Miracle-dz/UniFAR-FTUs huggingface dataset:
On detecting harmonic oscillations

In this paper, we focus on the following testing problem: assume that we are given observations of a real-valued signal along the grid 0, 1, . , N − 1, corrupted by white Gaussian noise. We want to distinguish between two hypotheses: (a) the signal is a nuisance – a linear combination of dn harmonic oscillations of known frequencies, and (b) signal is the sum of a nuisance and a linear combination of a given number ds of harmonic oscillations with unknown frequencies, and such that the distance (measured in the uniform norm on the grid) between the signal and the set of nuisances is at least ρ > 0. We propose a computationally efficient test for distinguishing between (a) and (b) and show that its “resolution” (the smallest value of ρ for which (a) and (b) are distinguished with a given confidence 1 − α) is O(p ln(N/α)/N), with the hidden factor depending solely on dn and ds and independent of the frequencies in question. We show that this resolution, up to a factor which is polynomial in dn, ds and logarithmic in N, is the best possible under circumstances. We further extend the outlined results to the case of nuisances and signals close to linear combinations of harmonic oscillations, and provide illustrative numerical results.
Medical Image Colorization using Optimization Technique

Colorization is a term used to describe a computerized process for adding color to black and white pictures, movies or TV programs. This process can also be used to convert the gray scale medical images to their colorized version, as color increases the visual appeal of an image and it also makes medical visualization more attractive. In the medical field, there used plenty of images especially X-Rays like dental, chest, leg, hand X-Rays and MRI Images. In this paper, we apply colorization based on optimization to colorize medical images and also evaluate its performance in terms of information loss using three proposed correlation coefficient parameters.
EntityBases: Compiling, Organizing and Querying Massive Entity Repositories

The current approaches for linking information across sources, often called record linkage, require finding common attributes between the sources and comparing the records using those attributes. This often leads to unsatisfactory results because the sources are often missing information or contain incorrect or outdated information. We are addressing this problem by developing the technology to build massive entity knowledgebases, which we call EntityBases. The key idea is to create a comprehensive knowledgebase for the entities of interest (e.g., companies). In order to build such a knowledge base, we must address the issues of linking entities with multi-valued attributes obtained from heterogeneous sources and providing a virtual repository that can be efficiently queried. This paper describes how we have addressed these issues and shows how an EntityBaseTM can be used for understanding and linking text documents.
Automatic Removal of “ Garbage Strings ” in OCR Text : An Implementation

In many of our OCR/IR experiments, we found that “garbage strings” generated by OCR devices caused complications for information retrieval systems. In particular, index sizes more than doubled, formulas used to determine statistical evidence were distorted, and document ranking was affected. To help correct these problems, we implemented a set of rules to automatically “clean up” the OCR text prior to indexing. We have applied this system, called rmgarbage, in several of our experiments and it is currently being applied by the Department of Energy (DOE) to their large scale Licensing Support Network (LSN) which consists primarily of OCR text.
Cache management for mobile databases: design and evaluation

Communication between mobile clients and database servers in a mobile computing environment is via wireless channels with low bandwidth and low reliability. A mobile client could cache its frequently accessed database items into its local storage in order to improve performance of database queries and availability of database items for query processing during disconnection. We describe a mobile caching mechanism for a mobile environment utilizing point to point communication paradigm. In particular, we investigate issues on caching granularity, coherence strategy, and replacement policy of mobile caching. Via a detailed simulation model, we compare our proposed caching mechanism with conventional ones and discover that our mobile caching mechanism outperforms conventional ones in most situations.
An Optimizing Method for Structuring Inferentially Linked Discourse

In recent times, there has been an increase in the number of Natural Language Generation systems that take into consideration a user's inferences. The statements generated by these systems are typically connected by inferential links, which are opportunistic in nature. In this paper, we describe a discourse structuring mechanism which organizes inferentially linked statements as well as statements connected by certain prescriptive links. Our mechanism first extracts relations and constraints from the output of a discourse planner. It then uses this information to build a directed graph whose nodes are rhetorical devices, and whose links are the relations between these devices. The mechanism then applies a search procedure to optimize the traversal through the graph. This process generates an ordered set of linear discourse sequences, where the elements of each sequence are maximally connected. Our mechanism has been implemented as the discourse organization component of a system called WISHFUL which generates concept explanations.
Unit Testing Concurrent Java Programs

