Miracle-dz/UniFAR-FTUs huggingface dataset:
Leveraging SDN for Efficient Anomaly Detection and Mitigation on Legacy Networks

In this paper, we investigate the applicability of Software-Defined Networking (SDN), and specifically the use of the OpenFlow protocol as a means to enhance the legacy Remote Triggered Black-Hole (RTBH) routing approach, towards Distributed Denial of Service (DDoS) attack mitigation. More specifically, we exploit the network programmability of OpenFlow to match and handle traffic on a per-flow level, in order to preserve normal operation of the victim, while pushing the mitigation process upstream towards the edge of the network. To this end, we implemented and evaluated a sketch-based anomaly detection and identification mechanism, capable of pinpointing the victim and remotely triggering the mitigation of the offending network traffic. The evaluation is based on the combination of datasets containing real DDoS attacks and normal background traffic from an operational university campus network. Our results demonstrated that the proposed approach succeeds in identifying the victim of the attack and efficiently filtering the malicious sources.
Effect of optical digitizer selection on the application accuracy of a surgical localization system-a quantitative comparison between the OPTOTRAK and flashpoint tracking systems.

Application accuracy is a crucial factor for stereotactic surgical localization systems, in which space digitization camera systems are one of the most critical components. In this study we compared the effect of the OPTOTRAK 3020 space digitization system and the FlashPoint Model 3000 and 5000 3D digitizer systems on the application accuracy for interactive localization of intracranial lesions. A phantom was mounted with several implantable frameless markers which were randomly distributed on its surface. The target point was digitized and the coordinates were recorded and compared with reference points. The differences from the reference points represented the deviation from the "true point. " The root mean square (RMS) was calculated to show the differences, and a paired t-test was used to analyze the results. The results with the phantom showed that, for 1-mm sections of CT scans, the RMS was 0.76 +/- 0. 54 mm for the OPTOTRAK system, 1.23 +/- 0.53 mm for the FlashPoint Model 3000 3D digitizer system, and 1.00 +/- 0.42 mm for the FlashPoint Model 5000 system. These preliminary results showed that there is no significant difference between the three tracking systems, and, from the quality point of view, they can all be used for image-guided surgery procedures.
Illustration of a Multi-agent Systems Concept as User's Collaborative Software System

To introduce the multi-agent systems (MaS) as a new technology in software engineering and making it acceptable by the industries requires adequate clarification to show the advantages and the improvements of this technology over the existing ones. A substantial survey in the field of multi-agent systems research literature reveals that the majority of the system developers have not accurately identified the purpose behind applying the multi-agent system from the human computer interaction (HCI) perspective, as a userpsilas cooperative system. The aim of this paper is to illustrate how the MaS concept is centred on establishing a user collaborative system and explain why this concept is essential to the modern software engineering strategies. The research also identifies the multi-agent systems problem domains and its emphasis on the existing Web services user coordination problem. It then proposes high level semantic Web architecture. The research concludes by a listing of the advantages of applying multi-agent systems, from the usability and quality perspectives.
What to do and how to do it: Translating natural language directives into temporal and dynamic logic representation for goal management and action execution

Robots that can be given instructions in spoken language need to be able to parse a natural language utterance quickly, determine its meaning, generate a goal representation from it, check whether the new goal conflicts with existing goals, and if acceptable, produce an action sequence to achieve the new goal (ideally being sensitive to the existing goals). In this paper, we describe an integrated robotic architecture that can achieve the above steps by translating natural language instructions incrementally and simultaneously into formal logical goal description and action languages, which can be used both to reason about the achievability of a goal as well as to generate new action scripts to pursue the goal. We demonstrate the implementation of our approach on a robot taking spoken natural language instructions in an office environment.
Clinical studies with oral lipid based formulations of poorly soluble compounds

This work is an attempt to give an overview of the clinical data available on lipid based formulations. Lipid and surfactant based formulations are recognized as a feasible approach to improve bioavailability of poorly soluble compounds. However not many clinical studies have been published so far. Several drug products intended for oral administration have been marketed utilizing lipid and surfactant based formulations. Sandimmune® and Sandimmune Neoral® (cyclosporin A, Novartis), Norvir® (ritonavir), and Fortovase® (saquinavir) have been formulated in self-emulsifying drug delivery systems (SEDDS). This review summarizes published pharmacokinetic studies of orally administered lipid based formulations of poorly aqueous soluble drugs in human subjects. Special attention has been paid to the physicochemical characteristics of the formulations, when available and the impact of these properties on the in vivo performance of the formulation. Equally important is the effect of concurrent food intake on the bioavailability of poorly soluble compounds. The effect of food on the bioavailability of compounds formulated in lipid and surfactant based formulations is also reviewed.
Tie me up, tie me down!: the interplay of the unemployment compensation system, fixed-term contracts and rehirings

