Miracle-dz/UniFAR-FTUs huggingface dataset:
A Hybrid Method Using Temporal and Spatial Information for 3D Lidar Data Segmentation

This paper proposes a novel hybrid segmentation method for 3D Light Detection and Ranging (Lidar) data. The presented approach gains robustness against the under-segmentation issue, i.e., assigning several objects to one segment, by jointly using spatial and temporal information to discriminate nearby objects in the data. When an autonomous vehicle has a complex dynamic environment, such as pedestrians walking close to their nearby objects, determining if a segment consists of one or multiple objects can be difficult with spatial features alone. The temporal cues allow us to resolve such ambiguities. In order to get temporal information, a motion field of the environment is estimated for subsequent 3D Lidar scans based on an occupancy grid representation. Then we propose a hybrid approach using the mean-shift method and the distance dependent Chinese Restaurant Process (ddCRP). After the segmentation blobs are spatially extracted from the scene, the mean-shift seeks the number of possible objects in the state space of each blob. If the mean-shift algorithm determines an under-segmented blob, the ddCRP performs the final partition in this blob. Otherwise, the queried blob remains the same and it is assigned as a segment. The computational time of the hybrid method is below the scanning period of the Lidar sensor. This enables the system to run in real time.
Influence of Ambiguity on Success of Public Infrastructural Megaprojects in Kenya

The objective of this study was to investigate the influence of ambiguity on success of public infrastructural megaprojects in Kenya. The need for this study arose from the thesis that ambiguity is a key cause of complexity that results in infrastructural megaprojects being delivered over budget, behind schedule, with benefit shortfalls, over and over again. The study was designed as multiple-method research based on virtual constructionist ontology recognizing that complexity is the mid-point between order and disorder. A cross-sectional census survey of completed public infrastructural megaprojects was conducted using two interlinked questionnaires. Quantitative data was analyzed using descriptive and inferential statistics while qualitative data was analyzed using expert judgment, scenario mapping and retrospective sense-making. The projects surveyed majorly utilized fixed price contracts with the outcome of increased delivery within budget than within schedule. The results showed that ambiguity had significant negative influence on process and overall success of public infrastructural megaprojects but had no significant relationship with product and organizational success. Projects in which the client assumed responsibility for cost and schedule risk had higher chances of meeting both cost and schedule objectives. In order to manage the negative effects of ambiguity, we recommend a new perspective to contract design of public infrastructural megaprojects based on complexity science, blending both outcome and behavior-based contracts. Such contracts should ensure that, in the face of ambiguity, the contractors are able to act in the best interest of their clients and that the clients have access to quality Project Management Information Systems.
Solutions to Problems Occurring over the Enterprise System Adoption Lifecycle: A Preliminary Study

The paper investigates solutions incorporated by companies to overcome problems occurring during enterprise system (ES) adoption. It draws from the experience of Polish practitioners who participated in ES implementations. Following grounded theory approach and incorporating open and axial coding the solutions given by respondents were classified into 14 main categories and their distribution across the system lifecycle was analyzed. The research revealed uneven distribution of solutions from different
Effects of Direct-to-Consumer Advertising on Medication Choice: The Case of Antidepressants

Although direct-to-consumer advertising (DTCA) has generated substantial controversy, little is known about its effects on consumer and physician behavior. In this article, the authors examine the impact of DTCA and physician detailing on the choice of antidepressant medication. The authors find that detailing has a much greater effect on medication choice in the antidepressant market than does DTCA.
Selecting the selector: Comparison of update rules for discrete global optimization

We compare some well‐known Bayesian global optimization methods in four distinct regimes, corresponding to high and low levels of measurement noise and to high and low levels of “quenched noise” (which term we use to describe the roughness of the function we are trying to optimize). We isolate the two stages of this optimization in terms of a “regressor,” which fits a model to the data measured so far, and a “selector,” which identifies the next point to be measured. The focus of this paper is to investigate the choice of selector when the regressor is well matched to the data.
Mobility Patterns of Asian Students: The Case of Tourism and Hospitality Management Students in the United Kingdom

ABSTRACT This study aimed to investigate the driving forces behind Asian students studying tourism and hospitality in the United Kingdom at 3 stages: (a) choosing a foreign country, (b) selecting the United Kingdom as the host country, and (c) undertaking tourism and hospitality courses. We collected data using questionnaires distributed among tourism and management students attending a major higher education provider in the United Kingdom. The findings identified subgroups of push and pull factors that explain the movement patterns of Asian students toward studying tourism and hospitality in the United Kingdom. Using a mathematical equation, this study reveals that seeking a better life, the nature of the program, and external influences significantly impact students’ movements.
Reductibility considerations for an aggregated Markov chain

