Miracle-dz/UniFAR-FTUs huggingface dataset:
Cache Design for Embedded Real-Time Systems

Caches have long been a mechanism for speeding memory access and are popular in embedded hardware architectures from microcontrollers to core-based ASIC designs. However, caches are considered ill-suited for embedded real-time systems because they provide a probabilistic performance boost— a cache may or may not contain the desired data at an y given moment. Analysis that guarantees when an item will or will not be in the cache has proven difficult, so many real-time systems simply disable caching and schedule tasks based on worst-case memory access time. Yet there are several cache organizations that provide the benefit of caching without the real-time drawbacks of hardware-managed caches. These are software-managed caches, and several different examples can be found, from DSP-style on-chip RAM to academic designs. This paper compares the operation and organization of caches as found in general-purpose processors, microcontrollers, and DSPs; it also discusses designs for embedded realtime systems.
Mobile App Retrieval for Social Media Users via Inference of Implicit Intent in Social Media Text

People often implicitly or explicitly express their needs in social media in the form of "user status text". Such text can be very useful for service providers and product manufacturers to proactively provide relevant services or products that satisfy people's immediate needs. In this paper, we study how to infer a user's intent based on the user's "status text" and retrieve relevant mobile apps that may satisfy the user's needs. We address this problem by framing it as a new entity retrieval task where the query is a user's status text and the entities to be retrieved are mobile apps. We first propose a novel approach that generates a new representation for each query. Our key idea is to leverage social media to build parallel corpora that contain implicit intention text and the corresponding explicit intention text. Specifically, we model various user intentions in social media text using topic models, and we predict user intention in a query that contains implicit intention. Then, we retrieve relevant mobile apps with the predicted user intention. We evaluate the mobile app retrieval task using a new data set we create. Experiment results indicate that the proposed model is effective and outperforms the state-of-the-art retrieval models.
Evaluation of Optimization Methods for Nonrigid Medical Image Registration Using Mutual Information and B-Splines

A popular technique for nonrigid registration of medical images is based on the maximization of their mutual information, in combination with a deformation field parameterized by cubic B-splines. The coordinate mapping that relates the two images is found using an iterative optimization procedure. This work compares the performance of eight optimization methods: gradient descent (with two different step size selection algorithms), quasi-Newton, nonlinear conjugate gradient, Kiefer-Wolfowitz, simultaneous perturbation, Robbins-Monro, and evolution strategy. Special attention is paid to computation time reduction by using fewer voxels to calculate the cost function and its derivatives. The optimization methods are tested on manually deformed CT images of the heart, on follow-up CT chest scans, and on MR scans of the prostate acquired using a BFFE, Tl, and T2 protocol. Registration accuracy is assessed by computing the overlap of segmented edges. Precision and convergence properties are studied by comparing deformation fields. The results show that the Robbins-Monro method is the best choice in most applications. With this approach, the computation time per iteration can be lowered approximately 500 times without affecting the rate of convergence by using a small subset of the image, randomly selected in every iteration, to compute the derivative of the mutual information. From the other methods the quasi-Newton and the nonlinear conjugate gradient method achieve a slightly higher precision, at the price of larger computation times.
Network Deficiency Exacerbates Impairment in a Mouse Model of Retinal Degeneration

Neural oscillations play an important role in normal brain activity, but also manifest during Parkinson’s disease, epilepsy, and other pathological conditions. The contribution of these aberrant oscillations to the function of the surviving brain remains unclear. In recording from retina in a mouse model of retinal degeneration (RD), we found that the incidence of oscillatory activity varied across different cell classes, evidence that some retinal networks are more affected by functional changes than others. This aberrant activity was driven by an independent inhibitory amacrine cell oscillator. By stimulating the surviving circuitry at different stages of the neurodegenerative process, we found that this dystrophic oscillator further compromises the function of the retina. These data reveal that retinal remodeling can exacerbate the visual deficit, and that aberrant synaptic activity could be targeted for RD treatment.
On Some Distributions and Their Pattern Entropies

We study the block entropy of patterns of sequences generated by uniform and monotonic memoryless source distributions. In the former case, the pattern entropy decreases the most from the memoryless entropy, and in the latter the least. General upper and lower bounds are presented and then applied to these distributions. Tighter bounds are derived for a uniform case. All bounds provide almost precise characterization of the pattern entropies of uniform distributions, distributions over the integers, and the geometric distribution. Of specific interest are distributions over the integers that have infinite entropy rates in the memoryless case but bounded pattern block entropies
Evaluating the toxicity of nitrogen-functionalized carbon nanotubes

ii To T.K. iii ACKNOWLEDGMENTS I have many people to acknowledge for their support and guidance in this project. I'd like to thank my advisor, Dr. Timothy Mattes, who provided me with the opportunity to be a part of this research endeavor. Thank you to Dr. David Cwiertny and Dr. Richard Valentine, who also served as mentors to me throughout this project. I would like to thank my labmates in the Mattes Research group, as well as J.D. for his assistance. Thank you to my classmates in the EES program, as well as the faculty and staff in the Civil and Environmental Engineering Department. Finally, I would like to thank my family and R.D. for their constant encouragement and support throughout this journey.
HiDb : A Haskell In-Memory Relational Database

