Search results for: satellite imagery classification

Authors: M. Z. Kurian, M. V. Chidananda Murthy, H. S. Guruprasad

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An approach to super-resolve the low-resolution (LR) image is presented in this paper which is very useful in multimedia communication, medical image enhancement and satellite image enhancement to have a clear view of the information in the image. The proposed Advanced B-Spline method generates a high-resolution (HR) image from single LR image and tries to retain the higher frequency components such as edges in the image. This method uses B-Spline technique and Crispening. This work is evaluated qualitatively and quantitatively using Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR). The method is also suitable for real-time applications. Different combinations of decimation and super-resolution algorithms in the presence of different noise and noise factors are tested.

Keywords: advanced b-spline, image super-resolution, mean square error (MSE), peak signal to noise ratio (PSNR), resolution down converter

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Authors: Bahareh Golchin, Nooshin Riahi

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One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such as the opinions, feelings, attitudes and emotions of people towards the products, services, organizations, people, topics, events and features in the written text. These indicate the greatness of the problem space. In the real world, businesses and organizations are always looking for tools to gather ideas, emotions, and directions of people about their products, services, or events related to their own. This article uses the Twitter social network, one of the most popular social networks with about 420 million active users, to extract data. Using this social network, users can share their information and opinions about personal issues, policies, products, events, etc. It can be used with appropriate classification of emotional states due to the availability of its data. In this study, supervised learning and deep neural network algorithms are used to classify the emotional states of Twitter users. The use of deep learning methods to increase the learning capacity of the model is an advantage due to the large amount of available data. Tweets collected on various topics are classified into four classes using a combination of two Bidirectional Long Short Term Memory network and a Convolutional network. The results obtained from this study with an average accuracy of 93%, show good results extracted from the proposed framework and improved accuracy compared to previous work.

Keywords: emotion classification, sentiment analysis, social networks, deep neural networks

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Authors: Ahmad A. Kader

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In the principles of Microeconomics course taught during the Fall Semester 2019, 158out of 179 students participated in the completion of two questionnaires and a survey describing their demographic and academic profiles. The two questionnaires include the 29 items of the Rotter Locus of Control Scale and the 52 items of the Schraw andDennisonMetacognitive Awareness Scale. The 52 items consist of 17 items describing knowledge of cognition and 37 items describing the regulation of cognition. The paper is intended to show the combined influence of locus of control, metacognitive knowledge, and metacognitive regulation on student performance. The survey covers variables that have been tested and recognized in economic education literature, which include GPA, gender, age, course level, race, student classification, whether the course was required or elective, employments, whether a high school economic course was taken, and attendance. Regression results show that of the economic education variables, GPA, classification, whether the course was required or elective, and attendance are the only significant variables in their influence on student grade. Of the educational psychology variables, the regression results show that the locus of control variable has a negative and significant effect, while the metacognitive knowledge variable has a positive and significant effect on student grade. Also, the adjusted R square value increased markedly with the addition of the locus of control, metacognitive knowledge, and metacognitive regulation variables to the regression equation. The t test results also show that students who are internally oriented and are high on the metacognitive knowledge scale significantly outperform students who are externally oriented and are low on the metacognitive knowledge scale. The implication of these results for educators is discussed in the paper.

Keywords: locus of control, metacognitive knowledge, metacognitive regulation, student performance, economic education

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Authors: Arif Armagan Gozutok, Alper Kule, Burak Tos, Selman Demirel

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Wireless communication chain requires effective ways to keep throughput efficiency high while it suffers location-dependent, time-varying burst errors. Several techniques are developed in order to assure that the receiver recovers the transmitted information without errors. The most fundamental approaches are error checking and correction besides re-transmission of the non-acknowledged packets. In this paper, stop & wait (SAW) and chase combined (CC) hybrid automated repeat request (HARQ) protocols are compared and analyzed in terms of throughput and average delay for the usage of low earth orbit (LEO) mega-constellations case. Several assumptions and technological implementations are considered as well as usage of low-density parity check (LDPC) codes together with several constellation orbit configurations.

Keywords: HARQ, LEO, satellite constellation, throughput

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Authors: Makhdoom Saad Wasim Ghouri, Muneeba Butt, Mohammad Ashraf Tahir, Rashid Bhatti, Akbar Ali, Abdul Rehman, Abdul Basit, Muzzamel Rehman, Shahbaz Aslam, Farakh Mansoor, Ahmad Fayyaz, Hadia Siddiqui

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Lip print analysis (Cheiloscopy) is the new emerging technique that might be the guardian angel in establishing the personal identity. Cheiloscopy is basically the study of elevations and depressions present on the external surface of the lips. In our study, 600 lip prints samples were taken (300 males and 300 females). Lip prints of each individual were divided into four quadrants and the upper middle portion. For general classification, middle part of the lower lip almost 10 mm wide would be taken into consideration. After analysis of lip-prints, our results show that lip prints are the unique and permanent character of every individual. No two lip print was matched with each other even of the identical twins. Our study reveals that there is equal distribution of lip print patterns among all the four quadrants of lips and the upper middle portion; these distributions were statistically analyzed by applying chi-square test which shows the significant results. In general classification, 5 lip print types/patterns were studied, Type 1 (Vertical lines), Type 2 (Branched pattern), Type 3 (Intersected pattern), Type 4 (Reticular pattern) and Type 5 (Undetermined). Type 1 and Type 2 were found to be the most frequent patterns in female population, while Type 3 and Type 4 most commonly found in male population. These results were also analyzed by applying Chi-square test, and the results show significance statistically. Thus, establishing sex determination on the basis of lip print types among the gender. Type 5 was the least common pattern among genders.

Keywords: cheiloscopy, distribution, quadrants, sex determination

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Authors: Daniel E. Martin, Chenghai Yang

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Variable-rate aerial application systems are becoming more readily available; however, aerial applicators typically only use the systems for constant-rate application of materials, allowing the systems to compensate for upwind and downwind ground speed variations. Much of the resistance to variable-rate aerial application system adoption in the U.S. pertains to applicator’s trust in the systems to turn on and off automatically as desired. The objectives of this study were to evaluate a commercially available variable-rate aerial application system under field conditions to demonstrate both the response and accuracy of the system to desired application rate inputs. This study involved planting oats in a 35-acre fallow field during the winter months to establish a uniform green backdrop in early spring. A binary (on/off) prescription application map was generated and a variable-rate aerial application of glyphosate was made to the field. Airborne multispectral imagery taken before and two weeks after the application documented actual field deposition and efficacy of the glyphosate. When compared to the prescription application map, these data provided application system response and accuracy information. The results of this study will be useful for quantifying and documenting the response and accuracy of a commercially available variable-rate aerial application system so that aerial applicators can be more confident in their capabilities and the use of these systems can increase, taking advantage of all that aerial variable-rate technologies have to offer.

Keywords: variable-rate, aerial application, remote sensing, precision application

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Authors: Teoman Ozer, Ozlem Orhan

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This study deals with symmetry group properties and conservation laws of partial differential equations. We give a geometrical interpretation of notion of μ-prolongations of vector fields and of the related concept of μ-symmetry for partial differential equations. We show that these are in providing symmetry reduction of partial differential equations and systems and invariant solutions.

Keywords: λ-symmetry, μ-symmetry, classification, invariant solution

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Authors: Mohamed H. Kosba, Heba A. Ibrahim, H. Rozita

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Statement of the Problem: The life expectancy for transfusion-dependent thalassemia patients has increased dramatically with iron-chelation therapy and other modern management modalities. In these patients, the most dominant maxillofacial manifestations are protrusion of zygomatic bones and premaxilla due to the hyperplasia of bone marrow. The purpose of this study is to determine the prevalence of malocclusion and orthodontic treatment needs according to the Dental Aesthetic Index (DAI) among Malay transfusion-dependent thalassemia patients. Orientation: This is a cross-sectional study consist of 43 Malay transfusion-dependent thalassemia patients, 22 males, and 19 females with the mean age of 15.9 years old (SD 3.58). The subjects were selected randomly from patients attending Paediatrics and Internal Medicine Clinic at Hospital USM and Hospital Sultana Bahiyah. The subjects were assessed for malocclusion according to Angle’s classification, and orthodontic treatment needs using DAI. The results show that 22 of the subjects (51.1%) have class II malocclusion, 12 subjects (28%) have class І, while 9 subjects (20.9%) have class Ⅲ. The assessment of orthodontic treatment needs to reveal 22 cases (51.1%) fall in the normal/minor needs category, 12 subjects (28%) fall in the severe and very severe category, while 9 subjects (20.9%) fall in the definite category. Conclusion & Significance: Half of Malay transfusion-dependent thalassemia patients have Class Ⅱmalocclusion. About 28% had malocclusion and required orthodontic treatment. This research shows that Malay transfusion-dependent thalassemia may require orthodontic management; earlier intervention to reduce the complexity of the treatment later, suggesting functional appliance as a suitable treatment option for them, a twin block appliance together with headgear to restrict maxillary growth suggested for management. The current protocol implemented by the Malaysian Ministry of Health for the management of these patients seems to be sufficient since the result shows that about 28% require orthodontic treatment need, according to DAI.

Keywords: prevalence, DAI, thalassaemia, angle classification

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Authors: A. D. Rao, Sachiko Mohanty, R. Gayathri, V. Ranga Rao

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Modeling on coupled physical and biogeochemical processes of coastal waters is vital to identify the primary production status under different natural and anthropogenic conditions. About 7, 500 km length of Indian coastline is occupied with number of semi enclosed coastal bodies such as estuaries, inlets, bays, lagoons, and other near shore, offshore shelf waters, etc. This coastline is also rich in wide varieties of ecosystem flora and fauna. Directly/indirectly extensive domestic and industrial sewage enter into these coastal water bodies affecting the ecosystem character and create environment problems such as water quality degradation, hypoxia, anoxia, harmful algal blooms, etc. lead to decline in fishery and other related biological production. The present study is focused on the southeast coast of India, starting from Pulicat to Gulf of Mannar, which is rich in marine diversity such as lagoon, mangrove and coral ecosystem. Three dimensional Massachusetts Institute of Technology general circulation model (MITgcm) along with Darwin biogeochemical module is configured for the western Bay of Bengal (BoB) to study the biogeochemistry over this region. The biogeochemical module resolves the cycling of carbon, phosphorous, nitrogen, silica, iron and oxygen through inorganic, living, dissolved and particulate organic phases. The model domain extends from 4°N-16.5°N and 77°E-86°E with a horizontal resolution of 1 km. The bathymetry is derived from General Bathymetric Chart of the Oceans (GEBCO), which has a resolution of 30 sec. The model is initialized by using the temperature, salinity filed from the World Ocean Atlas (WOA2013) of National Oceanographic Data Centre with a resolution of 0.25°. The model is forced by the surface wind stress from ASCAT and the photosynthetically active radiation from the MODIS-Aqua satellite. Seasonal climatology of nutrients (phosphate, nitrate and silicate) for the southwest BoB region are prepared using available National Institute of Oceanography (NIO) in-situ data sets and compared with the WOA2013 seasonal climatology data. The model simulations with the two different initial conditions viz., WOA2013 and the generated NIO climatology, showed evident changes in the concentration and the evolution of the nutrients in the study region. It is observed that the availability of nutrients is more in NIO data compared to WOA in the model domain. The model simulated primary productivity is compared with the spatially distributed satellite derived chlorophyll data and at various locations with the in-situ data. The seasonal variability of the model simulated primary productivity is also studied.

Keywords: Bay of Bengal, Massachusetts Institute of Technology general circulation model, MITgcm, biogeochemistry, primary productivity

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Authors: Rafik Baouche, Rabah Chaouchi

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This work reports the first comprehensive stress field interpretation from the eleven recently drilled wells in the Berkaoui Basin, Algerian Sahara. A cumulative length of 7000+m acoustic image logs from 06 vertical wells were investigated, and a mean NW-SE (128°-145° N) maximum horizontal stress (SHMax) orientation is inferred from the B-D quality wellbore breakouts. The study integrates log-based approach with the downhole measurements to infer pore pressure, in-situ stress magnitudes. Vertical stress (Sv), interpreted from the bulk-density profiles, has an average gradient of 22.36 MPa/km. The Ordovician and Cambrian reservoirs have a pore pressure gradient of 13.47-13.77 MPa/km, which is more than the hydrostatic pressure regime. A 17.2-18.3 MPa/km gradient of minimum horizontal stress (Shmin) is inferred from the fracture closure pressure in the reservoirs. Breakout widths constrained the SHMax magnitude in the 23.8-26.5 MPa/km range. Subsurface stress distribution in the central Saharan Algeria indicates that the present-day stress field in the Berkaoui Basin is principally strike-slip faulting (SHMax > Sv > Shmin). Inferences are drawn on the regional stress pattern and drilling and reservoir development.

Keywords: stress, imagery, breakouts, sahara

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Authors: Minghui Zhang, Sirine Fkaier, Sabri Fernana, Svetlana Kiseleva, Denis Kiselev

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The real-time identification of bacteria and fungi is difficult because they emit much weaker signals than pollen. In 2020, Plair developed Rapid-E+, which extends abilities of Rapid-E to detect smaller bioaerosols such as bacteria and fungal spores with diameters down to 0.3 µm, while keeping the similar or even better capability for measurements of large bioaerosols like pollen. Rapid-E+ enables simultaneous measurements of (1) time-resolved, polarization and angle dependent Mie scattering patterns, (2) fluorescence spectra resolved in 16 channels, and (3) fluorescence lifetime of individual particles. Moreover, (4) it provides 2D Mie scattering images which give the full information on particle morphology. The parameters of every single bioaerosol aspired into the instrument are subsequently analysed by machine learning. Firstly, pure species of microbes, e.g., Bacillus subtilis (a species of bacteria), and Penicillium chrysogenum (a species of fungal spores), were aerosolized in a bioaerosol chamber for Rapid-E+ training. Afterwards, we tested microbes under different concentrations. We used several steps of data analysis to classify and identify microbes. All single particles were analysed by the parameters of light scattering and fluorescence in the following steps. (1) They were treated with a smart filter block to get rid of non-microbes. (2) By classification algorithm, we verified the filtered particles were microbes based on the calibration data. (3) The probability threshold (defined by the user) step provides the probability of being microbes ranging from 0 to 100%. We demonstrate how Rapid-E+ identified simultaneously microbes based on the results of Bacillus subtilis (bacteria) and Penicillium chrysogenum (fungal spores). By using machine learning, Rapid-E+ achieved identification precision of 99% against the background. The further classification suggests the precision of 87% and 89% for Bacillus subtilis and Penicillium chrysogenum, respectively. The developed algorithm was subsequently used to evaluate the performance of microbe classification and quantification in real-time. The bacteria and fungi were aerosolized again in the chamber with different concentrations. Rapid-E+ can classify different types of microbes and then quantify them in real-time. Rapid-E+ enables classifying different types of microbes and quantifying them in real-time. Rapid-E+ can identify pollen down to species with similar or even better performance than the previous version (Rapid-E). Therefore, Rapid-E+ is an all-in-one instrument which classifies and quantifies not only pollen, but also bacteria and fungi. Based on the machine learning platform, the user can further develop proprietary algorithms for specific microbes (e.g., virus aerosols) and other aerosols (e.g., combustion-related particles that contain polycyclic aromatic hydrocarbons).

Keywords: bioaerosols, laser-induced fluorescence, Mie-scattering, microorganisms

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Authors: Omer Altaf, Liam Wotherspoon, Rolando Orense

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The Wairau Plains are located in the northeast of the South Island of New Zealand, with alluvial deposits of fine-grained silts and sands combined with low-lying topography suggesting the presence of liquefiable deposits over significant portions of the region. Liquefaction manifestations were observed in past earthquakes, including the 1848 Marlborough and 1855 Wairarapa earthquakes, and more recently during the 2013 Lake Grassmere and 2016 Kaikōura earthquakes. Therefore, a good understanding of the deposits that may be susceptible to liquefaction is important for land use planning in the region and to allow developers and asset owners to appropriately address their risk. For this purpose, multiple approaches have been employed to develop regional-scale maps showing the liquefaction vulnerability categories for the region. After applying semi-qualitative criteria linked to geologic age and deposit type, the higher resolution surface mapping of geomorphologic characteristics encompassing the Wairau River and the Opaoa River was used for screening. A detailed basin geologic model developed for groundwater modelling was analysed to provide a higher level of resolution than the surface-geology based classification. This is used to identify the thickness of near-surface gravel deposits, providing an improved understanding of the presence or lack of potentially non-liquefiable crust deposits. This paper describes the methodology adopted for this project and focuses on the influence of geomorphic characteristics and analysis of the detailed geologic basin model on the liquefaction classification of the Lower Wairau Plains.

Keywords: liquefaction, earthquake, cone penetration test, mapping, liquefaction-induced damage

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Authors: Sahin Emrah Amrahov, Fatih Aybar, Serhat Dogan

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In this paper we consider the rule reduct generation problem. Rule Reduct Generation (RG) and Modified Rule Generation (MRG) algorithms, that are used to solve this problem, are well-known. Alternative to these algorithms, we develop Pruning Rule Generation (PRG) algorithm. We compare the PRG algorithm with RG and MRG.

Keywords: rough sets, decision rules, rule induction, classification

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Authors: Rabia Munsaf Khan, Eshrat Fatima

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The analysis of the spatial extent and temporal change of vegetation cover using remotely sensed data is of critical importance to agricultural sciences. Pakistan, being an agricultural country depends on this resource as it makes 70% of the GDP. The case study is of Lal Suhanra National Park, which is not only the biggest forest reserve of Pakistan but also of Asia. The study is performed using different temporal images of Landsat. Also, the results of Landsat are cross-checked by using Sentinel-2 imagery as it has both higher spectral and spatial resolution. Vegetation can easily be detected using NDVI which is a common and widely used index. It is an important vegetation index, widely applied in research on global environmental and climatic change. The images are then classified to observe the change occurred over 15 years. Vegetation cover maps of 2000 and 2016 are used to generate the map of vegetation change detection for the respective years and to find out the changing pattern of vegetation cover. Also, the NDVI values aided in the detection of percentage decrease in vegetation cover. The study reveals that vegetation cover of the area has decreased significantly during the year 2000 and 2016.

Keywords: Landsat, normalized difference vegetation index (NDVI), sentinel 2, Greenland monitoring

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Authors: G. Stamatopoulou, M. Symeonaki, C. Michalopoulou

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In this work, we study the intergenerational social mobility in Greece, in order to provide up-to-date evidence on the changes in the mobility patterns throughout the years. An analysis for both men and women aged between 25-64 years old is carried out. Three main research objectives are addressed. First, we aim to examine the relationship between the socio-economic status of parents and their children. Secondly, we investigate the evolution of the mobility patterns between different birth cohorts. Finally, the role of education is explored in shaping the mobility patterns. For the analysis, we draw data on both parental and individuals' social outcomes from different national databases. The social class of origins and destination is measured according to the European Socio-Economic Classification (ESeC), while the respondents' educational attainment is coded into categories based on the International Standard Classification of Education (ISCED). Applying the Markov transition probability theory, and a range of measures and models, this work focuses on the magnitude and the direction of the movements that take place in the Greek labour market, as well as the level of social fluidity. Three-way mobility tables are presented, where the transition probabilities between the classes of destination and origins are calculated for different cohorts. Additionally, a range of absolute and relative mobility rates, as well as distance measures, are presented. The study covers a large time span beginning in 1940 until 1995, shedding light on the effects of the national institutional processes on the social movements of individuals. Given the evidence on the mobility patterns of the most recent birth cohorts, we also investigate the possible effects of the 2008 economic crisis.

Keywords: cohort analysis, education, Greece, intergenerational mobility, social class

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Authors: Dilusha Rajapakse

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The main reason for printing coloured imageries, pattern or motif onto textiles is to enhance the visual appearance of the surface so that the final textile product would get the required attention from potential customers. Such colours and patterns are permanently applied onto the textiles using conventional static colourants, and we expect such decorations to be last for the entire lifecycle of the textile product. The focus of this research presentation is to discuss the ability to integrate multicolour and pattern changing aesthetics onto textiles with the application of water based photochromic colourants. By adopting a research through design approach, a number of iterative flatbed screen printing experiments were conducted to explore the process of printing water based photochromic colours on textile surfaces. The research resulted in several technical parameters that have to be considered during the process of screen printing. Moreover, a modified printing technique that could be used to apply decorative photographic imagery onto textile with multicolour changing effects was also identified. A number of product applications for such dynamic printed textiles were revealed, and appropriate visual evidence was referred to justify the finding.

Keywords: dynamic aesthetics, multicolour changing textiles, non-emissive colours, printed textile design

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for easy creation and classification of institutional risk profiles supporting endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support set up of the most important risk factors. Subsequently, risk profiles employ risk factors classifier and associated configurations to support digital preservation experts with a semi-automatic estimation of endangerment group for file format risk profiles. Our goal is to make use of an expert knowledge base, accuired through a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation of risk factors for a requried dimension for analysis. Using the naive Bayes method, the decision support system recommends to an expert the matching risk profile group for the previously selected institutional risk profile. The proposed methods improve the visibility of risk factor values and the quality of a digital preservation process. The presented approach is designed to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and values of file format risk profiles. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert and to define its profile group. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: linked open data, information integration, digital libraries, data mining

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Authors: Ahmed A. A. Fadol, Guangji Tong, Wlaa Mohamed

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This paper provides a comprehensive analysis of food insecurity in Sudan, focusing on consumption patterns and their implications, employing the Integrated Food Security Phase Classification (IPC) assessment framework. Years of conflict and economic instability have driven large segments of the population in Sudan into crisis levels of acute food insecurity according to the (IPC). A substantial number of people are estimated to currently face emergency conditions, with an additional sizeable portion categorized under less severe but still extreme hunger levels. In this study, we explore the multifaceted nature of food insecurity in Sudan, considering its historical, political, economic, and social dimensions. An analysis of consumption patterns and trends was conducted, taking into account cultural influences, dietary shifts, and demographic changes. Furthermore, we employ logistic regression and random forest analysis to identify significant independent variables influencing food security status in Sudan. Random forest clearly outperforms logistic regression in terms of area under curve (AUC), accuracy, precision and recall. Forward projections of the IPC for Sudan estimate that 15 million individuals are anticipated to face Crisis level (IPC Phase 3) or worse acute food insecurity conditions between October 2023 and February 2024. Of this, 60% are concentrated in Greater Darfur, Greater Kordofan, and Khartoum State, with Greater Darfur alone representing 29% of this total. These findings emphasize the urgent need for both short-term humanitarian aid and long-term strategies to address Sudan's deepening food insecurity crisis.

Keywords: food insecurity, consumption patterns, logistic regression, random forest analysis

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Authors: K. Sathishkumar, V. Thiagarasu

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Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed.

Keywords: microarray technology, gene expression data, clustering, gene Selection

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Authors: Sang-Keun Moon, Hong-Rok Lim, Jin-O Kim

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This paper presents a Power Quality (PQ) modeling and filtering processes for the distribution system disturbances using recognition learning methods. Typical PQ waveforms with mathematical applications and gathered field data are applied to the proposed models. The objective of this paper is analyzing PQ data with respect to monitoring, discriminating, and evaluating the waveform of power disturbances to ensure the system preventative system failure protections and complex system problem estimations. Examined signal filtering techniques are used for the field waveform noises and feature extractions. Using extraction and learning classification techniques, the efficiency was verified for the recognition of the PQ disturbances with focusing on interactive modeling methods in this paper. The waveform of selected 8 disturbances is modeled with randomized parameters of IEEE 1159 PQ ranges. The range, parameters, and weights are updated regarding field waveform obtained. Along with voltages, currents have same process to obtain the waveform features as the voltage apart from some of ratings and filters. Changing loads are causing the distortion in the voltage waveform due to the drawing of the different patterns of current variation. In the conclusion, PQ disturbances in the voltage and current waveforms indicate different types of patterns of variations and disturbance, and a modified technique based on the symmetrical components in time domain was proposed in this paper for the PQ disturbances detection and then classification. Our method is based on the fact that obtained waveforms from suggested trigger conditions contain potential information for abnormality detections. The extracted features are sequentially applied to estimation and recognition learning modules for further studies.

Keywords: power quality recognition, PQ modeling, waveform feature extraction, disturbance trigger condition, PQ signal filtering

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Authors: Ismail Sualman, Mohd Khairuddin Othman

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General Election has been the backbone of democracy that permits people to choose their representatives as they deem fit. The support preferences of the voter differ from one to another, particularly in a plural society like Malaysia. The turning up of high numbers of young voters during the Malaysia 14th General Election has been said to have been caused by social media including Facebook, Twitter, WhatsApp, Instagram, YouTube and Telegram, WeChat and SMS/MMs. It has been observed that, besides using social media as an interaction tool among social friends, it is also an important source of information to know about issues, politics and politicians. This paper exhibits the role of social media in providing political information to young voters, before an election and during the election campaign. This study examines how this information is being translated into election support. A total of 799 Malay young respondents in Selangor have been surveyed and interviewed. This study revealed that social media has become the source of political information among Malay young voters. This research suggested that social media had a significant effect on the support during the election. Social media plays an important role in carrying information such as current issues, voting trends, candidate imagery and matters that may influence the view of young voters. The information obtained from social media has been translated into a voting decision.

Keywords: social media, political behaviour, voters’ choice, election.

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Authors: Mariza Kaskara, Stella Girtsou, Maria Prodromou, Alexia Tsouni, Christodoulos Mettas, Stavroula Alatza, Kyriaki Fotiou, Marios Tzouvaras, Charalampos Kontoes, Diofantos Hadjimitsis

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Natural hazard assessment and monitoring are crucial components in managing the risks associated with fires, floods, and geohazards, particularly in regions prone to these natural disasters, such as Greece and Cyprus. Recent advancements in technology led to the development of state-of-the-art systems for assessing and monitoring these hazards. These technologies, developed by the BEYOND Center of Excellence of the National Observatory of Athens, have been successfully applied in Greece and are now set to be transferred to Cyprus. The implementation of these advanced technologies in Greece has significantly improved the country's ability to respond to these natural hazards. Enhancing disaster resilience is crucial as it significantly improves our ability to predict, prepare for, and mitigate the impacts of natural disasters, ultimately saving lives and reducing economic losses. For wildfire risk assessment, a scalar wildfire occurrence risk index has been created based on the predictions of machine learning models. Our objective was to train an ML model that learns to derive a fire susceptibility score when given as input a vector of features assigned to certain spatiotemporal coordinates. Predicting fire danger is crucial for the sustainable management of forest fires as it provides essential information for designing effective prevention measures and facilitating response planning for potential fire incidents. For flood risk assessment, a multi-faceted approach has been employed, including the application of remote sensing techniques, the collection and processing of data from population, buildings, technical studies and field visits, as well as hydrological and hydraulic simulations. All input data are used to create precise flood hazard maps according to various flooding scenarios, detailed flood vulnerability and flood exposure maps, which finally produce the flood risk map. Critical points are identified, and mitigation measures are proposed for the worst-case scenario, namely, refuge areas are defined, and escape routes are designed. Flood risk maps can assist in raising awareness and save lives. For geohazards monitoring (e.g., landslides, subsidence), synthetic aperture radar (SAR) and optical satellite imagery have been combined with geomorphological and meteorological data and other landslide/ground deformation contributing factors. To monitor critical infrastructures, including dams, advanced InSAR (Interferometric SAR) methodologies are used for identifying surface movements through time. Monitoring these hazards provides valuable information for understanding processes and could lead to early warning systems to protect people and infrastructure. The success of these systems in Greece has paved the way for their transfer to Cyprus to enhance Cyprus's capabilities in natural hazard assessment and monitoring. This transfer is being made through knowledge transfer activities, fostering continuous collaboration between Greek and Cypriot experts. Furthermore, small demonstration actions are implemented to showcase the effectiveness of these technologies in real-world scenarios. In conclusion, the transfer of advanced natural hazard assessment technologies from Greece to Cyprus represents a significant step forward in enhancing the entire region's resilience to disasters. The EXCELSIOR project, funding this opportunity, is committed to empowering Cyprus with the tools and expertise needed to effectively manage and mitigate the risks associated with these natural hazards. Acknowledgment: Authors acknowledge the 'EXCELSIOR': ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project.

Keywords: earth observation, monitoring, natural hazards, remote sensing

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Authors: Hantian Wu, Bo Huang, Yuan Zeng

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Divisions between wealthy and poor, private and public landscapes are propagated by the increasing economic inequality of cities. While these are the spatial reflections of larger social issues and problems, urban design can at least employ spatial techniques that promote more inclusive rather than exclusive, overlapping rather than segregated, interlinked rather than disconnected landscapes. Indeed, the type of edge or border between urban landscapes plays a critical role in the way the environment is perceived. China experiences rapid urbanization, which poses unpredictable environmental challenges. The urban green cover and water body are under changes, which highly relevant to resident wealth and happiness. However, very limited knowledge and data on their rapid changes are available. In this regard, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understating the driving forces of urban landscape changes can be a significant contribution for urban planning and studying. High-resolution remote sensing data has been widely applied to urban management in China. The map of urban land use map for the entire China of 2018 with 10 meters resolution has been published. However, this research focuses on the large-scale and high-resolution remote sensing land use but does not precisely focus on the seasonal change of urban covers. High-resolution remote sensing data has a long-operation cycle (e.g., Landsat 8 required 16 days for the same location), which is unable to satisfy the requirement of monitoring urban-landscape changes. On the other hand, aerial-remote or unmanned aerial vehicle (UAV) sensing are limited by the aviation-regulation and cost was hardly widely applied in the mega-cities. Moreover, those data are limited by the climate and weather conditions (e.g., cloud, fog), and those problems make capturing spatial and temporal dynamics is always a challenge for the remote sensing community. Particularly, during the rainy season, no data are available even for Sentinel Satellite data with 5 days interval. Many natural events and/or human activities drive the changes of urban covers. In this case, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understanding the mechanism of urban landscape changes can be a significant contribution for urban planning and studying. This project aims to use the high spatiotemporal fusion of remote sensing data to create short-cycle, high-resolution remote sensing data sets for exploring the high-frequently urban cover changes. This research will enhance the long-term monitoring applicability of high spatiotemporal fusion of remote sensing data for the urban landscape for optimizing the urban management of landscape border to promoting the inclusive of the urban landscape to all communities.

Keywords: urban land cover changes, remote sensing, high spatiotemporal fusion, urban management

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Authors: Ali Ashtiani, Hamid Shirazi

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This paper reviews the status of existing practice and research related to measuring pavement cracking and using crack density as a pavement surface evaluation protocol. Crack density for pavement evaluation is currently not widely used within the airport community and its use by the highway community is limited. However, surface cracking is a distress that is closely monitored by airport staff and significantly influences the development of maintenance, rehabilitation and reconstruction plans for airport pavements. Therefore crack density has the potential to become an important indicator of pavement condition if the type, severity and extent of surface cracking can be accurately measured. A pavement distress survey is an essential component of any pavement assessment. Manual crack surveying has been widely used for decades to measure pavement performance. However, the accuracy and precision of manual surveys can vary depending upon the surveyor and performing surveys may disrupt normal operations. Given the variability of manual surveys, this method has shown inconsistencies in distress classification and measurement. This can potentially impact the planning for pavement maintenance, rehabilitation and reconstruction and the associated funding strategies. A substantial effort has been devoted for the past 20 years to reduce the human intervention and the error associated with it by moving toward automated distress collection methods. The automated methods refer to the systems that identify, classify and quantify pavement distresses through processes that require no or very minimal human intervention. This principally involves the use of a digital recognition software to analyze and characterize pavement distresses. The lack of established protocols for measurement and classification of pavement cracks captured using digital images is a challenge to developing a reliable automated system for distress assessment. Variations in types and severity of distresses, different pavement surface textures and colors and presence of pavement joints and edges all complicate automated image processing and crack measurement and classification. This paper summarizes the commercially available systems and technologies for automated pavement distress evaluation. A comprehensive automated pavement distress survey involves collection, interpretation, and processing of the surface images to identify the type, quantity and severity of the surface distresses. The outputs can be used to quantitatively calculate the crack density. The systems for automated distress survey using digital images reviewed in this paper can assist the airport industry in the development of a pavement evaluation protocol based on crack density. Analysis of automated distress survey data can lead to a crack density index. This index can be used as a means of assessing pavement condition and to predict pavement performance. This can be used by airport owners to determine the type of pavement maintenance and rehabilitation in a more consistent way.

Keywords: airport pavement management, crack density, pavement evaluation, pavement management

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Authors: Izabel Cristina Zattar, Gilberto Passos Lima, Guilherme Schünemann de Oliveira

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In Brazil, there are several institutions committed to the development of new businesses based on product innovation. Among them are business incubators, universities and science institutes. Business incubators can be defined as nurseries for new companies, which may be in the technology segment, discussed in this article. Business incubators provide services related to infrastructure, such as physical space and meeting rooms. Besides these services, incubators also offer assistance in the form of information and communication, access to finance, relationship networks and business monitoring and mentoring processes. Business incubators support not all technology companies. One of the business incubators tasks is to assess the nature and feasibility of new business proposals. To assist this goal, this paper proposes a methodology for evaluating new business using the Analytic Hierarchy Process (AHP). This paper presents the concepts used in the assessing methodology application for new business, concepts that have been tested with positive results in practice. This study counts on three main steps: first, a hierarchy was built, based on new business manuals used by the business incubators. These books and manuals relate business selection requirements, such as the innovation status and other technological aspects. Then, a questionnaire was generated, in order to guide incubator experts in the parity comparisons at all hierarchy levels. The weights of each requirement are calculated from information obtained from the questionnaire responses. Finally, the proposed method was applied to evaluate five new business proposals, which were applying to be part of a company incubator. The main result is the classification of these new businesses, which helped the incubator experts to decide what companies were more eligible to work with. This classification may also be helpful to the decision-making process of business incubators in future selection processes.

Keywords: Analytic Hierarchy Process (AHP), Brazilian companies incubators, technology companies, incubator

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Authors: P. Panwalkar, K. Veravalli, R. Gwynn, M. Tofighi, R. Clement, A. Mofidi

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When operating on tibial plateau fracture especially medial tibial plateau, it has regularly been said “where do I put my thumb to reduce the fracture”. This refers to the ideal placement of the buttress device to hold the fracture till union. The aim of this study was to see if one can identify this sweet spot using a CT scan. Methods: Forty-five tibial plateau fractures with medial plateau involvement were identified and included in the study. The preoperative CT scans were analysed and the medial plateau involvement pattern was classified based on modified radiological classification by Yukata et-al of stress fracture of medial tibial plateau. The involvement of part of plateau was compared with position of buttress plate position which was classified as medial posteromedial or both. Presence and position of the buttress was compared with ability to achieve and hold the reduction of the fracture till union. Results: Thirteen fractures were type-1 fracture, 19 fractures were type-2 fracture and 13 fractures were type-3 fracture. Sixteen fractures were buttressed correctly according to the potential deformity and twenty-six fractures were not buttressed and three fractures were partly buttressed correctly. No fracture was over butressed! When the fracture was buttressed correctly the rate of the malunion was 0%. When fracture was partly buttressed 33% were anatomically united and 66% were united in the plane of buttress. When buttress was not used, 14 were malunited, one malunited in one of the two planes of deformity and eleven anatomically healed (of which 9 were non displaced!). Buttressing resulted in statistically significant lower mal-union rate (x2=7.8, p=0.0052). Conclusion: The classification based on involvement of medial condyle can identify the placement of buttress plate in the tibial plateau. The correct placement of the buttress plate results in predictably satisfactory union. There may be a correlation between injury shape of the tibial plateau and the fracture type.

Keywords: knee, tibial plateau, trauma, CT scan, surgery

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Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

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Graphical-based passwords have existed for decades. Their major advantage is that they are easier to remember than an alphanumeric password. However, their disadvantage (especially recognition-based passwords) is the smaller password space, making them more vulnerable to brute force attacks. Graphical passwords are also highly susceptible to the shoulder-surfing effect. The gesture-based password method that we developed is a grid-free, template-free method. In this study, we evaluated the gesture-based passwords for usability and vulnerability. The results of the study are significant. We developed a gesture-based password application for data collection. Two modes of data collection were used: Creation mode and Replication mode. In creation mode (Session 1), users were asked to create six different passwords and reenter each password five times. In replication mode, users saw a password image created by some other user for a fixed duration of time. Three different duration timers, such as 5 seconds (Session 2), 10 seconds (Session 3), and 15 seconds (Session 4), were used to mimic the shoulder-surfing attack. After the timer expired, the password image was removed, and users were asked to replicate the password. There were 74, 57, 50, and 44 users participated in Session 1, Session 2, Session 3, and Session 4 respectfully. In this study, the machine learning algorithms have been applied to determine whether the person is a genuine user or an imposter based on the password entered. Five different machine learning algorithms were deployed to compare the performance in user authentication: namely, Decision Trees, Linear Discriminant Analysis, Naive Bayes Classifier, Support Vector Machines (SVMs) with Gaussian Radial Basis Kernel function, and K-Nearest Neighbor. Gesture-based password features vary from one entry to the next. It is difficult to distinguish between a creator and an intruder for authentication. For each password entered by the user, four features were extracted: password score, password length, password speed, and password size. All four features were normalized before being fed to a classifier. Three different classifiers were trained using data from all four sessions. Classifiers A, B, and C were trained and tested using data from the password creation session and the password replication with a timer of 5 seconds, 10 seconds, and 15 seconds, respectively. The classification accuracies for Classifier A using five ML algorithms are 72.5%, 71.3%, 71.9%, 74.4%, and 72.9%, respectively. The classification accuracies for Classifier B using five ML algorithms are 69.7%, 67.9%, 70.2%, 73.8%, and 71.2%, respectively. The classification accuracies for Classifier C using five ML algorithms are 68.1%, 64.9%, 68.4%, 71.5%, and 69.8%, respectively. SVMs with Gaussian Radial Basis Kernel outperform other ML algorithms for gesture-based password authentication. Results confirm that the shorter the duration of the shoulder-surfing attack, the higher the authentication accuracy. In conclusion, behavioral features extracted from the gesture-based passwords lead to less vulnerable user authentication.

Keywords: authentication, gesture-based passwords, machine learning algorithms, shoulder-surfing attacks, usability

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Authors: Shafqat Ullah Khan, Ammar Nasir

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Using planar antenna array (PAA) in radars, Broadcasting, satellite antennas, and sonar for the detection of targets, Helps provide instant beam pattern control. High flexibility and Adaptability are achieved by multiple beam steering by using a Planar array and are particularly needed in real-life Sanrio’s where the need arises for several high-directivity beams. Faulty sensors in planar arrays generate asymmetry, which leads to service degradation, radiation pattern distortion, and increased levels of sidelobe. The POA, a nature-inspired optimization algorithm, accurately determines faulty sensors within an array, enhancing the reliability and performance of planar array antennas through extensive simulations and experiments. The analysis was done for different types of faults in 7 x 7 and 8 x 8 planar arrays in MATLAB.

Keywords: Planar antenna array, , Pelican optimisation Algorithm, , Faculty sensor, Antenna arrays

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Authors: Carolijn Van Noort

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The aim of this research is to understand how the emerging power bloc BRICS employs infrastructure development narratives to construct a new world order. BRICS is an international body consisting of five emerging countries that collaborate on economic and political issues: Brazil, Russia, India, China, and South Africa. This study explores the projection of infrastructure development narratives through an analysis of BRICS’ attention to infrastructure investment and financing, its support of the New Partnership on African Development and the establishment of the New Development Bank in Shanghai. The theory of Strategic Narratives is used to explore BRICS’ commitment to infrastructure development and to distinguish three layers: system narratives (BRICS as a global actor to propose development reform), identity narratives (BRICS as a collective identity joining efforts to act upon development aspirations) and issue narratives (BRICS committed to a range of issues of which infrastructure development is prominent). The methodology that is employed is a narrative analysis of BRICS’ official documents, media statements, and website imagery. A comparison of these narratives illuminates tensions at the three layers and among the five member states. Identifying tensions among development infrastructure narratives provides an indication of how policymaking for infrastructure development could be improved. Subsequently, it advances BRICS’ ability to act as a global actor to construct a new world order.

Keywords: BRICS, emerging powers, infrastructure development, strategic narratives

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Authors: Zhang Xin

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Barrier lakes are lakes formed by storing water in valleys, river valleys or riverbeds after being blocked by landslide, earthquake, debris flow, and other factors. They have great potential safety hazards. When the water is stored to a certain extent, it may burst in case of strong earthquake or rainstorm, and the lake water overflows, resulting in large-scale flood disasters. In order to ensure the safety of people's lives and property in the downstream, it is very necessary to monitor the barrier lake. However, it is very difficult and time-consuming to manually monitor the barrier lake in high altitude areas due to the harsh climate and steep terrain. With the development of earth observation technology, remote sensing monitoring has become one of the main ways to obtain observation data. Compared with a single satellite, multi-satellite remote sensing cooperative observation has more advantages; its spatial coverage is extensive, observation time is continuous, imaging types and bands are abundant, it can monitor and respond quickly to emergencies, and complete complex monitoring tasks. Monitoring with multi-temporal and multi-platform remote sensing satellites can obtain a variety of observation data in time, acquire key information such as water level and water storage capacity of the barrier lake, scientifically judge the situation of the barrier lake and reasonably predict its future development trend. In this study, The Sarez Lake, which formed on February 18, 1911, in the central part of the Pamir as a result of blockage of the Murgab River valley by a landslide triggered by a strong earthquake with magnitude of 7.4 and intensity of 9, is selected as the research area. Since the formation of Lake Sarez, it has aroused widespread international concern about its safety. At present, the use of mechanical methods in the international analysis of the safety of Lake Sarez is more common, and remote sensing methods are seldom used. This study combines remote sensing data with field observation data, and uses the 'space-air-ground' joint observation technology to study the changes in water level and water storage capacity of Lake Sarez in recent decades, and evaluate its safety. The situation of the collapse is simulated, and the future development trend of Lake Sarez is predicted. The results show that: 1) in recent decades, the water level of Lake Sarez has not changed much and remained at a stable level; 2) unless there is a strong earthquake or heavy rain, it is less likely that the Lake Sarez will be broken under normal conditions, 3) lake Sarez will remain stable in the future, but it is necessary to establish an early warning system in the Lake Sarez area for remote sensing of the area, 4) the coordinative remote sensing observation technology is feasible for the high altitude barrier lake of Sarez.

Keywords: coordinative observation, disaster, remote sensing, geographic information system, GIS

Procedia PDF Downloads 107