Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving PCM Endurance with Randomized Address Remapping in Hybrid Memory System

Phase-Change-Memory (PCM) has emerged as a promising alternative of DRAM main memory. A new hybrid memory architecture, where DRAM serves as cache of PCM main memory, has been proposed to leverage PCM's high scalability and DRAM's fast access time. One biggest issue of PCM is the limited number of writes to storage cells. We argue that good cache mechanism will decrease PCM writes dramatically in hybrid memory system. In this paper, we demonstrate that traditional set associative cache is susceptible to malicious attacks, which lead certain PCM cells to wear-out by constant cache flushes. A novel approach called Randomized Address Remapping (RAR) is proposed to hide the mapping details between DRAM and PCM. With this approach, the attacks based on set associative cache do not work, while the efficiency of caching still remains. We present Static Randomized Address Remapping (SRAR) and Dynamic Randomized Address Remapping (DRAR) in this paper. SRAR invalidates set associative cache based attacks by distributing their address accesses to different sets. DRAR uses a region-based approach to change the mapping dynamically, in case that the static mapping relationship is discovered by attacker compromising operating system. Experimental results show that RAR approaches can prevent malicious attacks and improve PCM endurance greatly.
How transcription proceeds in a large artificial heterochromatin in human cells

Heterochromatin is critical for genome integrity, and recent studies have suggested the importance of transcription in heterochromatin for maintaining its silent state. We previously developed a method to generate a large homogeneously staining region (HSR) composed of tandem plasmid sequences in human cells that showed typical heterochromatin characteristics. In this study, we examined transcription in the HSR. We found that transcription of genes downstream to no-inducible SRα promoter was restricted to a few specific points inside the large HSR domain. Furthermore, the HSR localized to either to the surface or to the interior of the nucleolus, where it was more actively transcribed. The perinucleolar or intranucleolar locations were biased to late or early S-phase, and the location depended on either RNA polymerase II/III or I transcription, respectively. Strong activation of the inducible TRE promoter resulted in the reversible loosening of the HSR domain and the appearance of transcripts downstream of not only the TRE promoters, but also the SRα promoters. During this process, detection of HP1α or H3K9Me3 suggested that transcription was activated at many specific points dispersed inside large heterochromatin. The transcriptional rules obtained from studying artificial heterochromatin should be useful for understanding natural heterochromatin.
AggreSet: Rich and Scalable Set Exploration using Visualizations of Element Aggregations

Datasets commonly include multi-value (set-typed) attributes that describe set memberships over elements, such as genres per movie or courses taken per student. Set-typed attributes describe rich relations across elements, sets, and the set intersections. Increasing the number of sets results in a combinatorial growth of relations and creates scalability challenges. Exploratory tasks (e.g. selection, comparison) have commonly been designed in separation for set-typed attributes, which reduces interface consistency. To improve on scalability and to support rich, contextual exploration of set-typed data, we present AggreSet. AggreSet creates aggregations for each data dimension: sets, set-degrees, set-pair intersections, and other attributes. It visualizes the element count per aggregate using a matrix plot for set-pair intersections, and histograms for set lists, set-degrees and other attributes. Its non-overlapping visual design is scalable to numerous and large sets. AggreSet supports selection, filtering, and comparison as core exploratory tasks. It allows analysis of set relations inluding subsets, disjoint sets and set intersection strength, and also features perceptual set ordering for detecting patterns in set matrices. Its interaction is designed for rich and rapid data exploration. We demonstrate results on a wide range of datasets from different domains with varying characteristics, and report on expert reviews and a case study using student enrollment and degree data with assistant deans at a major public university.
Impact-induced fracture mechanisms of immiscible PC/ABS (50/50) blends

This paper presents a study on fracture mechanisms of polycarbonate (PC)/acrylonitrile-butadiene-styrene (ABS) (50/50) blends with different ABS types under a drop weight impact test (DWIT) using a circular sheet specimen. Formation of secondary crack indicated by a stress-whitening layer on the mid-plane of scattered specimens and secondary surface of fracture perpendicular to primary fracture surface were captured under scanning electron microscope (SEM). Although the both blends finally failed in brittle modes, SEM observation showed that their secondary fracture mechanisms were completely different. Observation through the thickness of the etched PC/ABS specimen samples using SEM also clearly showed that PC and ABS were immiscible. The immiscibility between PC and ABS was indicated by presence of their layer structures through the thickness of the blends. It was revealed that layer of ABS structure was influenced by size of rubber particle and this latter parameter then affected microstructure and fracture mechanisms of the blends. Impact-induced fracture mechanisms of the blends due to such microstructures are discussed in this paper. It was also pointed out that the secondary cracking was likely caused by interface delamination between PC and ABS layers in the core due to transverse shear stress generated during the impact test.
A threshold voltage independent floating resistor circuit exhibiting both positive and negative resistance values

