Miracle-dz/UniFAR-FTUs huggingface dataset:
Hexagonal Descriptor Particle Swarm Optimization with Knowledge-Crowding for Face Recognition

Automatic identification of various facial expressions with high recognition value is important for human computer interaction as the facial behavior of a human can be treated as an important factor for information representation as well as communication. A number of basic factors such as cluttered background, occlusion, and camera movement and illumination variations degrade the image quality resulting in poor performance for identifying different facial expressions. Moreover the identification of the automatic feature detection in facial behavior requires high degree of correlation between the training and test images. Face recognition is done by minimizing the objective function which leads to selection of optimal set of fiducial points. The method preserves the local information from different facial views for mapping neighboring input to its corresponding output, resulting in low dimensional representation for encoding the relationships of the data. The proposed method Hexagonal Descriptor Particle Swarm Optimization with Knowledge-Crowding (HDPSO-KC) overcomes from local optima and improves global search process and collaborative work. The method also covers the problem of eliminating the particles in denser regions in Pareto front distribution. The proposed methodology is validated with benchmark datasets for analyzing the performance over other methods.
Illiquidity and the Measurement of Stock Price Synchronicity

Prior research in accounting and finance uses stock price synchronicity, based on R2s from market model regressions, to measure stock price informativeness. The premise underlying this literature is that low levels of R2 are indicative of share prices reflecting more firm-specific information. Yet, empirical studies often find low R2 to be associated with variables that reflect a relatively weak information environment. Our study posits and provides evidence that stock illiquidity biases downwards the measurement of R2. Exploiting an exogenous shock to illiquidity, we demonstrate how reductions in illiquidity reduce this bias and cause increases in R2 measures. Using an international sample, we document that illiquidity is the primary determinant of the variation in R2 across and within countries. We demonstrate how failing to control for illiquidity in synchronicity research using the R2 measure can lead to biased coefficients that either reduce the power of tests or induce potentially false rejections of a null hypothesis. Lastly, we introduce a new method that can be used in testing changes in synchronicity around an event. This method circumvents the estimation of a market model and thereby minimizes the bias in the R2 measure induced by illiquidity.
SNET : a statistical normalisation method for Twitter

ii Declaration . iv Acknowledgements . v List of Figures . ix List of Tables . x List of Abbreviations . xi Chapter 1: Introduction . 1 1.1. Background of the study . 2 1.2. Objective of the Research . 4 1.2.1. Problem Statement . 4 1.2.2. Hypothesis . 6 1.3. Research Contributions . 6 1.4. Thesis Structure . 8 Chapter 2: Literature Review . 9 2.1. Informal Texts . 10 2.2. Noisy Texts . 11 2.3. Text Normalisation . 13 2.4. Problem Classification . 14 2.4.1. Problems at a character-level . 14 2.4.1.1. Misspellings . 14 2.4.1.2. Abbreviations . 18 2.4.1.3. Repeated characters . 20 2.4.1.4. OOV words . 20 2.4.2. Problems at a Sentence-level . 25 2.4.2.1. Ungrammatical sentences . 25 2.4.2.2. Missing words and punctuation issues . 26 2.5. Summary of Existing Normalisation Models at Character-level and Sentence-level . 27 2.6. Evaluation Approach . 32 Chapter 3: Normalisation Techniques . 36 3.1. Normalisation Setup . 37 vii 3.2. Data Collection . 38 3.3. Preparing of Collected Tweets . 39 3.4. The Use of English Dictionaries for Text Normalisation . 43 3.5. Types of Noisy Tweets . 43 3.6. Tokenising Text Algorithm . 46 3.7. Individual Techniques for Solving Each Noisy Problem . 47 3.7. 1. Techniques for Removing Repeated Characters . 49 3.7. 2. Techniques for Detecting Abbreviations . 50 3.7. 3. Techniques for Correcting Misspelled Words . 50 3.7. 4. Normalisation Process . 52 3.8. Statistical Normalisation Method for Twitter (SNET) . 56 3.9. Chapter Summary . 57 Chapter 4: Experimental Results and Discussion . 58 4.1. Experimental Setup . 58 4.2. Evaluation Metrics . 60 4.2.1. BLEU Metric . 60 4.2.2. WER Metric . 61 4.2.3. Paired t-tests . 62 4.2.4. Run-Time Efficiency . 63 4.3. Evaluation Results . 63 4.3.1. Results from Individual Techniques . 64 4.3.1.1. Removing repeated characters . 64 4.3.1.2. Detecting abbreviations . 66 4.3.1.3. Correcting misspelled words . 67 4.3.2. Results from Combination of Techniques . 69 4.3.2.1. The combination of RRC  DAB  SC techniques . 70 4.3.2.2. The combination of RRC SC  DAB techniques . 72 4.3.2.3. The combination of DAB  RRC  SC techniques . 74 4.3.2.4. The combination of DAB  SC  RRC techniques . 76 4.3.2.5. The combination of SC  RRC  DAB techniques . 78 4.3.2.6. The combination of SC  DAB  RRC techniques . 79 4.3.3. Baseline Model (Text Cleanser (TC)) . 81
Active Response System in Anomalous Intrusion Detection on Android

