Miracle-dz/UniFAR-FTUs huggingface dataset:
New similarity measure method on time series

Similarity measure on time series is the basis of time series data mining,a new similarity measure method on time series—SMVT by describing time series with symbol based on variation trends and defining trend distance.The variation trends similarity of time series are measured with this method,which is concise and straightforward,trends description scientific,and reflects the overall variation trends of time series well.Applying the new similarity method for clustering computation of time series,the experimental results show that the method can measure the similarity of time series effectively from the perspective of variation trends,which explains its well practicability and good application prospect.
From first to third stream activities in higher education: the case of the Spanish Defence University centre

ABSTRACT The paper adds to the debate on the relationship between military spending and economic growth by analysing the contribution of a military university centre to regional economic development. It goes beyond traditional economic impact studies by including research related effects and integrating “third stream” activities. Conceptualization and categorization are carried out to thoroughly analyse the different dimensions of knowledge and “third stream” actions. The analysis is performed from its settlement and during its first 5 years of existence which allows showing how the strategy of community engagement is developed. The conclusion suggests that, as traditional military roles extend, and military education institutions become higher education institutions, a comprehensive evaluation should be taken into account to enrich the public debate on government spending.
Research on the Scale of 1:10 000 Digital Maps Revision Based on High Resolution Remote Sensing Data

Describes the basic flow,revising ways and key technics about the Scale of 1:10 000 digital maps revision based on high resolution remote sensing data in datail.Further more,Object oriented class rules and information extracting technics are used to obtain updating special information.At the end,this pa- per give a conclusion that utilizing high resolution remote sensing data to revise digital maps is a feasible method of quickly,efficiently and cost saving.
P2P Multi-dimensional Range Query System Based on Kademlia

Structured P2P networks has good expandability,but it is difficult to support multiple keywords query or range queries.This paper analyzes the existing complex query,and proposes a P2P multi-dimensional range query system based on Kademlia which named K-net.When processes multi-dimensional range query,it deals with dimension reduction and range partition simultaneously.This method can reduce the bandwidth required for query.The simulation results show that this system has good query accuracy and expansibility.
A Comparison of the Effect of Text-Picture and Audio-Picture Annotations in Second Language Vocabulary Recall among Iranian EFL Learners

The present study compared the effect of text-picture and audio-picture multimedia annotations in second language vocabulary recall among Iranian EFL learners. The participants were selected from two classes of 80 students who were studying advanced-level English at in a language institute in Iran. Their level of English proficiency was determined on the basis of their scores on the PET proficiency test. Sixty-two students were selected for the main procedure, and were then randomly divided into two experimental groups: the textannotation and audio-annotation group; and a control group. After answering a vocabulary pretest, participants clicked on the highlighted unknown words to access available annotations while reading. The text-picture group was able to see textual explanation and pictorial description, and the audio-picture group was able to see pictorial description explanation and hear a spoken explanation. After reading, students completed the post-tests. The results of the study demonstrate that audio-picture annotation is more effective than text-picture annotation in facilitating immediate L2 vocabulary recall. The results suggestthat providing audio or text annotation of new words can help recall of new vocabulary when reading.
An Infrastructure to Support Usability Problem Data Analysis

Increasing the usability of software by integrating usability engineering into the development cycle has become common practice. Although usability engineering is effective, it can be expensive, and organizations want to receive the best possible returns on their investments. Oftentimes, however, organizations spend large sums of money collecting usability problem data through activities such as usability testing, but do not receive acceptable returns on those investments during redesign. The primary reason is that there is an almost complete lack of methods and tools for usability problem data analysis to transform raw usability data into effective inputs for developers. In this thesis, we develop an infrastructure for usability problem data analysis to address the need for better returns on usability engineering investments. The infrastructure consists of four main components: a framework, a process, tools, and semantic analysis technology. Embedded within the infrastructure is the User Action Framework, a conceptual framework of usability concepts, which is used to organize usability data. The process addresses extraction of usability problems from raw usability data, diagnosis of problems according to usability concepts, and reporting of problems in a form that is usable by developers. The tools leverage the framework and guide practitioners through the process, while the semantic analysis technology supplements the capabilities of the tools to automate parts of the process.
Combining Semi-Supervised Learning and Active Learning for Shallow Semantic Parsing

