Miracle-dz/UniFAR-FTUs huggingface dataset:
Labelling clusters in an anomaly based IDS by means of clustering quality indexes

Intrusion detection systems have in the recent years become an important part of most defence-in-depth network perimeter security setups. These intrusion detection systems either apply misuse or anomaly based techniques to detect malicious activities. To detect malicious activity, misuse based systems search for signatures of previously known malicious activities. Anomaly based systems on the other side, flag behaviour that deviates from what is expected to be benign activities. Most intrusion detection systems are misuse based, but more and more systems now use a combination of both techniques, where anomaly based techniques are often used to assist the misuse based detection engines. One method for classifying observed activities in an anomaly based intrusion detection system is clustering. A major difficulty regarding clustering based systems is to interpret the nature of the obtained clusters and label them as normal or malicious. One labelling strategy is to apply clustering quality evaluation techniques to determine whether or not a massive attack is present in the observed activities. Then, a combination of these evaluation techniques and cluster parameters can be used to interpret the nature of the clusters. This thesis investigates the application of Dunn’s index and C-index in this labelling strategy. These clustering quality indexes are combined with clustering parameters to develop algorithms for proper labelling of observed activities. The original definition of the C-index requires similar cluster sizes for accurate clustering quality evaluations. As similar cluster sizes are rare in clustering based intrusion detection systems, we propose two modified C-indexes for use in situations with unequal cluster sizes. A prototype, simulating a clustering based intrusion detection system, has been developed to test and measure the performance of clustering quality indexes in this labelling strategy. The results from these simulations show that the application of both the Dunn’s index and the modified C-index in this labelling strategy produce accurate labelling of activity clusters. These results also demonstrate that this labelling strategy outperforms classical cardinality based labelling strategies in heavily attacked environments where massive attacks are frequent.
Connected Companies' Compensation

When portfolio managers trade the stocks of companies run by people with whom they have social connections, these trades earn better returns than trades in companies with whom they have no connections (Cohen et al., 2008). We look at the effects of social connections from the firm’s side, examining the compensation of firm executives. Executive compensation in connected firms is substantially higher than in unconnected firms. The channel through which this result occurs appears to be share voting—connected funds are more likely to vote against shareholder-initiated proposals on executive compensation, thereby protecting their cronies from the discipline of corporate governance. The evidence is consistent with higher compensation being the quid pro quo for information flow from firm to fund.
Comparison of Lower Genital Tract Microbiota in HIV-Infected and Uninfected Women from Rwanda and the US

Introduction Previous studies have shown that alterations of the bacterial microbiota in the lower female genital tract influence susceptibility to HIV infection and shedding. We assessed geographic differences in types of genital microbiota between HIV-infected and uninfected women from Rwanda and the United States. Methods Genera of lower genital tract bacterial microbiota were identified by high-throughput pyrosequencing of the 16S rRNA gene from 46 US women (36 HIV-infected, 10 HIV-uninfected) and 40 Rwandan women (18 HIV-infected, 22 HIV-uninfected) with similar proportions of low (0–3) Nugent scores. Species of Lactobacillus were identified by assembling sequences along with reference sequences into phylogenetic trees. Prevalence of genera and Lactobacillus species were compared using Fisher's exact tests. Results Overall the seven most prevalent genera were Lactobacillus (74%), Prevotella (56%), Gardnerella (55%), Atopobium (42%), Sneathia (37%), Megasphaera (30%), and Parvimonas (26%), observed at similar prevalences comparing Rwandan to US women, except for Megasphaera (20% vs. 39%, p = 0.06). Additionally, Rwandan women had higher frequencies of Mycoplasma (23% vs. 7%, p = 0.06) and Eggerthella (13% vs. 0%, p = 0.02), and lower frequencies of Lachnobacterium (8% vs. 35%, p<0.01) and Allisonella (5% vs. 30%, p<0.01), compared with US women. The prevalence of Mycoplasma was highest (p<0.05) in HIV-infected Rwandan women (39%), compared to HIV-infected US women (6%), HIV-uninfected Rwandan (9%) and US (10%) women. The most prevalent lactobacillus species in both Rwandan and US women was L. iners (58% vs. 76%, p = 0.11), followed by L. crispatus (28% vs. 30%, p = 0.82), L. jensenii (20% vs. 24%, p = 0.80), L. gasseri (20% vs. 11%, p = 0.37) and L. vaginalis (20% vs. 7%, p = 0.10). Discussion We found similar prevalence of most major bacterial genera and Lactobacillus species in Rwandan and US women. Further work will be needed to establish whether observed differences differentially impact lower genital tract health or susceptibility to genital infections.
Credit Risk Measurement on Customers of B2B Market