Conventional unit-testing practices focus on testing small units of programs sequentially and are very likely to miss concurrent bugs such as race conditions, deadlocks and memory inconsistencies even when done extensively. They are not suitable for unit testing multithreaded programs. This paper outlines guidelines for writing effective unit tests for concurrent Java programs. It also explores and compares the frameworks available currently for writing such tests. The most widely used unit testing frameworks for Java - TestNG and JUnit - do not provide good support for testing concurrent issues. Other frameworks such as MultiThreadedTC and Concurrency Analyzer allow the coordination of unit test’s threads to produce a specific scheduling. However, it is the responsibility of the developer to test for all possible interleavings and scheduling of threads to unearth existing bugs and hence they are a deterministic way of approaching the problem. This paper presents an alternate approach to the problem by integrating TestNG with the Java Path Finder(JPF) software model checker. JPF can be used to identify all possible interleavings of threads across execution paths to non deterministically detect concurrent bugs. In addition to this, it detects deadlocks by checking if all the threads have reached a blocked state at any point of execution. Adoption of such practices have helped in reducing concurrency related issues in our platforms to a great extent. It has helped in identifying issues early on in the development cycle and better reliability. Many open source platforms such as Ehcache run concurrent unit tests as part of their development process to maintain code quality. This, augmented with stress testing concurrency tools greatly help in improving the quality of code.
Use of regional climate model simulations as input for hydrological models for the Hindukush-Karakorum-Himalaya region

The most important climatological inputs required for the calibration and validation of hydrological models are temperature and precipitation that can be derived from observational records or alternatively from regional climate models (RCMs). In this paper, meteorological station observations and results of the PRECIS (Providing REgional Climate for Impact Studies) RCM driven by the outputs of reanalysis ERA 40 data and HadAM3P general circulation model (GCM) results are used as input in the hydrological model. The objective is to investigate the effect of precipitation and temperature simulated with the PRECIS RCM nested in these two data sets on discharge simulated with the HBV model for three river basins in the Hindukush-Karakorum-Himalaya (HKH) region. Six HBV model experiments are designed: HBV-Met, HBV-ERA and HBV-Had, HBV-MetCRU-corrected, HBV-ERABenchmark and HBV-HadBenchmark where HBV is driven by meteorological stations data, data from PRECIS nested in ERA-40 and HadAM3P, meteorological stations CRU corrected data, ERA-40 reanalysis and HadAM3P GCM data, respectively. Present day PRECIS simulations possess strong capacity to simulate spatial patterns of present day climate characteristics. However, also some quantitative biases exist in the HKH region, where PRECIS RCM simulations underestimate temperature and overestimate precipitation with respect to CRU observations. The calibration and validation results of the HBV model experiments show that the performance of HBV-Met is better than the HBV models driven by other data sources. However, using input data series from sources different from the data used in the model calibration shows that HBV-Had is more efficient than other models and HBV-Met has the least absolute relative error with respect to all other models. The uncertainties are higher in least efficient models (i.e. HBV-MetCRU-corrected and HBV-ERABenchmark) where the model parameters are also unrealistic. In terms of both robustness and uncertainty ranges the HBV models calibrated with PRECIS output performed better than other calibrated models except for HBV-Met which has shown a higher robustness. This suggests that in data sparse regions such as the HKH region data from regional climate models may be used as input in hydrological models for climate scenarios studies.
BRIDGES: A System to Enable Creation of Engaging Data Structures Assignments with Real-World Data and Visualizations

Although undergraduate enrollment in Computer Science has remained strong and seen substantial increases in the past decade, retention of majors remains a significant concern, particularly for students at the freshman and sophomore level that are tackling foundational courses on algorithms and data structures. In this work, we present BRIDGES, a software infrastructure designed to enable the creation of more engaging assignments in introductory data structures courses by providing students with a simplified API that allows them to populate their own data structure implementations with live, real-world, and interesting data sets, such as those from popular social networks (e.g., Twitter, Facebook). BRIDGES also provides the ability for students to create and explore {\em visualizations} of the execution of the data structures that they construct in their course assignments, which can promote better understanding of the data structure and its underlying algorithms; these visualizations can be easily shared via a weblink with peers, family, and instructional staff. In this paper, we present the BRIDGES system, its design, architecture and its use in our data structures course over two semesters.
From Nondeterministic Buchi and Streett Automata to Deterministic Parity Automata

