Miracle-dz/UniFAR-FTUs huggingface dataset:
SenseWit: Pervasive Floorplan Generation Based on Only Inertial Sensing

Mobile crowdsourcing is deemed as a powerful technique to solve traditional problems. But the crowdsourced data from smartphones are generally with low quality, which induce crucial challenges and hurt the applicability of crowdsourcing applications. This paper presents our study to address such challenges in a concrete application, namely floorplan generation. In order to utilize pedestrians' traces for indoor location inference, existing proposals mostly rely on infrastructural references or accurate data sources, which are by nature restricted in terms of applicability and pervasiveness. Our proposal called SenseWit is motivated by the observation that people's behavior offers meaningful clues for location inference. The noise, ambiguity, and behavior diversity contained in the crowdsourced data, however, mean non-trivial challenges in generating high-quality floorplans. We propose 1) a novel concept called Nail to identify featured locations in indoor space and 2) a heuristic pathlet bundling algorithm to progressively discover the internal layouts. We implement SenseWit and conduct real-world experiments in different spaces. Our work offers an efficient technique to obtain high-quality structures (either logical or physical) from low-quality data. We believe it can be generalized to other crowdsourcing applications.
Bio-Based Aromatic Epoxy Monomers for Thermoset Materials

The synthesis of polymers from renewable resources is a burning issue that is actively investigated. Polyepoxide networks constitute a major class of thermosetting polymers and are extensively used as coatings, electronic materials, adhesives. Owing to their outstanding mechanical and electrical properties, chemical resistance, adhesion, and minimal shrinkage after curing, they are used in structural applications as well. Most of these thermosets are industrially manufactured from bisphenol A (BPA), a substance that was initially synthesized as a chemical estrogen. The awareness on BPA toxicity combined with the limited availability and volatile cost of fossil resources and the non-recyclability of thermosets implies necessary changes in the field of epoxy networks. Thus, substitution of BPA has witnessed an increasing number of studies both from the academic and industrial sides. This review proposes to give an overview of the reported aromatic multifunctional epoxide building blocks synthesized from biomass or from molecules that could be obtained from transformed biomass. After a reminder of the main glycidylation routes and mechanisms and the recent knowledge on BPA toxicity and legal issues, this review will provide a brief description of the main natural sources of aromatic molecules. The different epoxy prepolymers will then be organized from simple, mono-aromatic di-epoxy, to mono-aromatic poly-epoxy, to di-aromatic di-epoxy compounds, and finally to derivatives possessing numerous aromatic rings and epoxy groups.
The art of writing science

The value of writing well should not be underestimated. Imagine, for example, that you hold in your hand two papers, both of which describe precisely the same set of experimental results. One is long, dense, and filled with jargon. The other is concise, engaging, and easy to follow. Which are you more likely to read, understand, and cite? The answer to this question hits directly at the value of good writing: writing well leverages your work. That is, while even the most skillful writing cannot turn bad science into good science, clear and compelling writing makes good science more impactful, and thus more valuable. The goal of good writing is straightforward: to make your reader's job as easy as possible. Realizing this goal, though, is not so simple. I, for one, was not a natural-born writer; as a graduate student, my writing was weak and rambling, taking forever to get to the point. But I had the good fortune to postdoc under an outstanding scientific communicator, who taught me the above-described lesson that writing well is worth the considerable effort it demands. Thus inspired, I set out to teach myself how to communicate more effectively, an effort that, some fifteen years later, I am still pursuing. Along the way I have learned a thing or two that I believe make my papers easier to read, a few of which I am pleased to share with you here. Before I share my hard-won tips, though, I have an admission: there is no single, correct way to write. In fact, there are a myriad of solutions to the problem of writing well (see, e.g., Refs.1–4). The trick, then, is not to copy someone else's voice, but rather to study what works—and what does not—in your own writing and that of others to formulate your own guide to effective communication. Thus, while I present here some of my most cherished writing conventions (i.e., the rules that I force on my own students), I do not mean to imply that they represent the only acceptable approach. Indeed, you (or your mentor) may disagree strongly with many of the suggestions I make below. This, though, is perfectly fine: my goal is not to convince you that I have found the one true way, but instead simply to get people thinking and talking about writing. I do so in the hope that this will inspire a few more young scientists to develop their own effective styles.
The Wrapping Loop and Rap1 C-terminal (RCT) Domain of Yeast Rap1 Modulate Access to Different DNA Binding Modes*

