Miracle-dz/UniFAR-FTUs huggingface dataset:
SLEUTH: Single-pubLisher attack dEtection Using correlaTion Hunting

Several data management challenges arise in the context of Internet advertising networks, where Internet advertisers pay Internet publishers to display advertisements on their Web sites and drive traffic to the advertisers from surfers' clicks. Although advertisers can target appropriate market segments, the model allows dishonest publishers to defraud the advertisers by simulating fake traffic to their own sites to claim more revenue. This paper addresses the case of publishers launching fraud attacks from numerous machines, which is the most widespread scenario. The difficulty of uncovering these attacks is proportional to the number of machines and resources exploited by the fraudsters. In general, detecting this class of fraud entails solving a new data mining problem, which is finding correlations in multidimensional data. Since the dimensions have large cardinalities, the search space is huge, which has long allowed dishonest publishers to inflate their traffic, and deplete the advertisers' advertising budgets. We devise the approximate SLEUTH algorithms to solve the problem efficiently, and uncover single-publisher frauds. We demonstrate the effectiveness of SLEUTH both analytically and by reporting some of its results on the Fastclick network, where numerous fraudsters were discovered.
Microbial abundance in surface ice on the Greenland Ice Sheet

Measuring microbial abundance in glacier ice and identifying its controls is essential for a better understanding and quantification of biogeochemical processes in glacial ecosystems. However, cell enumeration of glacier ice samples is challenging due to typically low cell numbers and the presence of interfering mineral particles. We quantified for the first time the abundance of microbial cells in surface ice from geographically distinct sites on the Greenland Ice Sheet (GrIS), using three enumeration methods: epifluorescence microscopy (EFM), flow cytometry (FCM), and quantitative polymerase chain reaction (qPCR). In addition, we reviewed published data on microbial abundance in glacier ice and tested the three methods on artificial ice samples of realistic cell (102–107 cells ml−1) and mineral particle (0.1–100 mg ml−1) concentrations, simulating a range of glacial ice types, from clean subsurface ice to surface ice to sediment-laden basal ice. We then used multivariate statistical analysis to identify factors responsible for the variation in microbial abundance on the ice sheet. EFM gave the most accurate and reproducible results of the tested methodologies, and was therefore selected as the most suitable technique for cell enumeration of ice containing dust. Cell numbers in surface ice samples, determined by EFM, ranged from ~ 2 × 103 to ~ 2 × 106 cells ml−1 while dust concentrations ranged from 0.01 to 2 mg ml−1. The lowest abundances were found in ice sampled from the accumulation area of the ice sheet and in samples affected by fresh snow; these samples may be considered as a reference point of the cell abundance of precipitants that are deposited on the ice sheet surface. Dust content was the most significant variable to explain the variation in the abundance data, which suggests a direct association between deposited dust particles and cells and/or by their provision of limited nutrients to microbial communities on the GrIS.
Numerical Generation and Absorption of Fully Nonlinear Periodic Waves

Permanent form periodic waves with zero-average mass flux are generated in a two-dimensional numerical wave tank solving fully nonlinear potential flow equations. An absorbing beach is modeled at the end of the tank in which (1) an external free-surface pressure absorbs energy from high frequency waves; and (2) a pistonlike condition absorbs energy from low-frequency waves. A feedback mechanism adaptively calibrates the beach parameters to absorb the period-averaged energy of incident waves. Wave generation and absorption are validated over constant depth, for tanks and beaches of various lengths, and optimal parameter values are identified for which reflection from the beach is reduced to a few percent. Shoaling of periodic waves is then modeled over a 1:50 slope, up to very close to the breaking point. A quasi-steady state is reached in the tank for which (not previously calculated) characteristics of fully nonlinear shoaling waves are obtained.
CLIP at TREC 2016 : LiveQA and RTS

The Computational Linguistics and Information Processing lab at the University of Maryland participated in two TREC tracks this year. The LiveQA and the Real-Time Summarization tasks both involve information processing in real time. We submitted eight runs in the total. In both tasks, our best system had the highest precision among all automatic participating systems. This paper describes the architecture and configuration of the systems behind those runs.
Susceptibility of Modern Systems and Software to Soft Errors

It is widely understood that most downtime is accounted for by programming errors and administration time. However, recent work has indicated an increasing cause of downtime may stem from transient hardware errors caused by external factors, such as cosmic rays. Moving to denser semiconductor technol- ogies at lower voltages will cause an increase in transient errors. We investigate the trends in transient errors and the susceptibility of operating systems and applications to them, and we introduce ideas regarding software transient error recoverability. We believe that if transient errors become a prominent prob- lem, that it will be possible to improve commodity system availability with simple software recovery. Results indicate that in the Linux kernel and a Java virtual machine few errors need to be fatal. We also propose two recovery examples which we believe indicate that it is possible to increase error detec- tion and recovery without the cost of a fail-over cluster.
XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification.

