Miracle-dz/UniFAR-FTUs huggingface dataset:
Methodology and Framework to Construct and Integrate Digital Habitat Ecosystem Architecture

The Digital Ecosystem (DE) concept is a new emerging paradigm based on self-organizing Information and Communication Technology (ICT) nodes and links. A DE comprises digital devices also referred to as the Interdependent Digital Species (IDS). We extend the DE idea to that of a Digital Habitat Ecosystem Architecture (DHEA) where a DHEA is a DE used in built up environments. Although the DE concept was introduced some years ago for business enterprises, it does not have a formal development methodology. In this paper, we propose a methodology and a framework to create DHEA’s. The methodology will discuss the knowledge of sharing, integration and collaboration of existing digital devices which can be incorporated in one dynamic system. Furthermore, it will give the brief idea to develop a framework for the development of the DHEA. This methodology and framework proposes a pathway to develop a dynamic model that can monitor and control existing wireless devices available in the home environment, instead of using separate static devices. The dynamic model is to incorporate all the basic and advanced requirements. Additionally, this dynamic DHEA will identify the shortcomings of data communication and networking challenges in Digital Species (DS) and propose solutions to overcome those issues.
Reachability analysis of hybrid systems using bisimulations

A unified approach to decidability questions for the verification of hybrid systems is obtained by the construction of a bisimulation. These are finite state quotients whose reachability properties are equivalent to those of the original infinite state system. This approach has had some success in the reachability analysis of timed automata and linear hybrid automata. We use results from stratification theory, subanalytic sets and model theory of fields in order to extend earlier results on the existence of bisimulations for certain classes of analytic vector fields.
Systematic Prediction of Scaffold Proteins Reveals New Design Principles in Scaffold-Mediated Signal Transduction

Scaffold proteins play a crucial role in facilitating signal transduction in eukaryotes by bringing together multiple signaling components. In this study, we performed a systematic analysis of scaffold proteins in signal transduction by integrating protein-protein interaction and kinase-substrate relationship networks. We predicted 212 scaffold proteins that are involved in 605 distinct signaling pathways. The computational prediction was validated using a protein microarray-based approach. The predicted scaffold proteins showed several interesting characteristics, as we expected from the functionality of scaffold proteins. We found that the scaffold proteins are likely to interact with each other, which is consistent with previous finding that scaffold proteins tend to form homodimers and heterodimers. Interestingly, a single scaffold protein can be involved in multiple signaling pathways by interacting with other scaffold protein partners. Furthermore, we propose two possible regulatory mechanisms by which the activity of scaffold proteins is coordinated with their associated pathways through phosphorylation process.
Bias between MNI and Talairach coordinates analyzed using the ICBM‐152 brain template

MNI coordinates determined using SPM2 and FSL/FLIRT with the ICBM‐152 template were compared to Talairach coordinates determined using a landmark‐based Talairach registration method (TAL). Analysis revealed a clear‐cut bias in reference frames (origin, orientation) and scaling (brain size). Accordingly, ICBM‐152 fitted brains were consistently larger, oriented more nose down, and translated slightly down relative to TAL fitted brains. Whole brain analysis of MNI/Talairach coordinate disparity revealed an ellipsoidal pattern with disparity ranging from zero at a point deep within the left hemisphere to greater than 1‐cm for some anterior brain areas. MNI/Talairach coordinate disparity was generally less for brains fitted using FSL. The mni2tal transform generally reduced MNI/Talairach coordinate disparity for inferior brain areas but increased disparity for anterior, posterior, and superior areas. Coordinate disparity patterns differed for brain templates (MNI‐305, ICBM‐152) using the same fitting method (FSL/FLIRT) and for different fitting methods (SPM2, FSL/FLIRT) using the same template (ICBM‐152). An MNI‐to‐Talairach (MTT) transform to correct for bias between MNI and Talairach coordinates was formulated using a best‐fit analysis in one hundred high‐resolution 3‐D MR brain images. MTT transforms optimized for SPM2 and FSL were shown to reduced group mean MNI/Talairach coordinate disparity from a 5‐13 mm to 1‐2 mm for both deep and superficial brain sites. MTT transforms provide a validated means to convert MNI coordinates to Talairach compatible coordinates for studies using either SPM2 or FSL/FLIRT with the ICBM‐152 template. Hum Brain Mapp 2007. © 2007 Wiley‐Liss, Inc.
A Simple Model of the Nominal Term Structure of Interest Rates

This paper presents a simple two-factor model of nominal term structure of interest rates, in which the log-price kernel has an autoregressive drift process and a nonlinear GARCH volatility process. With these two state-variable processes, closed-form solutions are derived for zero-coupon bond prices as well as yield to maturity for a given time to maturity.
Understanding Human Teaching Modalities in Reinforcement Learning Environments: A Preliminary Report

