Miracle-dz/UniFAR-FTUs huggingface dataset:
Smoking Out the Heavy-Hitter Flows with HashPipe

Identifying the “heavy hitter” flows or flows with large traffic volumes in the dataplane is important for several applications e.g., flow-size aware routing, DoS detection and traffic engineering. However, measurement in the data plane is constrained by the need for line-rate processing (at 10-100Gb/s) and limited memory in switching hardware. We propose HashPipe, a heavy hitter detection algorithm using emerging programmable data planes. HashPipe implements a pipeline of hash tables which retain counters for heavy flows in various stages while evicting lighter flows over time. We prototype HashPipe in P4 and evaluate it with CAIDA packet traces from an ISP backbone link. We find that HashPipe identifies 95% of the 300 heaviest flows with less than 80KB of memory on a trace that contains 500,000 flows.
Bulge–disc decompositions and structural bimodality of Ursa Major cluster spiral galaxies

We present bulge and disc (B/D) decompositions of existing K' surface brightness profiles for 65 Ursa Major (UMa) cluster spiral galaxies. This improves upon the disc-only fits of Tully et al. The 1996 disc fits were used by Tully & Verheijen for their discovery of the bimodality of structural parameters in the UMa cluster galaxies. It is shown that our new one-dimensional B/D decompositions yield disc structural parameters that differ only slightly from the basic fits of Tully et al. and evidence for structural bimodality of UMa galaxies is maintained. Our B/D software for the decomposition of one-dimensional surface brightness profiles of galaxies uses a non-linear minimization scheme to recover the best-fitting Sersic bulge and the exponential disc while accounting for the possible presence of a compact nucleus and spiral arms and for the effects of seeing and disc truncations. In agreement with Tully & Verheijen, we find that the distribution of near-infrared disc central surface brightnesses is bimodal with an F-test confidence of 80 per cent. There is also strong evidence for a local minimum in the luminosity function at M K' ≃ -22. A connection between the brightness bimodality and a dynamical bimodality, based on new H i linewidths, is identified. The B/D parameters are presented in Table 1.
Fluid-structure traveling wave filters based on the mammalian cochlea

Micromachined fluid-structure systems capable of acoustic sensing and mechanical frequency analysis are demonstrated. These systems act as passive mechanical acoustic filters. A capacitive sensing scheme is incorporated into the structure to produce 32 channels of filtered output, each sensitive to a particular frequency band. Inspiration for the design is taken from the structure of the mammalian cochlea.
New content-based features for the distinction of violent videos and martial arts

Real violence is unwanted content in video portals as it is forensically relevant in video surveillance systems. Naturally, both domains have to deal with mass data which makes the detection of violence by hand an impossible task. We introduce one component of a system for automated violence detection from video content: the differentiation of real violence and martial arts videos. In particular, we introduce two new feature transformations for jitter detection and local interest point detection with Gestalt laws. Descriptions are classified in a two-step machine learning process. The experimental results are highly encouraging: the novel features perform exceptionally well and the classification process delivers practically acceptable recall and precision.
Stochastic Convenience Yield Implied from Commodity Futures and Interest Rates

We characterize a three-factor model of commodity spot prices, convenience yields, and interest rates, which nests many existing specifications. The model allows convenience yields to depend on spot prices and interest rates. It also allows for time-varying risk premia. Both may induce mean reversion in spot prices, albeit with very different economic implications. Empirical results show strong evidence for spot-price level dependence in convenience yields for crude oil and copper, which implies mean reversion in prices under the risk-neutral measure. Silver, gold, and copper exhibit time variation in risk premia that implies mean reversion of prices under the physical measure.
DEVELOPING AND TESTING THE CONSTRUCT VALIDITY INSTRUMENT OF TADZKIYATUN NAFS

This research aims to develop and test the construct validity of the tadzkiyatun nafs instrument at the Tarbiyah and Teacher Training Faculty of UIN Raden Intan Lampung. The Population of this research was the students of Tarbiyah and Teacher Training Faculty that consisted of 150 students. The method employed in this research was survey technique by using Likert Scale parameter. The result of the empirical research states that 37 items of the Tadzkiyatun Nafs instrument are spread out into five dimensions. The result of construct validity by using factor analysis proved that several numbers of items that have been estimated are 37 indicators with the value of > 0.30, out of 39 items, assuming that all items are estimated in accordance with the theory being constructed. The two other indicators are < 0.30 which then eliminated. The two items that were eliminated are item A4 on the Tauhid dimension, and point A11 on the shalat dimension. The implications of this research are expected can contribute to the progress of Islamic civilization, especially in relation to scientific integration by integrating Islamic sciences as its subject, and exact science as its methodology.
EFFECT OF CHARACTER AND TECHNICAL DIMENSIONS OF ETHICAL LEADERSHIP ON EMPLOYEE COMMITMENT IN THE TRANSPORT SECTOR PARASTATALS IN KENYA

