Miracle-dz/UniFAR-FTUs huggingface dataset:
Odométrie Visuelle Monoculaire en Environnement Sous-Marin

In robotics, localization from a camera is very classical. However, in the context of underwater robotics, the visual degradations induced by the medium properties make very difficult the use of cameras. Hence, most localization methods are based on proprioceptive sensors or acoustic positioning. On the other hand, visual odometry and visual SLAM have been exhaustively studied for aerial or terrestrial applications. However, the state-of-the-art algorithms tend to fail underwater. In this paper we tackle the problem of underwater visual localization and propose a new monocular visual odometry method dedicated to the underwater environment. The main application of this work is the localization of Remotely Operated Vehicles (ROV) used for archaeology surveys but the developed system can be used in any other applications, as long as visual information is
Coupling Functions for NM-64 and NM Without Lead Derived on the Basis of Calculated Apparent Cutoff Rigidities for CR Latitude Survey from Antarctica to Italy in Minimum of Solar Activity

In Dorman et al. (2007) it was calculate the apparent cut-off rigidities for the backward route (Antarctica-Italy) of the CR latitude survey performed on a ship during 1996-1997 solar minimum. These computations were done on the basis of results of trajectory calculations for inclined cut-off rigidities for various azimuth and zenith angles (0°, 15°, 30°, 45°, 60°) and azimuth directions changing from 0° to 360° in steps of 45°. The information on integral multiplicities of secondary neutrons detected by neutron monitor in dependence of zenith angle of incoming primary CR particles have been also used. This information is based on the theoretical calculations of meson-nuclear cascades of primary protons with different rigidities arriving to the Earth's atmosphere at zenith angles 0°, 15°, 30°, 45°, 60° and 75°. By using this information and data of CR latitude survey from Antarctica to Italy in minimum of solar activity we determine coupling functions for NM-64 and NM without lead.
User Interface for Interaction with a Virtual and Real Humanoid Robot

Easy programming and connection interfaces, makes a virtual reality a powerful tool for robotics. To include a virtual representation of a human-robot interface has severe advantages and attractive detailed visualizations of the results, auto collision checking visual representation of concepts from robotics teaching, etc. In order to interact with a Bioloid humanoid robot, we designed a user interface in software. This software uses VRML capabilities for pedagogical representation of this robot. The display of this structure, axles and frames ground interaction, com’s and other aspects can be manipulated by the user. Particular aspects of a humanoid robot that are recipients of this search are the different contact configurations possible.
Copyright 2014 Colin Stoy THE ROLE OF THE DGK1 AND PAH1 IN LIPID INTERCONVERSION ON SACCHAROMYCES CEREVISIAE VACUOLE PHYSIOLOGY, HOMEOSTASIS, PROTEIN SORTING AND FUSION BY

A variety of factors are needed for the homotypic fusion of the yeast vacuole, including a number of proteins and regulatory lipids. The deletion of the phosphatidic acid (PA) phosphatase gene Pah1, which converts PA in diacylglycerol kinase (DAG), was previously shown to produce a fragmented vacuole phenotype, greatly inhibit fusion and result in the vacuolar protein sorting defect. As such, the impact of the deletion of the complementary DAG kinase gene Dgk1, which converts DAG into PA, and the impact of deleting both genes was observed. The deletion of Dgk1 was observed to augment fusion, despite showing a moderately fragmented vacuolar phenotype. This fusion was shown to still be dependent on the core fusion machinery proteins, and resistant to inhibition by the DAG ligand C1B, and was better able to maintain fusion capacity when held for an extended time on ice. This deletion also had a unique protein profile, different from the wild type background, but not the inverse of the Pah1 deletion. The double deletion showed highly fragmented vacuoles, much like Pah1 deletion, though these vacuoles were able to reform after osmotic shock, similar to the wild type background, but unlike either single deletion strain. This strain displayed reduced fusion and, interestingly, what appeared to be either the aberrant production, or degradation, of proteins. This observation points to a potentially more global cause for the observed phenotypes.
On Extensibility and Personalizability of Multi-Modal Trip Planning

Trip planning is a practical task that has drawn extensive attention from the AI planning and scheduling community and the industrial/commercial sectors. In this paper, we consider the setting of the multi-modal trip planning, where users can exploit different transportation modes, such as walking, biking, public transit, and taxi. In such a context, it would be of benefit if the user was able to extend the cost base, including traveling time and fare, of the planner, and to personalize the planner according to her own constraints and preferences. To this end, we designed and developed a hipergraph-based multi-modal trip planner that allows users to upload auxiliary cost metrics (e.g., crime rates), to specify constraints as a theory in the linear temporal logic, and to express preferences as a preferential cost function.
Migration and its effect on extreme poor households ’ trajectories

