Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-Powered Wireless Sensor System using MEMS Piezoelectric Micro Power Generator

A thin-film lead zirconate titanate Pb(Zr,Ti)O3, MEMS piezoelectric micro power generator (PMPG) has been integrated with a commercial wireless sensor node (Telos) to enable a self-powered RF temperature sensor module. The PMPG and a power management module are designed to satisfy the sensor node's power requirement. An electromechanical model of PMPG has been developed to simulate the system and to maximize the power output. The second generation PMPG is designed to provide 0.173 mW power at 3 V DC with with 1 g excitation at 155.5 Hz. The power management module is developed to provide AC-DC rectification, energy storage, and active switching between the PMPG and the application circuit. To optimize the power requirement, sensor data is taken at a discontinuous interval. A test bed is developed for testing autonomous sensors with a simulated condition of an Alaskan natural gas pipeline. Scaling factors, cost and robustness are considered in the test bed design.
The Perceptions of Urban School Principals Regarding the Education of Students with Emotional and Behavioral Disorders.

x CHAPTER I: INTRODUCTION TO THE STUDY. 1 Working with Students with Emotional and Behavioral Disorders: A Sociocultural Perspective. 1 Statement of the Problem. 7 Historical and contextual framework. 7 Nature and effects of the problem. 14 Purpose of the Study. 21 Definition of Terms. 25 Significance of the Study. 27 Delimitations of the Study. 30 Chapter Outline. 32 CHAPTER II: REVIEW OF LITERATURE. 35 Introduction. 35 The Inclusion Debate. 36 Principals’ Attitudes and Conditions Inhibiting or Promoting the Inclusion of Students with Disabilities. 45 Leadership Practices: Principals as Agents of Change. 48 Characteristics of Effective Inclusive Settings for Students with Emotional and Behavioral Disorders. 52
Inverse-degree Sampling for Spectral Clustering

Among those classical clustering algorithms, spectral clustering performs much better than K-means in most cases. However, for the sake of cubic time complexity, spectral clustering is hardly used for clustering large-scale data sets. Therefore, sampling-based methods such as Nystr¡§om method and Column sampling are respectively conducted as potential approaches to tackle this challenge. As we know, current sampling-based methods often utilize the uniform or other random sampling policies to select representative data and tend to disregard the data in small size clusters. This paper proposes an unbiased sampling framework, derives a new sampling method called inverse-degree sampling and then introduces an entropy criterion to prove it in theory simply. According to the selection of representative data by inverse-degree sampling in spectral clustering, the time complexity of spectral clustering becomes quadratic. Experiments on both toy data and real-world data demonstrate both the good sampling performance and the comparable clustering quality.
Detection of vanA-Containing Enterococcus Species in Faecal Microbiota of Gilthead Seabream (Sparus aurata)

Vancomycin-resistant Enterococcus faecalis, E. faecium and E. durans isolates with the genotype vanA were detected in 7 of 118 faecal samples (5.9%) of natural gilthead seabream recovered off the coast of Portugal, and one vancomycin-resistant isolate/sample was further characterized. The genes erm(B), tet(L), tet(M), aac(6′)-aph(2″), aph(3′)-IIIa and/or ant(6)-Ia were identified in most of the 7 vancomycin-resistant enterococci. Sequence types ST273, ST313 and ST76 were detected in three E. faecium isolates and ST6 in two E. faecalis isolates. VanA-containing enterococci are suggested to be disseminated in fish in marine ecosystems close to areas of human activity.
Local public services and migration: educational change evidence from Norwegian municipalities.

"We take advantage of a large panel data base covering most Norwegian municipalities during seven years to examine the relationship between local public services and migration to and from municipalities for different age groups. The main innovation of the paper is that we use a survey data set to verify that the input measures employed as explanatory variables in the migration study actually are related to citizen satisfaction with local public services. We find that the results depend crucially on whether the input measures are instrumented. When input measures are instrumented, we find few effects of local public services on migration. "
The 9aaTAD Is Exclusive Activation Domain in Gal4

The Gal4 protein is a well-known prototypic acidic activator that has multiple activation domains. We have previously identified a new activation domain called the nine amino acid transactivation domain (9aaTAD) in Gal4 protein. The family of the 9aaTAD activators currently comprises over 40 members including p53, MLL, E2A and other members of the Gal4 family; Oaf1, Pip2, Pdr1 and Pdr3. In this study, we revised function of all reported Gal4 activation domains. Surprisingly, we found that beside of the activation domain 9aaTAD none of the previously reported activation domains had considerable transactivation potential and were not involved in the activation of transcription. Our results demonstrated that the 9aaTAD domain is the only decisive activation domain in the Gal4 protein. We found that the artificial peptides included in the original Gal4 constructs were results of an unintended consequence of cloning that were responsible for the artificial transcriptional activity. Importantly, the activation domain 9aaTAD, which is the exclusive activation domain in Gal4, is also the central part of a conserved sequence recognized by the inhibitory protein Gal80. We propose a revision of the Gal4 regulation, in which the activation domain 9aaTAD is directly linked to both activation function and Gal80 mediated inhibition.
Relationships between substrate, surface characteristics, and vegetation in an initial ecosystem

