Miracle-dz/UniFAR-FTUs huggingface dataset:
Connectionless port scan detection on the backbone

Considerable research has been done on detecting and blocking portscan activities that are typically conducted by infected hosts to discover other vulnerable hosts. However, the focus has been on enterprise gateway-level intrusion detection systems where the traffic volume is low and network configuration information is readily available. This paper investigates the effectiveness of existing portscan detection algorithms in the context of a large transit backbone network and proposes a new algorithm that meets the demands of aggregated high speed backbone traffic. Specifically, we evaluate two existing approaches - the portscan detection algorithm in SNORT, and a modified version of the TRW algorithm that is a part of the intrusion detection tool BRO. We then propose a new approach, TAPS, which uses sequential hypothesis testing to detect hosts that exhibit abnormal access patterns in terms of destination hosts and destination ports. We perform a comparative analysis of these three approaches using real backbone packet traces, and find that TAPS exhibits the best performance in terms of catching the maximum number of true scanners and yielding the least number of false positives. We have a working implementation of TAPS on our monitoring platform. Further implementation optimizations using bloom filters are identified and discussed
Anonymous Routing Protocol with Multiple hops for Communications in Highly Dynamic Hetrogenious Networks

Mobile ad hoc networks (MANETs) are increasingly adopted in both military and civilian usesdue to its self configuration and self-maintenance capabilities. MANETs are higly vulnerable to security threats due to inherent charateristics as wireless transmission , lack of fixed infrastructure , dynamically changing topoly, etc. The broadcast nature of the wireless medium makes MANETs susceptible to various malicious attacks. Traffics annalsis is one of the most serious security attacks in MANETs. For instance , in a battle field the enemy can physically destroy the important mobile nodes if they can identify and locate suck nodes by traffic analysis . In order to thwat such attacks , ananymous communication protocols are developed. For the purposes of security and robustness , an ideal anonymous routing protocals as in the route, in particular , those of the source and the destination. Multiple routes should be established to increase the difficulty of traffic analysis and to avoid broken paths due to node mobility . Existing schemes either make the unrealistic and undesired assumption that certain topological information about the network is known to the nodes , or cannot achieve all the properties described in the above . In the paper , we propose an anonymous routing protocol with multiple routes called ARMR, which can satisfy all the required properties. In addition, the protocal has the flexibility of creating fake routes to confuse the adversaries , thus increasing the level of anonmity. In the terms of communication efficiency , extensive simultion is carried out. Compared with AODV and MASK , our ARMR protocol gives a higer route request success rate under all situations and delay of our protocol is comparable to the best of these two protocols.
Multivariate Shape Modeling and Its Application to Characterizing Abnormal Amygdala Shape in Autism

Although there are many imaging studies on traditional ROI-based amygdala volumetry, there are very few studies on modeling amygdala shape variations. This paper present a first unified computational and statistical framework for modeling amygdala shape variations in a clinical population. The recently developed weighted spherical harmonic representation is used as to parameterize, to smooth out, and to normalize amygdala surfaces. The representation is subsequently used as an input for multivariate linear models accounting for age and brain size difference using SurfStat package that completely avoids the complexity of specifying design matrices. The methodology has been applied to detect abnormal local shape variations in 22 high functioning autistic subjects. We have localized significant shape difference in autism in the right amygdala. Further we have detected significant difference in interaction of shape and gaze fixation duration indicating localized abnormal association ∗Corresponding address: Moo K. Chung, Waisman Center #437, 1500 Highland Ave. Madison, WI. 53705. telephone: 608-217-2452, email://mkhung@wisc.edu, http://www.stat.wisc.edu/∼mchung of function and structure in autism.
The Effects of Relative Importance of User Constraints in Cloud of Things Resource Discovery: A Case Study

Over the last few years, the number of smart objects connected to the Internet has grown exponentially in comparison to the number of services and applications. The integration between Cloud Computing and Internet of Things, named as Cloud of Things, plays a key role in managing the connected things, their data and services. One of the main challenges in Cloud of Things is the resource discovery of the smart objects and their reuse in different contexts. Most of the existent work uses some kind of multi-criteria decision analysis algorithm to perform the resource discovery, but do not evaluate the impact that the user constraints has in the final solution. In this paper, we analyse the behaviour of the SAW, TOPSIS and VIKOR multi-objective decision analyses algorithms and the impact of user constraints on them. We evaluated the quality of the proposed solutions using the Pareto-optimality concept.
Getting newcomers engaged: the role of socialization tactics