By selecting customers' credit risk indicators of the domestic textile industry on the electronic trading market in China and using factor analysis method, clustering method, and ordered-logit model, it can be concluded that the comprehensive evaluation of customers' credit status is measured scientifically in B2B market. Therefore, customers' credit risk management is made effectively in accordance with the rating results.
Creating a Culture of Patient Safety through Innovative Hospital Design

Abstract : When SynergyHealth, St. Joseph's Hospital of West Bend, Wisconsin, decided to relocate and build an 82-bed acute care facility, they recognized the opportunity to design a hospital that focused on patient safety. Hospital leaders believed that if a facility design process was "engineered properly," it would enhance patient safety and create a patient safe culture. Unfortunately, the planners found little information to give them direction. To help them plan the new facility, they conducted a national learning lab, drawing what they could about patient safety from available literature; inviting experts from the health care profession and other fields, including transportation, spacecraft design, and systems engineering; and involving hospital board members, staff, physicians, and the facility design team. In this case study, the author describes the process used by St. Joseph's to design a new hospital around patient safety. The author also discusses safety design principles, providing examples of their application at St. Joseph's new facility. Finally, recommendations are presented for the architectural design of all health care systems, including new facilities, remodeling efforts, and additions.
An Analysis of How Spatiotemporal Dynamic Models of Brain Activity Could Improve MEG/EEG Inverse Solutions

MEG and EEG are noninvasive functional neuroimaging techniques that provide recordings of brain activity with high temporal resolution, and thus provide a unique window to study fast time-scale neural dynamics in humans. However, the accuracy of brain activity estimates resulting from these data is limited mainly because 1) the number of sensors is much smaller than the number of sources, and 2) the low sensitivity of the recording device to deep or radially oriented sources. These factors limit the number of sources that can be recovered and bias estimates to superficial cortical areas, resulting in the need to include a priori information about the source activity. The question of how to specify this information and how it might lead to improved solutions remains a critical open problem. In this paper we show that the incorporation of knowledge about the brain's underlying connectivity and spatiotemporal dynamics could dramatically improve inverse solutions. To do this, we develop the concept of the \textit{dynamic lead field mapping}, which expresses how information about source activity at a given time is mapped not only to the immediate measurement, but to a time series of measurements. With this mapping we show that the number of source parameters that can be recovered could increase by up to a factor of ${\sim20}$, and that such improvement is primarily represented by deep cortical areas. Our result implies that future developments in MEG/EEG analysis that model spatialtemporal dynamics have the potential to dramatically increase source resolution.
Exploring interactions between rat hepatocytes and nonparenchymal cells using gene expression profiling

