Miracle-dz/UniFAR-FTUs huggingface dataset:
People Detection with DSIFT Algorithm By

People detection is an interesting computer vision topic. Locating people in images and videos have many potential applications, such as human computer interaction and auto-focus cameras. There have been much effort on developing people detection algorithms, and among them, the “Dense ScaleInvariant Feature Transform (DSIFT) [1]” algorithms appear to be very effective. To implement our own people detection program, we utilized the DSIFT algorithm to extract feature vectors from images, and used Support Vector Machine (SVM) and Naive Bayes algorithms for classification. We explored different imaging processing and machine learning techniques, and assessed their performance.
The Use of Visual Text Mining to Support the Study Selection Activity in Systematic Literature Reviews: A Replication Study

Background: Systematic literature reviews (SLRs)are an important component to identify and aggregate research evidence from different empirical studies. One of the activities associated with the SLR process is the selection of primary studies. The process used to select primary studies can be arduous, particularly when the researcher faces large volumes of primary studies. Aim: An experiment was conducted as a pilot test to compare the performance and effectiveness of graduate students in selecting primary studies manually and using visual text mining (VTM) techniques. This paper describes a replication study. Method: The same experimental design and materials of the previous experiment were used in the current experiment. Result: The previous experiment revealed that VTM techniques can speed up the selection of primary studies and increase the number of studies correctly included/excluded (effectiveness). The results of the replication confirmed that studies are more rapidly selected using VTM. We observed that the level of experience in researching has a direct relationship with the effectiveness. Conclusion: VTM techniques have proven valuable in the selection of primary studies.
The Effects of Music

A study conducted with obese children showed a link between their favorite music and being able to run longer before A recent study by Nelson, Specian, Campbell & DeMello (2006) showed exercise in offenders to have reduced rate of depression, anxiety, and stress as well as improved behavior. Glaros & Janelle (2002) supported the study conducted by Spence, Poon, & Duck (1997) that found exercise to have an increasing effect on self esteem and physical self concept.
Estimating lower vocal tract features with closed-open phase spectral analyses

Previous studies have shown that, in addition to being speaker-dependent yet context-independent, lower vocal tract acoustics significantly impact the speech spectrum at mid-tohigh frequencies (e.g 3-6kHz). The present work automatically estimates spectral features that exhibit acoustic properties of the lower vocal tract. Specifically aiming to capture the cyclicity property of the epilarynx tube, a novel multi-resolution approach to spectral analyses is presented that exploits significant differences between the closed and open phases of a glottal cycle. A prominent null linked to the piriform fossa is also estimated. Examples of the feature estimation on natural speech of the VOICES multi-speaker corpus illustrate that a salient spectral pattern indeed emerges between 3-6kHz across all speakers. Moreover, the observed pattern is consistent with that canonically shown for the lower vocal tract in previous works. Additionally, an instance of a speaker’s formant (i.e. spectral peak around 3kHz that has been well-established as a characteristic of voice projection) is quantified here for the VOICES template speaker in relation to epilarynx acoustics. The corresponding peak is shown to be double the power on average compared to the other speakers (20 vs 10 dB).
An Experimental Evaluation of Aggregation Algorithms for Processing Top-K Queries

For processing top-K queries with monotone aggregation functions, the threshold algorithm (TA) and its family are important methods in many scenarios. From 1996 to 2003, Fagin et al. proposed a variety of TA-like algorithms such as the FA, TA, TAz, NRA and CA algorithms for different access methods as well as various data resources, but they did not report the experimental results of the TA-like algorithms in their seminal papers. Since then, some of the original TA-like algorithms have been implemented, improved or adapted in different situations and/or applications, however, the original algorithms have not been thoroughly compared and analyzed under the same experimental framework. To address this problem, in this paper, we carry out extensive experiments to measure the performance of the original aggregation algorithms and the slight adaptations of TA, TAz and NRA, and then we provide comprehensive surveys on the natures of the TA-like algorithms based on our experimental results.
ANALYSIS OF SOFTWARE REJUVENATION ON ADHOC CONFERENCING AND MEDIA DISTRIBUTION SYSTEM

: The project facilitates the concept of Software Rejuvenation and its importance in day to day software applications. Software Rejuvenation prevents ageing in software applications and helps in achieving a non-compromising performance. “Adhoc conferencing system” is chosen as a candidate as this has a variety of functionalities that involve conferencing, screen sharing and file sharing with more possibilities of anomalies like memory leaks, data corruption, etc., over a period of time.
Eg5 is static in bipolar spindles relative to tubulin

