Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Underwater Visual SLAM Fusing Acoustic Sensing

In this paper, we propose an approach for robust visual Simultaneous Localisation and Mapping (SLAM) in underwater environments leveraging acoustic, inertial and altimeter/depth sensors. Underwater visual SLAM is challenging due to factors including poor visibility caused by suspended particles in water, a lack of light and insufficient texture in the scene. Because of this, many state-of-the-art approaches rely on acoustic sensing instead of vision for underwater navigation.Building on the sparse visual SLAM system ORB-SLAM2, this paper proposes to improve the robustness of camera pose estimation in underwater environments by leveraging acoustic odometry, which derives a drifting estimate of the 6-DoF robot pose from fusion of a Doppler Velocity Log (DVL), a gyroscope and an altimeter or depth sensor. Acoustic odometry estimates are used as motion priors and we formulate pose residuals that are integrated within the camera pose tracking, local and global bundle adjustment procedures of ORB-SLAM2.The original design of ORB-SLAM2 supports a single map and it enters relocalisation when tracking is lost. This is a significant problem for scenarios where a robot does a continuous scanning motion without returning to a previously visited location. One of our main contributions is to enable the system to create a new map whenever it encounters a new scene where visual odometry can work. This new map is connected with its predecessor in a common graph using estimates from the proposed acoustic odometry. Experimental results on two underwater vehicles demonstrate the increased robustness of our approach compared to baseline ORB-SLAM2 in both controlled, uncontrolled and field environments.
On Performance Enhancement of MANET using Multi Criteria Algorithm

- Objectives: The objective is to design and develop a routing protocol that can be implemented on MANET to improve the performance and increase the throughput of network. Method: Minimizing the energy utilization of network hub is a standout amongst the most essential issues for routing in remote sensor organizes in perspective of the battery diminution in each sensor. As a result of the dynamic method for the Mobile Ad-hoc Network (MANET), routing in MANET gets the opportunity to test especially when on request multi-path routing traditions addresses certain issues, for instance, message overheads, link failures and hub's high versatility and certain QoS necessities (like high data parcel conveyance proportion, low end to end delay, low coordinating overhead, and low energy consumption)are to be satisfied. In spite of the fact that Energy utilization is the most difficult issue in routing protocol outline and various routing protocols have been proposed meaning to settle this issue. Findings: In this paper, we propose an upgraded rendition of multi-path routing project for mobile ad-hoc network, in view of the Ant Colony Optimization (ACO) a meta heuristic calculation, in which ants approach from source to destination by means of number of paths and considering pheromone, energy, mobility and distance –driven parameters. These methodologies attempt to delineate solution ability of swarms to scientific and designing issues. The presented routing protocol is highly versatile, productive and adaptable. The proposed technique depicts better results of residual energy, throughput, pheromone value and average delay.
Quadric Tracing: A Geometric Method for Accelerated Sphere Tracing of Implicit Surfaces ∗

Sphere tracing is a common raytracing technique used for rendering implicit surfaces deﬁned by a signed distance function (SDF). However, these distance functions are often expensive to compute, prohibiting several real-time applications despite recent eﬀorts to accelerate them. This paper presents quadric tracing, a method to precompute an augmented distance ﬁeld that signiﬁcantly accelerates rendering. This novel method supports two conﬁg-urations: (i) accelerating raytracing without losing precision, so the original SDF is still needed; (ii) entirely replacing the SDF and tracing an interpolated surface. Quadric tracing can oﬀer 20% to 100% speedup in rendering static scenes and thereby amortizes the slowdown caused by the complexity of the geometry.
A real-time intrusion detection system based on OC-SVM for containerized applications

A Digital Data Marketplace (DDM) is a digital infrastructure to facilitate policy-governed data sharing in a secure and trustworthy manner with container-based virtualization technologies. An intrusion detection systems (IDS) is essential to enforce the policies. We propose a real-time intrusion detection system that monitors and analyzes the Linux-kernel system calls of a running container. We adopt the One-Class Support Vector Machine (OC-SVM) to detect anomalies. The training data of the OC-SVM algorithm is collected and sanitized in a secure environment. We evaluate the detection capability of our proposed system against modern attacks, e.g. Machine Learning (ML) adversarial attacks, with a customized attack dataset. In addition, we investigate the influence of various feature extraction methods, kernel functions and segmentation length with four metrics. Our experimental results show that we can achieve a low FPR, with a worst case of 0.12, and a TPR of 1 for most attacks, when we adopt the term-frequency feature extraction method and we choose segmentation length of 30000. Furthermore, the optimal kernel functions depend on the concrete application being examined.
Features of the Organisation of Rooting Cuttings of Decorative Woody Plants Under Artificial Lighting with Led Equipment

