Search results for: soil classification

Authors: Haojie Wang, Xun Li, Rui Yin

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In order to solve the memorization overfitting in the model-agnostic meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to an exponential growth of computation, this paper also proposes a key data extraction method that only extract part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: mutex task generation, data augmentation, meta-learning, text classification.

Procedia PDF Downloads 143

Authors: Yao-Hong Tsai

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This paper presents a weighted approach to unconstrained iris recognition. Nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.

Keywords: authentication, iris recognition, adaboost, local binary pattern

Procedia PDF Downloads 225

Authors: Omar Nouri, Wafa Mnejja, Fatma Dhouib, Syrine Zouari, Wicem Siala, Ilhem Charfeddine, Afef Khanfir, Leila Farhat, Nejla Fourati, Jamel Daoud

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Purpose and Objective: Intensity modulated radiation (IMRT) technique, associated with induction chemotherapy (IC) and/or concomitant chemotherapy (CC), is actually the recommended treatment modality for nasopharyngeal carcinomas (NPC). The aim of this study was to evaluate the therapeutic results and the patterns of relapse with this treatment protocol. Material and methods: A retrospective monocentric study of 145 patients with NPC treated between June 2016 and July 2021. All patients received IMRT with integrated simultaneous boost (SIB) of 33 daily fractions at a dose of 69.96 Gy for high-risk volume, 60 Gy for intermediate risk volume and 54 Gy for low-risk volume. The high-risk volume dose was 66.5 Gy in children. Survival analysis was performed according to the Kaplan-Meier method, and the Log-rank test was used to compare factors that may influence survival. Results: Median age was 48 years (11-80) with a sex ratio of 2.9. One hundred-twenty tumors (82.7%) were classified as stages III-IV according to the 2017 UICC TNM classification. Ten patients (6.9%) were metastatic at diagnosis. One hundred-thirty-five patient (93.1%) received IC, 104 of which (77%) were TPF-based (taxanes, cisplatin and 5 fluoro-uracil). One hundred-thirty-eight patient (95.2%) received CC, mostly cisplatin in 134 cases (97%). After a median follow-up of 50 months [22-82], 46 patients (31.7%) had a relapse: 12 (8.2%) experienced local and/or regional relapse after a median of 18 months [6-43], 29 (20%) experienced distant relapse after a median of 9 months [2-24] and 5 patients (3.4%) had both. Thirty-five patients (24.1%) died, including 5 (3.4%) from a cause other than their cancer. Three-year overall survival (OS), cancer specific survival, disease free survival, metastasis free survival and loco-regional free survival were respectively 78.1%, 81.3%, 67.8%, 74.5% and 88.1%. Anatomo-clinic factors predicting OS were age > 50 years (88.7 vs. 70.5%; p=0.004), diabetes history (81.2 vs. 66.7%; p=0.027), UICC N classification (100 vs. 95 vs. 77.5 vs. 68.8% respectively for N0, N1, N2 and N3; p=0.008), the practice of a lymph node biopsy (84.2 vs. 57%; p=0.05), and UICC TNM stages III-IV (93.8 vs. 73.6% respectively for stage I-II vs. III-IV; p=0.044). Therapeutic factors predicting OS were a number of CC courses (less than 4 courses: 65.8 vs. 86%; p=0.03, less than 5 courses: 71.5 vs. 89%; p=0.041), a weight loss > 10% during treatment (84.1 vs. 60.9%; p=0.021) and a total cumulative cisplatin dose, including IC and CC, < 380 mg/m² (64.4 vs. 87.6%; p=0.003). Radiotherapy delay and total duration did not significantly affect OS. No grade 3-4 late side effects were noted in the evaluable 127 patients (87.6%). The most common toxicity was dry mouth which was grade 2 in 47 cases (37%) and grade 1 in 55 cases (43.3%).Conclusion: IMRT for nasopharyngeal carcinoma granted a high loco-regional control rate for patients during the last five years. However, distant relapses remain frequent and conditionate the prognosis. We identified many anatomo-clinic and therapeutic prognosis factors. Therefore, high-risk patients require a more aggressive therapeutic approach, such as radiotherapy dose escalation or adding adjuvant chemotherapy.

