Search results for: classification of soils

Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong

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Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.

Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation

Procedia PDF Downloads 81

Authors: Ayu Dwi Hardiyanti, Bernardus Anggit Winahyu, I. Gusti Agung Ayu Sugita Sari, Lestari Sutra Simamora, I. Wayan Warmada

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The Penosogan Formation sandstone, that has Middle Miosen age, has been deemed as a reservoir potential based on sample data from sandstone outcrop in Kebakalan and Kedawung villages, Karangsambung sub-district, Kebumen Regency, Central Java. This research employs the following analytical methods; petrography, X-ray diffraction (XRD), and porosity test. Based on the presence of micritic sandstone, muddy micrite, and muddy sandstone, the Penosogan Formation sandstone has a fine-coarse granular size and middle-to-fine sorting. The composition of the sandstone is mostly made up of plagioclase, skeletal grain, and traces of micrite. The percentage of clay minerals based on petrographic analysis is 10% and appears to envelop grain, resulting enveloping grain which reduces the porosity of rocks. The porosity types as follows: interparticle, vuggy, channel, and shelter, with an equant form of cement. Moreover, the diagenesis process involves compaction, cementation, authigenic mineral growth, and dissolving due to feldspar alteration. The maturity of the reservoir can be seen through the X-ray diffraction analysis results, using ethylene glycol solution for clay minerals fraction transformed from smectite–illite. Porosity test analysis showed that the Penosogan Formation sandstones has a porosity value of 22% based on the Koeseomadinata classification, 1980. That shows high maturity is very influential for the quality of reservoirs sandstone of the Penosogan Formation.

Keywords: sandstone reservoir, Penosogan Formation, smectite, XRD

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Authors: Parul Johri, Mala Trivedi

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Major Intrinsic proteins (MIPs), actively involved in the passive transport of small polar molecules across the membranes of almost all living organisms. MIPs that specifically transport water molecules are named aquaporins (AQPs). The permeability of membranes is actively controlled by the regulation of the amount of different MIPs present but also in some cases by phosphorylation and dephosphorylation of the channel. Based on sequence similarity, MIPs have been classified into many categories. All of the proteins are made up of the 20 amino acids, the only difference is there in their orientations. Again all the 20 amino acids are made up of the basic five elements namely: carbon, hydrogen, oxygen, sulphur and nitrogen. These elements are responsible for giving the amino acids the properties of hydrophilicity/hydrophobicity which play an important role in protein interactions. The hydrophobic amino acids characteristically have greater number of carbon atoms as carbon is the main element which contributes to hydrophobic interactions in proteins. It is observed that the carbon level of proteins in different species is different. In the present work, we have taken a sample set of 150 aquaporins proteins from Uniprot database and a dynamic programming code was written to calculate the carbon percentage for each sequence. This carbon percentage was further used to barcode the aqauporins of animals and plants. The protein taken from Oryza sativa, Zea mays and Arabidopsis thaliana preferred to have carbon percentage of 31.8 to 35, whereas on the other hand sequences taken from Mus musculus, Saccharomyces cerevisiae, Homo sapiens, Bos Taurus, and Rattus norvegicus preferred to have carbon percentage of 31 to 33.7. This clearly demarks the carbon range in the aquaporin proteins from plant and animal origin. Hence the atom level analysis of protein sequences can provide us with better results as compared to the residue level comparison.

Keywords: aquaporins, carbon, dynamic prgramming, MIPs

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Authors: Silvija Šiljeg, Ivan Marić, Ante Šiljeg

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The accessibility of urban green spaces (UGS) is an integral element in the quality of life. Due to rapid urbanization, UGS studies have become a key element in urban planning. The potential benefits of space for its inhabitants are frequently analysed. A functional transport network system and the optimal spatial distribution of urban green surfaces are the prerequisites for maintaining the environmental equilibrium of the urban landscape. An accessibility analysis was conducted as part of the Urban Green Belts Project (UGB). The development of a GIS database for Zadar was the first step in generating the UGS accessibility indicator. Data were collected using the supervised classification method of multispectral LANDSAT images and manual vectorization of digital orthophoto images (DOF). An analysis of UGS accessibility according to the ANGst standard was conducted in the first phase of research. The accessibility indicator was generated on the basis of seven objective measurements, which included average UGS surface per capita and accessibility according to six functional levels of green surfaces. The generated indicator was compared with subjective measurements obtained by conducting a survey (718 respondents) within statistical units. The collected data reflected individual assessments and subjective evaluations of UGS accessibility. This study highlighted the importance of using objective and subjective measures in the process of understanding the accessibility of urban green surfaces. It may be concluded that when evaluating UGS accessibility, residents emphasize the immediate residential environment, ignoring higher UGS functional levels. It was also concluded that large areas of UGS within a city do not necessarily generate similar satisfaction with accessibility. The heterogeneity of output results may serve as guidelines for the further development of a functional UGS city network.

Keywords: urban green spaces (UGS), accessibility indicator, subjective and objective measurements, Zadar

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Authors: M. Kozłowski, M. Kadela

