Search results for: hazard identification

Authors: Chitresh Kumar, Santanu Gupta

Abstract:

The research work intends to understand the process of initiation, planning and development of capital-intensive urban area level infrastructure development in East Asian Cities (specific to Indian Cities). With the onset of emphasis on sustainable urban transport, self-financed urban local bodies, it has become of utmost important to identify infrastructure and projects on a priority basis, which provide optimal utility to the urban area. Through identification of Spatial, Demographic and Socio-Economic and Political Instability Parameters and their trends for the past 60 years at the urban area and state level, the paper attempts to identify the most suitable time period when initiation of the project would become economically and demographically viable for the city.

Keywords: urban planning, regional planning, mass transit, infrastructure development, spatial planning

Procedia PDF Downloads 536

Authors: H. Nouri, I. E. Achouri, A. Grimes, H. Ait Said, M. Aissou, Y. Zebboudj

Abstract:

This paper aims to analysis the behaviour of DC corona discharge in wire-to-plate electrostatic precipitators (ESP). Current-voltage curves are particularly analysed. Experimental results show that discharge current is strongly affected by the applied voltage. The proposed method of current identification is to use the method of least squares. Least squares problems that of into two categories: linear or ordinary least squares and non-linear least squares, depending on whether or not the residuals are linear in all unknowns. The linear least-squares problem occurs in statistical regression analysis; it has a closed-form solution. A closed-form solution (or closed form expression) is any formula that can be evaluated in a finite number of standard operations. The non-linear problem has no closed-form solution and is usually solved by iterative.

Keywords: electrostatic precipitator, current-voltage characteristics, least squares method, electric field, magnetic field

Procedia PDF Downloads 415

Authors: Muhammad Arif Rahman, Gamma Abdul Jabbar, Enggar Handra Pangestu, Alfi Syahrin Qadri, Iryan Anugrah Putra, Rizqi Ramadhandi.

Abstract:

Indonesia lies above three major tectonic plates, Indo-Australia plate, Eurasia plate, and Pacific plate. Interactions between those plates resulted in high tectonic and volcanic activities that corelates into high risk of geological hazards in adjacent areas, one of the areas is in North of Sulawesi’s Islands. This case raises a problem in terms of infrastructure in order to mitigate existing infrastructure and various future infrastructures plan. One of the infrastructures that is essentials to enhance telecommunication aspect is submarine fiber optic cable, that has risk to geological hazard. This cable is essential that act as backbone in telecommunication. Damaged fiber optic cables can pose serious problem that make existing signal to be loss and have negative impact to people’s social and economic factor with also decreasing various governmental services performance. Submarine cables are facing challenges in terms of geological hazards, for instance are seamounts activity. Previous studies show that until 2023, five seamounts are identified in North of Sulawesi. Seamounts itself can damage and trigger many activities that can risks submarine cables, one of the examples is submarine landslide. Main focuses of this study are to identify new possible seamounts and submarine landslide path in area North of Sulawesi Islands to help minimize risks pose by those hazards, either to existing or future plan submarine cables. Using bathymetry data, this study conduct slope analysis and use distinctive morphological features to interpret possible seamounts. Then we mapped out valleys in between seamounts and determine where sediments might flow in case of landslide, and to finally, know how it affect submarine cables in the area.

Keywords: bathymetry, geological hazard, mitigation, seamount, submarine cable, submarine landslide, volcanic activity

Procedia PDF Downloads 53

Authors: Arslan Murtaza

Abstract:

RFID (Radio Frequency Identification) and WSN (Wireless sensor network) are two significant wireless technologies that have extensive diversity of applications and provide limitless forthcoming potentials. RFID is used to identify existence and location of objects whereas WSN is used to intellect and monitor the environment. Incorporating RFID with WSN not only provides identity and location of an object but also provides information regarding the condition of the object carrying the sensors enabled RFID tag. It can be widely used in stock management, asset tracking, asset counting, security, military, environmental monitoring and forecasting, healthcare, intelligent home, intelligent transport vehicles, warehouse management, and precision agriculture. This assessment presents a brief introduction of RFID, WSN, and integration of WSN and RFID, and then applications related to both RFID and WSN. This assessment also deliberates status of the projects on RFID technology carried out in different computing group projects to be taken on WSN and RFID technology.

Keywords: wireless sensor network, RFID, embedded sensor, Wi-Fi, Bluetooth, integration, time saving, cost efficient

Procedia PDF Downloads 315

Authors: Mohammad Alawairdhi

Abstract:

Customer Relationship Management (CRM) started gaining attention as late as the 1990s, and since then efforts are ongoing to define the domain’s precise specifications. There is yet no single agreed upon definition. However, a predominant majority perceives CRM as a mechanism for enhancing interaction with customers, thereby strengthening the relationship between a business and its clients. From the perspective of Information Technology (IT) companies, CRM systems can be viewed as facilitating software products or services to automate the marketing, selling and servicing functions of an organization. In this paper, we have proposed a Bluetooth enabled CRM system for small- and medium-scale organizations. In the proposed system, Bluetooth technology works as an automatic identification token in addition to its common use as a communication channel. The system comprises a server side accompanied by a user-interface support for both client and server sides. The system has been tested in two environments and users have expressed ease of use, convenience and understandability as major advantages of the proposed solution.

