Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning by watching Vernacular Iñupiaq-Inuit design learning as inspiration for design education

In this article, I explore a single case of vernacular clothing design — the practice and learning of design for contemporary Inupiaq-Inuit clothing made by women from Kaktovik in Northern Alaska — and I hope to contribute to a better understanding of design practice and learning in general. Design research has many unexplored areas, and one of these omissions is vernacular design, or folk design. In my opinion, professional and academic design may well have something to learn from vernacular design, although this research is about vernacular learning and about what, why and how the‘making’ discipline of clothing design is learned. This study was based on observations of and interviews with seamstresses and research-by-design, which includes authorial participation in designing and sewing in adherence to Inupiaq tradition. All of this was recorded on digital video film. The investigation of Inupiaq-Inuit clothing design indicates that watching was the most common way of learning, a phenomenon I have chosen to call learning-by-watching, a concept that can be seen as a development of both Schon and Wenger’s theories of learning, as influenced by John Dewey’s theory of learning-by-doing. This study will be discussed in connection with design education, from kindergarten to professional studies in higher education, in the forthcoming research project, Design Literacy, the purpose of which is to develop theory to improve design education in both compulsory and academic design education. Consequently, to improve design education in general, a thorough focus on learning-by-watching in communities of practice would make for more reflective practitioners and more sustainable design practices in the long run.Keywords: Vernacular design, clothing design, design thinking, learning-by-watching, learning-bydoing.
Data collection for the MASK kiosk: WOz vs. prototype system

The MASK consortium is developing a prototype multimodal multimedia service kiosk for train travel information and reservation, exploiting state of the art speech technology. We report on our efforts aimed at evaluating alternative user interface designs and at obtaining acoustic and language modeling data for the spoken language component of the overall system. Simulation methods with increasing degrees of complexity have been used to test the interface design, and to experiment with alternate operating modes. The majority of the speech data has been collected using successive versions of the spoken language system, whose capabilities are incrementally expanded after analysis of the most frequent problems encountered by users of the preceding version. The different data requirements of user interface design and speech corpus acquisition are discussed in light of the experience of the MASK project.
A female-specific cDNA sequence of Schistosoma mansoni encoding a mucin-like protein that is expressed in the epithelial cells of the reproductive duct

SUMMARY Seven cDN A clones of Schistosoma mansoni containing the C-terminal part of the deduced sequence of a mucin-like protein have been identified. The protein contains 28% threonines, 20% serines, and has a pi of 3middot;4. On Northern blots of RNA of adult worms, the cDNA clones detect 2 transcripts of 1middot;65 and 4middot;2 kb which are expressed only in female worms. The tissue of gene expression, as revealed by in situ hybridization, is the epithelium surrounding the female reproduction duct proximal to its entrance into the ootype. Accumulation of N-glycosylation sites suggests that the protein, like other mucins, might form a protective layer, coating the lining of the duct. Regarding its acidic pi, we hypothesize a role in preventing premature egg-shell formation. This is the first female-specifically transcribed sequence, hitherto known in S. mansonithat is not expressed in the vitellaria.
Learning Stochastic Bracketing Inversion Transduction Grammars with a Cubic Time Biparsing Algorithm

We present a biparsing algorithm for Stochastic Bracketing Inversion Transduction Grammars that runs in O(bn3) time instead of O(n6). Transduction grammars learned via an EM estimation procedure based on this biparsing algorithm are evaluated directly on the translation task, by building a phrase-based statistical MT system on top of the alignments dictated by Viterbi parses under the induced bigrammars. Translation quality at different levels of pruning are compared, showing improvements over a conventional word aligner even at heavy pruning levels.
AQWA: Adaptive Query-Workload-Aware Partitioning of Big Spatial Data

The unprecedented spread of location-aware devices has resulted in a plethora of location-based services in which huge amounts of spatial data need to be efficiently processed by large-scale computing clusters. Existing cluster-based systems for processing spatial data employ static data-partitioning structures that cannot adapt to data changes, and that are insensitive to the query workload. Hence, these systems are incapable of consistently providing good performance. To close this gap, we present AQWA, an adaptive and query-workload-aware mechanism for partitioning large-scale spatial data. AQWA does not assume prior knowledge of the data distribution or the query workload. Instead, as data is consumed and queries are processed, the data partitions are incrementally updated. With extensive experiments using real spatial data from Twitter, and various workloads of range and k-nearest-neighbor queries, we demonstrate that AQWA can achieve an order of magnitude enhancement in query performance compared to the state-of-the-art systems.
Mode Change Protocol for Multi-Mode Real-Time Systems upon Identical Multiprocessors

