Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Criticality Computation Method in Statistical Timing Analysis

The impact of process variations increases as technology scales to nanometer region. Under large process variations, the path and arc/node criticality provide effective metrics in guiding circuit optimization. To facilitate the criticality computation considering the correlation, the authors define the critical region for the path and arc/node in a timing graph, and propose an efficient method to compute the criticality for paths and arcs/nodes simultaneously by a single breadth-first graph traversal during the backward propagation. Instead of choosing a set of paths for analysis prematurely, we develop a new property of the path criticality to prune those paths with low criticality at very earlier stages, so that our path criticality computation method has linear complexity with respect of the timing edges in a timing graph. To improve the computation accuracy, cutset and path criticality properties are exploited to calibrate the computation results. The experimental results on ISCAS benchmark circuits show that our criticality computation method can achieve high accuracy with fast speed
A Prototype Application of Fuzzy Logic and Expert Systems in Education Assessment

This paper reports on the design and development of an expert fuzzy classification scoring system for grading student writing samples. The growing use of written response tests in the education sector provides fertile domain areas for new and innovative applications of soft computing and expert systems technology. The main function of the expert fuzzy classification scoring system is to support teachers in the evaluation of student writing samples by providing them with a uniform framework for generating ratings based on the consistent application of scoring rubrics. The system has been tested using actual student response data. A controlled experiment demonstrated that teachers using the expert fuzzy classification scoring system can make assessments in less time and with a level of accuracy comparable to the best teacher graders. The paper introduces fuzzy classification techniques that can encapsulate knowledge about imprecise qualities needed for constructing rule-based scoring models that provide consistent, uniform scoring results. This increased consistency in the application of the scoring rubrics allows for more valid individual and group assessment.
Chinese microblogging emotion classification based on support vector machine

Through the analysis and study of the emotional characteristics in Chinese micro-blog, this paper proposed a multidimensional sentiment classification method based micro-blog emotion classification, emoticon in micro-blog is adopted to train the support vector machine and divide micro-blog into seven types of emotions: happiness, fondness, sorrow, anger, fear, detestation and surprise. We used micro-blog emoticon to initial screen large-scale unmarked data, and automatically labeled them into seven types, then used this emotional corpus as training set to train the emotion classifier to classify micro-blog data into multiple emotion categories. The experimental results show that precision of unigram model for each type can reach 63.7%. Meanwhile, different feature selection methods for support vector machines and Naive Bayes classifier experiment have been adopted in the experiment, the precision and recall has reached more than 71%.
On the most metal‐poor PN and its binary central star

PNG135.9+55.9 is the most metal‐poor PN known in our Galaxy. The central star resides in a short‐period binary system with a compact component, probably a white dwarf. We describe new observations, which allowed us to determine the orbital period. The lower limit for the combined mass of both stars is close to the Chandrasekhar limit for white dwarfs, making this binary a possible progenitor of a supernova type Ia. The binary system must have recently emerged from a common envelope phase.
Considerations arising from a complementary learning systems perspective on hippocampus and neocortex

We discuss a framework for the organization of learning systems in the mammalian brain, in which the hippocampus and related areas form a memory system complementary to learning mechanisms in neocortex and other areas. The hippocampal system stores new episodes and “replays” them to the neocortical system, interleaved with ongoing experience, allowing generalization as cortical memories form. The data to account for include: 1) neurophysiological findings concerning representations in hippocampal areas, 2) behavioral evidence demonstrating a spatial role for hippocampus, 3) and effects of surgical and pharmacological manipulations on neuronal firing in hippocampal regions in behaving animals. We hypothesize that the hippocampal memory system consists of three major modules: 1) an invertible encoder subsystem supported by the pathways between neocortex and entorhinal cortex, which provides a stable, compressed, invertible encoding in entorhinal cortex (EC) of cortical activity patterns, 2) a memory separation, storage, and retrieval subsystem, supported by pathways between EC, dentate gyrus and area CA3, including the CA3 recurrent collaterals, which facilitates encoding and storage in CA3 of individual EC patterns, and retrieval of those CA3 encodings, in a manner that minimizes interference, and 3) a memory decoding subsystem, supported by the Shaffer collaterals from area CA1 to area CA3 and the bi‐directional pathways between EC and CA3, which provides the means by which a retrieved CA3 coding of an EC pattern can reinstate that pattern on EC. This model has shown that 1) there is a trade‐off between the need for information‐preserving, structure‐extracting encoding of cortical traces and the need for effective storage and recall of arbitrary traces, 2) long‐term depression of synaptic strength in the pathways subject to long‐term potentiation is crucial in preserving information, 3) area CA1 must be able to exploit correlations in EC patterns in the direct perforant path synapses. © 1997 Wiley‐Liss, Inc.
Mechanisms underlying the inhibition of interferon signaling by viruses