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Foamed concrete is known for its low self-weight and excellent thermal and acoustic properties. For many years, it has been used worldwide for insulation to foundations and roof tiles, as backfill to retaining walls, sound insulation, etc. However, in the last years it has become a promising material also for structural purposes e.g. for stabilization of weak soils. Due to favorable properties of foamed concrete, many interests and studies were involved to analyze its strength, mechanical, thermal and acoustic properties. However, these studies do not cover the investigation of fracture energy which is the core factor governing the damage and fracture mechanisms. Only limited number of publications can be found in literature. The paper presents the results of experimental investigation and numerical campaign of foamed concrete based on three-point bending test of beams with initial notch. First part of the paper presents the results of a series of static loading tests performed to investigate the fracture properties of foamed concrete of varying density. Beam specimens with dimensions of 100×100×840 mm with a central notch were tested in three-point bending. Subsequently, remaining halves of the specimens with dimensions of 100×100×420 mm were tested again as un-notched beams in the same set-up with reduced distance between supports. The tests were performed in a hydraulic displacement controlled testing machine with a load capacity of 5 kN. Apart from measuring the loading and mid-span displacement, a crack mouth opening displacement (CMOD) was monitored. Based on the load – displacement curves of notched beams the values of fracture energy and tensile stress at failure were calculated. The flexural tensile strength was obtained on un-notched beams with dimensions of 100×100×420 mm. Moreover, cube specimens 150×150×150 mm were tested in compression to determine the compressive strength. Second part of the paper deals with numerical investigation of the fracture behavior of beams with initial notch presented in the first part of the paper. Extended Finite Element Method (XFEM) was used to simulate and analyze the damage and fracture process. The influence of meshing and variation of mechanical properties on results was investigated. Numerical models simulate correctly the behavior of beams observed during three-point bending. The numerical results show that XFEM can be used to simulate different fracture toughness of foamed concrete and fracture types. Using the XFEM and computer simulation technology allow for reliable approximation of load–bearing capacity and damage mechanisms of beams made of foamed concrete, which provides some foundations for realistic structural applications.

Keywords: foamed concrete, fracture energy, three-point bending, XFEM

Procedia PDF Downloads 286

Authors: Vinay Kumar, M. Kishor, Sathyanarayana Rao Ts

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Background: Growth of elderly people in the general population in recent years is termed as ‘greying of the world’ where there is a shift from high mortality & fertility to low mortality and fertility, resulting in an increased proportion of older people as seen in India. Improved health care promises longevity but socio-economic factors like poverty, joint families and poor services pose a psychological threat. Epidemiological data regarding the prevalence of mental disorders in geriatric population with physical illness is required for proper health planning. Methods: Sixty consecutive elderly patients aged 60 years or above of both sexes, reporting with physical illness to general outpatient registration counter of JSS Medical College and Hospital, Mysore, India, were considered for the Study. With informed consent, they were screened with General Health Questionnaire (GHQ-12) and were further evaluated for diagnosing mental disorders according to WHO International Classification of Diseases (ICD-10) criteria. Results: Mental disorders were detected in 48.3%, predominantly depressive disorders, nicotine dependence, generalized anxiety disorder, alcohol dependence and least was dementia. Most common physical illness was cardiovascular disease followed by metabolic, respiratory and other diseases. Depressive disorders, substance dependence and dementia were more associated with cardiovascular disease compared to metabolic disease and respiratory diseases were more associated with nicotine dependence. Conclusions: Depression and Substance use disorders among elderly population is of concern, which needs to be further studied with larger population. Psychiatric morbidity will adversely have an impact on physical illness which needs proper assessment and management. This will enhance our understanding and prioritize our planning for future.

Keywords: Geriatric, mental disorders, physical illness, psychiatry

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Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation

Procedia PDF Downloads 331

Authors: Wendu Pang, Yaxin Luo, Junhong Li, Yu Zhao, Danni Cheng, Yufang Rao, Minzi Mao, Ke Qiu, Yijun Dong, Fei Chen, Jun Liu, Jian Zou, Haiyang Wang, Wei Xu, Jianjun Ren

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We aimed to compare the prognostic prediction value of positive lymph node number (PLNN) to the American Joint Committee on Cancer (AJCC) tumor, lymph node, and metastasis (TNM) staging system for patients with hypopharyngeal squamous cell carcinoma (HPSCC). A total of 826 patients with HPSCC from the Surveillance, Epidemiology, and End Results database (2004–2015) were identified and split into two independent cohorts: training (n=461) and validation (n=365). Univariate and multivariate Cox regression analyses were used to evaluate the prognostic effects of PLNN in patients with HPSCC. We further applied six Cox regression models to compare the survival predictive values of the PLNN and AJCC TNM staging system. PLNN showed a significant association with overall survival (OS) and cancer-specific survival (CSS) (P < 0.001) in both univariate and multivariable analyses, and was divided into three groups (PLNN 0, PLNN 1-5, and PLNN>5). In the training cohort, multivariate analysis revealed that the increased PLNN of HPSCC gave rise to significantly poor OS and CSS after adjusting for age, sex, tumor size, and cancer stage; this trend was also verified by the validation cohort. Additionally, the survival model incorporating a composite of PLNN and TNM classification (C-index, 0.705, 0.734) performed better than the PLNN and AJCC TNM models. PLNN can serve as a powerful survival predictor for patients with HPSCC and is a surrogate supplement for cancer staging systems.

Keywords: hypopharyngeal squamous cell carcinoma, positive lymph nodes number, prognosis, prediction models, survival predictive values

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Authors: P. Massanyi, L. Kichi, T. Slanina, E. Kolesar, J. Danko, N. Lukac, E. Tvrda, R. Stawarz, A. Kolesarova

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Target of this study was the analysis of the impact of crude glycerol on canine spermatozoa motility, morphology, viability, and membrane integrity. Experiments were realized in vitro. In the study, semen from 5 large dog breeds was used. They were typical representatives of large breeds, coming from healthy rearing, regularly vaccinated and integrated to the further breeding. Semen collections were realized at the owners of animals and in the veterinary clinic. Subsequently the experiments were realized at the Department of Animal Physiology of the SUA in Nitra. The spermatozoa motility was evaluated using CASA analyzer (SpermVisionTM, Minitub, Germany) at the temperature 5 and 37°C for 5 hours. In the study, 13 motility parameters were evaluated. Generally, crude glycerol has generally negative effect on spermatozoa motility. Morphological analysis was realized using Hancock staining and the preparations were evaluated at magnification 1000x using classification tables of morphologically changed spermatozoa. Data clearly detected the highest number of morphologically changed spermatozoa in the experimental groups (know twisted tails, tail torso and tail coiling). For acrosome alterations swelled acrosomes, removed acrosomes and acrosomes with undulated membrane were detected. In this study also the effect of crude glycerol on spermatozoa membrane integrity were analyzed. The highest crude glycerol concentration significantly affects spermatozoa integrity. Results of this study show that crude glycerol has effect of spermatozoa motility, viability, and membrane integrity. Detected changes are related to crude glycerol concentration, temperature, as well as time of incubation.

