Miracle-dz/UniFAR-FTUs huggingface dataset:
A Fast Automatic Ellipse Detector

In 2002, Kim et al described a fast and robust technique for the automatic detection of ellipses from a binary edge image. The current paper introduces some modifications to this algorithm which retain its speed, while increasing its detection performance. The two algorithms are then compared for the application of detecting wheels within images using a data-set of 100 images of cars.
Error Probability Analysis of a Novel Adaptive Beamforming Receiver for Large-Scale MIMO Communication System

A novel adaptive beamforming receiver is proposed for a multiple-input multiple-output (MIMO) communication system over multipath fading channels. By dividing a large number of receive antennas into many adaptive beamformers (ABFs), the proposed system reduces the array dimension in order to simplify the signal detection process and enjoys the benefit of beamforming techniques to improve the symbol-error rate (SER) performance. The effectiveness of the proposed system depends on the number of ABFs and the number of antennas per ABF. The statistical properties of complex Wishart matrices are applied to analyze the SER performance of the proposed system with both maximum-likelihood (ML) detection and zero-forcing (ZF) detection. Furthermore, we have derived an upper bound for SER of the ML detection based on the smallest eigenvalue distribution. Through our analysis, it has been shown that the proposed system using ML detection provides comparable SER performance, but with a lower complexity as compared to that of a conventional ML receiver due to reduced array dimensions.
Contrary Motion: An Oppositional Interactive Music System

The hypothesis of this interaction research project is that it can be stimulating for experimental musicians to confront a system which ‘opposes’ their musical style. The ‘contrary motion’ of the title is the name of a MIDI-based realtime musical software agent which uses machine listening to establish the musical context, and thereby chooses its own responses to dierentiate its position from that of its human interlocutant. To do this requires a deep consideration of the space of musical actions, so as to explicate what opposition should constitute, and machine listening technology (most prominently represented by new online beat and stream tracking algorithms) which gives an accurate measurement of player position so as to consistently avoid it. An initial pilot evaluation was undertaken, feeding back critical data to the developing design.
Ric-3 Promotes α7 Nicotinic Receptor Assembly and Trafficking through the ER Subcompartment of Dendrites

The function of Ric-3, which is required for nicotinic acetylcholine receptor (nAChR) expression in C. elegans, is unclear. Here we found that Ric-3 can promote or inhibit cell-surface delivery of α-bungarotoxin-binding nAChRs (BgtRs) composed of α7 subunits. At low levels, Ric-3 promoted BgtR assembly, endoplasmic reticulum (ER) release, and cell-surface delivery without trafficking from the ER. At high Ric-3 levels, Ric-3 suppressed BgtR surface delivery, but not its assembly, and BgtRs were retained in the ER or in Ric-3-containing aggregates. In PC12 cells, native BgtRs trafficked to the cell surface from the ER where low levels of endogenous Ric-3 were observed. In cultured neurons, native Ric-3 levels were higher than in PC12 cells, and Ric-3 and α7 subunits were found in somata and dendrites, but not axons, of inhibitory interneurons. Ric-3 trafficked with α7 subunits in rapidly moving vesicles to dendrites, where it was restricted to the ER subcompartment. We conclude that Ric-3 has two potential functions. At low levels, Ric-3 interactions are short-lived and promote BgtR assembly and ER release. At higher levels, Ric-3 interactions are longer-lived and mediate ER retention. In neurons, Ric-3 ER retention appears to promote transport within the dendritic ER subcompartment, thereby restricting α7 trafficking to dendrites and preventing axonal transport.
Coalitional Auralities: Notes on a Soundtrack to Punks, Bulldaggers, and Welfare Queens

Abstract:This GLQ forum celebrates the twentieth-anniversary publication of Cathy Cohen's "Punks, Bulldaggers, and Welfare Queens: The Radical Potential of Queer Politics? " The forum opens with Cohen's reflection on the article she wrote twenty years ago. Other authors in the forum then ruminate on such topics as the potential erasure of the queer political history that the original article provoked readers to consider in the time during and since its printing, the haunting answer to the original article's haunting subtitular question—"the radical potential of queer politics? ," and new political alliances that might fit under the rubric of queer in our contemporary moment.
Integrated scheduling, allocation and binding in High Level Synthesis for performance-area tradeoff of digital media applications