We investigated surface and vegetation dynamics in the artificial initial ecosystem "Chicken Creek" (Lusatia, Germany) in the years 2006–2011 across a wide spectrum of empirical data. We scrutinized three overarching hypotheses concerning (1) the relations between initial geomorphological and substrate characteristics with surface structure and terrain properties, (2) the effects of the latter on the occurrence of grouped plant species, and (3) vegetation density effects on terrain surface change. Our data comprise and conflate annual vegetation monitoring results, biennial terrestrial laser scans (starting in 2008), annual groundwater levels, and initially measured soil characteristics. The empirical evidence mostly confirms the hypotheses, revealing statistically significant relations for several goal variables: (1) the surface structure properties, local rill density, local relief energy and terrain surface height change; (2) the cover of different plant groups (annual, herbaceous, grass-like, woody, Fabaceae ), and local vegetation height; and (3) terrain surface height change showed significant time-dependent relations with a variable that proxies local plant biomass. Additionally, period specific effects (like a calendar-year optimum effect for the occurrence of Fabaceae ) were proven. Further and beyond the hypotheses, our findings on the spatiotemporal dynamics during the system's early development grasp processes which generally mark the transition from a geo-hydro-system towards a bio-geo-hydro system (weakening geomorphology effects on substrate surface dynamics, while vegetation effects intensify with time), where pure geomorphology or substrate feedbacks are changing into vegetation–substrate feedback processes.
Zero-moment point based balance control of leg-wheel hybrid structures with inequality constraints of kinodynamic behavior

This paper discusses a balance control method with kinodynamic constraints for leg-wheel hybrid structures in an effort to improve the mobility of locomotion over hard, flat surfaces. Preliminarily, we defined a prioritized Jacobian and a prioritized inverse of Jacobian to formulate the dynamically decoupled model in the task space for the constrained multi-contact multi-rigid-body system with a floating base. Our strategy has two tracks to accommodate the uncertainty and the complexity of the system dynamics. 1) The time-delay estimation and control are combined with the nonlinear programming. 2) Whole kinodynamic constraints are derived as functions of the control input. The proposed balance control algorithm allows the system to traverse desired trajectories satisfying the kinodynamic constraints and improves the mobility of locomotion. The effectiveness of the algorithm is tested with the dynamic simulations.
Design of wireless power management SOC for active capsule endoscope

This paper proposes a novel wireless power supply solution, and designs a power management system-on-chip (SOC) for active capsule endoscope. The SOC consists of a high-efficiency rectifier, two excellent performances low-dropout regulator (LDO) and a rapid battery charger management unit. The self-resonant coil inside the human body is used to receive energy, and the energy is rectified and regulated to generate a stable voltage for charging a button battery, which provides stable power for controlling and driving the system by the low dropout (LDO2) regulator fixed in the capsule endoscope. The power management SOC was designed using a 0.18-um CMOS high voltage process. Simulation results indicate that the rectifier has high conversion efficiency of voltage and power under 12mA load. The LDO1 output can keep at 4.4V in spite of the variations of input voltage and loading current. The preliminary system simulation indicates the SOC achieves control of battery charging-recharging.
Online Bulk Deletion

We consider online bulk-delete operations on a large database table organized as a primary (sparse) B+-tree index on a multi-attribute key. Using the natural range partitions induced by prefixes of the key, we define a multi-granular key-range locking protocol in which a bulk operation locks a small number of logical fragments of the table covering the target of the operation. We also present an efficient and recoverable bulk-delete algorithm that minimizes the work needed in B-tree rebalancing and in transaction rollback. All the locks needed for a bulk-delete operation are acquired during a scan of the leaf pages covering the target key range; in this scan the records qualifying for deletion are only marked as deleted. The records are physically deleted in a rebalance phase that avoids visiting subtrees in which all records qualify for deletion, thus saving considerably on the number of rebalancing operations.
Route description interpretation on automatically labeled robot maps

