Miracle-dz/UniFAR-FTUs huggingface dataset:
Equalized on-chip interconnect: modeling, analysis, and design

This thesis work explores the use of equalization techniques to improve throughput and reduce power consumption of on-chip interconnect. A theoretical model for an equalized on-chip interconnect is first suggested to provide mathematical formulation for the link behavior. Based on the model, a fast-design space exploration methodology is demonstrated to search for the optimal link design parameters (wire and circuit) and to generate the optimal performance-power trade-off curve for the equalized interconnects. This thesis also proposes new circuit techniques, which improve the revealed demerits of the conventional circuit topologies. The proposed charge-injection transmitter directly conducts pre-emphasis current from the supply into the channel, eliminating the power overhead of analog current subtraction in the conventional transmit pre-emphasis, while significantly relaxing the driver coefficient accuracy requirements. The transmitter utilizes a power efficient nonlinear driver by compensating non-linearity with pre-distorted equalization coefficients. A trans-impedance amplifier at the receiver achieves low static power consumption, large signal amplitude, and high bandwidth by mitigating limitations of purely-resistive termination. A test chip is fabricated in 90-nm bulk CMOS technology and tested over a 10 mm, 2μm pitched on-chip differential wire. The transceiver consumes 0.37-0.63 pJ/b with 2-6 Gb/s/ch. Thesis Supervisor: Vladimir M. Stojanović Title: Associate Professor
The more the merrier? Multivariate approaches to genome-wide association analysis

The vast majority of genome-wide association (GWA) studies analyze a single trait while large-scale multivariate data sets are available. As complex traits are highly polygenic, and pleiotropy seems ubiquitous, it is essential to determine when multivariate association tests (MATs) outperform univariate approaches in terms of power. We discuss the statistical background of 19 MATs and give an overview of their statistical properties. We address the Type I error rates of these MATs and demonstrate which factors can cause bias. Finally, we examine, compare, and discuss the power of these MATs, varying the number of traits, the correlational pattern between the traits, the number of affected traits, and the sign of the genetic effects. Our results demonstrate under which circumstances specific MATs perform most optimal. Through sharing of flexible simulation scripts, we facilitate a standard framework for comparing Type I error rate and power of new MATs to that of existing ones.
Matched filter based spectrum sensing and power level detection for cognitive radio network

In this paper, we study the matched filter based spectrum sensing in a more reasonable cognitive radio (CR) scenario when the primary user (PU) could possibly work on more than one transmit power levels. Besides the traditional sensing target where the secondary user (SU) should decide the presence of PU, an additionally new target here could be also recognizing the power levels of PU, which achieves more "cognition" for CR. We derive the closed form solutions for decision regions and several performance metrics, from which some interesting phenomenons are observed and the related discussions are provided. Numerical examples are presented to corroborate the proposed studies.
Evidence-based psychopharmacology 1. Appraising a single therapeutic trial: what is the evidence for treating earlyAlzheimer's disease with donepezil?

Expertise in setting appropriate, answerable clinical questions, undertaking an accurate search of databases, and appraising the evidence found are all key elements to practising evidence-based medicine. Using the published evidence of the utility of donepezil in Alzheimer's disease as an example, I have attempted to illustrate the process of critical appraisal of a therapeutic intervention. The study appraised was well conducted and the results indicate that donepezil may benefit some patients with Alzheimer's disease.
To appear in Second Language Research Learnability in the L2 acquisition of semantics: A bidirectional study of a semantic parameter

The study investigates the relationship between input, UG parameter values, and the native language in the acquisition of a purely semantic property that is superficially unrelated to its syntactic trigger, The Bare Noun/Proper Name parameter (Longobardi 1991, 1994, 1996, 2001, 2005). English and Italian bare nouns have identical syntactic form and distribution, but differ in available interpretations. On the other hand, proper names display cross-linguistic constant meaning but variable word order. Variation in this respect can be accounted for by a parameter that is set to one value in English and another one in Italian. A bidirectional study of the two properties was conducted. Individual results calculated with the native speaker accuracy as the cutoff point for successful acquisition indicate that parametric restructuring is attested in both learning directions. In the English Italian direction, the lack of one native interpretation in the target language (a contracting of the grammar) is achieved in the absence of negative evidence, in a Poverty of the Stimulus situation. In both directions, the semantic property is acquired based on input and/or positive evidence for the syntactic side of the parameter.
A Fully-Integrated Reconfigurable Dual-Band Transceiver for Short Range Wireless Communications in 180 nm CMOS

