Miracle-dz/UniFAR-FTUs huggingface dataset:
Creative Construction Conference 2018 , CCC 2018 , 30 June-3 July 2018 , Ljubljana , Slovenia Mobile-based 3 D Reconstruction of Building Environment

On-time environment perception of construction site is considered as an indispensable step for project management. Real-time tracking and feedback the status of construction facilitate progress monitoring and quality control. Image-based modelling and RGB-D mapping are considered as a non-invasive and low-cost technology which are always used for data collection and reconstruction of as-built building environments. Recently, the arrival of reliable and efficient computational of mobile terminal service has given us an opportunity to develop a mobile-based spatial data reconstruction system. Considering the capacity of processing and real-time performance on a mobile device, Oriented FAST and Rotated BRIEF (ORB) features are extracted. The ORB features are used for subsequent procedures, including tracking, mapping, relocalization and loop closing. In contrast to imagebased off-line modelling, a real time Simultaneous Localization and Mapping (SLAM) algorithm was utilized to estimate the camera trajectory while reconstruction the building environment. Keyframes selection strategy was proposed to reduce the redundant images and generate a robust and trackable sparse point clouds. The keyframes and sparse point clouds are transferred to a computer for generating dense point clouds, grid reconstruction and texture synthesis. Finally, the reconstruction result will be transferred back to mobile and can be displayed directly on a mobile device. As an initial effort, this paper investigated the potential of live reconstruction of indoor building scenes on an android mobile device. Taking the advantages of operable and portable, the system can be used for data acquisition of as-built information by construction workers. © 2018 The Authors. Published by Diamond Congress Ltd., Budapest University of Technology and Economics Peer-review under responsibility of the scientific committee of the Creative Construction Conference 2018.
JOSIE: Overlap Set Similarity Search for Finding Joinable Tables in Data Lakes

We present a new solution for finding joinable tables in massive data lakes: given a table and one join column, find tables that can be joined with the given table on the largest number of distinct values. The problem can be formulated as an overlap set similarity search problem by considering columns as sets and matching values as intersection between sets. Although set similarity search is well-studied in the field of approximate string search (e.g., fuzzy keyword search), the solutions are designed for and evaluated over sets of relatively small size (average set size rarely much over 100 and maximum set size in the low thousands) with modest dictionary sizes (the total number of distinct values in all sets is only a few million). We observe that modern data lakes typically have massive set sizes (with maximum set sizes that may be tens of millions) and dictionaries that include hundreds of millions of distinct values. Our new algorithm, JOSIE (Joining Search using Intersection Estimation) minimizes the cost of set reads and inverted index probes used in finding the top-k sets. We show that JOSIE completely out performs the state-of-the-art overlap set similarity search techniques on data lakes. More surprising, we also consider state-of-the-art approximate algorithm and show that our new exact search algorithm performs almost as well, and even in some cases better, on real data lakes.
Fatigue Sensitivity Analysis of Offshore Wind Turbine Structures

School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, chew0272@e.ntu.edu.sg Department of Civil and Transport Engineering, Norwegian University of Science and Technology, Trondheim, Norway, michael.muskulus@ntnu.no Energy Research Institute @ NTU, Nanyang Technological University, Singapore, nsrikanth@ntu.edu.sg School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, mktai@ntu.edu.sg School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, mykng@ntu.edu.sg
Support Vector Machine-Based Transmit Antenna Allocation for Multiuser Communication Systems

In this paper, a support vector machine (SVM) technique has been applied to an antenna allocation system with multiple antennas in multiuser downlink communications. Here, only the channel magnitude information is available at the transmitter. Thus, a subset of transmit antennas that can reduce multiuser interference is selected based on such partial channel state information to support multiple users. For training, we generate the feature vectors by fully utilizing the characteristics of the interference-limited setup in the multiuser downlink system and determine the corresponding class label by evaluating a key performance indicator, i.e., sum rate in multiuser communications. Using test channels, we evaluate the performance of our antenna allocation system invoking the SVM-based allocation and optimization-based allocation, in terms of sum-rate performance and computational complexity. Rigorous testing allowed for a comparison of a SVM algorithm design between one-vs-one (OVO) and one-vs-all (OVA) strategies and a kernel function: (i) OVA is preferable to OVO since OVA can achieve almost the same sum rate as OVO with significantly reduced computational complexity, (ii) a Gaussian function is a good choice as the kernel function for the SVM, and (iii) the variance (kernel scale) and penalty parameter (box constraint) of an SVM kernel function are determined by 21.56 and 7.67, respectively. Further simulation results revealed that the designed SVM-based approach can remarkably reduce the time complexity compared to a traditional optimization-based approach, at the cost of marginal sum rate degradation. Our proposed framework offers some important insights for intelligently combining machine learning techniques and multiuser wireless communications.
The neuronal group selection theory: promising principles for understanding and treating developmental motor disorders

