Miracle-dz/UniFAR-FTUs huggingface dataset:
A Dynamic Data Structure for Real Time Face Recognition

Intelligent Face Recognition systems, capable of recognizing persons' identity from their face images for surveillance and authentication purposes, are required to respond in real time. The recognition of the identity of an unknown face in real time is a major challenge due to heavy computational requirements of training and testing large number of face images. The data structure plays an important role in reducing the access time to fetch the data for execution by the CPU. In this paper, a dynamic data structure is proposed which enables real time face recognition. Haar wavelets’ multi-resolution features are used corresponding to all scales that describe each face image. The proposed work enables extraction of the features for all face images in the given face data base and trains the classifier in maximum 5-6 seconds while it takes only 0.02 second on an average, i.e. near real time, to recognize an unknown face image.
Trends of ozone and meteorological parameters at high alpine sites

Climate change and changes in the large scale chemical composition of the atmosphere influence thebiodiversity in and the appearance of protected areas even at remote sites. Data sets from Global Atmosphere Watch (GAW) stations are most appropriate to study background air pollution and meteorological trends. For the alpine sites Sonnblick, Jungfraujoch and Hohenpeißenberg we found increasing ozone concentrations until≈ 2003 especially in winter, whereas in summer there is a small decrease (period 1993-2011). The ozone increase in winter is favoured by changes in the air flow regimes and – to some degree – in an increasing sunshine duration, whereas in summer thereare notrendsin those meteorological parameters that are relevant for ozone.
CURVE COUNTING AND BIRATIONAL GEOMETRY OF COMPACTIFIED MODULI SPACES OF CURVES

Although curve counting has been studied for thousands of years, it still remains an active area of research. Recent introduction of virtual intersection theory by Li-Tian ([37]) and Behrend-Fantechi ([3, 4]) provided an efficient way of constructing a curve counting invariant which remains constant under deformation. Examples include Gromov-Witten invariants, Donaldson-Thomas invariants, and Pandharipande-Thomas invariants. All these invariants are defined as the virtual intersection numbers on compactified moduli spaces of curves in a given smooth projective variety X. The purpose of this paper is to discuss two major issues for curve counting invariants. (1) Comparison of the compactified moduli spaces of curves. (2) Methods of calculating virtual intersection numbers. For item (1), the moduli space of smooth curves in X can be compactified by taking closures in the Hilbert scheme, the stable map space, or the moduli space of semistable sheaves. We will see recent comparison results of these compactifications in two directions; one by Mori theory and the other by elementary modification. For item (2), we will itemize all known methods for calculating virtual intersection numbers. Special emphasis will be laid on the method of localization by cosection due to J. Li and the author ([24]). Various applications are discussed as well. The layout of this paper is as follows. Quick introductions on curve counting invariants and virtual intersection theory are given in §2 and §4 respectively. In §3, we recall several well-known compactified moduli spaces of curves. In §5, we state the comparison problem for rational curves and survey Mori theoretic results. In §6, comparison results by elementary modification are discussed. In §7, a closely related problem of comparing compactifications of M0,n is discussed.
Development of a regional flood frequency estimation model for Pilbara, Australia