A fully-integrated reconfigurable dual-band (760-960 MHz and 2.4-2.5 GHz) transceiver (TRX) for short range wireless communications is presented. The TRX consists of two individually-optimized RF front-ends for each band and one shared power-scalable analog baseband. The sub-GHz receiver has achieved the maximum 75 dBc 3rd-order harmonic rejection ratio (HRR3) by inserting a Q-enhanced notch filtering RF amplifier (RFA). In 2.4 GHz band, a single-ended-to-differential RFA with gain/phase imbalance compensation is proposed in the receiver. A ΣΔ fractional-N PLL frequency synthesizer with two switchable Class-C VCOs is employed to provide the LOs. Moreover, the integrated multi-mode PAs achieve the output P1dB (OP1dB) of 16.3 dBm and 14.1 dBm with both 25% PAE for sub-GHz and 2.4 GHz bands, respectively. A power-control loop is proposed to detect the input signal PAPR in real-time and flexibly reconfigure the PA's operation modes to enhance the back-off efficiency. With this proposed technique, the PAE of the sub-GHz PA is improved by ×3.24 and ×1.41 at 9 dB and 3 dB back-off powers, respectively, and the PAE of the 2.4 GHz PA is improved by ×2.17 at 6 dB back-off power. The presented transceiver has achieved comparable or even better performance in terms of noise figure, HRR, OP1dB and power efficiency compared with the state-of-the-art.
Laser scanning module with large sending aperture and inherent high angular position accuracy for 3D LiDAR

One design of state of the art laser scanner systems in automotive applications is based on oscillating mirror modules. The requirement of a large mirror surface for eye-safe transmission beams is a major drawback for fast and reproducible scanning. Tolerances of angular positioning, position sensing as well as vibrational perturbations limit the position accuracy of such a mirror and thus, the accuracy of the transmission spot position in the field of view (FoV). In contrast to scanner modules, Flash LiDAR systems provide high accuracy of spot positions. However, due to simultaneous illumination of the entire FoV, the maximum measurable range degrades. Our approach for a scanner module, presented in this paper, combines a micro lens array (MLA) with an objective lens for generating one optical telescope assembly for each angular scan position exclusively. The consequence is a maximum transmission beam diameter without angular FoV reduction along with minimum mirror dimensions. In order to avoid shadings between adjacent scan spots in the target distance, created by beam cut-offs at the aperture-stop of the objective lens, an array of optimized optical elements is provided additionally to the MLA. With adequate design of the MLA, the reliability of the scanner module regarding the angular positioning accuracy increases significantly. We demonstrate that the noise of the spot position is suppressed in dependence on the aperture-stop dimensions of the MLA. In conclusion, we present a new solution for a 3D LiDAR scanner module with a reliable spot-position accuracy comparable to 3D-camera/Flash LiDAR systems but with higher distance measurement range.
Chemical and Physical Cues Synergistically Affect Mating Behavior Sequences of Male Dasylepida ishigakiensis (Coleoptera: Scarabaeidae)

We investigated physical and chemical cues involved in male mating behavior of the white grub beetle, Dasylepida ishigakiensis (Scarabaeidae). When presented with female attractant pheromone (R)-2-butanol lures in a flight tunnel, nearly all males exhibited orientation and touching behaviors to freshly killed males and females and to intact glass models. Males landed and bent their abdomens on male and female bodies, but not on intact glass models. When treated with one female equivalent (FE) extract, washed immature male bodies and glass models both evoked stronger male responses than untreated equivalents, with the former eliciting a greater response than the treated glass models. Male responses to target male and female bodies decreased with increased numbers of washings of target bodies with organic solvents. These results suggest that the chemical factors that elicit male abdominal bending behavior are present on the body surface in both sexes. Washed immature male bodies treated with 1 FE or one male equivalent (ME) of extract induced strong male abdominal bending behavior. Washed mature female bodies treated with 1 ME extract also evoked male responses. Extracts of both sexes included factors eliciting male abdominal bending behavior. These results suggest that both physical and chemical cues derived from conspecifics cooperate to facilitate male mating recognition in D. ishigakiensis. The mating process of this species in the field is highly synchronized. Thus, after orienting to a female-like object, the only information males require by touching is whether the sex attractant pheromone that attracted them is indeed from a conspecific.
MCbiclust: a novel algorithm to discover large-scale functionally related gene sets from massive transcriptomics data collections