In the development discourse, migration is seen a contested concept because it can produce both desirable and undesirable outcomes. This paper focuses on analysing migration as a livelihood option for extreme poor households drawing upon Stimulating Household Improvements Resulting in Economic Empowerment (SHIREE 2 ) programme data. In the qualitative longitudinal household tracking tool of SHIREE programme, we found different kinds of migration contexts, notably: rural to urban migration, seasonal migration, border crossing migration, and natural disaster related migrations. Our study found that low incomes, loss of earning opportunities, evictions, health shocks, lack of specialized skills, bonded labour and fraud were factors underpinning unsuccessful migration. On the other hand, migrations that developed social networks, had support from NGOs, resulted in reduced dependency ratios, and chose the right destination tended to be positive experiences that helped improve migrants’ wellbeing.
CCL 5 , CCR 1 and CCR 5 in murine glioblastoma : immune cell infiltration and survival rates are not dependent on individual expression of either CCR 1 or CCR 5

Glioblastoma multiforme (GBM) is the most malignant brain tumor. Microglia/macrophages are found within human GBM where they likely promote tumor progression. We report that CCL5, CCR1, and CCR5 are expressed in glioblastoma. Individual deletion of CCR1 or CCR5 had little to no effect on survival of tumor bearing mice, or numbers of glioblastoma-infiltrated microglia/ macrophages or lymphocytes. CCL5 promoted in vitro migration of wild type, CCR1or CCR5deficient microglia/macrophages that was blocked by the dual CCR1/CCR5 antagonist, MetCCL5. These data suggest that CCL5 functions within the glioblastoma microenvironment through CCR1 and CCR5 in a redundant manner.
Image Edge Detection Algorithm based on GM ( 1 , 1 , C )

In the traditional method of edge detection by using grey prediction model, for the denominator (development coefficient) in the time response sequence of the classic GM(1,1) model may approach to the ill-condition of 0 when the original sequence constituted by the local image data is very close, we apply another model GM(1,1,C) from the grey prediction model family into image edge detection. Firstly choose pixel sequences from four main texture directions as the original sequence of grey prediction model, carry out the operation of GM(1,1,C),then the fitted residual sum for each sequence is calculated and the difference between the maximum residual sum of the sequences and the minimum residual sum in the same neighborhood is used as an indicator of the local neighborhood fluctuation of the image to measure degree of being edge, and finally set a threshold to extract the edge. The experimental results show that the proposed algorithm can obtain better effect.
Nonlinear attitude and position control for a quadrotor UAV

Nowadays, quadrotor UAV platforms have began to spread around and starts to catch the attention of the industry for their applications in various tasks like the monitoring of impervious or dangerous areas and the transportations of payloads. All these missions can require the UAV to cope with external disturbances from the environment, the wind for example, or to sustain aggressive manoeuvrers with large variations of attitude angles. The linear control applied to quadrotor platforms has been deeply explored and many successful applications have been developed in the recent years. This kind of control based on standard and well known techniques provides drones that can work fine in a certain range of angles around the hovering condition but it obtains poor performances in the case of aggressive flight. The purpose of this thesis is the development of a nonlinear control architecture for the quadrotor UAV platform of the FLYART laboratory. During the development of this work many control strategies have been developed and analysed in order to obtain a controlled system able to cope with difficult working conditions. The tuning of these control laws has been handled applying the H∞ tuning technique to the developed control system. The starting point is the backstepping method, analysed at the beginning of the third chapter after a brief introduction to the quadcopters in the first chapter and the presentation of the quadrotor model in the second one. Then the integral backstepping technique has been implemented in two different ways in order to gain robustness for the system and compensate possible disturbances and uncertainties of the real system. After these control laws, it has been tackled the problem of singularities carried by the attitude angle parametrization with the proposal of a geometric control architecture that allows to avoid this inconvenient. All the control laws are mathematically developed in this thesis work and the resulting simulations are shown in the last chapter.
Modelling Automobile Driver’s Toll-Lane Choice Behaviour at a Toll Plaza