This paper presents the development of regional flood frequency estimation (RFFE) models for Pilbara, Western Australia as a part of Australian Rainfall and Runoff (ARR) revision. The Pilbara is an economically important arid region, which is rich in natural resources and mining activities. A total of 11 catchments are selected from the Pilbara region to develop the RFFE models. The selected catchments are arid with average annual rainfall values are in the range of 200 and 350 mm. For each of the selected catchments, flood quantiles are estimated for 6 annual exceedance probabilities (AEPs), which are 50%, 20%, 10%, 5%, 2% and 1% using two estimation approaches: (i) annual maximum flood series (AMS): Log Pearson Type 3 (LP3) distribution-Bayesian procedure and (ii) partial duration series (PDS) (with average number of events per year equal to 0.5): Generalised Pareto distribution and L moments procedure. The AMS consists of maximum discharge value in each calendar year; however, the PDS consists of all the independent peak flows over a certain threshold. Two different RFFE models are developed (using AMS and PDS data) using an index flood method where the 10% AEP flood quantile (Q10) is used as the index variable and a dimensionless growth factor for AEP of x% (GFx) is used to estimate Qx (where, x = 50%, 20%, 10%, 5%, 2% and 1%). The prediction equation for the index flood is developed using an ordinary least squares regression with two predictor variables (catchment area and design rainfall intensity). The results demonstrate that the performance of the two RFFE models is quite similar. For AEPs of 50% to 1%, the absolute median relative error values of the estimated flood quantiles are found to be in the range of 23% to 46% and 42% to 56% for AMS and PDS based RFFE models, respectively. The results reveal that both the models are able to generate flood quantiles with a good accuracy; however the AMS-based RFFE model outperforms the PDS-based model.
A simpler construction of traceable and linkable ring signature scheme

Traceable and linkable ring signature scheme (TLRS) plays a major role in the construction of auditable privacy-preserving blockchain-s, as it empowers the auditor with traceability of signers’ identities. A recent work by Li gives a modular construction of TLRS by usage of classic ring signature, one-time signature and zero-knowledge proofs, and has security against malicious auditors. In this paper, we introduce sTLRS, a simpler modi(cid:12)cation of TLRS which is constructed directly from classic ring signature, without any additional one-time signatures or zero-knowledge proofs. sTLRS has public key size reduced by 80% and veri(cid:12)cation time reduced by over 50%, compared to TLRS. Moreover, we can further modify the sTLRS to achieve anonymity, unforgeability, link-ability, nonslanderability and traceability against malicious auditors.
Bayesian Methods in Nutrition Epidemiology and Regression-based Predictive Models in Healthcare

Bayesian Methods in Nutrition Epidemiology and Regression-based Predictive Models in Healthcare. (December 2010) Saijuan Zhang, B.S., Southeast University; M.A., University of Oklahoma Co–Chairs of Advisory Committee: Dr. Raymond J. Carroll Dr. Jianhua Huang This dissertation has mainly two parts. In the first part, we propose a bivariate nonlinear multivariate measurement error model to understand the distribution of dietary intake and extend it to a multivariate model to capture dietary patterns in nutrition epidemiology. In the second part, we propose regression-based predictive models to accurately predict surgery duration in healthcare. Understanding the distribution of episodically consumed dietary components is an important problem in public health. Short-term measurements of episodically consumed dietary components are zero-inflated skewed distributions. So-called two-part models have been developed for such data. However, there is much greater public health interest in the usual intake adjusted for caloric intake. Recently a nonlinear mixed effects model has been developed and fit by maximum likelihood using nonlinear mixed effects programs. However, the fitting is slow and unstable. We develop a Monte-Carlo-based fitting method in Chapter II. We demonstrate numerically that our methods lead to increased speed of computation, converge to reasonable solutions, and have the flexibility to be used in either a frequentist or a Bayesian manner. Diet consists of numerous foods, nutrients and other components, each of which have distinctive attributes. Increasingly nutritionists are interested in exploring
RESEARCH ON MONITORING OF VOLCANIC DEFORMATION USING SAR INTERFEROMETRY