Metabolite profiling in biomarker discovery, enzyme substrate assignment, drug activity/specificity determination, and basic metabolic research requires new data preprocessing approaches to correlate specific metabolites to their biological origin. Here we introduce an LC/MS-based data analysis approach, XCMS, which incorporates novel nonlinear retention time alignment, matched filtration, peak detection, and peak matching. Without using internal standards, the method dynamically identifies hundreds of endogenous metabolites for use as standards, calculating a nonlinear retention time correction profile for each sample. Following retention time correction, the relative metabolite ion intensities are directly compared to identify changes in specific endogenous metabolites, such as potential biomarkers. The software is demonstrated using data sets from a previously reported enzyme knockout study and a large-scale study of plasma samples. XCMS is freely available under an open-source license at http://metlin.scripps. edu/download/.
Transfer Learning in Hierarchical Feature Spaces

Transfer learning provides an approach to solve target tasks more quickly and effectively by using previously acquired knowledge learned from source tasks. As one category of transfer learning approaches, feature-based transfer learning approaches aim to find a latent feature space shared between source and target domains. The issue is that the sole feature space can't exploit the relationship of source domain and target domain fully. To deal with this issue, this paper proposes a transfer learning method that uses deep learning to extract hierarchical feature spaces, so knowledge of source domain can be exploited and transferred in multiple feature spaces with different levels of abstraction. In the experiment, the effectiveness of transfer learning in multiple feature spaces is compared and this can help us find the optimal feature space for transfer learning.
A New Lower Bound for the List Update Problemin the Partial Cost ModelJune 21 , 1999

The optimal competitive ratio for a randomized online list update algorithm is known to be at least 1.5 and at most 1.6, but the remaining gap is not yet closed. We present a new lower bound of 1.50084 for the partial cost model. The construction is based on game trees with incomplete information, which seem to be generally useful for the competitive analysis of online algorithms.
Inbreeding and outbreeding depression in male courtship song characters in Drosophila montana

In Drosophila montana, male courtship song frequency is closely associated with male courtship success and offspring survival. Other pulse characters (pulse length and cycle number) may also affect female mate choice, whereas pulse train characters (interpulse interval, pulse number and pulse train length) are not associated with these male fitness components. Inbreeding depression in these song characters was investigated by comparing the songs of inbred and outbred fly strains. The average change in most song characters as a result of inbreeding was only a few percent. However, in male song frequency the average inbreeding depression was about 14%, suggesting that this song character is associated with fitness. Outbreeding depression and the genetic architecture of song characters were investigated with interpopulation crosses and joint scaling tests. For pulse train characters the generation means show only evidence of additivity, and the existence of dominance or epistasis in these characters was strongly rejected in each case. In pulse characters the means of the F1 males were lower than the average of the parental generations. In pulse length and cycle number this difference was attributable to dominance alone. In frequency there was outbreeding depression also in the F2 generation, suggesting a break-up of favourable epistatic gene combinations. The outbreeding depression in this character in the F1 generation was caused by dominance, and in the F2 also by duplicate epistasis between dominant decreasers. The possible role of outbreeding depression and epistasis in speciation is discussed.
Sanitary and phytosanitary standards as bridge to cross

This research assesses the effects of sanitary and phytosanitary (SPS) standards in international trade by introducing a new concept, bridge to cross (BTC), with product standards. The BTC in this paper is the regulatory gap between the exporting and importing countries with regard to any particular SPS measure. Assuming that each country's standard is binding in its own domestic markets, the standard of the importing country emerges as an effective trade barrier only when it exceeds the standard in the domestic market of the exporting country. Given the need to account for unobserved heterogeneity (multilateral resistance) in empirical trade models, if SPS regulations do not vary significantly over time, the effect of the regulation cannot be identified. However, the effect of BTC can still be identified because it varies by the pair of countries involved in the trade. As an application we apply the method to an SPS regulation relating to aflatoxin contamination in maize. In our empirical analysis we find that the effect of BTC varies by the size of the exporter and that the effect is stronger for poorer countries.
A Multiscale Metric for 3D Mesh Visual Quality Assessment

