Miracle-dz/UniFAR-FTUs huggingface dataset:
Name that sculpture

We describe a retrieval based method for automatically determining the title and sculptor of an imaged sculpture. This is a useful problem to solve, but also quite challenging given the variety in both form and material that sculptures can take, and the similarity in both appearance and names that can occur. Our approach is to first visually match the sculpture and then to name it by harnessing the meta-data provided by Flickr users. To this end we make the following three contributions: (i) we show that using two complementary visual retrieval methods (one based on visual words, the other on boundaries) improves both retrieval and precision performance; (ii) we show that a simple voting scheme on the tf-idf weighted meta-data can correctly hypothesize a subset of the sculpture name (provided that the meta-data has first been suitably cleaned up and normalized); and (iii) we show that Google image search can be used to query expand the name sub-set, and thereby correctly determine the full name of the sculpture. The method is demonstrated on over 500 sculptors covering more than 2000 sculptures. We also quantitatively evaluate the system and demonstrate correct identification of the sculpture on over 60% of the queries.
Application of a niched Pareto genetic algorithm for selecting features for nuclear transients classification

Feature selection for transient classification is the problem of choosing among several monitored parameters (i.e., the features) to be used for efficiently recognizing the developing transient patterns. It is a critical issue for the application of “on condition” diagnostic techniques in complex systems, such as the nuclear power plants, where hundreds of parameters are measured. Indeed, irrelevant and noisy features have been shown to unnecessarily increase the complexity of the classification problem and degrade the diagnostic performance.
Establishing Motion Correspondence * Center For

We propose a proximal uniformity constraint to solve the correspondence problem. According to this constraint, most objects in the real world follow smooth paths and cover a small distance in a small time. An efficient, non iterative polynomial time approximation algorithm which minimizes the proximal uniformity cost function and establishes correspondence over n frames is proposed. Any method u s ing smoothness of motion alone cannot operate correctly without assuming correct initial correspondence, the correspondence in first two frames. Therefore, we propose the use of gradient based optical flow for establishing the initial correspondence. This way the proposed approach combines the qualities of the gradient and token based methods for motion correspondence. The algorithm is then extended to take care of restricted cases of occlusion. The experimental results for real and synthetic sequences are presented to support our claims.
Leader-follower based target detection model for mobile molecular communication networks

This paper proposes a leader-follower based target detection model for mobile molecular communication networks. The proposed model divides application functionalities of molecular communication networks over the two types of mobile bio-nanomachine: leader and follower bio-nanomachines. Leader bio-nanomachines distribute in the environment to detect a target and create an attractant gradient around the target. Follower bio-nanomachines move based on the attractant gradient made by leader bio-nanomachines, approach the target and perform necessary functionalities such as releasing drug molecules. The functional division demonstrated through the model facilitates the design and development of molecular communication networks as it can reduce the number of functionalities that need to be implemented on individual bio-nanomachines.
An efficient time slot allocation algorithm in wireless networks

Wireless communication networks provide convenience, however, also challenges to multimedia services due to typically limited bandwidth and various Quality of Service (QoS) requirements. For a wireless communication network service provider/administrator, it is then essential to develop an effective resource allocation policy so as to fully satisfy possibly different QoS requirements by different classes of traffic; while in the meantime, for example, the overall long-term system revenue rate can be maximized. In this paper, we consider the problem of time slot allocation for multiple classes of traffic in wireless networks under throughput and delay constraints. To solve the problem, we propose an algorithm that is a novel combination of the Markovian decision process (MDP) and Lagrangean relaxation (LR). Another primal heuristic based on the policy enhancement algorithm is also developed for comparison purposes. Our experiment results show that the proposed approach can find a near optimal time slot allocation policy to maximize long-term system revenue under QoS requirements.
On the Synchronization of Physical-Layer Network Coding

When data are transmitted in a wireless network, they reach the target receiver as well as other receivers in the neighborhood. Rather than a blessing, this attribute is treated as an interference-inducing nuisance in most wireless networks today (e.g., IEEE 802.11). Physical-layer network coding (PNC), however, has been proposed to take advantage of this attribute. Unlike "conventional" network coding which performs arithmetic coding on digital bit streams after they are decoded, PNC makes use of the additive nature of simultaneously arriving electromagnetic (EM) waves and applies the network coding arithmetic at the physical layer. As a result, the destructive effect of interference is eliminated and the capacity of networks is boosted significantly. A key requirement of PNC is synchronization among nodes, which has not been addressed previously. This is the focus of this paper. Specifically, we investigate the impact of imperfect synchronization (i.e., finite synchronization errors) on PNC. We show that with BPSK modulation, PNC still yields significantly higher capacity than straightforward network coding when there are synchronization errors. And interestingly, this remains to be so even in the extreme case where synchronization is not performed at all
Increase in caudate nuclei volumes of first-episode schizophrenic patients taking antipsychotic drugs.

