Search results for: IT capabilities

Authors: Azeddine El-Hassouny, Chandrashekhar Meshram, Geraldin Nanfack

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In recent years, learning from data with noisy labels (Label Noise) has been a major concern in supervised learning. This problem has become even more worrying in Deep Learning, where the generalization capabilities have been questioned lately. Indeed, deep learning requires a large amount of data that is generally collected by search engines, which frequently return data with unreliable labels. In this paper, we investigate the Label Noise in Deep Learning using variational inference. Our contributions are : (1) exploiting Label Noise concept where the true labels are learnt using reparameterization variational inference, while observed labels are learnt discriminatively. (2) the noise transition matrix is learnt during the training without any particular process, neither heuristic nor preliminary phases. The theoretical results shows how true label distribution can be learned by variational inference in any discriminate neural network, and the effectiveness of our approach is proved in several target datasets, such as MNIST and CIFAR32.

Keywords: label noise, deep learning, discrete latent variable, variational inference, MNIST, CIFAR32

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Authors: Atefeh Saljooghi Khoshkar, Jafar Hassanpour

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One of the main problems of the design stage relating to many tunneling projects is the lack of an appropriate standard for the provision of engineering geological data in a predefined format. In particular, this is more reflected in highway and railroad tunnel projects in which there is a number of tunnels and different professional teams involved. In this regard, comprehensive software needs to be designed using the accepted methods in order to help engineering geologists to prepare standard reports, which contain sufficient input data for the design stage. Regarding this necessity, applied software has been designed using macro capabilities and Visual Basic programming language (VBA) through Microsoft Excel. In this software, all of the engineering geological input data, which are required for designing different parts of tunnels, such as discontinuities properties, rock mass strength parameters, rock mass classification systems, boreability classification, the penetration rate, and so forth, can be calculated and reported in a standard format.

Keywords: engineering geology, rock mass classification, rock mechanic, tunnel

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Authors: Chika Catherine Ayogu

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Rehabilitation plays an important and integral part in the life of roadway rehabilitation management system. It is a systematic method for inspection and rating the roadway condition in a given area. The system performs a cost effective analysis of various maintenance and rehabilitation strategies. Finally the system prioritize and recommend roadway rehabilitation and maintenance to maximize results within a given budget amount. During execution of maintenance activity, the system also tracks labour, materials, equipment and cost for activities performed. The system implements physical assessment field inspection and rating of each street segment which is then entered into a database. The information is analyzed using a software, and provide recommendations and project future conditions. The roadway management system provides a deterioration curve for each segment based on input then assigns the most cost-effective maintenance strategy based on conditions, surface type and functional classification, and available budget. This paper investigates the roadway management system and its capabilities to assist in applying the right treatment to the right roadway at the right time so that expected service life of the roadway is extended as long as possible with acceptable cost.

Keywords: effectiveness, rehabilitation, roadway, software system

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Authors: Yasser M. Abd-elrhman, Mohamed A. Gepreel, Kiochi Nakamura, Ahmed Abd El-Moneim, Sengo Kobayashi, Mervat M. Ibrahim

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Titanium alloys are known as highly bio compatible metallic materials due to their high strength, low elastic modulus, and high corrosion resistance in biological media. Besides other important material features, the corrosion parameters and corrosion products are responsible for limiting the biological and chemical bio compatibility of metallic materials that produce undesirable reactions in implant-adjacent and/or more distant tissues. Electrochemical corrosion behaviors of novel beta titanium alloys, Ti-4.7Mo-4.5Fe, Ti-3Mo-0.5Fe, and Ti-2Mo-0.5Fe were characterized in naturally aerated Ringer’s solution at room temperature compared with common used biomedical titanium alloy, Ti-6Al-4V. The corrosion resistance of titanium alloys were investigated through open circuit potential (OCP), potentiodynamic polarization measurements and optical microscope (OM). A high corrosion resistance was obtained for all alloys due to the stable passive film formed on their surfaces. The new present alloys are promising metallic biomaterials for the future, owing to their very low elastic modulus and good corrosion resistance capabilities.