A toll-lane selection process at a toll plaza can be looked at as an outcome of the choice processes of individual drivers. In this paper an attempt is made to develop a random utility based discrete multinomial choice model for the behaviour of automobile drivers while selecting toll-lanes at a toll plaza. Specifically, a multinomial Logit model is developed and calibrated using disaggregate level choice data from three toll plazas with different geometry and rates of arrival of vehicles. The calibrated Logit models from the different sites when statistically compared show that a generic model, applicable to all the sites, is possible. Such a generic model is also developed. The use of the proposed model can improve the analysis of traffic flow at toll plazas and ultimately lead to more effective designs of these facilities. Keyword: Toll Plaza, Discrete Multinomial Choice Model, Multinomial Logit Model.
Effect of Clinical Pathway Implementation on Outcomes of Patients with Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) is an incapacitating and progressive respiratory state that leads to significant burden, both medically and economically. Clinical pathway (CP) promotes the quality of care through the continuum by improving risk-adjusted patient outcomes, increasing patient satisfaction, promoting patient safety, and optimizing the use of resources. The aim of this study: was to evaluate the effect of clinical pathway implementation on outcomes of patients with chronic obstructive pulmonary disease. Patients and Methods: A quasi experimental research design was used. 60 adult patients with COPD of both sexes were included; they were sequentially recruited equally into 2 groups (control and study groups 30 for each). A study was performed at the Chest Department in Assiut University Hospitals. One tool was utilized for data collection: COPD assessment sheet and Clinical Pathway Protocol. Results: There was highly significant statistical difference between the two groups concerning hospital stay and anxiety level and dyspnea degree on discharge. Conclusion and Recommendations: implementation of CP in the COPD patients' management significantly decreased the hospital stay and improved dyspnea and decrease anxiety levels therefore yielding cost savings. The CP should be implemented for COPD patients to replace the conventional nursing care plan.
Optimal Design of Digital Fractional Order Differentiator using Updated Cuckoo Search Algorithm

A recently developed metaheuristic techniques cuckoo search algorithm and its updated version are used to design finite impulse response digital fractional order differentiator. In standard cuckoo search, the switching parameter which maintains the balance between local and global random walk is kept constant. Here, the impact of linearly increasing switching parameter is studied on convergence rate and performance parameters of digital fractional order differentiator to get better exploration in search space. The results obtained from updated algorithm are compared for magnitude and phase errors, execution time and fitness curve with standard cuckoo search algorithm and particle swarm optimization algorithm. It is discovered from extensive simulations that fractional order differentiator using updated cuckoo search algorithm outperforms other algorithms.
D Simulations for Wireless Ad Hoc Networks in Grid Environment

In this paper the usage of grid environment for fast simulation of wireless ad hoc networks in 3D terrains is presented. The possibilities and gains of the grid environment have proven to be very resourceful when simulating wireless ad hoc networks using the NS-2 simulator especially when considering lengthy simulations for performance evaluation with a heavy traffic load involving computing intensive calculations like the estimation of received power in a 3D environment based on the radio wave diffraction.
Vehicle Sensor and Event Detection through Smartphone Acceleration Data

Modern vehicles contain sensors tracking the state of the car. The recorded data is used for internal diagnostics and error reporting. Sharing and aggregating this data in a network could increase traffic safety by warning drivers or monitoring road quality. But vehicle sensor data is restricted and not standardized. To overcome restrictions, a smartphone could be used as a proxy from the real world to the network. In this thesis, vehicle sensor data is used to label acceleration data of a free positioned smartphone. It is investigated, whether vehicle system activations can be estimated with smartphone acceleration data. Events that are identified are Anti-lock Braking System (ABS), Electronic Stability Control (ESC), vehicles acceleration, and heavy braking. The results show that estimating events in a driving context is hardly achievable. The main problem is to transform acceleration vectors in the vehicle’s coordinate system, since the smartphone is freely positioned. Although, detecting vehicle sensors and driving events through smartphone data is a promising approach to overcome the lack of information resulting from restrictions of the vehicle’s sensor communication. Activations can not yet be accurately detected by acceleration data and more research for more accurate sensor readings of the smartphone has to be performed.
Small Slot Antenna with Enhanced Bandwidth and Band-Notched Performance for UWB Applications

─ A novel ultra wideband (UWB) printed slot antenna with band-notched performance is designed and manufactured. In order to increase the impedance bandwidth of the slot antenna, we use a rectangular slot with a pair of L-shaped strips protruded inside the slot on the ground plane that with this structure UWB frequency range can be achieved. Additionally, by using an N-shaped slot on the radiating stub, a frequency notch band performance has been obtained. The designed antenna has a small size of 20×20 mm 2 while showing the radiation performance in the frequency band of 3.12 to over 14.27 GHz with a band rejection performance in the frequency band of 5.03 to 5.86 GHz. Simulated and experimental results obtained for this antenna show that it exhibits good radiation behavior within the UWB frequency range. Index Terms ─ Printed Slot Antenna, N-Shaped Slot, Protruded L-Shaped Strip, Ultra-Wideband (UWB).
1 Assessing OSM Road Positional Quality With Authoritative Data

