Miracle-dz/UniFAR-FTUs huggingface dataset:
Combining sketch and wavelet models for anomaly detection

Statistics-based anomaly detections have been studied and implemented widely due to their potential to discover unseen anomalies. Several data analyzing techniques such as Wavelet have been successfully applied to this field of research. Wavelet analysis is one of the popular techniques that can be used to extract unusual patterns hidden within time-series data. When combined with the powerful data summarization technique like sketch, it could be able to detection significant changes in network data without any prior knowledge about the targeted traffic. In this paper, we study the anomaly detection approach based on the combination of random projection (sketch) and wavelet analysis. We apply our proposed algorithm to the traffic traces collected on the trans-Pacific transit backbone link (MAWI dataset), and compare it with other algorithms [1] [2], and the port heuristic methodology. The experimental results show that our algorithm can detect and identify a large number of anomalous traffic that are, for example, associated with some malware activities. Moreover, our proposed algorithm is also capable of detecting low-intensity anomalies as well as some types of malicious traffic that cannot be identified by the traditional wavelet analysis.
Gender Gaps in Undergraduate Fields of Study: Do College Characteristics Matter?

Despite gender parity in earned bachelor’s degrees, large gender gaps persist across fields of study. The dominant explanatory framework in this area of research assesses how gender differences in individual-level attributes predict gaps in major choice. The authors argue that individualistic accounts cannot provide a complete explanation because they fail to consider the powerful effects of the gendered institutional environments that inform and shape young men’s and women’s choices. The authors propose a cultural-organizational approach that considers how institutional characteristics and cultural contexts on college campuses may influence gendered choices and thus be associated with patterns of gender segregation across fields of study. The results of an analysis of institutional data on all U.S. degree-granting colleges and universities reveal substantial interinstitutional variation in gender segregation. Furthermore, structural and contextual institutional features related to peer culture, curricular focus, institutional commitment to gender equity, and the gender proportionality of the student body correlate with heightened or diminished levels of segregation.
3D shape isometric correspondence by spectral assignment

Finding correspondences between two 3D shapes is common both in computer vision and computer graphics. In this paper, we propose a general framework that shows how to build correspondences by utilizing the isometric property. We show that the problem of finding such correspondences can be reduced to the problem of spectral assignment, which can be solved by finding the principal eigenvector of the pairwise correspondence matrix. The proposed framework consists of four main steps. First, it obtains initial candidate pairs by performing a preliminary matching using local shape features. Second, it constructs a pairwise correspondence matrix using geodesic distance and these initial pairs. Next, the principal eigenvector of the matrix is computed. Finally, the final correspondence is obtained from the maximal elements of the principal eigenvector. In our experiments, we show that the proposed method is robust under a variety of poses. Furthermore, our results show a great improvement over the best related method in the literature.
Cerebral White Matter Integrity Mediates Adult Age Differences in Cognitive Performance

Previous research has established that age-related decline occurs in measures of cerebral white matter integrity, but the role of this decline in age-related cognitive changes is not clear. To conclude that white matter integrity has a mediating (causal) contribution, it is necessary to demonstrate that statistical control of the white matter–cognition relation reduces the magnitude of age–cognition relation. In this research, we tested the mediating role of white matter integrity, in the context of a task-switching paradigm involving word categorization. Participants were 20 healthy, community-dwelling older adults (60–85 years), and 20 younger adults (18–27 years). From diffusion tensor imaging tractography, we obtained fractional anisotropy (FA) as an index of white matter integrity in the genu and splenium of the corpus callosum and the superior longitudinal fasciculus (SLF). Mean FA values exhibited age-related decline consistent with a decrease in white matter integrity. From a model of reaction time distributions, we obtained independent estimates of the decisional and nondecisional (perceptual–motor) components of task performance. Age-related decline was evident in both components. Critically, age differences in task performance were mediated by FA in two regions: the central portion of the genu, and splenium–parietal fibers in the right hemisphere. This relation held only for the decisional component and was not evident in the nondecisional component. This result is the first demonstration that the integrity of specific white matter tracts is a mediator of age-related changes in cognitive performance.
The High Demand for Internet

