Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Noise Minimum Statistics Estimation Algorithm for Using in a Speech-Passing Noise-Rejecting Headset

This paper deals with configuration of an algorithm to be used in a speech-passing angle grinder noise-canceling headset. Angle grinder noise is annoying and interrupts ordinary oral communication. Meaning that, low SNR noisy condition is ahead. Since variation in angle grinder working condition changes noise statistics, the noise will be nonstationary with possible jumps in its power. Studies are conducted for picking an appropriate algorithm. A modified version of the well-known spectral subtraction shows superior performance against alternate methods. Noise estimation is calculated through a multi-band fast adapting scheme. The algorithm is adapted very quickly to the non-stationary noise environment while inflecting minimum musical noise and speech distortion on the processed signal. Objective and subjective measures illustrating the performance of the proposed method are introduced.
Improving Intrusion Analysis Effectiveness

Analysis vs. analysis The volume of data available to the analyst for the forensic analysis of an intrusion or other form of successful attack is enormous. Clearly, analyzing the textual data would be prohibitive as a networked environment will generate tens of thousands of log messages a day. In complex cases, where events must be correlated both temporally and spatially, the task is daunting. Many techniques are applicable to aid the analyst, including: data mining, machine learning, and visualization. Currently, no technique is the end all be all of forensic analysis. Consequently, this paper discusses our research towards the development of visualization techniques to aid the analysis process. These techniques are geared towards incorporation of all intrusion detection and analysis data, including both the original log data as well as the results of other intrusion detection and analysis tools. Incorporating all results into a single environment greatly increases the analyst's effectiveness. This will have the effect of reducing the lost time examining false positives, allowing identification of true anomalies, their sources, and their impact.
Optimal motion generation for autonomous vehicle in maze-like environment

In car-like autonomous vehicle systems, it is an essential task of generating the motion commands according to a given path/strategy. Quite a few theories and techniques have been proposed for the generation of the motion commands in autonomous vehicles, such as pure pursuit, Stanley's nonlinear feedback, chained-form control of kinematic model and the linearized optimal control of dynamic model. Here a non-linear optimization algorithm based on the vehicle's kinematic model and the actuators' model is proposed, which combines the control system dynamic behaviors and gives out the control sequences directly. It starts with modeling the local kinematic behavior and actuators' dynamics. Then online optimization algorithm is applied to the objective function of minimizing the energy cost, execution time and tracking error with some trade-off weights among them. The experiments showed that it worked well for vehicles running in maze-like environment.
An IWAPU STD System for OOV Query Terms and Spoken Queries

We have been proposing a Spoken Term Detection (STD) method for Out-Of-Vocabulary (OOV) query terms integrating various subword recognition results using monophone, triphone, demiphone, one third phone, and Sub-phonetic segment (SPS) models[1][2]. In this paper, we describe two methods for text OOV query terms and spoken queries. For text OOV query terms, we introduce four unique methods. First, we integrate multiple retrieval results obtained from multiple subword recognition[4][5]. Second, we use Deep Neural Network (DNN)[6] for computing output probabilities of Hidden Markov Models (HMM). Third, we apply a re-ranking method [7] utilizing highly ranked candidates. Fourth, DNN is also used for re-ranking for the retrieval results containing organizer’s results. For spoken queries, we use speech recognition results of several speech recognizers including our word-based HMM and DNN-HMM recognizer, our syllable-based HMM and DNN-HMM recognizer and google voice. A few retrieval results obtained by each recognizer are combined. In STD tasks (SDPWS) of IR for Spoken Documents in NTCIR-11, we submit 15 types of retrieval results. For text query terms, we use transcriptions of our various speech recognizers, only an organizer’s transcription, both of our transcriptions and an organizer’s transcription, and so on. For spoken queries, we also use the same transcriptions of spoken documents, as mentioned above. We also submit a run using organizer’s transcriptions for spoken documents, followed by our re-ranking methods.
Seasonal Dynamics of Ant Community Structure in the Moroccan Argan Forest