In this paper we revisit Safra's determinization constructions. We show how to construct deterministic automata with fewer states and, most importantly, parity acceptance conditions. Specifically, starting from a nondeterministic Buchi automaton with n states our construction yields a deterministic parity automaton with n<sup>2n+2</sup> states and index 2n (instead of a Rabin automaton with (12)<sup>n</sup>n<sup>2n</sup> states and n pairs). Starting from a nondeterministic Streett automaton with n states and k pairs our construction yields a deterministic parity automaton with n<sup>n(k+2)+2</sup>(k+1)<sup>2n(K+1)</sup> states and index 2n(k+1) (instead of a Rabin automaton with (12)<sup>n(k+1)</sup>n <sup>n(k+2)</sup>(k+1)<sup>2n(k+1)</sup> states and n(k+1) pairs). The parity condition is much simpler than the Rabin condition. In applications such as solving games and emptiness of tree automata handling the Rabin condition involves an additional multiplier of n<sup>2</sup>n! (or(n(k+1))<sup>2</sup>(n(k+1))! in the case of Streett) which is saved using our construction
Enhanced classical dysphonia measures and sparse regression for telemonitoring of Parkinson's disease progression

Dysphonia measures are signal processing algorithms that offer an objective method for characterizing voice disorders from recorded speech signals. In this paper, we study disordered voices of people with Parkinson's disease (PD). Here, we demonstrate that a simple logarithmic transformation of these dysphonia measures can significantly enhance their potential for identifying subtle changes in PD symptoms. The superiority of the log-transformed measures is reflected in feature selection results using Bayesian Least Absolute Shrinkage and Selection Operator (LASSO) linear regression. We demonstrate the effectiveness of this enhancement in the emerging application of automated characterization of PD symptom progression from voice signals, rated on the Unified Parkinson's Disease Rating Scale (UPDRS), the gold standard clinical metric for PD. Using least squares regression, we show that UPDRS can be accurately predicted to within six points of the clinicians' observations.
Two algorithms to segment white Gaussian data with piecewise constant variances

Two new algorithms are presented for the segmentation of a white Gaussian-distributed time series having unknown but piecewise-constant variances. The first "sequential/minimum description length (MDL)" idea includes a rough parsing via the GLR, a penalization of segmentations having too many parts via MDL, and an optional refinement stage. The second "Gibbs sampling" approach is Bayesian and develops a Monte Carlo estimator. From simulation, it appears that both schemes are very accurate in terms of their segmentation but that the sequential/MDL approach is orders of magnitude lower in its computational needs. The Gibbs approach can, however, be useful and efficient as a final post-processing step. Both approaches (and a hybrid) are compared with several algorithms from the literature.
Enhanced Method for Robust Mood Extraction from Skin Conductance

One of the key challenges in affective computing is the interpretation of physiological signals into affect. Mood, as a subclass of affect, is known to be reflected in skin conductance. While most reports concern strictly controlled laboratory settings, daily life situations pose more challenges in interpreting physiology because more bodily and cognitive processes that influence skin conductivity are involved; for example temperature regulation or physical and mental activity. Existing techniques to reduce the effects of these processes in order to extract mood from skin conductance are rather crude and leave room for improvement. We introduce a more sophisticated method based on skin conductance response subtraction that provides better resemblance with mood. Validation of our method, using comparison with two alternative methods, shows our method excels in differentiation between positive and negative moods from skin conductance. Our method thereby enhances mood extraction from skin conductance, thus improving robustness of mood
Behavior Prediction Based on Obstacle Motion Patterns in Dynamically Changing Environments

This paper proposes a behavior prediction method for navigation application in dynamically changing environments, which predicts obstacle behaviors based on learned obstacle motion patterns (OMP) from observed obstacle motion trajectories. A multi-level prediction model is then proposed that predicts long-term or short-term obstacle behaviors. Simulation results show that it works well in a complex environment and the prediction is consistent with actual behaviors.
Nematode sperm maturation triggered by protease involves sperm-secreted serine protease inhibitor (Serpin)

Spermiogenesis is a series of poorly understood morphological, physiological and biochemical processes that occur during the transition of immotile spermatids into motile, fertilization-competent spermatozoa. Here, we identified a Serpin (serine protease inhibitor) family protein (As_SRP-1) that is secreted from spermatids during nematode Ascaris suum spermiogenesis (also called sperm activation) and we showed that As_SRP-1 has two major functions. First, As_SRP-1 functions in cis to support major sperm protein (MSP)-based cytoskeletal assembly in the spermatid that releases it, thereby facilitating sperm motility acquisition. Second, As_SRP-1 released from an activated sperm inhibits, in trans, the activation of surrounding spermatids by inhibiting vas deferens-derived As_TRY-5, a trypsin-like serine protease necessary for sperm activation. Because vesicular exocytosis is necessary to create fertilization-competent sperm in many animal species, components released during this process might be more important modulators of the physiology and behavior of surrounding sperm than was previously appreciated.
Instruction fetch architectures and code layout optimizations