Aggregation of synchronized structures such as closed fork-join generalized stochastic Petri nets is often a challenging problem due to the absence of closed-form solutions. This paper provides a full characterization of the aggregation properties of a closed fork-join subnet with multiple branches by resorting to the asymptotic properties of the underlying continuous-time Markov chain (CTMC) as the number of tokens tends to infinity. The asymptotic analysis provides valuable insight into the aggregation of closed fork-join structures. The relationship between the firing rates of the original closed fork-join subnet and the approximate reducibility of the aggregated CTMC is investigated and illustrated with numerical examples.
Total Relationship Marketing Ed. 2

Total Relationship Marketing provides a genuinely unique new view of the meaning of marketing management and a complete introduction to the rapidly evolving field of relationship marketing. A major contribution to marketing thought internationally, this new edition of Gummesson's seminal title presents a powerful and in depth analysis of modern relationship marketing. Highly informative, practical in style, and packed with examples and cases from real companies, it is an essential resource for all serious marketing practitioners as well as both undergraduate and postgraduate students.
Introductory Statistical Inference

Weaknesses of the text include: (1) there are occasional sections using awkward grammar and there are numerous typesetting errors regarding inconsistent fonts (see p. 36, for example); (2) there is no mention of modern software; and (3) there are no exercises and no textbook website, thus limiting the text to being mainly a review of the literature, plus, selection of some examples and methods. Thus, it is unlike many other texts within the Chapman and Hall series, and it would not be my choice for a text to learn how to do MUNDA. I note that this text has also been reviewed by Blasius (2007), who also finds strengths, but also cautions that it is probably not intended as a text for learning how to do MUNDA.
Rat transgenesis via embryonic stem cells electroporated with the Kusabira‐orange gene

Functional germline-competent rat embryonic stem (ES) cell lines have been established by using a few inhibitors for FGF receptor, MEK and GSK3 in differentiation-related signaling pathways (Buehr et al., 2008; Hirabayashi et al., 2010). Although any alternative methods, such as somatic cell nuclear transplantation, are not applicable to produce gene-modiﬁed rats, the minimal essential materials for conducting transgenic studies, including reverse genetics approaches, are now ready for this rodent. The present study was undertaken to examine the production efﬁciency of chimeric rats by blastocyst injection of ES cells electroporated with a humanized Kusabira-Orange (huKO) gene and the germline transmission of the huKO gene from the chimeras to next generation. Blastocysts at E4.5 were recovered from Brown-Norway females, and zona-free embryos were plated on mitomycin-treated mouse embryonic ﬁbroblasts in N2B27 medium containing 2i (MEK inhibitor PD0325901, 1 m M; GSK3 inhibitor CHIR99021, 3 m M) and rat LIF (1,000U/ml ESGRO), as described by Buehr et al. (2008) withafewmodiﬁcations. AnEScelllineestablishedhere(namedasrESBN2i-4)wasderivedfromamale,basedonaPCRanalysis usingaprimersettodetecttherat Sry gene. At passage 8 of the rESBN2i-4line,25 m ghuKOgene(CAG/huKO-neoplasmid;7.5kb) was electroporated at 800V, 10 m F to 1 (cid:1) 10 6 ES cells in 500 m l of N2B27 medium supplemented with 10% FBS. The ES cells (passage 9) were treated with 200 m g/ml neomycin (G418) 48h after the electroporation, and neomycin-resistant huKO-positive colonies (passage 10) were harvested 7 days after electroporation (Fig. 1a)
A High Performance System for Intrusion Detection and Reaction Management

Detecting all kinds of intrusions efficiently requires a global view of the monitored network. This can only be achieved with an architecture which is able to gather data from all sources. We have developed a security operation center called SOCBox which is able to detect coordinated attacks that are not detected by traditional IDS. In this article, we present the global architecture of the SOCBox as well as several methods used to test its accuracy and performance. A real ISP network have been used as well as experiments in our lab.
RISE AND FALL OF SKELETAL MUSCLE SIZE OVER THE ENTIRE LIFE SPAN

history of coronary heart disease. The mean Epworth Sleepiness Scale score was 14.4 in persons with sleep apnea, compared with 10.3 in persons without sleep apnea. After controlling for variables associated with falls, sleep apnea, but not snoring, witnessed apnea, or an Epworth Score above 10, was associated with a greater risk of two or more falls during the previous 12 months (odds ratio (OR) 5 2.23, 95% confidence interval (CI) 5 1.11–4.47). Sleep apnea was also associated with a higher Geriatric Depression Scale score (third tertile vs rest, OR 5 2.26, 95% CI 5 1.14–4.48), and inclusion of the depression variable into the model attenuated the relationship between sleep apnea and falls. Including the MMSE score did not substantially alter these results (Table 1). To our knowledge, this is the first study examining the relationship between sleep apnea and falls in older persons. We demonstrated a doubling of the likelihood of falls in older persons with a previous diagnosis of sleep apnea. Hypoxemia and sleep disruption from sleep apnea are related to daytime functional impairments in executive function, vigilance, alertness, fine motor coordination, and psychological disturbance, which may be likely mechanisms. In our population, depression attenuated the magnitude of the association between sleep apnea and falls, suggesting that psychological disturbance may be one of the intermediary factors in the association between sleep apnea and falls. A relationship was not demonstrated between falls and our measure of daytime sleepiness, the Epworth Sleepiness Score, although this score does not differentiate underlying causes resulting in daytime sleepiness. Confirmation of our findings in other elderly populations would be useful, given aging population trends and the high burden from recurrent falls on health and community services.
Combining extreme learning machine and decision tree for duration prediction in HMM based speech synthesis

