Miracle-dz/UniFAR-FTUs huggingface dataset:
Cooperative Visual SLAM Algorithm based on Adaptive Covariance Intersection

Simultaneous localization and mapping (SLAM) is an essential capability for Unmanned Ground Vehicles (UGVs) travelling in unknown environments where globally accurate position data as GPS is not available. It is an important topic in the autonomous mobile robot research. This paper presents an Adaptive Decentralized Cooperative Vision-based SLAM solution for multiple UGVs, using the Adaptive Covariance Intersection (ACI) supported by a stereo vision sensor. In recent years, SLAM problem has gotten a speci c consideration, the most commonly used approaches are the EKFSLAM algorithm and the FAST-SLAM algorithm. The primary, which requires an accurate process and an observation model, su ers from the linearization problem. The last mentioned is not suitable for real-time implementation. In our work, the Visual SLAM (VSLAM) problem could be solved based on the Smooth Variable Structure Filter (SVSF) is proposed. This new lter is robust and stable to modelling uncertainties making it suitable for UGV localization and mapping problem. This new strategy retains the near optimal performance of the SVSF when applied to an uncertain system, it has the added bene t of presenting a considerable improvement in the robustness of the estimation process. All UGVs will add data features sorted by the ACI that estimate position on the global map. This solution gives, as a result, a large reliable map constructed by a group of UGVs plotted on it. This paper presents a Cooperative SVSF-VSLAM algorithm that contributes to solve the Adaptive Cooperative Vision SLAM problem for multiple UGVs. The algorithm was implemented on three mobile robots Pioneer 3-AT, using stereo vision sensors. Simulation results show e ciency and give an advantage to our proposed algorithm, compared to the Cooperative EKF-VSLAM algorithm mainly concerning the noise quality.
Toll-Like Receptor 2 ( TLR 2 ) Gene Expression in Psoriasis Vulgaris and its Correlation with Vitamin D 3 Serum Level before and after NB-UVB

Background: Psoriasis is a chronic, non-contagious skin disease characterized by red, inflamed cutaneous lesions covered with silvery-white scale. Both genetic and environmental factors are important in the etiology of the disease. The role of Toll like receptor 2 and vitamin D3 in the pathogenesis of psoriasis needs to be clarified. Objective: The aim of this research is to estimate the level of Toll-like receptor 2 gene expression in skin tissue of psoriasis patients and Vitamin D3 in serum of psoriasis patients and compare the results to healthy control. We also used narrow band-UVB-311 as a treatment and evaluated the same parameters in psoriasis patients before and after treatment. Patients and Methods: Fifteen patients of psoriasis and 15 age and sex matched healthy controls were enrolled in the study. TLR2 gene expression and Vitamin D3 serum levels were estimated and compared to healthy controls. Also these parameters were estimated after 36 sessions of NB-UVB. Resullts: There was statistically significant increase in the levels of TLR2 in psoriatic patients skin tissue compared to control (p<0.001). There was statistically significant decrease in the level of Vitamin D3 in psoriasis patients serum compared to control. After using NBUVB-311 as treatment, the level of TLR2 gene expression was significantly decreased (p<0.001) and the level of Vitamin D3 was significantly increased (p<0.001) in psoriasis patients. Conclusion: These results provide some evidence regarding the role of Toll-like receptor 2 and Vitamin D3 in psoriasis and effect of NB-UVB as a modality of treatment.
ON-SITE ASSESSMENT OF CURING EFFICIENCY BY MEANS OF ELECTRICAL RESISTIVITY MEASUREMENTS

The strong dependence of concrete electrical resistivity with the saturation degree of the concrete provides a practical tool to assess the drying behaviour of concrete by means of electrical measurements and thus, this technique may be used to monitor curing efficiency. As concrete resistivity is also influenced by other factors, such as cement type, w/c, type and content of mineral admixtures, it is required to uncouple their influence to accurately assess the drying behaviour through the use of a new parameter defined as “relative resistivity”, which has been presented in earlier works. This papers analyses the suitability of standard Wenner probes, with an electrode spacing of 50 mm, to detect early drying of the exposed concrete, because the current lines can reach deeper and wetter layers. Different concretes, in the range 20 to 65 MPa, have been exposed to drying conditions at early ages and the respective drying behaviours were characterised by multiple techniques, such as mass loss and electrical resistivity by Wenner technique using different electrode spacing. From the results, it is clearly shown that a closer electrode spacing is much more sensitive to identify the drying behaviour of the cover concrete, thus providing a practical tool to on site assessment of curing efficiency. Complementary aspects such as the variability of the measures and the need for a shape and size factor definition have been also dealt with.
Common Issues of Virtual Reality in NeuroRehabilitation Man