Using an administrative dataset, we document the importance of recalls in labour market transitions and in compensated unemployment in Spain and examine the interplay between the unemployment compensation system, the widespread use of fixed-term contracts and the layoff-rehire process. We estimate a discrete-time duration model with competing risks of exits in order to investigate the individual, job and firm attributes that influence the probabilities of leaving unemployment to return to the same employer or to find a new job with a different employer. Our findings indicate that recalls are very common, with nearly half of job losers returning to their former employers, and that, although these are widespread along the Spanish labour market, there are certain types of contracts, firms and sectors which are more prone to them.
Novel method for the spectrophotometric determination of isoniazid and ritodrine hydrochloride

A simple, rapid and sensitive spectrophotometric method for the determination of isoniazid (INH) and ritodrine hydrochloride (RTH) in pure form as well as dosage forms is described. The method is based on the diazotisation of 4,4'-sulphonyldianiline (dapsone, DAP) followed by a coupling reaction with either INH or RTH in sodium hydroxide medium. Beer's law is obeyed in the concentration range of 0.5-20 mug ml(-1) for INH at 440 nm and 0.5-18 mug ml(-1) for RTH at 460 nm. The method is successfully employed for the determination of INH/RTH in pharmaceutical preparations and the results agree favourably with the official and reported methods. Common excipients used as additives in pharmaceuticals do not interfere in the proposed method. The method-offers the advantages of simplicity, rapidity and sensitivity without the need for extraction or heating. Limit of detection (LOD) and limit of quantification (LOQ) are reported.
Supervised Manifold Learning for Media Interestingness Prediction

In this paper, we describe the models designed for automatically selecting multimedia data, e.g., image and video segments, which are considered to be interesting for a common viewer. Specifically, we utilize an existing dimensionality reduction method called Neighborhood MinMax Projections (NMMP) to extract the low-dimensional features for predicting the discrete interestingness labels. Meanwhile, we introduce a new dimensionality reduction method dubbed Supervised Manifold Regression (SMR) to learn the compact representations for predicting the continuous interestingness levels. Finally, we use the nearest neighbor classifier and support vector regressor for classification and regression, respectively. Experimental results demonstrate the effectiveness of the low-dimensional features learned by NMMP and SMR.
Segmentation of prostate ultrasound images using a parametric model

This article presents a method for automatic segmentation of prostate from abdominal freehand ultrasound images. A statistical model of prostate is estimated from a manually delineated images. The segmentation starts by smoothing the image to enhance edges by applying a modified version of the adaptive filter which detects individual speckles and remove them, while it preserves valuable details. Then the boundary is initialised starting from the model and the final form is sought by a simulated annealing optimisation algorithm. The performances of the algorithm were compared with manual segmentation, the average distance was 3.7 pixels with a standard deviation of 2.3.
The Notch Ligand Delta-Like 4 Regulates Multiple Stages of Early Hemato-Vascular Development

Background In mouse embryos, homozygous or heterozygous deletions of the gene encoding the Notch ligand Dll4 result in early embryonic death due to major defects in endothelial remodeling in the yolk sac and embryo. Considering the close developmental relationship between endothelial and hematopoietic cell lineages, which share a common mesoderm-derived precursor, the hemangioblast, and many key regulatory molecules, we investigated whether Dll4 is also involved in the regulation of early embryonic hematopoiesis. Methodology/Principal Findings Using Embryoid Bodies (EBs) derived from embryonic stem cells harboring hetero- or homozygous Dll4 deletions, we observed that EBs from both genotypes exhibit an abnormal endothelial remodeling in the vascular sprouts that arise late during EB differentiation, indicating that this in vitro system recapitulates the angiogenic phenotype of Dll4 mutant embryos. However, analysis of EB development at early time points revealed that the absence of Dll4 delays the emergence of mesoderm and severely reduces the number of blast-colony forming cells (BL-CFCs), the in vitro counterpart of the hemangioblast, and of endothelial cells. Analysis of colony forming units (CFU) in EBs and yolk sacs from Dll4+/− and Dll4−/− embryos, showed that primitive erythropoiesis is specifically affected by Dll4 insufficiency. In Dll4 mutant EBs, smooth muscle cells (SMCs) were seemingly unaffected and cardiomyocyte differentiation was increased, indicating that SMC specification is Dll4-independent while a normal dose of this Notch ligand is essential for the quantitative regulation of cardiomyogenesis. Conclusions/Significance This study highlights a previously unnoticed role for Dll4 in the quantitative regulation of early hemato-vascular precursors, further indicating that it is also involved on the timely emergence of mesoderm in early embryogenesis.
Stemming Indonesian