While traditional agent-based learning techniques have enjoyed considerable success, in recent years there has been a growing interest in improving such learning by leveraging humans as teachers. These human-in-the-loop methods have demonstrated substantial improvements by using human subjects in a variety of interaction modalities. Unfortunately, there are few, if any, guidelines about when one teaching modality is more appropriate than another. In addition to highlighting this important gap in the current literature, this paper presents a pilot study that compares two specific teaching modalities: learning by feedback and learning by demonstration, and proposes a set of hypotheses about their relative performance.
From polymers to proteins -- novel phases of short compact tubes

A framework is presented for understanding the common character of proteins. Proteins are linear chain molecules – however, the simple model of a polymer viewed as spheres tethered together does not account for many of the observed characteristics of protein structures. We show here that the notion of a tube of non-zero thickness allows one to bridge the conventional compact polymer phase with a novel phase employed by Nature to house biomolecular structures. We build on the idea that a non-singular continuum description of a tube (or a sheet) of arbitrary thickness entails discarding pairwise interactions and using appropriately chosen many body interactions. We suggest that the structures of folded proteins are selected based on geometrical considerations and are poised at the edge of compaction, thus accounting for their versatility and flexibility. We present an explanation for why helices and sheets are the building blocks of protein structures.
Multiwavelength optical networks with limited wavelength conversion

This paper proposes optical wavelength division multiplexed (WDM) networks with limited wavelength conversion that can efficiently support lightpaths (connections) between nodes. Each lightpath follows a route in the network and must be assigned a channel along each link in its route. The load /spl lambda//sub max/ of a set of lightpath requests is the maximum over all links of the number of lightpaths that use the link. At least /spl lambda//sub max/ wavelengths will be needed to assign channels to the lightpaths. If the network has full wavelength conversion capabilities then /spl lambda//sub max/ wavelengths are sufficient to perform the channel assignment. We propose ring networks with a fixed wavelength conversion capability within the nodes that can support all lightpath request sets with load /spl lambda//sub max/ at most W-1, where W is the number of wavelengths in each link. We also propose ring networks with selective pairwise wavelength conversion capability within the nodes that can support all lightpath request sets with load /spl lambda//sub max/ at most W. We also propose a star network with fixed wavelength conversion capability at its hub node that can support all lightpath request sets with load /spl lambda//sub max/ at most W. We extend this result to tree networks and networks with arbitrary topologies. These results show that significant improvements in traffic-carrying capacity can be obtained in WDM network by providing a very limited wavelength conversion capability within the network.
Artificial Neural Network for Mobile IDS Solution

The aim of this paper is to suggest an Artificial Neural Network architecture for decision making within intrusion detection systems. Taking as starting point the IMA_IDS solution [57] that presents a global agent architecture for enhanced intrusion network based solution, we suggest the use of ANN as a major decision algorithm to be included into the detection agents. Our goal is in fact to increase efficency by reducing the fault positive and increasing the detection capabilities with partial available information on network status.
Segmentation of salivary gland tumors in ultrasonic images based on anisotropic diffusion and random walk

Aimed at the difficult segmentation of ultrasonic tumor image with strong speckle noise, low contrast and weak boundaries, a novel method for segmentation of ultrasonic image is proposed. In order to suppress speckle noise and enhance the edge details, the anisotropic diffusion algorithm combined with the Laplacian operator is introduced into ultrasound images, of which the operator is able to discriminate the gray changes caused by noise or the edge. Then the random walk model in graph theory is employed to achieve an effective segmentation. Lots of clinical ultrasound images of salivary gland tumor are tested and the experiment results demonstrate that the proposed method possesses the nice properties of anisotropic diffusion algorithm and random walk algorithm, overcoming prone over-segmentation or under-segmentation in traditional random walk. In addition, the method bears a high calculating speed and segments tumor accurately and effectively.
Aging face verification in score-age space using single reference image template

The influence of age progression on the performance of face verification systems is a challenging and largely open research problem. When only one reference and one test image per subject are available, in this paper we propose to manage the aging influence on the adult face verification system through a score-age stacking technique to find the global decision boundary which can change across the age progression. This allows for improved long-term class separation by introducing a parameterized decision boundary in the scores-age space using a biométrie template created by a single reference image. This new method, based on the concept of classifier stacking and age-dependent decision boundary, compares favorably with the conventional face verification approach, which uses age-independent decision threshold. Our experiments on the MORPH database show that the use of the proposed scheme allows for improving the verification performance of baseline system.
Makespan-Optimal Cache Partitioning