OBJECTIVE This study examined the pathomorphology of the caudate nuclei in first-episode schizophrenic patients with minimal previous neuroleptic exposure. METHOD Magnetic resonance imaging (MRI) of the brain was used to examine longitudinally the caudate pathomorphology in 29 first-episode schizophrenic patients and 10 healthy comparison subjects. MRI scans were obtained after the subjects entered the study and at 18-month follow-up. The patients were treated with standardized neuroleptic regimens during the 18-month period. Volumetric assessments of the cerebral cortex, lateral ventricles, and caudate nuclei were performed on T1-weighted coronal brain sections. In addition, the patients were systematically evaluated for psychopathology at baseline and during treatment. RESULTS Caudate volumes increased 5.7% in the patients during the 18-month treatment interval, whereas they decreased 1.6% in the comparison subjects over the same time period. Greater amounts of antipsychotic medication received by patients before the first scan and younger age at the time of the first scan were associated with larger increases in caudate volume. CONCLUSIONS Caudate enlargement occurs early in the course of treatment in young first-episode schizophrenic patients. This may be a result of an interaction between neuroleptic treatment and the plasticity of dopaminergic neuronal systems in young patients.
Destage algorithms for disk arrays with non-volatile caches

In a disk array with a nonvolatile write cache, destages from the cache to the disk are performed in the background asynchronously while read requests from the host system are serviced in the foreground. We study a number of algorithms for scheduling destages in a RAID-5 system. We introduce a new scheduling algorithm, called linear threshold scheduling, that adaptively varies the rate of destages to disks based on the instantaneous occupancy of the write cache. The performance of the algorithm is compared with that of a number of alternative scheduling approaches such as least-cost scheduling and high/low mark. The algorithms are evaluated in terms of their effectiveness in making destages transparent to the servicing of read requests from the host, disk utilization, and their ability to tolerate bursts in the workload without causing an overflow of the write cache. Our results show that linear threshold scheduling provides the best read performance of all the algorithms compared, while still maintaining a high degree of burst tolerance. An approximate implementation of the linear-threshold scheduling algorithm is also described. The approximate algorithm can be implemented with much lower overhead, yet its performance is virtually identical to that of the ideal algorithm.
A Roadmap to Implement Rapid Transition as a Proposal of e-Learning Model

Digital age (information/computer age) offers many opportunities. Many transforms and changes have been made in public and private sectors. It is clear to say that education is one of the most important areas that has been trying to use IT tools. Today, e-learning is an important way of removing time and place constraints between students and instructors. In addition, it is the best way to make education sustainable in every organization. Many organizations can face problems during their e-learning experience. Having enough knowledge about e-learning is not a must for every organization in every sector. Therefore, in this study, the authors aim to provide a rapid transition for organizations that wants to set up an e-learning system. This paper gives some hints related to transition process. Therefore, theoretical framework of an e-learning system, selection of learning management system (LMS) and content management system (CMS), designing of a virtual classroom, online course implementation, controlling the project are explained, future works related to the framework are discussed.
Beauty production cross section measurements at E(cm) = 1.96-TeV

The RunII physics program at the Tevatron started in spring 2001 with protons and antiprotons colliding at an energy of {radical}s = 1.96 TeV, and it is carrying on with more than 500 pb{sup -1} of data as collected by both the CDF and D0 experiments. Recent results on beauty production cross section measurements are here reported.
Sparse representation based background subtraction in videos

Background subtraction is an important preprocessing technique for a wide variety of problems in computer vision including automatic video surveillance, anomaly detection etc. Our focus is on background subtraction of videos taken from stationary cameras. We use sparse representation and compressive sensing to propose a novel algorithm that separate the background image and present the foreground objects in each frame. Our method is robust to dynamic background scenario where the background changes with time. We also point towards the fact that our algorithm is highly parallalizable and so can subtract background in real time. We demonstrate the superiority of our method against Mixture of Gaussian, KDE model and Monnnet's method. Also our method is on par with AdaDGS in terms of visual result.
Objective Quality Assessment of Noised Stereoscopic Images

Stereoscopic images have been widely studied in recent years from a technical point of view, but the related quality assessment does not follow this enthusiasm. An objective quality assessment method for serious noised stereoscopic images is proposed. It is based on 2D quality evaluation and the characteristics of stereoscopic images. The disparity map for stereoscopic image pairs is an important indicator of stereoscopic image quality assessment. The metric Peak Signal to Noise Ratio (PSNR) is used to evaluate the quality of the noised disparity map, and the value of which is defined as DPSNR. The DPSNR methodology is used for objective quality assessment of serious noised stereoscopic images. The experimental results show that the proposed method could accurate and objective evaluation of stereoscopic images quality.
CS 599 : Structure and Dynamics of Networked Information ( Spring 2005 ) 01 / 12 / 2005 : Web graph structure and Authoritative Sources in Hyperlinked Environment Scribes :

