Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic and leakage power reduction in MTCMOS circuits using an automated efficient gate clustering technique

Reducing power dissipation is one of the most principle subjects in VLSI design today. Scaling causes subthreshold leakage currents to become a large component of total power dissipation. This paper presents two techniques for efficient gate clustering in MTCMOS circuits by modeling the problem via Bin-Packing (BP) and Set-Partitioning (SP) techniques. An automated solution is presented, and both techniques are applied to six benchmarks to verify functionality. Both methodologies offer significant reduction in both dynamic and leakage power over previous techniques during the active and standby modes respectively. Furthermore, the SP technique takes the circuit's routing complexity into consideration which is critical for Deep Sub-Micron (DSM) implementations. Sufficient performance is achieved, while significantly reducing the overall sleep transistors' area. Results obtained indicate that our proposed techniques can achieve on average 90% savings for leakage power and 15% savings for dynamic power.
Exploring Information Retrieval Features for Author Profiling

This paper describes the methods we have employed to solve the author profiling task at PAN-2014. Our goal was to rely mainly on features from Information Retrieval to identify the age group and the gender of the author of a given text. We describe the features, the classification algorithms employed, and how the experiments were run. Also, we provide an analysis of our results compared to other groups.
Hallym: Named Entity Recognition on Twitter with Word Representation

Twitter is a type of social media that contains diverse user-generated texts. Traditional models are not applicable to tweet data because the text style is not as grammaticalized as that of newswire. In this paper, we construct word embeddings via canonical correlation analysis (CCA) on a considerable amount of tweet data and show the efficacy of word representation. Besides word embedding, we use partof-speech (POS) tags, chunks, and brown clusters induced from Wikipedia as features. Here, we describe our system and present the final results along with their analysis. Our model achieves an F1 score of 37.21% with entity types and distinguishes 53.01% of the entity boundaries.
Supervised Region-Based Segmentation of Quickbird Multispectral Imagery

The segmentation of very high resolution (VHR) satellite imagery (such as Digital Globe QuickBird) is becoming increasingly important to geo-related applications. New sensors provide the ability to discriminate large scale objects that were not discernable with lower resolution satellite imagery such as Landsat TM. VHR satellite images also exhibit an incredible dynamic grey-value variety. These features, among others, impede existing algorithms developed for lower resolution satellite imagery to operate within the same degree of accuracy. This paper proposes a supervised approach to the segmentation of QuickBird multispectral imagery through the integration of the Hierarchical Split Merge Refinement (HSMR) framework. The HSMR framework was originally developed by Ojala and Pietikainen [1999] for unsupervised segmentation of textured areas. In this approach, user identified regions are employed to guide HSMR algorithmic processes. User knowledge is brought to segmentation and it is hypothesized that this will improve stabilization in HSMR segmentation across a variety of QuickBird 2.44 m multispectral satellite image scenes and improve control of segmentation at different scales.
Real-Time Human Pose Estimation and Gesture Recognition from Depth Images Using Superpixels and SVM Classifier

In this paper, we present human pose estimation and gesture recognition algorithms that use only depth information. The proposed methods are designed to be operated with only a CPU (central processing unit), so that the algorithm can be operated on a low-cost platform, such as an embedded board. The human pose estimation method is based on an SVM (support vector machine) and superpixels without prior knowledge of a human body model. In the gesture recognition method, gestures are recognized from the pose information of a human body. To recognize gestures regardless of motion speed, the proposed method utilizes the keyframe extraction method. Gesture recognition is performed by comparing input keyframes with keyframes in registered gestures. The gesture yielding the smallest comparison error is chosen as a recognized gesture. To prevent recognition of gestures when a person performs a gesture that is not registered, we derive the maximum allowable comparison errors by comparing each registered gesture with the other gestures. We evaluated our method using a dataset that we generated. The experiment results show that our method performs fairly well and is applicable in real environments.
Implementing Efficient Market Structure: Optimal Licensing in Natural Oligopoly When Tax Revenue Matters

This article studies the design of optimal mechanisms to regulate entry in natural oligopoly markets, assuming the regulator is unable to control the behavior of firms once they are in the market. We adapt the Clarke–Groves mechanism, characterize the optimal mechanism that maximizes the weighted sum of expected social surplus and expected tax revenue, and show that these mechanisms avoid budget deficits and prevent excessive entry. JEL classification: D43, D44, D45, H21, L13
Ethical Considerations when Employing Fake Identities in OSN for Research

