Miracle-dz/UniFAR-FTUs huggingface dataset:
PRECISION OF VISUAL LOCALIZATION USING DYNAMIC GROUND CONTROL POINTS

Abstract. Localization is one of the first steps in navigation. Especially due to the rapid development in automated driving, a precise and reliable localization becomes essential. In this paper, we report an investigation of the usage of dynamic ground control points (GCP) in visual localization in an automotive environment. Instead of having fixed positions, dynamic GCPs move together with the camera. As a measure of quality, we employ the precision of the bundle adjustment results. In our experiments, we simulate and investigate different realistic traffic scenarios. After investigating the role of tie points, we compare an approach using dynamic GCPs to an approach with static GCPs to answer the question how a comparable precision can be reached for visual localization. We show, that in our scenario, where two dynamic GCPs move together with a camera, similar results are indeed obtained to using a number of static GCPs distributed over the whole trajectory. In another experiment, we take a closer look at sliding window bundle adjustments. Sliding windows make it possible to work with an arbitrarily large number of images and to still obtain near real-time results. We investigate this approach in combination with dynamic GCPs and vary the no. of images per window.
Use of high-resolution unmanned aerial systems imagery and machine learning to evaluate grain sorghum tolerance to mesotrione

Abstract. Manual evaluation of crop injury to herbicides is time-consuming. Unmanned aerial systems (UAS) and high-resolution multispectral sensors and machine learning classification techniques have the potential to save time and improve precision in the evaluation of herbicide injury in crops, including grain sorghum (Sorghum bicolor L. Moench). The objectives of our research are to (1) evaluate three supervised classification algorithms [support vector machine (SVM), maximum likelihood, and random forest] for categorizing high-resolution UAS imagery to aid in data extraction and (2) evaluate the use of vegetative indices (VIs) collected from UAS imagery as an alternative to traditional methods of visible herbicide injury assessment in mesotrione-tolerant grain sorghum breeding trials. An experiment was conducted in a randomized complete block design using a factorial treatment arrangement of three genotypes by four mesotrione doses. Herbicide injury was rated visually on a scale of 0 (no injury) to 100 (complete plant mortality). The UAS flights were flown at 9, 15, 21, 27, and 35 days after treatment. Results show the SVM algorithm to be the most consistently accurate, and high correlations (r = − 0.83 to −0.94; p < 0.0001) were observed between the normalized difference VI and ground-measured herbicide injury. Therefore, we conclude that VIs collected with UAS coupled with machine learning image classification has the potential to be an effective method of evaluating mesotrione injury in grain sorghum.
Moored Array for African-Asian-Australian Monsoon Analysis and Prediction *

The Indian Ocean is unique among the three tropical ocean basins in that it is blocked at 25°N by the Asian landmass. Seasonal heating and cooling of the land sets the stage for dramatic monsoon wind reversals and intense seasonal rains over the Indian subcontinent, Southeast Asia, East Africa, and Australia. The Asian landmass also blocks the ocean to the north, so that currents cannot carry heat from the tropics to higher northern latitudes as in the other oceans. Ocean-atmosphere interactions in the region are highly dynamic, involving seasonal current reversals associated with monsoon wind forcing and significant exchanges of heat across the air-sea interface. The Indian Ocean also receives heat from the Pacific via the Indonesian Throughflow (Gordon 2001) while exporting heat to the Atlantic via the Aguhlas Current system (de Ruijter et al. 1999). Monsoon rains occur each year, supporting agricultural production that provides food for a third of the world's population. These rains are irregular, however, leading to years of drought or flood that have significant socioeconomic consequences (Webster et al. 1999). The failure of Indian summer monsoon rains in 2002 (Waple and Larimore 2003) and excessive rains in equatorial East Africa in late 2006 (Arguez 2007) are recent examples of •
Therapeutic management of chronic inflammatory rheumatic diseases in times of pandemic COVID 19