The mobile malicious programs would cause such face hazards economic loss,data loss and privacy leakages,et al.The paper,based on the existing Android intrusion detection systems,proposes the active response system in anomalous intrusion detection,thus to reduce the harm caused by malicious software.The system uses C/S structure,and the client collects the applications information in the smart-phone and is in charge of the response measures.The server analyzes promptly the executable file of applications from the client,finds the malicious programs which cause abnormal conditions to the phone.The experimental results show that this system could make timely and effective response to the abnormal behaviors found in the phone.
Climate Change and Inflation in WAEMU

The objective of our study is to analyze the effects of climate change on inflation in the WAEMU area. The equation of the Quantitative Theory of Money (QTM) and the generalized moments method (GMM) are retained. The annual data are from 1991 to 2015. We find that the main factors of inflation in WAEMU are economic growth, imported inflation and instability in rainfall. The authorities must therefore work to modernize agricultural techniques through the industrialization of the agricultural sector, literacy and the training of local farmers. In addition, states must make risk management a priority and allocate resources to it as part of local development plans.
Secure Multi-party Computation

SMC(Secure Multi-party Computation)mainly addresses the problem of cooperation within the distrustful partners,SMC requires the independence assurance of inputs and computation correctness,and meanwhile shouldn't leak any input to other partners. SMC could be widely used in internet ballot and internet auction. This paper analyzes the key technologies,including secure protocols,bit commitment,oblivious transfer,and zero-knowledge proof. Finally,the paper describes the applications of SMC,and these are significant in theory and practice.
Multi-Functional Platform for Indoor and Outdoor Monitoring

Wireless sensor networks have revolutionized the industry and science. In particular, these networks play a crucial role in monitoring indoor and outdoor events. While there are several solutions that solve multiple problems encountered in the field of monitoring with wireless sensor networks, many prove to be too specific. This makes it difficult to adapt applications for various types of monitoring. This thesis proposes a unique platform for sensor networks for monitoring events, allowing easy implementation of applications for this area and which is extensible and reconfigurable as much as possible. It also proposes a synchronization and aggregation protocol which can be used with the platform.
An Empirical Investigation of Volatility Dynamics in the Cryptocurrency Market

By employing an asymmetric Diagonal BEKK model, this paper examines volatility dynamics of five major cryptocurrencies, namely Bitcoin, Ether, Ripple, Litecoin, and Stellar Lumen. It is shown that the conditional variances of all the five cryptocurrencies are significantly affected by both previous squared errors and past conditional volatility. Moreover, in the case of Bitcoin, Ether, Ripple, and Litecoin, asymmetric past shocks have a significant effect in the current conditional variance. Similar results are obtained for the cryptocurrencies' conditional covariances, which are significantly affected by cross products of previous error terms and past covariance terms while capturing asymmetric effects of past shocks accordingly. It is also shown that time-varying conditional correlations exist and are mostly positive. Finally, the cryptocurrencies' volatility dynamics are found to be responsive to major news, with Bitcoin and Litecoin exhibiting one structural breakpoint each in the conditional variance. The results improve our understanding of interdependencies between cryptocurrencies as well as of the events that affect their volatility dynamics and thus have important implications for both cryptocurrency users and investors.
A NEW MESH SIMPLIFICATION ALGORITHM BASED ON VERTEX CLUSTERING

