Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative study of imaging transforms on diabetic retinopathy images

Retinal images are important in detection of ocular diseases. The retinal images have been evaluated and it has been used by doctors for the identification of retinal diseases like Diabetic Retinopathy and Hypertension. These images have low dynamic range and grey level contrast range. There are many alternative image enhancement techniques used for particular applications so that better diagnostic results can be obtained. This paper throws light on the uses of new imaging transform techniques for enhancement of retinal images like wavelet transform, curvelet transform and contourlet transform. The existing algorithms have been studied and the advantages and drawbacks of those algorithms are analysed and this paper gives clear picture of comparison between three imaging transforms. After experimental analysis contourlet transform gave best results for detection of edges compared to other two techniques. This method has been performed by calculating the Peak to signal noise ratio from datasets such as Drive and from medical institutions.
Carousel rides new tools for navigation in intangible Cultural Heritage

The creation of new tools to navigate the intangible cultural heritage data goes through the analysis of available data and their integration with new information that can be obtained either automatically, developing specific algorithms, either manually by intervention of sector experts. This new information, combined with those already available, permit the construction of recreational paths and discovery games that enable even a less experienced audience coming in contact with the intangible heritage. In this paper we present a work in progress to show new tools to navigate the intangible in different ways.
Application of Vibration and Acoustic Pressure Monitoring Techniques for Detection of Gear Failures

Manufacturing industry drives the world. Every manufacturing industry is having number of machines and gearboxes, which are used for power conversion, speed, reduction and torque amplification, can control many of them. Any defect induced in gear may costs high at the time of failure. For that early prediction of breakage of gear tooth is essential to avoid stoppage of that machine thereby increase in utilization. Condition monitoring is gaining importance because it can make contribution towards reducing equipments downtime and maintenance expenditure. It can also contribute towards safety in critical application by monitoring an early warning of potential catalostropic failure. This paper commences with various condition monitoring techniques used for detection of gear failure. It mainly consists of vibration monitoring and acoustic pressure monitoring techniques. Monitoring techniques are discussed with respect to frequency domain analysis. Various faults are induced into the gearbox such as crack on one tooth, broken tooth, wear of teeth, improper lubrication. For these faults detailed analysis were done.
Children and managed health care: analysis and recommendations.

Arevolution in health care has taken place during the past decade in the United States. The revolution was ignited by skyrocketing health care costs1 and fueled by the widespread public sentiment that the high cost of health care was the most important problem in the health care industry.2 The health insurance industry and providers responded to the public’s outcry by creating lower-cost health care insurance alternatives—managed health care plans. Managed health care is a vast array of financing and health care delivery systems that are designed to limit costs and ration health care. Employers and individuals seized the opportunity to lower their health care costs and began to buy these managed health care plans. Today, managed care plans are pervasive; 85% of all employed families and a growing number of those covered by Medicaid are in managed health care plans.3,4 By choosing managed health care, U.S. employers and consumers have changed the nation’s health care system.
Power Controlled Routing inWireless Multihop Communication for Higher End-to-End Bandwidth

In a wireless mobile network with wireless multihop transmissions such as a mobile adhoc network and a wireless multihop access network, end-to-end bandwidth from a source mobile computer to a destination one is less than 1/3 of bandwidth of a wireless communication link due to random waiting time for contention avoidance and RTS/CTS control for solving a hidden terminal problem. In this paper, the authors propose an adhoc routing protocol and a message transmission protocol with transmission power control for achieving higher end-to-end bandwidth. The maximum end-to-end bandwidth in the proposed protocols is 1/2 of bandwidth of a wireless communication link. Simulation results show that the proposed protocol provides about 60% higher end-to-end bandwidth than a conventional no power control protocol. In addition, it provides almost the same connectivity with conventional no power control protocols if density of mobile computers is sufficiently high.
Why Be Robust? The Contribution of Market Process Theory to the Robust Political Economy Research Program