Cocultivation of primary hepatocytes with a plethora of nonparenchymal cells (from within and outside the liver) has been shown to support hepatic functions in vitro. Despite significant investigation into this phenomenon, the molecular mechanism underlying epithelial–nonparenchymal interactions in hepatocyte cocultures remains poorly understood. In this study, we present a functional genomic approach utilizing gene expression profiling to isolate molecular mediators potentially involved in induction of liver‐specific functions by nonparenchymal cells. Specifically, primary rat hepatocytes were cocultivated with closely related murine fibroblast cell types (3T3‐J2, NIH‐3T3, mouse embryonic fibroblasts) to allow their classification as “high,” “medium,” or “low” inducers of hepatic functions. These functional responses were correlated with fibroblast gene expression profiles obtained using Affymetrix GeneChips. Microarray data analysis provided us with 17 functionally characterized candidate genes in the cell communication category (cell surface, extracellular matrix, secreted factors) that may be involved in induction of hepatic functions. Further analysis using various databases (i.e., PubMed, GenBank) facilitated prioritization of the candidates for functional characterization. We experimentally validated the potential role of two candidates in our coculture model. The cell surface protein, neural cadherin (N‐cadherin), was localized to hepatocyte–fibroblast junctions, while adsorbed decorin up‐regulated hepatic functions in pure cultures as well as cocultures with low‐inducing fibroblasts. In the future, identifying mediators of hepatocyte differentiation may have implications for both fundamental hepatology and cell‐based therapies (e.g., bioartificial liver devices). In conclusion, the functional genomic approach presented in this study may be utilized to investigate mechanisms of cell–cell interaction in a variety of tissues and disease states. (HEPATOLOGY 2004;40:545–554.)
Comprehensive fault evaluation on maglev train based on ensemble learning algorithm

In order to realize comprehensive fault evaluation on faults occurred in maglev train, aim at the difficulty in establishing the evaluation weight matrix and subjection matrix parameter, faint comprehensive evaluation method based on ensemble learning algorithm is proposed. First, the structure of the suspension system of maglev train is analyzed and a fault diagnosis model is built. Then ensemble learning is introduced to the train model with learning ability. At last, this method is applied to fault evaluation on maglev train suspension system. In comparison to single and integration classification method, the emulational results prove that the ensemble method works better on the problem, the advantage of the Ensemble Learning algorithm is manifested, and practice has proved that this method is competent for precision demand.
Behavioral buffering of global warming in a cold‐adapted lizard

Abstract Alpine lizards living in restricted areas might be particularly sensitive to climate change. We studied thermal biology of Iberolacerta cyreni in high mountains of central Spain. Our results suggest that I. cyreni is a cold‐adapted thermal specialist and an effective thermoregulator. Among ectotherms, thermal specialists are more threatened by global warming than generalists. Alpine lizards have no chance to disperse to new suitable habitats. In addition, physiological plasticity is unlikely to keep pace with the expected rates of environmental warming. Thus, lizards might rely on their behavior in order to deal with ongoing climate warming. Plasticity of thermoregulatory behavior has been proposed to buffer the rise of environmental temperatures. Therefore, we studied the change in body and environmental temperatures, as well as their relationships, for I. cyreni between the 1980s and 2012. Air temperatures have increased more than 3.5°C and substrate temperatures have increased by 6°C in the habitat of I. cyreni over the last 25 years. However, body temperatures of lizards have increased less than 2°C in the same period, and the linear relationship between body and environmental temperatures remains similar. These results show that alpine lizards are buffering the potential impact of the increase in their environmental temperatures, most probably by means of their behavior. Body temperatures of I. cyreni are still cold enough to avoid any drop in fitness. Nonetheless, if warming continues, behavioral buffering might eventually become useless, as it would imply spending too much time in shelter, losing feeding, and mating opportunities. Eventually, if body temperature exceeds the thermal optimum in the near future, fitness would decrease abruptly.
Simultaneous redundant via insertion and line end extension for yield optimization

In this paper, we formulate a problem of simultaneous redundant via insertion and line end extension for via yield optimization. Our problem is more general than previous works in the sense that more than one type of line end extension is considered and the objective function to be optimized directly accounts for via yield. We present a zero-one integer linear program based approach, that is equipped with two speedup techniques, to solve the addressed problem optimally. In addition, we describe how to modify our approach to exactly solve a previous work. Extensive experimental results are shown to demonstrate the effectiveness and efficiency of our approaches.
Genetic variation in the lactase gene, dairy product intake and risk for prostate cancer in the European Prospective Investigation into Cancer and Nutrition