In computer graphics,models are often discribed by polygonal meshes.Because the rendering and storage cost is proportional to the number of polygons,too large models are not practical.Model simplification techniques are widely used in computer graphics fields such as computer animation,virtual reality and interactive scientific visualization.In this paper a new algorithm of mesh simplification based on vertex clustering is presented.The algorithm adopts octree structure to subdivide the mesh model adaptively.A new error control method is also presented.The implementation of the algorithm is simple and it runs very fast.Examples illustrate the efficiency of the algorithm.
A Korean Morphological Analyzer using a Pre-analyzed Partial Word-phrase Dictionary

The Korean morphological analysis based on corpus usually uses the pre-analyzed full word-phrase dictionary(FWD) that is constructed from the corpus. If input words are not found in the FWD, the morphemes of the input words are analyzed using complicated analysis rules: code transformation, decomposition of morphemes, and restoration of original form. Such complicated analysis rules are inefficient in terms of programming, maintenance, and runtime and cause to reduce its accuracy and performance. In order to solve these problems, the method using a pre-analyzed partial word-phrase dictionary(PWD) was researched. This paper proposes new method that constructs the PWD from tagged corpus and analyzes Korean morpheme using the PWD. According to the experiments on Sejong corpus, the recall of morpheme analysis is 99.05%. And the accuracy of POS with homonym tagging based on Hidden-Markov-Model is 96.76%.
(Not) Everyone Can Be a Winner - The Role of Payoff Interdependence for Redistribution

How does payoff interdependence affect preferences for redistribution? We experimentally implement a zero-sum setting and one in which everyone can be simultaneously successful. Across these, we compare redistribution given an identical level of inequality. First, two subjectsâ€™ performances in a real-effort task translate into chances of winning a prize. Across treatments, we vary the interdependence of payoffs: either there is only a single prize or both subjects can potentially win a prize at the same time. Afterwards, a spectator can redistribute the prize money. If payoffs are not directly interdependent, the average amount redistributed decreases by 14-22%. In additional treatments, solely performance determines the prize allocation. Nevertheless, the impact of payoff interdependence remains unchanged. Comparing the settings with and without randomness, we find that its mere presence increases redistribution, even though there is no uncertainty about the (relative) performance of the two subjects.
Inter-Observer Reliability Assessments in Continuous Observation Time Motion Studies

ii Dedication . iii Acknowledgments. iv Vita . v List of Figures . viii List of Tables . x Chapter 1: Introduction. 1 Chapter 2: Literature Review: Inter-Observer Reliability in Workflow Time Studies. 5 Chapter 3: Problem Statement. 18 Chapter 4: Evidencing the Limitations of a Single Score IORA. 27 Chapter 5: Development of a Composite IORA for Workflow Time Studies. 44 Chapter 6: Validation of Our Proposed IORA Protocol in a Real-World Workflow Time Study. 61 Chapter 7: Discussion. 76 Chapter 8: Conclusions. 87 References . 89 Appendix A: Functions . 96
A Good Night’s Sleep Matters for Tourists: An Empirical Study for Hospitality Professionals