Many processing operations are nowadays applied on 3D meshes like compression, watermarking, remeshing and so forth; these processes are mostly driven and/or evaluated using simple distortion measures like the Hausdorff distance and the root mean square error, however these measures do not correlate with the human visual perception while the visual quality of the processed meshes is a crucial issue. In that context we introduce a full‐reference 3D mesh quality metric; this metric can compare two meshes with arbitrary connectivity or sampling density and produces a score that predicts the distortion visibility between them; a visual distortion map is also created. Our metric outperforms its counterparts from the state of the art, in term of correlation with mean opinion scores coming from subjective experiments on three existing databases. Additionally, we present an application of this new metric to the improvement of rate‐distortion evaluation of recent progressive compression algorithms.
Legged gaits planning for a novel ePaddle-based amphibious robot

In this paper, we present legged walking gaits for an amphibious reconfigurable robot based on a novel eccentric paddle mechanism (ePaddle). The ePaddle mechanism is a novel mechanism that is versatility in locomotion gaits. Five principal kinds of gaits can be achieved, including wheel-like rolling, legged walking, wheel-leg-integrated rolling, and two aquatic paddling gaits. We focus on two types of legged gaits among those possible gaits in this paper. The first one is adopted from a crawl gait that was designed originally for an open-link-based quadrupedal robot. The second legged gait that we introduce is a novel gait which has a duty factor up to 1.0 and keeps a larger static stability margin. The detailed motion planning methods are introduced and verified by simulations and experiments.
Biculturalism among Indigenous College Students

Biculturalism among Indigenous College Students Colton D. Miller Department of Counseling Psychology and Special Education, BYU Doctor of Philosophy Indigenous* college students in both Canada and the United States have the lowest rates of obtaining postsecondary degrees, and their postsecondary dropout rates are higher than for any other minority (Freeman & Fox, 2005; Mendelson, 2004; Reddy, 1993). There has been very little research done to uncover possible reasons for such low academic achievement and high dropout rates for Indigenous students. Some of the research that has been done indicates that one challenge for Indigenous students is the difficulty in navigating the cultural differences between higher education and their Indigenous cultures. Biculturalism is the ability of an individual to navigate two different cultures (Bell, 1990; Das & Kemp, 1997). Several scholars have suggested that biculturalism is an important construct in understanding academic persistence among Indigenous students (Jackson, Smith & Hill, 2003; Schiller, 1987). This study explored biculturalism among Indigenous college students and how it impacts their higher education experience. Indigenous college students (n=26) from the southwestern United States and central Canada participated in qualitative interviews for the study. The interviews were transcribed and interpreted using a synthesis of qualitative methods. Several themes related to the participants’ experience of biculturalism emerged from the qualitative analysis: institutional support for transition to college, racism, types of relationships to native culture, career issues, and family issues. The findings suggested that more needs to be done in terms of providing Indigenous students centers at universities, implementing mentor programs for incoming students, and educating future Indigenous college students, families, and communities about biculturalism and the culture of higher education. *Author’s note: The term Indigenous will be used to describe Native American/American Indian, First Nation and Metis student participants. Interviews were collected both in the United States and Canada. The terminology used to describe these populations differs across cultures; therefore, Indigenous will be used as a more general term, to describe the participants. The terminology used by cited authors was retained.
Application on self-provisioning of communication network service using fuzzy particle swarm optimization

In this paper, a self-provisioning of communication network service based on a fuzzy particle swarm optimization is proposed to minimize the configuration cost of four layer communication network. An swarm optimization called fuzzy particle swarm optimization (FPSO) is introduced. In this FPSO, the inertia weight of PSO is adaptively determined by a set of fuzzy rule. Also, a cross-mutated operation is presented to drive the solution to escape from local optima where the control parameter of this operation is also governed by a set of fuzzy rule. A performance comparison is given to show the performance of the proposed FPSO on the self-provisioning of communication network service and found that the performance of FPSO is significantly better than that of the existing hybrid PSO methods in a statistical sense.
A Method of Biomimetic Pattern Recognition for Speaker Recognition

A new method of speaker recognition based on Biomimetic Pattern Recognition and improved nearest neighbor method has been proposed. This new model based on "matter cognition" instead of "matter classification" in traditional statistical Pattern Recognition, which is closer to the function of human being. We experiment with the BPR by using improved nearest neighbor, which act through covering the high dimensional geometrical distribution of the sample class in the feature space. It is exciting that the recognition rate can achieve 100% in text-dependent test, and about 98.57% with 8.75% rejection rate and 1.43% error rate in text-independent test which shows that this method is efficient and practical.
A Novel Class-Based Data Fusion Technique for Information Retrieval