Obtaining a technology for rooting cuttings and standard seedlings of decorative woody plants under artificial lighting conditions is relevant in connection with the need to increase the amount of planting material required for green building. Currently, cuttings are carried out mainly in greenhouses during the growing season. The development of technology for rooting cuttings using lamps with different lighting parameters opens up the possibility of creating installations that are effective in various conditions. In the course of the study, organisational and technological measures were taken to modernise the greenhouse and install equipment for growing planting material of decorative plants. In accordance with the plan to study the characteristics of various crops using the technology of dynamic regulation of the spectral composition and temporal characteristics of LED lighting in a greenhouse, an assortment of decorative tree species has been developed. Heated greenhouses are equipped with automatic irrigation hotbeds. Cutting of coniferous, deciduous, fast- and slow-growing species of decorative woody plants (7 species and 3 cultivars in total) was carried out. Rooting was carried out under illumination with batch-type LED installations. The success of rooting is studied when using LEDs of various production, with different spectral composition and varying illumination intensity during year-round cultivation. The findings are necessary not only for the development of a regional technology for the year-round production of rooted cuttings of decorative woody plants, but also for the development of the engineering specifics of lighting equipment.
Factors to enhance the development of inclusive university communities: ideas, beliefs and attitudes of university teachers towards disability

Título: Factores para potenciar el desarrollo de comunidades universitarias inclusivas: ideas, creencias y actitudes del profesorado universitario hacia la discapacidad. Resumen: El éxito de los procesos de inclusión depende de varios factores, entre ellos del nivel de empoderamiento de la comunidad educativa frente al proceso. En este sentido, el rol del docente es un elemento clave, ya que la actitud y las expectativas que muestren ante los alumnos que presentan necesidades educativas especiales, influirán positiva o negativamente en su autoestima, motivación y aprendizaje. En el presente artículo se indagan en las ideas, creencias y actitudes hacia estudiantes con necesidades educativas especiales, de docentes, y se analiza la influencia que las variables género, edad, años de experiencia docente, contacto e información sobre la discapacidad tienen sobre dichas actitudes. En general, se pudo apreciar que las actitudes que presentaban los docentes eran bastante positivas, no obstante mostraban un gran desconocimiento de las experiencias de inclusión de los estudiantes con discapacidad que se llevan a cabo en su universidad, demandando mayor formación e información. Se discuten los resultados, se presentan las limitaciones del estudio, y se ofrecen futuras líneas de investigación. Palabras clave: Actitudes. Creencias. Inclusión. Profesorado. Universidad. Abstract: The success of the processes of inclusion depends on several factors, including the level of empowerment of the educational community in the process where the role of teachers is a key element, because their attitude and expectations of students with special educational needs will influence their self-esteem, motivation and learning. This article investigates the ideas, beliefs and attitudes towards SEN students demonstrated by teachers, and analyses the variables of gender, age, years of teaching experience, contacts and information about disability on these attitudes. Overall, it was observed that teachers’ attitudes were positive; however they showed a lack of knowledge of the experiences of inclusion of students with disabilities at the university and required more training and information. The results are discussed, the limitations of the study are presented, and suggestions for future research are offered.
Characterization of Bioactive Compounds in Fruit and Vegetable Bagasse

The use of agro-industrial residues is presented in food waste. The processing of them is an opportunity for the development of by-products, as well as the aggregation of lost value, and the sustainable use of these residues. The study aimed to characterize the bioactive compounds in grape, carrot, cocoa, and banana skins from the processing of juice, banana chips, and chocolate. The analyzed samples showed good moisture, satisfactory water activity value, with the highest flavonoid content in the grape sample (1.679 mg EQ/g) and the highest phenolic content in the cocoa epicarp sample (1.367 mg EAG/g). In this way, we verified the viability of using food peels in the food industry, enabling the use of waste generated.
Reinforcement Learning in Game Playing

- The single-player variant of Snake is a well-known and fashionable computer game that requires a player to navigate a line-based illustration of a snake through a two-dimensional piece of a grid, while avoiding collisions with the walls of the playing area and the body of the snake itself. The game keeps on getting more challenging as the snake navigates its way to the treats. The score is also increased accordingly. We have used Deep Reinforced Learning (DRL) to achieve AI in game playing. Deep Q-Learning is a particular type of Deep Reinforcement Learning. “ Q-Function ” is learnt by the network, which takes as input the current state of the environment and outputs a vector containing rewards for each possible action. The agent will then decide the action that maximizes the Q function. Based on this action, the environment is updated to another state by the game and a reward is assigned. needs a large number of action state pairs, so we could introduce Neural Network to store Q-factor of each state.
A Review of the Use Cases and Possible Technologies for 5G and Beyond Communications