In this paper, we propose new bilateral floating resistor circuits having both positive and negative resistance values. The equivalent resistance of this floating resistor in CMOS technology can be changed by using controlled-voltages, which is an advantage over polysilicon or diffused resistor in the integrated circuit. Moreover the characteristics of the proposed circuits are independent of the threshold voltage. We have simulated the proposed circuit by using HSPICE. Finally, we have confirmed that the proposed circuit is useful as an analog component.
An immunological model of distributed detection and its application to computer security

This dissertation explores an immunological model of distributed detection, called negative detection, and studies its performance in the domain of intrusion detection on computer networks. The goal of the detection system is to distinguish between illegitimate behaviour (nonself ), and legitimate behaviour (self ). The detection system consists of sets of negative detectors that detect instances of nonself; these detectors are distributed across multiple locations. The negative detection model was developed previously; this research extends that previous work in several ways. Firstly, analyses are derived for the negative detectionmodel. In particular, a framework for explicitly incorporating distribution is developed, and is used to demonstrate that negative detection is both scalable and robust. Furthermore, it is shown that any scalable distributed detection system that requires communication (memory sharing) is always less robust than a system that does not require communication (such as negative detection). In addition to exploring the framework, algorithms are developed for determining whether a nonself instance is an undetectable hole, and for predicting performance when the system is trained on nonrandom data sets. Finally, theory is derived for predicting false positives in the case when the training set does not include all of self. Secondly, several extensions to the model of distributed detection are described and analysed. These extensions include: multiple representations to overcome holes; activation thresholds and sensitivity levels to reduce false positive rates; costimulation by a human operator to eliminate autoreactive detectors; distributed detector generation to adapt to changing self sets; dynamic detectors to avoid consistent gaps in detection coverage; and memory, to implement signature-based detection. Thirdly, the model is applied to network intrusion detection. The system monitors TCP traffic in a broadcast local area network. The results of empirical testing of the model demonstrate that the system detects real intrusions, with false positive rates of less than one per day, using at most five kilobytes per computer. The system is tunable, so detection rates can be traded off against false positives and resource usage. The system detects new intrusive behaviours (anomaly detection), and exploits knowledge of past intrusions to improve subsequent detection (signature-based detection).
Science Choreography: A Movement-Based Approach to Biology Teaching

We would like to bring to the attention of readers a novel participatory movement–based technique we have been using to teach science and to encourage students to think creatively about science: science choreography. The project evolved as part of a Howard Hughes Medical Institute–funded multiyear collaboration between a team of scientist-educators at Wesleyan University and other institutions and dancerchoreographers from the Liz Lerman Dance Exchange. When the sequencing of the human genome was announced to the public, choreographer and MacArthur Fellow Liz Lerman was one of many who asked what this might mean for our future and the future of our children. To help answer these questions, she decided to make a multimedia piece, Ferocious Beauty: Genome, in collaboration with scientists at Wesleyan University and across the country (Science Choreography, 2011). After the work premiered, it became evident to us that we could use video performance clips from Ferocious Beauty: Genome as a “second textbook”—a launching point and source of enrichment for learning and thinking about concepts in biology. We also came to realize that a number of the tools used in dance making by the Dance Exchange could be easily adapted for use in the classroom, either alone or in combination with video clips from Ferocious Beauty: Genome. We were motivated by a variety of challenges faced by science teachers at all levels, including the perception by some
Who was the agent? The neural correlates of reanalysis processes during sentence comprehension

Sentence comprehension is a complex process. Besides identifying the meaning of each word and processing the syntactic structure of a sentence, it requires the computation of thematic information, that is, information about who did what to whom. The present fMRI study investigated the neural basis for thematic reanalysis (reanalysis of the thematic roles initially assigned to noun phrases in a sentence) and its interplay with syntactic reanalysis (reanalysis of the underlying syntactic structure originally constructed for a sentence). Thematic reanalysis recruited a network consisting of Broca's area, that is, the left pars triangularis (LPT), and the left posterior superior temporal gyrus, whereas only LPT showed greater sensitivity to syntactic reanalysis. These data provide direct evidence for a functional neuroanatomical basis for two linguistically motivated reanalysis processes during sentence comprehension. Hum Brain Mapp , 2011. © 2010 Wiley‐Liss, Inc.
Transcranial Low-Level Laser Therapy Improves Neurological Performance in Traumatic Brain Injury in Mice: Effect of Treatment Repetition Regimen