Purpose – The purpose of this study is to examine the relationship between socialization tactics and newcomer engagement and the mediating role of person‐job (PJ) and person‐organization (PO) fit perceptions, emotions, and self‐efficacy.Design/methodology/approach – A survey was completed by 140 co‐op university students at the end of their work term.Findings – Institutionalized socialization tactics were positively related to PJ and PO fit perceptions, emotions and self‐efficacy, but not newcomer engagement. Socialization tactics were indirectly related to newcomer engagement through PJ fit perceptions, emotions, and self‐efficacy.Research limitations/implications – Socialization tactics might be too broad and general to predict newcomer engagement. Future research should measure more specific socialization practices and job resources.Practical implications – Organizations that want to engage new hires should use social socialization tactics to create positive emotions, develop higher PJ fit perceptions,.
BindingDB in 2015: A public database for medicinal chemistry, computational chemistry and systems pharmacology

BindingDB, www.bindingdb. org, is a publicly accessible database of experimental protein-small molecule interaction data. Its collection of over a million data entries derives primarily from scientific articles and, increasingly, US patents. BindingDB provides many ways to browse and search for data of interest, including an advanced search tool, which can cross searches of multiple query types, including text, chemical structure, protein sequence and numerical affinities. The PDB and PubMed provide links to data in BindingDB, and vice versa; and BindingDB provides links to pathway information, the ZINC catalog of available compounds, and other resources. The BindingDB website offers specialized tools that take advantage of its large data collection, including ones to generate hypotheses for the protein targets bound by a bioactive compound, and for the compounds bound by a new protein of known sequence; and virtual compound screening by maximal chemical similarity, binary kernel discrimination, and support vector machine methods. Specialized data sets are also available, such as binding data for hundreds of congeneric series of ligands, drawn from BindingDB and organized for use in validating drug design methods. BindingDB offers several forms of programmatic access, and comes with extensive background material and documentation. Here, we provide the first update of BindingDB since 2007, focusing on new and unique features and highlighting directions of importance to the field as a whole.
Towards a hybrid row-column database for a cloud-based medical data management system

Medical data management becomes a real exigency. The emergence of new medical imaging techniques and the necessity to access medical information at any time have led to an inevitable need to find new advanced solutions for managing these critical data. Actual local archiving systems are very expensive and cannot support this heterogeneous and enormous data size. Cloud computing has attracted significant attention due to its major characteristics of elasticity, availability and pay-per-use. A good exploitation of this infrastructure constitutes an effective and promising solution for managing medical data and images. In this position paper, we highlight the challenges in integrating highly heterogeneous data such as DICOM files in the clouds. We then propose a novel hybrid row-column, two-level database architecture for the storage of heterogeneous data over the cloud.
An Attention-Driven Model for Grouping Similar Images with Image Retrieval Applications

Recent work in the computational modeling of visual attention has demonstrated that a purely bottom-up approach to identifying salient regions within an image can be successfully applied to diverse and practical problems from target recognition to the placement of advertisement. This paper proposes an application of a combination of computational models of visual attention to the image retrieval problem. We demonstrate that certain shortcomings of existing content-based image retrieval solutions can be addressed by implementing a biologically motivated, unsupervised way of grouping together images whose salient regions of interest (ROIs) are perceptually similar regardless of the visual contents of other (less relevant) parts of the image. We propose a model in which only the salient regions of an image are encoded as ROIs whose features are then compared against previously seen ROIs and assigned cluster membership accordingly. Experimental results show that the proposed approach works well for several combinations of feature extraction techniques and clustering algorithms, suggesting a promising avenue for future improvements, such as the addition of a top-down component and the inclusion of a relevance feedback mechanism.
AI-Based Feature Extraction and Cosine Similarity for Automation of Student Learning Assessment

This research is ongoing research into the student learning process which aims to develop artificial intelligence-based technology to calculate essay exam scores automatically, based on the textual proximity of students' answers to the answer key. This research uses an approach based on natural language processing (NLP) and text analysis. Feature extraction was carried out using the BERT model and similarity comparison using the Cosine distance method. Model evaluation was carried out using sensitivity and specificity tests. The model evaluation results show a sensitivity of 98.21%, which means this assessment model is able to detect positive cases well.
An integrated approach for production scheduling and maintenance of multi-component system

In this paper, an integrated approach for production scheduling and maintenance is proposed for a multi-component system. The model in this paper is based on the selective maintenance policy. The objective is to obtain a minimum cost solution with availability, allowable maintenance time as constraints. The optimization procedure using the proposed integrated approach results into maintenance decision in terms of maintenance actions namely, repair, replace or do-nothing for the system components along with the optimal production schedule on the machines. A simulated annealing algorithm is used for getting the near optimal solution. A numerical example is presented to demonstrate the application of the integrated approach.
Moving Home: Theorizing Housing Within a Politics of Mobility