Keywords: dog, semen, spermatozoa, acrosome, glycerol, CASA, viability

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Authors: K. P. Fasalu Rahman

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The financial services industry of Islam include large number of institutions, such as investment banks and commercial banks, investment companies and mutual insurance companies. All types of these financial institutions should have to deal with many issues and risks in their field of work. Islamic banks should expect to face two types of risks: risks that are similar to those faced by conventional financial intermediaries and risks that are unique to the Islamic Banks due to their compliance with the Shariah. The use of financial services and products that comply with the Shariah principles cause special issues for supervision and risk management. Risks are uncertain future events that could influence the achievement of the bank’s objectives, including strategic, operational, financial and compliance objectives. In Islamic banks, effective risk management deserves special attention. As an operational problem, risk management is the classification and identification of methods, processes, and risks in banks to supervise, monitor and measure them. In comparison to conventional banks, Islamic banks face big difficulties in identifying and managing risks due to bigger complexities emerging from the profit loss sharing (PLS) concept and nature of particular risks of Islamic financing. As the developing of managing risks tool becomes very essential, especially in Islamic banking as most of the products are depending on PLS principle, identifying and measuring each type of risk is highly important and critical in any Islamic finance based systems. This paper highlights the special and general risks surrounding Islamic banking. And it investigates in detail the need for risk management in Islamic banks. In addition to analyzing the effectiveness of risk management strategies adopted by Islamic financial institutions at present, this research is also suggesting strategies for improving risk management process of Islamic banks in future.

Keywords: Islamic banking, management, risk, risk management

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Authors: Rian O. Miranda, Lidia V. de Sa, Julio C. Suita

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The Brazilian Nuclear Energy Commission (CNEN) is the main manufacturer of radiopharmaceuticals in Brazil. The Nuclear Engineering Institute (IEN), located at Rio de Janeiro, is one of its main centers of research and production, attending public and private hospitals in the state. This radiopharmaceutical production is used in diagnostic and therapy procedures and allows one and a half million nuclear medicine procedures annually. Despite this, the country is not self-sufficient to meet national demand, creating the need for importation and consequent dependence on other countries. However, IEN facilities were designed in the 60's, and today its structure is inadequate in relation to the good manufacturing practices established by sanitary regulator (ANVISA) and radiological protection leading to the need for a new project. In order to adapt and increase production in the country, a new plant will be built and integrated to the existing facilities with a new 30 MeV Cyclotron that is actually in project detailing process. Thus, it is proposed to survey current CNEN and ANVISA standards for radiopharmaceutical production facilities, as well as the radiological protection analysis of each area of the plant, following good manufacturing practices recommendations adopted nationally besides licensing exigencies for radioactive facilities. In this way, the main requirements for proper operation, equipment location, building materials, area classification, and maintenance program have been implemented. The access controls, interlocks, segregation zones and pass-through boxes integrated into the project were also analyzed. As a result, IEN will in future have the flexibility to produce all necessary radioisotopes for nuclear medicine application, more efficiently by simultaneously bombarding two targets, allowing the simultaneous production of two different radioisotopes, minimizing radiation exposure and saving operating costs.

Keywords: cyclotron, legislation, norms, production, radiopharmaceuticals

Procedia PDF Downloads 119

Authors: Sophie Mills, Leila L. Touil, Richard Sisson

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Introduction: The TNM classification is the global standard for the staging of head and neck cancers. Accurate clinical-radiological staging of tumours (cTNM) is essential to predict prognosis, facilitate surgical planning and determine the need for other therapeutic modalities. This study aims to determine the accuracy of pre-operative cTNM staging using pathological TNM (pTNM) and consider possible causes of TNM stage migration, noting any variation throughout the COVID-19 pandemic. Materials and Methods: A retrospective cohort study examined records of patients with surgical management of head and neck cancer at a tertiary head and neck centre from November 2019 to November 2020. Data was extracted from Somerset Cancer Registry and histopathology reports. cTNM and pTNM were compared before and during the first wave of COVID-19, as well as with other potential prognostic factors such as tumour site and tumour stage. Results: 119 cases were identified, of which 52.1% (n=62) were male, and 47.9% (n=57) were female with a mean age of 67 years. Clinical and pathological staging differed in 54.6% (n=65) of cases. Of the patients with stage migration, 40.4% (n=23) were up-staged and 59.6% (n=34) were down-staged compared with pTNM. There was no significant difference in the accuracy of cTNM staging compared with age, sex, or tumour site. There was a statistically highly significant (p < 0.001) correlation between cTNM accuracy and tumour stage, with the accuracy of cTNM staging decreasing with the advancement of pTNM staging. No statistically significant variation was noted between patients staged prior to and during COVID-19. Conclusions: Discrepancies in staging can impact management and outcomes for patients. This study found that the higher the pTNM, the more likely stage migration will occur. These findings are concordant with the oncology literature, which highlights the need to improve the accuracy of cTNM staging for more advanced tumours.

Keywords: COVID-19, head and neck cancer, stage migration, TNM staging

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Authors: Janos Juhasz, Sandor Pongor, Balazs Ligeti

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Next-generation sequencing, especially whole genome shotgun sequencing, is becoming a common approach to gain insight into the microbiomes in a culture-independent way, even in clinical practice. It does not only give us information about the species composition of an environmental sample but opens the possibility to detect antimicrobial resistance and novel, or currently unknown, pathogens. Accurately and reliably detecting the microbial strains is a challenging task. Here we present a sensitive approach for detecting pathogens in metagenomics samples with special regard to detecting novel variants of known pathogens. We have developed a pipeline that uses fast, short read aligner programs (i.e., Bowtie2/BWA) and comprehensive nucleotide databases. Taxonomic binning is based on the lowest common ancestor (LCA) principle; each read is assigned to a taxon, covering the most significantly hit taxa. This approach helps in balancing between sensitivity and running time. The program was tested both on experimental and synthetic data. The results implicate that our method performs as good as the state-of-the-art BLAST-based ones, furthermore, in some cases, it even proves to be better, while running two orders magnitude faster. It is sensitive and capable of identifying taxa being present only in small abundance. Moreover, it needs two orders of magnitude less reads to complete the identification than MetaPhLan2 does. We analyzed an experimental anthrax dataset (B. anthracis strain BA104). The majority of the reads (96.50%) was classified as Bacillus anthracis, a small portion, 1.2%, was classified as other species from the Bacillus genus. We demonstrate that the evaluation of high-throughput sequencing data is feasible in a reasonable time with good classification accuracy.