Keywords: titanium alloys, corrosion resistance, Ringer’s solution, electrochemical corrosion

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Authors: Ahmed H. El-Masry, Mohamed A. Dabaon, Tarek F. El-Shafiey, Abd El-Hakim A. Khalil

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An experimental study was performed to investigate the behavior and strength of proposed technique to connect reinforced concrete (RC) beam to steel or composite columns. This approach can practically be used in several types of building construction. In this technique, the main beam of the frame consists of a transfer part (part of beam; Tr.P) and a common reinforcement concrete beam. The transfer part of the beam is connected to the column, whereas the rest of the beam is connected to the transfer part from each side. Four full-scale beam-column connections were tested under static loading. The test parameters were the length of the transfer part and the column properties. The test results show that using of the transfer part technique leads to modify the deformation capabilities for the RC beam and hence it increases its resistance against failure. Increase in length of the transfer part did not necessarily indicate an enhanced behavior. The test results contribute to the characterization of the connection behavior between RC beam - steel column and can be used to calibrate numerical models for the simulation of this type of connection.

Keywords: composite column, reinforced concrete beam, steel column, transfer part

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Authors: Julius Brejohn Calvert

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This Study Aimed to Investigate the Ecological Nature of Extremism Online. The Construction of a Far-Right Ecosystem Was Successful Using a Sample of Posts, Each With Separate Narrative Domains. Most of the Content Expressed Anti-black Racism and Pro-white Sentiments. Many Posts Expressed an Overt Disdain for the Recent Progress Made Regarding the United States and the United Kingdom’s Expansion of Civil Liberties to People of Color (Poc). Of Special Note, Several Anti-lgbt Posts Targeted the Ongoing Political Grievances Expressed by the Transgender Community. Overall, the Current Study Is Able to Demonstrate That Direct Measures of User Engagement, Such as Shares and Reactions, Can Be Used to Predict the Effect of a Post’s Radicalization Capabilities, Although Single Posts Do Not Operate on the Cognitive Processes of Radicalization Alone. In This Analysis, the Data Supports a Theoretical Framework Where Individual Posts Have a Higher Radicalization Capability Based on the Amount of User Engagement (Both Indirect and Direct) It Receives.

Keywords: cognitive psychology, cognitive radicalization, extremism online, domestic extremism, political science, political psychology

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Authors: Boris Melnikov, Ye Zhang, Dmitrii Chaikovskii

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We continue to consider one of the cybernetic methods in computational biology related to the study of DNA chains. Namely, we are considering the problem of reconstructing the not fully filled distance matrix of DNA chains. When applied in a programming context, it is revealed that with a modern computer of average capabilities, creating even a small-sized distance matrix for mitochondrial DNA sequences is quite time-consuming with standard algorithms. As the size of the matrix grows larger, the computational effort required increases significantly, potentially spanning several weeks to months of non-stop computer processing. Hence, calculating the distance matrix on conventional computers is hardly feasible, and supercomputers are usually not available. Therefore, we started publishing our variants of the algorithms for calculating the distance between two DNA chains; then, we published algorithms for restoring partially filled matrices, i.e., the inverse problem of matrix processing. In this paper, we propose an algorithm for restoring the distance matrix for DNA chains, and the primary focus is on enhancing the algorithms that shape the greedy function within the branches and boundaries method framework.

Keywords: DNA chains, distance matrix, optimization problem, restoring algorithm, greedy algorithm, heuristics

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Authors: Khalil Khanafer

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This study emphasizes on analyzing the effect of flow conditions and the geometric variation of the microcantilever’s bluff body on the microcantilever detection capabilities within a fluidic device using a finite element fluid-structure interaction model. Such parameters include inlet velocity, flow direction, and height of the microcantilever’s supporting system within the fluidic cell. The transport equations are solved using a finite element formulation based on the Galerkin method of weighted residuals. For a flexible microcantilever, a fully coupled fluid-structure interaction (FSI) analysis is utilized and the fluid domain is described by an Arbitrary-Lagrangian–Eulerian (ALE) formulation that is fully coupled to the structure domain. The results of this study showed a profound effect on the magnitude and direction of the inlet velocity and the height of the bluff body on the deflection of the microcantilever. The vibration characteristics were also investigated in this study. This work paves the road for researchers to design efficient microcantilevers that display least errors in the measurements.