This paper presents a novel Genetic Algorithm based exploration approach for integrated scheduling, allocation and binding in High Level Synthesis for Digital Media applications. The contributions of the proposed approach in this paper are: (a) Exploration of performance-hardware area tradeoffs of DSP digital media applications (b) Novel multi structure topology for chromosome encoding (c) Introduction of a novel cost function based on data pipelined performance-hardware area constraints (d) Novel load factor heuristic for chromosome decoding (e) Novel seeding process of the initial population based on serial and parallel implementation logic (f) Novel merit score (M-score) technique to assess the efficiency of the proposed approach (g) Novel cost value (C-value) metric that assesses the quality of final integrated solution. The proposed approach obtained an improvement of ≈ 2 % in quality of final solution compared to a current technique as well as achieved an efficiency of 58.33 % compared to same current approach, when applied on the digital media applications.
Energy-Accuracy Aware Localization for Mobile Devices

Mobile applications often need location data, to update locally relevant information and adapt the device context. While most smart-phones do include a GPS receiver, its frequent use is restricted due to high battery drain. We design and prototype an adaptive location service for mobile devices, a-Loc, that helps reduce this battery drain. Our design is based on the observation that the required location accuracy varies with location, and hence lower energy and lower accuracy localization methods, such as those based on WiFi and cell-tower triangulation, can sometimes be used. Our method automatically determines the dynamic accuracy requirement for mobile search-based applications. As the user moves, both the accuracy requirements and the location sensor errors change. A-Loc continually tunes the energy expenditure to meet the changing accuracy requirements using the available sensors. A Bayesian estimation framework is used to model user location and sensor errors. Experiments are performed with Android G1 and AT&T Tilt phones, on paths that include outdoor and indoor locations, using wardriving data from Google and Microsoft. The experiments show that a-Loc not only provides significant energy savings, but also improves the accuracy achieved, because it uses multiple sensors.
Classification of Software Defect Detected by Black-Box Testing: An Empirical Study

Software defects which are detected by black box testing (called black-box defect) are very large due to the wide use of black-box testing, but we could not find a defect classification which is specifically applicable to them in existing defect classifications. In this paper, we present a new defect classification scheme named ODC-BD (Orthogonal Defect Classification for Black-box Defect), and we list the detailed values of every attribute in ODC-BD, especially the 300 detailed black-box defect type. We aim to help black-box defect analyzers and black-box testers improve their analysis and testing efficiency. The classification study is based on 1860 black-box defects collected from 39 industry projects and 2 open source projects. Furthermore, two empirical studies are included to validate the use of our ODC-BD. The results show that our ODC-BD can improve the efficiency of black-box testing and black-box defect analysis.
Addressing Effective Hidden Web Search Using Iterative Deepening Search and Graph Theory

Deep web refers to the hidden portion of the WWW (World Wide Web) which cannot be accessed directly. One of the important issues in the WWW is how to search the hidden Web. Several techniques have been proposed in order to address this issue. In this paper, we have surveyed the current problems of retrieving information from hidden Web and proposed a solution to solve these problems using probability, iterative deepening search and graph theory.
Automatic Identifying Entity Type in Linked Data

Type information is an important component of linked data. Unfortunately, many linked datasets lack of type information, which obstructs linked data applications such as question answering and recommendation. In this paper, we study how to automatically identify entity type information from Chinese linked data and present a novel approach by integrating classification and entity linking techniques. In particular, entity type information is inferred from internal clues such as entity’s abstract, infobox and subject using classifiers. Moreover, external evidence is obtained from other knowledge bases using entity linking techniques. To evaluate the effectiveness of the approach, we conduct preliminary experiments on a real-world linked dataset from Zhishi.me 1 . Experimental results indicate that our approach is effective in identifying entity types.
How and Much Does the Housing Market Pay for Environmental Amenity? A Malaysian Case

There has been no empirical evidence of the importance of environmental amenity to house price reported from a developing market. This paper fills in the gap by taking the state of Terengganu, Malaysia as a case study. Based on the stated preferences for environmental amenity among potential home-buyers and 442 sale transactions recorded between 2006 and 2010, environmental amenity elements were included in the hedonic model of house price. The empirical results were generally consistent with those obtained from respondents’ feedbacks. This paper concludes that there is evidence to show that the housing market the study area places a significant importance of environmental amenity. As an implication, environmental amenity should remain as a major factor in a sustainable housing market in Malaysia.
Bridge Three-Port Converters for Solar Power Systems

