Miracle-dz/UniFAR-FTUs huggingface dataset:
Large-Scale Machine Learning and Applications

This thesis presents my main research activities in statistical machine learning after my PhD, starting from my post-doc at UC Berkeley to my present research position at Inria Grenoble. The first chapter introduces the context and a summary of my scientific contributions and emphasizes the importance of pluri-disciplinary research. For instance, mathematical optimization has become central in machine learning and the interplay between signal processing, statistics, bioinformatics, and computer vision is stronger than ever. With many scientific and industrial fields producing massive amounts of data, the impact of machine learning is potentially huge and diverse. However, dealing with massive data raises also many challenges. In this context, the manuscript presents different contributions, which are organized in three main topics. Chapter 2 is devoted to large-scale optimization in machine learning with a focus on algorithmic methods. We start with majorization-minimization algorithms for structured problems, including block-coordinate, incremental, and stochastic variants. These algorithms are analyzed in terms of convergence rates for convex problems and in terms of convergence to stationary points for non-convex ones. We also introduce fast schemes for minimizing large sums of convex functions and principles to accelerate gradient-based approaches, based on Nesterov’s acceleration and on Quasi-Newton approaches. Chapter 3 presents the paradigm of deep kernel machine, which is an alliance between kernel methods and multilayer neural networks. In the context of visual recognition, we introduce a new invariant image model called convolutional kernel networks, which is a new type of convolutional neural network with a reproducing kernel interpretation. The network comes with simple and effective principles to do unsupervised learning, and is compatible with supervised learning via backpropagation rules. Chapter 4 is devoted to sparse estimation—that is, the automatic selection of model variables for explaining observed data; in particular, this chapter presents the result of pluri-disciplinary collaborations in bioinformatics and neuroscience where the sparsity principle is a key to build intepretable predictive models. Finally, the last chapter concludes the manuscript and suggests future perspectives.
Environmentally Responsible Apparel Consumption and Convertible Dresses

Among the many methods to make sustainable garments, convertible garments have the potential to change style and function that allow consumers to keep and use garments longer with the possibility of enhancing sustainability. This research analyzes consumer preferences in changeable design options for convertible dresses and the consumers' influence on environmentally responsible apparel consumption (ERC) behaviors on their preferences regarding changeable design options of dresses, which are popular items. An online survey collected data from a convenient sample of 321 female college students from four universities in the United States. Data were analyzed using IBM SPSS through descriptive analysis, cluster analysis
Suporte à Modelação de Valor de Negócio

In a global market, it is increasingly important for companies to be able to shape their business and realize value exchanges with the network of partners they deal with. Thus, it is essential to model these exchanges of economic value through a business model that is easy to understand and use both by the user and by the software development team. However, there are few models (and methods) that allow modeling value exchanges. In addition, there are no drawing tools that align the business perspective with the software perspective. Thus, this MSc work aims at (i) studying the existing methods to represent business value, identifying their limitations, (ii) finding a solution that facilitates the development of software based on value, and (iii) evaluating the solution using evidence-based software engineering best practices. To achieve these objectives, we began by carrying out a systematic study to ensure a comprehensive view of all the existing value-driven methods. Next, we selected a technological environment where we developed a tool to support the DVD method ( textit Dynamic Value Description. This method allows modeling the main concepts associated with a value exchange and aligning the business perspective with the software perspective. The developed tool, DVDTool, allows the construction of a DVD value model, the generation of a service architecture described using SoaML, as well as the generation of requirements models expressed in an extension of the KAOS4Services model. Finally, we performed a quasi-experiment to evaluate the perceived efficacy and intention of use of our proposal. The results show that the tool was considered easy to use, useful, and the participants registered intention of using in the future.
A Presentation Support System by Expanding Embodiment with a Mobile Touchscreen Device

Most of the people make presentations by using tools such as pointers. However, the use of information devices such as laser pointers and mice can restrict the presenter’s embodied motions and actions. In this paper, we propose a presentation support system that can expand embodiment by using a portable touch screen device. First, we develop a prototype of the system by using an iPhone, and then, we perform experimental evaluation. Next, we performe the evaluation of the modes of PPTouch, and the effectiveness of the system in various situations is clarified. Then we performe comparison with conventional pointers, and evaluation by participants. Both experiments also show the effectives of PPTouch. Keywordspresentation support; expansion of embodiment
QA@INEX 2009: A common task for QA, focused IR and automatic summarization systems

QA@INEX aims to evaluate a complex question-answering task. In such a task, the set of questions is composed of factoid, precise questions that expect short answers, as well as more complex questions that can be answered by several sentences or by an aggregation of texts from dierent documents. Question-answering, XML/passage retrieval and automatic summarization are combined in order to get closer to real information needs.
A Framework For Fault Tolerance In Virtualized Servers