Hard real-time systems require both functionally correct executions and results that are produced on time. Control of the traffic (ground or air), control of engines, control of chemical and nuclear power plants are just some examples of such systems. Currently, numerous techniques exist that enable engineers to design realtime systems, while guaranteeing the correctness of their temporal behavior in a systematic way. These techniques generally model each functionality of the system by a recurrent task, characterized by a computing requirement, a temporal deadline and an activation rate. Commonly, real-time systems are modeled by a fixed set of such tasks. However, some applications exhibit multiple behaviors issued from several operating modes (e.g., an initialization mode, an emergency mode, a fault recovery mode, etc.), where each mode is characterized by its own set of functionalities, i.e., its set of tasks. During the execution of such multi-mode real-time systems (described in details in [9]), switching from the current mode (called the old-mode) to another one (the new-mode hereafter) requires to substitute the current executing tasks with the tasks of the target mode. This substitution introduces a transient stage, where the tasks of the oldand new-mode may be scheduled simultaneously, thereby leading to an overload which compromises the system schedulability. The scheduling problem during a transition between two modes has multiple aspects, depending on the behavior and requirements of the oldand new-mode tasks when a mode change is initiated (see e.g., [4], [6]). For instance, an old-mode task may be immediately aborted, or it may require to complete the execution of its current instance in order to preserve data consistency. On the other hand, a new-mode task sometimes requires
Comparative study of proportional-integral, sliding mode and fuzzy logic controllers for power converters

This paper presents a comparative evaluation of the proportional-integral, sliding mode and fuzzy logic controllers for applications to power converters. The mismatch between the characteristics which lead to varying performance is outlined. This paper also demonstrates certain similarities of fuzzy logic controller and sliding mode controller. Sensitivity of these controllers to supply voltage disturbances and load disturbances is studied and results are presented.
Spotting Subsequences Matching an HMM Using the Average Observation Probability Criteria with Application to Keyword Spotting

This paper addresses the problem of detecting keywords in unconstrained speech. The proposed algorithms search for the speech segment maximizing the average observation probability along the most likely path in the hypothesized keyword model. As known, this approach (sometimes referred to as sliding model method) requires a relaxation of the begin/endpoints of the Viterbi matching, as well as a time normalization of the resulting score. This makes solutions complex (i.e., LN2/2 basic operations for keyword HMM models with L states and utterances with N frames). We present here two altemative (quite simple and efficient) solutions to this problem. a) First we provide a method that finds the optimal segmentation according to the criteria of maximizing the average observation probability. It uses Dynamic Programming as a step, but does not require scoring for all possible begin/endpoints. While the worst case remains O(LN2), this technique converged in at most 3(L+2)N basic operations in each experiment for two very different applications. b) The second proposed algorithm does not provide a segmentation but can be used for the decision problem of whether the utterance should be classified as containing the keyword or not (provided a predefined threshold on the acceptable average observation probability). This allows the algorithm to be even faster, with fix cost of (L+2)N.
On the Impact of Prefiltering on Compressed Sensing in Presence of Invalid Measurements

We address the problem of sparse signal recovery in compressed sensing when a fraction of acquired measurements is invalid or damaged. This may occur due to some system malfunction or unreliable transmission medium. The current solution requires increasing the number of measurements to achieve accurate signal recovery, otherwise recovery performance is jeopardized. We study the performance impact of prefiltering the acquired measurements by detecting and omitting potentially invalid measurements prior to signal recovery. We demonstrate analytically and numerically that this approach significantly reduces the number of measurements required for accurate recovery, which leads to overall improvement of recovery performance, especially when a large fraction of measurements is invalid. Therefore, this approach enhances the ability of compressed sensing to tolerate realistic implementation challenges.
Function of weaponry in females: the use of horns in intrasexual competition for resources in female Soay sheep

In many species, females show reduced expression of a trait that is under sexual selection in males, and this expression is thought to be maintained through genetic associations with the male phenotype. However, there is also the potential for the female trait to convey an advantage in intrasexual conflicts over resources. We tested this hypothesis in a feral population of Soay sheep, in which males and females have a polymorphism for horn development, producing either full (normal horned), reduced (scurred) or no (polled, females only) horns. During the lambing period, females who possessed horns were more likely to initiate and win aggressive interactions, independent of age, weight and birthing status. The occurrence of aggression was also context dependent, decreasing over the lambing period and associated with local density. Our results demonstrate that a trait that confers benefits to males during intrasexual competition for mates may also be used by females in intrasexual competition over resources: males use weaponry to gain mates, whereas females use weaponry to gain food.
A double dissociation between striate and extrastriate visual cortex for pattern motion perception revealed using rTMS

