Miracle-dz/UniFAR-FTUs huggingface dataset:
Persistent queries over dynamic text streams

We wish to develop automated tools for information organisation that support information processing in the age of information overload. We present a filtering-based approach to persistent queries that uses clustering. We use the online version of the star algorithm developed in our previous work as our clustering tool because this algorithm computes, with high precision, naturally occurring topics in a collection and it admits an efficient online solution for dynamic streams of text. We describe the principle behind the filtering algorithms and show experimental data. We then discuss a system that uses these algorithms in support of information push by allowing users to submit persistent queries. Finally, we evaluate the persistent query system using TREC data.
Constrained PRFs for NC1 in Traditional Groups

We propose new constrained pseudorandom functions (CPRFs) in traditional groups . Traditional groups mean cyclic and multiplicative groups of prime order that were widely used in the 1980s and 1990s (sometimes called “pairing free” groups). Our main constructions are as follows. To achieve the security in the standard model, we develop a new technique using correlated-input secure hash functions.
Design of QoS Architecture for Global Cloud Computing Services by Adaptive Scheduling Algorithms

In this paper we will design architecture for cloud computing services with QoS by supported scheduling algorithm for resource allocation. Cloud generally uses virtualization technology which is specially designed for maximum resource utilization. The QoS of cloud environment for any kind of resource utilization is achieved feasibly by using QoS-aware Cache Replacement algorithm. This algorithm makes maximum utilization of resource in Cloud Environment. This accuracy is investigated by us using some measurements such as simple ping measurements which can be used as an indicator for some other QoS parameters such as jitter, throuput and delay. As a result, we were able to monitor the changes in QoS parameters during a number of days. This is also a first step towards defining QoS parameters to be included in Service Level Agreements for cloud computing in the foreseeable future. General Terms QoS-aware Cache Replacement algorithm, Service Level Agreements, virtualization
A formal approach to the slack driven scheduling problem in high-level synthesis

With the advent of deep sub-micron era, there is a growing need to consider the design closure problem in high-level synthesis. Previous work has shown that the slack (in terms of the number of clock cycles) is an effective means of tolerating variations in operation delays. In this paper, we propose an integer linear programming (ILP) approach for the slack driven scheduling problem. Our objective is to maximize the total useable slack under the design constraints (timing and resource). Compared with previous works our approach has the following two advantages: first, our approach guarantees the optimality; secondly, our approach is more suitable for the design space exploration.
Environmental control and adrenergic regulation of pineal activity in the diurnal tropical rodent, Arvicanthis ansorgei

Abstract: Like nocturnal rodents, the diurnal tropical rodent Arvicanthis ansorgei shows a daily rhythm in pineal melatonin content. Seasonal and photoperiodic variations in the biosynthetic activity of the pineal gland: arylalkylamine‐N‐acetyltransferase (AA‐NAT), hydroxyindole‐O‐methyltransferase (HIOMT) activities and melatonin content were measured in male and female A. ansorgei captured near Samaya, Mali, and kept either under artificial laboratory photoperiods [light‐dark (LD) cycles: LD 14:10, LD 12:12 or LD 10:14 or caught in the field in Mali and killed at four different times of the year (January, April, June and November). Under artificial photoperiod, the duration of the nocturnal peak of AA‐NAT activity and melatonin content increased with the duration of the dark period while the amplitude did not significantly change. In the field, annual variations in the amplitude of the nocturnal melatonin peak were observed with a maximum in April (highest temperature, low humidity and no grass availability, only seeds) and a minimum in November (high humidity, maximum green grass availability). The variations in the amplitude of the melatonin peak were not correlated with changes in AA‐NAT HIOMT activities, suggesting that seasonal variations in the amplitude of the melatonin peak are not driven by these enzymes. Daytime injections of the β‐adrenergic agonist, isoproterenol, stimulated melatonin synthesis in January, April and June, but not in November. The annual differences in the amplitude of the melatonin peak as well as the seasonal differences in the response to an adrenergic stimulation suggest that environmental factors other than photoperiod, such as temperature, humidity and consequent food availability, could be important in the regulation of the annual variations in the pineal biosynthetic activity in this species.
Unemployment and labour force participation in Turkey