How can liberal political theorists combine their normative commitments with realistic assumptions of human behaviour and capacities? This is an important question for scholars who wish to use their theories to evaluate existing political institutions and recommend practical alternatives. This chapter describes a particular approach to realism in political theory by using the notion of ‘robustness’ from the Robust Political Economy framework. Robust institutions are those that perform well even when people are neither omniscient nor perfectly motivated to follow the common good. I argue that these problems, of limited knowledge and self-interest, emerge from three assumptions about the constitution of human beings commonly found in the liberal theoretical tradition: methodological individualism, subjectivism and analytical egalitarianism. I propose a combination of public choice and market process theory as best suited to the task of evaluating the robustness of normative political theories because they allow us to apply these assumptions systematically to all domains of human activity. Compared to standard neo-classical methodology, this approach offers an enriched account of the epistemic challenge to social co-operation that individuals face and the role of institutions, including private property and voluntary exchange, in ameliorating this challenge. I show how this systematic evaluation of the motivational and epistemic properties of institutions can help critique and extend Rawls’ contractarian theory of justice and offer a new perspective on the role of realism in political theory.
Teacher Professional Development in Hong Kong Compared to Anglosphere: the Role of Confucian Philosophy

Teacher Professional Development” (aka teacher PD) has garnered research attention in recent years. Scholars seek to understand the teacher PD process, while practitioners are interested in deriving policies to facilitate teacher PD. The consensus emerging from the pool of literature is that teacher PD should be “individualized”: more focused on fostering teachers’ personal growth instead of enforcing “standard practices”. The Anglosphere has been leading in the domain of teacher PD, causing many regions to imitate its practices. Using documentary analysis, this paper reviews teacher PD policies in Hong Kong over the past forty years and compares them with practices typically adopted in the Anglosphere. The paper suggests that the PD policies of Hong Kong progressed from ‘solely teacher training’, to ‘emphasis on generic skills’, to ‘lifelong learning’. The concept of ‘Confucian Heritage Culture’ is used to explain the differences between the Angloshpere and Hong Kong in terms of PD practices. Implications for adapting teacher PD practices cross-culturally are discussed.
UI generation from task, domain and user models: the DB-USE approach

Information Systems UI (User Interface) generation from declarative models has been the focus of numerous and various approaches in the human computer interaction community. Typically, the different approaches use the different models based on their singular aspects. This paper proposes a new process that combines the task, domain, and user models taken together to drive the information system user interface design and code behind generation. To this end, we propose a framework, i.e., a methodological process, a meta-model and a software prototype called DB-USE.
Time-domain noise subtraction applied in the analysis of Lombard speech

This paper presents results of the comparison between speech produced in silence and speech in noise, also known as Lombard speech. A temporal filtering algorithm was developed which successfully removes the ambient noise from recordings of Lombard speech by locating and subtracting a recording of the noise performed in the same environment. The filtering algorithm yields overall noise attenuation between 15 and 30 dB without distorting the speech signal like spectral filtering approaches. In the subsequent acoustic analyses we examined the effect of varying levels of noise on vowel formants, glottal spectra and intensity. For most vowels we found significant rises in F1 and F2, but little variation in formant bandwidth. The overall rise in intensity between silent and 80 dB babble noise conditions was found to be of 9 dB. With growing effort higher harmonics are boosted by up to 6 dB whereas the average speech rate only drops by 5%. In Lombard speech the standard deviation of phone intensity is reduced.
Understanding Antibiotic Use in Minya District, Egypt: Physician and Pharmacist Prescribing and the Factors Influencing Their Practices