Abstract : In modern naval platforms, most of the critical operations are done with the help of automated systems. Specifically, operational decisions and actions are finalized using command and control systems (C2 systems). A wide variety of sensors, radars, communication devices, and weapons are connected to C2 systems. Generally speaking, C2 systems receive data from their respective sensors and radar and process that data. Officers then rely on C2 output to make sound decisions by using their technical knowledge combined with detailed scientific information.
How Citizens have Informed themselves about Covid-19 during the Pandemic

Fake news is defined as “false stories that appear to be news, spread on the Internet or using other media, usually created to influence political views or as a joke”, thus, it is not necessary false information, although often refers to false information [1]. COVID-19 pandemic has accelerated the generation as well as consumption of fake news. Afraid of the unknown virus, people started to consume all possible information they found on internet, while various parties with specific opinions or ideas started to generate and circulate false information and fake news. Fake news have impacted even to the health of people [2]. The paper analyses the five on-line surveys conducted by the author and her research team between December 2020 and March 2022. There are differences among the answers, mostly due to the COVID-19 situation as well as the differences in government measures. From these surveys, it emerged that the personality strongly impacts one's perception as well as behaviour changes. The paper discusses about the findings from the surveys in comparison to the literature to identify the limitation and future research topics.
The Role of WOM in Affecting the Intention to Purchase Online

Recent studies have focused on the influence of online word-of-mouth (WOM) on tourist behavior. However, the role of traditional versus online WOM on travel decisions remains to be expanded. This chapter addresses this research gap by empirically investigating the impact of offline and online WOM on travel decisions across four different cohorts: Generation Y, Generation X, the Baby Boomers, and the Silent Generation. In addition, it explores generational differences with regard to online booking intentions. Findings reveal that traditional WOM affects travel decisions by all cohorts, with a higher impact for the Baby Boomers and the Silent Generations. Online WOM has a higher influence for younger cohorts, who also show a higher intention to purchase online than older generations. Still, the results show that senior individuals are well aware of the possibilities offered by the Internet as both an information source and a purchase channel. The Role of WOM in Affecting the Intention to Purchase Online: A Comparison Among Traditional vs. Electronic WOM in the Tourism Industry
Service quality evaluation of a geriatric long-term care: A combination of SERVQUAL model and importance-performance analysis

Abstract To provide better and consistent services, it is critically important for a geriatric long-term care center to identify critical service items and then improve the weaknesses. This study combines service quality (SERVQUAL) model and importance-performance analysis to evaluate the service quality of this particular geriatric long-term care center. The results show that three items belong to major weaknesses, which should be addressed immediately in order to reduce the deficiencies. In contrast to major weaknesses, there are six major items classified into major strengths, which should be maintained to provide service excellence of this geriatric long-term care center in order to establish better and longer relationships with patients in the long-term perspectives. This paper provides a framework of combining SERVQUAL model and importance-performance analysis to evaluate the service quality of a geriatric long-term care center. The proposed framework works well in this case study.
Robust Deep Age Estimation Method Using Artificially Generated Image Set

Human age estimation is one of the key factors in the field of Human–Robot Interaction/Human–Computer Interaction (HRI/HCI). Owing to the development of deep‐learning technologies, age recognition has recently been attempted. In general, however, deep learning techniques require a large‐scale database, and for age learning with variations, a conventional database is insufficient. For this reason, we propose an age estimation method using artificially generated data. Image data are artificially generated through 3D information, thus solving the problem of shortage of training data, and helping with the training of the deep‐learning technique. Augmentation using 3D has advantages over 2D because it creates new images with more information. We use a deep architecture as a pre‐trained model, and improve the estimation capacity using artificially augmented training images. The deep architecture can outperform traditional estimation methods, and the improved method showed increased reliability. We have achieved state‐of‐the‐art performance using the proposed method in the Morph‐II dataset and have proven that the proposed method can be used effectively using the Adience dataset.
Does gender influence travel satisfaction with public transport

Gender is often used as a descriptive variable in transportation studies; however, few studies have dealt with its explanatory power over travel satisfaction. We investigated its influence on both satisfaction at overall and attribute levels and relative importance. A linear regression model was built. The findings yield that gender has a limited influence on overall satisfaction. However, women tend to be more critics about expected and delivered service. Future studies could investigate gender influence on satisfaction at multimodal scenarios.
Analysis and optimization techniques for real-time streaming image processing software on general purpose systems