ABSTRACT This article investigates the relationship between labour force participation rate and unemployment rate in Turkey a developing country. Cointegration analysis is carried out for the aggregate and gender-specific series. The findings indicate that there is no long-run relationship between labour force participation and unemployment rates in Turkey. Thus, unlike in the case of the developed countries, the unemployment invariance hypothesis is supported in Turkey.
Nasal Carriage of Epidemic Methicillin-Resistant Staphylococcus aureus 15 (EMRSA-15) Clone Observed in Three Chicago-Area Long-Term Care Facilities

ABSTRACT The spread of pandemic methicillin-resistant Staphylococcus aureus (MRSA) clones such as USA300 and EMRSA-15 is a global health concern. As a part of a surveillance study of three long-term care facilities in the Greater Chicago area, phenotypic and molecular characterization of nasal MRSA isolates was performed. We report a cluster of pandemic EMRSA-15, an MRSA clone rarely reported from the United States, detected during this study.
Antenna radiation characterization for on-body communication channel using creeping wave theory

Creeping wave theory is re-visited for BAN (Body Area Network) channel modeling. The formulation takes the characteristics of both antenna and human tissues into account. The field density at a certain distance from the radiating antenna can be directly determined by input power and on-body antenna gain. It is observed that the complicated on-body antenna gain measurement can be replaced by measuring antenna gain above infinitely large PEC (perfect electric conductor) plane to determine field density. Using time gating technique, the antenna gain above infinitely large PEC can be obtained by measuring continuous field on finitely large PEC, which is much easier to use in practice. The whole concept is validated through CST Microwave Studio. A very good agreement between the analytical model and full-wave simulation results is achieved.
Clinical Characteristics of Anomalous Correspondence

The correspondence status of 68 constant, early-age onset strabismics was evaluated with three common clinical tests to determine the prevalence of anomalous retinal correspondence (ARC) and which clinical features of the strabismus were most highly associated with the ARC. Ninety-six per cent, 71%, and 51% of the patients manifested ARC with the striated lens test, the synoptophore, and the afterimage test, respectively. The clinical features of the strabismus that were correlated, although weakly, with the diagnosis of ARC were: (1) the magnitude of the deviation at near for the striated lens test; (2) the age of the patient at the time of testing and the laterality of the deviation on the synoptophore; and (3) the age of the patient at the time of testing, the change in the deviation from distance to near, and the spherical equivalent refractive error for the afterimage test. A low correlation also existed between the age of the patient and the depth of ARC (superficial or deep-rooted). We conclude that the clinical features of strabismus cannot be utilized effectively to predict the status of retinal correspondence.
A Rating-Ranking Method for Crowdsourced Top-k Computation

Crowdsourced top- k computation aims to utilize the human ability to identify Top- k objects from a given set of objects. Most of existing studies employ a pairwise comparison based method, which first asks workers to compare each pair of objects and then infers the Top- k results based on the pairwise comparison results. Obviously, it is quadratic to compare every object pair and these methods involve huge monetary cost, especially for large datasets. To address this problem, we propose a rating-ranking-based approach, which contains two types of questions to ask the crowd. The first is a rating question, which asks the crowd to give a score for an object. The second is a ranking question, which asks the crowd to rank several (e.g., 3) objects. Rating questions are coarse grained and can roughly get a score for each object, which can be used to prune the objects whose scores are much smaller than those of the Top- k objects. Ranking questions are fine grained and can be used to refine the scores. We propose a unified model to model the rating and ranking questions, and seamlessly combine them together to compute the Top- k results. We also study how to judiciously select appropriate rating or ranking questions and assign them to a coming worker. Experimental results on real datasets show that our method significantly outperforms existing approaches.
Multiphotoreceptor and multioscillator system in avian circadian organization