Purpose: The purpose of this study was to determine the effect of the character and technical dimensions of ethical leadership on employee commitment among senior managers in the transport sector parastatals in Kenya. Methodology: The study adopted a descriptive correlational research design. The target population consisted of 253 senior managers in the transport sector parastatals. A sample of 153 senior managers was selected from the target population using the stratified random sampling technique. A self-administered questionnaire was used to collect data from senior managers. Data were analyzed using descriptive and inferential statistics. Results: Correlation analysis revealed a positive and significant relationship between the character dimension and employee commitment, r (111) = . 72, p < . 05, and also between the technical dimension and employee commitment, r (111) = . 56, p < . 05, Analysis of variance showed that employee commitment was significantly affected by the character dimension, F (1, 111) = 197.56, p < . 05 as well as the technical dimension, F (1, 111) = 55.23, p < . 05. Results of multiple linear regression indicated that 64% of the variance in employee commitment were caused by the character dimension, R 2 = . 64, F (1,111) = 197.56, p < . 05; β = . 78, p < . 05 while 33% of the variance in employee commitment were caused by the technical dimension, R 2 = . 33, F (1,111) = 55.23, p < . 05; β = . 65, p < . 05. Ethical climate was found to significantly moderate the relationship between the character and technical dimensions of ethical leadership and employee commitment, R 2 = . 67, F (7,105) = 30.56, p < . 05; β = . 24, p < . 05. Unique contribution to theory, practice and policy: Previous studies on ethical leadership have focused on the ethical characteristics of the leader and behavioral traits in the Western settings. This study has provided an in-depth examination of ethical leadership and its effect on employee commitment in the African context. In addition, the application of ethical climate as a moderating variable in this study presented the opportunity to further test its moderating effect on the relationship between the character and technical dimensions of ethical leadership and employee commitment in public organizational settings.
Temporal and harmonic combination-sensitive neurons in the zebra finch's HVc

Song learning shapes the response properties of auditory neurons in the song system to become highly selective for the individual bird's own (“autogenous”) song. The auditory representation of autogenous song is achieved in part by neurons that exhibit facilitated responses to combinations of components of song. To understand the circuits that underlie these complex properties, the combination sensitivity of single units in the hyperstriatum ventrale, pars caudale (HVc) of urethane-anesthetized zebra finches was studied. Some neurons exhibited nonlinear temporal summation, spectral summation, or both. The majority of these neurons exhibited low spontaneous rates and phasic responses. Most combination-sensitive neurons required highly accurate copies of sounds derived from the autogenous song and responded weakly to tone bursts, combinations of simple stimuli, or conspecific songs. Temporal combination-sensitive (TCS) neurons required either two or more segments of a single syllable, or two or more syllables of the autogenous song, to elicit a facilitated, excitatory response. TCS neurons integrated auditory input over periods ranging from 80 to 350 msec, although this represents a lower limit. Harmonic combination- sensitive (HCS) neurons required combinations of two harmonics with particular frequency and temporal characteristics that were similar to autogenous song syllables. Both TCS and HCS neurons responded much more weakly when the dynamical spectral features of the autogenous song or syllables were modified than when the dynamical amplitude (waveform) features of the songs were modified. These results suggest that understanding the temporal dynamics of auditory responses in HVc may provide insight into neuronal circuits modified by song learning.
Nasty, Brutish, and Short: Embeddedness Failure in the Pharmaceutical Industry

Since the early 1990s, U.S. pharmaceutical firms have partially outsourced the coordination of the clinical trials they sponsor to specialized firms called contract research organizations. Although these exchanges appeared ripe for the development of close, “embedded” ties, they were in fact “nasty, brutish, and short” — i.e., marked by ill-will and a bias toward replacing current exchange partners due to perceptions of underperformance. Drawing on in-depth field work, we use causal loop diagrams to capture this puzzle and to help explain it. Our analysis suggests that attempts to build embedded relations will fail if the parties do not recognize the limitations of the commitments they can credibly make. More generally, when managers misdiagnose as failure what is in fact a trade-off inherent in the design of their organizations, they risk engendering even worse outcomes than those they would otherwise attain.
A case study of task-based reorganization in a pursuit game simulation

Important to the effective performance of a multi-agent system, is using the appropriate organizational structure. Different organizations might be appropriate for different tasks, goals, and environmental conditions. As a result, sometimes a higher performance can be achieved by reorganizing to a more promising structure. One of the problems in reorganization is defining the criteria upon which to evaluate and find a promising organization to reorganize to. Considering the costs that can be associated to reorganization, most of the research to-date has been focused on reorganizing when system performance falls below a certain threshold. While some opportunities for reorganization might be lost. In this work, we perform a simulation study to identify effects of a task-based model of reorganization. The results demonstrate performance enhancements using our approach despite the costs associated
Comparison of Some Automatic and Manual Methods for Summary Evaluation Based on the Text Summarization Challenge 2