Online Social Networks (OSNs) have rapidly become a prominent and widely used service, offering a wealth of personal and sensitive information with significant security and privacy implications. Hence, OSNs are also an important - and popular - subject for research. To perform research based on real-life evidence, however, researchers may need to access OSN data, such as texts and files uploaded by users and connections among users. This raises significant ethical problems. Currently, there are no clear ethical guidelines, and researchers may end up (unintentionally) performing ethically questionable research, sometimes even when more ethical research alternatives exist. For example, several studies have employed `fake identities` to collect data from OSNs, but fake identities may be used for attacks and are considered a security issue. Is it legitimate to use fake identities for studying OSNs or for collecting OSN data for research? We present a taxonomy of the ethical challenges facing researchers of OSNs and compare different approaches. We demonstrate how ethical considerations have been taken into account in previous studies that used fake identities. In addition, several possible approaches are offered to reduce or avoid ethical misconducts. We hope this work will stimulate the development and use of ethical practices and methods in the research of online social networks.
The Economics of Language

The economics of language remains neglected territory. Language makes information operational. As a social technology, it is a resource of the symbolic species – some argue it defines the human species. Language affects ability to find employment; cultural identity, effective communication in business, international trade, and tourism; negotiations and settlement procedures; political activity; and conflict within and between nations.
Estimation of solar radiation on the tilted surfaces in Songkhla, Thailand

This work presents a method to estimate the average yearly solar radiation on tilted surfaces. In addition, calculation of the monthly average daily diffuse fraction correlation by using the monthly average daily solar radiation on horizontal surface of satellite data, and review of the monthly average daily diffuse solar radiation on horizontal surface of R. H. B. EXELL are presented. The proposed method is compared to the cases of Serm Janjai, Page, and Liu and Jordan. The estimation of an average yearly solar radiation consists of a zero azimuth surface and non-zero azimuth surface.
Distributed Visualization of Fluids using Grid

In this paper we focus on the application of grid technology for fluid visualization. Specifically, we are interested on distributed visualization using grid. The focused visualization technique is particle tracing. They can be thought as the trajectory of massless virtual particles upon the simulated flow. We propose a distributed particle tracing system and its implementation for collaborative visualization environments in computational grids. We decided for Globus as a middleware and offer solutions to minimize communications between application components during computation, a bottleneck for particle tracers in distributed memory environments. Besides, external memory (Out-ofCore) polices are discussed as an alternative approach to reduce this problem.
Low-Overhead Accrual Failure Detector

Failure detectors are one of the fundamental components for building a distributed system with high availability. In order to maintain the efficiency and scalability of failure detection in a complicated large-scale distributed system, accrual failure detectors that can adapt to multiple applications have been studied extensively. In this paper, an new accrual failure detector—LA-FD with low system overhead has been proposed specifically for current mobile network equipment on the Internet whose processing power, memory space and power supply are all constrained. It does not rely on the probability distribution of message transmission time, or on the maintenance of a history message window. By simple calculation, LA-FD provides adaptive failure detection service with high accuracy to multiple upper applications. The related experiments and results have also been presented.
A trust-funnel method for nonlinear optimization problems with general nonlinear constraints and its application to derivative-free optimization

A trust-funnel method is proposed for solving nonlinear optimization problems with general nonlinear constraints. It extends the one presented by Gould and Toint (Math. Prog., 122(1):155- 196, 2010), originally proposed for equality-constrained optimization problems only, to problems with both equality and inequality constraints and where simple bounds are also considered. As the original one, our method makes use of neither lter nor penalty functions and consider the objective function and the constraints as independently as possible. To handle the bounds, an active-set approach is employed. At last, we exploit and incorporate techniques developed for derivative-free optimization to obtain a nal method that can also be used to solve problems where the derivatives are unavailable or are available at a prohibitive cost.
Prospective identification of congenital cytomegalovirus infection in newborns using real-time polymerase chain reaction assays in dried blood spots.