Overuse of antibiotics has contributed to the emergence of antibiotic-resistant bacteria globally. In Egypt, patients can purchase antibiotics without a prescription, and we hypothesized frequent inappropriate antibiotic prescribing and dispensing. We interviewed physicians (n = 236) and pharmacists (n = 483) and conducted focus groups in Minya, Egypt, to assess attitudes and practices regarding antibiotic prescribing for outpatient acute respiratory infections (ARI). Antibiotics were reportedly prescribed most of the time or sometimes for colds by 150 (64%) physicians and 326 (81%) pharmacists. The most commonly prescribed antibiotics were β-lactams. Macrolides were the second most commonly prescribed for colds and sinusitis. The prescription of more than one antibiotic to treat pneumonia was reported by 85% of physicians. Most respondents thought antibiotic overuse contributes to resistance and reported “patient self-medication” as the biggest driver of overuse. Fifty physicians (21%) reported that they had prescribed antibiotics unnecessarily, citing patient over-the-counter access as the reason. Physicians <40 years of age and those who treat adults were more likely to prescribe antibiotics for colds. Overall, we found a high rate of unwarranted outpatient antibiotic prescribing and dispensing for ARIs. Patient access to OTC antibiotics contributes to over-prescribing. National guidelines for ARI treatment, provider education and national policy requiring a physician’s prescription for antibiotics may improve appropriate antibiotic use in Egypt.
The neural basis of mirror symmetry detection: a review

ABSTRACT The human visual system is extremely sensitive to the presence of bilateral (mirror) symmetry. In this review, I summarise the results of recent work investigating the neural basis of mirror symmetry detection, focusing in particular on brain stimulation evidence. Overall, available findings converge in pointing to the lateral occipital (LO) complex, especially in the right hemisphere, as a key region causally involved in symmetry detection. Interestingly, they also suggest that another region in the right extrastriate visual cortex, the occipital face area (OFA), is causally implied in symmetry detection, posing an interesting connection at the neural level between visual cortex responses to faces and to symmetry. Finally, this review also considers evidence on haptic symmetry detection in sighted and early blind individuals that points to LO as a multi-modal symmetry-sensitive region, and suggests that symmetry is a salient perceptual feature mediated by LO even when any visual experience is missing.
Rechargeable router placement with guaranteed QoS for green WLAN mesh networks

Nowadays, to solve the challenges of increasing energy consumption in communication networks, green mesh networks consisting of routers using renewable energy sources have been emerging as a promising solution. In this paper, we revisit the traditional router placement problem with QoS requirements and energy constraints in green WLAN Mesh Networks and introduce a new concept of failure rate to evaluate network performance. We formulate the rechargeable router placement as an optimization problem to minimize the required routers while guaranteeing the system QoS, including users' traffic demand, routers' energy consumption and network failure rate requirement. Furthermore, we propose a nearest cell association algorithm to reassign users to routers at different times and propose a greedy search algorithm to find approximate solutions for the router placement problem. Simulation results show that compared with the optimal placement achieved by exhaustive search, our proposed algorithm can achieve good performance with the significantly reduced computation complexity.
Privacy preserving database access through dynamic privacy filters with stable data randomization

There are scenarios where using production databases for testing are unavoidable. In a time/mission-critical situation where a developer is required to fix a bug immediately the only option is use production database for testing. However, this may pose a violation of privacy. In this paper, we describe a different approach utilizing a privacy filter that examines queries from an application to match with predefined privacy policy to decide the result return. The approach is illustrated using a prototype which was implemented with query modification and data randomization techniques.
Digital 0.0