In this paper, we compare some automatic and manual methods for summary evaluation. One of the essential points for evaluating a summary is how well the evaluation measure recognizes slight differences in the quality of the computer-produced summaries. In terms of this point, we examined ‘evaluation by revision’ using the data of the Text Summarization Challenge 2 (TSC2). Evaluation by revision is a manual method that was first used in TSC2, whose effectiveness has not been tested. First, we compared evaluation by revision with a ranking evaluation, which is a manual method used both in TSC1 and in TSC2, by checking the gaps of the edit distance from 0 to 1 at 0.1 intervals. To investigate the effectiveness of evaluation by revision, we also tested other automatic methods: content-based evaluation, BLEU and RED, and compare their results with that of evaluation by revision for reference. As a result, we found that evaluation by revision is effective for recognizing slight differences between computer-produced summaries. Second, we evaluated content-based evaluation, BLEU and RED by evaluation by revision, and compared the effectiveness of the three automatic methods. We found that RED is superior to the others in some examinations.
Convolutional Neural Networks for Document Image Classification

This paper presents a Convolutional Neural Network (CNN) for document image classification. In particular, document image classes are defined by the structural similarity. Previous approaches rely on hand-crafted features for capturing structural information. In contrast, we propose to learn features from raw image pixels using CNN. The use of CNN is motivated by the the hierarchical nature of document layout. Equipped with rectified linear units and trained with dropout, our CNN performs well even when document layouts present large inner-class variations. Experiments on public challenging datasets demonstrate the effectiveness of the proposed approach.
Marginal Willingness To Pay for Education and the Determinants of Enrollment in Mexico. Policy Research Working Papers.

Standard benefit-incidence analysis assumes that the subsidy, and quality of education services are the same for all income deciles. This strong assumption tends to minimize the distributional inequity at various education levels. Using a new approach, emphasizing marginal willingness to pay for education, the authors analyze the impact of public spending on the education spending behavior of the average household. They address several questions: What would an average household, with a given set of characteristics be willing to spend on an individual child, with given traits if subsidized public education facilities were unavailable? What would the household have saved by sending the child to public school rather than private school? How great are these savings for various income groups? What are the determinants of enrollment by income group, and by location? How do individuals'education expenditures affect enrollment patterns? Among their findings: 1) The non-poor households in urban areas get much of the subsidy, or"savings"from government provision of education services. 2) The wealthy value private education more than the poor do. 3) Differences in school quality are greater at the primary level. In other words, wealthy households get the lion's share of benefits from public spending on education. Household school enrollment, and transition to the next level of schooling, depend heavily on the cost of schooling, how far the head of the household went in school, the per capita household income, and the housing facilities, or services. But the government's effort also affects the probability of enrollment, and transition. The probability of enrollment is much higher for the 40 percent of higher-income households in urban areas, than it is for the 40 percent of lower-income households in rural areas. The best way to increase school enrollment is to successfully target public spending on education to poor households.
PacketCloud: an open platform for elastic in-network services

The Internet was designed with the end-to-end principle where the network layer provided merely the best-effort forwarding service. This design makes it challenging to add new services to the network layer. However, as the Internet connectivity becomes a commodity, users and applications increasingly demand new in-network services. This paper proposes PacketCloud, a cloudlet-based open platform to host elastic in-network services. PacketCloud can help both Internet Service Providers (ISPs) and emerging application/content providers deploy their services to strategic network locations. We have implemented a proof-of-concept prototype of PacketCloud based on the MobilityFirst architecture. PacketCloud introduces a small additional delay, and can scale well to handle high-throughput data traffic.
Evaluation of data passing and scheduling avoidance

Multimedia applications often transfer data between devices or output the same data to multiple devices at very high rates, and therefore require an efficient I/O subsystem. Data copying and context switching have long been identified as sources of I/O inefficiency, and consequently there have been many proposals of: (1) copy avoidance techniques, which pass data between application and system buffers without copying; (2) data passing avoidance techniques, which allow applications to perform multiple I/O operations on system buffers, without passing data to or from application buffers; and (3) scheduling avoidance techniques, which allow multiple I/O operations on system buffers to proceed at interrupt level, without scheduling. Adoption of such optimizations remains limited because most require major changes in the API or structure of existing operating systems. The authors recently proposed, however, new copy avoidance techniques, emulated copy and emulated share, which, unlike previous work, require no such changes. In their experiments, copy avoidance optimizations gave performance improvements almost as good as or better than those of data passing avoidance, and scheduling avoidance provided only modest performance improvements over priority scheduling. Their results suggest that the I/O performance of conventional operating systems can be greatly improved without the major changes in API or organization commonly advocated.
Domain Adaptation in the Context of Sport Video Action Recognition