Conoravirus 2019 or Covid-19 disease (acronym for COronaVirus Infectious Disease 2019) is an emerging highly contagious infection caused by the coronavirus strain SARS-CoV-2. In March 2020 it has been declared a pandemic by the World Health Organization (WHO). The rheumatologist is therefore faced with a challenge: an optimal management of COVID patients who are immunosuppressed not only by the disease but also by the immunosuppressive treatments they take. In fact, some of these drugs seem , oddly, to have antagonist effects on viral response and therefore are investigated in COVID treatment. Severe COVID-19 originates from a cytokine storm caused by increased levels of a number of cytokines and chemokines resulting in a multiorgan failure. The management of this cytokine storm is one of the major challenges regarding COVID-19 infection. Several pathways are investigated including drugs known to be efficient on rheumatology field (especially NSAIDs, corticosteroids, Disease Modifying Anti Rheumatic diseases (DMARDs): biological or synthetic ones such as methotrexate, salazopyrine, leflunomide and Hydroxychloroquine). Given these facts, this review aimed to summarize the existing data that may support the therapeuting decision making of rheumatologists in this pandemic context. Glucocorticoids should be used at its lowest necessary dose regardless of exposure or infection status if needed to controlee underlying disease. They should never be stopped precipitously . Stable patients with no COVID 19 infection or exposure should continue their treatment either NSAIDs or immunosuppressants (CsDMARDs, TsDMARDs or bDMARDs) with no modification or dose reduction in case of life threatening organ lesion. Anti malarial drugs is to not discontinue them, considering the antiviral efficacy and the immunomodulatory rather than immunosuppressive effect. The anti Il 6 is also not to be stopped given their action on the inflammatory reaction caused by COVID19. In case of confirmed COVID 19 infection it is recommended to temporarily stop other immunosuppressive treatments. That guidance does not replace clinical judgment of the rheumatologist based on clinical severity of the infection or the ARD. Mostly guideline panel recommends underlying general preventive measures, e.g., social distancing and hand hygiene, reducing exposure of patients with minimizing health encounters.
IoT-based Secure and Energy Efficient scheme for E-health applications

Background/objectives: This study presents a secure and energy-efficient scheme of patient’s data transmission fromwearable IoT sensors (WIS) to base station (BS). IoT sensors are widely used in the healthcare domain for realtime data collection and transmission. However, these sensors are resourceconstrained in terms of computational power and storage due to which chances of security breaches and threats increase. Moreover, with time the energy level of IoT sensors also degrade that sometimes leads towards loss of sensitive patient data. Purpose: The purpose of this study is to provide secure data transmission between wearable sensors and base stations and increasing energy efficiency of resource-constrained wearable IoT sensors.Method: The proposed scheme was tested by creating a mathematical model and then creating a simulation setup using the Cooja Contiki simulator. Findings: The results show that the proposed scheme provides secure and energy-efficient data transmission from WISs to BS as compared to the existing approaches. Further, the proposed scheme addresses some key issues including availability, reliability, scalability, and limited patient mobility. Novelty: Our research presented a unique approach for e-health applications using the IoT, where we considered the lightweight and secure scheme providing multiple group node
INFLUENCE OF FLY ASH AND SLAGS OF BOILER WITH CIRCULATING FLUIDIZED BED ON PROPERTIES OF CONCRETE

The properties of fly ash and slag of boilers with circulating fluidized bed are under consideration. In the Donetsk region several new generations of boilers are operating, permitting to burn the poor fossil fuels, including coal tailings. The ash and slag produced in this case are having somewhat different properties in contrast to the conventional waste TPP. In the study of fly ash and slag’s properties, the up-to-date methods are applied, based on X-ray phase (XRD), DT and spectral analyses. The question of the allocation of a large area of land for the storage of waste at thermal power plants. It was found that in windy weather wastes soar into the air, creating a cloud of dust and chemicals dissolved in rainwater and contaminate groundwater The aim of the present study is to identify the influence of fly ash on the strength properties of heavy concrete and on its resistance to water saturation and drying. The research strength of concrete based on mathematical experiment planning
Polygon Triangulation

The Polygon Triangulation Problem: Triangulation is the general problem of subdividing a spatial domain into simplices, which in the plane means triangles. We will focus in this lecture on triangulating a simple polygon (see Fig. 1). Formal definitions will be given later. (We will assume that the polygon has no holes, but the algorithm that we will present can be generalized to handle such polygons.) Such a subdivision is not necessarily unique, and there may be other criteria to be optimized in computing the triangulation.
Nava: A Persian Traditional Music Database for the Dastgah and Instrument Recognition Tasks

: Extensive research has been conducted in the field of music signal processing which targeted context-based music information retrieval. Unfortunately, research on the computer-based processing of the traditional Persian music is rare, which is due to lack of standard databases. In this paper, a database, named Nava, is introduced for two basic tasks of the traditional Persian music field, Dastgah classification and instrument recognition. In terms of instrument, Dastgah and artist, Nava has enough comprehensiveness and variety. It contains the sound of five common traditional instruments played by 40 artists in seven Dastgahs. In order to address the two mentioned basic tasks, a system is proposed which extracts a sequence of Mel frequency cepstral coefficients (MFCC) feature vectors from input music signal and then converts it to a fixed-length feature vector using i-vector technique. In the classification stage, the extracted i-vector is fed into a support vector machine classifier. The best obtained accuracy on the Nava database for the Dastgah classification and instrument recognition are about 34% and 98% respectively, which indicates the difficulty of the former in comparison with the latter.
Gliricidia Agroforestry Technology Adoption Potential in Selected Dryland Areas of Dodoma Region, Tanzania

