Miracle-dz/UniFAR-FTUs huggingface dataset:
Component-Based Support for Building Knowledge-Acquisition Systems

Mark A. Musen, Ray W. Fergerson, William E. Grosso, Natalya F. Noy, Monica Crubezy, and John H. GennariStanford Medical InformaticsStanford UniversityStanford, California 94305-5479U.S. A.Musen@Stanford.EDUhttp://www.smi. stanford.edu/projects/protegeDuring the past decade, there has been increasingconsensus within the knowledge-based–systemscommunity on appropriate conceptual componentsfor building intelligent computer programs. Intelli-gent systems are now generally construed in termsof both domain ontologies and abstract problem-solving methods that operate on knowledge basesdefined in terms of those ontologies. There hasbeen less consensus, however, regarding how tooptimize the operational components and the userinterfaces of tools that assist developers in the con-struction of knowledge-based systems. For the mostpart, such lack of consensus is to be expected, giventhe way in which domain considerations oftendominate the way in which knowledge can best beentered, browsed, and updated in any computer-based tool. In our research group at Stanford Uni-versity, we acknowledge both the central importanceand the great variability of domain-specific idiomsthat can enhance the functionality of knowledge-acquisition tools. Our work seeks specific ways toharness this variability and to allow developers totake advantage of alternative approaches.Our latest development in a series of computer-based knowledge-acquisition systems is known asProtege-2000. Protege-2000 is a meta-tool” that“helps users to construct domain-specific knowledge-acquisition systems that application experts can useto enter and browse the content knowledge of elec-tronic knowledge bases. The architecture of Pro-tege-2000 assumes that, as with Web browsers,users will want to enhance andcustom tailor the system’s behavior by means of a variety of “plug-ins. ” These plug-ins are modular pieces of programcode that add new functionalities to Protege-2000 inwell circumscribed ways. Developers can contrib-ute new Protege-2000 plug-ins to a library main-tained on the Internet, and can freely download newplug-ins to augment the behavior of their ownknowledge-acquisition systems constructed usingProtege-2000. Our approach establishes a new kindof knowledge-acquisition enterprise—one of build-ing knowledge-acquisition–tool
Depth map-based human activity tracking and recognition using body joints features and Self-Organized Map

In this paper, we implement human activity tracking and recognition system utilizing body joints features using depth maps. During HAR settings, depth maps are processed to track human silhouettes by considering temporal continuity constraints of human motion information and compute centroids for each activity based on contour generation. In body joints features, depth silhouettes are computed first through geodesic distance to identify anatomical landmarks which produce joint points information from specific body parts. Then, body joints are processed to produce centroid distance features and key joints distance features. Finally, Self-Organized Map (SOM) is employed to train and recognize different human activities from the features. Experimental results show that body joints features achieved high recognition rate over the conventional features. The proposed system should be applicable as e-healthcare systems for monitoring elderly people, surveillance systems for observing pedestrian traffic areas and indoor environment systems which recognize activities of multiple users.
An Optimized S-Box for Advanced Encryption Standard (AES) Design

This work presents an optimized Substitution Box (S-Box) for Advanced Encryption Standard (AES) design. The S-Box is one of the most important components of AES. During SubByte transformation, the eight bit input is substituted by eight bit output using the S-Box. S-Box is constructed by composing two transformation - multiplicative inverse in Galois Field GF(28) followed by an affine transformation. The S-Box is the most time and power consuming component of AES Algorithm. In this paper, we have modified the affine transformation and tried to reduce the time complexity of AES. The time consumption for AES S-Box is decreased by the proposed affine transformation.
Cooperative regulation of neurotensin content in PC12 pheochromocytoma cell cultures: effects of nerve growth factor, dexamethasone, and activators of adenylate cyclase

Nerve growth factor, dexamethasone, and forskolin or cholera toxin (CT) act cooperatively to increase the content of neurotensin (NT) in PC12 pheochromocytoma cells. Relatively small increases in NT content occur in the presence of NGF alone or dexamethasone alone, but not of forskolin or CT alone. Increases of 10- to 100-fold occur in the presence of NGF plus dexamethasone or NGF plus forskolin, and up to 600- fold increases occur in the presence of all three agents. These increases are extremely stable and persist for at least 2 weeks after removal of dexamethasone or forskolin. The complex regulation of NT stores in PC12 cells might reflect mechanisms that regulate NT content of normal chromaffin cells and/or neurons during development or in adult life. A small amount of stored NT is released in response to stimulation with 52 mM K+. This release is blocked in the presence of 2 mM Co2+, suggesting that it occurs via Ca2+-mediated exocytosis.
Robust estimation methods for impulsive noise suppression in speech