Commercial Off The Shelf (COTS) Chip Multi-Processor (CMP) systems are for cost reasons often used in industry for soft real-time stream processing. COTS CMP systems typically have a low timing predictability, which makes it difficult to develop software applications for these systems with tight temporal requirements. Restricting the way applications use the hardware and Operating System (OS) might alleviate this difficulty, so that certain types of applications could be run on COTS CMP systems with statistically verified temporal requirements. In this thesis we restrict the application domain to soft real-time medical image processing applications, which have a much more ‘stable’ usage of hardware resources than applications in general. Techniques at the application level are employed to improve the reproducibility (i.e. to reduce the variance) of the end-to-end latency of these imaging processing systems. Firstly, we study the effectiveness of a number of scheduling heuristics that are intended to improve the reproducibility of a stream processing application that is executed on COTS multiprocessor systems. Experiments show that the proposed heuristics can reduce the end-to-end latency with almost 60%, and reduce the variation in the latency with more than 90%, when compared with a naive scheduling heuristic that does not consider execution times, dependencies and the memory hierarchy. Secondly, we want to be able to integrate multiple real-time and best-effort applications on a single COTS CMP system without reducing the reproducibility of the real-time application too much. For this we examined the first component that is shared between different applications running on separate cores, the shared cache and in particular the bandwidth in the cache. We propose a technique that implements cache bandwidth reservation in software. This is achieved by dynamically duty-cycling best-effort applications based on their cache bandwidth usages measured with processor performance counters. With this technique we can control the latency increase of real-time applications that is caused by best-effort applications. Thirdly, we introduce the Probabilistic Time Triggered System (PTTS) model to analyze and optimize the end-to-end latency of a complete system that contains multiple time triggered interfaces. Our case study demonstrates the applicability of the PTTS model and the corresponding analysis techniques for an interventional X-ray system. We expect that the PTTS model is also applicable for other systems than medical image processing systems.
Sustainability assessment of a bus system in a mid-sized municipality

Transportation has significant economic, social and environmental impacts and is an important dimension of urban sustainability. Public transportation is recognisably a smart, efficient and sustainable mode of transportation. This paper describes a multi-criteria analysis to assess the sustainable performance of a bus transportation system in a Portuguese mid-sized municipality. The assessment is based on a list of 18 environmental, social, economic and institutional indicators. A group of specialists and political stakeholders defined the relative importance of these indicators. Results showed significant disparities in the sustainable performance of the analysed bus system. Political stakeholders were more sensitive to institutional indicators while specialists were more concerned with operational issues. The research also indicates that the institutional dimension is important for assessing the sustainability of a bus transportation system. The method proves to be useful for identifying the main problems of a bus transportation system and for supporting policies to mitigate these problems.
Excessive Use of Landiolol is Associated with a High Economic Cost

Intravenous landiolol hydrochloride can help prevent atrial fibrillation after cardiovascular surgery. We retrospectively evaluated the effects of landiolol use on the cost of two groups of patients from the same hospital. Landiolol was routinely used by the surgical team for Group L (n=27), and transdermal bisoprolol was mainly used for Group B (n=85). The costs per patient were1,025,000 yen (9,230 USD) in Group L and 47,000 yen (420USD) in Group B. Routine and excessive landiolol use after cardiovascular surgery was associated with a high economic cost. As economic cost is an important consideration, given hospital resource constraints, landiolol use should be carefully evaluated. Received: October 31, 2017; Accepted: November 08, 2017; Published: November 16, 2017 *Corresponding author: Susumu Isoda, Department of Cardiovascular Surgery, Fujisawa City Hospital, Fujisawa 2-6-1, Fujisawa, Kanagawa 251-8550, Japan, Fax no:-81-466-25-3545, Phone no:81-466-25-3111 ;E-mail: isodasusumu1@gmail.com
EFEITO DA DESIGUALDADE NO CRESCIMENTO ECONÔMICO DOS MUNICÍPIOS BRASILEIROS: UMA ANÁLISE COM BASE NO JACKKNIFE MODEL AVERAGING

O presente artigo investiga a relacao entre crescimento economico e desigualdade de renda levando em consideracao a incerteza com relacao a especificacao do modelo econometrico. Para evitar uma especificacao inadequada, aqui faz se uso da tecnica de ponderacao de modelos proposta em Hansen e Racine (2012) conhecida por Jackknife Model Averaging. Esta tecnica consiste em estimar todas as possiveis especificacoes de modelos com um amplo conjunto de variaveis e entao calcular um modelo que e uma media ponderada de todos os outros estimados. A escolha dos fatores de ponderacao e feita com base na minimizacao do criterio de validacao cruzada. Dado o elevado custo computacional, a analise foi feita levando-se em consideracao tres cenarios. Apesar do esforco de pesquisa, nossos resultados sugerem que nao ha evidencias de que a desigualdade de renda exerceu influencia sobre a taxa de crescimento da economia brasileira no periodo de 2000 a 2009.
Reconstructing What You Said: Text Inference Using Smartphone Motion