Keywords: customer relationship management, CRM, bluetooth, automatic identification token

Procedia PDF Downloads 330

Authors: Mehwish Jamil Noor

Abstract:

Morphological features of pollen (sculpturing) were useful for identification of different floral taxa. In this study 49 pollen grains, types belonging to 25 families were studied using Scanning Electron Microscope. Shape and sculpturing of pollen ranging from Psilate, scabrate to reticulate, bireticulate and echinolophate. Honey pollen was identified using morphological features, number and arrangement of pore and colpi, size and shape. It presents the first attempt from Pakistan involving extraction of pollen from honey, its identification and taxonomic analysis. Among pollen studied diversity in shape and sculpturing has been observed ranging from Psilate, scabrate to reticulate to bireticulate and echinolophate condition. Pollen has been identified with the help of morphological feature, number and arrangement of pore and colpi, size and shape, reference slides, light microscopic data and previous literature have been consulted for pollen identification. Pollen of closely related species resemble each other therefore pollen identification of airborne and honey pollen is not possible till species level. Survey of flora was carried in parallel to keep the record about the allergenic and melliferous preference of specific sites through surveys and interviews. Their pollination season and geographical distribution were recorded. Two hundred and five including wild and cultivated taxa were identified belonging to sixty-seven families. Major bee attracting wild shrub and trees includes Justicia adhatoda, Acacia nilotica, Ziziphus jujuba, Taraxicum officinalis, Artemisia dubia, Casuarina sp., Ulmus sp., Broussonetia papyrifera, Cupressus sp. or Pinus roxburghii etc. Cultivated crops like Pennisetum typhoides, Nigella sativa, Triticum sativum along with fruit trees of Pyrus, Prunus, Eryobotria, Citrus etc. are popular melliferous floras. Exotic/ introduced species like Eucalyptus or Parthenium hysterophorus, are also frequently visited by bees indicating the significance of those plants in the honey industry. It is concluded that different microscopic analysis techniques give more clear and authentic pictures of and melliferous pollen identification which is well supported by the floral calendar. The diversity of pollen are observed in case of melliferous pollen, and most of the windborne pollen were found less sculptured or psilate expressing the adaptation to the specific mode of pollination. Pollen morphology and sculpturing would serve as a reference for future studies.

Keywords: pollen, allergenic flora, sem, pollen key, Scanning Electron Microscopy (SEM)

Procedia PDF Downloads 182

Authors: LuoJiaoyang, Yu Hongyang

Abstract:

In this paper, we experimented with a new approach to multimodal identification using RGB, RGB-D and voice data. The multimodal combination of RGB and voice data has been applied in tasks such as emotion recognition and has shown good results and stability, and it is also the same in identity recognition tasks. We believe that the data of different modalities can enhance the effect of the model through mutual reinforcement. We try to increase the three modalities on the basis of the dual modalities and try to improve the effectiveness of the network by increasing the number of modalities. We also implemented the single-modal identification system separately, tested the data of these different modalities under clean and noisy conditions, and compared the performance with the multimodal model. In the process of designing the multimodal model, we tried a variety of different fusion strategies and finally chose the fusion method with the best performance. The experimental results show that the performance of the multimodal system is better than that of the single modality, especially in dealing with noise, and the multimodal system can achieve an average improvement of 5%.

Keywords: multimodal, three modalities, RGB-D, identity verification

Procedia PDF Downloads 55

Authors: Buse T. Aydın, Enver Ozdemir

Abstract:

In this study, a double layer authentication scheme between the aircraft and the Air Traffic Control (ATC) tower is designed to prevent any unauthorized aircraft from introducing themselves as friends. The method is a combination of classical cryptographic methods and new generation physical layers. The first layer has employed the embedded key of the aircraft. The embedded key is assumed to installed during the construction of the utility. The other layer is a physical attribute (flight path, distance, etc.) between the aircraft and the ATC tower. We create a mathematical model so that two layers’ information is employed and an aircraft is authenticated as a friend or foe according to the accuracy of the results of the model. The results of the aircraft are compared with the results of the ATC tower and if the values found by the aircraft and ATC tower match within a certain error margin, we mark the aircraft as a friend. In this method, even if embedded key is captured by the enemy aircraft, without the information of the second layer, the enemy can easily be determined. Overall, in this work, we present a more reliable system by adding a physical layer in the authentication process.

