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Automated craniofacial landmarks detection on 3D image using geometry characteristics information
Get PDFBackground:
Indirect anthropometry (IA) is one of the craniofacial anthropometry methods to perform the measurements on the digital facial images. In order to get the linear measurements, a few definable points on the structures of individual facial images have to be plotted as landmark points. Currently, most anthropometric studies use landmark points that are manually plotted on a 3D facial image by the examiner. This method is time-consuming and leads to human biases, which will vary from intra-examiners to inter-examiners when involving large data sets. Biased judgment also leads to a wider gap in measurement error. Thus, this work aims to automate the process of landmarks detection to help in enhancing the accuracy of measurement. In this work, automated craniofacial landmarks (ACL) on a 3D facial image system was developed using geometry characteristics information to identify the nasion (n), pronasale (prn), subnasale (sn), alare (al), labiale superius (ls), stomion (sto), labiale inferius (li), and chelion (ch). These landmarks were detected on the 3D facial image in .obj file format. The IA was also performed by manually plotting the craniofacial landmarks using Mirror software. In both methods, once all landmarks were detected, the eight linear measurements were then extracted. Paired t-test was performed to check the validity of ACL (i) between the subjects and (ii) between the two methods, by comparing the linear measurements extracted from both ACL and AI. The tests were performed on 60 subjects (30 males and 30 females).
Results:
The results on the validity of the ACL against IA between the subjects show accurate detection of n, sn, prn, sto, ls and li landmarks. The paired t-test showed that the seven linear measurements were statistically significant when p < 0.05. As for the results on the validity of the ACL against IA between the methods, ACL is more accurate when p ≈ 0.03.
Conclusions:
In conclusion, ACL has been validated with the eight landmarks and is suitable for automated facial recognition. ACL has proved its validity and demonstrated the practicability to be used as an alternative for IA, as it is time-saving and free from human biases
A bioactive injectable bulking material; a potential therapeutic approach for stress urinary incontinence
No full textStress urinary incontinence (SUI) is a life changing condition, affecting 20 million women worldwide. In this study, we developed a bioactive, injectable bulking agent that consists of Permacol™ (Medtronic, Switzerland) and recombinant insulin like growth factor-1 conjugated fibrin micro-beads (fib_rIGF-1) for its bulk stability and capacity to induce muscle regeneration. Therefore, Permacol™ formulations were injected in the submucosal space of rabbit bladders. The ability of a bulking material to form a stable and muscle-inducing bulk represents for us a promising therapeutic approach to achieve a long-lasting treatment for SUI. The fib_rIGF-1 showed no adverse effect on human smooth muscle cell metabolic activity and viability in vitro based on AlamarBlue assays and Live/Dead staining. Three months after injection of fib_rIGF-1 together with Permacol™ into the rabbit bladder wall, we observed a smooth muscle tissue like formation within the injected materials. Positive staining for alpha smooth muscle actin, calponin, and caldesmon demonstrated a contractile phenotype of the newly formed smooth muscle tissue. Moreover, the fib_rIGF-1 treated group also improved the neovascularization at the injection site, confirmed by CD31 positive staining compared to bulks made of Permacol TM only. The results of this study encourage us to further develop this injectable, bioactive bulking material towards a future therapeutic approach for a minimal invasive and long-lasting treatment of SUI. © 2019 Elsevier Lt
Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
No full textTo help individuals or companies make a systematic and more accurate decisions, sentiment analysis (SA) is used to evaluate the polarity of reviews. In SA, feature selection phase is an important phase for machine learning classifiers specifically when the datasets used in training is huge. Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. However, WOA suffers from the same problem faced by many other optimization algorithms and tend to fall in local optima. To overcome these problems, two improvements for WOA algorithm are proposed in this paper. The first improvement includes using Elite Opposition-Based Learning (EOBL) at initialization phase of WOA. The second improvement involves the incorporation of evolutionary operators from Differential Evolution algorithm at the end of each WOA iteration including mutation, crossover, and selection operators. In addition, we also used Information Gain (IG) as a filter features selection technique with WOA using Support Vector Machine (SVM) classifier to reduce the search space explored by WOA. To verify our proposed approach, four Arabic benchmark datasets for sentiment analysis are used since there are only a few studies in sentiment analysis conducted for Arabic language as compared to English. The proposed algorithm is compared with six well-known optimization algorithms and two deep learning algorithms. The comprehensive experiments results show that the proposed algorithm outperforms all other algorithms in terms of sentiment analysis classification accuracy through finding the best solutions, while its also minimizes the number of selected features. © 2018, Springer Science+Business Media, LLC, part of Springer Nature