A hallmark of the antiviral response is the induction of interferons. First discovered in 1957 by Issac and Lindeman, interferons are noted for their ability to interfere with viral replication. Interferons act via autocrine and paracrine pathways to induce an antiviral state in infected cells and in neighboring cells containing interferon receptors. Interferons are the frontline defenders against viral infection and their primary function is to locally restrict viral propagation. Viruses have evolved mechanisms to escape the host interferon response, thus gaining a replicative advantage in host cells. This review will discuss recent findings on the mechanisms viruses use to evade the host interferon response. This knowledge is important because the treatment of viral infections is a challenge of global proportions and a better understanding of the mechanisms viruses use to persist in the host may uncover valuable insights applicable to the discovery of novel drug targets.
Comparison of energy update models for wireless sensor nodes with supercapacitors

The key motivation for this work is the fact that modeling energy storage devices such as supercapacitors (SCs) for wireless sensor networks (WSNs) is important for the design and performance assessment of harvesting-aware routing protocols of the future. In this paper, we present a circuit-based model (CBM), a good fit to the empirical data available in the existing literature, and compare it with a linear energy model (LEM) that is often used in literature. Simple closed-form expressions for the number of packets routed by a single node have been derived, and the main point was to point out that the modeling the energy storage medium, namely the SC, impacts the parameter of interest. Our modeling approach and the subsequent comparisons show that the choice of models implies a significant difference in the throughput per node.
The Role of Social Communication Tools in Education from the Saudi Female Students' Perceptions.

This study aims at identifying the role of social communication tools in education from the Saudi female students’ perspectives that are studying at the college of education in King Saud University-Riyadh. This study used a survey, which was distributed to 500 female students. The results showed that 90% of respondents used social media where 95% said social media improved interaction with other and raised the sense of social responsibility, 56% used all tools of social media. 45% used social media more than 6 hours daily. 61% believed that social networks promoted democratic values and spread political culture.62% of respondents used social media to do homework or academic projects and researches. 99% of respondents believed that social media allowed following new information about their academic specialty and obtained specialized scientific consulting. 79% of respondents believed that one goal of creating accounts in social networks were learning specific science knowledge or a foreign language. 9% of respondents benefited from social media in social educational consulting. 44% of respondents preferred to debate in scientific and educational topics. 84% of respondents agreed that social networks provided the opportunity to form relationships with those interested in a particular scientific subject and exchanged experiences and information with them.
Converting System of Phonetics Transcriptions to Myanmar Text Using N-grams Language Models

Converting between Phonetics transcriptions and Myanmar text is a process of converting between the sequence of Phonetics transcriptions and Myanmar text. Phonetics transcription is based on the pronunciation of the language and the Myanmar text is based on the written language. One Phonetics alphabet can be represented many possible forms in written language that leads into word sense ambiguity problem. Another problem is that both of the Phonetics transcriptions and Myanmar text have no space to identify the boundary of syllables and words. This problem can be defined as segmentation problem for matching and mapping between Phonetics transcriptions and Myanmar text. To solve the word-sense ambiguity problem, the research developed n-grams language models from correct training data in Myanmar language. By using these trained n-grams language models, the system can be converted from Phonetics to Myanmar text. Instead of computing the probability on the trained n-grams data, the system matched the input data and the trained n-grams model data. The system has built n-grams models where unigram model, bi-grams model, trigrams model, 4-grams models and 5-grams models to train and convert between Phonetics and Myanmar text. To solve the segmentation problem, the system needed to break the input text into individual tokens. In the system, each token may be represented the consonant, or consonant clusters or vowels. To segment the input text Myanmar text or Phonetics transcriptions correctly, the proposed used the Unicode fonts for both Myanmar text and Phonetics transcriptions.
Reducing Cache Pollution of Threaded Prefetching by Controlling Prefetch Distance