In current multicore systems, cache memory is shared between multiple concurrent threads. Allocating the proper amount of cache to each thread is crucial to achieving high performance. Cache management in many existing systems is based on the least recently used replacement policy, which can lead to adverse contention between threads for shared cache space. Cache partitioning is a technique that reserves a certain amount of cache for each thread, and has been shown to work well in practice. We introduce the problem of determining the optimal cache partitioning to minimize the make span for completing a set of tasks. We analyze the problem using a model that generalizes a widely used empirical model for cache miss rates. Our first contribution is to give a mathematical characterization of the properties satisfied by an optimal partitioning. Second, we present an algorithm that finds a 1 +\epsilon approximation to the optimal partitioning in O(n log \frac{n}{\epsilon}log\frac{n}{\epsilon p}) time, where n is the number of tasks and p is a value that depends on the optimal solution. We compare our algorithm with several partitioning schemes used in practice or proposed in the literature. Simulations show that our algorithm achieves between 22-59% better make span compared to these algorithms.
OpenFire : Opening Networks to Reduce Network Attacks on Legitimate Services

Remote network attacks are a serious problem facing network administrators in universities, corporations, and governments today. Hackers, worms, and spammers will exploit and control hosts inside of a network to send junk E-mail, create bot nets, launch DDoS attacks, and steal sensitive information. Current solutions exist that attempt to deal with these threats, but they are often unsuccessful. In addition, security researchers have deployed honeypots to lure attackers and learn more about their techniques, but honeypots have had only limited success at gaining information and protecting other machines. In response to need for better security against network attacks, we present OpenFire. OpenFire is protection system that takes the opposite approach of traditional firewalls: instead of blocking unwanted traffic, it instead accepts all traffic, forwarding unwanted messages to a cluster of decoy machines. To the outside, all ports and all IP addresses appear open in an OpenFire network. To evaluate OpenFire, we deployed it in a live sub-network here at the University of Michigan. During a three-week evaluation period, we found that OpenFire reduced the number of attacks on legitimate computers by 57%, while honeypots only reduced attacks by 8%. OpenFire decoys also had considerably better exposure than honeypots, and were able to elicit over three times as many attacks during the evaluation period.
Superposition Coding Based Wireless Network Coding Scheme for Two-Way Cooperative Relaying

Recent advances in cooperative communication and wireless Network Coding (NC) may lead to huge performance gains in relay systems. In this context, we focus on the two-way relay scenario, where two nodes exchange information via a common relay. We design a practical Superposition Coding (SC) based NC scheme for Decode-and-Forward (DF) half-duplex relaying, where the goal is to increase the achievable rate. By taking advantage of the direct link and by providing a suboptimal yet efficient power division among the superposed layers, our proposed SC two-way relaying scheme outperforms the reference schemes, including the well-known 3-step DF-NC scheme and the capacity of 2-step schemes for a large set of SNRs, while approaching closely the performance bound.
Monte-Carlo-based channel characterization for underwater optical communication systems

We consider channel characterization for underwater wireless optical communication (UWOC) systems. We focus on the channel impulse response and, in particular, quantify the channel time dispersion for different water types, link distances, and transmitter/receiver characteristics, taking into account realistic parameters. We use the Monte Carlo approach to simulate the trajectories of emitted photons propagating in water from the transmitter towards the receiver. During their propagation, photons are absorbed or scattered as a result of their interaction with different particles present in water. To model angle scattering, we use the two-term Henyey-Greenstein model in our channel simulator. We show that this model is more accurate than the commonly used Henyey-Greenstein model, especially in pure sea waters. Through the numerical results that we present, we show that, except for highly turbid waters, the channel time dispersion can be neglected when working over moderate distances. In other words, under such conditions, we do not suffer from any inter-symbol interference in the received signal. Lastly, we study the performance of a typical UWOC system in terms of bit-error-rate using the simple on-off-keying modulation. The presented results give insight into the design of UWOC systems.
DaVIE: Database for the Visualization and Integration of Epigenetic data