The most important service hotels provide to their overnight guests is a good environment for sleeping. Business and holiday travelers have different perceptions of what makes a good sleep environment, and these perceptions are associated with satisfaction levels and return intentions. We develop and test a research model for guest satisfaction by drawing on trait activation theory. The model examines, simultaneously, the interactions between three sleep management practices and two types of travelers. Using both qualitative and quantitative methods, we find that traveler type moderates the relationship between the three sleep management practices—bed amenities, room design, and room environment—and guest satisfaction, which ultimately influences guest return intentions. The results indicate that offering the appropriate sleep environment for different types of travelers enhances their satisfaction levels and intentions to return. Theoretical and practical implications are discussed.
Modelling Evolutionary Long-Run Relationships: An Application to the Italian Energy Market

The paper considers a SUTSE model embedded in a dynamic framework to estimate an energy cost share model for the Italian economy in an evolutionary environment. This is achieved by allowing stochastic seasonal and trend components in the long-run specification and constructing an error correction mechanism to model short-run dynamics. Modelling instability in the structural time series approach has provided some improvement in the estimates of the elasticities of substitutions and of the price elasticities with respect to those obtained using deterministic trend and seasonal components. Tests for instability in the cointegrating regression support the evolutionary specification adopted. JEL classification: C51, C52, Q41 keywords: cointegration, energy substitution, strucutural time series approach, instability analysis * Address for correspondence: C. Morana, ICER, Villa Gualino, Viale Settimio Severo, 63, 10133, Torino, Italy. Tel (+39.11) 6603555, fax (+39.11) 6600082, e-mail: c.morana@iol.it. The author would like to thank ICER for providing funding and I.D. McAvinchey, A. Yannopoulos, A. Beltratti, F. Bagliano and R. Pecchenino for comments on a previous version of the paper. Many thanks also to B. Hansen to make available the GAUSS routine to carry out FMOLS and the instability tests. Any errors are my own.
Score level Fusion based Multimodal Biometric Identification.

Feature level based monomodal biometric systems perform person recognition based on a multiple sources of biometric information and are affected by problems like integration of evidence obtained from multiple cues and normalization of features codes since they are heterogeneous, in addition of monomodal biometric systems problems like noisy sensor data, non-universality and lack of individuality of the chosen biometric trait, absence of an invariant representation for the biometric trait and susceptibility to circumvention. Some of these problems can be alleviated by using multimodal biometric systems that consolidate evidence from scores of multiple biometric systems. In this work, we address two important issues related to score level fusion. We have studied the performance of a score level fusion based multimodal biometric system against different monomodal biometric system based on voice, fingerprint modalities and a bimodal biometric system based on feature level fusion of the same modalities. These systems have been evaluated in terms of their efficiency and identification rate on a close group from the test data. These results are shown using cumulative match characteristic curve. KeywordsFusion strategies; Multimodal biometrics; SVM; Gabor filters; MFCC.
AUTOMATIC TEST PACKET GENERATION IN NETWORK

Now a day’s we see that networks are widely distributed so administrators depends on various tools such as ping and traceroute to rectify the problem in the network. We proposed an automated and systematic approach for testing and debugging network called "Automatic Test Packet Generation"(ATPG). Initially ATPG reads router configuration and then generates a model which is device freelance. The model is used to generate the minimum number of test packets to cover every link and rule in network. ATPG is capable for detecting both functional and performance problems. Test packets are sent at regular intervals and special technique is used to localize faults.
The Institutional Framing of Policy Debates: Economics Versus the Environment

By framing the economics versus environment debate as a mixed-motive situation, opportunities become visible which allow greater benefits to all interests in the debate. Yet, social, cultural and institutional arrangements frame how we see these opportunities, creating a barrier to mixed-motive analyses. In this paper, we will use an institutional perspective to analyze how the economics versus environment debate emerges from institutions as presently structured. We will present an analysis of its present framing based on three aspects of institutions — regulative, normative and cognitive — and consider the prescriptive implications they expose at the managerial and organizational level of action. We conclude with an analysis of possible solutions to overcome them.
Warming and GDP Growth in the United States: A Heterogeneous, Common Factor Dynamic Panel Analysis