Keywords: metagenomics, taxonomy binning, pathogens, microbiome, B. anthracis

Procedia PDF Downloads 115

Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L. Duan

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The conditional density characterizes the distribution of a response variable y given other predictor x and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts as a motivating starting point. In this work, the authors extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zₚ, zₙ]. The zₚ component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zₙ component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach coined Augmented Posterior CDE (AP-CDE) only requires a simple modification of the common normalizing flow framework while significantly improving the interpretation of the latent component since zₚ represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of 𝑥-related variations due to factors such as lighting condition and subject id from the other random variations. Further, the experiments show that an unconditional NF neural network based on an unsupervised model of z, such as a Gaussian mixture, fails to generate interpretable results.

Keywords: conditional density estimation, image generation, normalizing flow, supervised dimension reduction

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Authors: Apisit Nawapanpong, Natthapat Boonjerm

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This project aims to analyze and identify the flight plan of low-altitude aviation in Thailand and other countries. The development of UAV technology has led the innovation and revolution in the aviation industry; this includes the development of new modes of passenger or freight transportation, and it has also affected other industries widely. At present, this technology is being developed rapidly and has been tested all over the world to make the most efficient for technology or innovation, and it is likely to grow more extensively. However, no flight plan for low-altitude operation has been published by the government organization; when compared with high-altitude aviation with manned aircraft, various unique factors are different, whether mission, operation, altitude range or airspace restrictions. In the study of the essential components of low-altitude operation measures to be practical and tangible, there were major problems, so the main consideration of this project is to analyze the components of low-altitude operations which are conducted up to the altitudes of 400 ft or 120 meters above ground level referring to the terrain, for example, air traffic management, classification of aircraft, basic necessity and safety, and control area. This research will focus on confirming the theory through qualitative and quantitative research combined with theoretical modeling and regulatory framework and by gaining insights from various positions in aviation industries, including aviation experts, government officials, air traffic controllers, pilots, and airline operators to identify the critical essential components of low-altitude flight operation. This project analyzes by using computer programs for science and statistics research to prove that the result is equivalent to the theory and be beneficial for regulating the flight plan for low-altitude operation by different essential components from this project and can be further developed for future studies and research in aviation industries.

Keywords: low-altitude aviation, UAV technology, flight plan, air traffic management, safety measures

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Authors: Felicia Orah Rein Moshe

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Soil erosion has become a priority global concern, impairing water quality and degrading ecosystem services. In Mediterranean climates, following a long dry period, the onset of rain occurs when agricultural soils are often bare and most vulnerable to erosion. Early storms transport sediments and sediment-bound pollutants into streams, along with dissolved chemicals. This results in loss of valuable topsoil, water quality degradation, and potentially expensive dredged-material disposal costs. Information on the provenance of fine sediment and priority sources of adsorbed pollutants represents a critical need for developing effective control strategies aimed at source reduction. Modifying sediment traps designed for marine systems, this study tested a cost-effective method to collect suspended sediments on a catchment scale to characterize stream water quality during first-flush storm events in a flashy Eastern Mediterranean coastal perennial stream. This study investigated the Kishon Basin, deploying sediment traps in 23 locations, including 4 in the mainstream and one downstream in each of 19 tributaries, enabling the characterization of sediment as a vehicle for transporting chemicals. Further, it enabled direct comparison of sediment-bound pollutants transported during the first-flush winter storms of 2020 from each of 19 tributaries, allowing subsequent ecotoxicity ranking. Sediment samples were successfully captured in 22 locations. Pesticides, pharmaceuticals, nutrients, and metal concentrations were quantified, identifying a total of 50 pesticides, 15 pharmaceuticals, and 22 metals, with 16 pesticides and 3 pharmaceuticals found in all 23 locations, demonstrating the importance of this transport pathway. Heavy metals were detected in only one tributary, identifying an important watershed pollution source with immediate potential influence on long-term dredging costs. Simultaneous sediment sampling at first flush storms enabled clear identification of priority tributaries and their chemical contributions, advancing a new national watershed monitoring approach, facilitating strategic plan development based on source reduction, and advancing the goal of improving the farm-stream interface, conserving soil resources, and protecting water quality.

Keywords: adsorbed pollution, dredged material, heavy metals, suspended sediment, water quality monitoring

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Authors: Kristina Amaleviciute, Ieva Jokubauskaite, Alvyra Slepetiene, Jonas Volungevicius, Inga Liaudanskiene