Background: Rap1 is a general regulator of transcription and a component of the telomere. Results: Rap1 binds DNA in at least two binding modes. Conclusion: Access to binding modes in vitro is affected by different regions of the protein. Significance: The ability of Rap1 to access different binding modes may impact its functions. Budding yeast Rap1 is a specific double-stranded DNA-binding protein involved in repression and activation of gene transcription and in the establishment of the nucleoprotein complex formed at telomeres. The DNA-binding domain (DBD) of Rap1 forms a high affinity complex with DNA where both Myb-like domains bind to the recognition site. However, we recently showed that the DBD can also access an alternative, lower affinity DNA-binding mode where a single Myb-like domain binds. This results in Rap1-DNA complexes with stoichiometry higher than previously anticipated. In this work, we show that the ability of the DBD to form higher stoichiometry complexes on DNA is maintained also in larger Rap1 constructs. This indicates that transition between at least two DNA-binding modes is a general property of the protein and not a specific feature of the DBD in isolation. The transition between binding modes is modulated by the C-terminal wrapping loop within the DBD, consistent with the proposed model in which the transient opening of this region allows a switch between binding modes. Finally, we provide evidence that the Rap1 C terminus interacts with the DNA-binding domain, suggesting a complex network of interactions that couples changes in conformation of the protein to the binding of its DNA recognition sequence.
Missense Mutation R338W in ARHGEF9 in a Family with X-linked Intellectual Disability with Variable Macrocephaly and Macro-Orchidism

Non-syndromal X-linked intellectual disability (NS-XLID) represents a broad group of clinical disorders in which ID is the only clinically consistent manifestation. Although in many cases either chromosomal linkage data or knowledge of the >100 existing XLID genes has assisted mutation discovery, the underlying cause of disease remains unresolved in many families. We report the resolution of a large family (K8010) with NS-XLID, with variable macrocephaly and macro-orchidism. Although a previous linkage study had mapped the locus to Xq12-q21, this region contained too many candidate genes to be analyzed using conventional approaches. However, X-chromosome exome sequencing, bioinformatics analysis and segregation analysis revealed a novel missense mutation (c.1012C>T; p.R338W) in ARHGEF9. This gene encodes collybistin (CB), a neuronal GDP-GTP exchange factor previously implicated in several cases of XLID, as well as clustering of gephyrin and GABAA receptors at inhibitory synapses. Molecular modeling of the CB R338W substitution revealed that this change results in the substitution of a long electropositive side-chain with a large non-charged hydrophobic side-chain. The R338W change is predicted to result in clashes with adjacent amino acids (K363 and N335) and disruption of electrostatic potential and local folding of the PH domain, which is known to bind phosphatidylinositol-3-phosphate (PI3P/PtdIns-3-P). Consistent with this finding, functional assays revealed that recombinant CB CB2SH3−R338W was deficient in PI3P binding and was not able to translocate EGFP-gephyrin to submembrane microaggregates in an in vitro clustering assay. Taken together, these results suggest that the R338W mutation in ARHGEF9 is the underlying cause of NS-XLID in this family.
Identifying Health Domain URLs using SVM

World Wide Web contains large volume of information on various topics. Especially, in health domain, people surf the net before consulting experts. But it is not guaranteed that, only the relevant health related pages are retrieved. So there is a need for an automated system that could assist in identifying health related web pages. In this paper, an URL based approach is proposed to identify health domain URLs that will help to avoid fetching irrelevant web pages. One of the issues in URL based topic classification is difficulty in selection of suitable URL features. In this paper, only the 4-grams derived from URLs are used as features to determine the health related web page, without using any medical repository. Statistical dictionary based methods have been reported in the literature, but construction of such dictionary is not automatic. A machine learning technique to automatically learn statistical dictionary of terms from the training URLs is proposed. To classify a web page either as a health page or not, SVM binary classifier is designed with a dictionary of 4-grams derived from URLs. The bench mark dataset ODP has been used for evaluating the performance by conducting various experiments. With the proposed URL based approach, 87% of precision has been achieved, which is a significant improvement over the existing techniques.
Universities in the marketplace: the commercialization of higher education