Here, we investigate the graph structure of the Web-graph, the directed graph whose nodes are static pages and edges are links between these pages. Broder et al. [1] looked at some basic properties of this graph. They found that the web-graph has one large weakly connected component consisting of 91% of pages. This is not surprising since there is only one world wide web. This fact remains intact even when all nodes of degree more than 5 are removed: there still is a large component with more than 59 million pages. This shows that there are many different paths between pairs of nodes and the web will not be partitioned even if certain important pages were removed. The web was found to contain one strongly connected component (SCC) of approximately 56 million pages that were mutually reachable.
Design and Implementation of Op-Amp Based Low-Power CMOS Bandgap Voltage Reference with Minimum Supply oF 0 . 8V

A low power voltage source is generated by altering the device size in existing topology has been presented. Bandgap voltage reference is generated by combination of start-up, supply independent, operational amplifier (Op-amp) and bandgap core circuits which has been designed such that low sensitivity of temperature and supply variation. It has been designed with minimum supply of 0.8 V without use of low threshold device, and the maximum supply current is 35 µA. It has been implemented in 180 nm standard digital CMOS Process. The circuit generates a reference voltage of 540 mV and has a temperature coefficient of 14 ppm /°C from −40 °C to 120 °C. The generated reference voltage is independent of temperature and supply variations have been mathematically proved by analyzing the circuit design. Also, proper selection of on-chip passive components and its values has been chosen which is based on low noise. Comparing the pre and post layout simulation results has been presented.
Visualizing Global Patterns in Huge Digraphs

Traditional methods for depicting directed graphs are inadequate when the number of vertices and edges are too large. Also underlying geographical coordinates are generally not considered. A new visualisation method is presented which transforms graphs into a 3D surface which can be shown as a contour map superimposed over a geographical region thereby preserving the underlying geographical details.
Voices of Europe: Citizens, Referendums, and European Integration

Chapter 1 Introduction Chapter 2 Citizens, Democracy, and European Integration Chapter 3 Referendums on European Integration Chapter 4 Voting Behavior in Referendums Chapter 5 Policy Effects of Referendums Chapter 6 Assessing the Impact of Referendums Chapter 7 Extending the Use of Referendums Chapter 8 Conclusion Chapter 9 Appendix
Reduction of Non-stationary Noise for a Robotic Living Assistant using Sparse Non-negative Matrix Factorization

Due to the demographic changes, support by means of assistive systems will become inevitable for home care and in nursing homes. Robot systems are promising solutions but their value has to be acknowledged by the patients and the care personnel. Natural and intuitive human-machine interfaces are an essential feature to achieve acceptance of the users. Therefore, automatic speech recognition (ASR) is a promising modality for such assistive devices. However, noises produced during movement of robots can degrade the ASR performances. This work focuses on noise reduction by a non-negative matrix factorization (NMF) approach to efficiently suppress non stationary noise produced by the sensors of an assisting robot system.
Comparative study on machine learning techniques in predicting the QoS-values for web-services recommendations

This is an era of Internet computing and computing as a service on the internet is called cloud computing. Mainly three services like SaaS (applications), PaaS, and IaaS are being accessed through internet on demand, pay as per usage basis. Quality of Service (QoS) is the main issue in internet based computing for service providers and user-dependent as well as user-independent QoS parameters. In the current work we compared different machine learning algorithms for predicting the response time and throughput QoS values using past usage data. Bagging and support vector machines are found to be better performing prediction methods in comparison with other learning algorithms.
Long-term trends in real wages of labourers

This chapter presents a very long-term view of real wages of unskilled labourers in Sweden, particularly in Stockholm, from medieval times up to the present. Emphasis is on the pre-industrial era up to about 1860. The wages series is based on the building accounts of Stockholm City, supplemented with some institutional and parish archives.1 The accounts of the Town Council of Stockholm contain detailed descriptions of the building works initiated by the Council and the daily wages of various building workers. Here we focus on unskilled labourers, since this is the only category for which long series of daily wage rates are available.2 Parish accounts (e.g., Storkyrkoförsamlingen and the German Church) also provide information on wages. Wages were paid in cash and for most of the period examined there were no substantial additional benefits in kind (though the City occasionally did pay for the gloves used by labourers, and gave them some beer). In the late medieval era, though, beer and food could be a substantial part of wages (see Section 9.2 below). For the period 1365–1864, wages refer to daily summer rates of male unskilled labourers in Stockholm (the 1365 quotation actually refers to the town of Nyköping, about 100 km south of Stockholm). 3 From 1864 onwards, this series is linked to the series of wages for industrial and mining workers in Sweden presented by Svante
Conformal prediction for distribution-independent anomaly detection in streaming vessel data