Stemming words to (usually) remove suffixes has applications in text search, machine translation, document summarisation, and text classification. For example, English stemming reduces the words "computer", "computing", "computation", and "computability" to their common morphological root, "comput-". In text search, this permits a search for "computers" to find documents containing all words with the stem "comput-". In the Indonesian language, stemming is of crucial importance: words have prefixes, suffixes, infixes, and confixes that make matching related words difficult. In this paper, we investigate the performance of five Indonesian stemming algorithms through a user study. Our results show that, with the availability of a reasonable dictionary, the unpublished algorithm of Nazief and Adriani correctly stems around 93% of word occurrences to the correct root word. With the improvements we propose, this almost reaches 95%. We conclude that stemming for Indonesian should be performed using our modified Nazief and Adriani approach.
Speculative Genetic Scheduling Method for Hadoop Environments

The existence of computational intensive applications with a high degree of granularity which have to be executed as quickly as possible or sometimes with budget limitations makes the scheduling problem to be very important in today's distributed systems. In the context of the distributed systems being used by a various community of users, the quality and precision of the scheduling must be as close to optimality as possible. We present in this paper a scheduling method based on a genetic algorithm which respects the deadline constraints. Based on this model we developed a scheduler for MapReduce applications which also takes into account the heterogeneity of distributed systems. The developed scheduler was created for Hadoop platform, an already successful framework, and it can be built in conjunction with other existing Hadoop's schedulers like: fair-scheduler or capacity-scheduler. We tested and validated this model by testing its scalability and by comparing it with existing solutions in Hadoop. The novelty of this solution is that compared to other planners in Hadoop it meets the deadline and budget constraints and thus provides trust for the Hadoop platform.
Associations among entities related to Alzheimer Disease using Ontology based approach

Text mining is similar to data mining, except that data mining tools are designed to handle structured data from databases whereas Text mining can work with unstructured or semi-structured data sets such as emails, full-text documents and HTML files etc. The research aspect in Text mining includes Information Extraction, Information Search and Retrieval, Text Document Categorization (Supervised Classification), Text Document Clustering (Unsupervised Classification)and Text Summarization. This research work focuses on Information Extraction and mining of Association rules in which the Information Extraction is used to identify and extract textual information of specific types of entities and their relationships, and the mining of Association rules is nothing but extraction of semantic knowledge among entities that are extracted by Information Extraction phase. The goal of our research is to design information extraction approach to extract entities from Medline abstracts and to mine association rules among extracted entities. This work uses Bioinformatics databases Gene Ontology, MeSH ontology and Medline abstracts related to a particular interest particularly abstracts related to Alzheimer Disease. Keywords: Information Extraction, Gene name, Protein name, Regular Expression, Medline abstracts, Ontology, Alzheimer disease.
Condition Monitoring, Root Cause Analysis and Decision Support on Urgency of Actions

We discuss the use of a hybrid system utilizing Object Oriented Bayesian networks and influence diagrams for probabilistic reasoning under uncertainties in industrial process operations. The Bayesian networks are used for condition monitoring and root cause analysis of process operation. The recommended decision sequence of corrective actions and observations is obtained following the "myopic" approach. The BN inference on most probable root cause is used in an influence diagram for taking decisions on urgency of corrective actions vs. delivery deadline. The build-in chain of causality from root cause to process faults can provide the user with explanation facility and a simulation tool of the effect of intended actions.
A performance optimization method by gate sizing using statistical static timing analysis

We propose a gate resizing method for delay and power optimization that is based on statistical static timing analysis. Our method focuses on the component of timing uncertainties due to local random fluctuation. Utilizing our method, over-design of a circuit can be eliminated and high-performance and high-reliability LSI design can be realized. The effectiveness of our method is examined by 6 benchmark circuits. We verify that our method can reduce delay and power dissipation from the circuits optimized without the consideration of fluctuation.
WISE design for knowledge integration

