusion or exclusion of participants, appropriation strategies, obligations of participants, monitoring and sanctioning, and conflict resolution. Some extremely remote forests are governed entirely by appropriators and are not governed at all by external authorities. In most modern political-economies, however, it is rare to find any resource system – including the treasuries of private for-profit corporations – that are governed entirely by participants without rules made by local, regional, national, and international authorities also affecting key decisions (V. Ostrom 1991, 1997). Thus, in a self-governed system, participants make many, but not all, rules that affect the sustainability of the resource system and its use.
Moving a robot starting from a theory of actions

The paper describes an approach to reasoning about actions and planning that starting from a logical formalization arrives at the realization of an actual agent, the mobile robot "Tino". The reasoning tools allow the robot to derive plans from the knowledge about the environment and the action specification, while its reactive capabilities allow it to execute its plans in the real world. The formalization is based on the propositional dynamic logics framework, but exploits the correspondence that exists between propositional dynamic logics and description logics, to carefully weaken the logical inference process in order to keep the reasoning tools of the robot both effective and efficient. Such reasoning tools are then implemented by making use of a general knowledge representation system based on description logics, namely the system CLASSIC.
Detection of simulated malingering using forced choice recognition enhanced with event-related potential recording

Abstract A modified forced-choice procedure (HFCP) based on that of Hiscock and Hiscock (1989) for use with suspected malingerers is described. The major modification involves recording of the P300 event-related brain potential in response to the screen to which the subject responds. This “probe” screen is, in turn, modified to contain either a match or a mismatch to the initial sample number, as opposed to having the subject choose the match from a pair of stimuli (match and mismatch) which are simultaneously presented in the standard HFCP. The P300 recording procedure necessitated this change, which also forces the subject to say “yes” or “no” (to match and mismatch, respectively), rather than choosing the match. We found that behavioral performance on the standard HFCP correlated highly and significantly with performance on the P300-enhanced HFCP. Three variants of the modified HFCP were explored. In all variants, P300 amplitude was significantly larger to the match than to the mismatch in standard gro.
Biphasic release of endothelium-derived relaxing factor(s) by acetylcholine from perfused canine femoral arteries. Characterization of muscarinic receptors.

Experiments were designed to compare the release of endothelium-derived relaxing factor(s) in response to various muscarinic receptor agonists from canine femoral arteries mounted in organ chambers or perfused in a bioassay system. In rings of femoral arteries, suspended for isometric tension recording in organ chambers, acetylcholine induced endothelium-dependent relaxations during contractions evoked by prostaglandin F2 alpha. Atropine and pirenzepine antagonized these relaxations in a competitive manner, atropine with a higher affinity (KB = 1.9 X 10(-9) M) than pirenzepine (KB = 5.4 X 10(-7) M). Carbachol and McN-A-343 also evoked endothelium-dependent relaxations, and pirenzepine inhibited these responses with a similar low potency. The order of relative potency of the agonists in organ chamber studies was acetylcholine = carbachol much greater than McN-A-343. Isolated segments of femoral arteries with endothelium were perfused (2 ml/min) with modified Krebs-Ringer-bicarbonate solution containing indomethacin; the perfusate was bioassayed for endothelium-derived relaxing factor(s) by means of a ring of coronary artery without endothelium. When infused above but not below the femoral artery, low concentrations (10(-8)-10(-7) M) of acetylcholine caused transient relaxations of the bioassay ring contracted with prostaglandin F2 alpha; higher concentrations of acetylcholine caused sustained decreases in tension. Atropine inhibited the two phases of the concentration-relaxation curve with similar potencies. Pirenzepine inhibited both phases in a competitive manner but exhibited significantly higher potency against the first- (ED50, 1.9 X 10(-9) M) than against the second-phase responses (ED50, 2.1 X 10(-7) M). Compound McN-A-343 induced only transient decreases in tension, whereas carbachol caused sustained relaxations. (ABSTRACT TRUNCATED AT 250 WORDS)
Classifying Web Pages by Genre: An n-Gram Approach

The research reported in this paper is part of a larger project on the classification of Web pages by genre. Such classification is a potentially powerful tool in filtering the results of online searches. In this paper, we describe two sets of experiments investigating the automatic classification of Web pages by their genres. In these experiments, our approach is to represent the Web pages by profiles that are composed of fixed-length byte n-grams. The first set of experiments in this study examines the effect of three feature selection measures on the accuracy of Web page classification. The second set of experiments in this study compares the classification accuracy of three classification methods, each using n-gram representations of the Web pages. The classification methods which are compared are a distance function approach, the k-nearest neighbors method, and the support vector machine approach. We also examine a range of n-gram lengths and a range of Web page profile sizes to determine what combination(s) of n-gram length and profile size give the best classification accuracy. Each set of experiments is run on two well-known data sets, 7-Genre and KI-04, for which published results are available.