The neural mechanisms underlying the integration and segregation of motion signals are often studied using plaid stimuli. These stimuli consist of two spatially coincident dynamic gratings of differing orientations, which are either perceived to move in two unique directions or are integrated by the visual system to elicit the percept of a checkerboard moving in a single direction. Computations pertaining to the motion of the individual component gratings are thought to take place in striate cortex (V1) whereas motion integration is thought to involve neurons in dorsal stream extrastriate visual areas, particularly V5/MT. By combining a psychophysical task that employed plaid stimuli with 1 Hz offline repetitive transcranial magnetic stimulation (rTMS), we demonstrated a double dissociation between striate and extrastriate visual cortex in terms of their contributions to motion integration. rTMS over striate cortex increased coherent motion percepts whereas rTMS over extrastriate cortex had the opposite effect. These effects were robust directly after the stimulation administration and gradually returned to baseline within 15 minutes. This double dissociation is consistent with previous patient data and the recent hypothesis that both coherent and transparent motion percepts are supported by the visual system simultaneously and compete for perceptual dominance. Hum Brain Mapp 2009. © 2009 Wiley‐Liss, Inc.
Integration and segregation of prior outcomes in risky decisions

Two experiments were conducted to test if a prior outcome influences the likelihood to accept a current gamble. Undergraduate students participating as subjects imagined that they on a fictitious betting day at a horse-race track did not gamble in the prior race, that they gambled and won, or that they gambled and lost. Subjects rated in one session the likelihood of gambling in the current race. In another session they rated how satisfied they would be with not gambling, with winning, and with losing, respectively. The results of Experiment 1 showed that as compared to no prior outcome the ratings of likelihood of gambling increased after a gain and decreased after a loss. This was explained by the assumption, supported by the ratings of satisfaction, that the prior outcome only affected the satisfaction with the expected loss of the current choice, making it less negative after a gain and more negative after a loss. These results were replicated in Experiment 2. In addition, if subjects did not know with certainty the outcome of a previous choice to gamble, the likelihood to accept the current gamble and the ratings of the satisfaction with its expected outcomes were largely unaffected.
Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction

Semi-supervised regression based on the graph Laplacian suffers from the fact that the solution is biased towards a constant and the lack of extrapolating power. Based on these observations, we propose to use the second-order Hessian energy for semi-supervised regression which overcomes both these problems. If the data lies on or close to a low-dimensional submanifold in feature space, the Hessian energy prefers functions whose values vary linearly with respect to geodesic distance. We first derive the Hessian energy for smooth manifolds and continue to give a stable estimation procedure for the common case where only samples of the underlying manifold are given. The preference of ''linear" functions on manifolds renders the Hessian energy particularly suited for the task of semi-supervised dimensionality reduction, where the goal is to find a user-defined embedding function given some labeled points which varies smoothly (and ideally linearly) along the manifold. The experimental results suggest superior performance of our method compared with semi-supervised regression using Laplacian regularization or standard supervised regression techniques applied to this task.
A game player expertise level classification system using electroencephalography (EEG)

The success and wider adaptability of smart phones has given a new dimension to the gaming industry. Due to the wide spectrum of video games, the success of a particular game depends on how efficiently it is able to capture the end users’ attention. This leads to the need to analyse the cognitive aspects of the end user, that is the game player, during game play. A direct window to see how an end user responds to a stimuli is to look at their brain activity. In this study, electroencephalography (EEG) is used to record human brain activity during game play. A commercially available EEG headset is used for this purpose giving fourteen channels of recorded EEG brain activity. The aim is to classify a player as expert or novice using the brain activity as the player indulges in the game play. Three different machine learning classifiers have been used to train and test the system. Among the classifiers, naive Bayes has outperformed others with an accuracy of 88 % , when data from all fourteen EEG channels are used. Furthermore, the activity observed on electrodes is statistically analysed and mapped for brain visualizations. The analysis has shown that out of the available fourteen channels, only four channels in the frontal and occipital brain regions show significant activity. Features of these four channels are then used, and the performance parameters of the four-channel classification are compared to the results of the fourteen-channel classification. It has been observed that support vector machine and the naive Bayes give good classification accuracy and processing time, well suited for real-time applications.
Applying Data Mining Techniques to Intrusion Detection in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have become a hot research topic in recent years. They have many potential applications for both civil and military tasks. However, the unattended nature of WSNs and the limited computational and energy resources of their nodes make them susceptible to many types of attacks. Intrusion detection is one of the major and efficient defence methods against attacks in a network infrastructure. Intrusion Detection Systems can be seen as the second line of defence and they complement the security primitives that are adopted in order to prevent attacks against the computer network being protected. The peculiar features of a wireless sensor network pose stringent requirements to the design of intrusion detection systems. In this paper, we propose a hybrid, lightweight, distributed Intrusion Detection System (IDS) for wireless sensor networks. This IDS uses both misuse-based and anomaly-based detection techniques. It is composed of a Central Agent, which performs highly accurate intrusion detection by using data mining techniques, and a number of Local Agents running lighter anomaly-based detection techniques on the motes. Decision trees have been adopted as classification algorithm in the detection process of the Central Agent and their behaviour has been analysed in selected attacks scenarios. The accuracy of the proposed IDS has been measured and validated through an extensive experimental campaign. This paper presents the results of these experimental tests.
Calicivirus emergence from ocean reservoirs: zoonotic and interspecies movements.