Scaling research-based curriculum to the multitude of science teaching standards and contexts has proven difficult in the past. To respond to the challenge, the Web-based Inquiry Science Environment (WISE) offers designers a technology-enhanced, research-based, flexibly adaptive learning environment. The learning environment can incorporate new features such as modeling tools or hand-held devices. Using WISE, design teams can create projects that bend but do not break when customized to support new school contexts and state standards. WISE curriculum projects are created by diverse design teams that include classroom teachers, technologists, discipline experts, pedagogy researchers, and curriculum designers. WISE inquiry projects incorporate Internet materials and build on the commitments and talents of teachers as well as the constraints and opportunities of their classroom contexts rather than imposing new practices without concern for past successes. These design teams create projects that incorporate diverse features of the WISE learning environment to form specific patterns that are then combined into whole projects. We refer to the whole projects as implementing curriculum design patterns for student activities. The projects are tested to determine how the curriculum design patterns promote knowledge integration, then reviewed by WISE researchers and revised accordingly (see M. C. Linn, P. Bell, & E. A. Davis, in press, Internet Environments for Science Education). Hillsdale, NJ: Erlbaum. ). The most successful projects become part of the WISE library. This paper describes WISE design team practices, features of the WISE learning environment, and patterns of feature use in current library projects. The success of WISE in classrooms illustrates how flexibly adaptive projects can meet the needs of diverse teachers. Variation amongst library projects shows that designers can support inquiry with a wide variety of activities. Taken together, the library of projects and the success of students learning from them suggest that sustainable curricular innovations require extensive opportunities for customization and flexibly adaptive designs. © 2003 Wiley Periodicals, Inc. Sci Ed87:517–538, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/sce.10086
Big Data and the Data Value Chain: Translating Insights from Business Analytics into Actionable Results - The Case of Unit Load Device (ULD) Management in the Air Cargo Industry

Business intelligence and analytics enjoy a great deal of attention today. However, there is a lack of studies considering the full data value chain from (raw) data through business analytics to valuable decisions, i.e. also scrutinizing the latter stages of the data value chain, namely timely deployment and operational usage of valuable insights as demanded by practice. Following a design science approach, we develop a concept for the fast and flexible integration of valuable insights into daily decision support. A key feature of our concept is to provide valuable insights from business intelligence in an understandable manner to decision makers using a rule-based expert systems approach. In order to demonstrate the feasibility of our concept, we implemented a prototype in a complex real-world scenario, i.e. unit load device (ULD) management in the air cargo industry. This research in progress presents our preliminary findings and outlines the potential of the proposed concept.
Let’s (not) meet at the pool: A Black Canadian social history of swimming (1900s–1960s)

While sport has been touted as a bridge for racial equality, racial discrimination has been as present in recreational and sporting spaces, as in any other public spaces. Discrimination in these spaces can thus inform racial relations in a society. Few Canadian studies have been conducted on the development of racial discourses in the context of recreational spaces, especially from a historical perspective. Through the lens of swimming, a historically exclusive recreational and sporting activity, this paper aims at positioning swimming experiences within racial and power relations between Black and White people in Canada. The findings inform us that racial discourses were continuously reinforced in swimming spaces, and shaped Black Canadians’ experience. The particularities of and similarities between the various cases discussed also underscore the nuanced and varied effects of pre-1970s informal racial discrimination policy in Canada.
The Subsurface Geology of Mars: Remote Sensing of Impact Craters Using THEMIS, TES, MOC and MOLA

THEMIS, TES, MOC AND MOLA. L. L. Tornabene, J. E. Moersch, H. Y. McSween Jr., V. E. Hamilton, J. L. Piatek, K. A. Milam and P. R. Christensen; Department of Earth and Planetary Sciences, University of Tennessee, Knoxville, Tennessee 37996-1410, Hawai’i Institute of Geophysics and Planetology, University of Hawai’i, Honolulu, Hawai’i, 96822, USA, 3 Department of Geological Sciences, Arizona State University, Tempe, Arizona 85287–6305, USA.
A Controlled Preemption Scheme for Emergency Applications in Cellular Networks

In this paper, we introduce a threshold-based preemption strategy for supporting emergency traffic in cellular networks. Compared with current commercially used policies, our scheme can not only guarantee a certain amount of resources to public customers but can also provide immediate access for emergency users and flexibility for providers to adapt to different requirements and operating scenarios. In addition, under the combined preemption and queuing framework, interesting analytical relationships among channel occupancy, gross service time, and success probability for public traffic are revealed. Based on this, guidelines to further improve the satisfaction of public customers can be provided.
Modified Generalized Discriminant Analysis Using Orthogonalization in Feature Space and Difference Space

In this paper we propose a more efficient and effective algorithm of generalized discriminant analysis (GDA) by performing Gram-Schmidt orthogonalization procedure in feature space only once on difference vectors. The proposed method is substantially equivalent to class-incremental GDA [W. Zheng, ¿class-Incremental generalized discriminant analysis¿, neural computation 18, 979-1006 (2006)], since both methods search the essentially equivalent nonlinear optimal discriminative vectors in the range space of total scatter matrix and the null space of within-class scatter matrix. But since there is no need to compute the class mean in the proposed method as needed in class-incremental GDA, the computational cost is reduced greatly in the proposed method. The experiments on two standard face databases verified the effectiveness of the proposed method.