Hidden Markov Model (HMM) based speech synthesis using Decision Tree (DT) for duration prediction is known to produce over-averaged rhythm. To alleviate this problem, this paper proposes a two level duration prediction method together with outlier removal. This method takes advantages of accurate regression capability by Extreme Learning Machine (ELM) for phone level duration prediction, and the capability of distributing state durations by DT for state level duration prediction. Experimental results showed that the method decreased RMSE of phone duration, increased the fluctuation of syllable duration, and achieved 63.75% in preference evaluation. Furthermore, this method does not incur laborious manual alignment on training corpus.
Novel tools in quantitative risk management

This thesis proposes novel methods to analyze risk and dependence across a joint probability distribution. It is well known in finance and insurance that risk and dependence are vastly different in the tails compared to the rest of the distribution. Tails characterise events such as market crisis and natural catastrophes, and contribute to a significant portion of overall risk and dependence. However typical measures of risk and dependence capture the overall result and mask variations across the probability distribution. Random quantities are partitioned into infinitesimal layers capturing outcomes of various magnitude and likelihood. Risk and dependence are then measured across layers using established methods such as distortion and correlation. Layers are standard constructs representing (re)insurance coverage, capital consumption and shortfall, derivative payouts, and tranches of collateralised debt obligations. This thesis expresses layer endpoints using percentiles or more commonly known as Values–at–Risk (VaRs), hence each layer occupies a relative position in the probability distribution. This thesis also extends distortion risk measurement by capturing upside risk in addition to downside risk. In financial and insurance markets with strong competition and limited availability of capital, an explicit view of upside risk is required to reflect opportunity costs. Developments in this thesis formalise existing, and reveal new, insights to risk and diversification. For example the framework explains weak diversification in financial and insurance markets despite moderate correlations overall. The framework also deals with problems such as setting capital buffers, reinsurance purchase and assessing the credit quality of debt tranches. These insights arise from a deeper understanding of how risk and dependence varies across a probability distribution. Proposed methods apply consistent concepts such as VaRs, distortion and layers, and hence form a coherent analytical framework. These concepts are well established and hence the resulting framework integrates and expands current disparate approaches. The proposed framework is a complete tool to quantitative risk management, by first analysing risk and dependence when imperfectly dependent random quantities are aggregated, and then guiding strategies to optimally manage and reduce risk.
An Efficient Hardware Allocation Algorithm for Optical Hardware Architecture Design

This paper proposes an efficient hardware allocation algorithm for optical hardware architecture design. The proposed algorithm works on scheduled input graph and allocates binds function-al units, registers and interconnections by considering interdependency between operations and memory in elements in each control step, in order to share registers and interconnections connected to functional units, as much as possible. Also, the register allocation is especially executes the allocation optimal using graph coloring techniques. Therefore the overall resource is reduced. The effectiveness of the proposed algorithm has been proven by the experiment with the benchmark examples.
Virtual reality with customized positive stimuli in a cognitive-motor rehabilitation task

Virtual Reality applications for integrated cognitive and motor stroke rehabilitation show promise for providing more comprehensive rehabilitation programs. However, we are still missing evidence on its impact in comparison with standard rehabilitation, particularly in patients with cognitive impairment. Additionally, little is known on how specific stimuli in the virtual environment affect task performance and its consequence on recovery. Here we investigate the impact in stroke recovery of a virtual cognitive-motor task customized with positive stimuli, in comparison to standard rehabilitation. The positive stimuli were images based on individual preferences, and self-selected music (half of the sessions). 13 participants in the subacute stage of stroke, with cognitive and motor deficits, were allocated to one of two groups (VR, Control). Motor and cognitive outcomes were assessed at end of treatment (4–6 weeks) and at a 4-week follow-up. Both groups showed significant improvements over time in functional ability during task performance, but without changes in motor impairment. Cognitive outcomes were modest in both groups. For participants in the VR group, the score in the task was significantly higher in sessions with music. There were no statistical differences between groups at end of treatment and follow-up. The impact of VR therapy was lower than in similar studies with stroke patients without cognitive deficits. This study is a first step towards understanding how VR could be shaped to address the particular needs of this population.
A family of genes located on four separate 32-kilobase circular plasmids in Borrelia burgdorferi B31