Abstract In this study we describe the structure and composition of ant communities in the endemic Moroccan Argan forest, using pitfall traps sampling technique throughout the four seasons between May 2006 and February 2007. The study focused on two distinct climatic habitats within the Essaouira Argan forest, a semi-continental site at Lahssinate, and a coastal site at Boutazarte. Thirteen different ant species were identified, belonging to seven genera. Monomorium subopacum Smith and Tapinoma simrothi Krausse-Heldrungen (Hymenoptera: Formicidae) were the most abundant and behaviorally dominant ant species in the arganeraie. In addition, more specimens were captured in the semi-continental site than in the coastal area. However, no significant difference was observed in species richness, evenness, or diversity between both sites. Composition and community structure showed clear seasonal dynamics. The number of species, their abundance, their diversity, and their evenness per Argan tree were significantly dissimilar among seasons. The richness (except between summer and autumn), and the abundance and the evenness of ant species among communities, showed a significant difference between the dry period (summer and spring) and the rainy period (winter and autumn). Higher abundance and richness values occurred in the dry period of the year. Ant species dominance and seasonal climatic variations in the arganeraie might be among the main factors affecting the composition, structure, and foraging activity of ant communities. This study, together with recent findings on ant predation behavior below Argan trees, highlights the promising use of dominant ant species as potential agents of Mediterranean fruit fly bio-control in the Argan forest and surrounding ecosystems.
Web content outlier mining through mathematical approach and trust rating

In this Internet era, the WWW is flooded with voluminous amount of information with more replicated and irrelevant web pages. As the unnecessary and duplicated web pages increase the indexing space and time complexity, finding and removing these pages become a significant issue among the information retrieval and web mining research communities as most of the people rely on search engines to get the required information. Web content outlier mining plays a decisive role in covering all these aspects. Existing algorithms for web content outlier mining focuses attention on applying weightage only to structured documents whereas in this research work, a mathematical approach based on two way rectangular representations, signed approach of trust rating and correlation method is developed for retrieving right information without duplicates present in both structured and unstructured web documents.
Bayesian Real-time Optical Flow

Optical flow can be used to compute motion detection, time to collision, structure, focus of expansion as well as object segmentation. Unfortunately, most optical flow techniques do not provide accurate and dense measures that are useful for these types of computations. In addition, most techniques are also slow computationally. Albeit, one method proposed by Camus is able to perform optical flow computations in real-time capitalizing on redundancies in the computation and spatial-temporal sampling trade-offs. It is a simple technique based on simulating various motions and computing the SD (sum-difference) of patches. Its problem is that the produced field is not accurate and arbitrary in aperture and blank wall situations. We show that the simulating of various futures can be used as the factored samples that produce the likelihood probabilities that can be used in a particle filtering framework. Maximization/minimization or computing the expectations of the likelihood at a particular location does not necessarily produce the proper flow. We suggest that likelihoods are well behaved when their variance is small and these can be propagated firstly to address aperture problems and secondly to address the extended blank wall problem. We show this propagation with thresholded likelihood values and speculate on how the likelihood distributions can be integrated into an algorithm that has its basis in particle filtering.
The cone and the lazy bubble: two efficient alternatives between the point cursor and the bubble cursor

We evaluated two cursor designs in the continuum between the traditional point cursor and the bubble cursor by Grossman and Balakrishnan. The lazy bubble cursor expanded to envelop the closest target when the ratio of the distances to the closest and the second closest target was less than 1:2. In addition to this lazy behavior the cone cursor had a tail that stayed on the last enveloped target until the next target was enveloped. In an experiment with 18 participants we found that the bubble cursor was faster than our cursors that had smaller target activation areas but the difference remained very small. Of the bubble cursor variants the lazy bubble exhibited higher error rate than the other two. Thus, the winners on the objective metrics were the bubble cursor and the cone cursor. The lazy bubble cursor and the bubble cursor were preferred in subjective ratings.
Data driven approach for low-power pre-computation-based content addressable memory