Keywords: therapeutic results, prognostic factors, intensity-modulated radiotherapy, nasopharyngeal carcinoma

Procedia PDF Downloads 64

Authors: Sheldon Liu, Gordon Wang, Lei Liu, Xuefeng Liu

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Anomaly detection, also referred to as one-class classification, plays a crucial role in identifying product images that deviate from the expected distribution. This study introduces Data-centric Anomaly Detection with Diffusion Models (DCADDM), presenting a systematic strategy for data collection and further diversifying the data with image generation via diffusion models. The algorithm addresses data collection challenges in real-world scenarios and points toward data augmentation with the integration of generative AI capabilities. The paper explores the generation of normal images using diffusion models. The experiments demonstrate that with 30% of the original normal image size, modeling in an unsupervised setting with state-of-the-art approaches can achieve equivalent performances. With the addition of generated images via diffusion models (10% equivalence of the original dataset size), the proposed algorithm achieves better or equivalent anomaly localization performance.

Keywords: diffusion models, anomaly detection, data-centric, generative AI

Procedia PDF Downloads 82

Authors: H. J. Wattimanela, U. S. Passaribu, N. T. Puspito, S. W. Indratno

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Banda Sea collision zone (BSCZ) of is the result of the interaction and convergence of Indo-Australian plate, Eurasian plate and Pacific plate. This location in the eastern part of Indonesia. This zone has a very high seismic activity. In this research, we will be calculated rate (λ) and Mean Square Eror (MSE). By this result, we will identification of Poisson distribution of earthquakes in the BSCZ with the point process approach. Chi-square test approach and test Anscombe made in the process of identifying a Poisson distribution in the partition area. The data used are earthquakes with Magnitude ≥ 6 SR and its period 1964-2013 and sourced from BMKG Jakarta. This research is expected to contribute to the Moluccas Province and surrounding local governments in performing spatial plan document related to disaster management.

Keywords: molluca banda sea collision zone, earthquakes, mean square error, poisson distribution, chi-square test, anscombe test

Procedia PDF Downloads 300

Authors: Joy Aworookoroh

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Writing is one of the active skills in language learning. Students of English as a foreign language are expected to write efficiently and proficiently in the language; however, there are usually challenges to optimal performance and competence in writing. Errors, on the other hand, in a foreign language learning situation are more positive than negative as they provide the basis for solving the limitations of the students. This paper investigates the situation in the Department of English, Taraba State University Jalingo. Students are administered a descriptive writing test across different levels of study. The target students are multilingual with an L1 of either Kuteb, Hausa or Junkun languages. The essays are accessed to identify the different kinds of errors in them alongside the classification of the order. Errors of correctness, clarity, engagement, and delivery were identified. However, the study identified that the degree of errors reduces alongside the experience and exposure of the students to an EFL classroom.

Keywords: errors, writings, descriptive essay, multilingual

Procedia PDF Downloads 63

Authors: Elena B. Cherepetskaya, Vladimir A. Makarov, Dmitry V. Morozov, Ivan E. Sas

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Laboratory studies of the stress-strain behavior of rocks specimens were conducted by using acoustic emission and laser-ultrasonic diagnostics. The sensitivity of the techniques allowed changes in the internal structure of the specimens under uniaxial compressive load to be examined at micro- and macro scales. It was shown that microcracks appear in geologic materials when the stress level reaches about 50% of breaking strength. Also, the characteristic stress of the main crack formation was registered in the process of single-stage compression of rocks. On the base of laser-ultrasonic echoscopy, 2D visualization of the internal structure of rocky soil specimens was realized, and the microcracks arising during uniaxial compression were registered.

Keywords: acoustic emission, geomaterial, laser ultrasound, uniaxial compression

Procedia PDF Downloads 375

Authors: Donya Ashtiani Haghighi, Amirali Baniasadi

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Coronavirus (COVID-19) disease has spread abruptly all over the world since the end of 2019. Computed tomography (CT) scans and X-ray images are used to detect this disease. Different Deep Neural Network (DNN)-based diagnosis solutions have been developed, mainly based on Convolutional Neural Networks (CNNs), to accelerate the identification of COVID-19 cases. However, CNNs lose important information in intermediate layers and require large datasets. In this paper, Capsule Network (CapsNet) is used. Capsule Network performs better than CNNs for small datasets. Accuracy of 0.9885, f1-score of 0.9883, precision of 0.9859, recall of 0.9908, and Area Under the Curve (AUC) of 0.9948 are achieved on the Capsule-based framework with hyperparameter tuning. Moreover, different dropout rates are investigated to decrease overfitting. Accordingly, a dropout rate of 0.1 shows the best results. Finally, we remove one convolution layer and decrease the number of trainable parameters to 146,752, which is a promising result.

Keywords: capsule network, dropout, hyperparameter tuning, classification

Procedia PDF Downloads 78

Authors: Marie Bieber, Fabrice Cosson, Olivier Schmitt

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Europe's Global Navigation Satellite System, Galileo, provides worldwide positioning and navigation services. The satellites in space are only one part of the Galileo system. An extensive ground infrastructure is essential to oversee the satellites and ensure accurate navigation signals. High reliability and availability of the entire Galileo system are crucial to continuously provide positioning information of high quality to users. Outages are tracked, and operational availability is regularly assessed. A highly flexible and adaptive tool has been developed to automate the Galileo system availability analysis. Not only does it enable a quick availability consolidation, but it also provides first steps towards improving the data quality of maintenance tickets used for the analysis. This includes data import and data preparation, with a focus on processing strings used for classification and identifying faulty data. Furthermore, the tool allows to handle a low amount of data, which is a major constraint when the aim is to provide accurate statistics.

Keywords: availability, data quality, system performance, Galileo, aerospace

Procedia PDF Downloads 167

Authors: D. N. Kambrekar, S. B. Jagginavar, J. Aruna

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Grape stem borer, Celosterna scrabrator is an important production constraint in grapes in India. Hitherto this pest was a severe menace only on the aged and unmanaged fields but during the recent past it has also started damaging the newly established fields. In India, since Karnataka, Andra Pradesh, Tamil Nadu and Maharashtra are the major grape production states, the incidence of stem borer is also restricted and severe in these states. The grubs of the beetle bore in to the main stem and even the branches, which affect the translocation of nutrients to the areal parts of the plant. Since, the grubs bore inside the stem, the chewed material along with its excreta is discharged outside the holes and the frass is found on the ground just below the bored holes. The portion of vines above the damaged part has a sticky appearance. The leaves become pale yellow which looks like a deficiency of micronutrients. The leaves ultimately dry and drop down. The status of the incidence of the grape stem borer in different grape growing districts of Northern Karnataka was carried out during three years. In each taluka five locations were surveyed for the incidence of grape stem borer. Further, the experiment on management of stem borer was carried out in the grape gardens of Vijayapur districts under farmers field during three years. Stem borer infested plants that show live holes were selected per treatments and it was replicated three times. Live and dead holes observed during pre-treatment were closely monitored and only plants with live holes were selected and tagged. Different doses of chlorantraniliprole 0.4% GR were incorporated into the soil around the vine basins near root zone surrounded to trunk region by removing soils up to 5-10 cm with a peripheral distance of 1 to 1.5 feet from the main trunk where feeder roots are present. Irrigation was followed after application of insecticide for proper incorporation of the test chemical. The results indicated that there was sever to moderate incidence of the stem borer in all the grape growing districts of northern Karnataka. Maximum incidence was recorded in Belagavi (11 holes per vine) and minimum was in Gadag district (8.5 holes per vine). The investigations carried out to study the efficacy of chlorantraniliprole on grape stem borer for successive three years under farmers field indicated that chlorantraniliprole @ 15g/vine applied just near the active root zone of the plant followed by irrigation has successfully managed the pest. The insecticide has translocated to all the parts of the plants and thereby stopped the activity of the pest which has resulted in to better growth of the plant and higher berry yield compared to other treatments under investigation. Thus, chlorantraniliprole 0.4 GR @ 15g/vine can be effective means in managing the stem borer.

Keywords: chlorantraniliprole, grape stem borer, Celosterna scrabrator, management

Procedia PDF Downloads 442

Authors: Nadeem Munawar, Tariq Mahmood, Paula Rivadeneira, Ali Akhter

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In this paper, we review on rodent species which are common inhabitants of agricultural landscapes where they are an important prey source for a wide variety of avian, reptilian, and mammalian predators. Agricultural fields are surrounded by fallow land, which provide suitable sites for shelter and breeding for rodents, while shrubs, grasses, annual weeds and forbs may provide supplementary food. The assemblage of rodent’s fauna in the cropland habitats including cropped fields, meadows and adjacent field structures like hedgerows, woodland and field margins fluctuates seasonally. The mature agricultural crops provides good source of food and shelter to the rodents and these factors along with favorable climatic factors/season facilitate breeding activities of these rodent species. Changes in vegetation height and vegetative cover affect two important aspects of a rodent’s life: food and shelter. In addition, during non-crop period vegetation can be important for building nests above or below ground and it provides thermal protection for rodents from heat and cold. The review revealed that rodents form a very diverse group of mammals, ranging from tiny pigmy mice to big capybaras, from arboreal flying squirrels to subterranean mole rats, from opportunistic omnivores (e.g. Norway rats) to specialist feeders (e.g. the North African fat sand rats that feed on a single family of plants only). It is therefore no surprise that some species thrive well under the conditions that are found in agricultural fields. The review on the population dynamics of the rodent species indicated that they are agricultural pests probably due to the heterogeneous landscape and to the high rotativity of vegetable crop cultivation. They also cause damage to various crops, directly and indirectly, by gnawing, spoilage, contamination and hoarding activities, besides this behavior they have also significance importance in agricultural habitat. The burrowing activities of rodents alter the soil properties around their burrows which improve its aeration, infiltration, increase the water holding capacity and thus encourage plant growth. These properties are beneficial for the soil because they affect absorption of phosphorus, absorption zinc, copper, other nutrients and the uptake of water and thus rodents are known as indicator species in agricultural fields. Our review suggests that wide crop field’s borders, particularly those contiguous to various cropland fields, should be understood as priority sites for nesting, feeding, and cover for the rodent’s fauna. The goal of this review paper is to provide a comprehensive synthesis of understanding regarding rodent habitat and biodiversity in agricultural landscapes.

Keywords: agricultural landscapes, food, indicator species, shelter

Procedia PDF Downloads 169

Authors: Sawangjit Sopid

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In this study sugarcane field soils with a long history of atrazine application in Chachoengsao and Chonburi provinces have been explored for their potential of atrazine biodegradation. For the atrazine degrading bacteria isolation, the soils used in this study named ACS and ACB were inoculated in MS-medium containing atrazine. Six short rod and gram-negative bacterial isolates, which were able to use this herbicide as a sole source of nitrogen, were isolated and named as ACS1, ACB1, ACB3, ACB4, ACB5 and ACB6. From the 16S rDNA nucleotide sequence analysis, the isolated bacteria ACS1 and ACB4 were identified as Rhizobium sp. with 89.1-98.7% nucleotide identity, ACB1 and ACB5 were identified as Stenotrophomonas sp. with 91.0-92.8% nucleotide identity, whereas ACB3 and ACB6 were Klebsiella sp. with 97.4-97.8% nucleotide identity.

Keywords: atrazine-degrading bacteria, bioremediation, Thai isolates, bacteria

Procedia PDF Downloads 888

Authors: V. H. Nguyen, A. Castalone, C. Jamieson, M. Gummert

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Rice straw is an abundant biomass resource in Asian countries that can be used for bioenergy. In continuously flooded rice fields, it can be removed without reducing the levels of soil organic matter. One suitable bioenergy technology is anaerobic digestion (AD), but it needs to be further verified using rice straw as a feedstock. For this study, a batch AD system was developed using rice straw and cow dung. It is low cost, farm scale, with the batch capacity ranging from 5 kg to 200 kg of straw mixed with 10% of cow dung. The net energy balance obtained was from 3000 to 4000 MJ per ton of straw input at 15-18% moisture content. Net output energy obtained from biogas and digestate ranged from 4000 to 5000 MJ per ton of straw. This indicates AD as a potential solution for converting rice straw from a waste to a clean fuel, reducing the environmental footprint caused by current disposal practices.

Keywords: rice straw, anaerobic digestion, biogas, bioenergy

Procedia PDF Downloads 352

Authors: Rishi Pal Singh

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In Indian Scenario, Organic agriculture is growing by the conscious efforts of inspired people who are able to create the best promising relationship between the earth and men. Nowadays, the major challenge is its entry into the policy-making framework, its entry into the global market and weak sensitization among the farmers. But, during the last two decades, the contamination in environment and food which is linked with the bad agricultural potential/techniques has diverted the mind set of farmers towards the organic farming. In the view of above concept, a small-scale project has been installed to promote the 20 farmers from the Kunjura and surrounding villages for organic farming. This project is working since from the last 3 crops (starting from October, 2016) and found that it can meet both demands and complete development of rural areas. Farmers of this concept are working on the principles such that the nature never demands unreasonable quantities of water, mining and to destroy the microbes and other organisms. As per details of Organic Monitor estimates, global sales reached in billion in the present analysis. In this initiative, firstly, wheat and rice were considered for farming and observed that the production of crop has grown almost 10-15% per year from the last crop production. This is not linked only with the profit or loss but also emphasized on the concept of health, ecology, fairness and care of soil enrichment. Several techniques were used like use of biological fertilizers instead of chemicals, multiple cropping, temperature management, rain water harvesting, development of own seed, vermicompost and integration of animals. In the first year, to increase the fertility of the land, legumes (moong, cow pea and red gram) were grown in strips for the 60, 90 and 120 days. Simultaneously, the mixture of compost and vermicompost in the proportion of 2:1 was applied at the rate of 2.0 ton per acre which was enriched with 5 kg Azotobacter and 5 kg Rhizobium biofertilizer. To complete the amount of phosphorus, 250 kg rock phosphate was used. After the one month, jivamrut can be used with the irrigation water or during the rainy days. In next season, compost-vermicompost mixture @ 2.5 ton/ha was used for all type of crops. After the completion of this treatment, now the soil is ready for high value ordinary/horticultural crops. The amount of above stated biofertilizers, compost-vermicompost and rock phosphate may be increased for the high alternative fertilizers. The significance of the projects is that now the farmers believe in cultural alternative (use of disease-free their own seed, organic pest management), maintenance of biodiversity, crop rotation practices and health benefits of organic farming. This type of organic farming projects should be installed at the level of gram/block/district administration.

Keywords: organic farming, Kunjpura, compost, bio-fertilizers

Procedia PDF Downloads 196

Authors: Soo-yeon Seo, Seol-ki Kim, Su-jin Jung

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In the construction of a building, it is necessary to minimize construction period and secure enough work space for stacking of materials during the construction especially in city area. In this manner, various top-down construction methods have been developed and widely used in Korea. This paper investigates the stress variation of underground structure of a building constructed by using SPS (Strut as Permanent System) known as a top-down method in Korea through an analytical approach. Various types of earth pressure distribution related to ground condition were considered in the structural analysis of an example structure at each step of the excavation. From the analysis, the most high member force acting on beams was found when the ground type was medium sandy soil and a stress concentration was found in corner area.

Keywords: construction of building, top-down construction method, earth pressure distribution, member force, stress concentration

Procedia PDF Downloads 307

Authors: Yao-Hong Tsai

Abstract:

This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.

Keywords: image fusion, iris recognition, local binary pattern, wavelet

Procedia PDF Downloads 367

Authors: Sadia Nasrin Tisha, Mushfika Sharmin Rahman, Javier Orduz

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Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases.

Keywords: quantum machine learning, SVM, QSVM, matrix product state

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Authors: Mladen Dragičević, Mirjana Pejić Bach, Vanja Šimičević

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The purpose of this paper is to develop models that would enable predicting student success. These models could improve allocation of students among colleges and optimize the newly introduced model of government subsidies for higher education. For the purpose of collecting data, an anonymous survey was carried out in the last year of undergraduate degree student population using random sampling method. Decision trees were created of which two have been chosen that were most successful in predicting student success based on two criteria: Grade Point Average (GPA) and time that a student needs to finish the undergraduate program (time-to-degree). Decision trees have been shown as a good method of classification student success and they could be even more improved by increasing survey sample and developing specialized decision trees for each type of college. These types of methods have a big potential for use in decision support systems.

Keywords: data mining, knowledge discovery in databases, prediction models, student success

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Authors: Majid Bagherinia

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Lime and cement are frequently used as binders in the Deep Mixing Method (DMM) to improve soft clay soils. The most significant disadvantages of these materials are carbon dioxide emissions and the consumption of natural resources. In this study, three different biopolymers, guar gum, locust bean gum, and sodium alginate, were investigated for the improvement of soft clay using DMM. In the experimental study, the effects of the additive ratio and curing time on the Unconfined Compressive Strength (UCS) of stabilized specimens were investigated. According to the results, the UCS values of the specimens increased as the additive ratio and curing time increased. The most effective additive was sodium alginate, and the highest strength was obtained after 28 days.

Keywords: deep mixing method, soft clays, ground improvement, biopolymers, unconfined compressive strength

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Authors: Juan Heredia, Naci Dilekli

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The Ecuadorian Rainforest has been polluted for almost 60 years with little to no regard to oversight, law, or regulations. The consequences have been vast environmental damage such as pollution and deforestation, as well as sickness and the death of many people and animals. The aim of this paper is to quantify and localize the polluted zones, which something that has not been conducted and is the first step for remediation. To approach this problem, multi-spectral Remote Sensing imagery was utilized using a novel algorithm developed for this study, based on four normalized indices available in the literature. The algorithm classifies the pixels in polluted or healthy ones. The results of this study include a new algorithm for pixel classification and quantification of the polluted area in the selected image. Those results were finally validated by ground control points found in the literature. The main conclusion of this work is that using hyperspectral images, it is possible to identify polluted vegetation. The future work is environmental remediation, in-situ tests, and more extensive results that would inform new policymaking.

Keywords: remote sensing, oil pollution quatification, amazon forest, hyperspectral remote sensing

Procedia PDF Downloads 164

Authors: C. Rana, S. K. Jain

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The enormous amount of Web data has challenged its usage in efficient manner in the past few years. As such, a range of techniques are applied to tackle this problem; prominent among them is personalization and recommender system. In fact, these are the tools that assist user in finding relevant information of web. Most of the e-commerce websites are applying such tools in one way or the other. In the past decade, a large number of recommendation algorithms have been proposed to tackle such problems. However, there have not been much research in the evaluation criteria for these algorithms. As such, the traditional accuracy and classification metrics are still used for the evaluation purpose that provides a static view. This paper studies how the evolution of user preference over a period of time can be mapped in a recommender system using a new evaluation methodology that explicitly using time dimension. We have also presented different types of experimental set up that are generally used for recommender system evaluation. Furthermore, an overview of major accuracy metrics and metrics that go beyond the scope of accuracy as researched in the past few years is also discussed in detail.

Keywords: collaborative filtering, data mining, evolutionary, clustering, algorithm, recommender systems

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Authors: Navya Saira George, Patroba Achola Odera

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This study aims to determine spatio-temporal expansion of Kochi City, situated on the west coast of Kerala State in India. Remote sensing and GIS techniques have been used to determine land use/cover and urban expansion of the City. Classification of Landsat images of the years 1973, 1988, 2002 and 2018 have been used to reproduce a visual story of the growth of the City over a period of 45 years. Accuracy range of 0.79 ~ 0.86 is achieved with kappa coefficient range of 0.69 ~ 0.80. Results show that the areas covered by vegetation and water bodies decreased progressively from 53.0 ~ 30.1% and 34.1 ~ 26.2% respectively, while built-up areas increased steadily from 12.5 to 42.2% over the entire study period (1973 ~ 2018). The shift in land use from agriculture to non-agriculture may be attributed to the land reforms since 1980s.

Keywords: Geographical Information Systems, Kochi City, Land use/cover, Remote Sensing, Urban Sprawl

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Authors: Taehyun Kim, Taehyun Kim, Hyunjoo Park

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Photovoltaic facility occurs conflicts and disputes over environmental issues such as soil runoff, landscapes damage, and ecosystems damage. Because of these problems, huge social and economic cost occurred. The purpose of this study is to analyze resident‘s acceptability and conflict factors on the location of PV facilities, and suggest ways to promote resident’s acceptability and solutions for conflicts. Literature review, cases analysis, and expert interview on the acceptance and conflict factors related to the location of PV facilities are used to derive results. The results of this study are expected to contribute to the minimization of environmental impact and social conflict due to the development of renewable energy in the future.

Keywords: acceptance factor, conflict factor, factor analysis, photovoltaic facility

Procedia PDF Downloads 175

Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

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Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

Procedia PDF Downloads 73

Authors: Stefanie Rukavina, Sascha Gruss, Steffen Walter, Holger Hoffmann, Harald C. Traue

Abstract:

OPEN-EmoRecII is an open multimodal corpus with experimentally induced emotions. In the first half of the experiment, emotions were induced with standardized picture material and in the second half during a human-computer interaction (HCI), realized with a wizard-of-oz design. The induced emotions are based on the dimensional theory of emotions (valence, arousal and dominance). These emotional sequences - recorded with multimodal data (mimic reactions, speech, audio and physiological reactions) during a naturalistic-like HCI-environment one can improve classification methods on a multimodal level. This database is the result of an HCI-experiment, for which 30 subjects in total agreed to a publication of their data including the video material for research purposes. The now available open corpus contains sensory signal of: video, audio, physiology (SCL, respiration, BVP, EMG Corrugator supercilii, EMG Zygomaticus Major) and mimic annotations.

Keywords: open multimodal emotion corpus, annotated labels, intelligent interaction

Procedia PDF Downloads 416

Authors: Matthieu-P. Schapranow

Abstract:

Recruitment of participants for clinical trials requires the screening of a big number of potential candidates, i.e. the testing for trial-specific inclusion and exclusion criteria, which is a time-consuming and complex task. Today, a significant amount of time is spent on identification of adequate trial participants as their selection may affect the overall study results. We introduce a unique patient eligibility metric, which allows systematic ranking and classification of candidates based on trial-specific filter criteria. Our web application enables real-time analysis of patient data and assessment of candidates using freely definable inclusion and exclusion criteria. As a result, the overall time required for identifying eligible candidates is tremendously reduced whilst additional degrees of freedom for evaluating the relevance of individual candidates are introduced by our contribution.

Keywords: in-memory technology, clinical trials, screening, eligibility metric, data analysis, clustering

Procedia PDF Downloads 493

Authors: Birmohan Singh, V.K.Jain

Abstract:

Computer aided diagnosis systems provide vital opinion to radiologists in the detection of early signs of breast cancer from mammogram images. Masses and microcalcifications, architectural distortions are the major abnormalities. In this paper, a computer aided diagnosis system has been proposed for distinguishing abnormal mammograms with architectural distortion from normal mammogram. Four types of texture features GLCM texture, GLRLM texture, fractal texture and spectral texture features for the regions of suspicion are extracted. Support Vector Machine has been used as classifier in this study. The proposed system yielded an overall sensitivity of 96.47% and accuracy of 96% for the detection of abnormalities with mammogram images collected from Digital Database for Screening Mammography (DDSM) database.

Keywords: architecture distortion, mammograms, GLCM texture features, GLRLM texture features, support vector machine classifier

Procedia PDF Downloads 491

Authors: S. Athiralakshmi, B.E. Bhojaraja, U. Pruthviraj

Abstract:

In agriculture, remote sensing is applied for monitoring of plant development, evaluating of physiological processes and growth conditions. Especially valuable are the spatio-temporal aspects of the remotely sensed data in detecting crop state differences and stress situations. In this study, hyperion imagery is used for classifying arecanut crops based on their age so that these maps can be used in yield estimation of crops, irrigation purposes, applying fertilizers etc. Traditional hard classifiers assigns the mixed pixels to the dominant classes. The proposed method uses a sub pixel level classifier called linear spectral unmixing available in ENVI software. It provides the relative abundance of surface materials and the context within a pixel that may be a potential solution to effectively identifying the land-cover distribution. Validation is done referring to field spectra collected using spectroradiometer and the ground control points obtained from GPS.

Keywords: FLAASH, Hyperspectral remote sensing, Linear Spectral Unmixing, Spectral Angle Mapper Classifier.

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Authors: Antoine F. Dedewanou, Eric N. Ekpinda

Abstract:

We investigate whether and how deposit insurance program affects savings decisions in the Economic Community of Central African States (ECCAS). Specifically, using the World Bank’s 2014 and 2011 Global Financial Inclusion (Global Findex) databases, we apply special regressor approach. We find that the deposit insurance program increases significantly, everything else equal, the probability that people save their money at a financial institution by 11 percentage points in Gabon, by 22.2 percentage points in DR Congo and by 15.1 percentage points in Chad. These effects are matched with positive effects of age and education level. But in Cameroon, the effect of deposit insurance is not significant. The policies aimed at fostering financial inclusion will be more effective if there is a deposit insurance scheme in place, along with awareness among young people, and education programs. JEL Classification: G21, O12, O16

Keywords: deposit insurance, savings, special regressor, ECCAS countries

Procedia PDF Downloads 188

Authors: Abdelazim Makki Ibrahim, Esamaldeen Ali

Abstract:

This study aims at analysing the load settlement behavior and predict the bearing capacity of piled raft foundation a series of finite element models with different foundation configurations and stiffness were established. Numerical modeling is used to study the behavior of the piled raft foundation due to the complexity of piles, raft, and soil interaction and also due to the lack of reliable analytical method that can predict the behavior of the piled raft foundation system. Simple analytical models are developed to predict the average settlement and the load sharing between the piles and the raft in piled raft foundation system. A simple example to demonstrate the applications of these charts is included.

Keywords: finite element, pile-raft foundation, method, PLAXIS software, settlement

Procedia PDF Downloads 557