Declining soil fertility is one of the major problems facing producers of field crops in most dryland areas of Sub-Saharan Africa. In response to the declining soil fertility, extensive participatory research has been undertaken by the World Agroforestry (ICRAF) and smallholder farmers in Dodoma region, Tanzania. The research has, amongst others, led to the development of Gliricidia agroforestry technology. The positive impact of Gliricidia intercropping on crop yields has been established. However, information on farmers’ willingness and ability to adopt the Gliricidia agroforestry technology on their farms is limited. This study predicts the adoption of Gliricidia agroforestry and conventional mineral fertilizer use technology. Focus Group Discussions (FGDs) were conducted with groups of farmers, purposively selected based on five sets of criteria: (i) at least 2 years of experience in either trying or using Gliricidia agroforestry technology, (ii) at least 1 year of experience in either trying or using the mineral fertilizer technology (iii) at least 10 years of living in the study villages, (iv) the age of 18 years and above, and (v) sex. The Adoption and Diffusion Outcome Prediction Tool (ADOPT) was used to predict the peak adoption levels and the respective time in years. A sensitivity analysis was conducted to assess the effect of change in adoption variables on predicted peak adoption levels and time to peak adoption. The results revealed variations in peak adoption levels with Gliricidia agroforestry technology exhibiting the highest peak of 67.6% in 12 years, and that the most influential variable to the peak adoption is the upfront cost of investing in Gliricidia agroforestry and fertilizer technologies. However, in Gliricidia agroforestry technology most production costs are incurred in the first year of project establishment but impact the long term biophysical and economic benefits. Moreover, farmers practicing agroforestry technology accrue environmental benefits, such as soil erosion control. Based on the results, it is plausible to argue that Gliricidia agroforestry technology has a high adoption potential and its adoption is influenced by investment costs. We recommend two actions to attract smallholder farmers investing in agroforestry technologies. First, enhancing farmers’ access to inputs at affordable prices. Second, raising farmers’ awareness of the long-term environmental benefits of Gliricidia agroforestry technology.
Almost Surely Stable Deep Dynamics

We introduce a method for learning provably stable deep neural network based dynamic models from observed data. Specifically, we consider discrete-time stochastic dynamic models, as they are of particular interest in practical applications such as estimation and control. However, these aspects exacerbate the challenge of guaranteeing stability. Our method works by embedding a Lyapunov neural network into the dynamic model, thereby inherently satisfying the stability criterion. To this end, we propose two approaches and apply them in both the deterministic and stochastic settings: one exploits convexity of the Lyapunov function, while the other enforces stability through an implicit output layer. We demonstrate the utility of each approach through numerical examples.
Fabrication and electrical characterization of Organic Field-Effect Transistor based on CSA doped PANi-Ta2O5 nanocomposite

Top-contact, bottom-gate o rganic field-effect transistors (OFETs) based on Polyaniline (PANi)-Tantalum Pentoxide (Ta 2 O 5 ) nanocomposite doped with Camphor Sulphonic Acid (CSA) as the active semiconductor layer and Poly Methyl Methacrylate (PMMA) as the gate dielectric were investigated. Gold was thermally evaporated for the top source and drain contacts of 80-90 nm thickness with a conducting channel of 1 mm length and 1cm width. A relatively good charge carrier mobility of 0.12 cm 2 /V-s was achieved. This may be ascribed to the highly crystalline nature of the nanocomposite, the diminished contact resistance due to the long channel and the symbiosis developed between the organic semiconductor and the polymer dielectric. The smaller source-to-drain current and high saturation drain voltage may be accounted for the long channel effect. The device exhibited a threshold voltage of -12.89 V, a moderate current on/off ratio of ~10 3 and a subthreshold swing of 9.3 V/dec. The agglomerated globular morphology of the PANi nanocomposite and the high carrier mobility can immensely contribute towards using the OFET device for room-temperature based application, particularly in the gas sensing field.
Comparative evaluation of cyclic fatigue fracture resistance of newer Ni Ti rotary files: An in vitro study

The single-file technique has been developed for shaping the vast majority of canals, regardless of their length, diameter, or curvature. Aim: This study compared the cyclic fatigue fracture resistance in canal after instrumentation with single file system and multiple file system i.e- One Curve, F360 (single file systems) and Neoendo (multiple rotary file). Method: Ten rotary instruments of each type and totalling 30 instruments of 25 mm in length were divided into 3 groups. Group 1: Neoendo, Group 2:F360, Group 3: One Curve. The dental hand piece was mounted on a mobile device that allowed for the simple placement of each instrument inside the artificial canal. To prevent the instruments from slipping out and to allow for observation of the instruments, the artificial canals were covered with glass. The time was then converted into number of cycles to failure. NCF = Number of rotations per minute x Time to fracture.Result: The mean values of time in seconds to fracture in F360 were lowest followed by Neoendo and highest was found in One Curve group.
Evaluation of the Hydraulic Performance of a Rear-Parapet Vertical Breakwater under Regular Waves through Hydraulic Experiments