Keywords: ADS-B, communication with physical layer security, cryptography, identification friend or foe

Procedia PDF Downloads 140

Authors: Mojtaba Saeedinezhad, Sarah Yousefi

Abstract:

In this paper, we present a hybrid subspace approach for Time Delay Estimation (TDE) in multivariable systems. While several methods have been proposed for time delay estimation in SISO systems, delay estimation in MIMO systems were always a big challenge. In these systems the existing TDE methods have significant limitations because most of procedures are just based on system response estimation or correlation analysis. We introduce a new hybrid method for TDE in MIMO systems based on subspace identification and explicit output error method; and compare its performance with previously introduced procedures in presence of different noise levels and in a statistical manner. Then the best method is selected with multi objective decision making technique. It is shown that the performance of new approach is much better than the existing methods, even in low signal-to-noise conditions.

Keywords: system identification, time delay estimation, ARX, OE, merit ratio, multi variable decision making

Procedia PDF Downloads 330

Authors: Marcos Bosques-Perez, Walter Izquierdo, Harold Martin, Liangdon Deng, Josue Rodriguez, Thony Yan, Mercedes Cabrerizo, Armando Barreto, Naphtali Rishe, Malek Adjouadi

Abstract:

Aerial imagery is a powerful tool when it comes to analyzing temporal changes in ecosystems and extracting valuable information from the observed scene. It allows us to identify and assess various elements such as objects, structures, textures, waterways, and shadows. To extract meaningful information, multispectral cameras capture data across different wavelength bands of the electromagnetic spectrum. In this study, the collected multispectral aerial images were subjected to principal component analysis (PCA) to identify independent and uncorrelated components or features that extend beyond the visible spectrum captured in standard RGB images. The results demonstrate that these principal components contain unique characteristics specific to certain wavebands, enabling effective object identification and image segmentation.

Keywords: big data, image processing, multispectral, principal component analysis

Procedia PDF Downloads 149

Authors: Bernard Kumi-Boateng, Issaka Yakubu

Abstract:

Forest fire, which is, an uncontrolled fire occurring in nature has become a major concern for the Forestry Commission of Ghana (FCG). The forest fires in Ghana usually result in massive destruction and take a long time for the firefighting crews to gain control over the situation. In order to assess the effect of forest fire at local scale, it is important to consider the role fire plays in vegetation composition, biodiversity, soil erosion, and the hydrological cycle. The occurrence, frequency and behaviour of forest fires vary over time and space, primarily as a result of the complicated influences of changes in land use, vegetation composition, fire suppression efforts, and other indigenous factors. One of the forest zones in Ghana with a high level of vegetation stress is the Goaso forest area. The area has experienced changes in its traditional land use such as hunting, charcoal production, inefficient logging practices and rural abandonment patterns. These factors which were identified as major causes of forest fire, have recently modified the incidence of fire in the Goaso area. In spite of the incidence of forest fires in the Goaso forest area, most of the forest services do not provide a cartographic representation of the burned areas. This has resulted in significant amount of information being required by the firefighting unit of the FCG to understand fire risk factors and its spatial effects. This study uses Remote Sensing and Geographic Information System techniques to develop a fire risk hazard model using the Goaso Forest Area (GFA) as a case study. From the results of the study, natural forest, agricultural lands and plantation cover types were identified as the major fuel contributing loads. However, water bodies, roads and settlements were identified as minor fuel contributing loads. Based on the major and minor fuel contributing loads, a forest fire risk hazard model with a reasonable accuracy has been developed for the GFA to assist decision making.

Keywords: forest, GIS, remote sensing, Goaso

Procedia PDF Downloads 434

Authors: Rhaptyalyani Herno Della, Nyimas Septi Rika Putri, Rika Nabila

Abstract:

The growth of population and economic activities in urban areas needs support economic development, needs to be balanced with adequate environmental infrastructure development. Settlement can avoid from rundown condition and uninhabitable if the development of urban area accordance with healthy development. Identifying database of slum in this study reference to the Review of the Spatial Plan Development of Palembang City, Laws of Public Works Department about Technical Guidelines on the Quality Improvement Housing and Slum and Urban Spatial Global Report on Human Settlements 2003. A case study for identifying in Palembang riverbanks area are located in two districts; Ilir Timur I and Ilir Timur II. This study do the identification of slum areas based on several variables about physical and non physical aspect, then the result of identification are used to define a policy that can be used to improve the area.