We discuss a new robust time domain filtering method that detects and reconstructs speech segments corrupted by impulsive noise. Robust statistical methods are very effective in the case of impulsive environments such as wireless communications and cellular phone applications. The speech signal may be corrupted by impulsive noise lasting several milliseconds. We utilize a robust estimator of covariance based on one-dimensional projections and sample median calculations to detect these impulsive segments. This method, called projection statistics, is a very computationally efficient algorithm to suppress the impulses. We estimate the missing segments of speech using the linear prediction technique whose parameters are estimated using a robust Schweppe-type Huber generalized maximum likelihood (GM) estimator. A robust estimator is needed since speech signals closely follow the Laplacian distribution rather than the Gaussian and edges from the impulses may be leftover in the signal. We provide preliminary simulation results from actual speech containing co-channel and fading interferences from cellular phones
The Effectiveness of Internet Content Filters

As part of its defense of the Child Online Protection Act, which seeks to prevent minors from viewing commercially published harmful-to-minors material on the World Wide Web, the U.S. Department of Justice commissioned a study of the prevalence of “adult” materials and the effectiveness of Internet content filters in blocking them. As of 2005–2006, about 1.1% of webpages indexed by Google and MSN were adult—hundreds of millions of pages. About 6% of a set of 1.3 billion searches executed on AOL, MSN and Yahoo! in summer 2005 retrieved at least one adult webpage among the first ten results, and about 1.7% of those results are adult webpages. These estimates are based on both simple random samples of webpages indexed by search engines and on a stratified random sample of searches. Webpages with sexually explicit content intended for adult entertainment (i.e., not in an educational, medical or artistic context) were used to test a variety of Internet content filters for underblocking—failing to block webpages that they are intended to block. A random sample of “clean” webpages with no sexual content or reference to sex was used to test the filters for overblocking—blocking webpages they are not intended to block. Webpages retrieved by the most popular searches according to Wordtracker were also categorized and used to test filters. Generally, filters with lower rates of underblocking had higher rates of overblocking. If the filter most effective at blocking adult materials were applied to search indexes, typical query results, or the results of popular queries, the number of clean pages blocked in error would exceed the number of adult pages blocked correctly.  This work was supported by the United States Department of Justice. I testified on behalf of the United States at trial in Am. Civil Liberties Union v. Gonzales, 478 F. Supp. 2d 775 (E.D. Pa. 2007), and submitted expert declarations in the related matter of Gonzales v. Google, 234 F.R. D. 674, 688 (N.D. Ca. 2006). Much of the data collection was performed by a group led by Paul Mewett at CRA International. I am grateful to David Freedman, Raphael Gomez, Theodore Hirt, Joel McElvain and an anonymous referee for helpful conversations or comments on an earlier draft. 
Continuously moving table time‐of‐flight angiography of the peripheral veins

Time‐of‐flight (TOF) MR angiography allows for noninvasive vessel imaging. To overcome the limited volumetric coverage of standard TOF techniques, the aim of this study was to investigate the combination of TOF and continuously moving table (CMT) acquisitions for peripheral vein imaging based on image subtraction. Two acquisition strategies are presented: a simple two‐step method based on 2‐fold CMT acquisition and an advanced one‐step method requiring only one continuous scan. Image quality of both CMT TOF techniques was evaluated by semiquantitative image grading and by signal‐to‐noise ratio and contrast‐to‐noise ratio analysis for veins of the upper and lower leg in 10 healthy volunteers. Results were compared to a standard stationary two‐dimensional (2D) TOF multistation acquisition. Image grading revealed good image quality for both CMT TOF methods, thereby confirming the feasibility of axial 2D CMT TOF to assess the veins of the lower extremities during a single scan. Quantitative evaluation showed no significant difference in signal‐to‐noise ratio and contrast‐to‐noise ratio compared to the stationary experiment. Additional measurements in three patients with postthrombotic changes and varicosities demonstrated the clinical applicability of the presented methods. CMT TOF provides promising results and permits the detection of various pathologic changes of the venous system. Magn Reson Med 63:1219–1229, 2010. © 2010 Wiley‐Liss, Inc.
Automating Model Acquisition by Fault Knowledge Re-Use , DR , the Diagnostic Remodeler Algorithm

This paper addresses the problem of automated model acquisition through the re-use of fault knowledge. The Diagnostic Remodeler (DR) algorithm has been implemented for the automated generation of behavioural component models with an explicit representation of function by re-using fault-based knowledge. DR re-uses as its first application the fault-based knowledge of the Jet Engine Troubleshooting Assistant (JETA). DR extracts a model of the Main Fuel System using real-world engine fault knowledge and two types of background knowledge as input: device dependent and device independent background knowledge. To demonstrate DR's generality, it has also been applied to a coffee maker fault knowledge base to extract the component models of a full coffee device.
Reversible full/half adder with optimum power dissipation

