Miracle-dz/UniFAR-FTUs huggingface dataset:
Denial-of-Service, Probing & Remote to User (R2L) Attack Detection using Genetic Algorithm

Nowadays it is very important to maintain a high level security to ensure safe and trusted communication of information between various organizations. But secured data communication over internet and any other network is always under threat of intrusions and misuses. To control these threats, recognition of attacks is critical matter. Probing, Denial of Service (DoS), Remote to User (R2L) Attacks are some of the attacks which affects large number of computers in the world daily. Detection of these attacks and prevention of computers from it is a major research topic for researchers throughout the world. In this paper idea for use of a Genetic Algorithm (GA) based approach for generation of rules to detect Probing, DoS and R2L attacks on the system is proposed. General Terms Network Security, Genetic Algorithms.
Person resolution in person search results: WebHawk

Finding information about people on the Web using a search engine is difficult because there is a many-to-many mapping between person names and specific persons (i.e. referents). This paper describes a person resolution system, called WebHawk. Given a list of pages obtained by submitting a person query to a search engine, WebHawk facilitates person search in three steps: First of all, a filter removes those pages that contain no information about any person. Secondly, a cluster groups the remaining pages into different clusters, each for one specific person. To make the resulting clusters more meaningful, an extractor is used to induce query-oriented personal information from each page. Finally, a namer generates an informative description for each cluster so that users can find any specific person easily. The architecture of WebHawk is presented, and the four components are discussed in detail, with a separate evaluation of each component presented where appropriate. A user study shows that WebHawk complements most existing search engines and successfully improves users' experience of person search on the Web.
Adventures in Anesthetic Mechanisms

&NA; Exaggerated Anesthetic Requirements in the Preferentially Anesthetized Brain. By J. F. Antognini and K. Schwartz. ANESTHESIOLOGY 1993; 79:1244–9. Abstract reprinted with permission. Background: The brain is assumed to be the site of anesthetic action, but anesthetics have effects elsewhere, such as the spinal cord. A preferentially anesthetized goat brain model was used to determine the importance of anesthetic action in the brain. Methods: Six goats were anesthetized with isoflurane; after tracheal intubation and insertion of a femoral arterial catheter, bilateral neck dissections were performed to isolate the external carotid arteries and external jugular veins. The occipital arteries were ligated to prevent vertebral blood from entering the carotid system. (Goats do not have direct, significant vertebral artery contributions to the brain, and they lack internal jugular veins.) Control isoflurane minimum alveolar concentration (MAC) was determined using a dew-claw clamp as the painful stimulus. Following this, cranial venous blood was drained into a bubble oxygenator in which an isoflurane vaporizer was placed in line with the gas flow. Oxygenator arterial isoflurane concentration was estimated from the isoflurane partial pressure in the oxygenator exhaust. Isoflurane administration via the lungs was discontinued and the isoflurane partial pressure in the blood delivered via the carotid artery was increased by an amount required to bracket the partial pressures permitting and preventing movement in response to dew-claw stimulation. The native circulation was reestablished and MAC determined again. Results: Cerebral isoflurane requirements were 1.2 ± 0.3% (mean ± SD) before bypass, increased to 2.9 ± 0.7% during bypass when the brain was preferentially anesthetized, and decreased to 1.3 ± 0.1% after bypass. Conclusions: The results support the importance of subcortical structures, such as the spinal cord, in the generation of purposeful movement in response to a painful stimulus under general anesthesia.
A Hybrid Approach to Survival Model Building Using Integration of Clinical and Molecular Information in Censored Data

In medical society, the prognostic models, which use clinicopathologic features and predict prognosis after a certain treatment, have been externally validated and used in practice. In recent years, most research has focused on high dimensional genomic data and small sample sizes. Since clinically similar but molecularly heterogeneous tumors may produce different clinical outcomes, the combination of clinical and genomic information, which may be complementary, is crucial to improve the quality of prognostic predictions. However, there is a lack of an integrating scheme for clinic-genomic models due to the P ≫ N problem, in particular, for a parsimonious model. We propose a methodology to build a reduced yet accurate integrative model using a hybrid approach based on the Cox regression model, which uses several dimension reduction techniques, L2 penalized maximum likelihood estimation (PMLE), and resampling methods to tackle the problem. The predictive accuracy of the modeling approach is assessed by several metrics via an independent and thorough scheme to compare competing methods. In breast cancer data studies on a metastasis and death event, we show that the proposed methodology can improve prediction accuracy and build a final model with a hybrid signature that is parsimonious when integrating both types of variables.
Towards a hermeneutic method for interpretive research in information systems