Keywords: slum, riverbanks area, urban area, infrastructure

Procedia PDF Downloads 324

Authors: Faiz N. K. Yusufi, Aquil Ahmed, Jamal Ahmad

Abstract:

Diabetes in India is growing at an alarming rate and the complications caused by it need to be controlled. Coronary heart disease (CHD) is one of the complications that will be discussed for prediction in this study. India has the second most number of diabetes patients in the world. To the best of our knowledge, there is no CHD risk score for Indian type 2 diabetes patients. Any form of CHD has been taken as the event of interest. A sample of 750 was determined and randomly collected from the Rajiv Gandhi Centre for Diabetes and Endocrinology, J.N.M.C., A.M.U., Aligarh, India. Collected variables include patients data such as sex, age, height, weight, body mass index (BMI), blood sugar fasting (BSF), post prandial sugar (PP), glycosylated haemoglobin (HbA1c), diastolic blood pressure (DBP), systolic blood pressure (SBP), smoking, alcohol habits, total cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), low density lipoprotein (LDL), very low density lipoprotein (VLDL), physical activity, duration of diabetes, diet control, history of antihypertensive drug treatment, family history of diabetes, waist circumference, hip circumference, medications, central obesity and history of CHD. Predictive risk scores of CHD events are designed by cox proportional hazard regression. Model calibration and discrimination is assessed from Hosmer Lemeshow and area under receiver operating characteristic (ROC) curve. Overfitting and underfitting of the model is checked by applying regularization techniques and best method is selected between ridge, lasso and elastic net regression. Youden’s index is used to choose the optimal cut off point from the scores. Five year probability of CHD is predicted by both survival function and Markov chain two state model and the better technique is concluded. The risk scores for CHD developed can be calculated by doctors and patients for self-control of diabetes. Furthermore, the five-year probabilities can be implemented as well to forecast and maintain the condition of patients.

Keywords: coronary heart disease, cox proportional hazard regression, ROC curve, type 2 diabetes Mellitus

Procedia PDF Downloads 204

Authors: Nastaran Moosavi, Mohammad Mokhtari

Abstract:

Seismic inversion is a technique which has been in use for years and its main goal is to estimate and to model physical characteristics of rocks and fluids. Generally, it is a combination of seismic and well-log data. Seismic inversion can be carried out through different methods; we have conducted and compared post-stack and pre- stack seismic inversion methods on real data in one of the fields in the Persian Gulf. Pre-stack seismic inversion can transform seismic data to rock physics such as P-impedance, S-impedance and density. While post- stack seismic inversion can just estimate P-impedance. Then these parameters can be used in reservoir identification. Based on the results of inverting seismic data, a gas reservoir was detected in one of Hydrocarbon oil fields in south of Iran (Persian Gulf). By comparing post stack and pre-stack seismic inversion it can be concluded that the pre-stack seismic inversion provides a more reliable and detailed information for identification and prediction of hydrocarbon reservoirs.

Keywords: density, p-impedance, s-impedance, post-stack seismic inversion, pre-stack seismic inversion

Procedia PDF Downloads 304

Authors: Gerardo Arias, Richard Wall, Jamie Stevens

Abstract:

Lucilia bufonivora Moniez, is an obligate parasite of toads and frogs widely distributed in Europe. Its sister taxon Lucilia silvarum Meigen behaves mainly as a carrion breeder in Europe, however it has been reported as a facultative parasite of amphibians. These two closely related species are morphologically almost identical, which has led to misidentification, and in fact, it has been suggested that the amphibian myiasis cases by L. silvarum reported in Europe should be attributed to L. bufonivora. Both species remain poorly studied and their taxonomic relationships are still unclear. The identification of the larval specimens involved in amphibian myiasis with molecular tools and phylogenetic analysis of these two closely related species may resolve this problem. In this work seventeen unidentified larval specimens extracted from toad myiasis cases of the UK, the Netherlands and Switzerland were obtained, their COX1 (mtDNA) and EF1-α (Nuclear DNA) gene regions were amplified and then sequenced. The 17 larval samples were identified with both molecular markers as L. bufonivora. Phylogenetic analysis was carried out with 10 other blowfly species, including L. silvarum samples from the UK and USA. Bayesian Inference trees of COX1 and a combined-gene dataset suggested that L. silvarum and L. bufonivora are separate sister species. However, the nuclear gene EF1-α does not appear to resolve their relationships, suggesting that the rates of evolution of the mtDNA are much faster than those of the nuclear DNA. This work provides the molecular evidence for successful identification of L. bufonivora and a molecular analysis of the populations of this obligate parasite from different locations across Europe. The relationships with L. silvarum are discussed.

Keywords: calliphoridae, molecular evolution, myiasis, obligate parasitism

Procedia PDF Downloads 215

Authors: Francesco Pandolfi, Georgios Baltzopoulos, Iunio Iervolino

Abstract:

The impact of extreme winds on industrial assets and the built environment is gaining increasing attention from stakeholders, including the corporate insurance industry. This has led to a progressively more in-depth study of building vulnerability and fragility to wind. Wind vulnerability models are used in probabilistic risk assessment to relate a loss metric to an intensity measure of the natural event, usually a gust or a mean wind speed. In fact, vulnerability models can be integrated with the wind hazard, which consists of associating a probability to each intensity level in a time interval (e.g., by means of return periods) to provide an assessment of future losses due to extreme wind. This has also given impulse to the world- and regional-scale wind hazard studies.Another approach often adopted for the probabilistic description of building vulnerability to the wind is the use of fragility functions, which provide the conditional probability that selected building components will exceed certain damage states, given wind intensity. In fact, in wind engineering literature, it is more common to find structural system- or component-level fragility functions rather than wind vulnerability models for an entire building. Loss assessment based on component fragilities requires some logical combination rules that define the building’s damage state given the damage state of each component and the availability of a consequence model that provides the losses associated with each damage state. When risk calculations are based on numerical simulation of a structure’s behavior during extreme wind scenarios, the interaction of component fragilities is intertwined with the computational procedure. However, simulation-based approaches are usually computationally demanding and case-specific. In this context, the present work introduces the ExtReMe wind risk assESsment prototype Software, ERMESS, which is being developed at the University of Naples Federico II. ERMESS is a wind risk assessment tool for insurance applications to industrial facilities, collecting a wide assortment of available wind vulnerability models and fragility functions to facilitate their incorporation into risk calculations based on in-built or user-defined wind hazard data. This software implements an alternative method for building-specific risk assessment based on existing component-level fragility functions and on a number of simplifying assumptions for their interactions. The applicability of this alternative procedure is explored by means of an illustrative proof-of-concept example, which considers four main building components, namely: the roof covering, roof structure, envelope wall and envelope openings. The application shows that, despite the simplifying assumptions, the procedure can yield risk evaluations that are comparable to those obtained via more rigorous building-level simulation-based methods, at least in the considered example. The advantage of this approach is shown to lie in the fact that a database of building component fragility curves can be put to use for the development of new wind vulnerability models to cover building typologies not yet adequately covered by existing works and whose rigorous development is usually beyond the budget of portfolio-related industrial applications.

Keywords: component wind fragility, probabilistic risk assessment, vulnerability model, wind-induced losses

Procedia PDF Downloads 172

Authors: Jafar Ahmadi, Nafiseh Noormohammadi, Sedegeh Fabriki Ourang

Abstract:

GRF, Growth regulating factor, genes encode a novel class of plant-specific transcription factors. The GRF proteins play a role in the regulation of cell numbers in young and growing tissues and may act as transcription activations in growth and development of plants. Identification of GRF genes and their expression are important in plants to performance of the growth and development of various organs. In this study, to better understanding the structural and functional differences of GRFs family, 45 GRF proteins sequences in A. thaliana, Z. mays, O. sativa, B. napus, B. rapa, H. vulgare, and S. bicolor, have been collected and analyzed through bioinformatics data mining. As a result, in secondary structure of GRFs, the number of alpha helices was more than beta sheets and in all of them QLQ domains were completely in the biggest alpha helix. In all GRFs, QLQ, and WRC domains were completely protected except in AtGRF9. These proteins have no trans-membrane domain and due to have nuclear localization signals act in nuclear and they are component of unstable proteins in the test tube.

Keywords: domain, gene family, GRF, motif

Procedia PDF Downloads 440

Authors: Mehrnaz Mostafavi

Abstract:

Recent advances in single-molecule protein identification (ID) and quantification techniques are poised to revolutionize proteomics, enabling researchers to delve into single-cell proteomics and identify low-abundance proteins crucial for biomedical and clinical research. This paper introduces a different approach to single-molecule protein ID and quantification using tri-color amino acid tags and a plasmonic nanopore device. A comprehensive simulator incorporating various physical phenomena was designed to predict and model the device's behavior under diverse experimental conditions, providing insights into its feasibility and limitations. The study employs a whole-proteome single-molecule identification algorithm based on convolutional neural networks, achieving high accuracies (>90%), particularly in challenging conditions (95–97%). To address potential challenges in clinical samples, where post-translational modifications affecting labeling efficiency, the paper evaluates protein identification accuracy under partial labeling conditions. Solid-state nanopores, capable of processing tens of individual proteins per second, are explored as a platform for this method. Unlike techniques relying solely on ion-current measurements, this approach enables parallel readout using high-density nanopore arrays and multi-pixel single-photon sensors. Convolutional neural networks contribute to the method's versatility and robustness, simplifying calibration procedures and potentially allowing protein ID based on partial reads. The study also discusses the efficacy of the approach in real experimental conditions, resolving functionally similar proteins. The theoretical analysis, protein labeler program, finite difference time domain calculation of plasmonic fields, and simulation of nanopore-based optical sensing are detailed in the methods section. The study anticipates further exploration of temporal distributions of protein translocation dwell-times and the impact on convolutional neural network identification accuracy. Overall, the research presents a promising avenue for advancing single-molecule protein identification and quantification with broad applications in proteomics research. The contributions made in methodology, accuracy, robustness, and technological exploration collectively position this work at the forefront of transformative developments in the field.

Keywords: nano proteomics, nanopore-based optical sensing, deep learning, artificial intelligence

Procedia PDF Downloads 56

Authors: Afifa Aslam, Muhammad Ibrahim, Abid Mahmood, Muhammad Usman Alvi, Fariha Jabeen, Umara Tabassum

Abstract:

Many factors cause air pollution in Pakistan, which poses a significant threat to human health. Diesel fuel and gasoline motor vehicles, as well as industrial companies, pollute the air in Pakistan's cities. The study's goal is to determine the level of air pollution in a Pakistani industrial city and to establish risk levels for the health of the population. We measured the intensity of air pollution by chemical characterization and examination of air samples collected at stationary remark sites. The PM10 levels observed at all sampling sites, including residential, commercial, high-traffic, and industrial areas were well above the limits imposed by Pakistan EPA, the United States EPA, and WHO. We assessed the health risk via chemical factors using a methodology approved for risk assessment. All Igeo index values greater than one were considered moderately contaminated or moderately to severely contaminated. Heavy metals have a substantial risk of acute adverse effects. In Faisalabad, Pakistan, there was an enormously high risk of chronic effects produced by a heavy metal acquaintance. Concerning specified toxic metals, intolerable levels of carcinogenic risks have been determined for the entire population. As a result, in most of the investigated areas of Faisalabad, the indices and hazard quotients for chronic and acute exposure exceeded the permissible level of 1.0. In the current study, re-suspended roadside mineral dust, anthropogenic exhaust emissions from traffic and industry, and industrial dust were identified as major emission sources of elemental particulate contents. Because of the unacceptable levels of risk in the research area, it is strongly suggested that a comprehensive study of the population's health status as a result of air pollution should be conducted for policies to be developed against these risks.

Keywords: elemental composition, particulate pollution, Igeo index, health risk assessment, hazard quotient

Procedia PDF Downloads 72

Authors: Tsega Asresa Mengistu, Getahun Tigistu

Abstract:

Computer vision is an artificial intelligence subfield that allows computers and systems to retrieve meaning from digital images. It is applied in various fields of study self-driving cars, video surveillance, agriculture, Quality control, Health care, construction, military, and everyday life. Aromatic and medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, and other natural health products for therapeutic and Aromatic culinary purposes. Herbal industries depend on these special plants. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs, and going to export not only industrial raw materials but also valuable foreign exchange. There is a lack of technologies for the classification and identification of Aromatic and medicinal plants in Ethiopia. The manual identification system of plants is a tedious, time-consuming, labor, and lengthy process. For farmers, industry personnel, academics, and pharmacists, it is still difficult to identify parts and usage of plants before ingredient extraction. In order to solve this problem, the researcher uses a deep learning approach for the efficient identification of aromatic and medicinal plants by using a convolutional neural network. The objective of the proposed study is to identify the aromatic and medicinal plant Parts and usages using computer vision technology. Therefore, this research initiated a model for the automatic classification of aromatic and medicinal plants by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides the root, flower and fruit, latex, and barks. The study was conducted on aromatic and medicinal plants available in the Ethiopian Institute of Agricultural Research center. An experimental research design is proposed for this study. This is conducted in Convolutional neural networks and Transfer learning. The Researcher employs sigmoid Activation as the last layer and Rectifier liner unit in the hidden layers. Finally, the researcher got a classification accuracy of 66.4 in convolutional neural networks and 67.3 in mobile networks, and 64 in the Visual Geometry Group.

Keywords: aromatic and medicinal plants, computer vision, deep convolutional neural network

Procedia PDF Downloads 403

Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

Abstract:

Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: genetic data, Pinzgau cattle, supervised learning, machine learning

Procedia PDF Downloads 532

Authors: Jin Liang, Q. Li, Yue Qi, Liying Wang, Wenhua Yu, Xun Liu

Abstract:

Fertility is very important for women. The gender role of women gives them the fertility ability. Giving birth to a boy or a girl might have effect on the mother’s life in the past in China. However, with the shifting of traditional attitudes and views, the women's social status and living situation have been transformed. Although the pregnancy and childbirth can still bring them a major impact on their lives, the form and content of the impact have changed. So we investigated the rural women of Hebei province after birth to reflect their living situation changes before and after birth and the differences of their living situation from women in the past by using a self-made rural women life situation change questionnaire, the index of well-being, and the index of general effect questionnaire. It has shown that women’s living situation after babybirth in Hebei province is well in general, and their mind and body, as well as their interpersonal relationships and social status, were all enhanced. The women’s living situation after babybirth was positively related to and could anticipate subjective happiness, and specifically, the rural women’s mind and body, their interpersonal relationship and social status in rural women life situation change questionnaire are the main predicted factors to subjective happiness. Furthermore, the women’s self-identification on female roles was influenced by the children’s gender. Specifically, women with only one daughter had highest self-identification on female roles, consisting with their families' concept about children’s gender, which indicated family values have a great effect on women’s self-identification on female roles in rural. Moreover, the women’s living situation and subjective happiness are both impacted by home incomes.

Keywords: rural women, parturition, well-being, life quality

Procedia PDF Downloads 223

Authors: Ronit Chakraborty, Sugata Banerji

Abstract:

There has been a marked increase in the reported prevalence of Autism Spectrum Disorder (ASD) among children in the US over the past two decades. This research has analyzed the growth in state-level ASD prevalence against 45 different potentially explanatory factors, including socio-economic, demographic, healthcare, public policy, and political factors. The goal was to understand if these factors have adequate predictive power in modeling the differential growth in ASD prevalence across various states and if they do, which factors are the most influential. The key findings of this study include (1) the confirmation that the chosen feature set has considerable power in predicting the growth in ASD prevalence, (2) the identification of the most influential predictive factors, (3) given the nature of the most influential predictive variables, an indication that a considerable portion of the reported ASD prevalence differentials across states could be attributable to over and under diagnosis, and (4) identification of Florida as a key outlier state pointing to a potential under-diagnosis of ASD there.

Keywords: autism spectrum disorder, clustering, machine learning, predictive modeling

Procedia PDF Downloads 83

Authors: E. Ormeno, C. Gutigny, J. Ruffault, J. Madrigal, M. Guijarro, C. Lecareux, C. Ballini

Abstract:

Mediterranean plant species feature numerous metabolic and morpho-physiological responses crucial to survive under both, typical Mediterranean drought conditions and future aggravated drought expected by climate change. Whether these adaptive responses will, in turn, increase the ecosystem perturbation in terms of fire hazard, is an issue that needs to be addressed. The aim of this study was to test whether recurrent and aggravated drought in the Mediterranean area favors the accumulation of waxes in leaf litter, with an eventual increase of litter flammability. The study was conducted in 2017 in a garrigue in Southern France dominated by Quercus coccifera, where two drought treatments were used: a treatment with recurrent aggravated drought consisting of ten rain exclusion structures which withdraw part of the annual precipitation since January 2012, and a natural drought treatment where Q. coccifera stands are free of such structures and thus grow under natural precipitation. Waxes were extracted with organic solvent and analyzed by GC-MS and litter flammability was assessed through measurements of the ignition delay, flame residence time and flame intensity (flame height) using an epiradiator as well as the heat of combustion using an oxygen bomb calorimeter. Results show that after 5 years of rain restriction, wax content in the cuticle of leaf litter increases significantly compared to shrubs growing under natural precipitation, in accordance with the theoretical knowledge which expects increases of cuticle waxes in green leaves in order to limit water evapotranspiration. Wax concentrations were also linearly and positively correlated to litter flammability, a correlation that lies on the high flammability own to the long-chain alkanes (C25-C31) found in leaf litter waxes. This innovative investigation shows that climate change is likely to favor ecosystem fire hazard through accumulation of highly flammable waxes in litter. It also adds valuable information about the types of metabolites that are associated with increasing litter flammability, since so far, within the leaf metabolic profile, only terpene-like compounds had been related to plant flammability.

Keywords: cuticular waxes, drought, flammability, litter

Procedia PDF Downloads 155

Authors: Gamze Ozel, Selen Cakmakyapan

Abstract:

We introduce a new model called the Marshall-Olkin Rayleigh distribution which extends the Rayleigh distribution using Marshall-Olkin transformation and has increasing and decreasing shapes for the hazard rate function. Various structural properties of the new distribution are derived including explicit expressions for the moments, generating and quantile function, some entropy measures, and order statistics are presented. The model parameters are estimated by the method of maximum likelihood and the observed information matrix is determined. The potentiality of the new model is illustrated by means of real life data set.

Keywords: Marshall-Olkin distribution, Rayleigh distribution, estimation, maximum likelihood

Procedia PDF Downloads 487

Authors: V. Agostini, S. Gino, S. Inturri, A. Piccinini

Abstract:

In cases of corpse identification or parental testing performed on exhumed alleged dead father, usually, we seek and acquire organic samples as bones and/or bone fragments, teeth, nails and muscle’s fragments. The DNA analysis of these cadaveric matrices usually leads to identifying success, but it often happens that the results of the typing are not satisfactory with highly degraded, partial or even non-interpretable genetic profiles. To aggravate the interpretative panorama deriving from the analysis of such 'classical' organic matrices, we must add a long and laborious treatment of the sample that starts from the mechanical fragmentation up to the protracted decalcification phase. These steps greatly increase the chance of sample contamination. In the present work, instead, we want to report the use of 'unusual' cadaveric matrices, demonstrating that their forensic genetics analysis can lead to better results in less time and with lower costs of reagents. We report six case reports, result of on-field experience, in which eyeswabs and cartilage were sampled and analyzed, allowing to obtain clear single genetic profiles, useful for identification purposes. In all cases we used the standard DNA tissue extraction protocols (as reported on the user manuals of the manufacturers such as QIAGEN or Invitrogen- Thermo Fisher Scientific), thus bypassing the long and difficult phases of mechanical fragmentation and decalcification of bones' samples. PCR was carried out using PowerPlex® Fusion System kit (Promega), and capillary electrophoresis was carried out on an ABI PRISM® 310 Genetic Analyzer (Applied Biosystems®), with GeneMapper ID v3.2.1 (Applied Biosystems®) software. The software Familias (version 3.1.3) was employed for kinship analysis. The genetic results achieved have proved to be much better than the analysis of bones or nails, both from the qualitative and quantitative point of view and from the point of view of costs and timing. This way, by using the standard procedure of DNA extraction from tissue, it is possible to obtain, in a shorter time and with maximum efficiency, an excellent genetic profile, which proves to be useful and can be easily decoded for later paternity tests and/or identification of human remains.