We have identified four loci in Borrelia burgdorferi B31 that contain open reading frames capable of encoding six proteins that are related to the antigenic proteins OspE and OspF. We have designated these proteins Erp, for OspEF-related protein, and named their respective genes erp. The erpA and erpB genes are linked, as are erpC and erpD, and the pairs probably constitute two operons. The erpG and erpH genes appear to be monocistronic. The ErpA and ErpC proteins are expressed by B. burgdorferi B31 in culture and are recognized by a polyclonal antiserum raised against the OspE protein of B. burgdorferi N40. The four erp loci are each located on different 32-kb circular plasmids that contain additional DNA sequences that are homologous to each other and to an 8.3-kb circular plasmid of B. burgdorferi sensu lato Ip2l. All four 32-kb plasmids can be maintained within a single bacterium, which may provide a model for the study of plasmid replication and segregation in B. burgdorferi.
Représentations de la géométrie et des contraintes cartographiques pour la généralisation du linéaire routier

La generalisation cartographique est le processus complexe qui permet d'assurer la lisibilite d'une carte obtenue par reduction d'echelle. Nous considerons dans cette these la generalisation d'objets lineaires, et plus particulierement les routes, et nous developpons de nouveaux algorithmes, bases sur de nouvelles representations de ces elements. La courbure semble etre un bon indicateur des details significatif d'un objet lineaire, en particulier des routes, dont les details importants sont en premier lieu les epingles a cheveux, et en general tout changement de direction. Nous avons d'abord programme un lissage de la courbure qui garantit d'une part que la forme generale de la courbe est conservee, et qui offre d'autre part un seuillage des rayons de courbure directement relie au parametre de la gaussienne. Cette propriete que nous demontrons offre une garantie de lisibilite a la courbe habillee de son nouveau symbole. Le lissage de la courbure provoque des deformations de la courbe, entrainant une perte des connexions au reseau. Pour fixer les points extremites de chaque courbe, nous avons developpe divers methodes de recalage de la courbe generalisee. Enfin, afin de prendre en compte des ensembles varies de contrainte cartographique, nous avons mis en place un modele iteratif, utilisant une traduction des imperatifs cartographiques en contraintes mecaniques. La pertinence de ce modele est discutee, et compare au paradigme multi-agent.
Hyperspectral data analysis and supervised feature reduction via projection pursuit

As the number of spectral bands of high-spectral resolution data increases, the ability to detect more detailed classes should also increase, and the classification accuracy should increase as well. Often the number of labelled samples used for supervised classification techniques is limited, thus limiting the precision with which class characteristics can be estimated. As the number of spectral bands becomes large, the limitation on performance imposed by the limited number of training samples can become severe. A number of techniques for case-specific feature extraction have been developed to reduce dimensionality without loss of class separability. Most of these techniques require the estimation of statistics at full dimensionality in order to extract relevant features for classification. If the number of training samples is not adequately large, the estimation of parameters in high-dimensional data will not be accurate enough. As a result, the estimated features may not be as effective as they could be. This suggests the need for reducing the dimensionality via a preprocessing method that takes into consideration high-dimensional feature-space properties. Such reduction should enable the estimation of feature-extraction parameters to be more accurate. Using a technique referred to as projection pursuit (PP), such an algorithm has been developed. This technique is able to bypass many of the problems of the limitation of small numbers of training samples by making the computations in a lower-dimensional space, and optimizing a function called the projection index. A current limitation of this method is that, as the number of dimensions increases, it is likely that a local maximum of the projection index will be found that does not enable one to fully exploit hyperspectral-data capabilities.
Etude de la coalescence dans les rampes de sprays : application au système d'aspersion des réacteursà eau pressurisée

L’efficacite du systeme d’aspersion, dispositif de securite utilise dans les reacteurs nucleaires, depend de la taille et de la vitesse des gouttes, evoluant au cours de leur chute. Cette these a vise a comprendre les differents mecanismes agissant lors de la collision entre les gouttes. La construction d’un banc experimental a permis d'identifier avec precision les differents regimes de collision : la coalescence, la separation par etirement ou par reflexion et le rebond. Les resultats experimentaux ont ete unifies grâce a la creation d��un nouveau nombre de Weber dit « symetrique » qui a contribue au developpement de trois nouveaux modeles decrivant les transitions entre les regimes pour des gouttes de tailles differentes. Le role de la de la masse volumique et de la viscosite de la phase gazeuse a ensuite ete identifie et une correlation empirique en a ete deduite. L’ensemble des resultats a enfin ete utilise dans une analyse prospective de l’interaction entre deux sprays.