Threaded prefetching based on Chip Multiprocessor (CMP) issues memory requests for data needed later by the main computation, and therefore may lead to increased stress on limited shared cache space and bus bandwidth. In our earlier work, we had proposed an effective threaded prefetching technique that selects proper prefetch distance for specific application to improve the timeliness of prefetching. In this paper, we first estimate the upper limit of prefetch distance for specific application in our proposed threaded prefetching technique, and then analyze the effect of increasing prefetch distance on shared cache pollution. Our experimental evaluations indicated that the bounded range of effective prefetch distance can be determined using our method, and the shared cache pollution can be reduced by controlling prefetch distance in our proposed threaded prefetching technique.
Randomly Ranked Mini Slots for Fair and Efficient Medium Access Control in Ad Hoc Networks

Ad hoc networks offer infrastructure-free operation, where no entity can provide reliable coordination among nodes. Medium access Control (MAC) protocols in such a network must overcome the inherent unreliability of the network and provide high throughput and adequate fairness to the different flows of traffic. In this paper, we propose a MAC protocol that can achieve an excellent balance between throughput and fairness. Our protocol has two versions: randomly ranked mini slots (RRMS) utilizes control-message handshakes similar to IEEE 802.11. Randomly ranked mini slots with busy tone (RRMS-BT) is the better performer of the two, but requires a receiver busy tone. The protocol makes use of granule time slots and sequences of pseudorandom numbers to maximize spatial reuse and divide the throughput fairly among nodes. We demonstrate the performance of this protocol using simulation with fixed and random topologies and show that these results are robust to difficult network configurations and unsynchronized clocks. We further develop novel metrics of long-term and short-term fairness for rigorous performance evaluation. Our simulation results include a detailed comparison between the proposed protocol and existing protocols that have been shown to excel in terms of throughput or fairness
Radio and X-Ray Observations of the Jet in Centaurus A

We present new, high dynamic range VLA images of the inner jet of the closest radio galaxy, Centaurus A. Over a 10 yr baseline we detect apparent subluminal motions (v ~ 0.5c) in the jet on scales of hundreds of parsecs. The inferred speeds are larger than those previously determined using VLBI on smaller scales and provide new constraints on the angle made by the jet to the line of sight if we assume jet-counterjet symmetry. The new images also allow us to detect faint radio counterparts to a number of previously unidentified X-ray knots in the inner part of the jet and counterjet, showing conclusively that these X-ray features are genuinely associated with the outflow. However, we find that the knots with the highest X-ray/radio flux density ratios do not have detectable proper motions, suggesting that they may be related to standing shocks in the jet; we consider some possible internal obstacles that the jet may encounter. Using new, high-resolution Chandra data, we discuss the radio to X-ray spectra of the jet and the discrete features that it contains, and we argue that the compact radio and X-ray knots are privileged sites for the in situ particle acceleration that must be taking place throughout the jet. We show that the offsets observed between the peaks of the radio and X-ray emission at several places in the Cen A jet are not compatible with the simplest possible models involving particle acceleration and downstream advection together with synchrotron and expansion losses.
Who Leads Advocacy through Social Media in Japan? Evidence from the "Tsukuba Civic Activities Cyber-Square" Facebook Page

Although the importance of advocacy activities by civil society organizations (CSOs) in policy and decision-making procedures has been greatly emphasized in the literature of political science and social policy, we have relatively little understanding of the relevance and impact of the leading actors who structure the diverse networks and discourses through social media; further recognition is needed in both fields. The purpose of this study is to analyze civil society organizations at the local government level involved in advocacy activities through the use of social media such as Facebook and Twitter. Our study focuses on a specific Japanese Facebook community page—the “Tsukuba Civic Activities Cyber-Square”—aimed at enhancing civil society activities in Japan. This page is operated by the municipal government of Tsukuba, in collaboration with the University of Tsukuba and Intel Corporation. Our findings indicate that social networking services such as Facebook can provide civil society organizations with: (1) more political opportunities to advocate; (2) more chances to connect with the local government; and (3) create opportunities to exert greater presence, despite their limited financial and political resources.
Curvature, cones and characteristic numbers

Abstract We study Einstein metrics on smooth compact 4-manifolds with an edge-cone singularity of specified cone angle along an embedded 2-manifold. To do so, we first derive modified versions of the Gauss–Bonnet and signature theorems for arbitrary Riemannian 4-manifolds with edge-cone singularities, and then show that these yield non-trivial obstructions in the Einstein case. We then use these integral formulæ to obtain interesting information regarding gravitational instantons which arise as limits of such edge-cone manifolds.
EARLYZER: perceptualy motivated robust TFR of speech