This paper presents an approach to combine automatic semantic place labeling of robot-generated maps with reasoning on human route descriptions. Enabling robots to understand human route descriptions can simplify HRI situations in household or industrial settings. However, solving this problem requires handling the ambiguity present in route descriptions and the possible unreliability of the semantic perception capabilities of the robot. We address this problem by absorbing these uncertainties in a probability distribution measuring the likelihood of the different interpretations (paths) of a given route description and selecting its MAP solution. The approach is evaluated on a dataset of route descriptions transcribed into a suitable representation using standard information retrieval metrics. These performance measurements indicate that the method can correctly interpret route descriptions even in challenging environments.
Evaluation of Dynamic Voltage and Frequency Scaling as a Differential Power Analysis Countermeasure

Differential power analysis (DPA) attack is a major concern for secure embedded devices (Ravi et al., 2004)-(Ors et al., 2004). Currently proposed countermeasures (Pramstaller, 2005)-(Tin and Verbauwhede, 2004) to prevent DPA imposes significant area, power and performance overheads. In addition they either require special standard cell library and design flows or algorithmic modifications. Recently, random dynamic voltage and frequency scaling (RDVFS) has been proposed (Yang et al., 2005) as a DPA countermeasure, which has less area, power and performance overheads and it does not require special cell library nor design flows nor algorithmic modifications. However, in a synchronous digital circuit, the operating frequency can be detected by monitoring glitches on the power line. In this paper, the authors show that using this information, it is possible to mount a DPA attack on circuits employing RDVFS countermeasure. The authors propose an alternative technique which only varies the supply voltage randomly. Experimental results on AES core with SPICE level simulations show that our proposed method significantly weakens the DPA attack by reducing the correlation of power to processed data
Aircraft Observations of a Coastally Trapped Wind Reversal off the California Coast

Abstract The summertime marine atmospheric boundary layer off the California coast is normally characterized by northerly winds associated with the Pacific high. This pattern is occasionally disturbed by episodes of southerly winds and a finger of fog or low stratus adjacent to the coastline extending approximately 100 km offshore. These events propagate northward along the coast with speeds between 5 and 12 m s−1 and have a life span of several days. These occurrences have been referred to as coastally trapped wind reversals (CTWRs), coastally trapped disturbances, or southerly surges. The CTWR event of 22–25 June 2006 was explored by the University of Wyoming King Air research aircraft to document the physical characteristics of the wind reversal in an attempt to infer the forcing mechanisms responsible for the propagation. Two flights from 23 June are presented that are representative of the CTWR during its mature stage. Sawtooth maneuvers depict the CTWR vertical structure, and isobaric legs directly .
THE STABILIZING PROPERTIES OF NONNEGATIVITY CONSTRAINTS IN LEAST-SQUARES IMAGE RECONSTRUCTION

The incorporation of nonnegativity constraints in image reconstruction problems is known to have a stabilizing effect on solution methods. In this paper, we both demonstrate and provide an explanation of this phenomena when the image reconstruction problem of interest has least squares form. The benefits of using this natural constraint suggest the importance of incorporating a priori knowledge about solutions when possible. In fact, if this prior information is significantly strong, sophisticated likelihood functions and computational methods may not be necessary.
Facial Expression Recognition based on Independent Component Analysis

As an important part of artificial intelligence and pattern recognition, facial expression recognition has drawn much attention recently and numerous methods have been proposed. Feature extraction is the most important part which directly affects the final recognition results. Independent component analysis (ICA) is a subspace analysis method, which is also a novel statistical technique in signal processing and machine learning that aims at finding linear projections of the data that maximize their mutual independence. In this paper, we introduce the basic theory of ICA algorithm in detail and then present the process of facial expression recognition based on ICA model. Finally, we use PCA and ICA algorithm to extract facial features, and then SVM classifier is used for facial expression recognition. Experimental results show ICA is a real effective facial expression recognition method and the recognition rate based on ICA is greater than based on PCA and 2DPCA
Peeping Tom in the Neighborhood: Keystroke Eavesdropping on Multi-User Systems

A multi-user system usually involves a large amount of information shared among its users. The security implications of such information can never be underestimated. In this paper, we present a new attack that allows a malicious user to eavesdrop on other users' keystrokes using such information. Our attack takes advantage of the stack information of a process disclosed by its virtual file within procfs, the process file system supported by Linux. We show that on a multi-core system, the ESP of a process when it is making system calls can be effectively sampled by a "shadow" program that continuously reads the public statistical information of the process. Such a sampling is shown to be reliable even in the presence of multiple users, when the system is under a realistic workload. From the ESP content, a keystroke event can be identified if they trigger system calls. As a result, we can accurately determine inter-keystroke timings and launch a timing attack to infer the characters the victim entered. We developed techniques for automatically analyzing an application's binary executable to extract the ESP pattern that fingerprints a keystroke event. The occurrences of such a pattern are identified from an ESP trace the shadow program records from the application's runtime to calculate timings. These timings are further analyzed using a HiddenMarkovModel and other public information related to the victim on a multi-user system. Our experimental study demonstrates that our attack greatly facilitates password cracking and also works very well on recognizing English words.
Microstructural White Matter Changes Underlying Cognitive and Behavioural Impairment in ALS – An In Vivo Study Using DTI