We describe our experience implementing an in-memory relational database in Haskell that supports the standard CRUD (create, read, update, delete) operations while providing the requisite ACID (atomicity, consistency, isolation, durability) guarantees. We rely on Haskell’s STM module to provide atomicity and isolation. We use a combination of STM, Haskell’s type system, and dynamic type-checking in order to enforce consistency. We implement undo-redo logging and eventual disk writes to provide durability. We also provide a Haskell library which clients can use to connect to and send transactions to the database. We found that while the STM module greatly eased the implementation of transactions, the lack of support for de-serializing data into a dynamic type was not ideal.
xxx SEISMIC DATA FILTERING WITH HIERARCHICAL LAPPED TRANSFORMS AND HIDDEN MARKOV MODELS

We propose a method for uncoherent noise removal in geophysical data. The Multiple Wavelet Stacking is based on a concurrent use of wavelet-based shrinkage and data and time-scale dependent threshold choice. Since one singular wavelet does not match all the time-varying properties of a signal, the simultaneous use of several wavelets is able to lower some shrinkage shortcomings, such as wavelet dependency, and to further reduce the residual noises. Motivation and related works Wavelet transforms have emerged as efficient tools for signa l separation and noise filtering in several geophysical applications. In heavy noise conditions, wavelet-based techniques generally owe their robustness to their attractive time-scale proper ties. Wavelet based denoising, or wavelet shrinkage [Miao and Cheadle, 1998], arises from the work of D. Donoho, based on the energy compaction properties of these time-scale operators [Donoho, 1995]. With the most widely used signal model [Ulrych et al., 1999], let represent an actual geophysical record. It can be decomposed in an underlying signal , and two noise components and , respectively coherent and random:
Student Response to Teaching of Memory Cues and Resumption Strategies in Computer Science Classes

Programming is a creative process that requires the ability to concentrate and juggle multiple concepts simultaneously in one's mind. Existing research shows there is a tangible cost when a programmer is interrupted as the programmer must recover the context of his work and refocus on the task at hand. However, CS students are rarely taught about interruptions and how to manage them. Instead, teaching tends to focus only on technical concepts. In addition, there is little research on interruptions with respect to CS students. Therefore, our research examines what happens when CS students are taught about interruptions and how to cope with them. The objective of this paper is to determine if CS students are affected by interruptions, what knowledge CS students possess regarding memory cues and resumption strategies, and what their opinion is of this material. We conducted a study with approximately two-hundred undergraduate CS students to answer these questions. Our study was comprised of an initial questionnaire, a seminar on memory cues and resumption strategies, and a follow-up questionnaire. Our results demonstrate that CS students are affected by interruptions, but 73% of students report not knowing methods to mitigate them. After learning about memory cues and resumption strategies, students report that the material was useful and that they want to study it. Their most significant feedback is that they have a strong desire to include these techniques in CS curriculums, reporting a mean score of 7.78 out of 10, where 0 signifies strong disagreement and 10 signifies strong agreement.
An Adaptable Application Offloading Scheme Based on Application Behavior

The advancement of personal devices such as PDAs and mobile phones become ubiquitous and their increasing computing capabilities allow users to perform tasks that used to be performed on workstations. However, we cannot expect to run all tasks on top of personal devices because of the limited resources. Application offloading allow us to overcome this issue by porting part of an application to a nearby server or workstation with more capabilities. In this paper we present a new application offloading mechanism to perform offloading based on the execution history of applications, and adaptable to the current conditions of the environment and device. We record the consumed resources and the state of the device and surrogates, and we use that information to perform an adaptable offloading. We show that our scheme can prevent the overhead of profiling and also reduce the execution time of an application against pure runtime offloading.
Suppression of human lens epithelial cell proliferation by proteasome inhibition, a potential defense against posterior capsular opacification.