Low-level laser (light) therapy (LLLT) has been clinically applied around the world for a spectrum of disorders requiring healing, regeneration and prevention of tissue death. One area that is attracting growing interest in this scope is the use of transcranial LLLT to treat stroke and traumatic brain injury (TBI). We developed a mouse model of severe TBI induced by controlled cortical impact and explored the effect of different treatment schedules. Adult male BALB/c mice were divided into 3 broad groups (a) sham-TBI sham-treatment, (b) real-TBI sham-treatment, and (c) real-TBI active-treatment. Mice received active-treatment (transcranial LLLT by continuous wave 810 nm laser, 25 mW/cm2, 18 J/cm2, spot diameter 1 cm) while sham-treatment was immobilization only, delivered either as a single treatment at 4 hours post TBI, as 3 daily treatments commencing at 4 hours post TBI or as 14 daily treatments. Mice were sacrificed at 0, 4, 7, 14 and 28 days post-TBI for histology or histomorphometry, and injected with bromodeoxyuridine (BrdU) at days 21–27 to allow identification of proliferating cells. Mice with severe TBI treated with 1-laser Tx (and to a greater extent 3-laser Tx) had significant improvements in neurological severity score (NSS), and wire-grip and motion test (WGMT). However 14-laser Tx provided no benefit over TBI-sham control. Mice receiving 1- and 3-laser Tx had smaller lesion size at 28-days (although the size increased over 4 weeks in all TBI-groups) and less Fluoro-Jade staining for degenerating neurons (at 14 days) than in TBI control and 14-laser Tx groups. There were more BrdU-positive cells in the lesion in 1- and 3-laser groups suggesting LLLT may increase neurogenesis. Transcranial NIR laser may provide benefit in cases of acute TBI provided the optimum treatment regimen is employed.
Spoofing prevention method

A new approach for filtering spoofed IP packets, called spoofing prevention method (SPM), is proposed. The method enables routers closer to the destination of a packet to verify the authenticity of the source address of the packet. This stands in contrast to standard ingress filtering which is effective mostly at routers next to the source and is ineffective otherwise. In the proposed method a unique temporal key is associated with each ordered pair of source destination networks (AS's, autonomous systems). Each packet leaving a source network S is tagged with the key K(S, D), associated with (S, D), where D is the destination network. Upon arrival at the destination network the key is verified and removed. Thus the method verifies the authenticity of packets carrying the address s which belongs to network S. An efficient implementation of the method, ensuring not to overload the routers, is presented. The major benefits of the method are the strong incentive it provides to network operators to implement it, and the fact that the method lends itself to stepwise deployment, since it benefits networks deploying the method even if it is implemented only on parts of the Internet. These two properties, not shared by alternative approaches, make it an attractive and viable solution to the packet spoofing problem.
Understanding and measuring circular polarization

Many modern satellite and terrestrial point-to-point communications systems use circular polarization (CP) wave propagation in order to maximize the polarization efficiency component of the link budget. Therefore, in an undergraduate electromagnetics syllabus, an introduction to the topic of circular polarization is necessary to promote an understanding of the propagation aspects of modern communications system design. Students new to the antennas and propagation discipline often have difficulty in grasping the concept of CP; therefore, in this paper, the essential aspects of this topic are reinforced by a tutorial description of CP in terms of wave propagation, antenna properties, and measurement techniques. A simple laboratory-based project is described that requires the design, fabrication, and measurement of a crossed dipole antenna. The measured input impedance and radiation patterns are correlated with theory to highlight the conditions necessary to support CP wave propagation. By combining basic electromagnetic concepts with a series of simple intuitive laboratory experiments, the students can more easily visualize, and hence understand, CP wave propagation and its use in communications systems design.
Reliable Clock Skew Estimation Algorithm for one-way measurements

Owing to the asymmetry of Internet paths, more and more studies have turned to the measurement for one-way metrics. However, since the clocks at end systems often behave diversely, the synchronization between the end hosts is what we care about all along. In this paper, we firstly propose a general model for clock skew estimation in one-way measurements, which turns the problem of clock skew estimation to the solution of n-dimension equation group, and give the equation group what it needs based on different presumptions. We then present a Piece-wise Reliable Clock Skew Estimation Algorithm (PRCSEA), which introduces the reliability test of estimation results and eliminates the extra presumptions needed by other algorithms, such as only one clock adjustment in the measurements. PRCSEA solves the skew estimation problem in a heuristic way, and it can handle many special cases affecting the estimation of clock skew, such as routing change, clock hiccup and network congestion. PRCSEA is the only algorithm that can handle non-constant clock skew to the best of our knowledge. The time complexity of PRCSEA is O(n*logn), which is the same as that of Paxson's algorithm.
Classifying Cognitive Load and Driving Situation with Machine Learning

