Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of RNS Based Addition Subtraction and Multiplication Units

Residue number systems have gained significant importance in the field of high-speed digital signal processing due to their carry-free nature and speed-up provided by parallelism. The cynical aspect in the application of RNS is the selection of the moduli set and the design of the conversion units. In the residue number system, a set of moduli which are independent of each other is given. An integer is represented by the residue of each modulus and the arithmetic operations are based on the residues individually. The arithmetic operations based on residue number system can be performed on various moduli independently to avoid the carry obtained in addition, subtraction and multiplication, which is usually time consuming. Thus, the comparison and division are more complicated and the fraction number computation is immured. In this paper, work is done by the residues of the number and performed Addition, Subtraction and Multiplication are performed which shows more advantages of Carry Free nature. Performance of RNS based Addition, subtraction and Multiplication Units has been implemented for modulo set {2 n -1, 2 n , 2 n +1} for n=2,3 with the targeted device of Spartan 3E using hardware description language called Verilog and synthesized in Xilinx ISE 13.2.
FACE IDENTIFICATION USING MULTIPLE COMBINATION STRATEGY FOR HUMAN ROBOT INTERACTION

Abstract The ability to recognize people is positively necessary for interaction between robots and people. In this paper, we introduce interesting security system that is able to recognize, track and remember user's face. System uses moving camera that has pan/tilt and zoom function like robot's eyes. In order to construct system, we propose the face identification method based on combining multiple features and applying multiple matching algorithms. Also, we address the benefits of multiple instances and show that identification ability can be improved by using proper combination strategy.
Automatic Head Tracking of The Common Marmoset.

New technologies for manipulating and recording the nervous system allow us to perform unprecedented experiments. However, the influence of our experimental manipulations on psychological processes must be inferred from their effects on behavior. Today, quantifying behavior has become the bottleneck for large-scale, high throughput, experiments. The method presented here addresses this issue by using deep learning algorithms for video-based animal tracking. Here we describe a reliable automatic method for tracking head position and orientation from simple video recordings of the common marmoset (Callithrix jacchus). This method for measuring marmoset behavior allows for the indirect estimation of gaze within foveal error, and can easily be adapted to a wide variety of similar tasks in biomedical research. In particular, the method has great potential for the simultaneous tracking of multiple marmosets to quantify social behaviors.
Bandwidth Measurement via TCP Connection

We introduce a novel mechanism for actively measuring available bandwidth along a network path. Instead of adding probe traffic to the network, the new mechanism exploits data packets transmitted in a TCP connection (inline measurement). We call a modified version of TCP that incorporates the proposed mechanism ImTCP (Inline measurement TCP). ImTCP is based on Reno TCP, with a modification to the sender program only. The ImTCP sender adjusts the transmission intervals of data packets, then estimates available bandwidth of the network path between sender and receiver utilizing the arrival intervals of ACK packets. Simulations show that the new measurement mechanism does not degrade TCP data transmission performance, has no effect on surrounding traffic and yields acceptable measurement results in intervals as short as 1-4 RTTs (round-trip times).
An FPGA-based scalable simulation accelerator for tile architectures

FPGA-based simulation systems can simulate processor behavior in realistic time. In order to practically simulate tile many-core architectures, we propose ScalableCore for prototyping system development using multiple FPGAs. In this paper, we present an FPGA-based platform called ScalableCore system 1.1, which consists of several simulation tiles named ScalableCore Units. Each tile is connected to four neighbor tiles via interface boards called ScalableCore Boards, and so increasing the target number of cores is easy. We also describe useful techniques by which to achieve high scalability of simulation and to implement complicated hardware functions on an FPGA. The developed system simulates the behavior of a tile architecture with DMA communications and NoC 14.2 times faster than a corresponding software-based functional simulator running on a standard computer with an Intel Core2Duo processor. We verified that the ScalableCore system is cycle-accurate by comparing the simulation behavior on a software-based simulator.
Automating Configuration Troubleshooting with Dynamic Information Flow Analysis

Software misconfigurations are time-consuming and enormously frustrating to troubleshoot. In this paper, we show that dynamic information flow analysis helps solve these problems by pinpointing the root cause of configuration errors. We have built a tool called ConfAid that instruments application binaries to monitor the causal dependencies introduced through control and data flow as the program executes -- ConfAid uses these dependencies to link the erroneous behavior to specific tokens in configuration files. Our results using ConfAid to solve misconfigurations in OpenSSH, Apache, and Postfix show that ConfAid identifies the source of the misconfiguration as the first or second most likely root cause for 18 out of 18 real-world configuration errors and for 55 out of 60 randomly generated errors. ConfAid runs in only a few minutes, making it an attractive alternative to manual debugging.
Space-efficient Data Structures