This paper analyzes whether temperature changes influence economic growth in the contiguous 48 US states by employing panel methods that address both heterogeneity and cross-sectional dependence. Ultimately, it is determined that the negative effect of warming (proxied by cooling degree days) is restricted to agriculture GDP and found in only a few (mostly northern and more agriculturally dependent) states. But when weathers’ impact was measured by average summer temperature, the negative effect — still restricted to agriculture GDP — was substantially and significantly larger (a finding similar to previous work) and more geographically uniform.
TreeSnap: A citizen science app connecting tree enthusiasts and forest scientists

Citizen science engages non‐professional scientists in scientific re‐ search (Bonney et al., 2009; Conrad & Hilchey, 2011; Dickinson et al., 2012; Dickinson, Zuckerberg, & Bonter, 2010; McKinley et al., 2017). For researchers, citizen science offers exciting opportunities to ex‐ pand the range and scope of data collected and involve a broader and more diverse group of observers and data contributors (Pocock, Tweddle, Savage, Robinson, & Roy, 2017). By incorporating a large number of interested people working in parallel, citizen science has the potential to accelerate the pace or expand the scope of research projects. In today's world of constrained research funding, commu‐ nicating the value of scientific research to the public is increasingly important yet avenues for sharing scientific research with general audiences are few and researchers typically have little institutional support for education and outreach activities, despite outreach Received: 1 February 2019 | Revised: 10 April 2019 | Accepted: 16 April 2019 DOI: 10.1002/ppp3.41
Analysis of Java Programs Using Bytecode Based Frameworks

Java SDG(System dependence Graph) API and JOANA (Java Object-sensitive Analysis) are two bytecode based analysis frameworks available for analyzing object oriented java programs for different applications. In the present era, the continuous evolution of the customer expectations and requirements has resulted in the increase of size of the software. This arises the problems in maintaining software. Both the frameworks i.e Java SDG API and Joana consist of different variety of analysis techniques which are based on dependence graph generation and computation of slices of an input program. In our work, we make a comparative analysis study on the effectiveness and efficiency of both these above mentioned analysis frameworks in generating the corresponding intermediate dependence graph and computing slices. The dependence graph we have generated is SDG and we have used backward slicing approach in order to compute slices. The two-phase graph reachability algorithm is used in our work in case of Java SDG API in order to perform slicing. The two web start applications are used in order to generate and view SDG in case of Joana which are IFC console and Joana graph viewer. The analysis is based on the bytecode of the program under consideration. The experimental analysis shows that Joana can be extended for more diverse applications.
Assessing Banking Profit Efficiency Using Stochastic Frontier Analysis

Objective - The banking sector plays an important role in the Indonesian economy. The sustainability of the Indonesian banking sector will depend on the ability of every banking institution to maintain their competitiveness. Banking competitiveness is reflected in the level of efficiency of the banking system itself. Methodology/Technique - The purpose of this research is to assess the efficiency of 21 banks on the IDX between 2008-2017 using Stochastic Frontier Analysis. Findings - The findings of this research show a maximum efficiency score of 0.69 and the bank's average score among the research sample with the input and output allocation which can generate profits is 0.69 - 0.43 = 0.26. Overall, the banking sector in the Indonesian capital market between 2008 - 2017 recorded an efficiency score of 0.43. With this score, the banking system in the Indonesian capital market is still considered to be inefficient (0.43 <0.5). The results also demonstrate that the distribution of efficiency scores polarized in two poles. In the first pole, there were 11 banks that had a relatively good efficiency score (> = 0,5) and in the second pole, there were 10 banks with low efficiency scores (less than 0.5). Novelty – From the results, it can be concluded that several output variables, such as total loans (Y1) and securities (Y3), and input variables such as prices of labor (W2) and inflation (Z), have a significant effect on banking profits. Meanwhile, input variables such as the price of fund variables or the total funds (W1) and the price of physical capital were reflected in the depreciation of fixed assets (W3), and the output variables of income and interest (Y2) had an insignificant effect on bank profits. Type of Paper - Keywords: Bank Efficiency; IDX, Stochastic Frontier Analysis, Indonesia. JEL Classification: G10, G14, G19.