Online collaborative mapping projects, such as OpenStreetMap (OSM), have been developed not only to provide public and free information about many types of geospatial features, including communication and transportation networks such as roads, trails and railways, but also to give its users the chance to contribute with their local knowledge about the places. There must be, however, a special concern for the quality assurance within these community driven maps. The aim of this paper is to assess the positional differences between the road network available in OSM for some regions of the Coimbra Municipality, Portugal, and the data provided by the Coimbra City Hall, considered as reference. The assessment is made by computing the distance between the features’ lines, extracted from OSM and the reference data, using two approaches. One regards the application of a workflow, which uses tools already available in GIS software. The other approach applies directly the FOSS4G-based procedure developed by Brovelli et al. (2015).
Tar Removal by Combination of Plasma with Catalyst

Gasification of a biomass is an industrial process utilised to produce synthesis gas that can be used to generate electricity. The generated synthesis gas is however often polluted with tar and other pollutants, and thus cleaning before its further use is necessary. The objective of this paper is to investigate the potential of tar removal by non-thermal plasma generated by atmospheric pressure discharges in combination with TiO2 catalyst in various operating conditions. Naphthalene was used as a model tar compound and its decomposition and by-products formation was analysed by means of the FTIR spectrometry. The results showed higher naphthalene removal efficiency in ambient air with the catalyst than without it (almost 80 % and 40 %, respectively, at 11 kV, 500 Hz).
Global Optimization using Monte Carlo Tree Search in discrete State Lattices

Global Optimization is a highly researched area with applications in different scientific fields. The goal to find the overall best solution to a problem has been tried to solve with many different approaches. Two of the more popular algorithms are the Genetic Algorithms and the Monte Carlo methods which both have the idea of using random numbers to find global optima. In this thesis, a new Global Optimization algorithm is proposed that is influenced to an extent by the two latter methods, among others. This new method is at its core a modified variant of the Monte Carlo Tree Search, which is usually applied in the gaming domain. The idea of the algorithm is that it operates on a binary subset lattice. All elements of this subset lattice are encoded as binary strings that can be viewed as discrete states in the solution space. This form of states is based on the idea of the state representation in Genetic Algorithms. The name of the algorithm can be justified by means of this short description: (binary) Subset Lattice Monte Carlo Tree Optimization. Furthermore, two enhancements of the base version of the algorithm are presented. Firstly, the UCD algorithm is integrated which provides a mathematical framework in order to make the most use of transpositions. Secondly, the RAVE algorithm is added. This AMAF-technique has the task to spread rewards in more regions of the lattice. After careful research, it can be assumed that the UCD algorithm is used for the first time in combination with RAVE. The performance of the algorithm is first tested on artificial benchmark functions by comparing it with a Genetic Algorithm. Additionally, the performance is investigated on the more complex Lennard-Jones Atomic Clusters problem. The results of these experiments indicate that the Subset Lattice Monte Carlo Tree Optimization is able to find optima in particularly large solution spaces. In case of such solution spaces, it outperformed the Genetic Algorithm. In contrast to that, the newly proposed algorithm has difficulties to converge to global optima at even simple test functions. In these cases, the algorithm only improved its solution up to a certain point. These results lead to suggestions of how this first version of a new optimization algorithm can be enhanced in the future.
Large-scale habitat associations of birds in lowland Iceland : Implications for conservation

Iceland is responsible for many internationally important populations of breeding bird species, yet very little is currently known about how these species use the habitats available to them. Lowland areas of Iceland, in particular, have undergone significant landscape changes over the last century, such as widespread drainage of wetlands and conversion to agriculture, changes in grazing pressure and recently, extensive afforestation. The impact of these changes on breeding bird species will depend on the relative importance of different habitats for each species, and the threats facing those habitats. Here we report the results of a large-scale survey of the factors influencing patterns of habitat selection of eight populations of Charadriiform bird species throughout lowland Iceland; oystercatcher Haematopus ostralegus, golden plover Pluvialis apricaria, dunlin Calidris alpina, snipe Gallinago gallinago, whimbrel Numenius phaeopus, black-tailed godwit Limosa limosa, redshank Tringa totanus and arctic skua Stercorarius parasiticus. Ordination analyses and multiple logistic regression models are constructed to explore the components of habitats that influence the distribution of these species. Five of the eight species analysed showed significant preferences for lowland wetland habitats and four significantly selected areas containing wet features such as pools and high water tables. These results allow us to identify future conflicts in land use that are likely to result from government-supported large-scale afforestation of lowland areas and hydro-electric developments. 2005 Elsevier Ltd. All rights reserved.
Conceptualizing Involvement

A state-of-the-art review paper for the construct of involvement is presented. This paper outlines prior studies which show the antecedents of involvement to be due to personal characteristics, object characteristics and/or situational characteristics. One or more of these factors is proposed to influence the consumer's level of involvement in various research areas of involvement with advertising, involvement with products and involvement with purchase decisions.