Abstract: A Three Port Converter (TPC), which can interface with renewable sources, storage elements and loads simultaneously, is a good candidate for the solar power systems. My aim is to produce constant output power in all times (day & night). So I used three port full bridge converters in solar electrical energy. A systematic method for generating Three Port Converter topologies from Full Bridge Converters are described here. By using this systematic method, a novel full-bridge TPC (FB-TPC) is developed for renewable power system applications which feature simple topologies and control, a reduced number of devices and single-stage power conversion between any two of the three ports. This method splits the two switching legs of the FBC into two switching cells with different sources and allows a dc bias current in the transformer. The FB-TPC consists of two bidirectional ports and an isolated output port. The primary circuit of the converter functions as a buck-boost converter and provides a power flow path between the ports on the primary side, while the third port provides the power balance in the system ports. The full bridge three port converter is designed and simulated using MATLAB/SIMULINK. The output parameters such as output voltage, current and power were obtained.
Uniformity Level Approach to Fingerprint Ridge Frequency Estimation

segmentation, normalization, filtering, binarization and filtering. Each of these stages has proved to be very essential for achieving a well enhanced fingerprint image. The major prerequisites to filtering a fingerprint image are ridge orientation and frequency estimations. While ridge orientation estimation is done to obtain the orientation of the ridges, ridge frequency estimation is done with a view to ascertaining the number of ridges within a unit length. The number is useful for fingerprint image filtering. In this paper, a modified fingerprint ridge frequency estimation algorithm is implemented. The modified algorithm consists of stages for estimating ridge orientation and uniformity levels. Two types of images; namely synthetic and real fingerprints were used to evaluate the performance of the algorithm. The results of the evaluation reveal that the modified algorithm shows greater speed and effectiveness than its original version. Facts also emerged on the basic characteristics of the estimates.
A Novel EOG/EEG Hybrid Human–Machine Interface Adopting Eye Movements and ERPs: Application to Robot Control

This study presents a novel human-machine interface (HMI) based on both electrooculography (EOG) and electroencephalography (EEG). This hybrid interface works in two modes: an EOG mode recognizes eye movements such as blinks, and an EEG mode detects event related potentials (ERPs) like P300. While both eye movements and ERPs have been separately used for implementing assistive interfaces, which help patients with motor disabilities in performing daily tasks, the proposed hybrid interface integrates them together. In this way, both the eye movements and ERPs complement each other. Therefore, it can provide a better efficiency and a wider scope of application. In this study, we design a threshold algorithm that can recognize four kinds of eye movements including blink, wink, gaze, and frown. In addition, an oddball paradigm with stimuli of inverted faces is used to evoke multiple ERP components including P300, N170, and VPP. To verify the effectiveness of the proposed system, two different online experiments are carried out. One is to control a multifunctional humanoid robot, and the other is to control four mobile robots. In both experiments, the subjects can complete tasks effectively by using the proposed interface, whereas the best completion time is relatively short and very close to the one operated by hand.
Learning New Technology: the Polarization of the Wage Distribution

This paper presents novel evidence regarding the relationship between technological progress, occupational tasks and wage inequality. By applying a counterfactual quantile regression analysis to historic U.S. data, we show that the evolution of wage inequality in the lower echelon of the wage distribution was due entirely to a reduction of within-group wage inequality, which was determined, in turn, by more homogeneous remuneration paid to workers performing routine tasks. Changes in the differential between the remuneration paid to technology-complementary and technology-substitute tasks had only a negligible impact on wage inequality among low-wage workers, which casts some doubt on the validity of basing a theory of wage inequality on routinization-biased technical change operating through a labor demand channel. To reconcile the routinization hypothesis with the data, we develop a model in which skill-heterogeneous workers face endogenous occupational choices and learning costs in connection with operating a new technology. Even in the absence of changes in wage differentials, the model argues that technical change can generate an empirically consistent non-monotone effect on wage inequality by affecting the average level of skills within different groups of workers.
Fear of Failure and Entrepreneurial Risk Perception

Abstract The present study provides an understanding of the role of fear of failure in entrepreneurial decision making by examining the mediating role of appraisal dimensions through the study of the impact of fear (state and trait) on entrepreneurial risk perception and using the cognitive-motivational-relational process and the Appraisal Tendencies Framework as based theories. Using a sample of students, we confirmed that trait fear is significantly related with higher entrepreneurial risk perception and this relation is mediated by cognitive appraisal dimensions especially the certainty theme. The same relationship is not confirmed for the state fear, even the statistical difference between students in entrepreneurial risk perception due to state fear condition.
People tracking with a mobile robot: a comparison of Kalman and particle filters

People tracking is an essential part for modern service robots. In this paper we compare three different Bayesian estimators to perform such task: Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF) and Sampling Importance Resampling (SIR) Particle Filter. We give a brief explanation of each technique and describe the system implemented to perform people tracking with a mobile robot using sensor fusion. Finally, we report several experiments where the three filters are compared in terms of accuracy and robustness. In particular we show that, for this kind of applications, the UKF can perform as well as a particle filter but at a much lower computational cost.
A network architecture for providing per-flow delay guarantees with scalable core