Stellen Sie sich vor, 1. Deutschlands Chef-Feuerwehrmann empfiehlt Brandbeschleuniger zum Löschen, und 2. Deutschlands Chirurgen empfehlen neue Operationsmethoden, bei denen bisher alle Patienten verstorben sind. Man müsse eben nur noch die richtigen Konzepte für deren Anwendung erarbeiten, aber diese Kleinigkeiten sollten der Einführung der neuen Technologie jetzt sofort doch wirklich nicht im Wege stehen, 3. dass die deutsche Automobilindustrie den Führerschein für 3-Jährige fordert. Schließlich müsse man die Kleinen frühzeitig auf die neue Technologie der Fortbewegung vorbereiten. Deutschland sei nun einmal die Welt-Auto-NationNummer 1 und da könne man sich nicht leisten, gegenüber anderen zurück zufallen, 4. dass die SPD vorschlägt, man solle die Unterschiede zwischen Arm und Reich vergrößern, ist schwer vorzustellen, aber versuchen Sie es bitte trotzdem, 5. dass die Vereinigung der deutschen Winzer und Bierbrauer durchgesetzt hat, dass im Land des Bieres und Weines die nachkommende Generation endlich schon in Kindergarten und Grundschule flächendeckend und verpflichtend ein Alkoholkompetenztraining erhält – beginnend mit einem halben Schnaps am Tag. Das müsse sein, denn wir wollen unseren Vorsprung im Knowhow nicht verlieren, liegen wir doch im europäischen Durchschnitt beim Schnaps-Ausschank in unseren Bildungseinrichtungen deutlich abgeschlagen im unteren Mittelfeld. Sie können sich das nicht vorstellen? Dann lesen Sie weiter, denn genau dies ist in Deutschland Realität! – Nicht bei der Feuerwehr, den Chirurgen, im Autooder Weinbaubau, sondern nur beim wertvollsten, wichtigsten, uns allen am nächsten liegenden höchsten Gut, das wir überhaupt haben – unseren Kindern. Wir wissen, was ihnen gut tut und was nicht – aufgrund zahlreicher wissenschaftlicher Untersuchungen aus Medizin, Psychologie, Entwicklungspsychologie, Entwicklungsneurobiologie und kognitiver Neurowissenschaft. Junge Menschen brauchen Kontakt mit ihresgleichen, mit verständnisund liebevollen Erwachsenen und mit der Natur. Den Umgang mit digitaler Informationstechnik hingegen – sei es in der Freizeit oder in Bildungseinrichtungen wie Kindertagesstätten und Schulen – brauchen sie nicht.
Supramodal Effects of Covert Spatial Orienting Triggered by Visual or Tactile Events

Event-related functional magnetic resonance imaging was used to identify brain areas involved in spatial attention and determine whether these operate unimodally or supramodally for vision and touch. On a trial-by-trial basis, a symbolic auditory cue indicated the most likely side for the subsequent target, thus directing covert attention to one side. A subsequent target appeared in vision or touch on the cued or uncued side. Invalidly cued trials (as compared with valid trials) activated the temporo-parietal junction and regions of inferior frontal cortex, regardless of target modality. These brain areas have been associated with multimodal spatial coding in physiological studies of the monkey brain and were linked to a change in the location that must be attended to in the present study. The intraparietal sulcus and superior frontal cortex were also activated in our task, again, regardless of target modality, but did not show any specificity for invalidly cued trials. These results identify a supramodal network for spatial attention and reveal differential activity for inferior circuits involving the temporo-parietal junction and inferior frontal cortex (specific to invalid trials) versus more superior intraparietal-frontal circuits (common to valid and invalid trials).
Lobster Robots 12

We are developing lobster-based underwater robots based on biomimetic neurotechnology. The robots employ a lobster-like physical plant with modularized three degree-of-freedom legs, claw and tail-like hydrodynamic control surfaces, adaptive antennal-like sensors and a neural-circuit based finite-state-machinebased controller. The behavior of this system is based on a library of action patterns reverse engineered from the behavior of the lobsters in the target operational environment. Fig. 1. Lobster Robot Prototype.
Tracking Performance of Semi-Supervised Large Margin Classifiers in Automatic Modulation Classification