Content addressable memory (CAM) plays an important role in the performance of many applications such as DCT transforms, processor caches, database accelerators, and network routers because it enables high-speed search operations with hardware acceleration. However, the power consumption of CAM is rather high because within CAM, searching is conducted in parallel for all registered words. Hence, pre-computation-based CAM, i.e., PB-CAM, was proposed in [1] in order to reduce the number of parallel-operated words by first filtering using a precomputation circuit called the parameter extractor. In this work, we propose a data driven algorithm — local grouping (LG) — to synthesize a parameter extractor for PB-CAM such that the registered data can be uniformly mapped to construct parameters; the cost of implementing the parameter extractor is also decreased. Moreover, we also adopt a discard and interlace (DAI) method that can further reduce the impact on non-uniform cases, which happens when most data are identical in some data blocks before LG processing. In experiments, average power consumption reduction of 60.4% was achieved and the number of CMOSs used was also reduced by 0.52%, when compared with the conventional gate-block selection algorithm [2].
Evaluation of psychology clinicians' attitudes towards computerised cognitive behaviour therapy, for use in their future clinical practice, with regard to treating those suffering from anxiety and depression.

iii Acknowledgements . vi Introduction . 1 Background of Problem . 1 Purpose of the Study . 3 Definition of Terms . 4 Literature Review . 6 Introduction . 6 Anxiety . 7 Available Treatments for Anxiety . 8 Depression . 12 Treatment as Usual . 16 Psychopharmacological Treatment . 16 Placebo Effect . 19 Cognitive Behavioural Therapy . 21 Focus . 22 Cognitive Model . 22 Purpose & Techniques of CBT . 23 Efficacy of CBT . 25 Efficacy of Computerized CBT Treatments . 30 Computerized Experience . 33 Computerized Disclosure Styles . 40 Computerized-­‐Cognitive Behavioral Therapy . 42 History of CCBT . 43 CCBT Components . 45 Efficacy of CCBT . 46 Cost Effectiveness of CCBT . 63 Generalized Attitudes towards CCBT . 64 Methodology . 78 Definitions of Important Terms . 78 Mixed Methods Research . 79 Design . 81 Participants . 82 Apparatus/ Materials . 83 Procedures . 84 Research Questions . 85 Ethical Considerations . 89 Results . 91 Quantitative Results . 91 General Questions . 98 Recommend Data . 99 Qualitative Results . 100 Recommend Data . 100 Why recommend Data . 100 Advantages of a client using CCBT. 103 CLINICIANS’ ATTITUDES TOWARDS CCBT vii i Disadvantages of a client using CCBT . 105 Client using CCBT, alone or with counselor . 107 Concluding comments . 108 Discussion . 111 Discussion of Findings . 111 Research Limitations . 116 Future Research . 117 Conclusions . 120 References . 124 Appendices . 132 Appendix A: Informed Consent . 132 Appendix B: Recruitment Email . 134 Appendix C: Survey . 135 CLINICIANS’ ATTITUDES TOWARDS CCBT Introduction Background of Problem The Internet has dramatically influenced how transactions and interactions take place around the world, making communication easier and breaking down boundaries. In December 2009, 74% of adult Americans aged 18 and older were using the Internet; of this 60% of adult Americans used broadband connections in their home and 55% were using the Internet wirelessly (Rainie, 2010). Of those surveyed, 93% in the 18-29 year old category were Internet users as well as 94% of college students (Rainie, 2010). The Internet and the technological advancements that have occurred have allowed individuals access a much greater amou
Microfluidic tools to investigate protein crystallization