We used fluorescent speckle microscopy to probe the dynamics of the mitotic kinesin Eg5 in Xenopus extract spindles, and compared them to microtubule dynamics. We found significant populations of Eg5 that were static over several seconds while microtubules flux towards spindle poles. Eg5 dynamics are frozen by adenylimidodiphosphate. Bulk turnover experiments showed that Eg5 can exchange between the spindle and the extract with a half life of <55 s. Eg5 distribution in spindles was not perturbed by inhibition of its motor activity with monastrol, but was perturbed by inhibition of dynactin with p50 dynamitin. We interpret these data as revealing the existence of a static spindle matrix that promotes Eg5 targeting to spindles, and transient immobilization of Eg5 within spindles. We discuss alternative interpretations of the Eg5 dynamics we observe, ideas for the biochemical nature of a spindle matrix, and implications for Eg5 function.
Development of a fuzzy logic wall following controller for steering mobile robots

This paper describes the design of a fuzzy logic controller for wall following-navigation of a differentially steered mobile robot. To maintain the distance of the mobile robot from the wall is a basic behavior that mobile robot should have. This paper proposes embedded fuzzy logic controller in order to make the mobile robot can running with smoothly and stable for wall following case. The designed fuzzy controller uses MATLAB® and it was simulated using Microsoft Visual C++. To verify our approach, a differentially steered mobile robot is implemented with ArduinoTM Nano. The experiment of simulation and test results methodology were presented to show the validity of the proposed.
A Lorentzian Bayesian Approach for Robust Iterative Multiframe Super-Resolution Reconstruction with Lorentzian-Tikhonov Regularization

Recently, it has seen a great deal of work in the development of algorithms addressing the problem of super-resolution. Although many such algorithms have been proposed, the almost SRR (super-resolution reconstruction) estimations are based on L1 or L2 statistical norm estimation thus these SRR methods are usually very sensitive to their assumed model of data and noise that limits their utility. This paper reviews some of these SRR estimator methods and addresses their shortcomings. We propose a novel SRR approach based on the stochastic regularization technique of Bayesian MAP estimation by minimizing a cost function. The Lorentzian norm is used for measuring the difference between the projected estimate of the high-resolution image and each low resolution image, removing outliers in the data and Tikhonov regularization and Lorentzian Tikhonov regularization are used to remove artifacts from the final answer and improve the rate of convergence. The experimental results confirm the effectiveness of our method and demonstrate its superiority to other super-resolution methods based on L1 and L2 norm for a several noise models such as noiseless, additive white Gaussian noise (AWGN) and salt & pepper noise
Toward Attribute E cient Learning Algorithms

We make progress on two important problems regarding attribute e cient learnability. First, we give an algorithm for learning decision lists of length k over n variables using 2 ~ O(k ) logn examples and time n ~ O(k 1=3). This is the rst algorithm for learning decision lists that has both subexponential sample complexity and subexponential running time in the relevant parameters. Our approach establishes a relationship between attribute e cient learning and polynomial threshold functions and is based on a new construction of low degree, low weight polynomial threshold functions for decision lists. For a wide range of parameters our construction matches a 1994 lower bound due to Beigel for the ODDMAXBIT predicate and gives an essentially optimal tradeo between polynomial threshold function degree and weight. Second, we give an algorithm for learning an unknown parity function on k out of n variables using O(n1 1=k) examples in time polynomial in n. For k = o(logn) this yields a polynomial time algorithm with sample complexity o(n). This is the rst polynomial time algorithm for learning parity on a superconstant number of variables with sublinear sample complexity. Supported by an NSF Mathematical Sciences Postdoctoral Research Fellowship.
Cardiovascular Effects of Pulmonary Exposure to Single-Wall Carbon Nanotubes

Background Engineered nanosized materials, such as single-wall carbon nanotubes (SWCNT), are emerging as technologically important in different industries. Objective The unique physical characteristics and the pulmonary toxicity of SWCNTs raised concerns that respiratory exposure to these materials may be associated with cardiovascular adverse effects. Methods In these studies we evaluated aortic mitochondrial alterations by oxidative stress assays, including quantitative polymerase chain reaction of mitochondrial (mt) DNA and plaque formation by morphometric analysis in mice exposed to SWCNTs. Results A single intrapharyngeal instillation of SWCNTs induced activation of heme oxygenase-1 (HO-1), a marker of oxidative insults, in lung, aorta, and heart tissue in HO-1 reporter transgenic mice. Furthermore, we found that C57BL/6 mice, exposed to SWCNT (10 and 40 μg/mouse), developed aortic mtDNA damage at 7, 28, and 60 days after exposure. mtDNA damage was accompanied by changes in aortic mitochondrial glutathione and protein carbonyl levels. Because these modifications have been related to cardiovascular diseases, we evaluated whether repeated exposure to SWCNTs (20 μg/mouse once every other week for 8 weeks) stimulates the progression of atherosclerosis in ApoE−/− transgenic mice. Although SWCNT exposure did not modify the lipid profiles of these mice, it resulted in accelerated plaque formation in ApoE−/− mice fed an atherogenic diet. Plaque areas in the aortas, measured by the en face method, and in the brachiocephalic arteries, measured histopathologically, were significantly increased in the SWCNT-treated mice. This response was accompanied by increased mtDNA damage but not inflammation. Conclusions Taken together, the findings are of sufficient significance to warrant further studies to evaluate the systemic effects of SWCNT under workplace or environmental exposure paradigms.
Asynchronous Byzantine consensus