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The main task of this research was to investigate the chemical composition of the differently used soil in profiles. To identify the differences in the soil were investigated organic carbon (SOC) and its fractional composition: dissolved organic carbon (DOC), mobile humic acids (MHA) and C to N ratio of natural and anthropogenically affected Luvisols. Research object: natural and anthropogenically affected Luvisol, Akademija, Kedainiai, distr. Lithuania. Chemical analyses were carried out at the Chemical Research Laboratory of Institute of Agriculture, LAMMC. Soil samples for chemical analyses were taken from the genetics soil horizons. SOC was determined by the Tyurin method modified by Nikitin, measuring with spectrometer Cary 50 (VARIAN) in 590 nm wavelength using glucose standards. For mobile humic acids (MHA) determination the extraction procedure was carried out using 0.1 M NaOH solution. Dissolved organic carbon (DOC) was analyzed using an ion chromatograph SKALAR. pH was measured in 1M H2O. N total was determined by Kjeldahl method. Results: Based on the obtained results, it can be stated that transformation of chemical composition is going through the genetic soil horizons. Morphology of the upper layers of soil profile which is formed under natural conditions was changed by anthropomorphic (agrogenic, urbogenic, technogenic and others) structure. Anthropogenic activities, mechanical and biochemical disturbances destroy the natural characteristics of soil formation and complicates the interpretation of soil development. Due to the intensive cultivation, the pH values of the curve equals (disappears acidification characteristic for E horizon) with natural Luvisol. Luvisols affected by agricultural activities was characterized by a decrease in the absolute amount of humic substances in separate horizons. But there was observed more sustainable, higher carbon sequestration and thicker storage of humic horizon compared with forest Luvisol. However, the average content of humic substances in the soil profile was lower. Soil organic carbon content in anthropogenic Luvisols was lower compared with the natural forest soil, but there was more evenly spread over in the wider thickness of accumulative horizon. These data suggest that the organization of geo-ecological declines and agroecological increases in Luvisols. Acknowledgement: This work was supported by the National Science Program ‘The effect of long-term, different-intensity management of resources on the soils of different genesis and on other components of the agro-ecosystems’ [grant number SIT-9/2015] funded by the Research Council of Lithuania.

Keywords: agrogenization, dissolved organic carbon, luvisol, mobile humic acids, soil organic carbon

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Authors: Syed Qasim Gilani, Muhammad Umair, Muhammad Noman, Syed Bilawal Shah, Aqib Abbasi, Muhammad Waheed

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Cardiovascular Diseases(CVD's) are the major cause of death in the world. The main reason for these deaths is the unavailability of first aid for heart failure. In many cases, patients die before reaching the hospital. We in this paper are presenting innovative online health service for Cardiac Patients. The proposed online health system has two ends. Users through device developed by us can communicate with their doctor through a mobile application. This interface provides them with first aid.Also by using this service, they have an easy interface with their doctors for attaining medical advice. According to the proposed system, we developed a device called Cardiac Care. Cardiac Care is a portable device which a patient can use at their home for monitoring heart condition. When a patient checks his/her heart condition, Electrocardiogram (ECG), Blood Pressure(BP), Temperature are sent to the central database. The severity of patients condition is checked using Artificial Intelligence Algorithm at the database. If the patient is suffering from the minor problem, our algorithm will suggest a prescription for patients. But if patient's condition is severe, patients record is sent to doctor through the mobile Android application. Doctor after reviewing patients condition suggests next step. If a doctor identifies the patient condition as critical, then the message is sent to the central database for sending an ambulance for the patient. Ambulance starts moving towards patient for bringing him/her to hospital. We have implemented this model at prototype level. This model will be life-saving for millions of people around the globe. According to this proposed model patients will be in contact with their doctors all the time.

Keywords: cardiovascular disease, classification, electrocardiogram, blood pressure

Procedia PDF Downloads 171

Authors: Luanna B. Prevost, Kelli Carter, Margaurete Romero, Kirsti Martinez

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Writing is an essential scientific practice, yet, in several countries, the increasing university science class-size limits the use of written assessments. Written assessments allow students to demonstrate their learning in their own words and permit the faculty to evaluate students’ understanding. However, the time and resources required to grade written assessments prohibit their use in large-enrollment science courses. This study examined the use of machine learning algorithms to automatically analyze student writing and provide timely feedback to the faculty about students' writing in biology. Written responses to questions about matter and energy transformation were collected from large-enrollment undergraduate introductory biology classrooms. Responses were analyzed using the LightSide text mining and classification software. Cohen’s Kappa was used to measure agreement between the LightSide models and human raters. Predictive models achieved agreement with human coding of 0.7 Cohen’s Kappa or greater. Models captured that when writing about matter-energy transformation at the ecosystem level, students focused on primarily on the concepts of heat loss, recycling of matter, and conservation of matter and energy. Models were also produced to capture writing about processes such as decomposition and biochemical cycling. The models created in this study can be used to provide automatic feedback about students understanding of these concepts to biology faculty who desire to use formative written assessments in larger enrollment biology classes, but do not have the time or personnel for manual grading.

Keywords: machine learning, written assessment, biology education, text mining

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Authors: Sina Fatolahzadeh, Sergio A. Sepúlveda

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This paper presents advanced developments in close-range, terrestrial remote sensing techniques to enhance the characterization of rock masses. The study integrates two state-of-the-art laser-scanning technologies, the HandySCAN and GeoSLAM laser scanners, to extract high-resolution geospatial data for rock mass analysis. These instruments offer high accuracy, precision, low acquisition time, and high efficiency in capturing intricate geological features in small to medium size outcrops and slope cuts. Using the HandySCAN and GeoSLAM laser scanners facilitates real-time, three-dimensional mapping of rock surfaces, enabling comprehensive assessments of rock mass characteristics. The collected data provide valuable insights into structural complexities, surface roughness, and discontinuity patterns, which are essential for geological and geotechnical analyses. The synergy of these advanced remote sensing technologies contributes to a more precise and straightforward understanding of rock mass behavior. In this case, the main parameters of RQD, joint spacing, persistence, aperture, roughness, infill, weathering, water condition, and joint orientation in a slope cut along the Sea-to-Sky Highway, BC, were remotely analyzed to calculate and evaluate the Rock Mass Rating (RMR) and Geological Strength Index (GSI) classification systems. Automatic and manual analyses of the acquired data are then compared with field measurements. The results show the usefulness of the proposed remote sensing methods and their appropriate conformity with the actual field data.