Nos ultimos 20 anos, universidades tem mudado seu tradicional foco de formacao para cada vez mais enfatizar ensino e pesquisas multidisciplinares estreitamente relacionadas com finalidades praticas e comerciais. Na academia surgem questionamentos acerca dessas mudancas e manifestacoes preocupadas com a crescente tendencia de administrar as atividades universitarias sob o principio empresarial, de alocacao e gestao de recursos baseado no lucro. Universities in the marketplace, de Derek Bok, expresidente da Universidade de Harvard (1971-91), e uma oportuna contribuicao ao debate. As preocupacoes do autor, conhecido tambem pelo lema “se voce pensa que educacao e cara, experimente a ignorância”, estao expressas no prefacio do livro, no qual afirma que as universidades “tem estado muito mais agressivas do que antigamente em tentar ganhar dinheiro de suas atividades de ensino e pesquisa. Muitas instituicoes tem lancado [. ] uma variada gama de iniciativas comerciais”. Bok deixa clara sua inquietacao sobre o fato de a recente tendencia mudar o carater academico das instituicoes de ensino superior e comprometer seus essenciais valores de continuada confianca e lealdade para com os professores, os estudantes e o publico em geral. Contra essas tendencias, ele recomenda a adocao de “apropriadas politicas” para limitar seus aspectos negativos. Segundo Bok, o inicio da comercializacao nas universidades data dos principios do seculo XX, o autor menciona as ideias de Thorstein Veblen (1918), os anuncios da Universidade de Chicago para atrair estudantes nos primeiros anos do seculo e a contratacao de um treinador de 26 anos de idade, com um salario igual ao do presidente da Universidade de Harvard em 1905, para mostrar que as atividades comerciais no interior das universidades nao sao um fenomeno recente. Entretanto, tais tendencias cresceram significativamente depois da Segunda Guerra Mundial e com muito mais forca depois da Lei Bayh-Dole (1980) que permitiu que as universidades possuissem a propriedade e licenciassem patentes de inovacoes desenvolvidas a partir do fomento publico de suas atividades. Nos Estados Unidos, a colaboracao entre as universidades e as empresas gerou sucessos comerciais, como o Vale do Silicio, o Triângulo de Pesquisa, o Milagre de Austin e a Rota 128. A comercializacao no interior das universidades, em muitos casos liderada pelas business schools, e refletida em uma serie de tendencias, em que se percebe: 1) a influencia das forcas UNIVERSITIES IN THE MARKETPLACE: THE COMMERCIALIZATION OF HIGHER EDUCATION
Improving transient state myoelectric signal recognition in hand movement classification using gyroscopes

Pattern recognition of myoelectric signals in upper-limb prosthesis control has been subject to intense research for several years. However, few systems have yet been successfully clinically implemented. One possible explanation for this discrepancy is that published reports mostly focus on classification accuracy of myoelectric signals recorded under laboratory conditions as the metric for the system's performance. These data are usually acquired only during the static state of the contraction in a fixed seated position. This supports the test subject in performing repeatable contractions throughout the experiment and generally results in an unrealistically high classification accuracy. In clinical testing however, subjects have to perform various activities of daily living, causing the limb to move in different positions. These variations in limb positions can significantly decrease robustness and usability of myoelectric control systems. Recent reports have shown that the so-called limb position effect can be resolved for the static state of the signal by adding accelerometer data to the feature vector. Including data from the transient state of the signals for classifier training generally significantly increases the classification error so it is mostly not considered in published reports. In this paper, we investigate the classification accuracy of transient EMG data, taking into account the limb position effect. We demonstrate that a classifier trained with features from EMG, accelerometer and gyroscope outperforms classifiers using only EMG or EMG and accelerometer data when classifying transient EMG data.
Multiclass object detection system in imaging sensor network using Haar-like features and Joint-Boosting algorithm

This paper proposes an efficient scheme for detecting different object classes in an imaging sensor network. The object detection system detects all the instances of objects (for which the classifier was trained) in the given image, regardless of their scales and locations. Therefore, the image can be thus seen as a set of sub-windows that are to be evaluated by the detector. The detector selects those sub-windows that contain the instances of the objects trained. The traditional approach for multiclass object detection is to use different independent classifiers to the image, at multiple locations and scales. This can be slow and requires a lot of training data. To achieve a fast and robust implementation, shared features are used. In the existing schemes, part-based models have been used for evaluating the object features, so these features being more class-specific cannot share more information among different classes. Hence in this paper, rectangular features called Haar-like features which are more generic is used and thus more number of features can be shared. The proposed scheme uses Joint-Boosting algorithm for training the multiclass object classifier. The benefits of illumination normalisation or variance normalisation technique used to neutralise the effect of changing lighting conditions are explored. Though the proposed scheme is validated for car and pedestrian classes, the training and detection techniques used in this scheme can be generalised for any object class.
Simple and effective techniques for core-region detection and slant correction in offline script recognition