 Abstract—This paper classifies a driver's cognitive state in real driving situations to improve the in-vehicle information service that judges a user's cognitive load and driving situation. We measure the driver's eye movement and collect driving sensor data such as braking, acceleration, and steering angles that are used to classify the driver's state. A set of data about the driver's degree of cognitive load, regarded as a training set, is obtained from steering operation and task cognition. Given such information, we use a machine-learning method to classify the driver's cognitive load. We achieved reasonable accuracy in certain driving situations in which the driver moves abnormally for an appropriate service supporting safe driving. surrounding situation, the range of eye movement may increase because the driver's cognitive load has increased. This means that a high cognitive load and a change of eye movement are related. Eye movement is used in the field of physiological psychology for clarifying control (1). It is directly related to perception and can be considered an indication of mental load. Driving a car requires prediction of the surrounding environment and is influenced by the situation. Therefore, a user's cognitive load can be classified using these features. To do this, we measure the driver's eye movement and gather driving data such as accelerator use, braking, and steering. This paper takes a machine-learning approach to the above cognitive state identification problem in a realistic car-driving task. We set up cognitive loads according to the steering-entropy method (2) and a definition of the task cognition situation. This paper is organized as follows. Section II presents related works. Section III defines cognitive load. Section IV describes our classification model for cognitive load. Section V presents a performance evaluation. The final section provides conclusions.
Light Field Multi-View Video Coding With Two-Directional Parallel Inter-View Prediction

Light field (LF) technology has been popularly adopted by a wide range of conventional industries. However, one problem when dealing with LFs is the sheer size of data volume. There have been many multi-view video coding (MVC)-based LF video coding methods reported in the literature, aiming at finding the best prediction structure for LF video coding. It is clear that the number of possible prediction structures is unlimited, and it is also observed that the coding bit-rate can be reduced by increasing the number of bi-directionally encoded views in the prediction structure. However, none work has been conducted to analyze the relationship of the prediction structure with its coding performance. In light of this observation, we first design a new LF-MVC prediction structure by extending the inter-view prediction into a two-directional parallel structure. Analytical models for source coding rate and encoding time are developed to analyze their relationships with the prediction structure, and are proven to be well-matched to our experimental results. Experimental evaluation of two LF video sequences demonstrates that the proposed LF-MVC prediction structure can achieve a factor of 26% bit-rate reduction against the conventional MVC prediction structure for an LF video with 5 × 5 views, and a further 34% bit-rate reduction for an LF video with a larger 10 × 10 views. Compared with the state-of-the-art MVC-based LF video coding prediction structures in the literature, LF-MVC can achieve the best coding performance, and with its high encoding efficiency, is well suited for deployment in practical LF-based 3D systems.
An Object-Oriented Approach to the Design of Dialogue Management Functionality

Dialogues may be seen as comprising commonplace routines on the one hand and specialized, task-specific interactions on the other. Object-orientation is an established means of separating the generic from the specialized. The system under discussion combines this object-oriented approach with a self-organizing, mixed-initiative dialogue strategy, raising the possibility of dialogue systems that can be assembled from ready-made components and tailored, specialized components.
Elevator-First: A Deadlock-Free Distributed Routing Algorithm for Vertically Partially Connected 3D-NoCs

In this paper, we propose a distributed routing algorithm for vertically partially connected regular 2D topologies of different shapes and sizes (e.g., 2D mesh, torus, ring). The topologies that are the target of this algorithm are of practical interest in the 3D integration of heterogeneous dies using Through-Silicon-Vias (TSVs). Indeed, TSV-based 3D integration allows to envision the stacking of dies with different functions and technologies, using as an interconnect backbone a 3D-NoC. Intrinsically, 3D topologies have better performances, but yield and active area (and thus the cost) are function of the number of TSVs; therefore, the designs tend to use only a subset of available TSVs between two dies. The definition of blockage free and low implementation cost distributed deterministic routing on this kind of topology is thus of theoretical and practical interests. We formally prove that independently of the shape and dimensions of the planar topologies and of the number and placement of the TSVs, the proposed routing algorithm using two virtual channels in the plane is deadlock and livelock free. We also experimentally show that the performance of this algorithm is still acceptable when the number of vertical connections decreases.
Resilient packet header compression through coding

Header compression saves bandwidth, but it also introduces error propagation whenever packets are lost. We propose to use error correcting codes on the compressed packet headers. The result is an overall system that maintains most of the bandwidth savings of header compression and yet is robust with respect to errors. The key to achieving this tradeoff is appropriate distribution of parity symbols across the packets. The proposed system performs better than ordinary header compression and as well as the TWICE algorithm. In most cases, the effects of the error propagation can be almost removed, such that the end-to-end packet loss rate is similar to a system with no header compression, while the bitrate savings are largely maintained.