Photoperiodism and circadian rhythms have been studied intensively in birds because Aves are typical seasonal breeders and diurnal animals. Light is the most important environmental factor involved in entrainment of circadian rhythms and photoperiodism. The eyes and the extraocular photoreceptors, such as the pineal organ and hypothalamus, are reported to have an important function not only for photoreception but also for circadian organization in nonmammalian vertebrates, including birds. In this report, we review the roles of the eyes, pineal organ, and deep brain as the components of the multiphotoreceptor and multioscillator system in avian circadian organization. Microsc. Res. Tech. 53:43–47, 2001. © 2001 Wiley‐Liss, Inc.
Influence of 2-(18F) Fluoro-2-Deoxy-d-Glucose Positron Emission Tomography/Computed Tomography on Recurrent Ovarian Cancer Diagnosis and on Selection of Patients for Secondary Cytoreductive Surgery

The objective of this prospective study was to compare the sensitivities and the specificities of combined 2-(18F) fluoro-2-deoxy-d-glucose positron emission tomography/computed tomography (PET/CT), abdominal/transvaginal ultrasound (US), and CT for diagnosing recurrent ovarian cancer (OC) and to evaluate the influence of PET/CT on referral of patients with solitary recurrence to secondary cytoreductive surgery. From April 2005 to November 2007, 60 patients were consecutively included to PET/CT 68 times. The inclusion criteria were remission of 3 months or longer and recurrent OC suspected from physical examination, US, or increasing cancer antigen 125 (CA125) level (>50 U/mL or >15% above baseline level). Recurrent OC was diagnosed 58 times in 52 patients. The sensitivities of US, CT, and PET/CT for diagnosing recurrence were 66% (P = 0.003), 81% (P = 0.0001), and 97% (P < 0.0001), respectively. The specificity of US, CT, and PET/CT for diagnosing recurrence was 90%. Positron emission tomography/CT diagnosed recurrence in 19 (66%) of 29 patients without recurrence according to US and in 10 (50%) of 20 patients without recurrence after CT. Multiple recurrent tumors were found using PET/CT in 27 (69%) of 39 patients with solitary tumors on US and in 8 (42%) of 19 patients with solitary tumors on CT. We conclude that the diagnostic value of PET/CT for detecting recurrent OC was higher than those of US and CT and that PET/CT more accurately identified patients with solitary recurrence. However, prospective clinical trials are needed to specify the characteristics of patients most likely to undergo complete secondary surgery and to further clarify the role of PET/CT in selecting patients for secondary surgery.
Frequency band utilization enhancement for chipless RFID tag through place value encoding

Radio frequency identification (RFID) chipless tag is presented that achieves a high code density per frequency by encoding place values for time specific applications. In comparison with previous work that encodes the complete identification number, the proposed encoding scheme shows an increase in code density per frequency by almost 200%. The chipless tag is excited using linearly polarized plane wave and Radar Cross Section (RCS) vs. frequency in the 7-8.2 GHz band is analyzed.
Symbolic verification of synthesized RTL using Boolean satisfiability and uninterpreted RTL transformations

We present a symbolic verification methodology to verify the register transfer logic (RTL) design generated during high-level synthesis (HLS) against the behavioral specification. The significant contributions of this paper are the following: (i) a symbolic verification methodology capable of verifying synthesis decisions at various stages of HLS; (ii) the use of SAT tool as the main verification engine - this enables the verification methodology to handle larger designs when compared with BDD-based methodologies; (iii) a exploitation of a set of uninterpreted RTL transformations that aid equivalence checking using SAT tools, and provide better diagnostics
Distributed Spatial Filtering Over Networked Systems