Crustal deformation is one of important information for understanding of magma behavior under the volcano. We are monitoring such deformation at volcanic observation stations which have GPS, tiltmeter, strainmeter, and so on. However it is not often enough for its full understanding because of complexity of its spatial distribution. Since constructing denser observation network is not realistic, we want to utilize interferometric synthetic aperture radar technique (InSAR) for covering an insufficiency of the observation density. InSAR is one of tools which can detect specially detailed crustal deformation, and has been used in crustal deformation studies of worldwide volcanoes. However InSAR is usually disturbed by some noise sources, the atmospheric, the ionospheric, and so on. Such noise obscures crustal deformation signal, and sometimes causes a misinterpretation for crustal deformation. Recently numerical weather model with high precision is available, and the simulation of atmospheric delay using its result came to be able to reduce the atmospheric noise precisely. Ozawa and Shimizu [1] obtained the accuracy of 1.3cm in 1-sigma confidence in a case study of the atmospheric delay simulation in Mt. Fuji, the highest mountain in Japan. However it is not always enough for understanding of volcanic activity. Then InSAR timeseries analysis such as small baseline approach (SBAS) [2] is used recently. Especially, SBAS approach can obtain deformation time-series by simple least-square method, and then was used in many researches. Basically, SBAS approach uses interferograms obtained for single orbit path, and reduces a noise which depends on a condition of observation time by only the effect of smoothing. Then advanced InSAR time-series analysis with additional noise reduction effect will enable us to detect more precise deformation and to understand more detailed magma behavior. Moreover SBAS approach has a problem that interferograms by different observation modes and/or by different SAR sensors cannot be connected directory. For resolving such problem and for improving accuracy of deformation detection, we devised InSAR time-series analysis using interferograms for multiple observation modes. In this study, we propose this new InSAR time-series approach, and demonstrate its usefulness from case studies in Japanese volcanic islands. 2. INSAR TIME-SERIES ANALYSIS
Exploring Energy Efficient Quantum-resistant Signal Processing Using Array Processors

Quantum computers threaten to break public-key cryptography schemes such as DSA and ECDSA in polynomial time, which poses an imminent threat to secure signal processing. Ring learning with error (RLWE) lattice-based cryptography (LBC) is one of the most promising families of post-quantum cryptography (PQC) schemes in terms of efficiency and versatility. Two conventional methods to compute polynomial multiplication, the most compute-intensive routine in the RLWE schemes, are convolutions and Number Theoretic Transform (NTT). In this work, we explore the energy efficiency of polynomial multiplier using systolic architecture for the first time. As an early exploration, we design two high-throughput systolic array polynomial multipliers, including NTT-based and convolution-based, and compare them to our low-cost sequential (non-systolic) NTT-based multiplier. Our sequential NTT-based multiplier achieves 3x speedup over the state-of-the-art FGPA implementation of the polynomial multiplier in the NewHope-Simple key exchange mechanism on a low-cost Artix7 FPGA. When synthesized on a Zynq UltraScale+ FPGA, the NTT-based systolic and convolution-based systolic designs achieve on average 1.7x and 7.5x speedup over our sequential NTT-based multiplier respectively, which can lead to generating over 2x more signatures per second by CRYSTALS-Dilithium, a PQC digital signature scheme. These explorations help designers select the right PQC implementations for making future signal processing applications quantum-resistant.
Flexitime and employee happiness at workplace: A quantitative study of software houses

Employee happiness is an emerging concept that has been incorporated with internal workplace flexibility or flexitime. The aim of this study is to find out the relationship of internal workplace flexibility with employee happiness. Employee happiness at the workplace has been studied through the lens of three components, including affective organizational commitment, employee engagement and job satisfaction. These constructs have been studied collectively to acquire a comprehensive understanding regarding their relationships, outcomes and influences on one another. For this study, data have been collected from ten registered software houses of Lahore, Pakistan, through selfadministrated questionnaire, 358 participants participated in the survey. Non-parametric analysis of the data shows that flexitime has a positive relationship with affective organizational commitment, employee engagement, job satisfaction and thus employee happiness. Thus it can be concluded that when organizations give discretion to its employees to decide about when, where, what and how to work, it makes employees more committed, engaged, satisfied and thus happier.
How Knowledge about or Experience with Hydrogen Fueling Stations Improves Their Public Acceptance