Microfluidic Tools to Investigate Protein Crystallization A dissertation presented to the Faculty of the Graduate School of Arts and Sciences of Brandeis University, Waltham, Massachusetts by Michael Heymann There is no guarantee that a given protein has a crystalline phase, but even existence of an equilibrium crystalline phase is not sufficient for a crystal to form because the transformation of a protein solution to a crystal is governed by two non-equilibrium processes: nucleation and growth. Consequently, supersaturation kinetics play an essential role in crystallization and we argue that the optimal crystallization strategy should screen kinetic trajectories involving variables such as depth of supersaturation, duration of supersaturation, and sample volume. We have developed a Phase Chip technology based on emulsion microfluidics in which nanoliter volumes of protein solution are encapsulated in oil and stabilized by surfactant. Crystallization is a stochastic process; we experimentally optimize crystal nucleation and growth by generating hundreds of different kinetic paths simultaneously by varying both temperature and concentration of the protein solution. By using a dialysis membrane, one can optimize kinetic trajectories against various small molecule solutes, like salts, pH and surfactants. We also made the Phase Chip compatible with in situ diffraction studies by synchrotron diffraction. This entails finding conditions on-chip for which one crystal is grown per drop and then isolating hundreds of drops stored on a x-ray transparent microfluidic device. Single, non-cryoprotected crystals were too small and sensitive to radiation damage to collect a complete diffraction data set of isomorphous crystals at room temperature, but a full data set could be obtained by merging many single diffraction patterns.
A DTC Niche Plexus Surrounds the Germline Stem Cell Pool in Caenorhabditis elegans

The mesenchymal distal tip cell (DTC) provides the niche for Caenorhabditis elegans germline stem cells (GSCs). The DTC has a complex cellular architecture: its cell body caps the distal gonadal end and contacts germ cells extensively, but it also includes multiple cellular processes that extend along the germline tube and intercalate between germ cells. Here we use the lag-2 DTC promoter to drive expression of myristoylated GFP, which highlights DTC membranes and permits a more detailed view of DTC architecture. We find that short processes intercalating between germ cells contact more germ cells than seen previously. We define this region of extensive niche contact with germ cells as the DTC plexus. The extent of the DTC plexus corresponds well with the previously determined extent of the GSC pool. Moreover, expression of a differentiation marker increases as germ cells move out of the plexus. Maintenance of this DTC plexus depends on the presence of undifferentiated germ cells, suggesting that germ cell state can influence niche architecture. The roles of this DTC architecture remain an open question. One idea is that the DTC plexus delivers Notch signaling to the cluster of germ cells comprising the GSC pool; another idea is that the plexus anchors GSCs at the distal end.
Using word sense disambiguation for semantic role labeling

Word sense disambiguation (WSD) is the process of identifying the correct meaning, or sense of a word in a given context. Semantic role labeling (SRL) aims at identifying the relations between predicates in a sentence and their associated arguments. They are two fundamental tasks in natural language processing to find a sentence-level semantic representation. To date, they have mostly been modeled in isolation. However, this approach neglects logical constraints between them. In this work, we present some novel word sense features for SRL and find that they can improve the performance significantly. Later, we exploit pipeline strategies which verify the automatic all word sense disambiguation could help the semantic role labeling and vice versa. We further propose a Markov logic model that jointly labels semantic roles and disambiguates all word senses. We show that this joint approach leads to a higher performance for WSD and SRL than those pipeline approaches.
Understanding the Role of the Ventrolateral Prefrontal Cortex in Emotional Memory using Transcranial Direct Current Stimulation and Transcranial Magnetic Stimulation