Keywords: fluidic cell, FSI, microcantilever, flow direction

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Authors: Alex B. Cusick

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The objective of this study is to improve upon the current ²³⁸PuO₂ fuel technology for space and defense applications. Modern RTGs (radioisotope thermoelectric generators) utilize the heat generated from the radioactive decay of ²³⁸Pu to create heat and electricity for long term and remote missions. Application of RTG technology is limited by the scarcity and expense of producing the isotope, as well as the power output which is limited to only a few hundred watts. The scarcity and expense make the efficient use of ²³⁸Pu absolutely necessary. By utilizing the decay of ²³⁸Pu, not only to produce heat directly but to also indirectly induce fission in ²³⁹Pu (which is already present within currently used fuel), it is possible to see large increases in temperature which allows for a more efficient conversion to electricity and a higher power-to-weight ratio. This concept can reduce the quantity of ²³⁸Pu necessary for these missions, potentially saving millions on investment, while yielding higher power output. Current work investigating radioisotope power systems have focused on improving efficiency of the thermoelectric components and replacing systems which produce heat by virtue of natural decay with fission reactors. The technical feasibility of utilizing (α,n) reactions to induce fission within current radioisotopic fuels has not been investigated in any appreciable detail, and our study aims to thoroughly investigate the performance of many such designs, develop those with highest capabilities, and facilitate experimental testing of these designs. In order to determine the specific design parameters that maximize power output and the efficient use of ²³⁸Pu for future RTG units, MCNP6 simulations have been used to characterize the effects of modifying fuel composition, geometry, and porosity, as well as introducing neutron moderating, reflecting, and shielding materials to the system. Although this project is currently in the preliminary stages, the final deliverables will include sophisticated designs and simulation models that define all characteristics of multiple novel RTG fuels, detailed enough to allow immediate fabrication and testing. Preliminary work has consisted of developing a benchmark model to accurately represent the ²³⁸PuO₂ pellets currently in use by NASA; this model utilizes the alpha transport capabilities of MCNP6 and agrees well with experimental data. In addition, several models have been developed by varying specific parameters to investigate their effect on (α,n) and (n,fi ssion) reaction rates. Current practices in fuel processing are to exchange out the small portion of naturally occurring ¹⁸O and ¹⁷O to limit (α,n) reactions and avoid unnecessary neutron production. However, we have shown that enriching the oxide in ¹⁸O introduces a sufficient (α,n) reaction rate to support significant fission rates. For example, subcritical fission rates above 10⁸ f/cm³-s are easily achievable in cylindrical ²³⁸PuO₂ fuel pellets with a ¹⁸O enrichment of 100%, given an increase in size and a ⁹Be clad. Many viable designs exist and our intent is to discuss current results and future endeavors on this project.

Keywords: radioisotope thermoelectric generators (RTG), Pu-238, subcritical reactors, (alpha, n) reactions

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Authors: Chijindu Okpalaoka, Charles Chinedu Onuselogu

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COVID-19, humanity's coronavirus disease caused by SARS-CoV-2, was first detected in late 2019 in Wuhan, China. COVID-19 lacked an established conventional pharmaceutical therapy, and as a result, the outbreak quickly became an epidemic affecting the entire World. Only a qPCR assay is reliable for diagnosing COVID-19. Clustered, regularly interspaced short palindromic repeats (CRISPR) technology is being researched for speedy and specific identification of COVID-19, among other therapeutic techniques. Apart from its therapeutic capabilities, the CRISPR technique is being evaluated to develop antiviral therapies; nevertheless, no CRISPR-based medication has been approved for human use to date. Prophylactic antiviral CRISPR in living being cells, a Cas 13-based approach against coronavirus, has been developed. While this method can be evolved into a treatment approach, it may face substantial obstacles in human clinical trials for licensure. This study discussed the potential applications of CRISPR-based techniques for developing a speedy and accurate feasible treatment alternative for the COVID-19 virus.