Semantic analysis is one of the fundamental and key problems in the research of content-based Text Mining.Most of supervised machine learning methods led to poor performance when work on limited tagged data.This paper investigated a novel semi-supervised learning algorithm—Transductive Support Vector Machine for shallow semantic parsing.An optimization strategy of selecting training instances,based on active learning,was integrated with TSVM.The experiment result shows that the method integrating TSVM and optimization strategy for shallow semantic parsing outperforms supervised methods on small tagged data.
Extracting Structured Information from Chinese Wikipedia and Measuring Relatedness between Words

The Wikipedia is the biggest web-based encyclopedia,which is written collaboratively by volunteers around the world.It has many advantages,such as wide knowledge coverage,highly structured and rapid information update.However,the Wikipedia official website just provides some original data files,and much structured semantic knowledge can't be used directly.Therefore,in this paper,we firstly extract the structured information from these data files;then,we design the object model for the information in Wikipedia,and provide an open API for Wikipedia information;finally,we propose a novel method to compute relatedness between words.
BioNLP 2010: Year in review

Humans are much more accurate at text mining than machines. Presumably this is because humans are more intelligent than machines. We argue that the way to narrow this gap is by more effective machine learning. One obvious difference between humans and machines is the large amounts of training data machines require for successful learning. We will discuss some novel ways of obtaining training data for machine learning. We will also discuss why humans appear to be different in their requirements for training data and what this may imply for the future of machine learning.
Strategic planning in ATM with a stochastic anytime approach

This paper presents a strategic trajectory de- confliction algorithm that can be applied during the pre- departure and the flight execution phases. The proposed method detects conflicts using an algorithm based on axis-aligned min- imum bounding box and resolves them cooperatively using a collision-free trajectory planning algorithm based on a stochastic optimization technique named Particle Swarm Optimization (PSO). PSO modifies the trajectories of the aircraft involved with an overall minimum cost. Determining optimal trajectories with short time intervals in the flight phase is not feasible, hence an anytime approach using PSO is applied. This approach yields trajectories whose quality increases with increase in available computation time. Thus, the method could be applied to Medium- Term Conflict Detection and Resolution (MTCDR) and even Short-Term Conflict Detection and Resolution (STCDR) depend- ing on the look-ahead times. The method has been validated with simulations in scenarios with multiple aircraft in a common airspace.
Multivariate Quality Control Chart Based on Projection Pursuit Methods

Genetic algorithms are employed to optimize projection directions.This paper analyzes the relationship between multivariate data and their projection.It is tested that if the multivariate data have a normal distribution,the projection of the data has the same distribution,so that the control of the data can transfer to the control of the projection.Simulation is included.
Introduction: Forecasting in peace research

Prediction and forecasting have now fully reached peace and conflict research. We define forecasting as predictions about unrealized outcomes given model estimates from realized data, and predictions more generally as the assignment of probability distributions to realized or unrealized outcomes. Increasingly, scholars present within- and out-of-sample prediction results in their publications and sometimes even forecasts for unrealized, future outcomes. The articles in this special issue demonstrate the ability of current approaches to forecast events of interest and contributes to the formulation of best practices for forecasting within peace research. We highlight the role of forecasting for theory evaluation and as a bridge between academics and policymakers, summarize the contributions in the special issue, and provide some thoughts on how research on forecasting in peace research should proceed. We suggest some best practices, noting the importance of theory development, interpretability of models, r.
Prädiktive Antriebsregelung zum energieoptimalen Betrieb von Hybridfahrzeugen

Die in dieser Arbeit beschriebene Pradiktive Antriebsregelung nutzt Telematikinformationen fur den kraftstoffoptimalen Betrieb von Hybridfahrzeugen. Es wird insbesondere die mathematische Modellbildung des Antriebsstrangs, die Pradiktion vorausliegender Fahrzustande sowie der Algorithmus zur Ermittlung optimaler Steuergrosen erlautert.
Security Analysis of the IEEE 802.1x Protocol

The 802.1x protocol is a protocol for port based net work access control,which was provided by IEEE in March,2001.This paper gives a brief introduction to architecture and authentication mechanism of the 802.1x protocol.It also presents some security problems existed in the 802.1x protocol and gives corresponding solutions.
Privacy and Personal Data Protection in Electronic Voting: Factors and Measures

In general, electronic voting as the technology advancement offers the opportunities to reduce the time and budget of implementation which present the greater advantages than traditional approach. It seeks establish the privacy framework in the context of electronic voting that aligns with the mutual comprehension of relevant factors and measures. The result found that privacy concern and perceived benefit have influenced personal data protection significantly. The success and failure of electronic voting implementation depend on the fulfilment of the voter needs on privacy and personal data protection.
Proposing a model for evaluating market efficiency of OTAs: Theoretical approach