5G communication system is rapidly taking shape and for many organizations, including administrations, it is important to be aware of developments in this regard. At this stage, it is essential to know about 5G use cases and possible key technologies. This paper describes several anticipated 5G use cases across a handful of different sectors. It is important to remember that these comprise only a subset of possible use cases and these are all still new. As-yet more new use cases are expected to emerge and the need to prepare their adaption in 5G and beyond. From wireless transmission, wireless access and network perspectives, the possible key technologies of 5G, including Massive Multiple Input Multiple Output (MIMO), Beam-forming, Device-to-Device communication system (D2D), non-orthogonal multiple access (NOMA), Full duplex, Small cells, cognitive radio(CR), etc. and their latest progress are presented comprehensively and thoroughly. Each has enormous advantages but also limitations. The Full duplex which will help to double the capacity of the channel compared to the Half-duplex technology of 4G and Small cells combined with millimeter waves to have a wide bandwidth. These Small-Cells are essential for energy reduction and also for improving latency. But these Small-Cells require the use of intelligent antennas, that is to say, the diagrams of which are directive and reconfigurable at the request of the user Future research challenges regarding 5G and beyond wireless communication are also discussed.
Surface modification of cellulose nanocrystals by esterification and ATRP reactions for advanced applications

In this thesis, the surface functionalization of cellulose nanocrystals (CNC) by esterification and ATRP reactions was envisaged, with the objective to develop novel advanced materials. A convenient method to characterize the polymers grafted on CNC by Si-ATRP has been first developed, based on DLS, DSC and TGA analyses. The efficiency of the SI-ATRP and SI-ARGET ATRP methods to initiate the grating of polystyrene (PS) or poly(4-vinylpyridine) (P4VP) at the CNC surface were then compared. The pH-responsive P4VP-g-CNC nano-hybrids were subsequently utilized to stabilize gold nanoparticles (AuNPs), in view of producing recyclable catalysts. The catalytic activity of the Au@P4VP-g-CNC material – tested with the reduction of 4-nitrophenol – was significantly improved compared with single AuNPs. UV-responsive poly(cinnamoyloxy ethyl methacrylate) (PCEM) polymers were also grafted on CNC, to produce particles with UV absorbing properties. The PCEM-g-CNC nano-hybrids obtained turned out to be efficient UV/thermal stabilizers and reinforcing agents in PVC films. Finally, a facile method to prepare colloidosomes from w/o inverse Pickering emulsions stabilized by cinnamate-modified CNC was proposed. Colloidosomes with robust shells and allowing the slow release of encapsulated molecules such as rhodamine B or fluorescent deoxyribonucleic acid were then obtained.
Malnutrition and Some Related Factors in Primary School Children in Saudi Arabia: Systemic Review

Background: Malnutrition is an underlying factor in many diseases in both children and adults, and it contributes greatly to the disability-adjusted life years worldwide. It is a major public health concern in developing countries among children since it places a heavy burden on already disadvantaged communities. Methods: This is systematic review was carried out, including PubMed, Google Scholar, and EBSCO using the following terms in different combinations: Malnutrition, overweight, underweight, systemic review, primary school children, Saudi Arabia. Results: The review included 9 studies from different countries that assess the level of malnutrition and associated factors among school children. Many of studies reported high prevalence of malnutrition among school children which included overweight, stunting, wasting and underweight. The studies reported that age, gender, regularity of father’s employment, and dietary factors were associated with malnutrition. Also, the type of school attended was found to be associated with malnutrition. Conclusion: This review concluded that there was high malnutrition prevalence among school children in different parts and its affected by many factors like age and gender.
A Study on Peripheral Neuropathy and Its Related Risk Factors Associated With hba1c Levels