A comparison of aesthetic outcome between tissue adhesive and subcuticular suture in thyroidectomy wound closure in a multiracial country: A randomized controlled trial
No full textObjectives: Monofilament sutures, both absorbable and non-absorbable, have been used for wound closure. Tissue adhesive has been used in closure of clean, low tension wounds. However, there have been very few published studies on the aesthetic outcomes in neck surgeries. The aim of this study is to compare the patients' and doctors’ satisfaction scores in the aesthetic outcome between both methods of closure of thyroidectomy wounds using validated scoring systems. Methods: A double-blinded randomised controlled trial comparing the aesthetic outcome between tissue adhesive and conventional suture was conducted among patients undergoing thyroid and parathyroid surgeries. Ninety-six patients were randomised into two treatment groups. Patients' wounds were scored by an independent observer using the SBSES score at 6 weeks postoperatively and observer component of the POSAS score at 3 months. Results: Forty-nine patients were randomised to the tissue adhesive group while forty-seven patients received the conventional method. There was no statistical difference in the aesthetic outcome using the patient's scoring system between both arms, with a median score of 9 (p = 0.25, SD ± 6.5). The observer's satisfaction score using POSAS was also not statistically significant (median score of 14 (p = 0.77, SD ± 6.2)). No significance was found in the observer's median score using the SBSES scoring system either (score 3, p = 0.12, SD ± 1.3). However, there was significant reduction in the duration of closure using glue (4.42 mins vs 6.36 mins, p < 0.05). Conclusion: Tissue adhesive offers a comparable cosmetic result to the absorbable suture in thyroidectomy wound closure. © 201
Adsorption of Acid Blue 113 from aqueous solution onto nutraceutical industrial coriander seed spent: Isotherm, kinetics, thermodynamics and modeling studies
No full textIn this study, use of low-cost nutraceutical industrial coriander seed spent (NICSS) for removing Acid Blue 113 (AB113) from aqueous solution has been explored. Biosorption studies were done under varying conditions of initial pH, initial dye concentration, adsorbent dosage, particle size of the adsorbent and temperature to assess the adsorption capacity, kinetics and equilibrium thermodynamics. Optimal adsorption took place at acidic pH. A two-level fractional factorial experimental design (FFED) and analysis of variance (ANOVA) showed that a maximum adsorption value of 90.00 mg/mL was possible. The influence of each parameter and combination of parameters on the final adsorption capacity of the system was studied. The dye uptake followed a pseudo-second order kinetic paradigm and was best described by the Langmuir isotherm. Intra-particle diffusion showed that the adsorption mechanism was more governed by external mass transfer. AB113 adsorption on NICSS was endothermic and almost spontaneous. The NICSS has a highly fibrous matrix with hierarchical porous structure as evidenced by SEM images. Analysis of the spent showed that it possesses cellulosic and ligno-cellulosic materials having both hydrophilic and hydrophobic properties. The results proved that NICSS efficiently removes AB113 from water and textile industrial effluents. © 2019 Desalination Publications. All rights reserved
A New Multilevel Inverter Topology With Reduce Switch Count
No full textMultilevel inverters are a new family of converters for dc-ac conversion for the medium and high voltage and power applications. In this paper, two new topologies for the staircase output voltage generations have been proposed with a lesser number of switch requirement. The first topology requires three dc voltage sources and ten switches to synthesize 15 levels across the load. The extension of the first topology has been proposed as the second topology, which consists of four dc voltage sources and 12 switches to achieve 25 levels at the output. Both topologies, apart from having lesser switch count, exhibit the merits in terms of reduced voltage stresses across the switches. In addition, a detailed comparative study of both topologies has been presented in this paper to demonstrate the features of the proposed topologies. Several experimental results have been included in this paper to validate the performances of the proposed topologies with different loading condition and dynamic changes in load and modulation indexes. © 2013 IEEE
Evaluation of Municipal Solid Wastes Based Energy Potential in Urban Pakistan