This thesis focuses on the design of succinct and compressed data structures for collections of string-based data, specifically sequences of semi-structured documents in textual format, sets of strings, and sequences of strings. The study of such collections is motivated by a large number of applications both in theory and practice. For textual semi-structured data, we introduce the concept of semi-index, a succinct construction that speeds up the access to documents encoded with textual semi-structured formats, such as JSON and XML, by storing separately a compact description of their parse trees, hence avoiding the need to re-parse the documents every time they are read. For string dictionaries, we describe a data structure based on a path decomposition of the compacted trie built on the string set. The tree topology is encoded using succinct data structures, while the node labels are compressed using a simple dictionary-based scheme. We also describe a variant of the path-decomposed trie for scored string sets, where each string has a score. This data structure can support efficiently top-k completion queries, that is, given a string p and an integer k, return the k highest scored strings among those prefixed by p. For sequences of strings, we introduce the problem of compressed indexed sequences of strings, that is, representing indexed sequences of strings in nearly-optimal compressed space, both in the static and dynamic settings, while supporting supports random access, searching, and counting operations, both for exact matches and prefix search. We present a new data structure, the Wavelet Trie, that solves the problem by combining a Patricia trie with a wavelet tree. The Wavelet Trie improves on the state-of-the-art compressed data structures for sequences by supporting a dynamic alphabet and prefix queries. Finally, we discuss the issue of the practical implementation of the succinct primitives used throughout the thesis for the experiments. These primitives are implemented as part of a publicly available library, Succinct, using state-of-the-art algorithms along with some improvements.
Limited-Vocabulary Estonian Continuous Speech Recognition System using Hidden Markov Models

The article presents a limited-vocabulary speaker independent continuous Estonian speech recognition system based on hidden Markov models. The system is trained using an annotated Estonian speech database of 60 speakers, approximately 4 hours in duration. Words are modelled using clustered triphones with multiple Gaussian mixture components. The system is evaluated using a number recognition task and a simple medium-vocabulary recognition task. The system performance is explored by employing acoustic models of increasing complexity. The number recognizer achieves an accuracy of 97%. The medium-vocabulary system recognizes 82.9% words correctly if operating in real time. The correctness increases to 90.6% if real-time requirement is discarded.
Modelling and Simulation of Asynchronous Systems Using the LARD Hardware Description Language

LARD is a hardware description language which uses CSP-like channel communication to describe the behaviour of asynchronous VLSI systems. This communication abstraction makes LARD a much more productive language for this type of modelling than conventional languages such as VHDL. LARD simulations can be useful for debugging, for performance analysis , and for validating the behavioural model against a corresponding gate-level schematic. The latter requires co-simulation if the model is non-deterministic. The LARD toolkit has been implemented in a very flexible fashion and is readily adapted to other tasks.
Parametric Study of Diffusion-Enhancement Networks for Spatiotemporal Grouping in Real-Time Artificial Vision

This is the first Annual Technical Summary of the MIT Lincoln Laboratory effort into the parametric study of diffusion-enhancement networks for spatiotemporal grouping in real-time artificial vision. Spatiotemporal grouping phenonena are examined in the context of static and time-varying imagery. Dynamics that exhibit static feature grouping on multiple scales as a function of time and long-range apparent motion between time-varying inputs are developed for a biologically plausible diffusion-enhancement bilayer. The architecture consists of a diffusion and a contrast-enhancement layer coupled by feedforward and feedback connections: input is provided by a separate feature extracting layer. The model is cast as an analog circuit that is realizable in VLSI, the parameters of which are selected to satisfy a psychophysical database on apparent motion.
THE ASSOCIATION BETWEEN COMMON MEASURES OF STRETCH-SHORTENING CYCLE FUNCTION

The purpose of this study was to assess the relationships between common measures of stretch shortening cycle function during a drop jump. Fifteen males from team sports performed three drop jumps from a height of 0.3 m onto a force platform. Ground contact time (CT), flight time (FT), height jumped (HJ), reactive strength index (RSI), reactive strength ratio (RSR) and vertical leg-spring stiffness were recorded for each drop jump. Associations between measures were calculated using Pearson’s r correlations. Large negative correlations were found between CT vs RSR and CT vs Kvert. Large positive correlations were found between FT vs HJ, FT vs RSI, RSR vs RSI, RSI vs Kvert and RSR vs Kvert. The results suggest that although metrics of stretch shortening cycle function are related they appear to assess different capabilities within an athlete.
HIV-1 Protease in the Fission Yeast Schizosaccharomyces pombe