Hydrogen, which is expected to be a popular type of next-generation energy, is drawing attention as a fuel option for the formation of a low-carbon society. Because hydrogen energy is different in nature from existing energy technologies, it is necessary to promote sufficient social recognition and acceptability of the technology for its widespread use. In this study, we focused on the effect of initiatives to improve awareness of hydrogen energy technology, thereby investigating the acceptability of hydrogen energy to those participating in either several hydrogen energy technology introduction events or professional seminars. According to the survey results, participants in the technology introduction events tended to have lower levels of hydrogen and hydrogen energy technology knowledge than did participants in the hydrogen-energy-related seminars, but confidence in the technology and acceptability of the installation of hydrogen stations near their own residences tended to be higher. It was suggested that knowledge about hydrogen and technology could lead to improved acceptability through improved levels of trust in the technology. On the other hand, social benefits, such as those for the environment, socioeconomics, and energy security, have little impact on individual levels of acceptance of new technology.
On the absorption of cosmic radiation by employment of fullerene-bound 2- (2,6-dihydroxophenyl)benzaldehyde

By switching between several conformational and chemical modes, 2-(2,6-dihydroxophenyl)benzaldehyde can absorb harmful radiation, especially cosmic radiation. Dispersion of fullerenes carrying adsorbed 2-(2,6-dihydroxophenyl)benzaldehyde in the Martian stratosphere and mesosphere should contribute considerably to the atmospheric protection from harmful radiation on Mars.
Survey on Spatial Keyword Search

Many applications are featured with both text and location i nformation, which leads to a novel type of search: spatial keyword search (SKS). The SKS is gain ing attention from the database community only recently. A large variety of problems remain ope n. Spatial and text data have been independently studied for decades. Spatial data have many u nique features that are drastically different from text data. As a result, most of the existing techn iques for string processing are either inapplicable or inefficient when adapted to spatial databas es. My Ph.D research is in the general area of SKS. The areas related to my research include the near st neighbor search, range search, approximate string search, the spatial keyword and approxima te string search. This document surveys these related areas.
Effects of Different Culture Media, Carbon and Nitrogen Sources and Solid Substrates on Growth of Termitomyces Mushrooms

In 2009-2011, five different Termitomyces sporocarps were collected from Chiang Mai, Payao and Petchaboon Provinces in Thailand and pure cultures were isolated. Fungi were identified based on morphological and molecular characteristics. One isolate was identified as T. clypeatus while the others probably represent four unknown species. Growth on different carbon, nitrogen and solid substrates was tested. Of ten culture media, malt extract agar was the best for mycelia growth for all isolates. Sucrose was the best carbon source for Termitomyces sp. CMUTM001 and CMUTM002. Fructose was the best carbon source for T. clypeatus CMUTM003 and CMUTM005, while the best growth of isolate CMUTM005 was on glucose. Peptone was the best nitrogen source for enhancing radial growth. In addition, job’s tear grain medium gave the highest mycelial growth and may be a suitable substrate for Termitomyces mycelial inocula production. This study provides valuable information concerning the cultivation of Termitomyces mushrooms.
Ayrılık Nedenleri Ölçeği: Geçerlik ve Güvenirlik Çalışması

The current study aims to test the reliability and validity of the Sprecher’s (1994) “Reasons for the Breakup” scale. The sample consisted of 165 female and 47 male (a total of 212) who experienced a break up within the past one year. Both exploratory (principal) and confirmatory analyses were used to test the factor structure of the scale. Results revealed a five-factor solution for the scale. These are the reasons referring to the partner, reasons referring to the self, personal difference, reasons referring to the relationship/dyad or interaction, and reasons referring to the external factors. All standardized factor loadings were significant in the confirmatory factor analysis. Factor loadings of the items ranged from . 41 and . 87 for reasons referring to the partner, . 53 and . 82 for reasons referring to the self, . 51 and . 62 for reasons referring to the relationship/dyad or interaction, and . 26 and . 97 for reasons referring to the external factors. Additionally, the relationship between the sub-factors of reasons for the breakup and attachment dimensions (attachment anxiety and avoidance), experienced negative and positive emotions after the breakup, and overall distress were examined. Attachment anxiety was positively associated with reasons referring to the partner and reasons referring to the relationship/dyad or interaction and negatively associated with reasons referring to the self. In terms of experienced emotions, while reasons referring to the partner sub-scale were positively related with negative emotional experience and overall distress, it was negatively related with positive emotional experience. In conclusion, the findings indicated that the Turkish version of the scale is a reliable tool in the assessment of the reasons for the breakup in romantic relationships.
EVALUATING AND VALIDATING THE PROTOCOL FOR GAMMA (γ) RADIATION INDUCED MUTATIONS IN FLORAL DISTINCT ROSA SPP