Smartphones and tablets are becoming ubiquitous within our connected lives and as a result these devices are increasingly being used for more and more sensitive applications, such as banking. The security of the information within these sensitive applications is managed through a variety of different processes, all of which minimise the exposure of this sensitive information to other potentially malicious applications. This paper documents experiments with the ‘zero-permission’ motion sensors on the device as a side-channel for inferring the text typed into a sensitive application. These sensors are freely accessible without the phone user having to give permission. The research was able to, on average, identify nearly 30 percent of typed bigrams from unseen words, using a very small volume of training data, which was less than the size of a tweet. Given the natural redundancy in language this performance is often enough to understand the phrase being typed. We found that large devices were typically more vulnerable, as were users who held the device in one hand whilst typing with fingers. Of those bigrams which were not correctly identified over 60 percent of the errors involved the space bar and nearly half of the errors are within two keys on the keyboard.
Call the midwife! Business incubation, enterprise development and entrepreneurship enablement in developing economies

Enabling domestic entrepreneurship is one pathway for alleviating poverty. In developing economies however, public policies prioritize health and education above entrepreneurship promotion. While international development funding has traditionally supported social and environmental interventions, more recent corporate philanthropic funding has been invested in business incubators to support domestic entrepreneurship. This article examines how business incubation and enterprise development impact on poverty alleviation in developing economies. From the analysis of empirical data gathered from four philanthropy-funded business incubators, their role in how sustainable new venture creation and multiple capital formation contributes to poverty alleviation is explained. The findings contribute to entrepreneurship enablement theory.
Analisis Pengaruh Manajemen Laba Kinerja Perusahaan Kualitas Audit Dan Investment Opportunity Set Terhadap Biaya Ekuitas

The aim of this study is to analyze the effect of earnings management, corporate performance, audit quality, and investment opportunity set on cost of equity. These samples included 461 for JII and LQ-45 during the period 2004-2015. The sampling technique is purposive sampling. Variable earnings management, corporate performance, quality audit, and investment opportunity set as independent variables. Earnings management is proxied by the model Short Term Discretionary Accruals (STDA), proxy corporate performance by Return on Assets (ROA), proxy for audit quality Ukuran Kantor Akuntan Publik (KAP), and the investment opportunity set proxy for Price Earning Ratio (PER). While the dependent variable cost of equity proxy for the model Ohlson. This analysis using multiple linear regression which is previously performed through classical assumption test. The results of research both at the JII and LQ-45 shows that earnings management did not significantly affect the cost of equity, the company's performance did not significantly affect the cost of equity, and Investment opportunity set (IOS) significantly affects the cost of equity. While audit quality affect the cost of equity in companies incorporated in the index JII, but the LQ-45 quality of audit does not affect the cost of equity.
Logical Games as an Educational Tool in the Social Media Environment

Games provide people mainly with entertainment. The purpose of this article is to show some positive side effects of games. The main benefit might be educational. Some games whose main purpose is educational will be analyzed herein. Normally learning is sometimes tedious and unpleasant; therefore, teaching using games in a manner that is pleasurable for students is welcome and should be encouraged.
Factors affecting Organizational Commitment of General Hospital Nurses in Small and Medium Sized Cities

Purpose: This study was done to investigate the relationships between nursing work environment, leader-member exchange(LMX), peer support, and organizational commitment in one city with a severe nurse shortage. Methods: Participants were 198 nurses who had worked for more than 6 months with the same head nurse. They worked in five general hospitals located in one city. In April 2016 participants completed a survey questionnaire about their nursing work environment, LMX, peer support, and organizational commitment. Data were analyzed using descriptive statistics, t-test, ANOVA, Pearson correlation coefficient, and multiple regression. Results: There was a significant difference in nursing work environment by experience of turnover (t=-2.58, p=.010). LMX showed significant difference by department (F=3.81, p=.011). Factors influencing nurses’ organizational commitment were nurse participation in hospital affairs (β=.23, p=.028) and nurse manager ability, leadership and support (β=.18, p=.022). Explanatory power was 18.2% in the regression model. Conclusion: The results suggest that it is necessary to improve the nursing work environment in order to increase organizational commitment. Improvement of the nursing system should be considered along with supplementation of nurses particularly during a severe nurse shortage.