Background HIV-1 protease (PR) is an essential viral enzyme. Its primary function is to proteolyze the viral Gag-Pol polyprotein for production of viral enzymes and structural proteins and for maturation of infectious viral particles. Increasing evidence suggests that PR cleaves host cellular proteins. However, the nature of PR-host cellular protein interactions is elusive. This study aimed to develop a fission yeast (Schizosaccharomyces pombe) model system and to examine the possible interaction of HIV-1 PR with cellular proteins and its potential impact on cell proliferation and viability. Results A fission yeast strain RE294 was created that carried a single integrated copy of the PR gene in its chromosome. The PR gene was expressed using an inducible nmt1 promoter so that PR-specific effects could be measured. HIV-1 PR from this system cleaved the same indigenous viral p6/MA protein substrate as it does in natural HIV-1 infections. HIV-1 PR expression in fission yeast cells prevented cell proliferation and induced cellular oxidative stress and changes in mitochondrial morphology that led to cell death. Both these PR activities can be prevented by a PR-specific enzymatic inhibitor, indinavir, suggesting that PR-mediated proteolytic activities and cytotoxic effects resulted from enzymatic activities of HIV-1 PR. Through genome-wide screening, a serine/threonine kinase, Hhp2, was identified that suppresses HIV-1 PR-induced protease cleavage and cell death in fission yeast and in mammalian cells, where it prevented PR-induced apoptosis and cleavage of caspase-3 and caspase-8. Conclusions This is the first report to show that HIV-1 protease is functional as an enzyme in fission yeast, and that it behaves in a similar manner as it does in HIV-1 infection. HIV-1 PR-induced cell death in fission yeast could potentially be used as an endpoint for mechanistic studies, and this system could be used for developing a high-throughput system for drug screenings.
A randomized, controlled trial of ginseng consumption on the immune response to a moderate exercise stress protocol in non-athletic women

Background: Ginseng is a popular herbal remedy that has been proposed to increase resistance to stress and en- hance immune function. Regular moderate exercise results in an acute physiological stress that affects immune function. Objective: This study was conducted to investigate the effects of daily consumption of a standardized ginsenoside- containing North American ginseng (Panax quinquefolius) extract on immune function before, immediately after, and during recovery from moderate exercise in healthy, non-athletic women. Research design and methods: A double-blinded randomized trial was conducted where healthy female subjects (n=12) were randomized to receive either ginseng (1125 mg/d; n=6) or placebo (n=6) for four weeks. An exercise test was per- formed and peripheral blood collected before and after the four-week treatment period. Immune assays (phenotype analy- sis, neutrophil function, lymphocyte proliferation and natural killer cell cytotoxicity) were performed before, immediately after, and 30 minutes post-exercise. Results: Ginseng-treated subjects had a lower (P<0.05) proportion of antigen mature CD4+CD45RO+ peripheral blood cells before and after exercise, and experienced a sustained reduction (P<0.05) in the proportions of total CD28+ and CD4+CD28+ cells during recovery from exercise. The ginseng group had significantly higher mitogen-stimulated neutro- phil function (oxidative burst) at all exercise protocol time points (P<0.05). There were no effects of ginseng on the pro- portions of other immune cells, lymphocyte proliferation, or natural killer cell cytotoxicity in peripheral blood. Conclusions: The consumption of ginseng for a four-week period improved the ability of neutrophils to respond to stimu- lation and produced changes consistent with less T cell activation after an acute exercise stress.
Molecular and pharmacological properties of insect biogenic amine receptors: lessons from Drosophila melanogaster and Apis mellifera.

In the central nervous system (CNS) of both vertebrates and invertebrates, biogenic amines are important neuroactive molecules. Physiologically, they can act as neurotransmitters, neuromodulators, or neurohormones. Biogenic amines control and regulate various vital functions including circadian rhythms, endocrine secretion, cardiovascular control, emotions, as well as learning and memory. In insects, amines like dopamine, tyramine, octopamine, serotonin, and histamine exert their effects by binding to specific membrane proteins that primarily belong to the superfamily of G protein-coupled receptors. Especially in Drosophila melanogaster and Apis mellifera considerable progress has been achieved during the last few years towards the understanding of the functional role of these receptors and their intracellular signaling systems. In this review, the present knowledge on the biochemical, molecular, and pharmacological properties of biogenic amine receptors from Drosophila and Apis will be summarized. Arch.
A robust spoken Q&A system with scarce in-domain resources