Use of virtual reality (VR) has been developing rapidly in the rehabilitation field. The efficacy and efficiency of VR application in either an immersive or a non-immersive type, has been demonstrated for different client groups during the last few decades. This book chapter provides a review of “what, how and why” of virtual reality application for neurorehabilitation, with a focus on cognitive rehabilitation. Examples of technology transfer to VR-assessment (such as retrospective and prospective memory assessment) and intervention for persons with special needs (for examples, everyday memory, community living skills and vocational training skills) will be highlighted. The client groups include persons with stroke, traumatic brain injury, schizophrenia, older adults with mild cognitive impairment and dementia. Ecological validity of VR-test will be discussed in terms of transfer ratio from training to real-life task. Hints in better designing, structuring the content in virtual environment (VE) for navigation, interaction, presence and immersion functions will be outlined. New development including tele-VR rehabilitation, artificial intelligence (AI) application in cognitive rehabilitation in neurological patients and vocational rehabilitation for schizophrenic trainees will be introduced.
Design and Implementation of Low Transition LFSR for Efficient BIST Architectures

In this paper we present a new low transition LFSR for efficient BIST architecture that produce the output for many clock cycles at once. In this paper, we introduce a novel architecture to perform high speed multiplication using ancient Vedic maths techniques. A new high speed approach utilizing 7:2 compressors for addition has been incorporated in the same. The compressor based multiplier is introduced in this paper, is two times faster than the popular methods. This proposed multiplier shows the reduction in power consumption and area. The proposed multiplier has shown the static, dynamic and total power consumption during the testing operation up-to 46.15%, 23.58% and 64.51% respectively for the Quartus II 9.1. KeywordsVedic multiplier; 7:2 Compressor; Urdhva Triyagbhyam; Built-In Self-Test; LFSR technique; low-power pattern generation.
Geography of Institutional Choice : Presidential and Parliamentary Systems

The relationship between political system type and democracy has been the subject to one of the most heated debates in comparative politics in the last decade. This paper establishes that this strand of research ignores the geographical clustering of presidential and parliamentary systems and argues that the relationship between system type and democracy may be spurious. When controlled for spatial correlation, income level, population size, Spanish colonial legacy, being post-communist or a sub-Saharan African country remain significant associates of political system type. Through case studies, the paper shows that elite bargaining and uncertainty are critical in the choice of institutions and that common historical trajectories leading to similar elite bargaining and uncertainty positions account for the geographical clustering. Ebru Erdem Nov 29, 2001 Draft
Layer-on-layer Assembly of Macroscopic 2 D and 3 D Carbon Nanomaterial Architectures

There are major shortcomings in the assembly of carbon nanomaterials into higher order structures. Twoand threedimensional structures are required for many desirable applications of these materials. Present methods for 2D assemblies include challenges with regards to scalability, suitability for a large variety of substrates, mechanical stability, and/or biocompatibility. Very few strategies exist for fabrication of three-dimensional structures. We developed an easily scalable spray coating fabrication process for in situ chemical crosslinking of carbon nanomaterials to develop more robust, flexible, and biocompatible coatings/films. Furthermore, the process has been adapted to provide a layer-on-layer deposition of nanomaterials into three-dimensional structures. This work enables the fabrication of more robust carbon nanotube and graphene coatings by a facile, scalable, and flexible method. It also elucidates a potential enabling technology for all-carbon nanomaterial 3D printing.
Analysis of Three IoT Wireless Sensors for Environmental Monitoring

This paper presents the functional design and integration of a complete WSN platform that can be used to remote environmental monitoring and target for IoT applications. The system of physical object devices, vehicles, buildings and other items embedded with sensors, electronics, software and network connectivity that enables these objects to collect and exchange data, this is called IoT. IoT is expected to generate large amounts of data from diverse locations. IoT is one of the platforms for today’s smart city and smart energy management systems. Wireless Sensor Network (WSN) is used to monitor environmental conditions such as sound, pressure, temperature etc. The application requirements are long lifetime, low cost, fast deployment, low maintenance; high number of sensors and high quality of service are considered in the specification. Low-effort platform reuse is also considered for the specifications and design levels for a wide array of related monitoring applications.
Building Pathways for Intercultural Learning : Globally Engaging First Generation Business Students

This paper presents the argument that experiential learning frameworks, based on constructivism, may be useful to determine how best to meet the call for intercultural competency development by creating sequenced and experientially based study abroad programming. More specifically, the case is made for the use of learning styles and motivation engagement concepts as a basis for intentionally designed short and intermediate term study abroad serving different learning goals from traditional study abroad and which dismantle barriers that inhibit participation rates in traditional study abroad opportunities.
Sovereign Debt Restructuring and Growth