Keywords: COVID-19, CRISPR technique, Cas13, SARS-CoV-2, prophylactic antiviral

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Authors: Im-Nam Jang, Yong-Sik Ahn

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In this study sintered wick was formed in a heat pipe through the process of sintering a mixture of copper powder with particle sizes of 100μm and 200μm, mixed with a pore-forming agent. The heat pipe's thermal resistance, which affects its heat transfer efficiency, is determined during manufacturing according to powder type, thickness of the sintered wick, and filling rate of the working fluid. Heat transfer efficiency was then tested at various inclination angles (0°, 45°, 90°) to evaluate the performance of heat pipes. Regardless of the filling amount and test angle, the 200μm copper powder type exhibited superior heat transfer efficiency compared to the 100μm type. After analyzing heat transfer performance at various filling rates between 20% and 50%, it was determined that the heat pipe's optimal heat transfer capability occurred at a working fluid filling rate of 30%. The width of the wick was directly related to the heat transfer performance.

Keywords: heat pipe, heat transfer performance, effective pore size, capillary force, sintered wick

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Authors: Espen Oland

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This paper presents a solution to the problem of autonomous rendezvous for spacecraft equipped with one main thruster for translational control and three reaction wheels for rotational control. With fewer actuators than degrees of freedom, this constitutes an underactuated control problem, requiring a coupling between the translational and rotational dynamics to facilitate control. This paper shows how to obtain this coupling, and applies the results to autonomous rendezvous between a follower spacecraft and a leader spacecraft. Additionally, since the thrust is constrained between zero and an upper bound, no negative forces can be generated to slow down the speed of the spacecraft. A combined speed and attitude control logic is therefore created that can be divided into three main phases: 1) The orbital velocity vector is pointed towards the desired position and the thrust is used to obtain the desired speed, 2) during the coasting phase, the attitude is changed to facilitate deceleration using the main thruster, 3) the speed is decreased as the spacecraft reaches its desired position. The results are validated through simulations, showing the capabilities of the proposed approach.

Keywords: attitude control, spacecraft rendezvous, translational control, underactuated rigid body

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Authors: Sourav Sarkar, Manashjit Gogoi

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In the evolving landscape of cancer diagnostics, optical biosensing has emerged as a promising tool due to its sensitivity and specificity. This study explores the potential of CdS/ZnS core-shell quantum dots (QDs) capped with 3-Mercaptopropionic acid (3-MPA), which aids in the linking chemistry of QDs to various cancer antibodies. The QDs, with their unique optical and electronic properties, have been integrated into the biosensor design. Their high quantum yield and size-dependent emission spectra have been exploited to improve the sensor’s detection capabilities. The study presents the design of this QD-enhanced optical biosensor. The use of these QDs can also aid multiplexed detection, enabling simultaneous monitoring of different cancer biomarkers. This innovative approach holds significant potential for advancing cancer diagnostics, contributing to timely and accurate detection. Future work will focus on optimizing the biosensor design for clinical applications and exploring the potential of QDs in other biosensing applications. This study underscores the potential of integrating nanotechnology and biosensing for cancer research, paving the way for next-generation diagnostic tools. It is a step forward in our quest for achieving precision oncology.

Keywords: quantum dots, biosensing, cancer, device

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Authors: Sabita Mahapatra

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‘Going green’ has been an emerging issue worldwide driving companies to continuously enhance their green capabilities and implement innovative green practices to protect the environment and improve business performance. Green has become a contemporary business environmental issue. The resource advantage theory is adopted in the present study to observe the impact of marketing orientation and green innovation practices on environmental and firm’s performance. The small and medium firms compared to large firms have different approach towards market orientation as a strategic tool. The present study proposes a conceptual framework regarding the impact of market orientation on environmental and firm’s performance through green innovation practices in the context of small and medium scale industries (SMEs). The propositions developed in the present paper would provide scope for future research study to validate the conceptual framework in the emerging economy like India.

Keywords: market orientation, green innovation practices, environment performance, corporate performance, emerging market

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Authors: Wuttigrai Ngamsirijit

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Talent management in today’s modern organizations has become data-driven due to a demand for objective human resource decision making and development of analytics technologies. HR managers have been faced with some obstacles in exploiting data and information to obtain their effective talent management decisions. These include process-based data and records; insufficient human capital-related measures and metrics; lack of capabilities in data modeling in strategic manners; and, time consuming to add up numbers and make decisions. This paper proposes a framework of talent management through integration of talent value chain and human capital analytics approaches. It encompasses key data, measures, and metrics regarding strategic talent management decisions along the organizational and talent value chain. Moreover, specific predictive and prescriptive models incorporating these data and information are recommended to help managers in understanding the state of talent, gaps in managing talent and the organization, and the ways to develop optimized talent strategies.    