Nowadays there is an increasing interest on deploying spoken conversational agents to provide ubiquitous Question and Answering information to customers about corporate services and commercial products and supporting different users' devices such as PC desktops or mobile phones. Unfortunately, creating an accurate system requires a lot of handwork, where developers must consider several factors such as the performance of the ASR system, the presence of typos in the transcribed queries, the large number of possible variations to ask for the same information using different sentences, or the subtle differences that could exist between similar, but semantically different, questions. In this paper, we propose a methodology for quickly creating robust spoken-based conversational agents with very low resources. Our solution only requires few hand-made query samples, which are automatically expanded to deal with the use of different synonyms and wordings; next, spoken queries are automatically generated using a TTS system and then the audio files are corrupted to simulate different noise conditions and environments that the final users can experiment when they query the system using their voice with means of their mobile devices or by using a kiosk. Then, these audio files are subsequently transcribed using a general purpose ASR which produces an n-best list of recognized results that is first used to retrieve relevant documents and then re-ranked in order to select the final answer. Our tests on a set of 21 different topics proves that our proposal can get a 13% absolute better accuracy than a standard IR using an index with only in-domain answers and 6.3% better than a system including millions of negative out-of-domain candidate answers which is what it is expected for a scalable system.
Positive and negative reinforcement activate human auditory cortex

Prior studies suggest that reward modulates neural activity in sensory cortices, but less is known about punishment. We used functional magnetic resonance imaging and an auditory discrimination task, where participants had to judge the duration of frequency modulated tones. In one session correct performance resulted in financial gains at the end of the trial, in a second session incorrect performance resulted in financial loss. Incorrect performance in the rewarded as well as correct performance in the punishment condition resulted in a neutral outcome. The size of gains and losses was either low or high (10 or 50 Euro cent) depending on the direction of frequency modulation. We analyzed neural activity at the end of the trial, during reinforcement, and found increased neural activity in auditory cortex when gaining a financial reward as compared to gaining no reward and when avoiding financial loss as compared to receiving a financial loss. This was independent on the size of gains and losses. A similar pattern of neural activity for both gaining a reward and avoiding a loss was also seen in right middle temporal gyrus, bilateral insula and pre-supplemental motor area, here however neural activity was lower after correct responses compared to incorrect responses. To summarize, this study shows that the activation of sensory cortices, as previously shown for gaining a reward is also seen during avoiding a loss.
Nuclear norm minimization and tensor completion in exploration seismology

We consider the problem of multidimensional seismic data signal recovery and noise attenuation. These data are multi-dimensional signals that can be described via a low-rank fourth-order tensor in the frequency-space domain. Tensor completion strategies can be used to recover unrecorded observations and to improve the signal-to-noise ratio of seismic data volumes. Tensor completion is posed as an inverse problem and solved via a convex optimization algorithm where a misfit function is minimized in conjunction with the nuclear norm of the tensor. This formulation offers automatic rank determination. We illustrate the performance of the algorithm with a synthetic example and with a real data set obtained by an onshore seismic survey.
Energy-Aware Wireless Networking with Directional Antennas: The Case of Session-Based Broadcasting and Multicasting

We consider ad hoc wireless networks that use directional antennas and have limited energy resources. To explore quantitatively the advantage offered by the use of directional antennas over the case of omnidirectional antennas, we consider the case of connection-oriented multicast traffic. Building upon our prior work on multicasting algorithms, we introduce two protocols that exploit the use of directional antennas and evaluate their performance, We observe significant improvement with respect to the omnidirectional case, in terms of both energy efficiency and network lifetime. Additionally, we show that further substantial increase in the network's lifetime can be achieved by incorporating a simple measure of a node's residual energy into the node's cost function.
Distortion of depth perception in a virtual environment application

Virtual Environment (VE) technology suffers from a variety of hardware and software problems that interfere with the ability to present the experience of being immersed in a synthetic world. Most notably, the poor quality of the viewing surfaces in head-mounted displays has led to many complications in the development of VE systems. These visual displays have a low spatial or pixel resolution that creates several side effects. Because the ability to present depth cues is hampered by the low resolution, the presentation of a sufficiently realistic three-dimensional world is very difficult. Depth perception is distorted by the lack of resolution in two ways. One, the threshold distance at which an object is just visible is much closer than in the real world. Two, the error and variance in estimating the depth of an object are significantly greater than in the real world. This thesis presents a series of mathematical analyses of these distortions, including a model of perspective geometry and the relevant human psychophysical biases. Algorithms are presented that improve both distorted threshold depth perception and distorted depth estimation. Experiments have been conducted to evaluate the usefulness of the algorithms in terms of both perceptual performance and training performance. The ability of the geometric models to predict human performance in the experiments serves as a measure of the models' effectiveness in devising solutions. The findings suggest that the visible range can be extended using the proposed algorithms without significantly affecting the ability to estimate depth. Thesis Supervisor: Nathaniel I. Durlach Title: Senior Research Scientist, M.I. T. Research Laboratory of Electronics