There are two major forms of developmental motor disorders: cerebral palsy (CP) and clumsiness. CP is an umbrella term covering a group of non-progressive, but often changing, motor impairment syndromes secondary to lesions or anomalies of the brain arising in the early stages of development1. It affects about 1 in 500 live-born children2. Clumsy children nowadays are classified according to DSM-IV as having developmental coordination disorder (DCD), a term denoting children who have such poor motor coordination that it affects daily activities at home and at school, but with normal intelligence and without obvious neurological pathology3. The prevalence of DCD is about 10% (6 to 13%4–6). The understanding of the motor problems in both groups of children is hampered by the large heterogeneity within each group. In both groups children differ in the expression of their motor dysfunction, in comorbidity such as the presence of cognitive and behavioural disorders, and in aetiology. In addition, the relation between the various motor disorders and the structural abnormalities of the brain is far from simple. CP is, by definition, attributed to lesions or anomalies of the young brain, but the abnormalities of the brain cannot always be visualized with imaging techniques. Despite there being some relation between lesions of the periventricular white matter and spastic diplegia, and between unilateral lesions and spastic hemiplegia, the site of the lesion does not correlate exactly with the type of motor dysfunction7–9. In children with DCD the connection between structural abnormalities of the brain and motor dysfunction is still more ambiguous. Recently Hadders-Algra and Touwen10 argued that indications for preand perinatal brain damage can be found only in one third of children with minor motor dysfunction. This could imply that most clumsy children do not have macroscopic anomalies of the brain, but dysfunctions at the microscopic level of the nervous system, with abnormalities in the neurotransmitter or receptor systems, for example.
Addressing Bystander Exclusion in Shared Spaces During Immersive Virtual Experiences

In today’s consumer virtual reality (VR) systems, head-mounted displays (HMDs) remain the dominant interface for experiencing immersive virtual environments (VEs). As the focus generally is on maximizing the sense of presence, the immersed user stands isolated while collocated bystanders are excluded from the virtual experience. This disconnect between the physical and virtual world negatively influences social acceptability of immersive VR applications. In this position paper, we discuss two approaches to address the usage of HMDs in shared spaces, specifically tackling the problem of excluded bystanders. First, we promote the idea of immersive notifications that allow non-immersed users and real-world systems to communicate real-world information to an immersed user while maintaining experienced presence. In a second example, we describe a projection-based system for bystanders to experience substitutional realities in a semi-immersive manner, additionally providing a means to interact with the VE without requiring HMDs.
Self-Organized Co-Clustering for textual data synthesis

Recently, different studies have demonstrated the interest of co-clustering, which simultaneously produces row-clusters of observations and column-clusters of features. The present work introduces a novel co-clustering model for parsimoniously summarizing textual data in document-term format. In addition to highlighting homogeneous co-clusters-as other existing algorithms do-we also distinguish noisy co-clusters from significant ones, which is particularly useful for sparse document-term matrices. Furthermore, our model proposes a structure among the significant co-clusters and thus provides better interpretability for the user. The approach proposed competes with state-of-the-art methods for document and term clustering, and offers user-friendly results. The model relies on the Poisson distribution, and a constrained version of the Latent Block Model, which is a probabilistic approach for co-clustering. A Stochastic Expectation-Maximization algorithm is proposed to perform the model's inference as well as a model selection criterion to choose the number of co-clusters.
Dominant Obligate Anaerobes Revealed in Lower Respiratory Tract Infection in Horses by 16S rRNA Gene Sequencing

ABSTRACT Obligate anaerobes are important etiological agents in pneumonia or pleuropneumonia in horses, because they are isolated more commonly from ill horses that have died or been euthanized than from those that survive. We performed bacterial identification and antimicrobial susceptibility testing for obligate anaerobes to establish effective antimicrobial therapy. We used 16S rRNA gene sequencing to identify 58 obligate anaerobes and compared the results with those from a phenotypic identification kit. The identification results of 16S rRNA gene sequencing were more reliable than those of the commercial kit. We concluded that genera Bacteroides and Prevotella—especially B. fragilis and P. heparinolytica—are dominant anaerobes in lower respiratory tract infection in horses; these organisms were susceptible to metronidazole, imipenem and clindamycin.
Measuring regional innovation in one dimension: More lost than gained?

In both academic literature and political discussions the concept of innovation is recognized as an essential ingredient in economic development and competitiveness for firms, regions, and nations. Innovation also ranks at the top of policy agendas in the field of regional policy. Therefore, the attractiveness of an appropriate innovation index for ranking regions and further developing them along a more or less objective measurement scale is evident. However, whether such rankings help convey a better understanding of innovation and its drivers, or whether they are merely a special type of i? ½beauty contesti? ½ with little substance is the focus of our analyses. To deny the latter, the innovation output indicators used for the composite index have to be appropriate representatives of the underlying innovation concept and each indicator has to be driven by the same impact factors. If this is not the case, interpretation of the index inevitably gives rise to partly inappropriate policy recommendations. In order to demonstrate this claim we elaborate a set of innovation indicators at the regional level based on the theoretical concept of the OECD document i? ½The Measurement of Scientific and Technological Activities, Proposed Guidelines for Collecting and Interpreting Technological Innovation Datai? ½ known as the i? ½Oslo Manuali? ½ (OECD, 2005) and their empirical implementation in the Community Innovation Survey. Additionally, innovation drivers well established in the literature are collected to estimate their impact on each innovation indicator as well as on the composite index derived from the innovation indicators. The question whether innovation should be measured as a multidimensional concept and investigated using various indicators or whether simplifying innovation to a one-dimensional concept is appropriate is clearly answered in favor of the multidimensional approach. Surprisingly, this is not due to the multidimensionality of the indicators themselves (all statistical measures indicate that the considered variables are sufficiently represented by one component), but to our first evidence that the innovation output indicators are driven by various impact factors and can therefore be influenced by various political strategies. According to these findings any type of innovation ranking is of very limited use.
Adolescent health in the Eastern Mediterranean Region Mokdad

Objectives The 22 countries of the East Mediterranean Region (EMR) have large populations of adolescents aged 10–24 years. These adolescents are central to assuring the health, development, and peace of this region. We described their health needs. Methods Using data from the Global Burden of Disease Study 2015 (GBD 2015), we report the leading causes of mortality and morbidity for adolescents in the EMR from 1990 to 2015. We also report the prevalence of key health risk behaviors and determinants. Results Communicable diseases and the health consequences of natural disasters reduced substantially between 1990 and 2015. However, these gains have largely been offset by the health impacts of war and the emergence of non-communicable diseases (including mental health disorders), unintentional injury, and self-harm. Tobacco smoking and high body mass were common health risks amongst adolescents. Additionally, many EMR countries had high rates of adolescent pregnancy and unmet need for contraception. Conclusions Even with the return of peace and security, adolescents will have a persisting poor health profile that will pose a barrier to socioeconomic growth and development of the EMR.
Hypoxia-inducible factor HIF-1 α modulates drugs resistance in colon cancer cells Factor inducible por hipoxia HIF-1 α modula

1 Universidad del Rosario School of Medicine and Health Sciences Clinical Research Group Bogotá D.C. Colombia. 2 Universidad Nacional de Colombia Bogotá Campus Faculty of Science Master’s Degree program in Biochemistry Bogotá D.C. Colombia. 3 Universidad del Rosario School of Medicine and Health Sciences Neuroscience Research Group Bogotá D.C. Colombia. 4 Universidad del Rosario School of Medicine and Health Sciences Doctoral program in Biomedical and Biological Sciences Bogotá D.C. Colombia. 5 Universidad del Rosario School of Natural Sciences and Mathematics Biochemistry and Biotechnology Research Group (Bio Bio) Bogotá D.C. Colombia.
Cryptanalysis of the Yeung - Mintzer fragile watermarking technique

The recent proliferation of digital multimedia content has raised concerns about authentication mechanisms for multimedia data. A number of authentication techniques based on digital watermarks have been proposed in the literature. In this paper we examine the security of the Yeung–Mintzer authentication watermarking technique and show that it is vulnerable to different types of impersonation and substitution attacks whereby an attacker is able to either create or modify images that would be considered authentic. We present two attacks. The first attack infers the secret watermark insertion function. This enables an attacker to embed a valid watermark in any image. The attack works without knowledge of the binary watermark inserted in the image, provided the attacker has access to a few images that have been watermarked with the same secret key (insertion function) and contain the same watermark. We show simulation results in which the watermark and the watermark insertion function can be mostly reconstructed in a few (1–5) minutes of computation, using as few as two images. The second attack we present, which we call the “collage attack” is a variation of the Holliman–Memon counterfeiting attack. The proposed variation does not require knowledge of the watermark logo and produces counterfeits of superior quality by means of a sophisticated dithering process. © 2002 SPIE and IS&T.
Mapping Insertions, Deletions and SNPs on Venter's Chromosomes

Background The very recent availability of fully sequenced individual human genomes is a major revolution in biology which is certainly going to provide new insights into genetic diseases and genomic rearrangements. Results We mapped the insertions, deletions and SNPs (single nucleotide polymorphisms) that are present in Craig Venter's genome, more precisely on chromosomes 17 to 22, and compared them with the human reference genome hg17. Our results show that insertions and deletions are almost absent in L1 and generally scarce in L2 isochore families (GC-poor L1+L2 isochores represent slightly over half of the human genome), whereas they increase in GC-rich isochores, largely paralleling the densities of genes, retroviral integrations and Alu sequences. The distributions of insertions/deletions are in striking contrast with those of SNPs which exhibit almost the same density across all isochore families with, however, a trend for lower concentrations in gene-rich regions. Conclusions Our study strongly suggests that the distribution of insertions/deletions is due to the structure of chromatin which is mostly open in gene-rich, GC-rich isochores, and largely closed in gene-poor, GC-poor isochores. The different distributions of insertions/deletions and SNPs are clearly related to the two different responsible mechanisms, namely recombination and point mutations.
Formal Modeling in Context Aware Systems

Ubiquitous computing environment consists of diverse range of hardware and software entities, and is about the interactivity of such entities. Context-awareness, being an important ingredient plays a vital role in enabling such interactive smart environments. The entities and contextual information provided/utilized by them must have invariant meanings in order to have a common understanding among them. This results in sharing of information with common semantics, at different times and at different places and provides testability of formalized knowledge, emerging as a pool of consistent contextual knowledge available to different context-aware systems. In this paper, we discuss our context model for the home domain and show that how it entails implicit reasoning.
Immortal time bias in observational studies of drug effects in pregnancy.

BACKGROUND The use of decongestants during the second or third trimesters of pregnancy has been associated with a decreased risk of preterm delivery in two observational studies. This effect may have been subject to immortal time bias, a bias arising from the improper classification of exposure during follow-up. We illustrate this bias by repeating the studies using a different data source. METHODS The United Kingdom Hospital Episodes Statistics and the Clinical Practice Research Datalink databases were linked to identify all live singleton pregnancies among women aged 15 to 45 years between 1997 and 2012. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals of preterm delivery (before 37 weeks of gestation) by considering the use of decongestants during the third trimester as a time-fixed (biased analysis which misclassifies unexposed person-time as exposed person-time) and time-varying exposure (unbiased analysis with proper classification of unexposed person-time). All models were adjusted for maternal age, smoking status, maternal diabetes, maternal hypertension, preeclampsia, and parity. RESULTS Of the 195,582 singleton deliveries, 10,248 (5.2%) were born preterm. In the time-fixed analysis, the HR of preterm delivery for the use of decongestants was below the null and suggestive of a 46% decreased risk (adjusted HR = 0.54; 95% confidence interval, 0.24-1.20). In contrast, the HR was closer to null (adjusted HR = 0.93 95% confidence interval, 0.42-2.06) when the use of decongestants was treated as a time-varying variable. CONCLUSION Studies of drug safety in pregnancy should use the appropriate statistical techniques to avoid immortal time bias, particularly when the exposure occurs at later stages of pregnancy.
The role of perceived privacy and perceived security in online market

Individuals mostly hesitate to use services offered via Internet due to their suspicions regarding the level of offered (1) protection of their privacy and (2) security of performing online transactions. Privacy is mostly concerned with the identifiable user data and users' rights to have control over their data. On the other hand, security provides the physical, logical, and procedural safeguards that are needed to keep the data private. Privacy cannot be achieved without obtaining security practice, nor will the usage of security mechanisms guarantee protection of privacy. Despite being closely linked in practice, privacy and security are perceived as separate issues by online users. Therefore, in this article the relationship between various privacy factors (factors that influence users' privacy concerns) and the perception of security protection during users' online activities is discussed. The role that perceived privacy and perceived security have in the e-service users' evaluation of a service is investigated.
Demand Forecasting: An Open-Source Approach

In this paper, we compare demand forecasting methods used by the supply chain department at Bilports to open-source forecasting methods. The design and implementation of the open-source forecasting system also attempts to use several external datasets such as consumer sentiment, housing permit starts, and weather to improve prediction quality. Additionally, the performance of the forecast is evaluated by the reduction of shipment lead times from China, the company’s pri mary vendor. The objective of our paper is to improve Bilports ’s forecasting capabilities. The primary motivation of this paper is to increase forecasting accuracy and identify the weaknesses of the methods used by the supply chain department. Our framework utilizes and compares both machine learning and statistical methods to generate a more cost effective and accurate forecast. We find that the modified open-source forecasting packages reduced the forecast error by 18 percent. Thus, the company’s ability to improve fulfillment rates and increase customer satisfaction.