Keywords: remote sensing, rock mechanics, rock engineering, slope stability, discontinuity properties

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Authors: Marco Vinicio Félix Lerma, Efrain Rubio Rosas, Fernando Ricardez Rueda, Victor Manuel Castaño Meneses

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This paper reports a spectral analysis of the exposure levels of radiofrequency electromagnetic fields originating from a wide variety of telecommunications sources present in an urban area of Lagos de Moreno, Jalisco, Mexico. The electromagnetic characterization of the urban zone under study was carried out by measurements in 118 sites. Measurements of TETRA,ISM434, LTE800, ISM868, GSM900, GSM1800, 3G UMTS,4G UMTS, Wlan2.4, LTE2.6, DECT, VHF Television and FM radio signals were performed at distances ranging over 10 to 1000m from 87 broadcasting towers concentrated in an urban area of about 3 hectares. The aim of these measurements is the evaluation of the electromagnetic fields power levels generated by communication systems because of their interaction with the human body. We found that in certain regions the general public exposure limits determined by ICNIRP (International Commission of Non Ionizing Radiation Protection) are overpassed from 5% up to 61% of the upper values, indicating an imminent health public hazard, whereas in other regions we found that these limits are not overpassed. This work proposes an electromagnetic pollution classification for urban zones according with ICNIRP standards. We conclude that the urban zone under study presents diverse levels of pollution and that in certain regions an electromagnetic shielding solution is needed in order to safeguard the health of the population that lives there. A practical solution in the form of paint coatings and fiber curtains for the buildings present in this zone is also proposed.

Keywords: electromagnetic field, telecommunication systems, electropollution, health hazards

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Authors: Javier Romera, Alberto Justo, Ignacio Fidalgo, Joshue Perez, Javier Araluce

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Nowadays, individuals with mobility needs face a significant challenge when docking vehicles. In many cases, after parking, they encounter insufficient space to exit, leading to two undesired outcomes: either avoiding parking in that spot or settling for improperly placed vehicles. To address this issue, the following paper presents a parking control system employing gestural teleoperation. The system comprises three main phases: capturing body markers, interpreting gestures, and transmitting orders to the vehicle. The initial phase is centered around the MediaPipe framework, a versatile tool optimized for real-time gesture recognition. MediaPipe excels at detecting and tracing body markers, with a special emphasis on hand gestures. Hands detection is done by generating 21 reference points for each hand. Subsequently, after data capture, the project employs the MultiPerceptron Layer (MPL) for indepth gesture classification. This tandem of MediaPipe's extraction prowess and MPL's analytical capability ensures that human gestures are translated into actionable commands with high precision. Furthermore, the system has been trained and validated within a built-in dataset. To prove the domain adaptation, a framework based on the Robot Operating System (ROS), as a communication backbone, alongside CARLA Simulator, is used. Following successful simulations, the system is transitioned to a real-world platform, marking a significant milestone in the project. This real vehicle implementation verifies the practicality and efficiency of the system beyond theoretical constructs.

Keywords: gesture detection, mediapipe, multiperceptron layer, robot operating system

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Authors: Endalkachew Abebe Kebede, Bojin Bojinov, Andon Vasilev Andonov, Orhan Dengiz

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Remote sensing has a potential application in assessing and monitoring the plants' biophysical properties using the spectral responses of plants and soils within the electromagnetic spectrum. However, only a few reports compare the performance of different remote sensing sensors against in-situ field spectral measurement. The current study assessed the potential applications of open data source satellite images (Sentinel 2 and Landsat 9) in estimating the biophysical properties of the wheat crop on a study farm found in the village of OvchaMogila. A Landsat 9 (30 m resolution) and Sentinel-2 (10 m resolution) satellite images with less than 10% cloud cover have been extracted from the open data sources for the period of December 2021 to April 2022. An Unmanned Aerial Vehicle (UAV) has been used to capture the spectral response of plant leaves. In addition, SpectraVue 710s Leaf Spectrometer was used to measure the spectral response of the crop in April at five different locations within the same field. The ten most common vegetation indices have been selected and calculated based on the reflectance wavelength range of remote sensing tools used. The soil samples have been collected in eight different locations within the farm plot. The different physicochemical properties of the soil (pH, texture, N, P₂O₅, and K₂O) have been analyzed in the laboratory. The finer resolution images from the UAV and the Leaf Spectrometer have been used to validate the satellite images. The performance of different sensors has been compared based on the measured leaf spectral response and the extracted vegetation indices using the five sampling points. A scatter plot with the coefficient of determination (R2) and Root Mean Square Error (RMSE) and the correlation (r) matrix prepared using the corr and heatmap python libraries have been used for comparing the performance of Sentinel 2 and Landsat 9 VIs compared to the drone and SpectraVue 710s spectrophotometer. The soil analysis revealed the study farm plot is slightly alkaline (8.4 to 8.52). The soil texture of the study farm is dominantly Clay and Clay Loam.The vegetation indices (VIs) increased linearly with the growth of the plant. Both the scatter plot and the correlation matrix showed that Sentinel 2 vegetation indices have a relatively better correlation with the vegetation indices of the Buteo dronecompared to the Landsat 9. The Landsat 9 vegetation indices somewhat align better with the leaf spectrometer. Generally, the Sentinel 2 showed a better performance than the Landsat 9. Further study with enough field spectral sampling and repeated UAV imaging is required to improve the quality of the current study.

Keywords: landsat 9, leaf spectrometer, sentinel 2, UAV

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Authors: Karina Reiter, Stefan Dullinger, Christoph Plutzar, Dietmar Moser

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Due to population growth and changing patterns of production and consumption, the demand for natural resources and, as a result, the pressure on Earth’s ecosystems are growing. Biodiversity mapping can be a useful tool for assessing species endangerment or detecting hotspots of extinction risks. This paper explores the benefits of using the change in trophic energy flows as a consequence of the human alteration of the biosphere in biodiversity mapping. To this end, multiple linear regression models were developed to explain species richness in areas where there is no human influence (i.e. wilderness) for three taxonomic groups (birds, mammals, amphibians). The models were then applied to predict (I) potential global species richness using potential natural vegetation (NPPpot) and (II) global ‘actual’ species richness after biomass appropriation using NPP remaining in ecosystems after harvest (NPPeco). By calculating the difference between predicted potential and predicted actual species numbers, maps of estimated species richness loss were generated. Results show that biomass appropriation for human use can indeed be linked to biodiversity loss. Areas for which the models predicted high species loss coincide with areas where species endangerment and extinctions are recorded to be particularly high by the International Union for Conservation of Nature and Natural Resources (IUCN). Furthermore, the analysis revealed that while the species distribution maps of the IUCN Red List of Threatened Species used for this research can determine hotspots of biodiversity loss in large parts of the world, the classification system for threatened and extinct species needs to be revised to better reflect local risks of extinction.