Many real-time applications demand delay guarantees from the network. A network architecture designed to support these applications should be robust and scalable. The IntServ architecture provides per-flow QoS at the cost of robustness and scalability. The DiffServ architecture is robust and scalable but can provide QoS at a class level and not at a flow level.In this paper, our aim is to design architectures that are scalable and robust like DiffServ and at the same time able to provide per-flow QoS like IntServ. We propose a non work-conserving and a work-conserving architecture to achieve this goal. The guaranteeable delay regions of these architectures are the same as those of GPS based policies with rate proportional resource allocation. We also propose a scheme to provide meaningful throughput and responsiveness to best effort traffic even in the presence of heavy QoS load.
The case against controlled release lipoic acid:

Author's note: The following paper critically reviews claims that controlled release lipoic acid (CRLA) is the superior form of lipoic acid (LA) for nutritional and therapeutic uses. Although our position is forthright, our intention is to bring the relevant issues to the forefront of medical and scientific discussion and review. To date, CRLA has not been subjected to any challenges.
Integrating an HIV/HCV Brief Intervention in Prisoner Reentry: Results of a Multisite Prospective Study

Abstract Brief interventions to reduce harmful or problem behaviors have become increasingly popular in a variety of health fields, including HIV and hepatitis risk reduction. A central issue in intervention research involves the evaluation of what constitutes an effective “dose” of an intervention. This research examines the relative effectiveness of three alternative brief interventions of varying intensity designed to change the risk behaviors of inmates who are reentering society: a DVD-based, peer delivered intervention; the N1DA Standard HIV Intervention; and a standard practice condition (HIV educational video). All participants randomly received one of the interventions and were tested for HIV and HCV prior to release from custody. Thirty and ninety-day follow-ups examined changes in high-risk behaviors. Results reported here for 343 subjects who have completed the 90-day follow up indicate significant reductions in reported sexual risk behaviors for those participating the DVD intervention, compared to the other two brief interventions. This study is among the first to report any positive impacts on sexual behaviors among a population of inmates returning to the community.
Statistical Approach for Tapered Bearing Fault Detection using Different Methods

tools and the results were subsequently compared and it was found that the laser vibrometer gave higher kurtosis values and hence was more sensitive to bearing damage than the accelerometers. However, the accelerometers which were attached directly to the tapered bearing casing gave higher vibration values. From this study it can be recommended that in places where high sensitivity is extremely important it recommended that laser vibrometers be used.
Switching Activity Based Method for Minimizing Testing Power in Digital Circuits

Optimization of testing power is a major signiflcant task to be carried out in digital circuit design. Low power VLSI circuits dissipate more power during testing when compared with that of normal operation. In this paper a novel method is proposed to reduce the testing power and total energy by reordering the sequence of test vectors for minimum switching activity of the Circuit Under Test (CUT). Graph theory concept is used to develop the reordering algorithm which is based on heuristic approach to flnd near optimal solution for the problem. Fault coverage of the CUT is not afiected in this algorithm. The reduction of power dissipation and total energy during testing leads to increase in reliability of the circuit. Experimental results of the proposed algorithm with ISCAS85 benchmark circuits show that the switching activity is reduced signiflcantly compared to existing works.
Extracting Assumptions from Missing Data

Information integration is the task of aggregating data from multiple heterogeneous data sources. The understandings of context knowledge of data sources are often the keys to challenging problems in information integration such as handling missing and inconsistent data. Context logic provides a uni- fied framework for the modeling of data sources; nevertheless, the acquisition of large amounts of context knowledge is difficult. In this paper, we study the importance of a special type of context knowledge, namely assumption knowl- edge. Assumption knowledge refers to a set of implicit rules about assumptions on which a data source is based. We develop a decision tree classifier to ex- tract assumption knowledge from missing data and formalize the knowledge in context logic. Finally, we build an information aggregator with assumption knowledge reasoning, which is capable of explaining incomplete data aggre- gated from heterogeneous sources.
Neti Neti: in search of deity

A wide category of objects and scenes can be effectively searched and classified using the modern descriptors and classifiers. With the performance on many popular categories becoming satisfactory, we explore into the issues associated with much harder recognition problems. We address the problem of searching specific images in Indian stone-carvings and sculptures in an unsupervised setup. For this, we introduce a new dataset of 524 images containing sculptures and carvings of eight different Indian deities and three other subjects popular in the Indian scenario. We perform a thorough analysis to investigate various challenges associated with this task. A new image-representation is proposed using a sequence of discriminative patches mined in an unsupervised manner. For each image, these patches are identified based on their ability to distinguish the given image from the image most dissimilar to it. Then a rejection-based re-ranking scheme is formulated based on both similarity as well as dissimilarity between two images. This new scheme is experimentally compared with two baselines using state-of-the-art descriptors on the proposed dataset. Empirical evaluations demonstrate that our proposed method of image-representation and rejection cascade improves the retrieval performance on this hard problem as compared to the baseline descriptors.