PURPOSE Posterior capsular opacification (PCO) is caused by the proliferation, migration, and epithelial-mesenchymal transition (EMT) of the remaining lens epithelial cells (LECs) after cataract surgery. Studies have shown that proteasome inhibition interferes with EMT and remodeling of the extracellular matrix. This study was conducted to investigate suppression of LEC proliferation by proteasome inhibition and its signaling pathway. METHODS HLE B-3 cells and human lens epithelium explants from 17- to 20-week fetal lenses were cultured and treated with TGF-beta2 (1 or 10 ng/mL), FGF-2 (20 or 50 ng/mL), HGF (10 ng/mL) and 5 or 10 muM MG132. LEC proliferation was determined using both the WST-1 reagent and proliferating cell nuclear antigen (PCNA) expression. Protein expression was observed by Western blot analysis. Transfection with p21/p27 siRNA was performed to evaluate the mechanism of the antiproliferative effect of proteasome inhibition. RESULTS TGF-beta2 suppressed proliferation of HLE B-3 cells, whereas FGF-2 and HGF enhanced proliferation. Proliferation suppression by TGF-beta2 was blocked by adding FGF-2 or HGF. Proteasome inhibitor (MG132) treatment strongly inhibited the proliferation of LECs, either alone or in the presence of TGF-beta2, FGF-2, or HGF. These findings were confirmed by observing PCNA expression. Similar results were obtained with primary human LECs. Expression of cell cycle regulatory proteins was determined to evaluate the mechanism of the antiproliferative activity of proteasome inhibition. MG132 caused a significant increase in p21 and p27 protein and decrease in CDK2, but no change in p53, p57, CDK4, or CDK6 protein. The antiproliferative effect of MG132 was significantly reversed in samples transfected with p21 and p27 siRNA, which reduced p21 and p27 protein expression to very low levels that remained below basal control levels, even after treatment with MG132. CONCLUSIONS Proteasome inhibition decreases the proliferation of LECs in the presence or absence of TGF-beta2, FGF-2, and HGF. This process is mediated in part by an increase in p21 and p27 proteins. These findings suggest that proteasome inhibitors are good candidates for blocking development of PCO.
Learning metrics for diversity in instance retrieval

Instance retrieval (IR) is the problem of retrieving specific instances of a particular object, like a monument, from a collection of images. Currently, the most popular methods for IR use Bag of words (BoW) features for retrieval. However, a prominent problem for IR remains the tendency of BoW based methods to retrieve near-identical images as most relevant results. In this paper, we define diversity in IR as variation of physical properties among most relevant retrieved results for a query image. To achieve this, we propose both an ITML algorithm that re-fashions the BoW feature space into one that appreciates diversity better, and a measure to evaluate diversity in retrieval results for IR applications. Additionally, we also generate 200 hand-labeled images from the Paris dataset, for use in further research in this area. Experiments on the popular Paris dataset show that our method outperforms the standard BoW model in many cases.
A Novel Broadband UHF RFID Tag Antenna Mountable on Metallic Surface

A novel broadband UHF RFID tag antenna mountable on metallic surface is presented. The structures of T-matching network and double symmetrical radiating patches shorted to ground plane are employed. The proposed antenna has a half power bandwidth of 11.4% when placed in free air and covers two major segments of the UHF RFID band when mounted on metallic surface. The proposed antenna also has good radiation characteristics and cross-polarization performances in both conditions. The results show that the proposed antenna can work not only in free air but also on metallic surface for UHF RFID band.
Using Phrasal Verbs as an Index to Distinguish Text Genres

Previous studies have shown that text genres can be computationally distinguished by sophisticated computational and statistical methods. The current study adds to the previous body of work by incorporating phrasal verbs as a text genre identifier. Results indicate that phrasal verbs significantly distinguish between both the spoken/written and formal/informal dimensions, with considerably less computational expense than previous studies. Phrasal verbs also indicate degree of spokenness and formality that is significantly similar to previous computationally expensive studies. The study offers useful findings for text-identification research and for materials developers in the field of English as a second language.
Dry Bias and Variability in Vaisala RS80-H Radiosondes: The ARM Experience

Thousands of comparisons between total precipitable water vapor (PWV) obtained from radiosonde (Vaisala RS80-H) profiles and PWV retrieved from a collocated microwave radiometer (MWR) were made at the Atmospheric Radiation Measurement (ARM) Program’s Southern Great Plains Cloud and Radiation Testbed (SGP CART) site in northern Oklahoma from 1994 to 2000. These comparisons show that the RS80-H radiosonde has an approximate 5% dry bias compared to the MWR. This observation is consistent with interpretations of Vaisala RS80 radiosonde data obtained during the Tropical Ocean Global Atmosphere Coupled Ocean‐Atmosphere Response Experiment (TOGA COARE). In addition to the dry bias, analysis of the PWV comparisons as well as of data obtained from dual-sonde soundings done at the SGP show that the calibration of the radiosonde humidity measurements varies considerably both when the radiosondes come from different calibration batches and when the radiosondes come from the same calibration batch. This variability can result in peak-to-peak differences between radiosondes of greater than 25% in PWV. Because accurate representation of the vertical profile of water vapor is critical for ARM’s science objectives, an empirical method for correcting the radiosonde humidity profiles is developed based on a constant scaling factor. By using an independent set of observations and radiative transfer models to test the correction, it is shown that the constant humidity scaling method appears both to improve the accuracy and reduce the uncertainty of the radiosonde data. The ARM data are also used to examine a different, physically based, correction scheme that was developed recently by scientists from Vaisala and the National Center for Atmospheric Research (NCAR). This scheme, which addresses the dry bias problem as well as other calibration-related problems with the RS80-H sensor, results in excellent agreement between the PWV retrieved from the MWR and integrated from the corrected radiosonde. However, because the physically based correction scheme does not address the apparently random calibration variations observed, it does not reduce the variability either between radiosonde calibration batches or within individual calibration batches.
Low power design of RFID tags

