Search results for: comparative morphological features

Authors: Natalia Alzate-Carvajal, Diego A. Acevedo-Guzman, Victor Meza-Laguna, Mario H. Farias, Luis A. Perez-Rey, Edgar Abarca-Morales, Victor A. Garcia-Ramirez, Vladimir A. Basiuk, Elena V. Basiuk

Abstract:

Direct covalent functionalization of prefabricated free-standing graphene oxide paper (GOP) is considered as the only approach suitable for systematic tuning of thermal, mechanical and electronic characteristics of this important class of carbon nanomaterials. At the same time, the traditional liquid-phase functionalization protocols can compromise physical integrity of the paper-like material up to its total disintegration. To avoid such undesirable effects, we explored the possibility of employing an alternative, solvent-free strategy for facile and nondestructive functionalization of GOP with two representative aliphatic amines, 1-octadecylamine (ODA) and 1,12-diaminododecane (DAD), as well as with two aromatic amines, 1-aminopyrene (AP) and 1,5-diaminonaphthalene (DAN). The functionalization was performed under moderate heating at 150-180 °C in vacuum. Under such conditions, it proceeds through both amidation and epoxy ring opening reactions. Comparative characterization of pristine and amine-functionalized GOP mats was carried out by using Fourier-transform infrared, Raman, and X-ray photoelectron spectroscopy (XPS), thermogravimetric (TGA) and differential thermal analysis, scanning electron and atomic force microscopy (SEM and AFM, respectively). Besides that, we compared the stability in water, wettability, electrical conductivity and elastic (Young's) modulus of GOP mats before and after amine functionalization. The highest content of organic species was obtained in the case of GOP-ODA, followed by GOP-DAD, GOP-AP and GOP-DAN samples. The covalent functionalization increased mechanical and thermal stability of GOP, as well as its electrical conductivity. The magnitude of each effect depends on the particular chemical structure of amine employed, which allows for tuning a given GOP property. Morphological characterization by using SEM showed that, compared to pristine graphene oxide paper, amine-modified GOP mats become relatively ordered layered assemblies, in which individual GO sheets are organized in a near-parallel pattern. Financial support from the National Autonomous University of Mexico (grants DGAPA-IN101118 and IN200516) and from the National Council of Science and Technology of Mexico (CONACYT, grant 250655) is greatly appreciated. The authors also thank David A. Domínguez (CNyN of UNAM) for XPS measurements and Dr. Edgar Alvarez-Zauco (Faculty of Science of UNAM) for the opportunity to use TGA equipment.

Keywords: amines, covalent functionalization, gas-phase, graphene oxide paper

Procedia PDF Downloads 179

Authors: N. W. U. D. Chathurani, Shlomo Geva, Vinod Chandran, Proboda Rajapaksha

Abstract:

Selecting an appropriate image representation is the most important factor in implementing an effective Content-Based Image Retrieval (CBIR) system. This paper presents a multi-feature fusion approach for efficient CBIR, based on the distance distribution of features and relative feature weights at the time of query processing. It is a simple yet effective approach, which is free from the effect of features' dimensions, ranges, internal feature normalization and the distance measure. This approach can easily be adopted in any feature combination to improve retrieval quality. The proposed approach is empirically evaluated using two benchmark datasets for image classification (a subset of the Corel dataset and Oliva and Torralba) and compared with existing approaches. The performance of the proposed approach is confirmed with the significantly improved performance in comparison with the independently evaluated baseline of the previously proposed feature fusion approaches.

Keywords: feature fusion, image retrieval, membership function, normalization

Procedia PDF Downloads 344

Authors: Bo Wang

Abstract:

The geometric processing of multi-source remote sensing data using control data of different scale and different accuracy is an important research direction of multi-platform system for earth observation. In the existing block bundle adjustment methods, as the controlling information in the adjustment system, the approach using single observation scale and precision is unable to screen out the control information and to give reasonable and effective corresponding weights, which reduces the convergence and adjustment reliability of the results. Referring to the relevant theory and technology of quotient space, in this project, several subjects are researched. Multi-layer quotient space of multi-geometric features is constructed to describe and filter control data. Normalized granularity merging mechanism of multi-layer control information is studied and based on the normalized scale factor, the strategy to optimize the weight selection of control data which is less relevant to the adjustment system can be realized. At the same time, geometric positioning experiment is conducted using multi-source remote sensing data, aerial images, and multiclass control data to verify the theoretical research results. This research is expected to break through the cliché of the single scale and single accuracy control data in the adjustment process and expand the theory and technology of photogrammetry. Thus the problem to process multi-source remote sensing data will be solved both theoretically and practically.