Reaching agreement in an asynchronous environment is essential to guarantee consistency in distributed data processing. All previous asynchronous protocols were either probabilistic or they assumed a fail-stop mode of failure. The deterministic protocol presented in this paper reaches a Strong Byzantine Agreement in a system of asynchronous processors; and therefore can sustain arbitrary faults. In our model, processors can be completely asynchronous, though the communication network has the property that a message being sent by a correctly operating processor to a set of processors will reach its destinations within a predetermined period Δ. Additional results presented in the paper prove that in the above model one cannot reach a consensus within a bounded time. A correctly operating processor should wait to receive messages from other processors before making a decision. This result holds also for Weak Byzantine Agreement, but not for nontrivial consensus. We present a trivial protocol to reach a nontrivial consensus in bounded time.
Japanese Dependency Parsing Using Relative Preference of Dependency

This paper presents a new statistical Japanese dependency parser which models a relative preference of dependency. Most conventional Japanese dependency parsers are based on binary classification where all possible pairs of segments are classified into positive (dependent) or negative (non-dependent) examples. However, such methods are not suitable for dependency parsing, since the goal of this task is not to classify pairs of segments into two classes, but to select the most likely modifiee out of all candidates. The proposed method is based on this observation and models how likely a pair of segments have a dependency relation in comparison with other pairs. Experiments using the Kyoto University Corpus show that the method outperforms previous systems as well as improves the training efficiency.
Edge pricing of multicommodity networks for heterogeneous selfish users

We examine how the selfish behavior of heterogeneous users in a network can be regulated through economic disincentives, i.e., through the introduction of appropriate taxation. One wants to impose taxes on the edges so that any traffic equilibrium reached by the selfish users who are conscious of both the travel latencies and the taxes will minimize the social cost, i.e., will minimize the total latency. We generalize previous results of Cole, Dodis and Roughgarden that held for a single origin-destination pair to the multicommodity setting. Our approach, which could be of independent interest, is based on the formulation of traffic equilibria as a nonlinear complementarity problem by Aashtiani and Magnanti (1981), We extend this formulation so that each of its solutions will give us a set of taxes that forces the network users to conform, at equilibrium, to a certain prescribed routing. We use the special nature of the prescribed minimum-latency flow in order to reduce the difficult nonlinear complementarity formulation to a pair of primal-dual linear programs. LP duality is then enough to derive our results.
Using Higher-level Linguistic Knowledge for Speech Recognition Error Correction in a Spoken Q/A Dialog

Speech interface is often required in many application environments such as telephonebased information retrieval, car navigation systems, and user-friendly interfaces, but the low speech recognition rate makes it difficult to extend its application to new fields. Several approaches to increase the accuracy of the recognition rate have been researched by error correction of the recognition results, but previous approaches were mainly lexical-oriented ones in post error correction. We suggest an improved syllable-based model and a new semantic-oriented approach to correct both semantic and lexical errors, which is also more accurate for especially domain-specific speech error correction. Through extensive experiments using a speech-driven in-vehicle telematics information retrieval, we demonstrate the superior performance of our approach and some advantages over previous lexical-oriented approaches.
Orbit: Efficient Processing of Iterations

Various scienti c applications compute iterations on a huge set of input data. Examples include parameter sweep, which processes the same model through hundreds or thousands of input data, scienti c visualization and numeric methods to solve hyperbolic equations. The state of the art for executing such applications is to model them as scienti c work ows and to run them in HPC infrastructure. The execution model strives to combine pipeline parallelism, among activities of the work ow, with intra-work ow parallelism over data partitions, both of them subjected to work ow characteristics. In such scenario, the scienti c work ow execution model can be approximated to that of parallel query processing. In fact, database groups at LNCC and COPPE have implemented parallel work ow engines, QEF and Chiron, under this assumption. In order to full integrate iterations within a data processing execution model, an extension is required to treat the loop control operator. In this paper we investigate the problem of e ciently executing scienti c work ows that include iterations. We introduce Orbit which is a generic operator to manage the data ow in an iterative procedure. An execution model centered into Orbit is proposed including a centralized and parallelized modes. Additionally, two new execution strategies are investigated: rst-tuplerst, rst-iterationrst. We have obtained initial results that evaluate the di erent execution strategies in both centralized and parallel modes.
One-Round ID-Based Threshold Signature Scheme from Bilinear Pairings