This letter concerns distributed spatial filtering over networked systems, i.e., transforming signal values given for nodes to those with a desired spatial frequency characteristic via a distributed computation. An existing filtering algorithm can achieve only low-pass filter characteristics, which limits its range of applications. To address this limitation, we extend the aforementioned filtering algorithm using an additional design parameter. We then present a characterization of all the realizable filter characteristics as a necessary and sufficient condition for achieving distributed spatial filtering. As a result, it is shown that the extended algorithm increases the range of the realizable filter characteristics. The proposed method is verified not only by simulation but also by denoising experiments for a real sensor network. The results show that the proposed method effectively reduces spatial noise and achieves higher performance than an average consensus algorithm and an average filter.
Extensions to Tree-Recursive Neural Networks for Natural Language Inference

Understanding textual entailment and contradiction is considered fundamental to natural language understanding. Tree-recursive neural networks, which exploit valuable syntactic parse information, achieve state-of-the-art accuracy among pure sentence encoding models for this task. In this course project for CS224D, we explore two extensions to tree-recursive neural networks deep TreeLSTMs and attention mechanisms over TreeLSTMs and evaluate our models on the Stanford Natural Language Inference (SNLI) corpus. Our best models show∼2% improvement in classification accuracy compared to a pure sentence TreeLSTM encoder baseline.
Grammatical constructions , frame structure , and metonymy : Their contributions to metaphor computation

In conceptual metaphor theory, mappings between source and target frames entail relations between roles within those frames. However, the contributing functions of metonymic relations between frame roles and type constraints on those roles ‒ e.g., whether the role is of type Entity or Process ‒ must also be established. These metonymic links and type constraints enable metaphoric conceptualization, as does the particular frame structure of the metaphor’s target and source domains. In this paper we use computational implementations of ontological structures developed in Embodied Construction Grammar and our own constructed metaphor repository to explore these relationships. We demonstrate that both role-to-role metonymic relations and type constraints on the roles are important in generating the correct metaphoric interpretation. In this way, the formal treatment of frameinternal and frame-to-frame mappings is brought to the fore in metaphor analysis.
Economic Value Added ( EVA ® ) . Is it really the best performance measure ? A Review of the Theoretical and Empirical Literature . The case of Athens Stock Exchange ( ASE )

The aim of this paper is to extensively discuss the underlying concept of Economic Value Added, henceforth EVA, to present its strengthens and weaknesses, to discuss the revealed results from the empirical studies up to now concerning its usefulness as a financial performance measure, and finally, to show the results of the first empirical study on the issue conducted in the Greek capital market. Despite all positive and encouraging comments about EVA, emphasised by Stewart (1991; 1994; 1999), Sheehan (1994), Walbert (1994), Stern, Stewart and Chew (1995) and other EVA proponents such as Tully (1993), O’Byrne (1996), Ehrbar (1998), Stern (1974; 2001) and Grant (2003) among others, the empirical literature which came out provided mixed results for the usefulness of EVA in explaining stock returns. Studies focused on whether EVA is more highly associated with stock returns than other performance measures provided mixed and controversial results. This study employs pooled time-series, cross sectional data of 163 listed companies in the ASE over the period 1992 – 2001 to examine whether EVA or the traditional accounting-based measures are associated more strongly with stock returns. Relative information content tests reveal that stock returns are more closely associated with earnings per share than with EVA. However, incremental information content tests suggest that EVA adds considerable explanatory power to earnings per share in explaining stock
X-ray sources in dwarf galaxies in the Virgo cluster and the nearby field

Theextenttowhichdwarfgalaxiesrepresentessentiallyscaleddownversionsofgiantgalaxies is an important question with regards the formation and evolution of the galaxy population as a whole. Here, we address the specific question of whether dwarf galaxies behave like smaller versions of giants in terms of their X-ray properties. We discuss two samples of around 100 objects each, dwarfs in the Virgo cluster and dwarfs in a large Northern hemisphere area. We find nine dwarfs in each sample with Chandra detections. For the Virgo sample, these are in dwarf elliptical (or dwarf lenticular) galaxies and we assume that these are (mostly) low-mass X-ray binaries (LMXB) [some may be nuclear sources]. We find a detection rate entirely consistent with scaling down from massive ellipticals, viz. about one bright (i.e.
Design and Evaluation of an Efficient Semispace-based Memory Reclamation Scheme