Keywords: biodiversity loss, biomass harvest, human appropriation of net primary production, species richness

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Authors: Masoud Ghahvechi Pour

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Risk management is a systematic and regular process of identifying, analyzing and responding to risks throughout the project's life cycle in order to achieve the optimal level of elimination, reduction or control of risk. The purpose of project risk management is to increase the probability and effect of positive events and reduce the probability and effect of unpleasant events on the project. Risk management is one of the most fundamental parts of project management, so that unmanaged or untransmitted risks can be one of the primary factors of failure in a project. Effective risk management does not apply to risk regression, which is apparently the cheapest option of the activity. However, the main problem with this option is the economic sensitivity, because what is potentially profitable is by definition risky, and what does not pose a risk is economically interesting and does not bring tangible benefits. Therefore, in relation to the implemented project, effective risk management is finding a "middle ground" in its management, which includes, on the one hand, protection against risk from a negative direction by means of accurate identification and classification of risk, which leads to analysis And it becomes a comprehensive analysis. On the other hand, management using all mathematical and analytical tools should be based on checking the maximum benefits of these decisions. Detailed analysis, taking into account all aspects of the company, including stakeholder analysis, will allow us to add what will become tangible benefits for our project in the future to effective risk management. Identifying the risk of the project is based on the theory that which type of risk may affect the project, and also refers to specific parameters and estimating the probability of their occurrence in the project. These conditions can be divided into three groups: certainty, uncertainty, and risk, which in turn support three types of investment: risk preference, risk neutrality, specific risk deviation, and its measurement. The result of risk identification and project analysis is a list of events that indicate the cause and probability of an event, and a final assessment of its impact on the environment.

Keywords: risk, management, knowledge, risk management

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Authors: Burcu Babadağ Savaş, Nihal Orlu, Güler Balcı Alparslan, Ertuğrul Çolak, Cengiz Korkmaz

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Introduction/objectives: We aimed to investigate the effect of humor on pain and state anxiety in patients with rheumatoid arthritis (RA) receiving biologic intravenous (IV) infusion therapy. Method: The study sample consisted of 36 patients who met the classification criteria for RA and inclusion criteria in a rheumatology outpatient clinic at a university hospital between September 2020 and November 2021. Two sample groups were formed: the intervention group (watching a comedy movie) (n=18) and the control group (n=18). The intervention group consisted of the patient watching a comedy movie of his/her choice from an archive created by the researchers during the biological IV infusion therapy (approximately 90-120 minutes). The data collection instruments used before and after the test were the descriptive identification form, the visual analog scale (VAS), and the state anxiety scale. Results: The mean VAS scores of patients in the intervention group were 5.05 ± 2.01 in the pre-test and 2.61 ± 1.91 in the post-test. The mean state anxiety scores of patients in the intervention group were 45.94 ± 9.97 in the pre-test and 34.22 ± 6.57 in the post-test. Thus, patients who watched comedy movies during biologic IV infusion therapy in the infusion center had a greater reduction in pain scores than the control group and the effect size was small. Although there was a decrease in state anxiety scores in both groups, there was no significant difference between groups and the effect size was not relevant. Conclusions: During IV infusion therapy, watching comedy movies is recommended as a nursing care intervention for reducing pain in patients with RA in cooperation with other health professionals.

Keywords: watching comedy movie, humor, pain, anxiety, nursing, care

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Authors: Peace Liz Sasha Musonge

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Behavioral aspects of species nutrition such as feeding methods and food type are archetypal biological traits signifying how species have adapted to their environment. This concept of functional feeding groups (FFG) analysis is currently used to ascertain the trophic levels of the aquatic food web in a specific microhabitat. However, in Eastern Africa, information about the FFG classification of benthic macroinvertebrates in highland rivers and streams is almost absent, and existing studies have fragmented datasets. For this reason, we carried out a robust study to determine the feed type, trophic level and FFGs, of 56 macroinvertebrate taxa (identified to family level) from Albertine rift valley streams. Our findings showed that all five major functional feeding groups were represented; Gatherer Collectors (GC); Predators (PR); shredders (SH); Scrapers (SC); and Filterer collectors. The most dominant functional feeding group was the Gatherer Collectors (GC) that accounted for 53.5% of the total population. The most abundant (GC) families were Baetidae (7813 individuals), Chironomidae NTP (5628) and Caenidae (1848). Majority of the macroinvertebrate population feed on Fine particulate organic matter (FPOM) from the stream bottom. In terms of taxa richness the Predators (PR) had the highest value of 24 taxa and the Filterer Collectors group had the least number of taxa (3). The families that had the highest number of predators (PR) were Corixidae (1024 individuals), Coenagrionidae (445) and Libellulidae (283). However, Predators accounted for only 7.4% of the population. The findings highlighted the functional feeding groups and habitat type of macroinvertebrate communities along an altitudinal gradient.

Keywords: trophic levels, functional feeding groups, macroinvertebrates, Albertine rift

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Authors: I. Nava-Arenas, N. Ruiz-Ordaz, C. J. Galindez-Mayer, M. L. Luna-Guido, S. L. Ruiz-López, A. Cabrera-Orozco, D. Nava-Arenas

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Among the most important herbicides, the organochlorine compounds are of considerable interest due to their recalcitrance to the chemical, biological, and photolytic degradation, their persistence in the environment, their mobility, and their bioacummulation. The most widely used herbicides in North America are primarily 2,4-dichlorophenoxyacetic acid (2,4-D), the triazines (atrazine and simazine), and to a lesser extent diuron. The contamination of soils and water bodies frequently occurs by mixtures of these xenobiotics. For this reason, in this work, the operational stability to changes in the composition of the medium supplied to an aerobic biofilm reactor was studied. The reactor was packed with fragments of volcanic rock that retained a complex microbial film, able to degrade a mixture of organochlorine herbicides atrazine, simazine, diuron and 2,4-D, and whose members have microbial genes encoding the main catabolic enzymes atzABCD, tfdACD and puhB. To acclimate the attached microbial community, the biofilm reactor was fed continuously with a mineral minimal medium containing the herbicides (in mg•L-1): diuron, 20.4; atrazine, 14.2, simazine, 11.4, and 2,4-D, 59.7, as carbon and nitrogen sources. Throughout the bioprocess, removal efficiencies of 92-100% for herbicides, 78-90% for COD, 92-96% for TOC and 61-83% for dehalogenation were reached. In the microbial community, the genes encoding catabolic enzymes of different herbicides tfdACD, puhB and, occasionally, the genes atzA and atzC were detected. After the acclimatization, the triazine herbicides were eliminated from the mixture formulation. Volumetric loading rates of the mixture 2,4-D and diuron were continuously supplied to the reactor (1.9-21.5 mg herbicides •L-1 •h-1). Along the bioprocess, the removal efficiencies obtained were 86-100% for the mixture of herbicides, 63-94% for for COD, 90-100% for COT, and dehalogenation values of 63-100%. It was also observed that the genes encoding the enzymes in the catabolism of both herbicides, tfdACD and puhB, were consistently detected; and, occasionally, the atzA and atzC. Subsequently, the triazine herbicide atrazine and simazine were restored to the medium supply. Different volumetric charges of this mixture were continuously fed to the reactor (2.9 to 12.6 mg herbicides •L-1 •h-1). During this new treatment process, removal efficiencies of 65-95% for the mixture of herbicides, 63-92% for COD, 66-89% for TOC and 73-94% of dehalogenation were observed. In this last case, the genes tfdACD, puhB and atzABC encoding for the enzymes involved in the catabolism of the distinct herbicides were consistently detected. The atzD gene, encoding the cyanuric hydrolase enzyme, could not be detected, though it was determined that there was partial degradation of cyanuric acid. In general, the community in the biofilm reactor showed some catabolic stability, adapting to changes in loading rates and composition of the mixture of herbicides, and preserving their ability to degrade the four herbicides tested; although, there was a significant delay in the response time to recover to degradation of the herbicides.

Keywords: biodegradation, biofilm reactor, microbial community, organochlorine herbicides

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Authors: Halimatu S. Abdullahi, Ray E. Sheriff, Fatima Mahieddine

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Agriculture is essential to the continuous existence of human life as they directly depend on it for the production of food. The exponential rise in population calls for a rapid increase in food with the application of technology to reduce the laborious work and maximize production. Technology can aid/improve agriculture in several ways through pre-planning and post-harvest by the use of computer vision technology through image processing to determine the soil nutrient composition, right amount, right time, right place application of farm input resources like fertilizers, herbicides, water, weed detection, early detection of pest and diseases etc. This is precision agriculture which is thought to be solution required to achieve our goals. There has been significant improvement in the area of image processing and data processing which has being a major challenge. A database of images is collected through remote sensing, analyzed and a model is developed to determine the right treatment plans for different crop types and different regions. Features of images from vegetations need to be extracted, classified, segmented and finally fed into the model. Different techniques have been applied to the processes from the use of neural network, support vector machine, fuzzy logic approach and recently, the most effective approach generating excellent results using the deep learning approach of convolution neural network for image classifications. Deep Convolution neural network is used to determine soil nutrients required in a plantation for maximum production. The experimental results on the developed model yielded results with an average accuracy of 99.58%.

Keywords: convolution, feature extraction, image analysis, validation, precision agriculture

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Authors: Thilini Hathurusinghe, Uthpalie Siriwardhana, W. M. Ediri Arachchi, Ranga Thudugala, Indeewari Herath, Gayani Senanayake

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The foramen magnum is more prone to protect than other skeletal remains during high impact and severe disruptive injuries. Therefore, it is worthwhile to explore whether these measurements can be used to determine the human gender which is vital in forensic and anthropological studies. The idea was to find out the ability to use quantitative measurements of foramen magnum as an anatomical indicator for human gender estimation and to evaluate the gender-dependent variations of foramen magnum using quantitative measurements. Randomly selected 113 subjects who underwent CT head scans at Sri Jayawardhanapura General Hospital of Sri Lanka within a period of six months, were included in the study. The sample contained 58 males (48.76 ± 14.7 years old) and 55 females (47.04 ±15.9 years old). Maximum length of the foramen magnum (LFM), maximum width of the foramen magnum (WFM), minimum distance between occipital condyles (MnD) and maximum interior distance between occipital condyles (MxID) were measured. Further, AreaT and AreaR were also calculated. The gender was estimated using binomial logistic regression. The mean values of all explanatory variables (LFM, WFM, MnD, MxID, AreaT, and AreaR) were greater among male than female. All explanatory variables except MnD (p=0.669) were statistically significant (p < 0.05). Significant bivariate correlations were demonstrated by AreaT and AreaR with the explanatory variables. The results evidenced that WFM and MxID were the best measurements in predicting gender according to binomial logistic regression. The estimated model was: log (p/1-p) =10.391-0.136×MxID-0.231×WFM, where p is the probability of being a female. The classification accuracy given by the above model was 65.5%. The quantitative measurements of foramen magnum can be used as a reliable anatomical marker for human gender estimation in the Sri Lankan context.

Keywords: foramen magnum, forensic and anthropological studies, gender estimation, logistic regression

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