This paper studies the relation between sovereign debt restructurings with external private creditors and growth during the period 1970–2010. We find that, while growth generally declines in the aftermath of a sovereign debt restructuring, agreements that allow countries to exit a default spell (final restructurings) are associated with improving growth. The difference can be significant. In general, three years after restructuring, growth is about 5% lower compared to countries that did not face restructuring over the same period. The exception is for final restructurings, which result in positive growth in the years immediately after the restructuring. Final restructurings are associated with larger debt reliefs, and we show that post-restructuring growth is higher in countries that exit final restructurings with relatively low debt levels.
GreedyFlow : Distributed Greedy Packet Routing between Landmarks in DTNs

Delay Tolerant Networks (DTNs) have attracted much research interest recently due to its adaptability in areas without infrastructures. In such scenarios, moving data from one place (landmark) to another place (landmark) is essential for data communication between different areas. However, current DTN routing algorithms either fail to fully utilize node mobility or have additional requirements that cannot be satisfied easily in DTNs. Therefore, in this paper, we propose a distributed greedy routing algorithm, namely GreedyFlow, for efficient packet routing between landmarks in DTNs. GreedyFlow builds a local traffic map and a global landmark map on each node. The local traffic map indicates the node’s knowledge about the amount of traffic (node transition) between landmarks in the area where it primarily visits. The global landmark map shows the distribution of landmarks in the system and is built offline. In packet routing, the global landmark map shows the general packet forwarding direction, while the local traffic map helps determine the next-hop landmark on the fastest path in the forwarding direction. As a result, packets are greedily forwarded toward their destination landmarks. We also propose advanced components to enhance the consistency of local traffic maps and exploit node-based forwarding, both of which help improve the packet routing efficiency. Extensive real trace driven experiments demonstrate the high efficiency of GreedyFlow.
Analysis of Development Productivity in Information System Adaptive and Perfective Maintenance

—This paper presents a development productivity model for Information System (IS) adaptive/perfective maintenance process. The modelling approach is from economic perspective. The productivity model considers the economic value of the maintenance activity, pre-committed fixed cost and variable cost consumed in adaptive/perfective maintenance. Factors that influence the productivity are analysed using simulation. The simulation provides a tool for IS project managers to tune the project parameters to obtain the optimal productivity in adaptive/perfective maintenance.
Fuzzy SART Clustering for 3 D Reconstruction from Irregular LIDAR Data

– Fuzzy Simplified Adaptive Resonance Theory (Fuzzy SART) is proposed for clustering the normal vectors of coplanar triangles in a Triangulated Irregular Network (TIN) derived from raw, irregularly spaced LIDAR data. The raw LIDAR data is triangulated using a greedy insertion triangulation algorithm. The algorithm is modified to implement a proposed noise filtering technique which improves Fuzzy SART’s coplanar clustering performance. Furthermore, several proposed preprocessing techniques, specifically scaling and translating the LIDAR data, are also implemented and were found to improve clustering accuracy. Then, a proposed multiple or planar regression algorithm further refines the coplanar grouping by removing outliers and merging multiple clusters representing singular planes. Finally, further refinement is achieved by calculating the intersection of the best fit roof planes and moving nearby points close to that intersection to exist at the intersection, resulting in straight roof ridges.
MX STRUCTURAL METADATA AS MIR TOOLS

In this paper two main topics are covered: a new model for melodic fragments or indexes and its embedding in MX, the new XML-based format currently undergoing the IEEE standardization process, in order to take advantage of its structural layer in a MIR-oriented perspective. Our goal is to show how music information retrieval methods can be improved by the use of particular melodic invariants coming from graph theoretic tools applied to melodies in order to catch more musical transformations than other methods as, for example, permutations of subfragments. This approach to the melodic similarity problem leads to associate a musical graph to each melodic segment in order to extract MIR-useful invariant quantities.
2 First-Order Correction of Conditional Losses 2 . 1 First-order Gaussian correction

This article describes a new numerical method, based on Stein’s method and zero bias transformation, to compute CDO tranche prices. We propose first order correction terms for both Gauss and Poisson approximations and the approximation errors are discussed. We then combine the two approximations to price CDOs tranches in the conditionally independent framework using a realistic local correlation structure. Numerical tests show that the method provides robust results with a very low computational burden. Acknowledgement: this work is partially supported by La Fondation du Risque. We are also grateful to the referees for very valuable comments and suggestions.
1 MESOSCALE STRUCTURES WITHIN THE AURORAL BULGE