BACKGROUND Congenital cytomegalovirus (CMV) infection is a public health issue, and implementation of neonatal screening has been debated. Detection of CMV DNA by polymerase chain reaction (PCR) of dried blood spots (DBS) routinely collected for metabolic screening from all newborns has been proposed for congenital CMV infection screening. The goal of this study was to prospectively assess the performance of 2 CMV PCR assays of DBS for CMV neonatal screening in a selected population of neonates. METHODS We studied prospective congenital CMV screening in a population of neonates either born with symptoms compatible with congenital CMV or born to mothers with a history of primary infection during pregnancy. For each neonate, 2 CMV PCR assays of DBS were blindly performed in parallel with a gold standard technique (ie, CMV PCR of a urine sample). RESULTS Two hundred seventy-one neonates were studied, and CMV infection, defined by a positive urine sample in the first week of life, was confirmed in 64 (23.6%). Nineteen infected (29.7%) neonates were symptomatic, and 45 (70.3%) were asymptomatic. The ranges of sensitivity, specificity, positive predictive value, and negative predictive value for the 2 CMV PCR assays of DBS were 95.0%-100%; 98.1%-99.0%; 94.1%-96.9%, and 98.5%-100%, respectively. CONCLUSIONS The sensitivity and specificity of both CMV PCR assays of DBS to identify congenital CMV were very high in this population of neonates with a high risk of sequelae. These new data should be considered in the ongoing debate on the appropriateness of the use of DBS as a sample to screen for congenital CMV infection.
Toward an Expanded Research Agenda for Visualization in Transportation: Incorporating SAFETEA-LU Directives for ‘Planning’

The rapid growth in computational system capabilities, fueled by continuous development in the microprocessor and computer graphics industries, have resulted in a level of computer image generation capability that was largely unimaginable by those involved in defense applications of ‘visual simulation’ in the 1980s. While early monochrome, mainframe-based systems (e.g., those by General Electric, Evans and Sutherland, Singer Link, and others) lacked the resolution and scene content of today’s microprocessor-based systems,
Supersymmetric D -term inflation, reheating, and Affleck-Dine baryogenesis

The phenomenology of supersymmetric models of inflation, where the inflationary vacuum energy is dominated by {ital D} terms of a U(1), is investigated. Particular attention is paid to the questions of how to arrange for sufficient {ital e} folds of inflation to occur, what kind of thermal history is expected after the end of inflation, and how to implement successful baryogenesis. Such models are argued to require a more restrictive symmetry structure than previously thought. In particular, it is nontrivial that the decays of the fields driving {ital D} inflation can reheat the Universe in such a way as to avoid the strong gravitino production constraints. We also show how the initial conditions for Affleck-Dine baryogenesis can arise in these models and that the simplest flat directions along which a baryon number is generated can often be ruled out by the constraints coming from a decoherence of the condensate in a hot environment. At the end, we find that successful reheating and baryogenesis can take place in a large subset of {ital D}-inflationary models. {copyright} {ital 1999} {ital The American Physical Society}
A dynamic monitoring for energy consumption reduction of a trust-based intrusion detection system in mobile Ad-hoc networks

Nodes in MANETs are subject to many security leaks, because the communication between nodes occurs using the wireless medium without an infrastructure. Each node has a limited amount of energy available, because they are powered by batteries. Performing monitoring operations to establish whether a node is fair or not requires a large amount of energy, hence their reduction is desirable when they are not needed. A node behavior could dynamically change over time, because it could be compromised by external agents, or it could have a selfish behavior due to energy saving reasons. Thus, monitoring is needed also when a node behavior is fair in a given period of time. The proposed approach of dynamic monitoring could help in saving energy without affecting the accuracy of the IDS. For this purpose, we introduced a function that changes the probability of monitoring a packet depending on the trustworthiness of the involved agent. The results of this work show that the detection accuracy can be unaltered under some conditions, improving the energy saving.
Automatic mining of functionally equivalent code fragments via random testing

Similar code may exist in large software projects due to some common software engineering practices, such as copying and pasting code and n-version programming. Although previous work has studied syntactic equivalence and small-scale, coarse-grained program-level and function-level semantic equivalence, it is not known whether significant fine-grained, code-level semantic duplications exist. Detecting such semantic equivalence is also desirable because it can enable many applications such as code understanding, maintenance, and optimization. In this paper, we introduce the first algorithm to automatically mine functionally equivalent code fragments of arbitrary size - down to an executable statement. Our notion of functional equivalence is based on input and output behavior. Inspired by Schwartz's randomized polynomial identity testing, we develop our core algorithm using automated random testing: (1) candidate code fragments are automatically extracted from the input program; and (2) random inputs are generated to partition the code fragments based on their output values on the generated inputs. We implemented the algorithm and conducted a large-scale empirical evaluation of it on the Linux kernel 2.6. 24. Our results show that there exist many functionally equivalent code fragments that are syntactically different (i.e., they are unlikely due to copying and pasting code). The algorithm also scales to million-line programs; it was able to analyze the Linux kernel with several days of parallel processing.
Complete coverage path planning and guidance for cleaning robots