: Development of robust and efficient front-end is crucial for robust ASR. Proper time and frequency resolution of the TFR of speech, motivated by the auditory models is considered an important factor for robustness. An efficient method of realizing a variable resolution TFR using DTFT/Goertzel algorithm is proposed instead of the standard FFT based approach. It is shown that the new representation, called E arLyzer, is more robust than the FFT based Mel frequency cepstral coefficient representation for an automobile noisy speech recognition task.
Joint direct-calculation and adaptive nonlinear optimization algorithm for UWB 3D location

In this paper, a 3D UWB location method, joint direct-calculation and adaptive nonlinear optimization algorithm is proposed. First, performances of direct-calculation and nonlinear optimization algorithm are analyzed. Then we introduce joint direct-calculation and nonlinear optimization algorithm, and compare this method with the methods above. At last, using adaptive iterative step size to instead fixed step size of nonlinear optimization algorithm, an improved technique called joint direct-calculation and adaptive nonlinear optimization algorithm that we proposed is introduced. Simulation results indicate that the proposed method has potential in asynchronous UWB location.
Imitation and Mechanisms of Shared Attention: A Developmental Structure for Building Social Skills

This paper explores the use of imitation in an on-going research program aimed at enabling a humanoid robot to communicate naturally with humans. Our group has constructed an upper-torso humanoid robot, called Cog, in part to investigate how to build intelligent robotic systems by following a developmental progression of skills similar to that observed in human development. Just as a child learns social skills and conventions through interactions with its parents, our robot will learn to interact with people using natural social communication. Our models of social interaction are drawn from developmental models of normal children, developmental models of autism, and on models of the evolutionary development of social skills. In this paper, we consider the role that imitation plays in the development of a critical pre-cursor of normal human social development, mechanisms of shared attention. Mechanisms of shared attention serve to direct two individuals to attend to the same object in the environment, through eye direction, pointing gestures, and other means. Imitation serves a critical role in bootstrapping a system from simple eye behaviors to more complex social skills. We will present data from a face and eye finding system that serves as the basis of this developmental chain, and a short example of how this system can imitate the head movements of
On Some Approximation Algorithms for the Set Partition

We study the set partition problem, which is concerned with partitioning a collection of sets into P subcollections such that the maximum number of elements among all the subcollections is minimized. The problem is NP hard, even when P=2 and the cardinality of each set is 2. This special case is transferred to an edge partition problem for graphs. This paper evaluates the eeciency of diierent approximation algorithms for set partition problems under diierent scenarios, and also presents results on approximation algorithms for edge partition and related problems.
Concise review of recent studies in vitiligo

Vitiligo is an acquired pigmentry disorder of the skin and mucous membranes which manifests as white macules and patches due to selective loss of melanocytes. Etiological hypotheses of vitiligo include genetic, immunological, neurohormonal, cytotoxic, biochemical, oxidative stress and newer theories of melanocytorrhagy and decreased melanocytes survival. There are several types of vitiligo which are usually diagnosed clinically and by using a Wood's lamp; also vitiligo may be associated with autoimmune diseases, audiological and ophthalmological findings or it can be a part of polyendocrinopathy syndromes. Several interventions are available for the treatment for vitiligo to stop disease progression and/or to attain repigmentation or even depigmentation. In this article, we will present an overall view of current standing of vitiligo research work especially in the etiological factors most notably the genetic components, also, types and associations and various and newer treatment modalities.
Learning Rough-Terrain Autonomous Navigation

Autonomous navigation by a mobile robot through natural, unstructured terrain is one of the premier challenges in field robotics. The DARPA UPI program was tasked with advancing the state of the art in robust autonomous performance through challenging and widely varying environments. In order to accomplish this goal, machine learning techniques were heavily utilized to provide robust and adaptive performance, while simultaneously reducing the required development and deployment time. This paper describes the autonomous system, Crusher, developed for the UPI program, and the learning approaches that aided in its successful performance.
Measurement framework of partial cage quality

When an object is caged by a set of fingers, it cannot move arbitrarily far from the caging fingers regardless of what possible rigid motion it takes. Although this condition makes caging an attractive choice for nonprehensile manipulation, it could be too restrictive than necessary in many real cases. This is because some object motions rarely occur in reality. Therefore, some non-caging formations of fingers that only allow these escape motions can still effectively be deployed in many caging tasks. This paper proposes a simple framework for measuring the quality of non-caging formation. The framework takes geometrical information of partial cage as inputs and estimates the order of input's quality which is determined by the effort needed to make an object escape from partial cage. Results from preliminary experiments are presented to help support the proposal of the framework.