Keywords: decision making, human capital analytics, talent management, talent value chain

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Authors: Dharamvir Mangal

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Supply chain management has increasingly become an inevitable challenge to most companies to continuously survive and prosper in the global chain-based competitive environment. The current challenges of the Indian automotive world, their implications on supply chain are summarized and analyzed in this paper. In this competitive era of ‘LPG’ i.e. Liberalization, Privatization and Globalization, modern marketing systems, introduction of products with short life cycles, and the discriminating expectations of customers have enforced business enterprises to invest in and focus attention on their Supply Chains (SCs) in order to meet out the level of customer’s satisfaction and to survive in the competitive market. In fact, many of trends in the auto industry are reinforcing the need to redefine supply chain strategies layouts, and operations etc. Many manufacturing operations are designed to maximize throughput and lower costs with modest considerations for the crash on inventory levels and distribution capabilities. To improve profitability and efficiency, automotive players are seeking ways to achieve operational excellence, reduce operating cost and enhance customer service through efficient supply chain management.

Keywords: automotive industry, supply chain, challenges, market potential

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Authors: Bhuyain Mobarok Hossain

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Image classification and localization research is currently an important strategy in the field of computer vision. The evolution and advancement of deep learning and convolutional neural networks (CNN) have greatly improved the capabilities of object detection and image-based classification. Target detection is important to research in the field of computer vision, especially in video surveillance systems. To solve this problem, we will be applying a convolutional neural network of multiple scales at multiple locations in the image in one sliding window. Most translation networks move away from the bounding box around the area of interest. In contrast to this architecture, we consider the problem to be a classification problem where each pixel of the image is a separate section. Image classification is the method of predicting an individual category or specifying by a shoal of data points. Image classification is a part of the classification problem, including any labels throughout the image. The image can be classified as a day or night shot. Or, likewise, images of cars and motorbikes will be automatically placed in their collection. The deep learning of image classification generally includes convolutional layers; the invention of it is referred to as a convolutional neural network (CNN).

Keywords: image classification, object detection, localization, particle filter

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Authors: Beibit Karibayev, Akmaral Imanbayeva, Timur Namazbayev

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Currently, the small spacecraft (SSC) industry is experiencing a big boom in popularity. This is primarily due to ease of use, low cost and mobility. In addition, these programs can be implemented not only at the state level but also at the level of companies, universities and other organizations. For remote sensing of the Earth (ERS), small spacecraft with an orientation system is used. It is important to take into account here that a remote sensing device, for example, a camera for photographing the Earth's surface, must be directed at the Earth's surface. But this, at first glance, the limitation can be turned into an advantage using a patch antenna. This work proposed to use a patch antenna based on a unidirectional fractal in the SSC. The CST Microwave Studio software package was used for simulation and research. Copper (ε = 1.0) was chosen as the emitting element and reflector. The height of the substrate was 1.6 mm, the type of substrate material was FR-4 (ε = 4.3). The simulation was performed in the frequency range of 0 – 6 GHz. As a result of the research, a patch antenna based on fractal geometry was developed for ERS nanosatellites. The capabilities of these antennas are modeled and investigated. A method for calculating and modeling fractal geometry for patch antennas has been developed.

Keywords: antenna, earth remote sensing, fractal, small spacecraft

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Authors: Shayan Mohajer Hamidi

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Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

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Authors: Zahra Khan

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Hydrogels are a macromolecular network of hydrophilic copolymers with physical or chemical cross-linking structures with significant water uptake capabilities. They are a promising substrate for surface-enhanced Raman spectroscopy (SERS) as they are both flexible and biocompatible materials. Conventional SERS-active substrates suffer from limitations such as instability and inflexibility, which restricts their use in broader applications. Gelatin-based hydrogels have been synthesised in a facile and relatively quick method without the use of any toxic cross-linking agents. Composite gel material was formed by combining the gelatin with simple polymers to enhance the functional properties of the gel. Gold nanoparticles prepared by a reproducible seed-mediated growth method were combined into the bulk material during gel synthesis. After gel formation, the gel was submerged in the analyte solution overnight. SERS spectra were then collected from the gel using a standard Raman spectrometer. A wide range of analytes was successfully detected on these hydrogels showing potential for further optimization and use as SERS substrates for biomedical applications.

Keywords: gelatin, hydrogels, flexible materials, SERS

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Authors: D. Madhushanka, Y. Liu, H. C. Fernando

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Fires are one of the foremost factors of land surface disturbance in diverse ecosystems, causing soil erosion and land-cover changes and atmospheric effects affecting people's lives and properties. Generally, the severity of the fire is calculated as the Normalized Burn Ratio (NBR) index. This is performed manually by comparing two images obtained afterward. Then by using the bitemporal difference of the preprocessed satellite images, the dNBR is calculated. The burnt area is then classified as either unburnt (dNBR<0.1) or burnt (dNBR>= 0.1). Furthermore, Wildfire Severity Assessment (WSA) classifies burnt areas and unburnt areas using classification levels proposed by USGS and comprises seven classes. This procedure generates a burn severity report for the area chosen by the user manually. This study is carried out with the objective of producing an automated tool for the above-mentioned process, namely the World Wildfire Severity Assessment Tool (WWSAT). It is implemented in Google Earth Engine (GEE), which is a free cloud-computing platform for satellite data processing, with several data catalogs at different resolutions (notably Landsat, Sentinel-2, and MODIS) and planetary-scale analysis capabilities. Sentinel-2 MSI is chosen to obtain regular processes related to burnt area severity mapping using a medium spatial resolution sensor (15m). This tool uses machine learning classification techniques to identify burnt areas using NBR and to classify their severity over the user-selected extent and period automatically. Cloud coverage is one of the biggest concerns when fire severity mapping is performed. In WWSAT based on GEE, we present a fully automatic workflow to aggregate cloud-free Sentinel-2 images for both pre-fire and post-fire image compositing. The parallel processing capabilities and preloaded geospatial datasets of GEE facilitated the production of this tool. This tool consists of a Graphical User Interface (GUI) to make it user-friendly. The advantage of this tool is the ability to obtain burn area severity over a large extent and more extended temporal periods. Two case studies were carried out to demonstrate the performance of this tool. The Blue Mountain national park forest affected by the Australian fire season between 2019 and 2020 is used to describe the workflow of the WWSAT. This site detected more than 7809 km2, using Sentinel-2 data, giving an error below 6.5% when compared with the area detected on the field. Furthermore, 86.77% of the detected area was recognized as fully burnt out, of which high severity (17.29%), moderate-high severity (19.63%), moderate-low severity (22.35%), and low severity (27.51%). The Arapaho and Roosevelt National Forest Park, California, the USA, which is affected by the Cameron peak fire in 2020, is chosen for the second case study. It was found that around 983 km2 had burned out, of which high severity (2.73%), moderate-high severity (1.57%), moderate-low severity (1.18%), and low severity (5.45%). These spots also can be detected through the visual inspection made possible by cloud-free images generated by WWSAT. This tool is cost-effective in calculating the burnt area since satellite images are free and the cost of field surveys is avoided.

Keywords: burnt area, burnt severity, fires, google earth engine (GEE), sentinel-2

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Authors: Siddharth Satishchandran, Brian Khumalo

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Humans are able to derive semantic content from syntactic and pragmatic sources. Multimodal evidence from signaling theory, which examines communication between individuals within and across species, suggests that non-human primates possess similar syntactic and pragmatic capabilities. However, the extent remains unknown because primate pragmatics are relatively under-examined. Our paper reviews research within communication theory amongst non-human primates to understand current theoretical trends. We examine evidence for primate pragmatic capacities through observational, experimental, and theoretical work on gestures. Given fragmented theoretical perspectives, we provide a unified framework of communication for future research that contextualizes the available research under code biology. To achieve this, we rely on biological semiotics (biosemiotics), the philosophy of biology investigating prelinguistic meaning-making as a function of signs and codes. We close by discussing areas of potential research for studying gestural pragmatics amongst non-human primates, particularly chimpanzees (Pan troglodytes), Diana monkeys (Cercopithecus diana), and other potential candidates.

Keywords: pragmatics, non-human primates, gestural communication, biological semiotics

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Authors: Manthekeleng Linake, Fesi Liziwe

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The ongoing argument over the use of English as a learning and teaching language in schools was examined in this study. The nature of the language proficiency gap is particularly relevant in light of the present emphasis on learning and educational quality in contemporary debates, as well as the education sustainable development goal. As a result, an interpretivist paradigm, a qualitative technique, and a case study-based research design were used in the work. Two school principals, two teachers, two members of the School Governing Body (SGB), and four learners were chosen using purposive sampling from two schools in the Amathole West Education District. The researchers were able to acquire in-depth information on the disputes surrounding the use of English as a language of learning and teaching by using semi-structured interview questions and focus groups. Despite knowing that they do not have the potential to do well in English, teachers found that despite appreciating the value of mother tongue and cultural identity, they prefer to use English as the language of teaching in schools. The findings, on the other hand, revealed that proponents of mother-language-based education argue that learning one's mother tongue is a human right.

Keywords: English first additional language learners, social justice, human capabilities, language proficiency

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Authors: Prateeksha Mahamallik, Anjali Pal

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In the present study, Co(II)-adsolubilized surfactant modified alumina (SMA) was prepared, and methylene blue (MB) degradation was carried out on Co-SMA surface by visible light photo-Fenton process. The entire reaction proceeded on solid surface as MB was embedded on Co-SMA surface. The reaction followed zero order kinetics. Response surface methodology (RSM) and artificial neural network (ANN) were used for modeling the decolorization of MB by photo-Fenton process as a function of dose of Co-SMA (10, 20 and 30 g/L), initial concentration of MB (10, 20 and 30 mg/L), concentration of H2O2 (174.4, 348.8 and 523.2 mM) and reaction time (30, 45 and 60 min). The prediction capabilities of both the methodologies (RSM and ANN) were compared on the basis of correlation coefficient (R2), root mean square error (RMSE), standard error of prediction (SEP), relative percent deviation (RPD). Due to lower value of RMSE (1.27), SEP (2.06) and RPD (1.17) and higher value of R2 (0.9966), ANN was proved to be more accurate than RSM in order to predict decolorization efficiency.

Keywords: adsolubilization, artificial neural network, methylene blue, photo-fenton process, response surface methodology

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Authors: B. Kędra, R. Małkowski

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This paper presents information on Power System Component Simulator – a device designed for LINTE^2 laboratory owned by Gdansk University of Technology in Poland. In this paper, we first provide an introductory information on the Power System Component Simulator and its capabilities. Then, the concept of the unit is presented. Requirements for the unit are described as well as proposed and introduced functions are listed. Implementation details are given. Hardware structure is presented and described. Information about used communication interface, data maintenance and storage solution, as well as used Simulink real-time features are presented. List and description of all measurements is provided. Potential of laboratory setup modifications is evaluated. Lastly, the results of experiments performed using Power System Component Simulator are presented. This includes simulation of under frequency load shedding, frequency and voltage dependent characteristics of groups of load units, time characteristics of group of different load units in a chosen area.

Keywords: power converter, Simulink Real-Time, Matlab, load, tap controller

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Authors: Blessing Dwumah Manu, Dawn Wallin

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This study aims to explore school principal instructional leadership capabilities (Robinson, 2010) that support school performance in senior high schools in Ghana’s Northern Region. It explores the ways in which leaders (a) use deep leadership content knowledge to (b) solve complex school-based problems while (c) building relational trust with staff, parents, and students as they engage in the following instructional leadership dimensions: establishing goals and expectations; resourcing strategically; ensuring quality teaching; leading teacher learning and development and ensuring an orderly and safe environment (Patuawa et al, 2013). The proposed research utilizes a constructivist approach to explore the experiences of 18 school representatives (including principals, deputy principals, department heads, teachers, parents, and students) through an interview method.