Keywords: DNA, eye swabs and cartilage, identification human remains, paternity testing

Procedia PDF Downloads 92

Authors: Muhammad Fezan Afzal, Imran Khan, Salma Imtiaz

Abstract:

The need for human verification and identification requires from centuries for authentication. Since it is being used in big institutes like financial, government and crime departments, a continued struggle is important to make this system more efficient to prevent security breaches. Therefore, multiple devices are used to authenticate the biometric for each individual. A large number of devices are required to cover a large number of users. As the number of devices increases, cost will automatically increase. Furthermore, it is time-consuming for biometrics due to the devices being insufficient and are not available at every door. In this paper, we propose the framework and algorithm where the mobile of each individual can also perform the biometric authentication of attendance and security. Every mobile has a biometric authentication system that is used in different mobile applications for security purposes. Therefore, each individual can use the biometric system mobile without moving from one place to another. Moreover, by using the biometrics mobile, the cost of biometric systems can be removed that are mostly deployed in different organizations for the attendance of students, employees and for other security purposes.

Keywords: fingerprint, fingerprint authentication, mobile verification, mobile biometric verification, mobile fingerprint sensor

Procedia PDF Downloads 52

Authors: K. Khlifi, A. Haddouk, M. Hlaili, H. Mechergui

Abstract:

The present paper provides a detailed analysis of prior methods and approaches for non-linear load identification in residential buildings. The main goal of this analysis is to decipher the distorted signals and to estimate the harmonics influence on power systems. We have performed an analytical study of non-linear loads behavior in the residential environment. Simulations have been performed in order to evaluate the distorted rate of the current and follow his behavior. To complete this work, an instrumental platform has been realized to carry out practical tests on single-phase non-linear loads which illustrate the current consumption of some domestic appliances supplied with single-phase sinusoidal voltage. These non-linear loads have been processed and tracked in order to limit their influence on the power grid and to reduce the Joule effect losses. As a result, the study has allowed to identify responsible circuits of harmonic pollution.

Keywords: distortion rate, harmonic analysis, harmonic pollution, non-linear load, power factor

Procedia PDF Downloads 131

Authors: Chia-Chun Wu, Yu-Hsien Sung

Abstract:

This study aims to examine the consistency between students’ predictions and their actual observations on the bullying prevalence rate among different types of high-risk victims, thereby clarifying the reliability of students’ reports on the identification of bullying. A total of 1,732 Taiwanese students (734 males and 998 females) participated in this study. A Rasch model was adopted for data analysis. The results showed that students with “personality or behavioral issues” are more likely to be bullied in schools, based on both students’ predictions and actual observations. Moreover, the results differed significantly between genders and between various educational levels in students’ predictions and their actual observations on the bullying prevalence rate of different types of high-risk victims. To summarize, this study not only suggests that students’ reports on the identification of bullying are accurate and could be a valuable reference in terms of recognizing a bullying incident, but it also argues that more attention should be paid to students’ gender and educational level when taking their perspectives into consideration when it comes to identifying bullying behaviors.

Keywords: school bullying, student, bullying recognition, high-risk victims

Procedia PDF Downloads 69

Authors: Zoya Khan, Amina Muzaffar

Abstract:

Social media based brand communities are communities that are developed around a brand. In the highly globalized world of today, Facebook is undoubtedly being regarded and has been widely recognized as a trendy and well-accepted medium of marketing. By means of a Facebook fan page, organizations can effectually create, enhance, and sustain customer-brand relationship. In this article, we explore whether brand communities based on social media (a special type of online brand communities) have positive effects on the main community elements and value creation practices in the communities as well as on brand trust and brand loyalty. A survey was conducted and 201 valid responses were used for analysis. The results of structural equation modeling show that brand communities established on social media have positive effects on value creation practices. Brand use, impression management practices and brand identification has an impact on brand trust and this brand trust then further leads to brand loyalty.

Keywords: relationship quality, impression management practices, brand identification, brand trust, brand loyalty

Procedia PDF Downloads 460