This paper describes a complete coverage path planning and guidance methodology for a mobile robot, having the automatic floor cleaning of large industrial areas as a target application. The proposed algorithms rely on the a priori knowledge of a 2D map of the environment and cope with unexpected obstacles not represented on the map. A template based approach is used to control the path execution, thus incorporating, in a natural way, the kinematic and the geometric model of the mobile robot on the path planning procedure. The novelty of the proposed approach is the capability of the path planner to deal with a priori mapped or unexpected obstacles in the middle of the working space. If unmapped obstacles permanently block the planned trajectory, the path tracking control avoids these obstacles. The paper presents experimental results with a LABMATE mobile robot, confirming the feasibility of the total coverage path and the robustness of the path tracking behaviour based control.
Non-coherent hierarchical cooperation

Hierarchical cooperation is a communication strategy introduced recently by Özgür et al., where it was shown to significantly outperform standard multi-hop communication in some wireless scenarios. To achieve this gain over multi-hop communication, full availability of channel state information at all the nodes in the network is required. In this paper, we investigate the impact of absence of channel state information on the performance of hierarchical cooperation. If the product of coherence time and coherence bandwidth of the wireless channel is on the order of the number of nodes in the network, we show that non-coherent hierarchical cooperation achieves the same order rate as the coherent version. If the product is smaller than the number of nodes, we show that non-coherent hierarchical cooperation can still yield sizable gains over multihop communication, but may not achieve the same order rate as the coherent version.
Theoretical basis for convective invigoration due to increased aerosol concentration

The potential effects of increased aerosol loading on the development of deep convective clouds and resulting precipitation amounts are studied by employing the Weather Research and Forecasting (WRF) model as a detailed high-resolution cloud resolving model (CRM) with both detailed bulk and bin microphysics schemes. Both models include a physically-based activation scheme that incorporates a size-resolved aerosol population. We demonstrate that the aerosol-induced effect is controlled by the balance between latent heating and the increase in condensed water aloft, each having opposing effects on buoyancy. It is also shown that under polluted conditions, increases in the CCN number concentration reduce the cumulative precipitation due to the competition between the sedimentation and evaporation/sublimation timescales. The effect of an increase in the IN number concentration on the dynamics of deep convective clouds is small and the resulting decrease in domain-averaged cumulative precipitation is shown not to be statistically significant, but may act to suppress precipitation. It is also shown that even in the presence of a decrease in the domain-averaged cumulative precipitation, an increase in the precipitation variance, or in other words, andincrease in rainfall intensity, may be expected in more polluted environments, especially in moist environments. A significant difference exists between the predictions based on the bin and bulk microphysics schemes of precipitation and the influence of aerosol perturbations on updraft velocity within the convective core. The bulk microphysics scheme shows little change in the latent heating rates due to an increase in the CCN number concentration, while the bin microphysics scheme demonstrates significant increases in the latent heating aloft with increasing CCN number concentration. This suggests that even a detailed two-bulk microphysics scheme, coupled to a detailed activation scheme, may not be sufficient to predict small changes that result from perturbations in aerosol loading.
Interaction potential for silicon carbide: A molecular dynamics study of elastic constants and vibrational density of states for crystalline and amorphous silicon carbide

An effective interatomic interaction potential for SiC is proposed. The potential consists of two-body and three-body covalent interactions. The two-body potential includes steric repulsions due to atomic sizes, Coulomb interactions resulting from charge transfer between atoms, charge-induced dipole-interactions due to the electronic polarizability of ions, and induced dipole-dipole (van der Waals) interactions. The covalent characters of the Si–C–Si and C–Si–C bonds are described by the three-body potential. The proposed three-body interaction potential is a modification of the Stillinger-Weber form proposed to describe Si. Using the molecular dynamics method, the interaction potential is used to study structural, elastic, and dynamical properties of crystalline (3C), amorphous, and liquid states of SiC for several densities and temperatures. The structural energy for cubic (3C) structure has the lowest energy, followed by the wurtzite (2H) and rock-salt (RS) structures. The pressure for the structural t.