The potential to understand fundamental biological processes from gene expression data has grown parallel with the recent explosion of the size of data collections. However, to exploit this potential, novel analytical methods are required, capable of handling massive data matrices. We found current methods limited in the size of correlated gene sets they could discover within biologically heterogeneous data collections, hampering the identification of multi-gene controlled fundamental cellular processes such as energy metabolism, organelle biogenesis and stress responses. Here we describe a novel biclustering algorithm called Massively Correlated Biclustering (MCbiclust) that selects samples and genes from large datasets with maximal correlated gene expression, allowing regulation of complex pathway to be examined. The method has been evaluated using synthetic data and applied to large bacterial and cancer cell datasets. We show that the large biclusters discovered, so far elusive to identification by existing techniques, are biologically relevant and thus MCbiclust has great potential use in the analysis of transcriptomics data to identify large scale unknown effects hidden within the data. The identified massive biclusters can be used to develop improved transcriptomics based diagnosis tools for diseases caused by altered gene expression, or used for further network analysis to understand genotype-phenotype correlations.
Assessment and representation of variability in ecological niche model predictions

Ecological niche models are popular tools used in fields such as ecology, biogeography, conservation biology, and epidemiology. These models are used commonly to produce representations of species’ potential distributions, which are then used to answer other research questions; for instance, where species richness is highest, where potential impacts of climate change can be anticipated, or where to expect spread of invasive species or disease vectors. Although these representations of potential distributions are variable which contributes to uncertainty in these predictions, model variability is neglected when presenting results of ecological niche model analyses. Here, we present examples of how to quantify and represent variability in models, particularly when models are transferred in space and time. To facilitate implementations of analyses of variability, we developed R functions and made them freely available. We demonstrate means of understanding how much variation exists and where this variation is manifested in geographic space. Representing model variability in geographic space gives a reference of the uncertainty in predictions, so analyzing this aspect of model outcomes must be a priority when policy is to be set or decisions taken based on these models. Our open access tools also facilitate post modeling process that otherwise could take days of manual work.
Low Latency Rendering for Mobile Augmented Reality

Mobile augmented reality requires accurate alignment of virtual information with objects visible in the real world. We describe a system for mobile communications to be developed to meet these strict alignment criteria using a combination of computer vision, inertial tracking and low-latency rendering techniques. A prototype low-power and low-latency renderer using an off-the-shelf 3D card is discussed.
Quantification of hepatic steatosis with MRI: The effects of accurate fat spectral modeling

To develop a chemical‐shift–based imaging method for fat quantification that accounts for the complex spectrum of fat, and to compare this method with MR spectroscopy (MRS). Quantitative noninvasive biomarkers of hepatic steatosis are urgently needed for the diagnosis and management of nonalcoholic fatty liver disease (NAFLD).
Keyword extraction for contextual advertisement

As the largest online marketplace, eBay strives to promote its inventory throughout the Web via different types of online advertisement. Contextually relevant links to eBay assets on third party sites is one example of such advertisement avenues. Keyword extraction is the task at the core of any contextual advertisement system. In this paper, we explore a machine learning approach to this problem. The proposed solution uses linear and logistic regression models learnt from human labeled data, combined with document, text and eBay specific features. In addition, we propose a solution to identify the prevalent category of eBay items in order to solve the problem of keyword ambiguity.
Hardening an L4 microkernel against soft errors by aspect-oriented programming and whole-program analysis

Transient hardware faults in computer systems have become widespread as shrinking structures and low supply voltages reduce the amount of energy needed to trigger a fault. This paper describes the latest improvements of a software-based fault-tolerance mechanism called Generic Object Protection (GOP). It is based on Aspect-Orientied Programming in AspectC++ and has been used in a case study to harden the L4/Fiasco.OC microkernel. As a result, the improved GOP avoids 60% of kernel failures at an acceptable overhead of 19% code size and less than 1% runtime. The GOP improvements use static whole-program analysis and have been implemented in a prototypical manner. As an outlook, the paper presents envisioned language extensions providing whole-program control-flow and data-flow analyses in future AspectC++ versions.
Massively parallel classification of single-trial EEG signals using a min-max Modular neural network

This paper presents a method for classifying single-trial electroencephalogram (EEG) signals using min-max modular neural networks implemented in a massively parallel way. The method has three main steps. First, a large-scale, complex EEG classification problem is simply divided into a reasonable number of two-class subproblems, as small as needed. Second, the two-class subproblems are simply learned by individual smaller network modules in parallel. Finally, all the individual trained network modules are integrated into a hierarchical, parallel, and modular classifier according to two module combination laws. To demonstrate the effectiveness of the method, we perform simulations on fifteen different four-class EEG classification tasks, each of which consists of 1491 training and 636 test data. These EEG classification tasks were created using a set of non-averaged, single-trial hippocampal EEG signals recorded from rats; the features of the EEG signals are extracted using wavelet transform techniques. The experimental results indicate that the proposed method has several attractive features. 1) The method is appreciably faster than the existing approach that is based on conventional multilayer perceptrons. 2) Complete learning of complex EEG classification problems can be easily realized, and better generalization performance can be achieved. 3) The method scales up to large-scale, complex EEG classification problems.
Four-Element MIMO Antenna System for UWB Applications