The design of higher performance processors has been following two major trends: increasing the pipeline depth to allow faster clock rates, and widening the pipeline to allow parallel execution of more instructions. Designing a higher performance processor implies balancing all the pipeline stages to ensure that overall performance is not dominated by any of them. This means that a faster execution engine also requires a faster fetch engine, to ensure that it is possible to read and decode enough instructions to keep the pipeline full and the functional units busy. This paper explores the challenges faced by the instruction fetch stage for a variety of processor designs, from early pipelined processors, to the more aggressive wide issue superscalars. We describe the different fetch engines proposed in the literature, the performance issues involved, and some of the proposed improvements. We also show how compiler techniques that optimize the layout of the code in memory can be used to improve the fetch performance of the different engines described Overall, we show how instruction fetch has evolved from fetching one instruction every few cycles, to fetching one instruction per cycle, to fetching a full basic block per cycle, to several basic blocks per cycle: the evolution of the mechanism surrounding the instruction cache, and the different compiler optimizations used to better employ these mechanisms.
Self reported stressful life events and exacerbations in multiple sclerosis:prospective study

Abstract Objective To study the relation between self reported stressful life events not related to multiple sclerosis and the occurrence of exacerbations in relapsing-remitting multiple sclerosis. Design Longitudinal, prospective cohort study. Setting Outpatient clinic of department of neurology in the Netherlands. Participants Patients aged 18-55 with relapsing-remitting multiple sclerosis, who could walk with a cane or better (score of 0-6.0 on the expanded disability status scale), and had had at least two exacerbations in 24 months before inclusion in the study. Patients with other serious conditions were excluded. Main outcome measure The risk of increased disease activity as measured by the occurrence of exacerbations after weeks with stressful events. Results Seventy out of 73 included patients (96%) reported at least one stressful event. In total, 457 stressful life events were reported that were not related to multiple sclerosis. Average follow up time was 1.4 years. Throughout the study, 134 exacerbations occurred in 56 patients and 136 infections occurred in 57 patients. Cox regression analysis with time dependent variables showed that stress was associated with a doubling of the exacerbation rate (relative risk 2.2, 95% confidence interval 1.2 to 4.0, P = 0.014) during the subsequent four weeks. Infections were associated with a threefold increase in the risk of exacerbation, but this effect was found to be independent of experienced stress. Conclusion Stressful events were associated with increased exacerbations in relapsing-remitting multiple sclerosis. This association was independent of the triggering effect of infections on exacerbations of multiple sclerosis.
Towards a standard battery of microsatellite markers for the analysis of the Leishmania donovani complex

Abstract The investigation of microsatellite markers has recently superseded that of isoenzymes for many population-biology applications. Microsatellites have the advantages of being dominant, neutral, highly polymorphic and easily scored by high-throughput methods. However, it is necessary to develop a new panel of markers for each group of organisms of interest. Previously, only about 5% of the markers that amplify Leishmania major microsatellite loci were also found to amplify L. donovani loci. A panel of 20 microsatellite markers that are polymorphic in L. donovani and L. infantum has now been developed, using a rapid-enrichment method that will be suitable for developing libraries of markers for other trypanosomatid species. This is the first panel of polymorphic microsatellite markers, to be isolated de novo from any species of Leishmania, that is large enough for population-biology applications.
Tattooed female bodies: Considerations from the literature

In this article, we present an overview of literature that explores tattooed female bodies. Focusing particularly on literature on femininities and embodiment, we consider how tattooed women’s bodies are read culturally, and the implications of this reading for our further understanding of the social construction of femininities. We explore how hegemonic notions of femininities and embodiment intersect in our cultural reading of women’s tattooed bodies. To conclude, we look at how femininities and embodiment are important in under- standing how femininity is constituted, how women experience their tattooed bodies differently, and what this means in terms of how the body is read culturally.
Reconstituting the urban through community-articulated digital environments

In this paper, I introduce two approaches to the design of digital environments for community expression, and point to the implications of these designs on existing urban models which negate the value that digital technology can have in re-energizing community. My specific focus is on design approaches toward spatially-bounded, cultural communities in an internet proliferated era. First, I introduce Village Voice, a project which originates from my M.S work at the MIT Media Laboratory. The former project involved the design of a digital environment that could enable the sharing of knowledge, story, tradition, and concern across a physically bounded refugee community located within the Boston-area. Village Voice is based on a unique architecture, and raises provocative questions relative to important issues of public space and urbanism. Second, I introduce Basin Bytes, the subject of my ongoing doctoral research at the Harvard Graduate School of Design. This work is focused on the creation of an infrastructure to unite a large resource basin that currently maintains very few internal connections. The subject of the study here is whether such an important new technological space can be mediated by a socially aware intelligent agent.