Keywords: multi-source image geometric process, high precision geometric positioning, quotient space of multi-geometric features, optimized weight selection

Procedia PDF Downloads 283

Authors: Zuzanna Miodonska, Michal Krecichwost, Pawel Badura

Abstract:

Sigmatism (lisping) is a speech disorder in which sibilant consonants are mispronounced. The diagnosis of this phenomenon is usually based on the auditory assessment. However, the progress in speech analysis techniques creates a possibility of developing computer-aided sigmatism diagnosis tools. The aim of the study is to statistically verify whether specific acoustic features of sibilant sounds may be related to pronunciation correctness. Such knowledge can be of great importance while implementing classifiers and designing novel tools for automatic sibilants pronunciation evaluation. The study covers analysis of various speech signal measures, including features proposed in the literature for the description of normative sibilants realization. Amplitudes and frequencies of three fricative formants (FF) are extracted based on local spectral maxima of the friction noise. Skewness, kurtosis, four normalized spectral moments (SM) and 13 mel-frequency cepstral coefficients (MFCC) with their 1st and 2nd derivatives (13 Delta and 13 Delta-Delta MFCC) are included in the analysis as well. The resulting feature vector contains 51 measures. The experiments are performed on the speech corpus containing words with selected sibilant sounds (/ʃ, ʒ/) pronounced by 60 preschool children with proper pronunciation or with natural pathologies. In total, 224 /ʃ/ segments and 191 /ʒ/ segments are employed in the study. The Mann-Whitney U test is employed for the analysis of stigmatism and normative pronunciation. Statistically, significant differences are obtained in most of the proposed features in children divided into these two groups at p < 0.05. All spectral moments and fricative formants appear to be distinctive between pathology and proper pronunciation. These metrics describe the friction noise characteristic for sibilants, which makes them particularly promising for the use in sibilants evaluation tools. Correspondences found between phoneme feature values and an expert evaluation of the pronunciation correctness encourage to involve speech analysis tools in diagnosis and therapy of sigmatism. Proposed feature extraction methods could be used in a computer-assisted stigmatism diagnosis or therapy systems.

Keywords: computer-aided pronunciation evaluation, sigmatism diagnosis, speech signal analysis, statistical verification

Procedia PDF Downloads 299

Authors: Yasmine Abu Adla, Racha Soubra, Milana Kasab, Mohamad O. Diab, Aly Chkeir

Abstract:

Over the past several years, researchers have shown a great interest in assessing the mobility of elderly people to measure their functional status. Usually, such an assessment is done by conducting tests that require the subject to walk a certain distance, turn around, and finally sit back down. Consequently, this study aims to provide an at home monitoring system to assess the patient’s status continuously. Thus, we proposed a technique to automatically detect when a subject sits down while walking at home. In this study, we utilized a Doppler radar system to capture the motion of the subjects. More than 20 features were extracted from the radar signals, out of which 11 were chosen based on their intraclass correlation coefficient (ICC > 0.75). Accordingly, the sequential floating forward selection wrapper was applied to further narrow down the final feature vector. Finally, 5 features were introduced to the linear discriminant analysis classifier, and an accuracy of 93.75% was achieved as well as a precision and recall of 95% and 90%, respectively.

Keywords: Doppler radar system, stand-to-sit phase, TUG test, machine learning, classification

Procedia PDF Downloads 160

Authors: Rachel Falconer

Abstract:

Background: The United Nations Convention on the Rights of the Child sets out the duties placed on signatory nations to take measures to protect children from all forms of violence, abuse, neglect and maltreatment. The systems for ensuring this protection vary globally, shaped by national welfare policies. In England and Finland, past research has highlighted differences in how child protection issues are framed and how state agencies respond. However, less is known about how such differences impact processes of social work judgment and decision making in practice. Method: Data was collected as part of a wider PhD project in three stages. First, social workers in sites across England and Finland were asked to complete a short questionnaire. Participants were then asked to comment on two constructed case vignettes, and were interviewed about their experiences of child protection decision making at the point of referral. Interviews were analyzed using NVivo to draw out key themes. Findings: There were similarities in how the English and Finnish social workers responded to the case vignettes; for example, participants in both countries expressed concerns about similar risk factors and all felt further assessment was needed. Differences were observed, in particular, in regard to the sources of support and guidance participants referred to, with the English social workers appearing to rely more upon managerial input for their decisions than the Finnish social workers. These findings suggest evidence for two distinct decision making approaches: ‘supervised’ and ‘supported’ judgement. Implications for practice: The findings have relevance to the conference theme of research and evaluation of social work practice, and support the findings of previous studies that have emphasized the significance of organizational factors in child protection decision making. The comparative methodology has also helped to demonstrate how organizational factors can influence practice in different child protection system ‘orientations’. The presentation will discuss the potential practice implications of ‘supervised’, manager-led approaches to decision making as contrasted with ‘supported’, team-led approaches, inviting discussion about the relevance of these findings for social work in other countries.

Keywords: child protection, comparative research, decision making, social work, vignettes

Procedia PDF Downloads 252

Authors: Anas H. Aljemely, Jianping Xuan

Abstract:

Rolling bearing fault diagnosis plays a pivotal issue in the rotating machinery of modern manufacturing. In this research, a raw vibration signal and improved deep learning method for bearing fault diagnosis are proposed. The multi-dimensional scales of raw vibration signals are selected for evaluation condition monitoring system, and the deep learning process has shown its effectiveness in fault diagnosis. In the proposed method, employing an Exponential linear unit (ELU) layer in a convolutional neural network (CNN) that conducts the identical function on positive data, an exponential nonlinearity on negative inputs, and a particular convolutional operation to extract valuable features. The identification results show the improved method has achieved the highest accuracy with a 100-dimensional scale and increase the training and testing speed.