In digital circuits power dissipation can be significantly reduced using reversible logic. It is becoming prominent in applications involving quantum computing and low-power design. A new reversible full/half adder using combination of Feynman (CNOT), Toffoli (CCNOT) and Fredkin (CSWAP) gates is proposed. The proposed reversible full/half adder is found to be efficient in reducing constant inputs (ancilla bits), garbage outputs, number of transistors and gate count. The proposed full adder shows 47% reduction in power dissipation, 33% in constant inputs, 50% in garbage outputs and 67% in number of transistors in comparison with similar work present in literature. The energy saving factor of the proposed full-adder is found to be 2.01.
Distributed data acquisition unit with microsecond-accurate wireless clock synchronisation

This paper describes the implementation of the first portable, embedded data acquisition unit (BabelFuse) that is able to acquire and timestamp generic sensor data and trigger General Purpose I/O (GPIO) events against a microsecond-accurate wirelessly-distributed `global' clock. A significant issue encountered when fusing data received from multiple sensors is the accuracy of the timestamp associated with each piece of data. This is particularly important in applications such as Simultaneous Localisation and Mapping (SLAM) where vehicle velocity forms an important part of the mapping algorithms; on fast-moving vehicles, even millisecond inconsistencies in data timestamping can produce errors which need to be compensated for. The timestamping problem is compounded in a robot swarm environment especially if non-deterministic communication hardware (such as IEEE-802.11-based wireless) and inaccurate clock synchronisation protocols are used. The issue of differing timebases makes correlation of data difficult and prevents the units from reliably performing synchronised operations or manoeuvres. By utilising hardware-assisted timestamping, clock synchronisation protocols based on industry standards and firmware designed to minimise indeterminism, an embedded data acquisition unit capable of microsecond-level clock synchronisation is presented.
Functional modeling for liver imaging and nodule characterization

In this paper, we propose to use functional modeling to extract physiological characteristics from dynamic gadolinium-enhanced MRI. The clinical objective is to independently compute the two vascular supplies of the liver, coming from hepatic artery and portal vein. These supplies are progressively modified in hepatocarcinogenesis, and their assessment can be useful for nodule characterization. A first physiological microscopic model of liver vascularization, allows simulating the evolution of the contrast material concentration. After comparison of simulated and real curves, a simplified version of this model is used to extract arterial and portal perfusion parameters, in normal case and in hepatic nodules. These values are in accordance with data obtained by invasive methods.
Selective Consumption Tax Policy and Income-Expenditure Elasticities of Obesity-Linked Consumption Goods

Objective: To identify how consumption of 12 goods – alcohol, cigarettes, fast food, items sold at vending machines, purchases of food away from home, cookies, cakes, chips, candy, donuts, bacon, and carbonated soft drinks – varies across the income distribution by calculating their income-expenditure elasticites. Design and Methods: Data on 20,040 households from 2009-2012 from the Bureau of Labor Statistics’ Consumer Expenditure Survey were used. The data were analyzed using ordinary least squares regressions and Cragg’s double hurdle model which integrates (i) a binary model to determine the decision to consume and (ii) a truncated normal model to estimate the effects for conditional (y > 0) consumption.Results: Income had the greatest effect on expenditures for alcohol (0.314), food away from home (0.295), and fast food (0.284). A one percentage-point increase in income (approximately $428 at the mean) translated into a 0.314 percentage-point increase in spending on alcoholic beverages (approximately $1 annually at the mean). Income had the smallest influence on tobacco expenditures (0.007) and donut expenditures (-0.009). Conclusion: Percentage of a household’s discretionary budget spent on the studied goods falls substantially as income gets larger. Policies targeting the consumption of such goods will disproportionately impact lower-income households.
Noninvasive Source Localization of Interictal EEG Spikes: Effects of Signal-to-Noise Ratio and Averaging

Source localization using single current dipoles estimates equivalent centers of the spiking gray matter. The extent of the active cortex, however, is difficult to assess from scalp EEG because of the unknown individual volume conduction. The spatial scatter of dipole localizations of single spikes has been proposed as a measure of extent. Single spike localization, however, is strongly dependent on the signal-to-noise ratio (SNR), that is, the ratio of spike and background EEG amplitudes. On the other hand, averaging of all spikes yields only the localization of equivalent centers of activity. We investigated the influence of SNR and multiple subaverages on the estimation of spatial extent by comparing the localization scatter of 100 single spikes in 27 spike types of 25 epilepsy patients with 1000 different subaverages computed by random sampling and bootstrapping. Averaging increased SNR and therefore allowed for localization not only at the spike peak but also during spike onset when less cortex is active. In several subjects with known cortical lesions, the single spike scatter considerably exceeded the lesion. Single dipole scatter was highly correlated with SNR (r = −0.83, P < 0.0001) and was greatly reduced when analyzing multiple subaverages of 10, 25, 50, and 100 spikes. Thus, we found a dominant role of the SNR on the estimated extent and improvement by scatterplots based on the dipole localization of randomly sampled subaverages.
The Role of Admission Control in Assuring Multiple Services Quality