As one of the most popular exchange intermediary for travel products, the online travel agencies (OTAs) compete fiercely. Previous studies on the OTA market efficiency focus on the travel product prices and distribution channels competition, but contradictions and paradoxes can be found between the theoretical explanations and empirical results. This article proposed a theoretical model by identifying two determinants of the OTA market efficiency: the matching ability and market size. The study shows that (1) the matching ability improves the market efficiency by enlarging the market size and increasing the effective range of competition; (2) the comparative advantage in matching ability of one OTA will lead to the efficiency occupation of other OTAs; and that (3) new OTAs or long tail travel products may reduce market efficiency, but it provides the opportunity to reconstruct the traditional industrial chain. This study enriches the economic theory of OTA and provides commercial guides for practice.
Think non-ethnic, but act ethnic: Perspectives from South Asian entrepreneurs

Literature pertaining to ethnic entrepreneurship assumes that religious-cultural and generational factors espouse the intention and ability of the entrepreneur towards business development. And by way of business growth and development, such entrepreneurs should breakout from their local ethnic customer base to service a wider non-ethnic customer base. In reality, many ethnic entrepreneurs lack the resources, the motivation, the ability and/or intention to do this. Consequently, the development and success of the business become hampered. To this end, working within a context of ethnic entrepreneurship, the aim of this paper is to examine the notion that entrepreneurial intention, ability and opportunity inform business growth, development and how the entrepreneur defines the success thereof. Addressing this, 48 semi-structured interviews and 11 comparative case studies were conducted with first- and second-generation South Asian Sikh, Hindu and Pakistani Muslim entrepreneurs within Greater London. A phenomenological paradigm was adopted, with key-words-in-context used to analyze data. Findings note there is no evidence of genuine breakout. Instead, what defines business development and growth is three approaches: (i) content to remain, (ii) forced to remain, and (iii) struggling to adjust. Hindered are attempts to increase the customer and market base beyond that of local clients. Additionally, differences and success between the two generations are reflective of sectorial location, intention, ability and skill-sets, rather than generational or cultural influences. Essentially, the paper presents an alternative view of how entrepreneurial intention, ability and opportunity facilitate or inhibit small business growth and success. However, given the sample-frame and, socio-economic environment within Greater London, findings may not be generalizable. In conclusion, debate pertaining to ethnic entrepreneurship needs to be re-examined; because placing emphasis on culture, religion, ethnicity and generation may be misleading researchers as to the true nature of business requirements, problems and support for ethnic entrepreneurs.
Chinese geo-coding based on classification database of geographical names

Geo-coding is widely used in urban spatial location and analysis,but there is no perfect solution on Chinese geo-coding for the present because there is no uniform specification and fixed model for Chinese geographical names.To solve this problem,the authors used Chinese geo-coding based on the classification database of geographical names in this paper,and detailed the key technologies to realize the program: database of geographical names data model,address split,and address matching.Finally,the authors verified the program through the actual data.The experimental results show that the program can solve most of the problems about address matching.
A Survey of Computer Vision Methods for Counting Fruits and Yield Prediction

In Agriculture the automatic methods for counting the number of fruits play a critical role in crop management. In this paper a review of previous studies and systems to count the number of fruits on trees and their yield estimation is performed. The various computer vision and optimization techniques are presented to automate the process of counting fruits. Further the main features and drawbacks of the previous systems in this area are summarized in this paper.
Interactive visualization for group decision-making

In infrastructure planning, identifying ‘the best solution’ out of a given set of alternatives is a context-dependent multi-dimensional multi-stakeholder challenge in which competing criteria must be identified and trade-offs made. In a recent study, colleagues from Institute of Resources, Sustainability and Environment found that there is a need for a visualization tool that enables planners and decision makers to collectively explore individual preferences among those involved in the decision. This thesis concerns designing and evaluating an interactive visualization tool that facilitates group decisions by making the problem analysis more participatory, transparent, and comprehensible. To do so, we extend the interactive visualization tool ValueCharts to create Group ValueCharts. We conducted studies with two different groups to evaluate the effectiveness of Group ValueCharts in group decision-making. The first group was university staff in leading positions in different departments, presently engaged in and responsible for water infrastructure planning. The second group was employees of an analytics company who are involved in buying scientific software licenses. Each group was instructed on how to use the tool in application to their current decision problem. The discussions were audio recorded and the participants were surveyed to evaluate usability. The results indicate that participants felt the tool improved group interaction and information exchange, and made the discussion more participatory. Additionally, the participants strongly concur that the tool reveals disagreements and agreements within the group. These results suggest that Group ValueCharts has the ability to enhance transparency and comprehensibility in group decision-making.
REAL-TIME ROOT CAUSE IDENTIFICATION ON STREAMING HETEROGENEOUS DATA USING SPARK