We apply domain adaptation to the problem of recognizing common actions between differing court-game sport videos (in particular tennis and badminton games). Actions are characterized in terms of HOG3D features extracted at the bounding box of each detected player, and thus have large intrinsic dimensionality. The techniques evaluated here for domain adaptation are based on estimating linear transformations to adapt the source domain features in order to maximize the similarity between posterior PDFs for each class in the source domain and the expected posterior PDF for each class in the target domain. As such, the problem scales linearly with feature dimensionality, making the video-environment domain adaptation problem tractable on reasonable time scales and resilient to over-fitting. We thus demonstrate that significant performance improvement can be achieved by applying domain adaptation in this context.
STUDENT-CENTERED LEARNING IN RELATION TO CLASS PERFORMANCES AND SOFT SKILLS: A META-ANALYSIS AND SYSTEMATIC REVIEW

Background: Studies showed that SCL improved quality of medical education through knowledge acquisition, class performance, students’ attitude and soft skills. Although research about SCL and its impact has been widely known, overall correlation of SCL to the class performances has not yet been established. Strong correlation between SCL to class performances would serve the purpose of teaching and learning and more importantly would answer the skepticism of institution or faculty members in implementing SCL. In addition, learning through systematic review of others’ studies, how SCL influenced soft skill aspects would be benefited for medical educators. Soft skills such as learning motivation, communication skills, and teamwork may lead educators to the favor of SCL approaches. This review was to find the correlation of student-centered learning to the students’ performances and soft skill aspects in medical education.Method: To find the correlation of the SCL and class performances, we used meta-analysis. We also performed a systematic review to qualitatively find the relationship between SCL and other aspects, such as teamwork, communication skills, and learning motivation. Literatures were filtered from databases of: Proquest, Springerlink, Biomed Central (BMC) open, BMJ open, and Google Scholar. The inclusion criteria were published empirical articles (2000-2013) reported SCL’s effect on class performances or other aspects (learning motivation, teamwork, communication skills). We utilized PRISMA protocol to filter the inclusion articles. By reading abstracts and further snowballing searching, we found 12 articles for the meta-analysis and 33 articles for the systematic review. Results: Among 12 articles of the meta-analysis, 9 articles showed positive correlation between SCL and class performances. Three studies reported that SCL had no effect on the class performances. None of the articles reported any negative impact. We utilized the Comprehensive Meta-Analysis software to analyze the data and found r = 0.46 and 95% CI: 0.32 - 0.57. It showed a statistically significant correlation between SCL and class performances. On the systematic review, we found that SCL improved communication skills, team work, and learning motivation.Conclusion: From the meta-analysis we found that SCL improved class performances about 46%. It was showed that SCL methods were superior in improving soft skills such as communication skills, teamwork, and learning motivation.
Integrated Configuration of Enterprise Systems for Interoperability -- Towards Process Model and Business Document Specification Alignment

Enterprise systems (ES) can be understood as the de facto standard for holistic operational and managerial support within an organization. Most commonly ES are offered as commercial off-the-shelf packages, requiring customization in the user organization. This process is a complex and resource-intensive task, which often prevents small and midsize enterprises (SME) from undertaking configuration projects. Especially in the SME market independent software vendors provide pre-configured ES for a small customer base. The problem of ES configuration is shifted from the customer to the vendor, but remains critical. We argue that the yet unexplored link between process configuration and business document configuration must be closer examined as both types of configuration are closely tied to one another
VM-based Architecture for Network Monitoring and Analysis

A single physical machine provides multiple network monitoring and analysis services (e.g., IDS, QoS) which are installed on the same operating system. Isolation between services is weak and it is difficult to decide the optimum allocation of resources for each service. This paper presents a virtual-machine-based architecture for network traffic monitoring and analysis. Through virtualization, a machine under the architecture logically is divided into one host, one virtual machine monitor (VMM) and multiple virtual machines. The host is responsible for capturing network traffic, and multiplexing it to multiple virtual machines. Each virtual machine hosts a service. VMM performs functions such as isolating services and resolving the conflict between services. Compared with Xen, KVM is chosen as a VMM to implement the architecture. Some network optimizations of the architecture are given. Our evaluation results show that these optimizations can multiplex network traffic received by the host to all services, and improve the data receive performance of services by 67% compared to the architecture in which the traffic is directly transferred to virtual machines, instead of the host, and optimized methods are not adopted.