Background A relevant fraction of patients with amyotrophic lateral sclerosis (ALS) exhibit a fronto-temporal pattern of cognitive and behavioural disturbances with pronounced deficits in executive functioning and cognitive control of behaviour. Structural imaging shows a decline in fronto-temporal brain areas, but most brain imaging studies did not evaluate cognitive status. We investigated microstructural white matter changes underlying cognitive impairment using diffusion tensor imaging (DTI) in a large cohort of ALS patients. Methods We assessed 72 non-demented ALS patients and 65 matched healthy control subjects using a comprehensive neuropsychological test battery and DTI. We compared DTI measures of fiber tract integrity using tract-based spatial statistics among ALS patients with and without cognitive impairment and healthy controls. Neuropsychological performance and behavioural measures were correlated with DTI measures. Results Patients without cognitive impairment demonstrated white matter changes predominantly in motor tracts, including the corticospinal tract and the body of corpus callosum. Those with impairments (ca. 30%) additionally presented significant white matter alterations in extra-motor regions, particularly the frontal lobe. Executive and memory performance and behavioural measures were correlated with fiber tract integrity in large association tracts. Conclusion In non-demented cognitively impaired ALS patients, white matter changes measured by DTI are related to disturbances of executive and memory functions, including prefrontal and temporal regions. In a group comparison, DTI is able to observe differences between cognitively unimpaired and impaired ALS patients.
Pruning Bio-Ontologies

The explosive growth of biomedical data makes researchers and professionals recognize the need of developing large ontologies. However as the size of data increases and knowledge evolves, ontologies tend to grow big and large, and hence, retrieving manageable amount of information from large ontologies becomes a difficult and costly task. The purpose of this paper is to find and apply pruning methods from ontology engineering field to bio-ontologies as well as evaluate the results. These methods support systematic identification of relevant concepts and deletion of irrelevant part of an ontology. The paper shows how different pruning methods can be applied in bio-ontologies. To show the usefulness of pruning methods, a large bio-ontology called gene ontology is pruned to obtain a sub-ontology that contains only the relevant information a user is interested in
Gas turbine engine fault isolation based fuzzy inference logic with ECM trend plot report

A fuzzy inference logic system is proposed for gas turbine engine fault isolation. The gas path measurements used for fault isolation are exhaust gas temperature, low and high rotor speed, and fuel flow. The fuzzy inference logic uses rules developed from a model of performance influence coefficients to isolate engine faults while accounting for uncertainty in gas path measurements. Inputs to the fuzzy inference logic system are measurement deviations of gas path parameters which are transferred directly from the ECM (Engine Control Monitoring) program and outputs are engine module faults. The proposed fuzzy inference logic system is tested using simulated data developed from the ECM trend plot reports and the results show that the proposed fuzzy inference logic system isolates module faults with high accuracy rate in the environment of high level of uncertainty.
Obstacle avoidance control for redundant manipulators using collidability measure

We present a measure called collidability measure for obstacle avoidance control of redundant manipulators. Considering moving directions of manipulator links, the collidability measure is defined as the inverse of sum of predicted collision distances between links and obstacles. This measure is suitable for obstacle avoidance control since directions of moving links are as important as distances to obstacles. For dynamic redundancy resolution, null space control is utilized to avoid obstacles by minimizing the collidability measure. Also, by clarifying decomposition in the joint acceleration level, we present a simple dynamic control law with bounded joint torques which guarantees tracking of a given end-effector trajectory and improves a kinematic cost function such as collidability measure. Simulation results are presented to illustrate the effectiveness of the proposed algorithm.
Ver ICS 2006-a Model Checker for Real-Time and Multi-Agent Systems ?

The papers presents the current stage of the development of VerICS a model checker for real-time and multi-agent systems. Depending on the type of a system considered, it enables to test various classes of properties from reachability to temporal, epistemic and deontic formulas. The model checking methods used to this aim include both SAT-based and enumerative ones. In the paper we focus on new features of the verifier: SAT-based model checking for multi-agent systems and several extensions and improvements to real-time systems’ verification.
Appendix for : A Bounded Model of Time Variation in Trend Inflation , NAIRU and the Phillips Curve

This appendix contains two sections. The first is a technical appendix which describes the prior and MCMC algorithm used to estimate our bivariate model of inflation and unemployment (labelled Bi-UC in the paper). It also provides additional estimation details about the other models used for comparison. The second is section contains a prior predictive analysis. Papers cited in this appendix are listed in the references in the paper itself.