Understanding the Role of the Ventrolateral Prefrontal Cortex in Emotional Memory using Transcranial Direct Current Stimulation & Transcranial Magnetic Stimulation by Ruth Rachel Weintraub-Brevda Advisor: Dr. Elizabeth F. Chua Emotional stimuli can have both beneficial and detrimental effects on memory, such that emotional stimuli can be distracting from current neutral working memory goals, while also leading to enhanced episodic memory for the distracting emotional stimuli. Recent evidence suggests that the ventrolateral prefrontal cortex (VLPFC) has multiple roles in the enhancing effects of emotion on memory through top-down/controlled processes, including 1) coping with negative distraction and 2) elaborative encoding of negative information. Additionally, previous research has alluded to hemispheric differences in the VLPFC (Chapter 1). However, previous research has been correlational, with no strong laterality tests of the VLPFC. Two experiments tested the roles of the left and right VLPFC in working memory and/or episodic memory tasks two using non-invasive brain stimulation techniques; transcranial direct current stimulation (tDCS) was used to increase cortical excitability of the VLFPC in Experiment 1 and transcranial magnetic stimulation (TMS) was used to inhibit the VLPFC in Experiment 2. Experiment 1 (Chapter 2) used tDCS to test whether the VLPFC is involved in working memory and episodic memory, and whether there are hemispheric differences. Results showed that the tDCS over left VLPFC led to improved working memory tasks with both neutral and negative distractors, and also indicated that there might be a greater demand on the
Proliferating Cell Nuclear Antigen Uses Two Distinct Modes to Move along DNA*

Proliferating cell nuclear antigen (PCNA) plays an important role in eukaryotic genomic maintenance by topologically binding DNA and recruiting replication and repair proteins. The ring-shaped protein forms a closed circle around double-stranded DNA and is able to move along the DNA in a random walk. The molecular nature of this diffusion process is poorly understood. We use single-molecule imaging to visualize the movement of individual, fluorescently labeled PCNA molecules along stretched DNA. Measurements of diffusional properties as a function of viscosity and protein size suggest that PCNA moves along DNA using two different sliding modes. Most of the time, the clamp moves while rotationally tracking the helical pitch of the DNA duplex. In a less frequently used second mode of diffusion, the movement of the protein is uncoupled from the helical pitch, and the clamp diffuses at much higher rates.
Instrumenting annotated programs

Instrumentation is commonly used to track application behavior: to collect program profiles; to monitor component health and performance; to aid in component testing; and more. Program annotation enables developers and tools to pass extra information to later stages of software development and execution. For example, the . NET runtime relies on annotations for a significant chunk of the services it provides. Both mechanisms are evolving into important parts of software development %, in the context of modern platforms such as Java and . NET.Instrumentation tools are generally not aware of the semantics of information passed via the annotation mechanism. This is especially true for post-compiler, e.g., run-time, instrumentation. The problem is that instrumentation may affect the correctness of annotations, rendering them invalid or misleading, and producing unforeseen side-effects during program execution. This problem has not been addressed so far.In this paper, we show the subtle interaction that takes place between annotations and instrumentation using several real-life examples. Many annotations are intended to provide information for the runtime; the virtual environment is a prominent annotation consumer, and must be aware of this conflict. It may also be required to provide runtime support to other annotation consumers. We propose an annotation taxonomy and show how instrumentation affects various annotations that were used in research and in industrial applications. We show how the annotations can expose enough information about themselves to prevent the instrumentation from accidentally corrupting the annotations. We demonstrate this approach on our annotations benchmark.
General Modeling of Layered Packet Video for Multicast Systems

Multicasting provides an economic way of distributing information from a sender to a group of receivers located at different sites of the networks. However, heterogeneous networks and variable traffic loads make the multicast more problematic. An efficient solution to the problem is to transmit layered signals, a base layer and several progressive enhancement layers. The local networks simply select the number of layers, according to the capacities. In the paper, a general model of layered packet video is proposed. Two layered compression methods are analysed. The examples show that the general model is suitable to describe layered video, and the model is helpful to design required layers. Layered packet loss rate is suggested as a measure of communication quality requirements. Numerical results show that layered video is more sensitive to the packet dropping than unlayered video and unequal loss protection is more efficient than equal protection. Keyword: layered video, multicasting, forward error correction codes (FEC).