Automatic modulation classification (AMC) in detected signals is an intermediate step between signal detection and demodulation, and is also an essential task for an intelligent receiver in various civil and military applications. In this paper, we propose a semi-supervised Large margin AMC and evaluate it on tracking the received signal to noise ratio (SNR) changes to classify most popular single carrier modulations in non-stationary environments. To achieve this objective, two structures for self-training of large margin classifiers were developed in additive white Gaussian noise (AWGN) channels with priori unknown SNR. A suitable combination of the higher order statistics (HOS) and instantaneous characteristics of digital modulation are selected as effective features. We investigated the robustness of the proposed classifiers with respect to different SNRs of the received signals via simulation results and we have shown that adding unlabeled input samples to the training set, improve the tracking capacity of the presented system to robust against environmental SNR changes. The performance of the automatic modulation classifier is presented in the form of k-fold cross-validation test, classification accuracy and confusion matrix methods. Simulation results show that the proposed approach is capable to classify the modulation class in unknown variable noise environment at even low SNRs.
Meeting Report: Alternatives for Developmental Neurotoxicity Testing

Developmental neurotoxicity testing (DNT) is perceived by many stakeholders to be an area in critical need of alternatives to current animal testing protocols and guidelines. To address this need, the Johns Hopkins Center for Alternatives to Animal Testing (CAAT), the U.S. Environmental Protection Agency, and the National Toxicology Program are collaborating in a program called TestSmart DNT, the goals of which are to: (a) develop alternative methodologies for identifying and prioritizing chemicals and exposures that may cause developmental neurotoxicity in humans; (b) develop the policies for incorporating DNT alternatives into regulatory decision making; and (c) identify opportunities for reducing, refining, or replacing the use of animals in DNT. The first TestSmart DNT workshop was an open registration meeting held 13–15 March 2006 in Reston, Virginia. The primary objective was to bring together stakeholders (test developers, test users, regulators, and advocates for children’s health, animal welfare, and environmental health) and individuals representing diverse disciplines (developmental neurobiology, toxicology, policy, and regulatory science) from around the world to share information and concerns relating to the science and policy of DNT. Individual presentations are available at the CAAT TestSmart website. This report provides a synthesis of workgroup discussions and recommendations for future directions and priorities, which include initiating a systematic evaluation of alternative models and technologies, developing a framework for the creation of an open database to catalog DNT data, and devising a strategy for harmonizing the validation process across international jurisdictional borders.
Hierarchical Models for 3 D Visual Inference

Recent research in visual inference from monocular images has shown that discriminatively trained image-based predictors can provide fast, automatic qualitative 3d visual reconstructions (human poses, dominant scene ground planes or facades) in real scenes. However, the stability of existing image representations tends to be perturbed by deformations and misalignments in the training set, which degrades the quality of learning and generalization. Instead, we advocate the use of hierarchical image descriptions in order to better tolerate variability at multiple levels of detail. We combine multilevel encodings with improved stability to geometric transformations, with metric learning and semi-supervised manifold regularization methods in order to further profile them for task-invariance – resistance to clutter and ‘within the same human pose class’ differences. We analyze the effectiveness of both descriptors and metric learning methods and show that each one can contribute, often substantially, to better 3d human pose estimates in cluttered images. Existing methods have successfully demonstrated that bag of features or regular-grid based representations of local descriptors (e.g. bag of shape context features, block of SIFT features [9, 1, 10] can be surprisingly effective at predicting 3d human poses, but the representations tend to be too inflexible for reconstruction in general scenes. It is more appropriate to view them as two useful extremes of a multilevel, hierarchical representation of images – a family of descriptors that progressively relaxes block-wise, rigid local spatial image encodings to increasingly weaker spatial models of position / geometry accumulated over increasingly larger image regions. Selecting the most competitive representation for an application (a typical set of people, motions, backgrounds or scales) reduces to either directly or implicitly learning a metric in the space of image descriptors, so that both good invariance and distinctiveness is achieved, e.g., for 3d reconstruction – suppress noise by maximizing correlation within the desired pose invariance class, but keep different classes separated, and turn off components that are close to being statistical random for the task of prediction, disregarding the class. Our research relies on techniques from object recognition, metric learning and semi-supervised learning, as follows: