Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploratory Use of PPG Signal in Continuous Authentication

One-time or static authentication is not sufficient in many applications and continuous authentication methods can provide a way to increase security in situations where an application could be compromised or misused after statically authenticating the user. The aim of this work is to evaluate the use of the Photoplethysmographic Signal (PPG) in continuous authentication and identify the requirements of the system that should be used to record and process the signal. Different types of sensors, sampling rates, and analog to digital conversion resolutions were tested in order to identify the configuration that best suits the application requirements. The algorithms used for processing the PPG signal as well as the size of the samples used in the authentication process were also analyzed during the experiments. In order to achieve the set objective, a dataset of PPG signals was developed since it was not possible to find open datasets with long term monitoring samples of individuals.
Evaluative Phrase Extraction from Customer Review

When we want to buy products on an EC site, we can get some information from merchandise pages and customer reviews. In merchandise pages, there is information provided by producers. On the other hand, we can get subjective information wrote by a customer from customer reviews. Subjective information contains relative comparison or subjective evaluation made by customers, and it is different depending on products. Therefore, we cannot decide evaluative phrases previously. In this study, the main aim is extracting evaluative phrases from customer reviews automatically. We use the dependency analysis to achieve the aim. Furthermore, we group similar evaluative phrases by using similarities of dependency. Then we judge the similarity using a graph analysis method. Speaking concretely, we represent relation between noun and adjective as a bipartite graph. The word similarity is defined using the bipartite graph similarity. Using this method, we confirmed that evaluative phrases are classified into appropriate categories according to their meanings.
flow cytometry , differential analysis This article is included in the Bioconductor gateway

High-dimensional mass and flow cytometry (HDCyto) experiments have become a method of choice for high-throughput interrogation and characterization of cell populations. Here, we present an updated R-based pipeline for differential analyses of HDCyto data, largely based on Bioconductor packages. We computationally define cell populations using FlowSOM clustering, and facilitate an optional but reproducible strategy for manual merging of algorithm-generated clusters. Our workflow offers different analysis paths, including association of cell type abundance with a phenotype or changes in signalling markers within specific subpopulations, or differential analyses of aggregated signals. Importantly, the differential analyses we show are based on regression frameworks where the HDCyto data is the response; thus, we are able to model arbitrary experimental designs, such as those with batch effects, paired designs and so on. In particular, we apply generalized linear mixed models or linear mixed models to analyses of cell population abundance or cell-population-specific analyses of signaling markers, allowing overdispersion in cell count or aggregated signals across samples to be appropriately modeled. To support the formal statistical analyses, we encourage exploratory data analysis at every step, including quality control (e.g., multi-dimensional scaling plots), reporting of clustering results (dimensionality reduction, heatmaps with dendrograms) and differential analyses (e.g., plots of aggregated signals). 1,2 3 1,2 1,2
Task-Conditioned Variational Autoencoders for Learning Movement Primitives

Consider a task such as pouring liquid from a cup into a container. Some parameters, such as the location of the pour, are crucial to task success, while others, such as the length of the pour, can exhibit larger variation. In this work, we propose a method that differentiates between specified task parameters and learned manner parameters. We would like to allow a designer to specify a subset of the parameters while learning the remaining parameters from a set of demonstrations. This is difficult because the learned parameters need to be interpretable and remain independent of the specified task parameters. To disentangle the parameter sets, we propose a Task-Conditioned Variational Autoencoder (TCVAE) that conditions on the specified task parameters while learning the rest from demonstrations. We use an adversarial loss function to ensure the learned parameters encode no information about the task parameters. We evaluate our method on pouring demonstrations on a Baxter robot from the MIME dataset. We show that the TC-VAE can generalize to task instances unseen during training and that changing the learned parameters does not affect the success of the motion.
Robot with an Olfactory Display: Decorating its Movements by Smells

This study explored olfactory displays for social robots. In particular, we tested decorating robot movements by using smells as a way for nonverbal expression. To this end, two prototype devices which enabled a humanoid robot to present smells during its movements were developed based on the following design requirements: (1) the smell presentation had to be synchronized with the robot movements, (2) the devices could be easily mounted to the robot, (3) the devices could present and switch between multiple smells, and (4) the intensity of the smell presentation was controllable. Initial pilot tests were conducted with human participants.
Randomized Bregman Coordinate Descent Methods for Non-Lipschitz Optimization

We propose a new \textit{randomized Bregman (block) coordinate descent} (RBCD) method for minimizing a composite problem, where the objective function could be either convex or nonconvex, and the smooth part are freed from the global Lipschitz-continuous (partial) gradient assumption. Under the notion of relative smoothness based on the Bregman distance, we prove that every limit point of the generated sequence is a stationary point. Further, we show that the iteration complexity of the proposed method is $O(n\varepsilon^{-2})$ to achieve $\epsilon$-stationary point, where $n$ is the number of blocks of coordinates. If the objective is assumed to be convex, the iteration complexity is improved to $O(n\epsilon^{-1} )$. If, in addition, the objective is strongly convex (relative to the reference function), the global linear convergence rate is recovered. We also present the accelerated version of the RBCD method, which attains an $O(n\varepsilon^{-1/\gamma} )$ iteration complexity for the convex case, where the scalar $\gamma\in [1,2]$ is determined by the \textit{generalized translation variant} of the Bregman distance. Convergence analysis without assuming the global Lipschitz-continuous (partial) gradient sets our results apart from the existing works in the composite problems.
An Analysis of Major Influencial Factors for Innovation in Thai Automotive Industry

Innovation is one of the main sources of competitive advantage and essential for company growth. Companies put great effort in creating improving and introducing innovations. This paper presents a study on innovation in Thai automotive industry and determines the influential factors of innovation. The survey was conducted to explore influential factors, including supplier driven, technological driven, customer driven, organizational capabilities, competitors’ pressure, organizational learning and learning of study of competitors which have impacts on innovation in the automotive industries. The results were analyzed by using a multiple linear regression technique and factor analysis. We find that the keys positively effecting to innovation include supplier driven, technological driven, customer driven, organizational capabilities and organizational learning; while, on the other hand, competitors’ pressure and learning of study by competitors are negatively affecting to innovation in Thai automotive industries. And, technological driven is a key factor orienting innovation in Thai automotive industries.
A Reinforcement Learning Approach for Efficient Opportunistic Vehicle-to-Cloud Data Transfer

Vehicular crowdsensing is anticipated to become a key catalyst for data-driven optimization in the Intelligent Transportation System (ITS) domain. Yet, the expected growth in massive Machine-type Communication (mMTC) caused by vehicle-to-cloud transmissions will confront the cellular network infrastructure with great capacity-related challenges. A cognitive way for achieving relief without introducing additional physical infrastructure is the application of opportunistic data transfer for delay-tolerant applications. Hereby, the clients schedule their data transmissions in a channel-aware manner in order to avoid retransmissions and interference with other cell users. In this paper, we introduce a novel approach for this type of resource-aware data transfer which brings together supervised learning for network quality prediction with reinforcement learning-based decision making. The performance evaluation is carried out using data-driven network simulation and real world experiments in the public cellular networks of multiple Mobile Network Operators (MNOs) in different scenarios. The proposed transmission scheme significantly outperforms state-of-the-art probabilistic approaches in most scenarios and achieves data rate improvements of up to 181% in uplink and up to 270% in downlink transmission direction in comparison to conventional periodic data transfer.
Attribute-Guard: Attribute-Based Flow Access Control Framework in Software-Defined Networking

Software-defined networking (SDN) decouples the control plane from the data plane, offering flexible network configuration and management. Because of this architecture, some security features are missing. On the one hand, because the data plane only has the packet forwarding function, it is impossible to effectively authenticate the data validity. On the other hand, OpenFlow can only match based on network characteristics, and it is impossible to achieve fine-grained access control. In this paper, we aim to develop solutions to guarantee the validity of flow in SDN and present Attribute-Guard, a fine-grained access control and authentication scheme for flow in SDN. We design an attribute-based flow authentication protocol to verify the legitimacy of the validity flow. The attribute identifier is used as a matching field to define a forwarding control. The flow matching based on the attribute identifier and the flow authentication protocol jointly implement fine-grained access control. We conduct theoretical analysis and simulation-based evaluation of Attribute-Guard. The results show that Attribute-Guard can efficiently identify and reject fake flow.
Review of Statistical Innovations in Trials Supporting Vaccine Clinical Development

Vaccines have a long history of providing protection to human health. As an example, eradication of the deadly disease, smallpox, was accomplished in 1980 via massive vaccination programs around the world. Vaccination was, in fact, recognized as the greatest public health achievement of the 20th century by the U.S. Centers for Disease Control and Prevention. In recent years, statisticians have played an increasingly important role as collaborative researchers in vaccine development. This review article highlights some of the innovative applications of statistical techniques that have contributed to the successful development of several vaccines for preventing diseases such as chickenpox, herpes zoster, rotavirus gastroenteritis, and cervical cancer. Real life examples will be used to illustrate statistical innovations in several areas, including trial design and adaptation, safety monitoring, endpoint measure, and the evaluation of correlates of protection. Many of these methods, while innovative and novel at the time, are now broadly applied across pharmaceutical and vaccine clinical programs. These statistical contributions are a reflection of the statisticians’ engagement and leadership, which has resulted in a substantial improvement of the scientific rigor, quality, and operational efficiency in vaccine development. This article was contributed as part of the 175th Anniversary celebration of the American Statistical Association.
The utilisation of prospective surveillance with bioelectrical impedance for early detection and instigation of treatment for breast cancer-related lymphoedema

have been changed from the original version. parenchymal/stromal elements, within the extracellular space (International Society of Lymphology, 2013). The most common cause is secondary lymphoedema, most often consequent to axillary surgery. Lymphoedema is a chronic, ‘incurable’ condition often leading to a reduction in quality of life (Morgan et al, 2005). Appropriate management involves early identification, therapy to reduce swelling and institution of lifelong maintenance therapy (Devoogdt et al, 2010). The incidence of clinically evident lymphoedema can be reduced by early treatment (Boccardo et al, 2009; Torres Lacomba et al, 2010). Early detection to guide early treatment can potentially be 18 Journal of Lymphoedema, 2019, Vol 14, No 1
Family plot: the impact of the endosperm and other extra-embryonic seed tissues on angiosperm zygotic embryogenesis

The zygotic embryos of angiosperms develop buried deep within seeds and surrounded by two main extra-embryonic tissues: the maternally derived seed coat tissues and the zygotic endosperm. Generally, these tissues are considered to play an important role in nurturing the developing embryo by acting as conduits for maternally derived nutrients. They are also critical for key seed traits (dormancy establishment and control, longevity, and physical resistance) and thus for seed and seedling survival. However, recent studies have highlighted the fact that extra-embryonic tissues in the seed also physically and metabolically limit embryonic development and that unique mechanisms may have evolved to overcome specific developmental and genetic constraints associated with the seed habit in angiosperms. The aim of this review is to illustrate how these studies have begun to reveal the highly complex physical and physiological relationship between extra-embryonic tissues and the developing embryo. Where possible I focus on Arabidopsis because of space constraints, but other systems will be cited where relevant.
Association of persistent wild-type measles virus RNA with long-term humoral immunity in rhesus macaques.

Recovery from measles results in life-long protective immunity. To understand induction of long-term immunity, rhesus macaques were studied for six months after infection with WT measles virus (MeV). Infection caused viremia and rash with clearance of infectious virus by 14 days. MeV RNA persisted in PBMCs for 30-90 days and in lymphoid tissue for 6 months most often in B cells but was rarely detected in BM. Antibody with neutralizing activity and binding specificity for MeV nucleocapsid (N), hemagglutinin (H) and fusion proteins appeared with the rash and avidity matured over 3-4 months. Lymph nodes had increasing numbers of MeV-specific antibody-secreting cells (ASCs) and germinal centers with late hyalinization. ASCs appeared in circulation with the rash and continued to appear along with peripheral Tfh cells for the study duration. ASCs in lymph nodes and PBMCs produced antibody to both H and N, with more H-specific ASCs in BM. From 14-21 days 20-100-fold more total ASCs than MeV-specific ASCs appeared in circulation suggesting mobilization of pre-existing ASCs. Therefore, persistence of MeV RNA in lymphoid tissue was accompanied by continued germinal center formation, ASC production, avidity maturation and accumulation of H-specific ASCs in BM to sustain neutralizing antibody and protective immunity.
A Tennis Movie Retrieval System using Segmented-Swing Matching

In this paper, we present a prototype of a tennis movie retrieval system using a user’s swing motion of a tennis racket. Our system leverages 3-axes acceleration data of swing motions obtained from a sensor device so that a user can retrieve the required tennis movies by intuitive swing motions with the sensor device. In our approach, the user’s swing motion is segmented into three parts: pre-hit part, hit part, and post-hit part, for the swing-motion matching process. The experiment results show that by applying our segmentation method of swing motion to the search system, the retrieval accuracy can be improved with low computation cost.
Differenzialdiagnose und Therapie

D er Begriff thrombotische Mikroangiopathie beschreibt eine ätiologisch sehr heterogene Gruppe von Erkrankungen (Tabelle 1), die in Verbindung mit einem Endothelschaden zu Thrombosen kleiner und kleinster arterieller sowie venöser Ge fäße führen. Diese Mikroangiopathie kann zu einem sekundären Verbrauch von Thrombozyten und einer mechanischen Hämolyse führen. Die Trias aus Coombsnegativer hämolytischer Anämie mit Nachweis von Fragmentozyten im Blut und Thrombopenie (mikroangiopathisch-hämolytische Anämie) sowie ischämischem Endorganschaden definiert eine thrombotische Mikroangiopathie. Abhängig von den beteiligten Gefäßsystemen können Nierenversagen, neurologische Symptome, kardiale Komplikationen, respiratorisches Versagen, Sehstörungen, Pankreatitis, Darmischämie und selten Hautveränderungen auftreten (1, 2). Unbehandelt ist die Letalität hoch, in früheren Publikationen ohne effektive Therapie liegt sie bei 72–94 % (3, 4). Eine thrombotische Mikroangiopathie zu erkennen und eine Plasmapherese innerhalb von 4–8 Stunden zu initiieren, ist essenziell für eine erfolgreiche Therapie (Empfehlungsgrad 1B) (5). Die Plasmapherese trug zur Reduktion der Letalität auf ungefähr 10–20 % bei thrombotisch-thrombozytopenischer Purpura (TTP) bei (3, e1). Ein diagnostischer und therapeutischer Algorithmus sowie eine Klassifikation der thrombotischen Mikroangiopathien finden sich in Grafik 1, eTabellen 2 und 3 sowie Tabelle 1, relevante Differenzialdiagnosen in eTabelle 1. Ein landesweites Erkrankungsregister mit Biobanking ist wünschenswert.
VISUALISATION OF STABILITY REGIONS FOR LOGISTIC DIFFERENCE EQUATIONS WITH MULTIPLE DELAYS

We consider linearised stability of nonlinear difference equations by investigating location of roots of the associated characteristic equations. The characteristic equation is given as a polynomial equation with the order determined by the delay in the difference equation. For some polynomial equations we visualise all the sets of coefficients such that all the roots locate inside the unit circle in the complex plane. The information can be translated to understand stability of the nonlinear difference equation in terms of its original parameters. We present some examples that delay in the difference equation can stabilise the equilibrium of the equation.
IT Governance in Shared Services in Public Sector

The importance of enterprise governance in IT has been demonstrated in both the private and the public sector. Some of the issues that implementing IT governance addresses are ITbusiness alignment, the demonstrable business value of IT, effective IT portfolio management, maximisation of the value of IT investments as well as mitigating the risk of IT failure. As the pressure on government ICT departments grows to provide additional services, to respond quickly to new business requirements, to increase effectiveness and to continue to demonstrate business value while under increased scrutiny and tight budgets, relatively new models of service delivery are being considered and implemented in the public sector across the world, these include outsourcing, public-private partnerships and the creation of shared service centres (SSC) to deliver inter-departmental services to government agencies. This paper will focus on SSCs in the public sector and will review the literature and present a case study of IT governance failure in an SSC in the Queensland government’s implementation of a centralised HR and payroll system. Based on the analysis completed, we explore the risks and benefits in SSCs and investigate key governance-related concerns in the creation, transition to and operation of SSCs in the public sector, highlighting the importance of the relationship between the SSC governance model and the scope of service delivery.
A NEW STOCHASTIC MODEL TO ESTIMATE THE INFLUENCE OF INSULIN ON CIRCULATING GHRELIN USING GAMMA DISTRIBUTION

Ghrelin is a novel peptide that acts on the growth hormone (GH) secretagogue receptor in the pituitary and hypothalamus. It may functions as a third physiological regulator of GH secretion, along with GH-releasing hormone and somatostatin. In addition to the action of ghrelin on the GH axis, it appears to have a role in the determination of energy homeostasis. Although feeding suppresses ghrelin production and fasting stimulates ghrelin release, the underlying mechanisms controlling this process remain unclear. Our data suggest that insulin may suppress circulating ghrelin independently of glucose, although glucose may have an additional effect. The purpose of this study was to estimate the influence of insulin on circulating ghrelin using gamma distribution with the help of duality principle.
The Electoral Gender Gap: A Generational Perspective

Traditionally, women were more likely to vote for conservative parties than men. Studies have shown a convergence of this gender gap over the years, side by side with a new “modern” gender gap, whereby women are more leftwing than men. Looking at the overall gender gap over time misses an important point, since this phenomenon may depend strongly on generational differences. These differences occur because the circumstances of a certain period powerfully affect the young people of that time, and these effects persist over the lifecycle of this cohort’s members (Mannheim, 1952). If a social change affects the political preferences of women, this effect will be strongest and most persistent among those women who were young when the change took place. Consequently, the electoral gender gap is likely to vary among cohorts. While some scholars have recognized the importance of generational differences regarding the electoral gender gap (Inglehart and Norris, 2000), differences between cohorts cannot be inferred from age effects, and might be mistakenly interpreted as over-time trends. This study explores the electoral gender gap from a generational perspective on the US (1948-2008) and the UK (1974-2010), using descriptive analyses as well as a statistical methodology (Yang & Land, 2013) which offers an improved technique for distinguishing between age, period and cohort (APC) effects using data from repeated surveys. Findings suggest that while the inversion of the electoral gender gap in the US may result from period effects, the UK shows only little variation over time. However, the results show cohort effects in the UK, but surprisingly no evidence for this kind of effect in the US. Work in progress, please do not cite without permission
A basis for the Kauffman skein module of the product of a surface and a circle

The Kauffman bracket skein module $S(M)$ of a 3-manifold $M$ is a $\mathbb{Q}(A)$-vector space spanned by links in $M$ modulo the so-called Kauffman relations. In this article, for any closed oriented surface $\Sigma$ we provide an explicit spanning family for the skein modules $S(\Sigma\times S^1)$. Combined with earlier work of Gilmer and Masbaum, we answer their question about the dimension of $S(\Sigma\times S^1)$ being $2^{2g+1} + 2g -1$.