Caliciviral infections in humans, among the most common causes of viral-induced vomiting and diarrhea, are caused by the Norwalk group of small round structured viruses, the Sapporo caliciviruses, and the hepatitis E agent. Human caliciviruses have been resistant to in vitro cultivation, and direct study of their origins and reservoirs outside infected humans or water and foods (such as shellfish contaminated with human sewage) has been difficult. Modes of transmission, other than direct fecal-oral routes, are not well understood. In contrast, animal viruses found in ocean reservoirs, which make up a second calicivirus group, can be cultivated in vitro. These viruses can emerge and infect terrestrial hosts, including humans. This article reviews the history of animal caliciviruses, their eventual recognition as zoonotic agents, and their potential usefulness as a predictive model for noncultivatable human and other animal caliciviruses (e.g., those seen in association with rabbit hemorrhagic disease).
Prioritization Preferences among General Practitioners in Hungary

Cost-utility analyses use the quality-adjusted life-year (QALY) as a measure of health benefit. Normally, they treat every QALY gain equally, that is, attach the same weight (or value) to each QALY gained. However, it appears that this practice does not reflect the distributional preferences of the general public nor of health care professionals. Maximizing the QALY gain from a given budget is not the only aim in priority setting. This article presents a study into such distributional preferences of general practitioners (GPs) for prioritization at the patient level in Hungary. Given the special position GPs have in many health care systems, including the Hungarian, more knowledge of their preferences is important. The authors used a discrete choice experiment to study these preferences, focusing on factors related to the characteristics of the patients, the disease, and treatment effects. Results show that the most important factors influencing the GPs’ decision were the age of the patient, the mortality of the disease, the impact of the disease on patients’ quality of life, and the potential for the full restoration of the previous health status. The treatment of patients without comorbidities was preferred to that of patients with comorbidities. Importantly, these preferences in GPs may steer the actual distribution of health care.
Thrombin generation testing in routine clinical practice: are we there yet?

Thrombin is the central enzyme in the coagulation cascade. Estimation of an individual’s potential to generate thrombin may correlate more closely with a hyper‐ or hypo‐coagulable phenotype, compared to traditional coagulation tests. The possible correlation and recent technical advances in thrombin generation measurement has caused a significant interest in the method and the development of commercial assays. Several variations of the assay exist depending on the defect to be investigated. Fluorogenic thrombin generation assays have acceptable intra‐laboratory variation but a higher inter‐laboratory variation. Variation in preanalytical variables makes comparisons between studies difficult. Thrombin generation is highly variable between individuals and there are suggestions that this may allow individualized treatment based on global haemostatic response in patients with bleeding disorders or on anticoagulant therapy. In patients with thrombotic disorders it may be possible to identify those at higher risk of recurrent thrombosis. For both scenarios, however, data from large prospective studies are lacking or inconclusive and a good relationship between thrombin generation and phenotype remains to be established. Further standardization of the assay is needed before large multicentre studies can be conducted and until then thrombin generation in routine clinical practice is not yet a reality.
A Secure Modified ID-Based Undeniable Signature Scheme

Hanet al. proposed the first identity-based undeniable signature sch me at the fourth ACM conference on electronic commerce. Zhang et al. showed two attacks (the denial attack and the forge attack) a gainst the scheme. In this paper, we modify the scheme to make it secu re against these attacks. We also show how to modify our scheme to make it be an ID-Based convertible undeniable signature scheme.