Abstract It has been argued that the social sciences have undergone a “mobility turn” over the last decade: a paradigm shift in which movement is seen to have become increasingly important to our social worlds. For the most part, housing studies is yet to extensively engage with this “paradigm shift”. In an attempt to engage with the ideas that the “mobility turn” has thrown up for housing studies this paper grapples with two key questions. First, where does housing studies fit in the new mobilities paradigm in the social sciences? And, second, how can housing studies contribute to this paradigm shift? This paper does this through an examination of how a politics of mobility can be usefully employed and extended by housing researchers. Looking specifically at two current dimensions of this politics: mobility as a right, and mobility as a resource, this paper argues that a third dimension – mobility as governmentality – should be introduced to the mobility turn’s politics of mobility.
Globally coupled collision handling using volume preserving impulses

We present a novel algorithm for collision processing on triangulated meshes. Our method robustly maintains a collision free state on complex geometries while resorting to collision resolution at time intervals often comparable to the frame rate. Our approach is motivated by the behavior of a thin layer of fluid inserted in the empty space between nearly-colliding parts of the simulated surface, acting as a cushioning mechanism. Point-triangle or edge-edge pairs on a collision course are naturally resolved by the incompressible response of this fluid buffer. This response is formulated into a globally coupled nonlinear system which we solve using Newton iteration and symmetric, positive definite solvers. The globally coupled treatment of collisions allows us to resolve up to two orders of magnitude more collisions than traditional greedy algorithms (e.g. Gauss-Seidel collision response) and take substantially larger time steps without compromising the visual quality of the simulation.
Direction Choice for Accelerated Convergence in Hit-and-Run Sampling

Hit-and-Run algorithms are Monte Carlo procedures for generating points that are asymptotically distributed according to general absolutely continuous target distributions G over open bounded regions S. Applications include nonredundant constraint identification, global optimization, and Monte Carlo integration. These algorithms are reversible random walks that commonly incorporate uniformly distributed step directions. We investigate nonuniform direction choice and show that, under regularity conditions on the region S and target distribution G, there exists a unique direction choice distribution, characterized by necessary and sufficient conditions depending on S and G, which optimizes the Doob bound on rate of convergence. We include computational results demonstrating greatly accelerated convergence for this optimizing direction choice as well as for more easily implemented adaptive heuristic rules.
Psychosomatic Non-Articular Rheumatism

It seems now to be fairly widely agreed that emotional factors are relevant to the study of rheumatism, and particularly of non-articular rheumatism or fibrositis. The Horder Report (1941) stated that " Worry, anxiety, mental shock, can be often recognized as promotive of rheumatic disease ". The relationship is perhaps more often expressed as a matter of differential diagnosis between muscular pains of psychoneurotic origin and what is described as " true rheumatism ". But quite apart from psychological considerations, there is much controversy as to what constitutes " true " non-articular rheumatism.
Modeling of Mitochondria Bioenergetics Using a Composable Chemiosmotic Energy Transduction Rate Law: Theory and Experimental Validation

Mitochondrial bioenergetic processes are central to the production of cellular energy, and a decrease in the expression or activity of enzyme complexes responsible for these processes can result in energetic deficit that correlates with many metabolic diseases and aging. Unfortunately, existing computational models of mitochondrial bioenergetics either lack relevant kinetic descriptions of the enzyme complexes, or incorporate mechanisms too specific to a particular mitochondrial system and are thus incapable of capturing the heterogeneity associated with these complexes across different systems and system states. Here we introduce a new composable rate equation, the chemiosmotic rate law, that expresses the flux of a prototypical energy transduction complex as a function of: the saturation kinetics of the electron donor and acceptor substrates; the redox transfer potential between the complex and the substrates; and the steady-state thermodynamic force-to-flux relationship of the overall electro-chemical reaction. Modeling of bioenergetics with this rate law has several advantages: (1) it minimizes the use of arbitrary free parameters while featuring biochemically relevant parameters that can be obtained through progress curves of common enzyme kinetics protocols; (2) it is modular and can adapt to various enzyme complex arrangements for both in vivo and in vitro systems via transformation of its rate and equilibrium constants; (3) it provides a clear association between the sensitivity of the parameters of the individual complexes and the sensitivity of the system's steady-state. To validate our approach, we conduct in vitro measurements of ETC complex I, III, and IV activities using rat heart homogenates, and construct an estimation procedure for the parameter values directly from these measurements. In addition, we show the theoretical connections of our approach to the existing models, and compare the predictive accuracy of the rate law with our experimentally fitted parameters to those of existing models. Finally, we present a complete perturbation study of these parameters to reveal how they can significantly and differentially influence global flux and operational thresholds, suggesting that this modeling approach could help enable the comparative analysis of mitochondria from different systems and pathological states. The procedures and results are available in Mathematica notebooks at http://www.igb. uci.edu/tools/sb/mitochondria-modeling.html.
Low-cost sequential ATPG with clock-control DFT