Data fusion in information retrieval combines the results from multiple retrieval models or document representations. The achievement of data fusion technique is dependent on the quality of the inputs; classical data fusion techniques fail to improve the retrieval if the quality of the retrieval results varies from low to high quality. In order to tackle this problem, in this paper we address the issue of high variation among the retrieval strategies or document representations which affect the combination of their outputs. Our investigation on the MALACH speech collection – in which different segment representations are available – shows that neither the classical data fusion (CombSUM) nor the weighted version (WCombSum) improve the retrieval. We propose a novel class-based data fusion technique to deal with this issue. The segments retrieved by models based on different document representations are classified according to the quality of the segment into three classes: high, intermediate, and low quality class; then the similarity scores of each segment are fused using the classical CombSUM. Our experimental results show that the new technique is significantly better than CombSUM or WCombSUM in combing results with high quality variation.
Gait recognition using Linear Discriminant Analysis with artificial walking conditions

In this paper, we present a novel method for the simulation of walking conditions and the generation of artificial subjects that are used for the application of Linear Discriminant Analysis. The proposed method works efficiently in situations where only one gallery sequence with one gait cycle is available for each subject in the database. The proposed method was experimentally assessed in combination with the Gait Energy Image (GEI) and the Shifted Energy Image (SEI). Very considerable improvements on the recognition and verification results are achieved.
An Empirical Analysis of Security Investment in Countermeasures Based on an Enterprise Survey in Japan

This paper presents a two-step empirical analysis of investing in security countermeasures based on an Japanese enterprise survey. At the first step, we verify the relations between probability of computer virus incidents and adopting a set of information security countermeasures. It is shown that “Defense Measure” associated with “Information Security Policy” and “Human Cultivation” has remarkable effects on virus incidents. At the second step, we analyze the effect of continuous investments in the three security countermeasures using two years’ data. The empirical results suggest that virus incidents were significantly reduced in those enterprises which adopted the three countermeasures both in 2002 and in 2003.
Evaluation of motion management strategies based on required margins

Strategies for delivering radiation to a moving lesion each require a margin to compensate for uncertainties in treatment. These motion margins have been determined here by separating the total uncertainty into components. Probability density functions for the individual sources of uncertainty were calculated for ten motion traces obtained from the literature. Motion margins required to compensate for the center of mass motion of the clinical treatment volume were found by convolving the individual sources of uncertainty. For measurements of position at a frequency of 33 Hz, system latency was the dominant source of positional uncertainty. Averaged over the ten motion traces, the motion margin for tracking with a latency of 200 ms was 4.6 mm. Gating with a duty cycle of 33% required a mean motion margin of 3.2–3.4 mm, and tracking with a latency of 100 ms required a motion margin of 3.1 mm. Feasible reductions in the effects of the sources of uncertainty, for example by using a simple prediction algorithm to anticipate the lesion position at the end of the latency period, resulted in a mean motion margin of 1.7 mm for tracking with a latency of 100 ms, 2.4 mm for tracking with a latency of 200 ms, and 2.1–2.2 mm for the gating strategies with duty cycles of 33%. A crossover tracking latency of 150 ms was found, below which tracking strategies could take advantage of narrower motion margins than gating strategies. The methods described here provide a means to guide selection of a motion management strategy for a given patient.
The Relation between Star Formation Rate and Accretion Rate in LINERs

It has been argued that there is a linear correlation between star formation rate (SFR) and accretion rate for normal bright active galactic nuclei (AGNs). However, it is still unclear whether this correlation holds for LINERs, the accretion rates of which are relatively low compared to those of normal bright AGNs. Radiatively inefficient accretion flows (RIAFs) are believed to be present in these LINERs. In this work, we derive accretion rates for a sample of LINERs from their hard X‐ray luminosities, based on spectral calculations for RIAFs. We find that LINERs follow the same correlation between SFR and accretion rate defined by normal bright AGNs when reasonable parameters are adopted for RIAFs. This means that the gases feeding black hole and star formation in these low‐luminosity LINERs may follow the same pattern as those in normal bright AGNs, which is roughly consistent with recent numerical simulations on quasar evolution.
Completing a Graduate Degree: A Case of a Female Student.

This paper was written as an assignment for one of my courses while pursuing a graduate degree in the Department of Education Studies at the University of British Columbia (UBC), Canada. I have made an attempt to explore perceptions and experiences of a female graduate student on four different aspects of her family and academic life. The four aspects that emerged as the themes while analysing interview transcript are: personal and family life; gender differences; funding and scholarship; and the role of supervisor. The paper also present how the interview was conducted, how the data were generated and how analysis was done. At the end of the paper I have presented my reflections.