There is increasing interest in hermeneutics as a research approach in the field of information systems. However, the problem facing researchers is that there is a paucity of information on the application of hermeneutics for empirical research in the social sciences; indeed, there is very little guidance on what exactly constitutes a hermeneutic method for the investigation of social phenomena. In order to address this problem, this paper provides an overview of concepts and principles from the related philosophies of phenomenology and hermeneutics; it then illustrates their application in an interpretive case study on the information systems development process. The insights obtained from the application of the hermeneutic method outlined in this paper have helped realize the study's objective of illustrating the link between phenomenological hermeneutics and the conduct of interpretive research.
Fine Granular Aspect Analysis using Latent Structural Models

In this paper, we present a structural learning model for joint sentiment classification and aspect analysis of text at various levels of granularity. Our model aims to identify highly informative sentences that are aspect-specific in online custom reviews. The primary advantages of our model are two-fold: first, it performs document-level and sentence-level sentiment polarity classification jointly; second, it is able to find informative sentences that are closely related to some respects in a review, which may be helpful for aspect-level sentiment analysis such as aspect-oriented summarization. The proposed method was evaluated with 9,000 Chinese restaurant reviews. Preliminary experiments demonstrate that our model obtains promising performance.
Towards Privacy in Enterprise Directory Services: A User-Centric Approach to Attribute Management

Enterprise directory services (EDS) are commonly used to store attributes related to individual users within a corporation, and provide those attributes to authorized users upon request. These attributes may contain sensitive personal information, such as citizenship or social security numbers. Consequently, access to such information is generally controlled, usually by traditional methods such as access control lists. However, if a user-centric identity management model is considered, in which users control their own information and control access to that information, traditional EDS implementations do not provide complete protection from a user perspective. We propose combining public key infrastructure, user-centric identity management, and EDS to allow users control of the personal information stored within a directory as well as who is allowed to access that information. We demonstrate how a user may employ PKI to encrypt individual attributes, then share decryption information with selected entities. Among other advantages, this solution eliminates the possibility of administrative access to users information, a potential threat that exists within many EDS
Illustrative Rendering of White Matter Fiber Bundles

Since the 1970s the science and technology behind magnetic resonance imaging (MRI) has steadily become more advanced. With today’s MRI technology, we can scan the human brain and record enough data to reconstruct tissue structures of the brain in a virtual 3D environment. These kind of medical visualizations allow for exploratory analysis of the scan, which can be a useful tool for the study of anatomy or pathology. However, such visualizations can quickly become too complex to manage for the viewer, resulting in reduced insight. This is especially a problem when dealing with large and dense sets of data, such as those referencing the entire white matter of the brain in whole-brain visualizations. A common approach to make more sense of such large data sets is to cluster the reconstructed white matter into bundles with anatomic meaning. While such clustering methods alleviate the issue somewhat, they generally continue to visually represent the bundle by its individual tissue structures, which is still cluttered. We investigate a novel visualization method by which to render such bundles, based on illustrative rendering. Illustrative rendering specializes in producing stylized images which allow for a great deal of abstraction. We aim to use guidelines and techniques from the traditional fields of hand drawn illustration to provide a more abstract illustrative visualization of the clustered white matter. The rendering technique will be accompanied by a focus & context technique based on the paradigm of exploded views. It interactively shifts the positions of contextual bundles in a non-obtrusive way, making room for viewing the focused bundle fully. This visualization enables us to see and work with the data on the higher level of bundles, rather than on that of the individually visualized white matter tissue.
Security Service Adaption for . . .

—Distributed embedded applications increasingly operate in changing environments where the application security depends on the type and properties of the currently used communication services and employed devices. While vulner-abilities, threats, and available security function processing power are changing, the applications, however, should automatically adapt to the varying conditions in order to maintain the necessary security without endeavor of users. We report on the security management subproject of the SIRENA project where we apply a special combination of policy-based management with model-based management in order to support fully automated security management functions at runtime as well as tool-assisted security requirement definition and system design. Within an application model, the definition of the ap-plication's high-level security policy is of special importance. It represents the abstract security requirements and forms the starting point for the automated derivation of suitable security subsystem configurations which enforce the policy under changing environment conditions. The abstract policy representation relies on the Generalized Role Based Access Control model (GRBAC).
The challenge of introducing a new software cost estimation technology into a small software organisation