One of the challenges in the analysis of large data sets, particularly in a population-based setting, is the ability to perform comparisons across projects. This has to be done in such a way that the integrity of each individual project is maintained, while ensuring that the data are comparable across projects. These issues are beginning to be observed in human DNA methylation studies, as the Illumina 450k platform and next generation sequencing-based assays grow in popularity and decrease in price. This increase in productivity is enabling new insights into epigenetics, but also requires the development of pipelines and software capable of handling the large volumes of data. The specific problems inherent in creating a platform for the storage, comparison, integration, and visualization of DNA methylation data include data storage, algorithm efficiency and ability to interpret the results to derive biological meaning from them. Databases provide a ready-made solution to these issues, but as yet no tools exist that that leverage these advantages while providing an intuitive user interface for interpreting results in a genomic context. We have addressed this void by integrating a database to store DNA methylation data with a web interface to query and visualize the database and a set of libraries for more complex analysis. The resulting platform is called DaVIE: Database for the Visualization and Integration of Epigenetics data. DaVIE can use data culled from a variety of sources, and the web interface includes the ability to group samples by sub-type, compare multiple projects and visualize genomic features in relation to sites of interest. We have used DaVIE to identify patterns of DNA methylation in specific projects and across different projects, identify outlier samples, and cross-check differentially methylated CpG sites identified in specific projects across large numbers of samples. A demonstration server has been setup using GEO data at http://echelon.cmmt. ubc.ca/dbaccess/, with login “guest” and password “guest. ” Groups may download and install their own version of the server following the instructions on the project's wiki.
Mentor teachers’ views of their mentees

Abstract Successful mentoring relationships are essential for novice teachers entering the teaching profession. The success of the mentoring process depends in large part on the diagnostic abilities of the mentor, but there is little research on how mentor teachers view their mentees. In this small-scale study, we explored how 11 mentor teachers describe similarities and differences between their mentee teachers. We found that mentor teachers’ descriptions predominantly relate to differences in personal engagement with pupils, identifying as a teacher, perfectionism and self-confidence. Mentors tended to describe these differences in terms of traits and dispositions. We provide suggestions for addressing this issue in mentor preparation and for using findings in mentor training, and we provide a conceptual framework for future studies of mentor teachers’ views of their mentees.
Supporting electronic group processes: a social perspective

In recent years, computer mediated communications technologies have presented themselves as a means of supporting group processes. The socialprocesses that take place on electronically supported group meetings are seen to influence the ways in which the technology is appropriated. The focus of this paper is on investigating group processes that take place electronically amongst a group of geographically dispersed individuals. Group processes are explored using an interpretivist strategy that draws upon concepts from Conclusions are drawn as processes may be supported. social network analysis. to how electronic group
FOSTERING PRODUCTIVE DISCIPLINARY ENGAGEMENT IN AN EVOLUTIONARY BIOLOGY CLASSROOM

Instructional designers frequently claim that they want to introduce authentic disciplinary practices in classrooms. Nevertheless, we still need a clear set of guidelines for evaluating the impact of those activities on teachers’ instruction and on students’ understanding of the disciplines they are studying. The aim of this paper is to outline a framework for assessing teacher guidance and student engagement over time in a science classroom that was derived from a review of the science studies literature (Ford & Forman, in press). Our framework identified three key, interrelated components of scientific practice that validate its authority: science as social; science as material; and science as rhetorical. In this paper, I will illustrate our framework using examples from a 9-week high school course in evolutionary biology.
Famous People Knowledge and the Right and Left Temporal Lobes

It is generally accepted that the anterior temporal lobes support knowledge of famous people. The specific roles of the right and left temporal lobe remain a subject of debate, with some studies suggesting differential roles based on modality (visual versus verbal information) and others category (person knowledge versus general semantics). The present study re-examined performance of semantic dementia patients with predominantly right and predominantly left temporal lobe atrophy on famous face, famous name and general semantic tasks, with the specific aim of testing the hypothesis that the right temporal lobe has a privileged role for person knowledge and the left temporal lobe for general semantic knowledge. Comparisons of performance rankings across tasks showed no evidence to support this hypothesis. By contrast, there was robust evidence from naming, identification and familiarity measures for modality effects: right-sided atrophy being associated with relatively greater impairment for faces and visual tasks and left-sided atrophy for names and verbal tasks. A double dissociation in test scores in two patients reinforced these findings. The data present a challenge for the influential ‘semantic hub’ model, which views the anterior temporal lobes as an area of convergence in which semantic information is represented in amodal form.
Alternative representation of N × N density matrix

We use polarization operators known from quantum theory of angular momentum to expand the N ×N dimensional density operators. Thereby, we construct generalized Bloch vectors representing density matrices. We study their properties and derive positivity conditions for any N. We also apply the procedure to study Bloch vector space for a qubit and a qutrit.
An Optimized Wireless Sensor Network Used in Video Surveillance System

This paper presents a new optimized method for wireless sensor network, which can be used in video surveillance systems. The new algorithm involves two steps. In the first step, the system integrates the time filtration and proportion of reliability weight, in order to intelligently merge and reinforce the results of kinds of sensors. In the second step, it uses compressive sensing to confirm the alarm sensors. By these processes, the accuracy of target detection can be increased effectively, and the video surveillance system can only be switched on a region where some targets are detected. Therefore, it can save system resources, and enhance overall efficiency.