This paper presents two new preprocessing techniques for cursive script recognition. Enhanced algorithms for core-region detection and effective uniform slant angle estimation are proposed. Reference lines composed of core-region are usually obtained as the ones surrounding highest density peaks, but are strongly affected by the presence of long horizontal strokes and erratic characters in the word. Therefore, it caused confusion with the actual core-region and leads to decisive errors in normalizing the word. To overcome this problem in core-region detection quantile is introduced to make resulting process robust. On the other hand, research community has introduced computationally heavy approaches to remove slant in cursive script. Therefore, a simple formalized and effective method is presented for the detection and removal of slant angle for offline cursive handwritten words to avoid heavy experimental efforts. Additionally, already not-slanted words are not affected negatively by applying this algorithm. The core-region detection is based on statistical features, while slant angle estimation is based on structure features of the word image. The algorithms are tested on IAM benchmark database of cursive handwritten words. Promising results for core-region detection, slant angle estimation/removal are reported and compared with widely applied Bozinovic and Srihari method (BSM).
Shortest Reconfiguration Paths in the Solution Space of Boolean Formulas

Given a Boolean formula and a satisfying assignment, a flip is an operation that changes the value of a variable in the assignment so that the resulting assignment remains satisfying. We study the problem of computing the shortest sequence of flips (if one exists) that transforms a given satisfying assignment \(s\) to another satisfying assignment \(t\) of the Boolean formula. Earlier work characterized the complexity of deciding the existence of a sequence of flips between two given satisfying assignments using Schaefer’s framework for classification of Boolean formulas. We build on it to provide a trichotomy for the complexity of finding the shortest sequence of flips and show that it is either in P, NP-complete, or PSPACE-complete. Our result adds to the small set of complexity results known for shortest reconfiguration sequence problems by providing an example where the shortest sequence can be found in polynomial time even though the path flips variables that have the same value in both \(s\) and \(t\). This is in contrast to all reconfiguration problems studied so far, where polynomial time algorithms for computing the shortest path were known only for cases where the path modified the symmetric difference only. Our proof uses Birkhoff’s representation theorem on a set system that we show to be a distributive lattice. The technique is insightful and can perhaps be used for other reconfiguration problems as well.
Classifying Patent Applications with Winnow

A new and distinct variety of peach, Prunus persica, tree with the following unique combination of desirable features: 1. Heavy and regular production of large, white flesh, clingstone fruit. 2. Fruit with a mild, sweet, subacid flavor with excellent eating quality. 3. Fruit with firm white flesh, good handling and shipping qualities. 4. An attractive fruit with a white ground color nearly overspread with a red blush. 5. Large tree size with vigorous, upright growth. 6. Relatively uniform ripening of fruit throughout the tree.
Integrated modular avionics for spacecraft — User requirements, architecture and role definition

This paper describes, from the perspective of the European Space Agency (ESA), the benefits of incorporating software partitioning technology, based upon the Integrated Modular Avionics (IMA) concept, into the spacecraft flight software architecture in terms of improving the reliability and security of space systems as well as the efficiency of the software development and validation processes. The result of the spin-in shall be known as Integrated Modular Avionics for Space (IMA-SP). One problem faced in space projects is how to manage software complexity. Larger industrial teams are needed to ensure responsibility for the software lifecycle, due to the increased functions and capability required for future missions. The problem is further complicated by the fact that uncorrelated spacecraft applications with different levels of criticality are integrated together into a single core software image, meaning a modification in one application results in regression testing all other applications at the maximum level of criticality. IMA is a solution that allows the aviation industry to manage their avionics complexity. IMA defines an integrated system architecture that preserves the fault containment and ‘separation of concerns’ properties of the federated architectures, where independent functional chains share a common computing resource. Each functional chain, or application, is protected against interference from other chains by a memory protection strategy and a guaranteed sole access to the computing resources. Applications are isolated from each other in time and memory using software partitions and communicate through controlled channels. An on-going study has derived a baseline IMA-SP definition covering: system requirements, software architecture; application services, lifecycle and process; and failure handling concepts. The findings from this study are presented in this paper.
Urban vehicle classification based on linear SVM with efficient vector sparse coding

This paper presents a new method to solve the urban vehicle classification problem by incorporating an efficient vector sparse coding technique with the linear support vector machine (SVM) classifier. Essentially, SIFT descriptors are able to give good local characteristics of a vehicle image. However, in general, SIFT feature vectors are nonlinearly discriminated. With sparse coding, the SIFT feature vectors can be firstly projected to a higher dimensional feature domain where the resultant sparse code vectors may be more distinguishable than those in original feature domain and thus the linear SVM classifier can be adopted. Conventional vector sparse coding is computationally expensive which reduces the practical value of sparse coding for real vehicle classification applications. In this paper, an efficient L2-norm constraint based vector sparse coding algorithm for vehicle classification has been formulated and derived accordingly. The performance evaluations using real vehicle images extracted from surveillance video data are carried out and six vehicle classes (bus, truck, SUV, van, car, and motorcycle) are considered. Experimental results validate the effectiveness of the proposed method and it is encouraged to see that a good classification performance is achieved.