Fostering innovation is the key to survival in today's IT business and is exemplified by introducing new technologies and methods to improve the development processes. We present a follow-up case study of technology transfer in a small software organisation. A new software estimation technique, Web-CoBRA was introduced to a small software company to improve their software estimation process. Web-CoBRA was considerably more accurate than the company's current estimation process. However, despite management being aware of this improvement, the company has not fully adopted the new method. We used interviews and the technology acceptance model (TAM) questionnaire to assess the extent to which Web-CoBRA was used by the company. We found take-up of part of the Web-CoBRA technology but the full technology and the support tools were not used. We identify the reasons for the failure to adopt the Web-CoBRA technology and identify several areas for improving technology transfer activities.
El Niño–southern oscillation influences on the Mahaweli streamflow in Sri Lanka

Despite advances over the last two decades in the capacity to predict the evolution of the El Niño–southern oscillation (ENSO) phenomenon and advances in understanding of the relationship between ENSO and climate, there has been little use of climate predictions for water resources management in the tropics. As part of an effort to develop such a prediction scheme, the ENSO influences on streamflow and rainfall in the upper catchment of the Mahaweli river in Sri Lanka were investigated with correlation analysis, composite analysis and contingency tables. El Niño conditions were often associated with decreased annual flows and La Niña with increased flows. The relationship of streamflow and rainfall with the ENSO index of NINO3 contrasted between January to September and October to December. During El Niño episodes the streamflow declines from January to September, but from October to December there is no clear relationship. On the other hand, rainfall shows a clear increase from October to December and declines during January, February, March, July and August. The simultaneous correlations of NINO3 with the aggregate January to September streamflow (r = −0.50), with January to September rainfall (r = −0.44) and with October to December rainfall (r = 0.48) are all significant at the 99% level. The correlation between one‐season‐in‐advance NINO3 with both January to September streamflow and October to December rainfall remained significant at the 99% level.
Statistical delay calculation, a linear time method

This paper discusses a statistical approach to static timing analysis. Delays of gates and wires are modeled by stochastic values instead of the triple best case, typical and worst case delay. This has the advantage of avoiding the overly pessimistic (optimistic) outcome of traditional worst (best) case calculations. The paper proposes a new approximate scheme to perform the delay calculations with stochastic delay values in linear time. The results are validated with Monte Carlo simulations. From a mathematical analysis some counter–intuitive properties of delays in the presence of uncertain delay values are shown. The results section shows that that traditional worst–case timing analysis is on average 21% too pessimistic for the set of IWLS ’91 combinational benchmark circuits for a given delay model. Also, it is shown that the traditional typical delay calculation underestimates the most likely circuit delay by 0 – 14%. Furthermore, due to the mathematical properties of the delay calculations, the uncertainty in the delay of a circuit is usually much smaller than the uncertainty in the delays of the individual delay elements.
Cognitive Impairment in Major Depressive Disorder: Clinical Relevance, Biological Substrates, and Treatment Opportunities

Major depressive disorder (MDD) is the leading cause of disability globally in both developed and developing nations. The staggering economic costs attributable to MDD are largely a consequence of impairment in role function. Evidence indicates that disturbance in the domain of cognitive function in individuals with MDD is the principal determinant of health outcome. This is the first book to comprehensively explore the domain of cognition in MDD. The literature describing cognitive dysfunction is reviewed with particular focus on clinical determinants, pathophysiology and causative factors. The patient subpopulations most susceptible are defined. A summary of contemporary assessment tools for research and clinical purposes is provided. Multimodality treatments and prevention strategies are described. This book is an invaluable resource for psychiatrists, neuropsychologists and other members of the mental health team, as well as for policy makers, vocation rehabilitation experts, disability providers and other stakeholders interested in improving health outcomes in MDD.
Dance One Scenario for Choreographic Coordination of Intelligent Agents in Entertainment Applications

Most researches in agent coordination for computer games focus on tactical/spatial coordination of NPCs (Non Playable Characters) seeking effective methods for accomplishing a collective task in the context of war games, FPS (First Person Shooters) and RTS (Real Time Strategy) (e.g., [Almeida et al. 2004; Madeira et al. 2005; Marthi et al. 2005]). Some research efforts have been employed to make the movements of group of agents more realistic and pleasant [Messick 1999; Reynolds 1999]. However, the aesthetic aspect plays a secondary role in the complexity of the task the group of agents must accomplish. This work represents a step forward towards a deeper concern on the aesthetic/choreographic dimension that may arise from the NPCs interactions. Based on a framework for supporting multi-agent choreographic coordination [Lima et al. 2005], we present an original 2D entertainment application, named DiscoTech, where agents reason, communicate and coordinate with each other in order to form groups and perform choreographies.
Cardiovascular Health Metrics and All-cause and Cardiovascular Disease Mortality Among Middle-aged Men in Korea: The Seoul Male Cohort Study