Keywords: instructional leadership, leadership content knowledge, solving complex problems, building relational trust and school performance

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Authors: Christina A. van Hal, Xiaoqian Jiang, Luyao Chen, Yan Chu, Robert D. Jolly, Yaobin Lin, Jitian Zhao, Kang Lin Hsieh

Abstract:

The COVID-19 Literature Summary App was created for the primary purpose of enabling academicians and clinicians to quickly sort through the vast array of recent coronavirus publications by topics of interest. Multiple methods of summarizing and sorting the manuscripts were created. A summary page introduces the application function and capabilities, while an interactive map provides daily updates on infection, death, and recovery rates. A page with a pivot table allows publication sorting by topic, with an interactive data table that allows sorting topics by columns, as wells as the capability to view abstracts. Additionally, publications may be sorted by the medical topics they cover. We used the CORD-19 database to compile lists of publications. The data table can sort binary variables, allowing the user to pick desired publication topics, such as papers that describe COVID-19 symptoms. The application is primarily designed for use by researchers but can be used by anybody who wants a faster and more efficient means of locating papers of interest.

Keywords: COVID-19, literature summary, information retrieval, Snorkel

Procedia PDF Downloads 130

Authors: Sameh Baccari, Mahmoud Neji

Abstract:

In recent years, the rapid developments on mobile devices and wireless technologies enable new dimension capabilities for the learning domain. This dimension facilitates people daily activities and shortens the distances between individuals. When these technologies have been used in learning, a new paradigm has been emerged giving birth to mobile learning. Because of the mobility feature, m-learning courses have to be adapted dynamically to the learner’s context. The main challenge in context-aware mobile learning is to develop an approach building the best learning resources according to dynamic learning situations. In this paper, we propose a context-aware mobile learning system called Collaborative and Context-aware Mobile Learning System (CCMLS). It takes into account the requirements of Mobility, Collaboration and Context-Awareness. This system is based on the semantic modeling of the learning context and the learning content. The adaptation part of this approach is made up of adaptation rules to propose and select relevant resources, learning partners and learning activities based not only on the user’s needs, but also on its current context.

Keywords: mobile learning, mobile technologies, context-awareness, collaboration, semantic web, adaptation engine, adaptation strategy, learning object, learning context

Procedia PDF Downloads 286

Authors: Foruzan Taheri, Seyedeh Negar Hosseinian, Katayoon Alizadeh

Abstract:

The small countryside city of Shandiz, with a population of about 13.297 is located 35 km to the west of the Mashhad metropolitan. Due to Shandiz’s natural beauty, suitable climate, and its close proximity to Mashhad which is the largest city in the eastern half of the country, many people own second houses in this area. In addition to this, Shandiz hosts millions of visitors annually. Its economic role, which is parallel and complementary to Mashhad, has caused population growth, the increase of activities, and physical expansion, all of which exceed the city’s capacity. The aim of this descriptive and analytical study was to evaluate the impact of city expansion on the environment and aid in preventing further harm to the natural environment of this perimeter. Data were collected from population and housing statistics during a different period of time-based on GIS. Results show that the existence of an integrated environmental management system in order to coordinate development projects and the expansion of tourism programs that meet environmental conditions are necessary and achieving sustainable development with quality of life in this area without considering environmental limitations and capabilities cannot be sustained.

Keywords: population growth, tourism, physical development, environmental impact, Shandiz City

Procedia PDF Downloads 335

Authors: David M Gilstrap

Abstract:

In an online course with a large enrollment, the potential exists for the instructor to become overburdened with having to respond to students’ emails, which consequently decreases the instructor’s efficiency in teaching the course. Repetition of instructions is an effective way of reducing confusion among students, which in turn increases their efficiencies, as well. World of Turf is the largest online course at Michigan State University, which employs Brightspace as its management system (LMS) software. Recently, the LMS upgraded its capabilities to utilize agents, which are auto generated email notifications to students based on certain criteria. Agents are additional tools that can enhance course design. They can be run on-demand or according to a schedule. Agents can be timed to effectively remind students of approaching deadlines. The content of these generated emails can also include reinforced instructions. With a large online course, even a small percentage of students that either do not read or do not comprehend the course syllabus or do not notice instructions on course pages can result in numerous emails to the instructor, often near the deadlines for assignments. Utilizing agents to decrease the number of emails from students has enabled the instructor to efficiently instruct more than one thousand students per semester without any graduate student teaching assistants.

Keywords: agents, Brightspace, large enrollment, learning management system, repetition of instructions

Procedia PDF Downloads 183