Search results for: canopy characters classification
975 A Multi-Scale Approach to Space Use: Habitat Disturbance Alters Behavior, Movement and Energy Budgets in Sloths (Bradypus variegatus)
Authors: Heather E. Ewart, Keith Jensen, Rebecca N. Cliffe
Abstract:
Fragmentation and changes in the structural composition of tropical forests – as a result of intensifying anthropogenic disturbance – are increasing pressures on local biodiversity. Species with low dispersal abilities have some of the highest extinction risks in response to environmental change, as even small-scale environmental variation can substantially impact their space use and energetic balance. Understanding the implications of forest disturbance is therefore essential, ultimately allowing for more effective and targeted conservation initiatives. Here, the impact of different levels of forest disturbance on the space use, energetics, movement and behavior of 18 brown-throated sloths (Bradypus variegatus) were assessed in the South Caribbean of Costa Rica. A multi-scale framework was used to measure forest disturbance, including large-scale (landscape-level classifications) and fine-scale (within and surrounding individual home ranges) forest composition. Three landscape-level classifications were identified: primary forests (undisturbed), secondary forests (some disturbance, regenerating) and urban forests (high levels of disturbance and fragmentation). Finer-scale forest composition was determined using measurements of habitat structure and quality within and surrounding individual home ranges for each sloth (home range estimates were calculated using autocorrelated kernel density estimation [AKDE]). Measurements of forest quality included tree connectivity, density, diameter and height, species richness, and percentage of canopy cover. To determine space use, energetics, movement and behavior, six sloths in urban forests, seven sloths in secondary forests and five sloths in primary forests were tracked using a combination of Very High Frequency (VHF) radio transmitters and Global Positioning System (GPS) technology over an average period of 120 days. All sloths were also fitted with micro data-loggers (containing tri-axial accelerometers and pressure loggers) for an average of 30 days to allow for behavior-specific movement analyses (data analysis ongoing for data-loggers and primary forest sloths). Data-loggers included determination of activity budgets, circadian rhythms of activity and energy expenditure (using the vector of the dynamic body acceleration [VeDBA] as a proxy). Analyses to date indicate that home range size significantly increased with the level of forest disturbance. Female sloths inhabiting secondary forests averaged 0.67-hectare home ranges, while female sloths inhabiting urban forests averaged 1.93-hectare home ranges (estimates are represented by median values to account for the individual variation in home range size in sloths). Likewise, home range estimates for male sloths were 2.35 hectares in secondary forests and 4.83 in urban forests. Sloths in urban forests also used nearly double (median = 22.5) the number of trees as sloths in the secondary forest (median = 12). These preliminary data indicate that forest disturbance likely heightens the energetic requirements of sloths, a species already critically limited by low dispersal ability and rates of energy acquisition. Energetic and behavioral analyses from the data-loggers will be considered in the context of fine-scale forest composition measurements (i.e., habitat quality and structure) and are expected to reflect the observed home range and movement constraints. The implications of these results are far-reaching, presenting an opportunity to define a critical index of habitat connectivity for low dispersal species such as sloths.Keywords: biodiversity conservation, forest disturbance, movement ecology, sloths
Procedia PDF Downloads 114974 The Effectiveness of Virtual Reality Training for Improving Interpersonal Communication Skills: An Experimental Study
Authors: Twinkle Sara Joseph
Abstract:
Virtual reality technology has emerged as a revolutionary power that can transform the education sector in many ways. VR environments can break the boundaries of the traditional classroom setting by immersing the students in realistic 3D environments where they can interact with virtual characters without fearing being judged. Communication skills are essential for every profession, and studies suggest the importance of implementing basic-level communication courses at both the school and graduate levels. Interpersonal communication is a skill that gains prominence as it is required in every profession. Traditional means of training have limitations for trainees as well as participants. The fear of being judged, the audience interaction, and other factors can affect the performance of a participant in a traditional classroom setting. Virtual reality offers a unique opportunity for its users to participate in training that does not set any boundaries that prevent the participants from performing in front of an audience. Specialised applications designed in VR headsets offer a range of training and exercises for participants without any time, space, or audience limitations. The present study aims at measuring the effectiveness of VR training in improving interpersonal communication skills among students. The study uses a mixed-method approach, in which a pre-and post-test will be designed to measure effectiveness. A preliminary selection process involving a questionnaire and a screening test will identify suitable candidates based on their current communication proficiency levels. Participants will undergo specialised training through the VR application Virtual Speech tailored for interpersonal communication and public speaking, designed to operate without the traditional constraints of time, space, or audience. The training's impact will subsequently be measured through situational exercises to engage the participants in interpersonal communication tasks, thereby assessing the improvement in their skills. The significance of this study lies in its potential to provide empirical evidence supporting VR technology's role in enhancing communication skills, thereby offering valuable insights for integrating VR-based methodologies into educational frameworks to prepare students more effectively for their professional futures.Keywords: virtual reality, VR training, interpersonal communication, communication skills, 3D environments
Procedia PDF Downloads 56973 Classify Land Use/Cover Change and Its Impact on Soil Erosion Using GIS from 2005 to 2015 in Nzhelele Valley Limpopo Province, South Africa
Authors: Blessing Mavhuru, Nthaduleni Nethengwe, Hector Chikoore, Onyango Beneah Daniel Odhiambo
Abstract:
The main objective of this study was to classify land use/cover and how it has changed in Nzhelele Valley Limpopo Province, South Africa. The study aimed to identify and analyse the types of land use/cover in the years 2005, 2010, and 2015 with a view to assess the impact on soil erosion over time. Using GIS, the changes within land use/cover were assessed through the classification of satellite images. The study area was classified into four major land cover/use classes, which are vegetation, gravel road, built up land and agricultural fields. Over the period 2005-2015 the resultant land use/cover demonstrated (i) a significant increase (12%) for vegetation cover, (ii) a significant decrease in agriculture (16%) land use/cover, (iii) increase in built-up land (1%), as well as (iv) an increase in gravel roads (3%). This study envisages assisting policy makers in decision making on land use management for Nzhelele Valley.Keywords: land use, land cover, change, soil erosion
Procedia PDF Downloads 254972 Redefining Lesbian Representation: The Evolution of Queer Female Desire in the Films of Céline Sciamma
Authors: Athira Sanjeev
Abstract:
The portrayal of lesbianism in cinema has undergone significant transformations. This study explores the evolving portrayal of lesbianism in the films of French director Céline Sciamma, focusing on how her works have redefined the representation of queer women in contemporary cinema. Through an analysis of Water Lilies (2007), Tomboy (2011), and Portrait of a Lady on Fire (2019), the study investigates the ways in which Sciamma’s films diverge from traditional depictions of lesbianism in film, which often relied on either fetishization or tragedy. Instead, Sciamma adopts a quiet, minimalist style that foregrounds emotional intimacy, offering a more nuanced and authentic portrayal of lesbian relationships. Through a comparative analysis of these films, this research explores the thematic and stylistic progression of Sciamma’s portrayal of lesbianism, highlighting her commitment to centering queer female experiences. The research highlights Sciamma's commitment to focusing on the complexities of desire, identity formation, and the female gaze, particularly through her use of visual storytelling, character development, and narrative silence. Her films emphasize the fluidity of gender and sexuality, portraying lesbianism not as a fixed identity but as part of a broader spectrum of human desire. Sciamma’s nuanced approach resists the traditional marginalization of lesbian characters, allowing them to exist as individuals rather than as plot devices or objects of spectacle. This study draws from queer theory and feminist film criticism to examine how Sciamma challenges conventional heteronormative narratives, prioritizes the female gaze, and subverts traditional cinematic representations of lesbian desire. It also explores how her work contributes to a broader conversation on the representation of queerness in contemporary French cinema, challenging heteronormative paradigms and offering new possibilities for depicting female relationships on screen. By tracing the evolution of her films, this research contributes to broader discussions on LGBTQ+ visibility in cinema and the cultural significance of lesbian representation in contemporary cinema.Keywords: female gaze, feminist film criticism, lesbianism in cinema, queer theory
Procedia PDF Downloads 21971 Historical Studies on Gilt Decorations on Glazed Surfaces
Authors: Sabra Saeidi
Abstract:
This research focuses on the historical techniques associated with the lajevardina and Haft-Rangi production methods in creating tiles, with emphasis on the identification of the techniques of inserting gold sheets on the surface of such historical glazed tiles. In this regard, firstly, the history of the production of enamel, gold plated, and Lajevardina glazed pottery work made during the Khwarizmanshahid and Mongol era (eleventh to the thirteenth century) have been assessed to reach a better understanding of the background and the history associated with historical glazing methods. After the historical overview of the production technique of glazed pottery work and introductions of the civilizations using those techniques, we focused on the niches production methods of enamel and Lajevardina glazing, which are two categories of decorations usually found in tiles. Next, a general classification method for various types of gilt tiles has been introduced, which is applicable to the tile works up to Safavid period (Sixteenth to the seventeenth century). Gilded lajevardina glazed tiles, gilt Haft-Rangi tiles, monolithic glazed gilt tiles, and gilt mosaic tiles are included in the categories.Keywords: gilt tiles, Islamic art, Iranian art, historical studies, gilding
Procedia PDF Downloads 123970 Sentinel-2 Based Burn Area Severity Assessment Tool in Google Earth Engine
Authors: D. Madhushanka, Y. Liu, H. C. Fernando
Abstract:
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
Procedia PDF Downloads 238969 Automated Tracking and Statistics of Vehicles at the Signalized Intersection
Authors: Qiang Zhang, Xiaojian Hu1
Abstract:
Intersection is the place where vehicles and pedestrians must pass through, turn and evacuate. Obtaining the motion data of vehicles near the intersection is of great significance for transportation research. Since there are usually many targets and there are more conflicts between targets, this makes it difficult to obtain vehicle motion parameters in traffic videos of intersections. According to the characteristics of traffic videos, this paper applies video technology to realize the automated track, count and trajectory extraction of vehicles to collect traffic data by roadside surveillance cameras installed near the intersections. Based on the video recognition method, the vehicles in each lane near the intersection are tracked with extracting trajectory and counted respectively in various degrees of occlusion and visibility. The performances are compared with current recognized CPU-based algorithms of real-time tracking-by-detection. The speed of the presented system is higher than the others and the system has a better real-time performance. The accuracy of direction has reached about 94.99% on average, and the accuracy of classification and statistics has reached about 75.12% on average.Keywords: tracking and statistics, vehicle, signalized intersection, motion parameter, trajectory
Procedia PDF Downloads 221968 Application of Lean Manufacturing Tools in Hot Asphalt Production
Authors: S. Bayona, J. Nunez, D. Paez, C. Diaz
Abstract:
The application of Lean manufacturing tools continues to be an effective solution for increasing productivity, reducing costs and eliminating waste in the manufacture of goods and services. This article analyzes the production process of a hot asphalt manufacturing company from an administrative and technical perspective. Three main phases were analyzed, the first phase was related to the determination of the risk priority number of the main operations in asphalt mix production process by an FMEA (Failure Mode Effects Analysis), in the second phase the Value Stream Mapping (VSM) of the production line was performed and in the third phase a SWOT (Strengths, Weaknesses Opportunities, Threats) matrix was constructed. Among the most valued failure modes were the lack training of workers in occupational safety and health issues, the lack of signaling and classification of granulated material, and the overweight of vehicles loaded. The analysis of the results in the three phases agree on the importance of training operational workers, improve communication with external actors in order to minimize delays in material orders and strengthen control suppliers.Keywords: asphalt, lean manufacturing, productivity, process
Procedia PDF Downloads 118967 Data Security: An Enhancement of E-mail Security Algorithm to Secure Data Across State Owned Agencies
Authors: Lindelwa Mngomezulu, Tonderai Muchenje
Abstract:
Over the decades, E-mails provide easy, fast and timely communication enabling businesses and state owned agencies to communicate with their stakeholders and with their own employees in real-time. Moreover, since the launch of Microsoft office 365 and many other clouds based E-mail services, many businesses have been migrating from the on premises E-mail services to the cloud and more precisely since the beginning of the Covid-19 pandemic, there has been a significant increase of E-mails utilization, which then leads to the increase of cyber-attacks. In that regard, E-mail security has become very important in the E-mail transportation to ensure that the E-mail gets to the recipient without the data integrity being compromised. The classification of the features to enhance E-mail security for further from the enhanced cyber-attacks as we are aware that since the technology is advancing so at the cyber-attacks. Therefore, in order to maximize the data integrity we need to also maximize security of the E-mails such as enhanced E-mail authentication. The successful enhancement of E-mail security in the future may lessen the frequency of information thefts via E-mails, resulting in the data of South African State-owned agencies not being compromised.Keywords: e-mail security, cyber-attacks, data integrity, authentication
Procedia PDF Downloads 138966 Numerical Regularization of Ill-Posed Problems via Hybrid Feedback Controls
Authors: Eugene Stepanov, Arkadi Ponossov
Abstract:
Many mathematical models used in biological and other applications are ill-posed. The reason for that is the nature of differential equations, where the nonlinearities are assumed to be step functions, which is done to simplify the analysis. Prominent examples are switched systems arising from gene regulatory networks and neural field equations. This simplification leads, however, to theoretical and numerical complications. In the presentation, it is proposed to apply the theory of hybrid feedback controls to regularize the problem. Roughly speaking, one attaches a finite state control (‘automaton’), which follows the trajectories of the original system and governs its dynamics at the points of ill-posedness. The construction of the automaton is based on the classification of the attractors of the specially designed adjoint dynamical system. This ‘hybridization’ is shown to regularize the original switched system and gives rise to efficient hybrid numerical schemes. Several examples are provided in the presentation, which supports the suggested analysis. The method can be of interest in other applied fields, where differential equations contain step-like nonlinearities.Keywords: hybrid feedback control, ill-posed problems, singular perturbation analysis, step-like nonlinearities
Procedia PDF Downloads 247965 Expansive-Restrictive Style: Conceptualizing Knowledge Workers
Authors: Ram Manohar Singh, Meenakshi Gupta
Abstract:
Various terms such as ‘learning style’, ‘cognitive style’, ‘conceptual style’, ‘thinking style’, ‘intellectual style’ are used in literature to refer to an individual’s characteristic and consistent approach to organizing and processing information. However, style concepts are criticized for mutually overlapping definitions and confusing classification. This confusion should be addressed at the conceptual as well as empirical level. This paper is an attempt to bridge this gap in literature by proposing a new concept: expansive-restrictive intellectual style based on phenomenological analysis of an auto-ethnography and interview of 26 information technology (IT) professionals working in knowledge intensive organizations (KIOs) in India. Expansive style is an individual’s preference to expand his/her horizon of knowledge and understanding by gaining real meaning and structure of his/her work. On the contrary restrictive style is characterized by an individual’s preference to take minimalist approach at work reflected in executing a job efficiently without an attempt to understand the real meaning and structure of the work. The analysis suggests that expansive-restrictive style has three dimensions: (1) field dependence-independence (2) cognitive involvement and (3) epistemological beliefs.Keywords: expansive, knowledge workers, restrictive, style
Procedia PDF Downloads 424964 Challenges in Experimental Testing of a Stiff, Overconsolidated Clay
Authors: Maria Konstadinou, Etienne Alderlieste, Anderson Peccin da Silva, Ben Arntz, Leonard van der Bijl, Wouter Verschueren
Abstract:
The shear strength and compression properties of stiff Boom clay from Belgium at the depth of about 30 m has been investigated by means of cone penetration and laboratory testing. The latter consisted of index classification, constant rate of strain, direct, simple shear, and unconfined compression tests. The Boom clay samples exhibited strong swelling tendencies. The suction pressure was measured via different procedures and has been compared to the expected in-situ stress. The undrained shear strength and OCR profile determined from CPTs is not compatible with the experimental measurements, which gave significantly lower values. The observed response can be attributed to the presence of pre-existing discontinuities, as shown in microscale CT scans of the samples. The results of this study demonstrate that the microstructure of the clay prior to testing has an impact on the mechanical behaviour and can cause inconsistencies in the comparison of the laboratory test results with in-situ data.Keywords: boom clay, laboratory testing, overconsolidation ratio, stress-strain response, swelling, undrained shear strength
Procedia PDF Downloads 147963 Artificial Reproduction System and Imbalanced Dataset: A Mendelian Classification
Authors: Anita Kushwaha
Abstract:
We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance.Keywords: bio-inspired computation, nature- inspired computation, natural computing, data mining
Procedia PDF Downloads 274962 Costume Portrayal In K. Asif’s Mughal E Azam
Authors: Anketa Kumar, Rajantheran Al Muniandy, Rishabh Kumar
Abstract:
For centuries, Indian costumes are admired for their great aesthetics, functional and narrative qualities. The purpose of the current study is to investigate the role of costumes as visual narratives in Hindi Cinema as Filmmaking is simply one of the most recent manifestations of the human desire to tell stories in which costume acts as a tool to be read as an Intertext by the viewers watching the films. The problem that promoted this study arose when clothes become an interesting topic when examined within the social structures in which they are worn. It is this visual image of dress worn by the character that is investigated in this research through Hindi Cinema of the 1960s, which was a reflection of the society in the realistic form. This research intends to integrate the application of Roland Barthes Semiotic theory in analyzing main movie characters in the National Award-Winning Hindi movie Mughal e Azam (1960). The research helps in filling the gap between the singular level of interpretation and another level that offers a solution towards bridging the gap in viewers' manifold interpretation of a particular movie product. This study focuses on how visual appearance communicates for building up of perception and can relate to notions of realism, defining cultural identity and status in the society. The research methodology is subjected analytical technique that employs in this research is qualitative and descriptive in nature with the use of the Freeze frame technique. The portrayal of costumes is explained with Barthes' principles of Semiotics. The freeze-frame technique stops the motion of the film on a single frame and allows the chosen image to be read as a still photograph. The finding during this research into costume portrayal in the movie was that freezing the frame in midst of running the films attracted attention towards intricate costume details, leading to record the nuanced observations of this minutiae during the movie. Given that during the application of interpretation while watching K Asif’s Mughal e Azam focused on certain aspects of costumes of the king. On the same idea, further research can be employed to strengthen the relation between costumes and visual narration.Keywords: character portrayal, costumes, Indian cinema, semiotics, visual significance
Procedia PDF Downloads 187961 Electromyography Pattern Classification with Laplacian Eigenmaps in Human Running
Authors: Elnaz Lashgari, Emel Demircan
Abstract:
Electromyography (EMG) is one of the most important interfaces between humans and robots for rehabilitation. Decoding this signal helps to recognize muscle activation and converts it into smooth motion for the robots. Detecting each muscle’s pattern during walking and running is vital for improving the quality of a patient’s life. In this study, EMG data from 10 muscles in 10 subjects at 4 different speeds were analyzed. EMG signals are nonlinear with high dimensionality. To deal with this challenge, we extracted some features in time-frequency domain and used manifold learning and Laplacian Eigenmaps algorithm to find the intrinsic features that represent data in low-dimensional space. We then used the Bayesian classifier to identify various patterns of EMG signals for different muscles across a range of running speeds. The best result for vastus medialis muscle corresponds to 97.87±0.69 for sensitivity and 88.37±0.79 for specificity with 97.07±0.29 accuracy using Bayesian classifier. The results of this study provide important insight into human movement and its application for robotics research.Keywords: electromyography, manifold learning, ISOMAP, Laplacian Eigenmaps, locally linear embedding
Procedia PDF Downloads 365960 Soil Sensibility Characterization of Granular Soils Due to Suffusion
Authors: Abdul Rochim, Didier Marot, Luc Sibille
Abstract:
This paper studies the characterization of soil sensibility due to suffusion process by carrying out a series of one-dimensional downward seepage flow tests realized with an erodimeter. Tests were performed under controlled hydraulic gradient in sandy gravel soils. We propose the analysis based on energy induced by the seepage flow to characterize the hydraulic loading and the cumulative eroded dry mass to characterize the soil response. With this approach, the effect of hydraulic loading histories and initial fines contents to soil sensibility are presented. It is found that for given soils, erosion coefficients are different if tests are performed under different hydraulic loading histories. For given initial fines fraction contents, the sensibility may be grouped in the same classification. The lower fines content soils tend to require larger flow energy to the onset of erosion. These results demonstrate that this approach is effective to characterize suffusion sensibility for granular soils.Keywords: erodimeter, sandy gravel, suffusion, water seepage energy
Procedia PDF Downloads 447959 KSVD-SVM Approach for Spontaneous Facial Expression Recognition
Authors: Dawood Al Chanti, Alice Caplier
Abstract:
Sparse representations of signals have received a great deal of attention in recent years. In this paper, the interest of using sparse representation as a mean for performing sparse discriminative analysis between spontaneous facial expressions is demonstrated. An automatic facial expressions recognition system is presented. It uses a KSVD-SVM approach which is made of three main stages: A pre-processing and feature extraction stage, which solves the problem of shared subspace distribution based on the random projection theory, to obtain low dimensional discriminative and reconstructive features; A dictionary learning and sparse coding stage, which uses the KSVD model to learn discriminative under or over dictionaries for sparse coding; Finally a classification stage, which uses a SVM classifier for facial expressions recognition. Our main concern is to be able to recognize non-basic affective states and non-acted expressions. Extensive experiments on the JAFFE static acted facial expressions database but also on the DynEmo dynamic spontaneous facial expressions database exhibit very good recognition rates.Keywords: dictionary learning, random projection, pose and spontaneous facial expression, sparse representation
Procedia PDF Downloads 308958 Decolonial Aesthetics in Ronnie Govender’s at the Edge and Other Cato Manor Stories
Authors: Rajendra Chetty
Abstract:
Decolonial aesthetics departs and delinks from colonial ideas about ‘the arts’ and the modernist/colonial work of aesthetics. Education is trapped in the western epistemic and hermeneutical vocabulary, hence it is necessary to introduce new concepts and work the entanglement between co-existing concepts. This paper will discuss the contribution of Ronnie Govender, a South African writer, to build decolonial sensibilities and delink from the grand narrative of the colonial and apartheid literary landscape in Govender’s text, At the Edge and other Cato Manor Stories. Govender uses the world of art to make a decolonial statement. Decolonial artists have to work in the entanglement of power and engage with a border epistemology. Govender’s writings depart from an embodied consciousness of the colonial wound and moves toward healing. Border thinking and doing (artistic creativity) is precisely the decolonial methodology posited by Linda T. Smith, where theory comes in the form of storytelling. Govender’s stories engage with the wounds infringed by racism and patriarchy, two pillars of eurocentric knowing, sensing, and believing that sustain a structure of knowledge. This structure is embedded in characters, institutions, languages that regulate and mange the world of the excluded. Healing is the process of delinking, or regaining pride, dignity, and humanity, not through the psychoanalytic cure, but the popular healer. The legacies of the community of Cato Manor that was pushed out of their land are built in his stories. Decoloniality then is a concept that carries the experience of liberation struggles and recognizes the strenuous conditions of marginalized people together with their strength, wisdom, and endurance. Govender’s unique performative prose reconstructs and resurrects the lives of the people of Cato Manor, their vitality and humor, pain and humiliation: a vibrant and racially integrated community destroyed by the regime’s notorious racial laws. The paper notes that Govender’s objective with his plays and stories was to open windows to both the pain and joy of life; a mission that is not didactic but to shine a torch on both mankind’s waywardness as well as its inspiring and often moving achievements against huge odds.Keywords: Govender, decoloniality, delinking, exclusion, racism, Cato Manor
Procedia PDF Downloads 158957 The Best Prediction Data Mining Model for Breast Cancer Probability in Women Residents in Kabul
Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini
Abstract:
The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.Keywords: decision tree, breast cancer, probability, data mining
Procedia PDF Downloads 140956 Spare Part Inventory Optimization Policy: A Study Literature
Authors: Zukhrof Romadhon, Nani Kurniati
Abstract:
Availability of Spare parts is critical to support maintenance tasks and the production system. Managing spare part inventory deals with some parameters and objective functions, as well as the tradeoff between inventory costs and spare parts availability. Several mathematical models and methods have been developed to optimize the spare part policy. Many researchers who proposed optimization models need to be considered to identify other potential models. This work presents a review of several pertinent literature on spare part inventory optimization and analyzes the gaps for future research. Initial investigation on scholars and many journal database systems under specific keywords related to spare parts found about 17K papers. Filtering was conducted based on five main aspects, i.e., replenishment policy, objective function, echelon network, lead time, model solving, and additional aspects of part classification. Future topics could be identified based on the number of papers that haven’t addressed specific aspects, including joint optimization of spare part inventory and maintenance.Keywords: spare part, spare part inventory, inventory model, optimization, maintenance
Procedia PDF Downloads 65955 Unseen Classes: The Paradigm Shift in Machine Learning
Authors: Vani Singhal, Jitendra Parmar, Satyendra Singh Chouhan
Abstract:
Unseen class discovery has now become an important part of a machine-learning algorithm to judge new classes. Unseen classes are the classes on which the machine learning model is not trained on. With the advancement in technology and AI replacing humans, the amount of data has increased to the next level. So while implementing a model on real-world examples, we come across unseen new classes. Our aim is to find the number of unseen classes by using a hierarchical-based active learning algorithm. The algorithm is based on hierarchical clustering as well as active sampling. The number of clusters that we will get in the end will give the number of unseen classes. The total clusters will also contain some clusters that have unseen classes. Instead of first discovering unseen classes and then finding their number, we directly calculated the number by applying the algorithm. The dataset used is for intent classification. The target data is the intent of the corresponding query. We conclude that when the machine learning model will encounter real-world data, it will automatically find the number of unseen classes. In the future, our next work would be to label these unseen classes correctly.Keywords: active sampling, hierarchical clustering, open world learning, unseen class discovery
Procedia PDF Downloads 173954 Using Trip Planners in Developing Proper Transportation Behavior
Authors: Grzegorz Sierpiński, Ireneusz Celiński, Marcin Staniek
Abstract:
The article discusses multi modal mobility in contemporary societies as a main planning and organization issue in the functioning of administrative bodies, a problem which really exists in the space of contemporary cities in terms of shaping modern transport systems. The article presents classification of available resources and initiatives undertaken for developing multi modal mobility. Solutions can be divided into three groups of measures–physical measures in the form of changes of the transport network infrastructure, organizational ones (including transport policy) and information measures. The latter ones include in particular direct support for people travelling in the transport network by providing information about ways of using available means of transport. A special measure contributing to this end is a trip planner. The article compares several selected planners. It includes a short description of the Green Travelling Project, which aims at developing a planner supporting environmentally friendly solutions in terms of transport network operation. The article summarizes preliminary findings of the project.Keywords: mobility, modal split, multimodal trip, multimodal platforms, sustainable transport
Procedia PDF Downloads 412953 Machine Learning-Driven Prediction of Cardiovascular Diseases: A Supervised Approach
Authors: Thota Sai Prakash, B. Yaswanth, Jhade Bhuvaneswar, Marreddy Divakar Reddy, Shyam Ji Gupta
Abstract:
Across the globe, there are a lot of chronic diseases, and heart disease stands out as one of the most perilous. Sadly, many lives are lost to this condition, even though early intervention could prevent such tragedies. However, identifying heart disease in its initial stages is not easy. To address this challenge, we propose an automated system aimed at predicting the presence of heart disease using advanced techniques. By doing so, we hope to empower individuals with the knowledge needed to take proactive measures against this potentially fatal illness. Our approach towards this problem involves meticulous data preprocessing and the development of predictive models utilizing classification algorithms such as Support Vector Machines (SVM), Decision Tree, and Random Forest. We assess the efficiency of every model based on metrics like accuracy, ensuring that we select the most reliable option. Additionally, we conduct thorough data analysis to reveal the importance of different attributes. Among the models considered, Random Forest emerges as the standout performer with an accuracy rate of 96.04% in our study.Keywords: support vector machines, decision tree, random forest
Procedia PDF Downloads 42952 A Consideration of Dialectal and Stylistic Shifts in Literary Translation
Authors: Pushpinder Syal
Abstract:
Literary writing carries the stamp of the current language of its time. In translating such texts, it becomes a challenge to capture such reflections which may be evident at several levels: the level of dialectal use of language by characters in stories, the alterations in syntax as tools of writers’ individual stylistic choices, the insertion of quasi-proverbial and gnomic utterances, and even the level of the pragmatics of narrative discourse. Discourse strategies may differ between earlier and later texts, reflecting changing relationships between narrators and readers in changed cultural and social contexts. This paper is a consideration of these features by an approach that combines historicity with a description, contextualizing language change within a discourse framework. The process of translating a collection of writings of Punjabi literature spanning 100 years was undertaken for this study and it was observed that the factor of the historicity of language was seen to play a role. While intended for contemporary readers, the translation of literature over the span of a century poses the dual challenge of needing to possess both accessibility and immediacy as well as adherence to the 'old world' styles of communicating and narrating. The linguistic changes may be observed in a more obvious sense in the difference of diction and word formation – with evidence of more hybridized and borrowed forms in modern and contemporary writings, as compared to the older writings. The latter not only contain vestiges of proverbs and folk sayings, but are also closer to oral speech styles. These will be presented and analysed in the form of chronological listing and by these means, the social process of translation from orality to written text can be seen as traceable in the above-mentioned works. More subtle and underlying shifts can be seen through the analysis of speech acts and implicatures in the same literature, in which the social relationships underlying language use are evident as discourse systems of belief and understanding. They present distinct shifts in worldview as seen at different points in time. However, some continuities of language and style are also clearly visible, and these aid the translator in putting together a set of thematic links which identify the literature of a region and community, and constitute essential outcomes in the effort to preserve its distinctive nature.Keywords: cultural change, dialect, historicity, stylistic variation
Procedia PDF Downloads 130951 A Geographical Framework for Studying the Territorial Sustainability Based on Land Use Change
Authors: Miguel Ramirez, Ivan Lizarazo
Abstract:
The emergence of various interpretations of sustainability, including weak and strong paradigms, can be traced back to the definition of sustainable development provided in the 1987 Brundtland report and the subsequent evolution of the sustainability concept. However, there has been limited scholarly attention given to clarifying the concept of sustainability within the theoretical and conceptual framework of geography. The discipline has predominantly been focused on understanding the diverse conceptions of sustainability within its epistemological boundaries, resulting in tensions between sustainability paradigms and their associated dimensions, including the incorporation of political perspectives, with particular emphasis on environmental geography's epistemology. In response to this gap, a conceptual framework for sustainability is proposed, effectively integrating spatial and territorial concepts. This framework aims to enhance geography's role in contributing to sustainability by utilizing the land system theory, which is based on the dynamics of land use change. Such an integrated conceptual framework enables incorporating methodological tools such as remote sensing, encompassing various earth observations and fusion methods, and supervised classification techniques. Additionally, it looks for better integration of socioecological information, thereby capturing essential population-related features.Keywords: geography, sustainability, land change science, territorial sustainability
Procedia PDF Downloads 86950 Meta-Instruction Theory in Mathematics Education and Critique of Bloom’s Theory
Authors: Abdollah Aliesmaeili
Abstract:
The purpose of this research is to present a different perspective on the basic math teaching method called meta-instruction, which reverses the learning path. Meta-instruction is a method of teaching in which the teaching trajectory starts from brain education into learning. This research focuses on the behavior of the mind during learning. In this method, students are not instructed in mathematics, but they are educated. Another goal of the research is to "criticize Bloom's classification in the cognitive domain and reverse it", because it cannot meet the educational and instructional needs of the new generation and "substituting math education instead of math teaching". This is an indirect method of teaching. The method of research is longitudinal through four years. Statistical samples included students ages 6 to 11. The research focuses on improving the mental abilities of children to explore mathematical rules and operations by playing only with eight measurements (any years 2 examinations). The results showed that there is a significant difference between groups in remembering, understanding, and applying. Moreover, educating math is more effective than instructing in overall learning abilities.Keywords: applying, Bloom's taxonomy, brain education, mathematics teaching method, meta-instruction, remembering, starmath method, understanding
Procedia PDF Downloads 24949 Variation in the Morphology of Soft Palate
Authors: Hema Lattupalli
Abstract:
Introduction: The palate forms a partition between the oral cavity and nasal cavity. The palate is made up of two parts hard palate and soft palate. The Hard palate forms the anterior part of the palate, the soft palate forms a movable muscular fold covered by mucous membrane that is suspended from the posterior border of a hard palate. Aim and Objectives: Soft palate morphological variations have a great paucity in the literature. It’s also believed that the soft palate has no such important anatomical variations. There is a variable presentation of the soft palate morphology in the lateral cephalograms. The aim of this study is to identify the velar morphology. Materials and Methods: 100 normal subjects between the age group of 20 – 35 were taken for the study. Method: Lateral Cephalogram (radiologic study). Results: Different shapes of the soft palate were observed in the lateral cephalograms. The morphology of soft palate was classified into six types 1.Leaf like (50 cases) most common type, 2.Straight line (20 cases), 3.S shaped (4 cases) very rare, 4.Butt like (10 cases), 5. Rat tail (6 cases), 6. Hook shaped (10 cases). Conclusion: This classification helps us to understand the better diversity of the velar morphology in mid-sagittal plane. These findings help us to understand the etiology of OSAS.Keywords: soft palate, cephalometric radiographs, morphology, cleft palate, obstructive sleep apnoea syndrome
Procedia PDF Downloads 363948 Extraction of Urban Land Features from TM Landsat Image Using the Land Features Index and Tasseled Cap Transformation
Authors: R. Bouhennache, T. Bouden, A. A. Taleb, A. Chaddad
Abstract:
In this paper we propose a method to map the urban areas. The method uses an arithmetic calculation processed from the land features indexes and Tasseled cap transformation TC of multi spectral Thematic Mapper Landsat TM image. For this purpose the derived indexes image from the original image such SAVI the soil adjusted vegetation index, UI the urban Index, and EBBI the enhanced built up and bareness index were staked to form a new image and the bands were uncorrelated, also the Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID) supervised classification approaches were first applied on the new image TM data using the reference spectra of the spectral library and subsequently the four urban, vegetation, water and soil land cover categories were extracted with their accuracy assessment.The urban features were represented using a logic calculation applied to the brightness, UI-SAVI, NDBI-greenness and EBBI- brightness data sets. The study applied to Blida and mentioned that the urban features can be mapped with an accuracy ranging from 92 % to 95%.Keywords: EBBI, SAVI, Tasseled Cap Transformation, UI
Procedia PDF Downloads 484947 Visual Thing Recognition with Binary Scale-Invariant Feature Transform and Support Vector Machine Classifiers Using Color Information
Authors: Wei-Jong Yang, Wei-Hau Du, Pau-Choo Chang, Jar-Ferr Yang, Pi-Hsia Hung
Abstract:
The demands of smart visual thing recognition in various devices have been increased rapidly for daily smart production, living and learning systems in recent years. This paper proposed a visual thing recognition system, which combines binary scale-invariant feature transform (SIFT), bag of words model (BoW), and support vector machine (SVM) by using color information. Since the traditional SIFT features and SVM classifiers only use the gray information, color information is still an important feature for visual thing recognition. With color-based SIFT features and SVM, we can discard unreliable matching pairs and increase the robustness of matching tasks. The experimental results show that the proposed object recognition system with color-assistant SIFT SVM classifier achieves higher recognition rate than that with the traditional gray SIFT and SVM classification in various situations.Keywords: color moments, visual thing recognition system, SIFT, color SIFT
Procedia PDF Downloads 471946 Hate Speech Detection in Tunisian Dialect
Authors: Helmi Baazaoui, Mounir Zrigui
Abstract:
This study addresses the challenge of hate speech detection in Tunisian Arabic text, a critical issue for online safety and moderation. Leveraging the strengths of the AraBERT model, we fine-tuned and evaluated its performance against the Bi-LSTM model across four distinct datasets: T-HSAB, TNHS, TUNIZI-Dataset, and a newly compiled dataset with diverse labels such as Offensive Language, Racism, and Religious Intolerance. Our experimental results demonstrate that AraBERT significantly outperforms Bi-LSTM in terms of Recall, Precision, F1-Score, and Accuracy across all datasets. The findings underline the robustness of AraBERT in capturing the nuanced features of Tunisian Arabic and its superior capability in classification tasks. This research not only advances the technology for hate speech detection but also provides practical implications for social media moderation and policy-making in Tunisia. Future work will focus on expanding the datasets and exploring more sophisticated architectures to further enhance detection accuracy, thus promoting safer online interactions.Keywords: hate speech detection, Tunisian Arabic, AraBERT, Bi-LSTM, Gemini annotation tool, social media moderation
Procedia PDF Downloads 16