We present ground-based optical, riometer, and magnetometer, Polar UVI and GOES magnetic field observations of a substorm on 24 November, 1997. This event involved a clear optical onset followed by poleward motion of auroras, i.e. an expanding auroral bulge. During the first minutes of the expansion phase, there were three distinct meso-scale (10–1000km) structures embedded in the bulge: a series of equatorward moving auroral arcs, a well-defined spiral pair, and north-south directed auroras. The spirals occurred several minutes after the onset, and indicate either a field-aligned current or a ballooningtype instability. The north-south aligned auroral forms occurred roughly 10min after the onset implying bursty bulk flow type flows in the central plasma sheet. The riometer data suggest high energy electron precipitation in the vicinity of the the poleward moving edge of the auroral bulge, starting at the onset and continuing until the north-south structure. In this paper, we examine this evolving auroral morphology.
Proteolytic Enzymes as Biological Markers for Tumor Diseases : Review

Nowadays, about one thousand proteolytic enzymes are isolated and purified from different organisms. According to the catalytic mechanism, the structure of the active center and their tertiary structure, proteases are divided into four main groups – aspartic peptidases, metallopeptidases, cysteine and serine peptidases. Most of them not only perform various physiological functions but are also involved in pathogenic mechanisms of different diseases. The aim of the present mini-review is to outline the main groups of proteases and individual enzymes typically used as biomarkers for tumor diseases as well as to designate certain enzymes that are promising for future application in oncology.
COMPARATIVE STUDY OF DIFFERENT BACKOFF ALGORITHMS IN IEEE 802 . 11 DCF MAC PROTOCOL

The IEEE 802.11 Medium access control layer is responsible for a structured channel access scheme. The medium access control (MAC) protocol is the main element that determines the system performance in wireless local area networks. Distributed coordination function (DCF) is the fundamental MAC technique of the IEEE 802.11 based WLAN standard. In IEEE 802.11 WLAN, network nodes experiencing collisions on the shared channel need to backoff for a random period of time, which is uniformly selected from the Contention Window (CW). This contention window is dynamically controlled by the Backoff algorithm. Backoff algorithm has to take an important and crucial decision to correctly predict the precious waiting time for the station before accessing the medium. Hence deigning an effective and efficient Backoff algorithm is required for Wireless Networks. This paper discusses, simulates and analyzes the various Backoff Algorithms and compares the results obtained using NS2 simulator.
Artificial neural network for bubbles pattern recognition on the images

Two-phase bubble flows have been used in many technological and energy processes as processing oil, chemical and nuclear reactors. This explains large interest to experimental and numerical studies of such flows last several decades. Exploiting of optical diagnostics for analysis of the bubble flows allows researchers obtaining of instantaneous velocity fields and gaseous phase distribution with the high spatial resolution non-intrusively. Behavior of light rays exhibits an intricate manner when they cross interphase boundaries of gaseous bubbles hence the identification of the bubbles images is a complicated problem. This work presents a method of bubbles images identification based on a modern technology of deep learning called convolutional neural networks (CNN). Neural networks are able to determine overlapping, blurred, and non-spherical bubble images. They can increase accuracy of the bubble image recognition, reduce the number of outliers, lower data processing time, and significantly decrease the number of settings for the identification in comparison with standard recognition methods developed before. In addition, usage of GPUs speeds up the learning process of CNN owning to the modern adaptive subgradient optimization techniques.
Experiments on aeronautical satellite communications using ETS-V satellite : Mobile satellite communications experiments using-ETS-V

The world's first aeronautical satellite communication experiments, conducted at L-band frequencies using a commercial aircraft, are described. An airborne antenna with electronically steerable beam and communication equipment was installed in a B-747F freighter flying over transoceanic flight routes. The satellite used in these experiments is the Engineering Test Satellite-Five (ETS-V). During the test period, various experiments, such as antenna pattern measurements, transmission performances, and voice quality evaluation were conducted. As the airborne antenna is the key component for the aeronautical satellite communication system, emphasis has been placed on antenna characteristics. Its performance is found to be closely related to the fading characteristics in low-elevation areas and to transmission error performance. >
Land-Use Changes , Mangrove Destruction , and Vulnerability in Maduganga Lagoon

I Human use of land is one of the most su 1997). Global cropland and pastures have increased significantly in the last three centuries, mostly at the expense of forests, natural grassland, steppes, and savannas. Since the 20 century the pace of land-use and land-cover changes (LUCC) has risen even further and is unprecedented in human history (Lambin et al., 2003, Ramankutty et al., 2005). Most scenarios predict a further increase in agricultural land of up to 40% until 2100 (Alcamo and Busch, 2005). LUCC may alter biogeochemical cycles (e.g. through the excessive input of nitrogen), have a direct impact on biodiversity and soil degradation, change water and radiation budgets and contribute to regional climatic changes as well as to global warming (Verburg et al., 2003; Lambin et al., 2001). Environmental degradation may also increase the vulnerability of people to all kinds of biophysical, economic or socio-political perturbations (Lambin et al., 2003; Renaud, 2006).