A four element multiple input multiple output (MIMO) antenna system for UWB applications is presented. The system consists of two identical slot dipoles and two identical planar monopoles. Polarization diversity between different kinds of antennas can realize lower coupling between antenna elements, and by using a couple of inverted L-shaped stubs and an inverted Z-shaped stub as decoupling structures, isolation can be further improved. For both simulation and measurement, higher than 17 dB isolation between antenna elements can be obtained through the whole UWB band (3.1–10.6 GHz). The envelope correlation coefficient, antenna gain, efficiency and other performances are also provided.
String-based flapping mechanism and modularized trailing edge control system for insect-type FWMAV

This paper presents the design process and experimental results of a brand new flapping and trailing edge control mechanism for a flapping wing micro air vehicle. The flapping mechanism, whose main components are fabricated from string, is suggested and optimized further by a modified pattern search method. The trailing edge control mechanisms for pitching and rolling moments are designed to be attached onto the present flapping mechanism in a modularized fashion. Prototypes of both mechanisms are fabricated and experimentally tested in order to examine the feasibility of the designs. It is expected that the present flapping mechanism will generate enough lift for the total weight of the vehicle. The present control mechanism is found to be able to supply sufficient control moment.
A vector Taylor series approach for environment-independent speech recognition

In this paper we introduce a new analytical approach to environment compensation for speech recognition. Previous attempts at solving analytically the problem of noisy speech recognition have either used an overly-simplified mathematical description of the effects of noise on the statistics of speech or they have relied on the availability of large environment-specific adaptation sets. Some of the previous methods required the use of adaptation data that consists of simultaneously-recorded or "stereo" recordings of clean and degraded speech. In this work we introduce the use of a vector Taylor series (VTS) expansion to characterize efficiently and accurately the effects on speech statistics of unknown additive noise and unknown linear filtering in a transmission channel. The VTS approach is computationally efficient. It can be applied either to the incoming speech feature vectors, or to the statistics representing these vectors. In the first case the speech is compensated and then recognized; in the second case HMM statistics are modified using the VTS formulation. Both approaches use only the actual speech segment being recognized to compute the parameters required for environmental compensation. We evaluate the performance of two implementations of VTS algorithms using the CMU SPHINX-II system on the 100-word alphanumeric CENSUS database and on the 1993 5000-word ARPA Wall Street Journal database. Artificial white Gaussian noise is added to both databases. The VTS approaches provide significant improvements in recognition accuracy compared to previous algorithms.
Implementing Security in Mobile Agents by using AES Technique

Mobile Agent is a program which travels from one platform to another in order to get its work done. An agent is safe in its owner site but when it ventures out and gets executed on some other platform, it becomes vulnerable to many attacks. There are many counter measures that have been proposed in this paper to overcome these attacks. Cryptography based technique i.e. Symmetric Key Algorithm (specifically AES) is one such counter measure taken to provide security. An example case study of client server application has been considered to address the issue of security. Mobile agent is implemented on the aglet client agent host using a platform known as Aglet. Aglet is a java object which moves in a network and gets executed on host which are aglet enabled. AES using Aglet and Java have been implemented to provide security to the mobile agent. The results show how the client agent and server agent can exchange information over internet in a secure manner. The private data entered by client agent is encrypted using AES key which is provided by the server agent to the client agent in an encrypted form. This means that only server agent can decrypt this because he has AES key. Keywords: Mobile Agent [MA], Aglets, AES, Encryption, Decryption
Inherited defects of coagulation factor V: the hemorrhagic side

Summary. Coagulation factor V (FV) is the protein cofactor required in vivo for the rapid generation of thrombin catalyzed by the prothrombinase complex. It also represents a central regulator in the early phases of blood clot formation, as it contributes to the anticoagulant pathway by participating in the downregulation of factor VIII activity. Conversion of precursor FV to either a procoagulant or anticoagulant cofactor depends on the local concentration of procoagulant and anticoagulant enzymes, so that FV may be regarded as a daring tight‐rope walker gently balancing opposite forces. Given this dual role, genetic defects in the FV gene may result in opposite phenotypes (hemorrhagic or thrombotic). Besides a concise description on the structural, procoagulant and anticoagulant properties of FV, this review will focus on bleeding disorders associated with altered levels of this molecule. Particular attention will be paid to the mutational spectrum of type I FV deficiency, which is characterized by a remarkable genetic heterogeneity and by an uneven distribution of mutations throughout the FV gene.