bandwidth has led to increasingly higherspeed links and caused an associated demand for routers with a high aggregate switching capacity. At the highest speeds, input-queued (IQ) switches have become the architecture of choice, mainly because the memory bandwidth of their packet buffers is very low compared to that of output-queued and shared-memory architectures. To perform well, however, an N × N IQ switch requires a good packet scheduling algorithm to determine which inputs to connect with which outputs in each time slot. The maximum-weight matching (MWM) algorithm finds, from among N ! possible matchings, the matching with the highest weight. Here, the weight of the edge connecting input i to output j can either be the number of packets queued at input i for output j or the age of the oldest packet at input i for output j. The MWM algorithm is known to provide a 100 percent throughput as long as no input or output is over subscribed. It achieves a low average delay by keeping queue lengths short. However, MWM is complex to implement: It needs O(N ) iterations in the worst case and does not lend itself to an easy pipelined implementation. These implementation obstacles have motivated the proposal of several scheduling algorithms for high-speed switches, such as iterative SLIP (iSLIP), iterative longest-queue first (iLQF), reservation with preemption and acknowledgment (RPA), and matrix unit cell scheduler (MUCS). However, these algorithms perform poorly compared to MWM when the input traffic is nonuniform: They induce large delays, and their throughput can be less than 100 percent. Thus, although the other algorithms mentioned aim to solve implementation problems, their performance is poor. This situation raises the question, is it possible for an algorithm to compete with MWM’s performance and yet be simple to implement? If yes, what feature of the problem remains to be exploited? The answer lies in recognizing two features of the high-speed switch-scheduling problem:
Sunni Suicide Attacks and Sectarian Violence

ABSTRACT Although fundamentalist Sunni Muslims have committed more than 85% of all suicide attacks, empirical research has yet to examine how internal sectarian conflicts in the Islamic world have fueled the most dangerous form of political violence. We contend that fundamentalist Sunni Muslims employ suicide attacks as a political tool in sectarian violence and this targeting dynamic marks a central facet of the phenomenon today. We conduct a large-n analysis, evaluating an original dataset of 6,224 suicide attacks during the period of 1980 through 2016. A series of logistic regression analyses at the incidence level shows that, ceteris paribus, sectarian violence between Sunni Muslims and non-Sunni Muslims emerges as a substantive, significant, and positive predictor of suicide attacks. Indeed, the context of sectarian conflict predicts the use of suicide attacks to a much greater degree than the contexts of militant outbidding or foreign occupation. We also present five case examples, illustrating the use of suicide attacks in sectarian conflicts in Lebanon, Iraq, Syria, Nigeria, and Pakistan. Our overall results indicate that only a reduction in sectarian violence, and especially conflicts involving fundamentalist Sunni Muslims, can prevent the continuing spread of the suicide-attack phenomenon.
Gene transcription during exposure to, and recovery from, cold and desiccation stress in Drosophila melanogaster

We exposed adult male Drosophila melanogaster to cold, desiccation or starvation, and examined expression of several genes during exposure and recovery. Frost was expressed during recovery from cold, and was up‐regulated during desiccation. Desiccation and starvation (but not cold) elicited increased expression of the senescence‐related gene smp‐30. Desat2 decreased during recovery from desiccation, but not in response to starvation or cold. Hsp70 expression increased after 1 h of recovery from cold exposure, but was unchanged in response to desiccation or starvation stress, and Hsp23 levels did not respond to any of the stressors. We conclude that D. melanogaster's responses to cold and desiccation are quite different and that care must be taken to separate exposure and recovery when studying responses to environmental stress.
Using Conditional Phase Change Operations to Probe the Nature of Quantum Mechanical Systems

Recent developments in quantum computing suggest that it could be possible to make conditional changes to the state of a quantum mechanical system without resorting to classical observation. It is accomplished through collective response of atoms comprising a lattice for the system and involves relative phase adjustments only. We exploit this possibility and describe experimental designs that could help elucidate quantum mechanical properties of these systems and distinguish between interpretations.
Participation in Contentious Politics: Rethinking the Roles of News, Social Media, and Conversation Amid Divisiveness

ABSTRACT When political disputes devolve into heated partisan conflicts, do the factors known to trigger electoral political engagement continue to operate, or do they change? We consider this question during a divisive electoral context—a gubernatorial recall—focusing on how media consumption, conversations, and interactions with social media feed into the decision to participate in politics. To do so, we employ high-quality survey data collected in the weeks before the 2012 Wisconsin recall election. Results indicate that during times of contentious politics, political communication does not operate as observed in less polarized settings, calling into question widely held assumptions about what spurs and suppresses electoral participation. Most notably, we find that broadcast news consumption negatively predicts participation, whereas political conversation with coworkers and use of political social media positively predict participation. The implications for electoral behavior research in contentious political environments are discussed.
University Ofhawaìi at Mānoa Department of Economics Working Paper Series Why Are There so Few Women in Executive Positions? an Analysis of Gender Differences in the Life-cycle of Executive Employment