Keywords: bearing fault prognostics, developed CNN model, multiple-scale evaluation, deep learning features

Procedia PDF Downloads 208

Authors: Mathieu Bourdeau, Philippe Basset, Julien Waeytens, Elyes Nefzaoui

Abstract:

As residential buildings account for a third of the overall energy consumption and greenhouse gas emissions in Europe, building energy modeling is an essential tool to reach energy efficiency goals. In the energy modeling process, calibration is a mandatory step to obtain accurate and reliable energy simulations. Nevertheless, the comparison between simulation results and the actual building energy behavior often highlights a significant performance gap. The literature discusses different origins of energy performance gaps, from building design to building operation. Then, building operation description in energy models, especially energy usages and users’ behavior, plays an important role in the reliability of simulations but is also the most accessible target for post-occupancy energy management and optimization. Therefore, the present study aims to discuss results on the calibration ofresidential building energy models using real operation data. Data are collected through a sensor network of more than 180 sensors and advanced energy meters deployed in three collective residential buildings undergoing major retrofit actions. The sensor network is implemented at building scale and in an eight-apartment sample. Data are collected for over one year and half and coverbuilding energy behavior – thermal and electricity, indoor environment, inhabitants’ comfort, occupancy, occupants behavior and energy uses, and local weather. Building energy simulations are performed using a physics-based building energy modeling software (Pleaides software), where the buildings’features are implemented according to the buildingsthermal regulation code compliance study and the retrofit project technical files. Sensitivity analyses are performed to highlight the most energy-driving building features regarding each end-use. These features are then compared with the collected post-occupancy data. Energy-driving features are progressively replaced with field data for a step-by-step calibration of the energy model. Results of this study provide an analysis of energy performance gap on an existing residential case study under deep retrofit actions. It highlights the impact of the different building features on the energy behavior and the performance gap in this context, such as temperature setpoints, indoor occupancy, the building envelopeproperties but also domestic hot water usage or heat gains from electric appliances. The benefits of inputting field data from an extensive instrumentation campaign instead of standardized scenarios are also described. Finally, the exhaustive instrumentation solution provides useful insights on the needs, advantages, and shortcomings of the implemented sensor network for its replicability on a larger scale and for different use cases.

Keywords: calibration, building energy modeling, performance gap, sensor network

Procedia PDF Downloads 158

Authors: Ronli Sifris

Abstract:

The last Australian Parliamentary inquiry into surrogacy took place in 2016. Since then, a number of countries have reviewed their surrogacy laws, including countries such as New Zealand and the United Kingdom, which traditionally have invoked similar legal approaches to Australia on a broad range of issues. The time is ripe to reform Australia’s surrogacy laws with a view to putting in place a system that best protects the rights of all parties to a surrogacy arrangement, and especially the rights of the child. There are two specific, linked issues which tend to be particularly contentious in the surrogacy context. The first relates to legal parentage. There are questions around whether the surrogate or the intended parents should be deemed the legal parents of a child born through surrogacy and what should be the process for any transfer of parentage. The second key issue relates to compensation and whether a surrogate should be compensated for the reproductive labour inherent in conceiving, gestating, and birthing a child. This paper will invoke a comparative analysis with a view to considering how different countries are regulating surrogacy and which approach best protects the rights all parties involved in the surrogacy arrangement, especially the rights of the children born through surrogacy. The specific countries to be considered are Australia, Canada, and California (United States). I have selected these countries for the following reasons: Australia is the jurisdiction where the author is based, it is, therefore, the jurisdiction with which she has the most familiarity. It allows altruistic surrogacy only and post-birth parentage orders in favour of the intended parents of children born through altruistic surrogacy California, as a jurisdiction allowing for compensated surrogacy and pre-birth parentage orders in favour of the intended parents, sits at the other end of the spectrum to Australia thereby providing an interesting point of comparison. Canada sits somewhere in the middle; it ostensibly allows only altruistic surrogacy, but in practice, many aspects of the Canadian process resemble compensated surrogacy. In addition to conducting a comparative analysis with other countries, the paper will also consider international human rights law as its overarching framework for determining the approach that best protects the rights of a child born through surrogacy. Particular attention will be paid to the United Nations Convention on the Rights of the Child as the key children’s rights treaty. The European Court of Human Rights will also be extensively considered as it has decided a number of cases relating to the rights of children born through surrogacy.

Keywords: surrogacy, children’s rights, australia, compensation, parentage

Procedia PDF Downloads 129

Authors: Kinnsley Travis, Camerron M. Crowder

Abstract:

Mapk8ip3 (Mitogen-Activated Protein Kinase 8 Interacting Protein 3) is a gene that codes for the JIP3 protein, which is a part of the JIP scaffolding protein family. This protein is involved in axonal vesicle transport, elongation and regeneration. Variants in the Mapk8ip3 gene are associated with a rare-genetic condition that results in a neurodevelopmental disorder that can cause a range of phenotypes including global developmental delay and intellectual disability. Currently, there are 18 known individuals diagnosed to have sequenced confirmed Mapk8ip3 genetic disorders. This project focuses on examining the impact of a subset of missense patient variants on the Jip3 protein function by overexpressing the mRNA of these variants in a zebrafish knockout model for Jip3. Plasmids containing cDNA with individual missense variants were reverse transcribed, purified, and injected into single-cell zebrafish embryos (Wild Type, Jip3 -/+, and Jip3 -/-). At 6-days post mRNA microinjection, morphological, behavioral, and microscopic phenotypes were examined in zebrafish larvae. Morphologically, we compared the size and shape of the zebrafish during their development over a 5-day period. Total locomotive activity was assessed using the Microtracker assay and patterns of movement over time were examined using the DanioVision assay. Lastly, we used confocal microscopy to examine sensory axons for swelling and shortened length, which are phenotypes observed in the loss-of-function knockout Jip3 zebrafish model. Using these assays during embryonic development, we determined the impact of various missense variants on Jip3 protein function, compared to knockout and wild-type zebrafish embryo models. Variants in the gene Mapk8ip3 cause rare-neurodevelopmental disorders due to an essential role in axonal vesicle transport, elongation and regeneration. A subset of missense variants was examined by overexpressing the mRNA of these variants in a Jip3 knock-out zebrafish. Morphological, behavioral, and microscopic phenotypes were examined in zebrafish larvae. Using these assays, the spectrum of disorders can be phenotypically determined and the impact of variant location can be compared to knockout and wild-type zebrafish embryo models.

Keywords: rare disease, neurodevelopmental disorders, mrna overexpression, zebrafish research

Procedia PDF Downloads 115

Authors: Sajadian Akram, Tavasoli F.

Abstract:

Breast cancer is the second most common cancer in the world and certainly the most frequent cancer mostly among women. This study was aimed to compare the effectiveness of individual counseling and group narrative therapy on female patients' life expectancy afflicted by breast cancer. The present study is a pre-test-post-test clinical trial. Fifty-five patients with breast cancer were randomly selected in the follow-up period and after their active medical treatment completion. Then, they were randomly divided into two groups: individual counseling and group counseling. Herth hope index (HHI) was used to measure the patients' hope level. Data were analyzed using t-test and SPSS software. hope rate was statistically significant in both groups receiving individual and group narrative therapy in the post-test compared to the pre-test (P <00000). Moreover, the comparative evaluation of hope in both groups (individual & group counseling) in the post-test showed that group narrative counseling is more effective than individual narrative counseling (P <00000). Conclusion: Narrative therapy promotes hope in breast cancer patients effectively. Due to the nature of breast cancer and its psychological effects in the post-treatment period, providing narrative group therapy can improve life quality. Patients' life quality changes in tandem with changes in hope.

Keywords: hope, narrative therapy, counseling, breast cancer

Procedia PDF Downloads 121

Authors: Roham Rafiee, Behzad Mazhari

Abstract:

Composite structures, having incredible properties, have gained considerable popularity in the last few decades. Among all types, polymer matrix composites are being used extensively due to their unique characteristics including low weight, convenient fabrication process and low cost. Having polymer as matrix, these type of composites show different creep behavior when compared to metals and even other types of composites since most polymers undergo creep even in room temperature. One of the most challenging topics in creep is to introduce new techniques for predicting long term creep behavior of materials. Depending on the material which is being studied the appropriate method would be different. Methods already proposed for predicting long term creep behavior of polymer matrix composites can be divided into five categories: (1) Analytical Modeling, (2) Empirical Modeling, (3) Superposition Based Modeling (Semi-empirical), (4) Rheological Modeling, (5) Finite Element Modeling. Each of these methods has individual characteristics. Studies have shown that none of the mentioned methods can predict long term creep behavior of all PMC composites in all circumstances (loading, temperature, etc.) but each of them has its own priority in different situations. The reason to this issue can be found in theoretical basis of these methods. In this study after a brief review over the background theory of each method, they are compared in terms of their applicability in predicting long-term behavior of composite structures. Finally, the explained materials are observed through some experimental studies executed by other researchers.

Keywords: creep, comparative study, modeling, composite materials

Procedia PDF Downloads 440

Authors: Wakkai Hosanna Hussaini

Abstract:

A formal structure of the English clause is composed of at least two elements – subject and verb, in structural grammar and at least one element – predicate, in systemic (functional) and generative grammars. Each of the elements can be represented by a word or group (of words). In modern English structure, very often speakers merge two words as one with the use of an apostrophe. Each of the two words can come from different elements or belong to the same element. In either case, result of the merger is called contraction. Although contractions constitute a part of modern English structure, they are considered informal in nature (more frequently used in spoken than written English) that is why they were initially viewed as constituting an evidence of language deterioration. To our knowledge, no formal syntactic theory yet has been particular on the contractions because of its deviation from the formal rules of syntax that seek to identify the elements that form a clause in English. The inconsistency between the formal rules and a contraction is established when two words representing two elements in a non-contraction are merged as one element to form a contraction. Thus the paper presents the various syntactic issues as effects arising from converting non-contracted to contracted forms. It categorizes English contractions and describes each category according to its syntactic relations (position and relationship) and morphological formation (form and content) as integral part of modern structure of English. This is a position paper as such the methodology is observational, descriptive and explanatory/analytical based on existing related literature. The inventory of English contractions contained in books on syntax forms the data from where specific examples are drawn. It is noted as conclusion that the existing syntactic theories were not originally established to account for English contractions. The paper, when published, will further expose the inadequacies of the existing syntactic theories by giving more reasons for the establishment of a more comprehensive syntactic theory for analyzing English clause/sentence structure involving contractions. The method used reveals the extent of the inadequacies in applying the three major syntactic theories: structural, systemic (functional) and generative, on the English contractions. Although no theory is without scope, shying away from the three major theories from recognizing the English contractions need to be broken because of the increasing popularity of its use in modern English structure. The paper, therefore, recommends that as use of contraction gains more popular even in formal speeches today, there is need to establish a syntactic theory to handle its patterns of syntactic relations and morphological formation.