High dairy protein intake has been found to be associated with increased prostate cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC). To further examine this possible relationship, we investigated the hypothesis that a genetic polymorphism in the lactase (LCT) gene might be associated with elevated dairy product intake and increased prostate cancer risk in a case–control study nested in EPIC. The C/T‐13910 lactase variant (rs4988235) was genotyped in 630 men with prostate cancer and 873 matched control participants. Dairy product consumption was assessed by diet questionnaire. Odds ratios (ORs) for prostate cancer in relation to lactase genotype were estimated by conditional logistic regression. Lactase genotype frequency varied significantly between countries, with frequencies of the T (lactase persistence) allele ranging from 7% in Greece to 79% in Denmark. Intake of milk and total dairy products varied significantly by lactase genotype after adjustment for recruitment center; adjusted mean intakes of milk were 44.4, 69.8 and 82.3 g/day among men with CC, CT and TT genotypes, respectively. The lactase variant was not significantly associated with prostate cancer risk, both in our data (adjusted OR for TT vs. CC homozygotes: 1.10, 95% CI: 0.76–1.59) and in a meta‐analysis of all the published data (combined OR for T allele carriers vs. CC homozygotes: 1.12, 0.96–1.32). These findings show that while variation in the lactase gene is associated with milk intake in men, the lactase polymorphism does not have a large effect on prostate cancer risk.
PENGARUH ALAT PERMAINAN EDUKATIF (PUZZLE) TERHADAP PERKEMBANGAN KOGNITIF ANAK USIA 5-6 TAHUN DI DESA LINAWAN KECAMATAN PINOLOSIAN KABUPATEN BOLAANG MONGONDOW SELATAN

Abstrack: Preschoolers are children at aged 36-60 months, during this period a child is prepared for school, where the senses and stimuli as well as acceptance of the receptor and memory process should be ready so that a child is capable to study with well, the learning process at this time is with play. Children’s kognitive ability could be indicated with play a game that using educational tool game. The purpose of this research is known the influence of educational tool game (puzzle) on children’s cognitive development at aged 5-6 years in the village of Pinolosian Sub-district Linawan Bolaang Mongondow Regency South. The design of this research uses pre-experiment method with one group pretest-posttest design. Sampling techniques uses sampling size, at least about 30 respondents. The results of statistical tests on Paired Sample t-test with a confidence level of 95% (α = 0.05) and the obtained p value 0.000<0.05. The conclusion indicates that there is the influence of teducational tool game (puzzle) children’s cognitive development at aged 5-6 years in the village of Pinolosian Sub-district Linawan Bolaang Mongondow Regency South. Keywords : Educational tool game (puzzle), Cognitive Development, preschoolers Abstrak: Anak prasekolah adalah anak yang berumur 36-60 bulan, pada masa ini anak dipersiapkan untuk sekolah, dimana panca indra dan sistim reseptor penerimaan rangsangan serta proses memori harus sudah siap sehingga anak mampu belajar dengan baik, proses belajar pada masa ini adalah dengan cara bermain. Kemanpuan Kognitif anak dapat ditunjukan dengan cara melaksanakan kegiatan bermain menggunakan alat permainan yang mengandung unsur atau nilai edukatif. Tujuan Penelitian ini adalah diketahui pengaruh alat permainan edukatif (puzzle) terhadap perkembangan kognitif anak usia 5-6 tahun di desa Linawan Kecamatan Pinolosian Kabupaten Bolaang Mongondow Selatan. Desain Penelitian ini menggunakan metode Pra Eksperimen dengan pendekatan one group pretest-post test design. Teknik pengambilan Sampel menggunakan sampling size sebesar minimal 30 orang responden. Hasil Uji Statistik hasil uji Paired Sample t-test dengan tingkat kepercayaan 95% (α=0,05) dan diperoleh p value 0,000 < 0,05. Kesimpulan yaitu ada pengaruh alat permainan edukatif (puzzle) terhadap perkembangan kognitif anak usia 5-6 tahun di Desa Linawan Kecamatan Pinolosian Kabupaten Bolaang Mongondow Selatan. Kata Kunci : Alat Permainan Edukatif (Puzzle), Perkembangan Kognitif, Anak prasekolah
Nonspecific Networking