Why are there so few women in executive positions? An analysis of gender differences in the life-cycle of executive employment By Abstract " Glass ceilings " and " sticky floors " are typical explanations for the low representation of women in top executive positions, but a focus on gender differences in promotions provides only a partial explanation. We consider the life-cycle of executive employment, which allows for a full characterization of the gender composition of executive management. We establish that there are few women in executive management because they have lower levels of human capital, are underrepresented in lower-level jobs, and are less likely to be perceived as high-productivity employees. We do not find that women have uniformly unfavorable promotion and demotion probabilities.
Process: program for research on operator control in an experimental simulated setting

An experimental tool for the investigation of human control behavior of slowly responding dynamic systems is described. Process (Program for Research on Operator Control in an Experimental Simulated Setting) is a simulation of a dynamic water-alcohol distillation system that is especially useful in research on operator training. In particular, Process was developed to conduct research on fault management skills. >
Symbol timing recovery using oversampling techniques

It is advantageous to use oversampling techniques with either /spl Delta//spl Sigma/ or broadband data converters in both wireline and wireless digital receivers. This paper discusses the oversampling techniques for all-digital implementation of symbol timing recovery in digital receivers. The idea of oversampling techniques for timing recovery is to adjust the timing phases while decimating the oversampled signals. The spurious signal introduced by adjusting the CIC's (cascaded integrator-comb) timing phase has been analyzed and was found to be a serious problem. In this paper, a dual-differentiator timing phase adjustable decimation filter has been proposed and was used for symbol timing recovery. Simulations were provided to verify the validity of the proposed method.
On recognition of non-native speech using probabilistic lexical model

Despite various advances in automatic speech recognition (ASR) technology, recognition of speech uttered by non-native speakers is still a challenging problem. In this paper, we investigate the role of different factors such as type of lexical model and choice of acoustic units in recognition of speech uttered by non-native speakers. More precisely, we investigate the influence of the probabilistic lexical model in the framework of Kullback-Leibler divergence based hidden Markov model (KL-HMM) approach in handling pronunciation variabilities by comparing it against hybrid HMM/artificial neural network (ANN) approach where the lexical model is deterministic. Moreover, we study the effect of acoustic units (being context-independent or clustered context-dependent phones) on ASR performance in both KL-HMM and hybrid HMM/ANN frameworks. Our experimental studies on French part of MediaParl as a bilingual corpus indicate that the probabilistic lexical modeling approach in the KL-HMM framework can capture the pronunciation variations present in non-native speech effectively. More precisely, the experimental results show that the KL-HMM system using context-dependent acoustic units and trained solely on native speech data can lead to better ASR performance than adaptation techniques such as maximum likelihood linear regression.
FEED-FORWARD AND SELF-ORGANIZING NEURAL NETWORKS FOR TEXT DOCUMENT RETRIEVAL

The aim of this paper is to survey the feed-forward and self-organizing neural networks for the text document retrieval models, which retrieve text documents in a natural language. These models come from linguistic and conceptual approach of the text document analysis, where problems of document representation and document database creation are being solved. The proposed structure of the feed-forward and self-organizing neural network models solve the problem of the document retrieval by a user’s query which is transformed into the set of keywords. However, learning algorithm and neural network invariance, which comes from utilization of the chosen neural networks, enable the decrease of computational complexity for the language analysis of text document retrieval process.
Accelerating the compaction of test sequences in sequential circuits through problem size reduction

The problem of compacting a set of test sequences for sequential circuits is modeled here with the help of a covering matrix, where the test sequences are modeled as columns with variable cost to reflect the cost (number of vectors) of covering selected subsets of circuit faults. From this formulation, reduction rules are extracted, particular to this type of problem which, iteratively applied, result in a significant reduction of the size of the initial compaction problem. A characteristic of the reduction rules is that their application will not compromise the optimum solution of the problem. The remaining reduced problem is then solved by a combination of a heuristic and an exact branch and bound algorithm. Experimental results using the above reduction rules show that the sizes of the given sets of test sequences are often significantly reduced and many times these rules directly produce the absolute minimum of the solution. The final results, compared with others from the literature and also with the absolute minima of the examples, computed separately, support the potential of the proposed approach.
Varicocele and male infertility: Part II: Pathophysiology of varicoceles in male infertility