Keywords: application, effects, English contractions, syntactic theories

Procedia PDF Downloads 268

Authors: O. Ekrami, P. Claes, S. Van Dongen

Abstract:

Fluctuating asymmetry (FA) has been studied for many years as an indicator of developmental stability or ‘genetic quality’ based on the assumption that perfect symmetry is ideally the expected outcome for a bilateral organism. Further studies have also investigated the possible link between FA and attractiveness or levels of masculinity or femininity. These hypotheses have been mostly examined using 2D images, and the structure of interest is usually presented using a limited number of landmarks. Such methods have the downside of simplifying and reducing the dimensionality of the structure, which will in return increase the error of the analysis. In an attempt to reach more conclusive and accurate results, in this study we have used high-resolution 3D scans of human faces and have developed an algorithm to measure and localize FA, taking a spatially-dense approach. A symmetric spatially dense anthropometric mask with paired vertices is non-rigidly mapped on target faces using an Iterative Closest Point (ICP) registration algorithm. A set of 19 manually indicated landmarks were used to examine the precision of our mapping step. The protocol’s accuracy in measurement and localizing FA is assessed using simulated faces with known amounts of asymmetry added to them. The results of validation of our approach show that the algorithm is perfectly capable of locating and measuring FA in 3D simulated faces. With the use of such algorithm, the additional captured information on asymmetry can be used to improve the studies of FA as an indicator of fitness or attractiveness. This algorithm can especially be of great benefit in studies of high number of subjects due to its automated and time-efficient nature. Additionally, taking a spatially dense approach provides us with information about the locality of FA, which is impossible to obtain using conventional methods. It also enables us to analyze the asymmetry of a morphological structures in a multivariate manner; This can be achieved by using methods such as Principal Components Analysis (PCA) or Factor Analysis, which can be a step towards understanding the underlying processes of asymmetry. This method can also be used in combination with genome wide association studies to help unravel the genetic bases of FA. To conclude, we introduced an algorithm to study and analyze asymmetry in human faces, with the possibility of extending the application to other morphological structures, in an automated, accurate and multi-variate framework.

Keywords: developmental stability, fluctuating asymmetry, morphometrics, 3D image processing

Procedia PDF Downloads 139

Authors: P. S. Jagadeesh Kumar, Mingmin Pan, Xianpei Li, Yanmin Yuan, Tracy Lin Huan

Abstract:

Researchers are doing enchanting research into the inherited features of Alzheimer’s disease and probable consistent therapies. In Alzheimer’s, memories are extinct in reverse order; memories formed lately are more transitory than those from formerly. Reminiscence therapy includes the conversation of past actions, trials and knowledges with another individual or set of people, frequently with the help of perceptible reminders such as photos, household and other acquainted matters from the past, music and collection of tapes. In this manuscript, the competence of reminiscence therapy for Alzheimer’s disease is measured using logistic regression based linear bootstrap aggregating. Logistic regression is used to envisage the experiential features of the patient’s memory through various therapies. Linear bootstrap aggregating shows better stability and accuracy of reminiscence therapy used in statistical classification and regression of memories related to validation therapy, supportive psychotherapy, sensory integration and simulated presence therapy.

Keywords: Alzheimer’s disease, linear bootstrap aggregating, logistic regression, reminiscence therapy

Procedia PDF Downloads 307

Authors: W. F. Ribeiro, J. L. N. Góes

Abstract:

The industrial process adds to engineering wood products features absent in solid wood, with homogeneous structure and reduced defects, improved physical and mechanical properties, bio-deterioration, resistance and better dimensional stability, improving quality and increasing the reliability of structures wood. These features combined with using fast-growing trees, make them environmentally ecological products, ensuring a strong consumer market. The wood I-joists are manufactured by the industrial profiles bonding flange and web, an important aspect of the production of wooden I-beams is the adhesive joint that bonds the web to the flange. Adhesives can effectively transfer and distribute stresses, thereby increasing the strength and stiffness of the composite. The objective of this study is to evaluate different resins in a shear strain specimens with the aim of analyzing the most efficient resin and possibility of using national products, reducing the manufacturing cost. First was conducted a literature review, where established the geometry and materials generally used, then established and analyzed 8 national resins and produced six specimens for each.