Diabetic peripheral neuropathy (DPN) patients frequently feel persistent pain, which is described as painful diabetic peripheral neuropathy (PDPN), which begins in both feet and frequently spreads to the calves, fingers, and hands. PDPN not only causes pain, but also affects patients' sleep, emotions, mental state, and everyday activities, resulting in a low quality of life and a significant financial burden. The goal of this study was to monitor if there was a link between the prevalence, pattern, and related risk factors of diabetic peripheral neuropathy and hemoglobin A1C (HbA1c) levels. In this crosssectional study, 150 type-2 diabetic patients were screened for DPN with PDPN and their HbA1c level was measured in every three months. DPN, PDPN and non-painful DPN were confirmed in patients displaying both clinical manifestations of neuropathy and neurological abnormalities assessment. DPN was detected in 24% (n = 36), while PDPN was found at 15% (n = 23) of the total patients. The prevalence of PDPN is 63.88% (n = 23) and non-painful DPN is 36.11% (n = 13) of total DPN (n = 36). Out of total PDPN (n = 23), the prevalence of symmetrical pain is 65% (n = 15), asymmetrical 35% (n = 8), sensory 26% (n = 6), motor 13% (n = 3), mixed (sensorimotor) 61% (n = 14), lower limb involvement 48% (n = 11), upper limb13% (n = 3) and both limb 39% (n = 9). In comparison to patients without DPN, both PDPN and non-painful DPN, patients had greater HbA1c levels (p<0.05). Furthermore, advanced age and longer diabetes duration were considerable and significant (p<0.05) risk factors for DPN with PDPN and non-painful DPN respectively. Overall, the findings imply that elevated HbA1c levels are closely linked to DPN, PDPN and non-painful DPN in type-2 diabetic patients and that HbA1c might be used as a predictive marker for DPN with PDPN and non-painful DPN in the patients studied. J. Bio-Sci. 29(2): 123-138, 2021 (December)
Low temperature dynamics of surface and bulk electronic structure of quantum dots

Absolute energies of band edges have proven to be very important for various applications like hydrogen generation, solar water splitting and solar cell optimization. Energy differences as small as 50–100 meV have been shown to largely affect device efficiencies. Device operational temperature can vary largely and temperature dependence of band gap is well known in bulk semiconductor literature. However, there are only a few studies on variation of band gap in quantum dots and none of them characterize the relative energy variation of band edges in spite of their importance in various applications. This is mainly due to the absence of an internal standard that can be used to study the variation of band edges. Here, in this paper, we introduce a technique wherein we utilize Cu dopant emission as an internal probe. Using this technique, we report the variation of band gap, conduction band and valence band edges of CdS and CdSe quantum dots as a function of temperature and size. We found that band gap variation is similar to that of bulk but with a higher average phonon energy. The band edge variation is characterized by a dominant conduction band shift for larger sizes with decreasing temperature while the smaller size QDs show the variation in both conduction band and valence band. Further, we have also utilized this method to study the binding energy of the trap states as a function of temperature using Cu photoluminescence quantum yield and average lifetime of Cu photoluminescence.
Enabling Settings for Learning: Observations Related to Design Communication

The paper addresses (re)design of educational premises. As learning situations diversify along with advancing ICT practices, an ever more challenging question for spatial design is: what provides enabling settings for learning? Apart from understanding the user requirements, the question is also about how well the settings are embedded into the local practices, and how various constraints, trends and potential opportunities are taken into account. In a (re)design process, multiple stakeholder perspectives are involved, each constrained in their expertise, way of articulating the topic area, and terminology used. That poses a challenge to design communication. Dialogue is a key for different stakeholders to learn from others’ points of view, and to establish a common ground. Yet, if participants of the process do not properly understand other stakeholders’ contributions, communication remains inefficient. The authors of this paper focus on a methodological question: how could different stakeholder perspectives be brought together to best capture information relevant to the spatial design of the educational settings ? Could an articulation tool help to focus attention on relevant issues in terms of spatial design and thereby, to map contributions within a bigger picture of the project? The authors of the paper take learning situation as a core concept as they seek to compose a simple articulation tool to aid dialogue in a (re)design process between key stakeholder perspectives.
Tractable Neural Networks for Identity Recognition

Deep neural networks are state-of-the-art for many applications, but the weights that parametrize them require signiﬁcant computational resources, making them inaccessible to less powerful devices (eg. mobile). In this project, we aim to reduce the computational demand of existing approaches for identity recognition. We propose the use of augmented hints which extend on the idea of hints from the FitNets model described by Romero et al., combining it with knowledge distillation as proposed by Hinton and Dean. Augmented hints use the outputs and intermediate representations of a larger teacher network to improve the training process of a smaller student network. The two-step augmented hints process ﬁrst initializes weights up to an intermediate layer of the student, using an intermediate layer of the teacher. The second step involves training the full student network, using the teacher network to regularize. Using augmented hints deﬁnitely allows student networks to achieve higher accuracies with fewer training epochs. Our results show that the larger the student network, the more the student accuracy improves as a result of using the augmented hints method. However, our results do not support the idea that augmented hints reduces the time it takes a small model to get to a ﬁxed accuracy. With very simple models, there is not enough complexity in the network for the time it takes to ﬁnd a good initialization to pay off at training or test time.