Considering that network overprovisioning by itself is not always an attainable and everlasting solution, admission control (AC) mechanisms are recommended to keep network load controlled and assure the required service quality levels. This article debates the role of AC in multiservice IP networks, providing an overview and discussion of current and representative AC approaches, highlighting their main characteristics, pros and cons regarding the management of network services quality. In this debate, particular emphasis is given to an enhanced monitoring-based AC proposal for assuring multiple service levels in multiclass networks
Towards an Efficient Multi-way Factorization of Multi-dimensional Big Data across a GPU Cluster

It has long been an important issue in various disciplines to examine massive multi-dimensional data by extracting the embedded multi-way factors. With the quick increases in both scales and dimensions of data under analysis, research challenges arise in order to reflect the dynamics of large-scale tensors while introducing no significant distortions in the factorization procedure in sophisticated applications. A massively parallel computing framework, namely H-PARAFAC, has been developed to enable Parallel Factor Analysis (PARAFAC) of massive tensors upon a "divide-and-conquer" theory (a modified alternating least squares approach). The hierarchical framework incorporates a coarse-grained model for coordinating the processing of sub tensors and a fine-grained parallel model for computing each sub tensor and fusing sub-factors. Experiments have been performed on a GPU cluster, and the results indicate that (1) the proposed method breaks the limitation on the size of data to be factorized, and (2) it dramatically outperforms the traditional counterparts in terms of both scalability and efficiency, e.g., The runtime increases linearly with the data volume increases in the order of n3.
A fast audio search method based on skipping irrelevant signals by similarity upper-bound calculation

In this paper, we describe an approach to accelerate fingerprint techniques by skipping the search for irrelevant sections of the signal and demonstrate its application to the divide and locate (DAL) audio fingerprint method. The search result for the applied method, DAL3, is the same as that of DAL mathematically. Experimental results show that DAL3 can reduce the computational cost of DAL to approximately 25% for the task of music signal retrieval.
Enhanced HMAX model with feedforward feature learning for multiclass categorization

In recent years, the interdisciplinary research between neuroscience and computer vision has promoted the development in both fields. Many biologically inspired visual models are proposed, and among them, the Hierarchical Max-pooling model (HMAX) is a feedforward model mimicking the structures and functions of V1 to posterior inferotemporal (PIT) layer of the primate visual cortex, which could generate a series of position- and scale- invariant features. However, it could be improved with attention modulation and memory processing, which are two important properties of the primate visual cortex. Thus, in this paper, based on recent biological research on the primate visual cortex, we still mimic the first 100–150 ms of visual cognition to enhance the HMAX model, which mainly focuses on the unsupervised feedforward feature learning process. The main modifications are as follows: (1) To mimic the attention modulation mechanism of V1 layer, a bottom-up saliency map is computed in the S1 layer of the HMAX model, which can support the initial feature extraction for memory processing; (2) To mimic the learning, clustering and short-term memory to long-term memory conversion abilities of V2 and IT, an unsupervised iterative clustering method is used to learn clusters with multiscale middle level patches, which are taken as long-term memory; (3) Inspired by the multiple feature encoding mode of the primate visual cortex, information including color, orientation, and spatial position are encoded in different layers of the HMAX model progressively. By adding a softmax layer at the top of the model, multiclass categorization experiments can be conducted, and the results on Caltech101 show that the enhanced model with a smaller memory size exhibits higher accuracy than the original HMAX model, and could also achieve better accuracy than other unsupervised feature learning methods in multiclass categorization task.
Water Deficit Increases Stilbene Metabolism in Cabernet Sauvignon Berries

The impact of water deficit on stilbene biosynthesis in wine grape (Vitis vinifera) berries was investigated. Water deficit increased the accumulation of trans-piceid (the glycosylated form of resveratrol) by 5-fold in Cabernet Sauvignon berries but not in Chardonnay. Similarly, water deficit significantly increased the transcript abundance of genes involved in the biosynthesis of stilbene precursors in Cabernet Sauvignon. Increased expression of stilbene synthase, but not that of resveratrol-O-glycosyltransferase, resulted in increased trans-piceid concentrations. In contrast, the transcript abundance of the same genes declined in Chardonnay in response to water deficit. Twelve single nucleotide polymorphisms (SNPs) were identified in the promoters of stilbene synthase genes of Cabernet Sauvignon, Chardonnay, and Pinot Noir. These polymorphisms resulted in eight changes within the predicted cis regulatory elements in Cabernet Sauvignon and Chardonnay. These results suggest that cultivar-specific molecular mechanisms might exist that control resveratrol biosynthesis in grapes.