Keywords: engineered wood products, structural resin, wood i-joist, Pinus taeda

Procedia PDF Downloads 276

Authors: Zameerpal Kaur

Abstract:

Ecocriticism comes into existence in 1990s, it tries to explore the relationship of literature with the natural world and further it examines the role that natural surroundings and environment play in the minds of the creative writers during their imagination and creative process. The present study is an attempt to focus on the comparative ecocritical analysis of Shiv Kumar Batalvi and Surjit Patar’s selected poetry in the theoretical framework of ecocriticism in order to shed light on the poet’s vigilant views about the relationship of human life and nature. Shiv Kumar Batalvi is a renowned modern Punjabi poet. He is essentially a poet of nature and love. His opinions towards nature support his position to be considered as a major representative of recent environmental issues and ecocritical concerns in Punjabi literature. He is one of the most outstanding modern Punjabi poets, is endowed with the most artistic temperament in whose poetry nature always has a dominating existence. He seems to consciously portray the scenes of natural surroundings into his poetry; in fact the titles of his poems in themselves signify his love for the nature. Surjit Patar, an imminent modern Punjabi poet tries to present a different picture of nature into his poems; he also uses to write poems about contemporary problems. Surjit Patar’s radical quarrel with the modern cultural context makes him reject all the absolutes and finalities in the form of transcendental reason and religion, history and evolution, he freely writes about the deterioration of nature at selfish materialistic society. He is modern poet who weaves the natural imagery with the syntax of his poems. Patar’s work reflects a universal voice that is dribbled with nuanced humanism and a sense of modernity that seemed neither dated, nor trapped in regional boundaries. Through his poetry he has given a voice to the fragile, disrupting borders, disturbing the status quo. An attempt to analyse the poetic works of above said poets from ecocritical perspective as well as especially focussing on various aspects of ecocriticism like ecocentric ethics, ecoaesthetics, anthropomorphism etc. has been made throughout the comparative study of the selected works.

Keywords: anthropocentrism, degradation, environment and literature, nature

Procedia PDF Downloads 468

Authors: Yufeng Li, Yinan Ma, Jing Wu, Chengnian Long

Abstract:

Infrared object detection aims at separating small and dim target from clutter background and its capabilities extend beyond the limits of visible light, making it invaluable in a wide range of applications such as improving safety, security, efficiency, and functionality. However, existing methods are usually sensitive to the noise of the input infrared image, leading to a decrease in target detection accuracy and an increase in the false alarm rate in high-noise environments. To address this issue, an infrared small target detection algorithm called YOLO-IR is proposed in this paper to improve the robustness to high infrared noise. To address the problem that high noise significantly reduces the clarity and reliability of target features in infrared images, we design a soft-threshold coordinate attention mechanism to improve the model’s ability to extract target features and its robustness to noise. Since the noise may overwhelm the local details of the target, resulting in the loss of small target features during depth down-sampling, we propose a deep and shallow feature fusion neck to improve the detection accuracy. In addition, because the generalized Intersection over Union (IoU)-based loss functions may be sensitive to noise and lead to unstable training in high-noise environments, we introduce a Wasserstein-distance based loss function to improve the training of the model. The experimental results show that YOLO-IR achieves a 5.0% improvement in recall and a 6.6% improvement in F1-score over existing state-of-art model.

Keywords: infrared small target detection, high noise, robustness, soft-threshold coordinate attention, feature fusion

Procedia PDF Downloads 69

Authors: Samra Isadounene, Amar Boukerrou, Dalila Hammiche

Abstract:

In this work, the composites were prepared with poly(lactic acid) (PLA) and olive husk flour (OHF) with different percentages (10, 20 and 30%) using extrusion method followed by injection molding. The morphological, mechanical properties and thermal behavior of composites were investigated. Tensile strength and elongation at break of composites showed a decreasing trend with increasing fiber content. On the other hand, Young modulus and storage modulus were increased. The addition of OHF resulted in a decrease in thermal stability of composites. The presence of OHF led to an increase in percentage of crystallinity (Xc) of PLA matrix.

Keywords: biopolymers, composites, mechanical properties, poly(lactic acid)

Procedia PDF Downloads 237

Authors: Saidu Garba Okereafor Stella

Abstract:

The presence of 15 organochlorine pesticides residue was assessed from 29 different fruits and fruit juice samples from selected farms in Kaduna and Niger States using the quick easy cheap effective rugged and safe (QuEChERS), followed by gas chromatography-tandem mass spectrometry (GC-MS/MS). The results showed the presence of varying concentrations of ten (10) organochlorine pesticide residues in all the samples with Endrin ketone showing the highest concentration in 3 samples from Kaduna (guava juice 1 and 2 0.099 to 0.145 mg/kg) and Niger States (orange juice J19 0.102 mg/kg). The heptachlor was detected at high concentration in 11 samples, 7 samples from Kaduna State (mango juice 0.011 mg/kg, Washington orange 0.014 mg/kg, Valencia orange fruit 0.020 mg/kg, orange juice 0.011, white guava fruit 0.024 mg/kg, guava juice 0.023 mg/kg, guava juice 2 0.024 mg/kg) and 4 samples from (mango juice 1 0.015 mg/kg, pineapple juice 1 0.0120 mg/kg pineapple juice 2 011 mg/kg and mix juice 2 0.012 mg/kg) from Niger State. Dieldrine and endosulfansulfate were detected at high levels in one sample each from Niger (guava fruit 0.019 mg/kg and mixed juice1 0.011mg/kg), respectively. However, all were above the maximum residue limits (MRLs) set by WHO/FAO which suggest that people consuming these type of contaminated fruits and fruits juices may contact diseases associated with those organochlorine pesticides residue. Minute concentrations of other organochlorines (α- BHC, δ- BHC, β- BHC, Lindane, and p’p DDT) ranged from 0.003 to 0.015 were recorded below the MRLs.