Root cause identification can provide huge breakthroughs in the process of business decision making. However, the huge size of input data requires a very highly sophisticated system to perform the analysis. This paper presents a parallelized root cause identification architecture that identifies a ranked list of root causes for the user’s query. The major components of the architecture includes conflict identification and elimination, parallelized data pre-processing, polarity identification and polarity based root cause identification. Experiments were conducted on dynamically retrieved data using APIs and the retrieved data is passed to the parallelized components implemented in Spark architecture. The in-memory processing architecture of Spark provides effective results in real-time, making the architecture scalable and robust
Goal Setting, Information, and Goal Revision: A Field Experiment

Abstract People typically set goals in settings where they cannot be sure of how they will perform, but where their performance is revealed to them in parts over time. When part of the uncertainty is resolved, initial goals may have turned out to be unrealistic and hence they no longer work as a motivation device. Revising goals may increase performance by making goals realistic, but may also adversely affect performance through reduced goal commitment. We study the effects of motivating university students to set goals and inviting them to revise their goals later, using a field experiment involving nearly 2,100 students. We use courses containing two midterms and a final exam, where midterms reduce uncertainty about students’ potential performance. We find that motivating students to set goals does not affect performance on average. Students with midterm grades lower than their goal, decrease their performance. This effect is driven by students who were motivated to set goals without being made aware that they can revise their goals later. This finding may help explain why the evidence of the effectiveness of goals on study performance is mixed.
Asymmetric Covariance, Volatility and the Impact of News

In this paper we investigate whether or not the conditional covariance between stock and market returns is asymmetric in response to good and bad news. Empirical observations such as the mean reversion of stock prices and asymmetric volatility can be readily explained by time varying risk premiums and it is the link between risk premiums and conditional covariance that we explore. Previous research has focussed on time varying betas but we propose that covariance asymmetry is a more powerful method of explaining such observed behaviour. Our model of conditional covariance accommodates both the sign and magnitude of return innovations and we find significant covariance asymmetry that can explain, at least in part, the mean reversion of stock prices and volatility feedback. We find little evidence in support of the leverage hypothesis of Christie (1982) in explaining asymmetric volatility. The results we obtain appear consistent across firm size, firm leverage, and temporal and cross sectional aggregations.
Value relevance of book values and earnings of listed non-financial firms in South Africa: a dynamic panel analysis

We analyse value relevance of book values and earnings before interest and taxes (EBIT) using a dynamic panel of non-financial firms listed on the Johannesburg Stock Exchange (JSE). In the aftermath of the global financial crisis, we seek to find out if share prices are linked to financial statement variables. A random sample of twenty-seven high- and low-capitalised firms was used. Using two-step System GMM with net asset value per share and average debt/equity ratio as additional regression instruments, we found EBIT to be value relevant but book value lacks value relevance. Analysts and investors on the JSE should thus focus more on EBIT when analysing companies they intend to invest in and should pay less attention to book value. Accounting standard setters can also put more measures that protect the integrity of reported EBIT as a way of helping investors and ensuring that accounting statements remain useful to investors.
Evaluation and Analysis of the Multimedia Course Books and Their Didactic Parts

Development of new teaching methods corresponding with current findings and modern didactic means initiated emergence of new forms of the educational materials. Multimedia course book is one of the materials mentioned which encompasses wide range of interactive, multimedia and hypermedia components. In Czech Republic, many multimedia course books are being introduced to market and the teacher must decide which one to choose. Many various aspects must be taken into account in process of choosing a course book, e.g. technical parameters, didactic equipment, control or quality of its individual parts. In case of common paper course books, approved evaluation tools are known. Can these tools be used for electronic course books as well? If yes, under what conditions? Should not we approach the multimedia course books as common pedagogic software? The authors have been dealing with possibilities of evaluating the multimedia course books in practice as well as in theory and they present some of possible solutions.