A new model of strategic networking is developed and analyzed, where an agent’s investment in links is nonspecific. The model comprises a large class of games which are both potential and superor submodular games. We obtain comparative statics results for Nash equilibria with respect to investment costs for supermodular as well as submodular networking games. We also study supermodular games with potentials. We find that the set of potential maximizers forms a sublattice of the lattice of Nash equilibria and derive comparative statics results for the smallest and the largest potential maximizer. Finally, we provide a broad spectrum of applications from social interaction to industrial organization.
From exp-concavity to variance control: High probability O(1/n) rates and high probability online-to-batch conversion

We present an algorithm for the statistical learning setting with a bounded exp-concave loss in $d$ dimensions that obtains excess risk $O(d / n)$ with high probability: the dependence on the confidence parameter $\delta$ is polylogarithmic in $1/\delta$. The core technique is to boost the confidence of recent $O(d / n)$ bounds, without sacrificing the rate, by leveraging a Bernstein-type condition which holds due to exp-concavity. This Bernstein-type condition implies that the variance of excess loss random variables are controlled in terms of their excess risk. Using this variance control, we further show that a regret bound for any online learner in this setting translates to a high probability excess risk bound for the corresponding online-to-batch conversion of the online learner.
A Covert Channel Detection Algorithm Based on TCP Markov Model

Covert channels are used for transmitting secret information, which can penetrate the existing security equipments and bring potential dangers up to the information security. So, it’s very essential to develop the correspondent detection algorithms. In the paper, the potential redundancies in TCP protocol are analyzed, and the covert channel algorithms are divided into several kinds according to TCP protocol. And then, a new covert channel detection method is proposed based on the TCP Markov model for different application scenarios. Experiments show that the proposed algorithm achieves sound detection performance.
Fast Probabilistic Matrix Factorization for recommender system

In the past decades, with the rapid growth of online user data, it becomes challenging to develop preference learning algorithms that are sufficiently flexible in modeling but also affordable in computation. The enormous datasets and the situation that users who may have few ratings make it extremely hard for many existing approaches to handle. Collaborative filtering[1] is the most successful and popular technology in recommender system. The core of collaborative filtering is collaborative filtering algorithm, while the Probabilistic Matrix Factorization is one of the most useful algorithm. The Probabilistic Matrix Factorization (PMF)[2] model performs well on the large, sparse, and very imbalanced Netflix dataset. However, common methodologies based on error metrics, such as RMSE(Root-Mean-Square Error), are not a natural fit for evaluating the whole recommendation task. In this paper, based on Netflix dataset, we introduce a new Probabilistic Matrix Factorization algorithm called fast PMF, which can get a much better speed results and lower RMSE by updating n% ratings in the top of every movies. By comparing the original PMF, we can get a better understanding of fast PMF. There is a sorting algorithm in fast PMF, we expect a better result by choosing a relatively better sorting algorithm in the future.
Organising Centres in the Semi-global Analysis of Dynamical Systems

The notion of organising centre of a bifurcation diagram is used as an ordering principle in the analysis of nonlinear problems in pure and applied dynamical systems theory. When considering a given, generic n-parameter family of dynamical systems the codimension n bifurcations are isolated in the parameter space, generating a more global array of lower codimension bifurcations. It often makes sense to add one extra parameter to the system, e.g., by varying a ‘constant’ coefficient. In such cases, semi-global parts of the given n-dimensional bifurcation set can be understood as generic slices in versal unfoldings of codimension n + 1 singularities. This can give great insight in the structure of the given system, as we shall illustrate in two extensive case studies.