Keywords: fruits and fruits juices, organochlorine pesticide residue, comparative studies, gc-ms spectrophometer

Procedia PDF Downloads 145

Authors: Kolawole Taiwo Olabode

Abstract:

This is a comparative study of ICTs adoption and use in selected manufacturing industries in for development. This study was carried out 2004 and was repeated 2013 (nine years after) using the same selected manufacturing industries to assess the level, improvement and extent ICT facilities used in these companies. The theory of modernization was explored to explain some developmental issues in this study. The same semi-structured questionnaire and IDI were used to elicit data on the subject matter. About 24.9% of the total workers (1,247) were sampled for this study using quota sampling technique. SPSS was used to analysis the quantitative data. The qualitative data was used to buttress the quantitative data. Findings indicated that Seven-Up Bottling Company and Frigoglass Glass Industry still remained Intensive ICT Users while only Niger Match Nigeria Limited still remained Non-Intensive ICT User while unfortunately, Askar Paint Nigeria Limited has gone liquidated. It is also important to discover that only the Intensive ICT users improved on relevant ICT facilities. The existing problems of ICT adoption and used in these companies remained the same in Niger Match Limited. The study concluded that for a society to be developed, management and government at all levels must do all things necessary to ensure that all existing organisations must be ICT compliance for workers and organisational performance and to enhance nation’s development in order to compete with other companies for global standard or recognition.

Keywords: ICT, intensive ICT-users, entrepreneurial, manufacturing industries, industries and development

Procedia PDF Downloads 301

Authors: Sarah Jacqueline Saram, Diya Baker, Jaishree Gandhewar

Abstract:

Named after the Slovakian microbiologist, Miroslav Kocur, the Kocuria spp. are an emerging cause of significant human infections. Their predilection for immunocompromised states, such as malignancy and metabolic disorders, is highlighted in the literature. The coagulase-negative, gram-positive cocci are commensals found in the skin and oropharynx of humans, and their growing presence as responsible organisms in ocular infections cannot be ignored. The severe, rapid, and unrelenting disease course associated with Kocuria keratitis is underlined in the literature. However, the clinical features are variable, which may impede making a diagnosis. Here, we describe a first account of an initial misdiagnosis due to reliance on subjective analysis features on a confocal microscope, which ultimately led to a delay in commencing the correct treatment. In documenting this, we hope to underline to clinicians the difficulties in recognising a Kocuria Rhizophilia keratitis due to its similar clinical presentation to an Acanthamoeba Keratitis, thus emphasizing the need for early investigations such as corneal scrapes to secure the correct diagnosis and prevent further harm and vision loss for the patient.

Keywords: keratitis, cornea, infection, rare, Kocuria

Procedia PDF Downloads 53

Authors: L. S. Chathurika

Abstract:

Early prediction of student performance is an important factor to be gained academic excellence. Whatever the study stream in secondary education, students lay the foundation for higher studies during the first year of their degree or diploma program in Sri Lanka. The information technology (IT) field has certain improvements in the education domain by selecting specialization areas to show the talents and skills of students. These specializations can be software engineering, network administration, database administration, multimedia design, etc. After completing the first-year, students attempt to select the best path by considering numerous factors. The purpose of this experiment is to predict the best study path using machine learning algorithms. Five classification algorithms: decision tree, support vector machine, artificial neural network, Naïve Bayes, and logistic regression are selected and tested. The support vector machine obtained the highest accuracy, 82.4%. Then affecting features are recognized to select the best study path.

Keywords: algorithm, classification, evaluation, features, testing, training

Procedia PDF Downloads 118

Authors: Abdelhak Nouri

Abstract:

Europium doped zinc oxide nanocolumns (ZnO:Eu) were deposited on indium tin oxide (ITO) substrate from an aqueous solution of 10⁻³M Zn(NO₃)₂ and 0.5M KNO₃ with different concentration of europium ions. The deposition was performed in a classical three-electrode electrochemical cell. The structural, morphology and optical properties have been characterized by x-ray diffraction (XRD), scanning electron microscopy (SEM), atomic force microscopy (AFM). The XRD results show high quality of crystallite with preferential orientation along c-axis. SEM images speculate ZnO: Eu has nanocolumnar form with hexagonal shape. The diameter of nanocolumns is around 230 nm. Furthermore, it was found that tail of crystallite, roughness, and band gap energy is highly influenced with increasing Eu ions concentration. The average grain size is about 102 nm to 125 nm.

Keywords: deterioration lattice, doping, nanostructures, Eu:ZnO

Procedia PDF Downloads 176

Authors: Anamarija Kuhar, Veronika Kloboves Prevodnik, Nataša Nolde, Ulrika Klopčič

Abstract:

The decision for immunocytochemistry (ICC) is usually made in the basis of the findings in Giemsa- and/or Papanicolaou- smears. More demanding diagnostic cases require preparation of additional cytological preparations. Therefore, it is convenient to suspend cytological samples in a liquid based medium (LBM) that preserve antigen and morphological properties. However, the duration of these properties being preserved in the medium is usually unknown. Eventually, cell morphology becomes impaired and altered, as well as antigen properties may be lost or become diffused. In this study, the influence of cytological sample storage length in in-house liquid based medium on antigen properties and cell morphology is evaluated. The question is how long the cytological samples in this medium can be stored so that the results of immunocytochemical reactions are still reliable and can be safely used in routine cytopathological diagnostics. The stability of 6 ICC markers that are most frequently used in everyday routine work were tested; Cytokeratin AE1/AE3, Calretinin, Epithelial specific antigen Ep-CAM (MOC-31), CD 45, Oestrogen receptor (ER), and Melanoma triple cocktail were tested on methanol fixed cytospins prepared from fresh fine needle aspiration biopsies, effusion samples, and disintegrated lymph nodes suspended in in-house cell medium. Cytospins were prepared on the day of the sampling as well as on the second, fourth, fifth, and eight day after sample collection. Next, they were fixed in methanol and immunocytochemically stained. Finally, the percentage of positive stained cells, reaction intensity, counterstaining, and cell morphology were assessed using two assessment methods: the internal assessment and the UK NEQAS ICC scheme assessment. Results show that the antigen properties for Cytokeratin AE1/AE3, MOC-31, CD 45, ER, and Melanoma triple cocktail were preserved even after 8 days of storage in in-house LBM, while the antigen properties for Calretinin remained unchanged only for 4 days. The key parameters for assessing detection of antigen are the proportion of cells with a positive reaction and intensity of staining. Well preserved cell morphology is highly important for reliable interpretation of ICC reaction. Therefore, it would be valuable to perform a similar analysis for other ICC markers to determine the duration in which the antigen and morphological properties are preserved in LBM.

Keywords: cytology samples, cytospins, immunocytochemistry, liquid-based cytology

Procedia PDF Downloads 138

Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

Abstract:

Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

Procedia PDF Downloads 75

Authors: Lin Li, P. G. R. N. I. Pussella

Abstract:

When representing spatial data and their attributes on different types of maps, the scale plays a key role in the process of map generalization. The process is consisted with two main operators such as selection and omission. Once some data were selected, they would undergo of several geometrical changing processes such as elimination, simplification, smoothing, exaggeration, displacement, aggregation and size reduction. As a result of these operations at different levels of data, the geometry of the spatial features such as length, sinuosity, orientation, perimeter and area would be altered. This would be worst in the case of preparation of small scale maps, since the cartographer has not enough space to represent all the features on the map. What the GIS users do is when they wanted to analyze a set of spatial data; they retrieve a data set and does the analysis part without considering very important characteristics such as the scale, the purpose of the map and the degree of generalization. Further, the GIS users use and compare different maps with different degrees of generalization. Sometimes, GIS users are going beyond the scale of the source map using zoom in facility and violate the basic cartographic rule 'it is not suitable to create a larger scale map using a smaller scale map'. In the study, the effect of map generalization for GIS analysis would be discussed as the main objective. It was used three digital maps with different scales such as 1:10000, 1:50000 and 1:250000 which were prepared by the Survey Department of Sri Lanka, the National Mapping Agency of Sri Lanka. It was used common features which were on above three maps and an overlay analysis was done by repeating the data with different combinations. Road data, River data and Land use data sets were used for the study. A simple model, to find the best place for a wild life park, was used to identify the effects. The results show remarkable effects on different degrees of generalization processes. It can see that different locations with different geometries were received as the outputs from this analysis. The study suggests that there should be reasonable methods to overcome this effect. It can be recommended that, as a solution, it would be very reasonable to take all the data sets into a common scale and do the analysis part.

Keywords: generalization, GIS, scales, spatial analysis

Procedia PDF Downloads 327

Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

Abstract:

Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

Procedia PDF Downloads 181

Authors: Sujay Kotwale, Ramasubba Reddy M.

Abstract:

Electrocardiogram (ECG) is a non-invasive technique used to study and analyze various heart diseases. Cardiac arrhythmia is a serious heart disease which leads to death of the patients, when left untreated. An early-time detection of cardiac arrhythmia would help the doctors to do proper treatment of the heart. In the past, various algorithms and machine learning (ML) models were used to early-time detection of cardiac arrhythmia, but few of them have achieved better results. In order to improve the performance, this paper implements principal component analysis (PCA) along with XGBoost model. The PCA was implemented to the raw ECG signals which suppress redundancy information and extracted significant features. The obtained significant ECG features were fed into XGBoost model and the performance of the model was evaluated. In order to valid the proposed technique, raw ECG signals obtained from standard MIT-BIH database were employed for the analysis. The result shows that the performance of proposed method is superior to the several state-of-the-arts techniques.

Keywords: cardiac arrhythmia, electrocardiogram, principal component analysis, XGBoost

Procedia PDF Downloads 117

Authors: Mais Khader, Xingjie Wei

Abstract:

This research sheds light on female entrepreneurs by providing new insights on the survival predictions of companies led by females in the UK. This study aims to build a predictive machine learning model of the survival of female-led & co-led small & medium enterprises (SMEs) in the UK over the period 2000-2020. The predictive model built utilised a combination of financial and non-financial features related to both companies and their directors to predict SMEs' survival. These features were studied in terms of their contribution to the resultant predictive model. Five machine learning models are used in the modelling: Decision tree, AdaBoost, Naïve Bayes, Logistic regression and SVM. The AdaBoost model had the highest performance of the five models, with an accuracy of 73% and an AUC of 80%. The results show high feature importance in predicting companies' survival for company size, management experience, financial performance, industry, region, and females' percentage in management.

Keywords: company survival, entrepreneurship, females, machine learning, SMEs

Procedia PDF Downloads 99