This paper presents a novel application of the theory of conformal prediction for distribution-independent on-line learning and anomaly detection. We exploit the fact that conformal predictors give valid prediction sets at specified confidence levels under the relatively weak assumption that the (normal) training data together with (normal) observations to be predicted have been generated from the same distribution. If the actual observation is not included in the possibly empty prediction set, it is classified as anomalous at the corresponding significance level. Interpreting the significance level as an upper bound of the probability that a normal observation is mistakenly classified as anomalous, we can conveniently adjust the sensitivity to anomalies while controlling the rate of false alarms without having to find any application specific thresholds. The proposed method has been evaluated in the domain of sea surveillance using recorded data assumed to be normal. The validity of the prediction sets is justified by the empirical error rate which is just below the significance level. In addition, experiments with simulated anomalous data indicate that anomaly detection sensitivity is superior to that of two previously proposed methods.
Terrorism: Deterrence May Backfire

Present anti-terrorist policy concentrates almost exclusively on deterrence. It seeks to fend off terrorism by raising the cost of undertaking terrorist acts. This paper argues that deterrence policy is less effective than generally thought and induces in some cases even more terrorism. This is, in particular, the case if deterrence policy induces a centralisation of decision-making in the polity and economy. Therefore, an effective anti-terrorist policy should focus more on reducing the expected benefits of terrorist acts to prospective terrorists. Such a policy is based on strengthening rather than weakening decentralised decision-making.
Glottal source modeling for singing voice synthesis

Naturalness of sound quality is essential for singing-voice synthesis. Since 95% of singing is voiced sound (Cook, 1990), the focus of this paper is to improve the naturalness of the vowel tone quality via glottal excitation modeling. We propose to use the LF-model (Fant et al., 1985) for the glottal wave shape in conjunction with pitch-synchronous, amplitude-modulated Gaussian noise, which adds an aspiration component to the glottal excitation. The associated analysis and synthesis procedures are also provided in this paper. By analyzing baritone recordings, we have found simple rules to change voice qualities from “laryngealized” (or “pressed”), to normal, to “breathy” phonation.
Distributed Abstract State Machines and Their Expressive Power

State Machines have been introduced as a “computation model that is more powerful and more universal than the standard computation models” by Yuri Gurevich in 1985 [11]. This is achieved by adopting classical concepts from logics and universal algebra, and their conservative extension to describe sequential steps. A number of variants of ASMs evolved over time, in particular parallel, distributed, and interactive versions [6, 2, 1]. In addition to theoretical considerations, ASMs have proven their practical benefits for the specification and analysis of real-world systems [4, 3]. Gurevich introduced in [7] the class of sequential small-step algorithms by only a few intuitive and amazingly liberal requirements, and proved every sequential smallstep algorithm to be represented by a sequential small-step ASM. “Small-step” means intuitively that the amount of change is bounded for all steps of the algorithm. [10] reexamines Gurevich’s theorem, and provides some further explanations and examples. Later, the results for sequential ASMs have been extended by Blass and Gurevich to parallel and interactive versions of ASMs [2, 1]. In the “Lipari Guide” [6], Gurevich describes the central constructs of distributed ASMs. In particular, a single run of a distributed ASM is defined as a partially ordered set of actions of sequential ASMs, called moves in [6]. These definitions have been examined in more detail in [12], and were applied for the specification and verification of several distributed algorithms [12, 5, 8]. This paper investigates distributed small-step ASMs. It translates, to some extent, Gurevichs characterization of sequential small-step algorithms to distributed small step algorithms. It turns out that this can be achieved indeed, even as a conservative extension of the sequential case.
On the SNR-Evolution of the MMSE Function of Codes for the Gaussian Broadcast and Wiretap Channels

This paper considers the signal-to-noise ratio (SNR)-evolution, meaning the behavior as a function of the SNR, of the minimum mean-square error (MMSE) function of code sequences in several multi-user settings in the additive white Gaussian noise regime. The settings investigated in this context include the Gaussian wiretap channel, the Gaussian broadcast channel (BC), and the Gaussian BC with confidential messages (BCC). This paper shows that the specific properties of the SNR-evolution of the MMSE and conditional MMSE functions are necessary and sufficient conditions for capacity or equivocation achieving code sequences. In some cases, the complete SNR-evolution of a family of code sequences can be determined, providing significant insight into the disturbance (in terms of MMSE) such codes have on unintended receivers at other SNRs. Moreover, the effects of an additional MMSE constraint on the capacity region and on the SNR-evolution of code sequences are considered in the BC and BCC settings. Such an analysis emphasizes the tradeoff between rates and limited disturbance on unintended receivers.