Varicoceles are found in 19 to 41% of infertile men, and is one treatable form of male infertility. The mechanism by which varicoceles cause the variable effect on male infertility and spermatogenesis is still unknown. Experimental animal models play a useful (but limited) role due to the sudden and variable iatrogenic nature of the varicoceles and the duration of the studies. Much of the human data are derived by the characterization of associated differences in measurable parameters between men with and without varicoceles. The role of hyperthermia, testicular blood flow and venous pressure changes, reflux of renal/adrenal products, hormonal dysfunction, autoimmunity, defects in acrosome reaction, and oxidative stress, in the pathophysiology of varicocele will be discussed.
Interplanetary Networks: Architectural Analysis, Technical Challenges and Solutions Overview

Future space exploration missions will need a robust, efficient and flexible communication infrastructure. This implies new communications and networking challenges, which are the ones of the so called InterPlaNetary (IPN) Internet. In that framework, the paper provides a description of the challenging scenario, surveys its technical problems and envisages possible advanced communications and networking solutions starting from the analysis of a specific IPN architecture, which represents the main contribution of the work.
Automatic vs. Explicit Memory Management: Settling the Performance Debate

While garbage collection’s software engineering benefits are indisputable, its performance impact remains controversial. Garbage collection proponents argue that its benefits outweigh its costs, but it is widely believed that garbage collection imposes an unacceptably high runtime and space performance penalty. This paper aims to settle this debate. We present the first empirical comparison of the performance costs of automatic versus explicit memory management in a garbage-collected language. Using a tracing and simulation based oracular memory manager, we execute unaltered Java programs as if they used explicit memory management. We examine the runtime, space consumption and virtual memory footprint of Java benchmarks across a range of general-purpose allocators and both copying and non-copying garbage collectors. We show that, at large heap sizes and under no memory pressure, the runtime performance of some garbage collection algorithms is competitive with the Lea memory allocator and occasionally outperforms it by up to 4%. However, our results confirm that garbage collection requires six times the physical memory to achieve this performance and suffers order-of-magnitude performance penalties when paging occurs.
Advances and challenges of probabilistic model checking

Probabilistic model checking is a powerful technique for formally verifying quantitative properties of systems that exhibit stochastic behaviour. Such systems are found in many domains: probabilistic behaviour may arise, for example, due to failures of unreliable components, communication across lossy media, or through the use of randomisation in distributed protocols. In this paper, we give a short overview of probabilistic model checking and of PRISM (www.prismmodelchecker.org), currently the leading software tool in this area. We then mention some of the limitations of these techniques, describe some of the advances that are being made to overcome them, and outline key challenges that remain in this research area.
General Education: The Front Lines of Equity and Inclusion at a Midsize Public University

ABSTRACT:Unequal academic outcomes in postsecondary education persist for students from underserved populations (students of color, low socioeconomic status, first-generation), despite increased access to higher education in the last half century. General education classes present prime opportunities to address academic inequity. They typically have larger enrollments than major studies courses, are taken by more first-year students, and often serve as gateway courses for admission into numerous academic programs. Identifying pockets of underachievement—equity gaps—among discrete populations is a critical first step in ensuring that institutions support and meet the needs of all students. Equity-mindedness, which views student success as a shared responsibility between the student and the institution, is a second vital component for achieving academic equity. This article discusses two large initiatives undertaken at a midsized public university that are designed to achieve academic equity for all students: the identification and elimination of academic equity gaps among students from underserved populations, especially in general education courses, and the development of an equity-minded campus culture that embraces diversity and serves all students equally.
Classification of TerraSAR-X Imagery for the Characterization of Amazon Tropical Forests

The objective of this study is to analyze the potential of TERRA SAR-X dual images, on the StripMap mode, for classification of forest cover and of land use classes resulting from human activities. The area under study is located in the portions of SW Brazilian Amazon region, Acre State. The StripMap images of TerraSAR-X, dual polarization, were processed in accordance with the following methodological steps: (a) generation of the covariance matrix; (b) application of the Enhanced Lee filter to reduce the speckle noise; (c) targets decomposition technique based on the Cloude and Pottier theorem; (d) thematic classification by algorithm MLC + ICM (Maximum Likelihood Classifier + Iterated Conditional Modes); (e) assessment of classification accuracy by Kappa statistics. This approach has shown the potential of TerraSAR-X images for the discrimination of primary forest, degraded forest, pastures and agricultural areas/bare soil. The best classification was derived from the combination of the image resulting from the amplitude components of the covariance matrix and the entropy image generated from the target decomposition theorem. The overall classification accuracy was 76% and the Kappa value of 0.67, whose analysis were supported by field survey realized simultaneously to the acquisition of the radar images. The state of art of the forest conditions analyzed by X-band radar imagery will be an important tool, together with other frequencies/SAR systems, to subsidize both the inventory and monitoring processes of land use/land cover in Brazilian Amazon.