Low-power design is essential for passive RFID tags to achieve expected level of sensitivity. Considering the mechanism of the passive tags powered, a low peak power is also important. This paper is focused on optimization on peak power. A tag IC is also presented. The IC, which is compatible with the EPC C1G2 RFID protocol, was designed and fabricated successfully by using a 0. 18µm process, with a tested sensitivity of −dBm.
Synthesis and Biological Activities of 4-Aminoantipyrine Derivatives Derived from Betti-Type Reaction

The present work deals with the synthesis and evaluation of biological activities of 4-aminoantipyrine derivatives derived from a three-component Betti reaction. The synthesis was initiated by the condensation of aromatic aldehyde, 4-aminoantipyrine, and 8-hydroxyquinoline in presence of fluorite as catalyst in a simple one-step protocol. The reactions were stirred at room temperature for 10–15 min achieving 92–95% yield. The structures of synthesized derivatives were established on the basis of spectroscopic and elemental analysis. All derivatives 4(a–h) were screened in vivo and in vitro for anti-inflammatory and anthelmintic activity against a reference drug, Diclofenac and Albendazole, respectively. The screening results show that compounds 4c, 4d, 4f, and 4h were found to possess potential anti-inflammatory activity while compounds 4a, 4b, 4e, and 4g are potent anthelmintic agents when compared with reference drugs, respectively. The bioactivity of these derivatives has also been evaluated with respect to Lipinski's rule of five using molinspiration cheminformatics software.
Receptive field structure of flow detectors for heading perception

Observer translation relative to the world creates image flow that expands from the observer's direction of translation (heading) from which the observer can recover heading direction. Yet, the image flow is often more complex, depending on rotation of the eye, scene layout and translation velocity. A number of models [1-4] have been proposed on how the human visual system extracts heading from flow in a neurophysiologically plausible way. These models represent heading by a set of neurons that respond to large image flow patterns and receive input from motion sensed at different image locations. We analysed these models to determine the exact receptive field of these heading detectors. We find most models predict that, contrary to widespread believe, the contributing motion sensors have a preferred motion directed circularly rather than radially around the detector's preferred heading. Moreover, the results suggest to look for more refined structure within the circular flow, such as bi-circularity or local motion-opponency.
Microstructures and Mechanical Properties of Co-Cr Dental Alloys Fabricated by Three CAD/CAM-Based Processing Techniques

The microstructures and mechanical properties of cobalt-chromium (Co-Cr) alloys produced by three CAD/CAM-based processing techniques were investigated in comparison with those produced by the traditional casting technique. Four groups of disc- (microstructures) or dumbbell- (mechanical properties) specimens made of Co-Cr alloys were prepared using casting (CS), milling (ML), selective laser melting (SLM), and milling/post-sintering (ML/PS). For each technique, the corresponding commercial alloy material was used. The microstructures of the specimens were evaluated via X-ray diffractometry, optical and scanning electron microscopy with energy-dispersive X-ray spectroscopy, and electron backscattered diffraction pattern analysis. The mechanical properties were evaluated using a tensile test according to ISO 22674 (n = 6). The microstructure of the alloys was strongly influenced by the manufacturing processes. Overall, the SLM group showed superior mechanical properties, the ML/PS group being nearly comparable. The mechanical properties of the ML group were inferior to those of the CS group. The microstructures and mechanical properties of Co-Cr alloys were greatly dependent on the manufacturing technique as well as the chemical composition. The SLM and ML/PS techniques may be considered promising alternatives to the Co-Cr alloy casting process.
Sparse signal recovery from nonlinear measurements

We treat the problem of minimizing a general continuously differentiable function subject to sparsity constraints. We present and analyze several different optimality criteria which are based on the notions of stationarity and coordinate-wise optimality. These conditions are then used to derive three numerical algorithms aimed at finding points satisfying the resulting optimality criteria: the iterative hard thresholding method and the greedy and partial sparse-simplex methods. The theoretical convergence of these methods and their relations to the derived optimality conditions are studied.