Climate change has resulted in increased intensity and frequency of typhoons and storm surges. Accordingly, attention has been paid to securing the breakwater’s stability to protect the safety of the port. Herein, hydraulic model experiments were conducted to evaluate the hydraulic performance of a vertical breakwater having a rear parapet. For comparison, cases in which the parapet was placed on the seaside, the harborside, and at the center of the breakwater were considered. Regular waves were used for convenient performance analysis. Five wave gauges and nine pressure transducers were installed to secure physical data for hydraulic performance evaluation. Results showed that a rear parapet can reduce the maximum wave force acting on the breakwater. Even though impulsive pressure was generated, it did not affect the stability of the breakwater owing to the phase difference between the maximum wave pressures acting on the caisson and parapet. By decreasing the maximum wave force, the required self-weight that satisfies the safety factor of 1.2 was reduced by up to 82.7%; the maximum bearing pressure was reduced by up to 47.6% compared with that of the parapet located on the seaside. Thus, the rear parapet was found to be more suitable for actual applications.
Elective course recommendation model for higher education program

Educational data mining (EDM) applies data mining techniques to resolve educational managing problems. This paper proposes a general process of EDM for elective course recommendations based on student grades. Furthermore, proper and inadequate reasons for applying conventional measurements in the course recommendation domain are studied and complemented with new proposed quality measurements. Several techniques were studied to establish a model for estimating the grades in elective courses. The experiments suggested that SVD classifier using course information gave the best results. The overall results indicate that the proposed model is able to provide personalized recommendations for individual students based on the student’s abilities.
Sentiment Analysis with Supervised Learning Techniques: A Survey

Objectives: This study aims two main goals; one is to provide complete notions relevant to sentiment analysis by SA mechanisms, its categorization, and its techniques. The second goal is to make a comprehensive study of supervised learning techniques used in SA classification to summarize the different works conducted in this area and track the recent developments. Methods: To achieve the first goal, several important survey studies, including modern and relevant works presented would be analyzed for full concepts around SA. As for the second objective of the study, the most important reports would be investigated, analyzed, and compared in the use of supervised learning techniques in SA from the previous to the recent researches till 2019. Findings: This study also made a comprehensive research of the supervised machine learning classifiers used in SA, its recent techniques and enhancement methods and the suggestion future works. There are still some open challenges in this area such as mining the complex reviews and implicit aspect identification. The sentiment language is also a challenge; thus, addressing each language according to its attributes is a difficult task and so the sentiment domain issue. Application/improvements: The information provided is used in assessing opinions and analyzing sentiment that could be used by researchers and institutions, and to identify different trends besides recommending the future research directions.
Design and Implementation of a Control Method for GaN-Based Totem-Pole Boost-Type PFC Rectifier in Energy Storage Systems

With the unceasing advancement of wide-bandgap (WBG) semiconductor technology, the minimal reverse-recovery charge Qrr and other more powerful natures of WBG transistors enable totem-pole bridgeless power factor correction to become a dominant solution for energy storage systems (ESS). This paper focuses on the design and implementation of a control structure for a totem-pole boost PFC with newfangled enhancement-mode gallium nitride field-effect transistors (eGaN FETs), not only to simplify the control implementation but also to achieve high power quality and efficiency. The converter is designed to convert a 90–264-VAC input to a 385-VDC output for a 2.6-kW output power. Lastly, to validate the methodology, an experimental prototype is characterized and fabricated. The uttermost efficiency at 230 VAC reaches 99.14%. The lowest total harmonic distortion in the current (ITHD) at high line condition (230 V) attains 1.52% while the power factor gains 0.9985.
GOVERNING THE INFORMAL FOOD SECTOR IN CITIES OF THE GLOBAL SOUTH

The role of the informal food sector in the urban food system cannot be appreciated or understood without the compilation and analysis of systematic and representative data on the activities of informal enterprises across a city and along food supply chains outside it. At present, there are significant gaps in the knowledge base about the character, operation, and roles of the informal food sector; a pre-requisite for sound and supportive governance. This paper presents evidence on the relative importance of the informal food sector and discusses various methodologies for improving the knowledge base. It identifies the challenges and opportunities facing individuals and enterprises operating in the sector as well as the challenges posed by informality more generally. The paper also examines the issue of informal sector governance, including policy prescriptions that have followed from different understandings of informality, and discusses various existing policies and possible interventions. We argue that maximizing the potential benefits of the informal food sector requires well designed institutional and policy frameworks, an appropriate enabling environment, and effective policies and interventions. The final section identifies priority areas for future research.