Among the highly fragrant Rosa species, Rosa gruss an teplitz and Rosa centifolia have high value in terms of commercial importance and economical trade. However, the absence of floral diversification and diversity in color patterns in these species acts as limiting factors in floriculture trade of these species. In the present study, we aimed to induce mutations using gamma radiations up to 120 Gy to observe the rate and the correlated effects on the several plant traits in micropropagated shoot tips of Rosa gruss an teplitz and Rosa centifolia. Irradiated shoot tips were micropropagated for one culture cycle and were acclimatized in a green house after in vitro rooting. Plants of irradiated population at 60 and 30 Gy showed 78.12 and 38.50% less culture rooting % age as well as 23.82 and 7 % less flower size as compared to non irradiated population of Rosa gruss an teplitz and Rosa centifolia respectively. Moreover, flower color component a* (+ redness – green, 36.16 and 27.16) and chroma (37.77 and 27.5) depicted minimum while L* (Lightness, 45.12 and 76.64), b* (+ yellow – blue, 10.69 and -4.14) and hue angle (17.1 and -8.58) maximum value. Apart from these variations, mutants of Rosa gruss an teplitz also produced variegated, pink color and different shape flowers. Genetic variations observed among the putative mutants of Rosa gruss an teplitz and Rosa centifolia were evaluated using twelve decamer RAPD primers. Phylogenetic inferences showed large genetic diversity in putative mutants as compared to mother plant.
CHARACTERIZATION AND IMPLEMENTATION OF AN INTEGRATED AUTOREGRESSIVE MODEL TO PREDICT THE THERMAL PERFORMANCE OF VEGETAL FAÇADES

This article presents the results of an experimental study carried out in a vegetal façade situated in a locality close to Madrid. The objectives of the study are to develop a performance predictive model of a vegetal façade whose independent variables are irradiance, exterior temperature and relative humidity, based on the effect of the vegetation on the environmental conditions of the building, as well as to characterize thermally the vegetal element by comparing two identical enclosures (with a vegetal layer present in one of them being the only difference). The results of the three-year monitoring period are analyzed by means of statistical data processing and an autoregressive model is fitted. This model estimates the temperature difference between both enclosures. The validation of the model based on the experimental data is done subsequently. Once the improvements caused by the vegetation on the interior environmental conditions of the building have been quantified, the results show that it is possible to predict with high accuracy the vegetation's performance, being the multiple R-squared of the estimated models around 85%. Furthermore, the application of the model is suitable for other buildings located in a similar climate to the one studied, as the independent variables exclusively depend on climate conditions.
Strategic Capacity Management When Customers Use Anecdotal Reasoning

http://repository.ust. hk/ir/ This version is available at HKUST Institutional Repository via If it is the author’s pre-published version, changes introduced as a result of publishing processes such as copy-editing and formatting may not be reflected in this document. For a definitive version of this work, please refer to the published version. Strategic Capacity Management When Customers Have Boundedly Rational Expectations
Integrating cochlear dead region diagnosis into the hearing instrument fitting process Fo cu s

It is well known that sensory hearing impairment is accompanied by supra-threshold deficits such as degraded frequency and temporal resolution. Until now, there have been few hearing instrument fitting rationales that have relied on these supra-threshold deficits to determine the optimal parameters of a particular hearing instrument fitting. However, recent research suggests that procedures which measure the extent of cochlear dead regions might influence aspects of the optimal prescribed frequency-gain characteristic. Individuals with a cochlear dead region may have different frequency-gain requirements than those with no dead region. New or revised fitting rationales may include an optional formula that can be used when there is evidence for cochlear dead regions (Dillon, 2006). Diagnosing the presence and the extent of a dead region may have important clinical implications for counselling and hearing instrument provision. 38