We present a new clock-control DFT technique for sequential circuits, based on clock partitioning and selective clock freezing, and we use it to break the global feedback loops and to generate clock waves to test the resulting sequential circuit with self-loops. Clock waves allow us to significantly reduce the complexity of sequential ATPG. Unlike scan, our non-intrusive DFT technique does not introduce any delay penalty; the generated tests may be applied at speed, have shorter application time, and dissipate less power.
Prospect Theory In The Wild: Evidence From The Field

The workhorses of economic analysis are simple formal models that can explain naturally occurring phenomena. Reflecting this taste, economists often say they will incorporate more psychological ideas into economics if those ideas can parsimoniously account for field data better than standard theories do. Taking this statement seriously, this article describes 10 regularities in naturally occurring data that are anomalies for expected utility theory but can all be explained by three simple elements of prospect theory: loss aversion, reflection effects, and nonlinear weighting of probability; moreover, the assumption is made that people isolate decisions (or edit them) from others they might be grouped with (Read, Loewenstein, and Rabin 1999; cf. Thaler, 1999). I hope to show how much success has already been had applying prospect theory to field data and to inspire economists and psychologists to spend more time in the wild.
Online In-Situ Interleaved Evaluation of Real-Time Push Notification Systems

Real-time push notification systems monitor continuous document streams such as social media posts and alert users to relevant content directly on their mobile devices. We describe a user study of such systems in the context of the TREC 2016 Real-Time Summarization Track, where system updates are immediately delivered as push notifications to the mobile devices of a cohort of users. Our study represents, to our knowledge, the first deployment of an interleaved evaluation framework for prospective information needs, and also provides an opportunity to examine user behavior in a realistic setting. Results of our online in-situ evaluation are correlated against the results a more traditional post-hoc batch evaluation. We observe substantial correlations between many online and batch evaluation metrics, especially for those that share the same basic design (e.g., are utility-based). For some metrics, we observe little correlation, but are able to identify the volume of messages that a system pushes as one major source of differences.
An international comparison of pre-service teacher attitudes towards inclusive education

education of pre-service teachers in teacher training institutions in four different countries: Australia, Canada, Hong Kong, and Singapore. Using the Attitudes Towards Inclusive Education Scale (Wilczenski, 1995) and a series of demographic variables, this study concludes that pre-service teachers' attitudes towards inclusive education differ between countries across three factors which have been labeled academic and physical, social, and behavioral. Pre-service teachers in this sample are most positive about including students with social concerns. An examination of the items in this factor revealed that these issues, such as shyness, would rarely require immediate intervention and large amounts of extra time and effort on the part of the teacher in the same way that the behavior factor would, which rated low in terms of positive attitudes internationally. Demographic variables which can be emphasized by teacher training institutions such as close contact with a person with a disability, training, teaching experience, knowledge of policy and law, and confidence levels, all had a significant impact on attitudes. This paper argues that teacher training institutions should consider for inclusion in their programs practical experiences with inclusive education in positive and supportive environments, opportunities for students to experience success and reflection, and academic content regarding knowledge of policy and law relating to inclusive education.
A Novel Multiple Relay Selection Strategy for LTE-Advanced Relay Systems

This paper considers a multiple decode-and-forward relay assisted network in the Long Term Evolution- Advanced (LTE-A) system. Multiple relay nodes (RNs) joint transmission is applied to enhance the fairness of capacity for edge user (UE). But a number of RNs activated in the same time-frequency block group (TFBG) will let inter-cell interference (ICI) be stronger, and will reduce the system average capacity. In order to reconcile this contradiction between average capacity and fairness, this paper proposes an utility function (UF) which takes "RN-UE's demand" and "RNs' efficiency" into account. Besides, a low complexity greedy multi-RN selection (GMRS) scheme based on the UF (GMRS-UF) also be proposed. The simulation results show that GMRS has low complexity but outstanding performance. Compared with previous RN selection strategy, GMRS-UF could reduce ICI by discarding inefficient RNs, thereby promoting the average system throughput. And GMRS-UF can achieve any compromise between average capacity and fairness.