In this paper, we propose a new ID-based threshold signature scheme from the bilinear pairings, which is provably secure in the random oracle model under the bilinear Diffie-Hellman assumption. Our scheme adopts the approach that the private key associated with an identity rather than the master key of PKG is shared. Comparing to the-state-of-art work by Baek and Zheng, our scheme has the following advantages. (1) The round-complexity of the threshold signing protocol is optimal. Namely, during the signing procedure, each party broadcasts only one message. (2) The communication channel is optimal. Namely, during the threshold signing procedure, the broadcast channel among signers is enough. No private channel between any two signing parties is needed. (3) Our scheme is much more efficient than the Baek and Zheng scheme in term of computation, since we try our best to avoid using bilinear pairings. Indeed, the private key of an identity is indirectly distributed by sharing a number x ID∈ $$\mathbb{Z}^{*}_{q}$$, which is much more efficient than directly sharing the element in the bilinear group. And the major computationally expensive operation called distributed key generation protocol based on the bilinear map is avoided. (4) At last, the proactive security can be easily added to our scheme.
Multimodal recognition based on face and ear using local feature

The pose issue which may cause loss of useful information has always been a bottleneck in face and ear recognition. To address this problem, we propose a multimodal recognition approach based on face and ear using local feature, which is robust to large facial pose variations in the unconstrained scene. Deep learning method is used for facial pose estimation, and the method of a well-trained Faster R-CNN is used to detect and segment the region of face and ear. Then we propose a weighted region-based recognition method to deal with the local feature. The proposed method has achieved state-of-the-art recognition performance especially when the images are affected by pose variations and random occlusion in unconstrained scene.
Study on the performance reverse logistics system for enterprises base on GA

In order to solve the problem of the natural resource consumption which is threatening the human survival, it is essential to construct the reverse logistics system (RLS) in the global scope to acquire the circulation economy. In view of such four factors as the infrastructure of RLS, the level of utilization of RLS, the knowledge level of staff of RLS and the level of system ensures of RLS, the Model of performance appraising & optimizing of the reverse logistics system for enterprises (MPAORLSE) in this article are presented. The model is solved by means of genetic algorithms(GA), so its result has much more objectivity. This model can be used to direct enterprises to appraise its performance of RLS, or to compare the performance with that of its rival.
Interoperable RT component for object detection and 3D pose estimation for service robots

Finding objects and tracking their poses are essential functions for service robots, in order to manipulate objects and interact with humans. We present an approach for object detection and 3D pose estimation for autonomous mobile robots, that is suitable for general uses in a modularized robot control system. Our apprach extracts local features from the input images, searches for the reference pattern, and then produces the 3D pose in camera coordinate system, using only a single reference image and the 6-DOF pose in it. We have created an RT(Robot Technology) component that can be used in any RT-based system, and developed an algorithm that can extend the range of detection and produce robust pose estimation. For evaluation, we have integrated our vision component in an autonomous robot system with a search-and-grasp task, and tested it with several objects that are found in ordinary domestic environment. We present the details of our approach, the design of our modular component design, and the results of the experiments in this paper.
Leveraging Biological Identifier Relationships and Related Documents to Enhance Information Retrieval for Proteomics

Leveraging Biological Identifier Relationships and Related Documents to Enhance Information Retrieval for Proteomics Andrew Smith, Kei Cheung, Michael Krauthammer, Martin Schultz and Mark Gerstein Department of Molecular Biophysics and Biochemistry, Department of Computer Science, Center for Medical Informatics, Department of Genetics, Program in Computational Biology and Bioinformatics, Department of Anesthesiology, Department of Pathology, Yale University, New Haven, CT USA Corresponding Author
Continuity Adjustments to Triangular Bézier Patches That Retain Polynomial Precision

In this paper, I discuss a method for increasing the continuity between two polynomial patches by adjusting their control points. The method described in this paper leaves the control points unchanged if the patches already meet with the desired level of continuity. Next I give two C degree n polynomial interpolation schemes that reproduce degree n polynomials, and show how to apply my continuity increasing scheme to these interpolants without decreasing their polynomial precision. The second of these interpolants is interesting in its own right, as it requires less data than other methods. Finally, I apply my continuity method to Clough-Tocher methods, and create split domain schemes with top-level polynomial precision.