Objectives This study estimated the association of cardiovascular health behaviors with the risk of all-cause and cardiovascular disease (CVD) mortality in middle-aged men in Korea. Methods In total, 12 538 men aged 40 to 59 years were enrolled in 1993 and followed up through 2011. Cardiovascular health metrics defined the following lifestyle behaviors proposed by the American Heart Association: smoking, physical activity, body mass index, diet habit score, total cholesterol, blood pressure, and fasting blood glucose. The cardiovascular health metrics score was calculated as a single categorical variable, by assigning 1 point to each ideal healthy behavior. A Cox proportional hazards regression model was used to estimate the hazard ratio of cardiovascular health behavior. Population attributable risks (PARs) were calculated from the significant cardiovascular health metrics. Results There were 1054 total and 171 CVD deaths over 230 690 person-years of follow-up. The prevalence of meeting all 7 cardiovascular health metrics was 0.67%. Current smoking, elevated blood pressure, and high fasting blood glucose were significantly associated with all-cause and CVD mortality. The adjusted PARs for the 3 significant metrics combined were 35.2% (95% confidence interval [CI], 21.7 to 47.4) and 52.8% (95% CI, 22.0 to 74.0) for all-cause and CVD mortality, respectively. The adjusted hazard ratios of the groups with a 6-7 vs. 0-2 cardiovascular health metrics score were 0.42 (95% CI, 0.31 to 0.59) for all-cause mortality and 0.10 (95% CI, 0.03 to 0.29) for CVD mortality. Conclusions Among cardiovascular health behaviors, not smoking, normal blood pressure, and recommended fasting blood glucose levels were associated with reduced risks of all-cause and CVD mortality. Meeting a greater number of cardiovascular health metrics was associated with a lower risk of all-cause and CVD mortality.
Random amplified polymorphic DNA (RAPD) markers readily distinguish cryptic mosquito species (Diptera: Culicidae: Anopheles)

The usefulness of random amplified polymorphic DNA (RAPD) was examined as a potential tool to differentiate cryptic mosquito species. It proved to be a quick, effective means of finding genetic markers to separate two laboratory populations of morphologically indistinguishable African malaria vectors, Anopheles gambiae and An. arabiensis. In an initial screening of fiftyseven RAPD primers, 377 bands were produced, 295 of which differed between the two species. Based on criteria of interpretability, simplicity and reproducibility, thirteen primers were chosen for further screening using DNA from thirty individuals of each species. Seven primers produced diagnostic bands, five of which are described here. Some problematic characteristics of RAPD banding patterns are discussed and approaches to overcome these are suggested.
Simple, XOR based, image edge detection

In this paper a simple, XOR based, approach to image edge detection is proposed, hereafter referred to as SXOR. From the well known fact that, generally, in plain-images, any arbitrarily chosen pixels are strongly correlated with their adjacent ones (regardless of spatial orientation, i.e. either if they are diagonally, vertically or horizontally oriented); the bitwise XOR logical operator is applied between all pixels, on image's successive pairs of rows and columns; thus, featuring existing differences (i.e. in between the pairs) and implicitly, all edges within the image. Conducted experimental results demonstrate the validity of the proposed approach (e.g. it reduces the amount of data and filters out useless information, while preserving the most important structural properties of the image) and its effectiveness, relative to several other operators.
Multiuser detection for CDMA systems with nonlinear modulation

Most of the extensive literature on multiuser detection for direct-sequence code division multiple access (CDMA) focuses on systems with (direct or differential) linear modulation. There are a number of existing CDMA systems, however, that do not fall within this setting. In this paper, we consider the general problem of multiuser detection for CDMA with nonlinear modulation. We have two basic goals: (i) To characterize the best possible performance obtainable using multiuser detection. To this end, we consider the maximum likelihood (ML) receiver, which assumes knowledge of the timing and complex amplitudes for all users, and the generalized likelihood ratio test (GLRT), which requires knowledge only of the timing for all users. Both receivers have complexity exponential in the number of users. (ii) To obtain low-complexity multiuser detectors that outperform the conventional single user detector (which ignores the presence of the multiple-access interference). We propose two new decision projection algorithms with complexity linear in the number of users.
Clustering Documents with Large Overlap of Terms into Different Clusters based on Similarity Rough Set Model

Similarity rough set model for document clustering (SRSM) uses a generalized rough set model based on similarity relation and term co-occurrence to group documents in the collection into clusters. The model is extended from tolerance rough set model (TRSM) (Ho and Funakoshi, 1997). The SRSM methods have been evaluated and the results showed that it perform better than TRSM. However, in document collections where there are words overlapped in different document classes, the effect of SRSM is rather small. In this paper we propose a method to improve the performance of SRSM method in such document collections.