Now that in language with garbage collection (GC) mechanism such as Java, the GC should be a direct impact on the performance of the program, and the requirement of real time GC is even higher in a real-time system. We proposed a memory reclamation scheme based on semi-space GC to satisfy the demands of real-time system. In the semi space copying collection process, large number of memory copying operations will bring a significant time overhead. Therefore, a mechanism of object classification and incomplete copying was proposed to reduce the costs of memory copying as well as to maintain a low degree of memory fragmentation. We implemented our solution on the Apache Harmony platform and the effectiveness of our collector prototype was measured through a series of benchmark tests.
Challenges with Audio Classification using Image Based Approaches for Health Measurement Applications

Image classification has had huge success in recent years, mainly due to the vast array of databases available. The lack of audio databases presents a problem when it comes to creating a deep neural network classifier aimed at measurement and monitoring of health-related sounds. Such sounds (i.e. cough) can be indicative of worsening health conditions, specifically as it relates to remote monitoring of older adults. The application of pre-existing deep neural network image classifiers to audio classification has been presented as a potential solution. This paper describes some of the issues associated with utilizing audio spectrograms to retrain the AlexNet image classifier for the purpose of remote patient monitoring. The spatial invariance assumption of the classifier is further investigated by creating two different classification tasks based on spectrograms computed from notes on a classical piano at four different noise levels; (1) octave classification and (2) note classification. As expected, the AlexNet classifier with clean data performs better when classifying octaves (98%), when compared to the note classification (83 %). When evaluating on audio with noise, the note classifier performance decreases more than the octave classification performance.
Dhrishti: A Visual Aiding System for Outdoor Environment

Visually impaired individuals face difficulties in safe and independent movement which bereave them from their day-to-day life activities in both outdoor and indoor environment. The evaluated number of visually impaired individuals in the world is said to be in millions. This paper mainly addresses the navigation of visually impaired in outdoor environment. The application developed proposes a smart portable cane that is equipped with sensors and camera to help the visually impaired to understand their surroundings, detect the obstacles and avoid them using Computer Vision, Neural networks and Internet of Things(IoT) in outdoor spaces thereby helping them to navigate safely. Our idea is to implement YOLO (You Only Look Once) algorithm for the obstacle detection using the DarkNet framework which is then used for object avoidance using an ultrasonic sensor. The main goal is to create a system which is easy, efficient and will have high computational speed as it has to work in the real time environment.
SISFAT: Smart irrigation system with flood avoidance technique

Our framework gives a Smart Irrigation System (SIS) by detecting the dampness content as it turns the engine ON/OFF automatically. Presently a-days, the Internet of Things (IoT) assumes a noteworthy part in many fields via computerizing the application. In agribusiness, the utilization of right and reasonable technique for water system to the product is essential by checking the amount of water appropriate to affirm the water substance of it. The benefit of utilizing this innovation is to lessen human intercession and still guarantee legitimate water system, utilizing sun powered boards to save and change over vitality, to defeat the flooding and to make keen water system. In this innovation the level of water and dampness is absolutely controlled with no power cut off. This will help the poor agriculturist to decrease the weight of manual exchanging ON/OFF. It will likewise lessen undesirable water asset and power utilization. This framework has a propelled highlight to stay away from surge which is the fundamental arrangement amid catastrophic event and water flood.
AWC C. elegans neuron: a biological sensor model

AWC sensory neurons of the nematode Caenorhabditis elegans are capable of detecting a wide variety of volatile compounds, as well as electric fields and temperature. In this work we present a detailed biophysical model of the neuron response to odor stimuli. Our model couples the intracellular transduction pathway to the electrical activity, giving a comprehensive view of the neuron functioning. This work represents a fist attempt for the realistic modeling of the stimulus-response coupling to be used for deep investigation of sensing function in C. elegans.