No full textSolid waste management needs re-evaluating in developing countries like Pakistan, which currently employs landfilling as a first option. Over time, increasing population will result in decreasing space for landfill sites, ultimately increasing the cost of landfilling, while increasing accumulated waste will cause pollution. Locating and preparing a sanitary landfill includes the securing of large sectors and also everyday activity with the end goal to limit potential negative impacts. Energy production from municipal solid waste (MSW) is a perceptive idea for large cities, such as Karachi, as waste, which is an undesirable output that adds to land and air pollution, is transformed into a vital source of energy. The current study strives to provide a destination to solid waste by evaluating the energy potential that waste provides for power generation by the process of incineration. A sustainable energy generation plant based on the Rankine cycle is proposed. This study evaluates the various landfill sites in the case study area to determine their sustainability for a waste to energy (WtE) plant. The implementation of the proposed plant will not only provide an ultimate destination to waste but also generate 121.9 MW electricity at 25% plant efficiency. Thus, the generated electricity can be used to run a WtE plant and meet the energy requirements of the residents. © 2019 by the authors
Identification of potential sites for runoff water harvesting
No full textRunoff water harvesting (RWH) is a potential solution for areas suffering from water scarcity, such as the western desert of Iraq. Site selection based on RWH ranking using a combination of a watershed modelling system, geographic information systems and remote sensing techniques may enable authorities and water engineers to determine potential solutions to water scarcity. In this work, these methods were employed to produce eight thematic maps of the volume of annual floods, basin area, basin length, maximum flow distance, drainage frequency density, lineament frequency density, basin slope and stream order. These maps were used to rank and classify probable sites based on equal weight and statistical weight. The results were then used to classify the selected sites into four classes, namely sites with very high, high, moderate and low RWH potential. The proposed method was shown to be beneficial in the identification of potential RWH sites. © 2017 ICE Publishing: All rights reserved
Identifying the Components of Social Capital by Categorical Principal Component Analysis (CATPCA)
No full textSocial capital is a promising concept, widely used by social science researchers in analysing factors that contribute to the persistence of various economic issues. Unfortunately, the search for the best way to define, measure and classify the appropriate components that constitute this intangible form of capital is far from complete. Generally, data on social capital are qualitative in nature (mostly of the nominal and ordinal types) and encompass a large number of variables. This challenges the researcher to find the best way to reduce these data to a small number of composites to be used as a proxy of measurement in further analysis. Although principal component analysis (PCA) is considered an appropriate method and has been widely adopted in past studies, the requirement that data must be at the numeric measurement level, as well as the assumptions of linear relationships between variables, might hinder the use of PCA in working with social capital data. Categorical principal component analysis (CATPCA) is a more flexible alternative, suitable for variables of mixed measurement levels (nominal, ordinal, and numeric) that may not be linearly related to each other. Based on theory and past studies, questionnaires have been constructed and fieldwork has been carried out to gather data on social capital in Malaysia. Later, using CATPCA, 42 potential variables were identified to represent components of social capital. Final results indicate that after withdrawing 9 variables with bad fits, CATPCA has categorized the balance of 33 variables into four dimensions of social capital. These dimensions can be described by 5 principal components, which have been identified as influence of spirituality and culture, benefits from interaction with friend, trusted person during financial difficulties, benefits from financial aid receive and benefits from involvement in association. The first component represents culture/spirituality, the new dimension created by this study to address social capital from the perspective of a developing country. The second, third, fourth and fifth components are in line with the consensus reached by scholars and advocates regarding the elements or components of social capital. The second and fifth actually fall under the rubrics of the social relation/networks dimension while the third and fourth under trust and norms. © 2018, Springer Science+Business Media B.V., part of Springer Nature
Predicting student’s campus placement probability using binary logistic regression
No full textStudents aspiring for technical education generally select educational institutions with good track record in campus placements. Many a times the reputation of such institute is determined by the pay packages offered by recruiters to its students. In this context it is pertinent to investigate and identify those factors that may influence the student campus placement chances in technical education. The State of Andhra Pradesh which has a high concentration of technical education institutes was chosen as the study area. A careful review of literature lead to the identification of six hypothetical determinants of student campus placement in technical education. A random sample 250 MBA student’s placement data were gathered from different institutes and six predictor binary logistic regression model was fitted to the data to estimate the odds for the student campus placement. Estimated Results of the study indicate that the chances of campus placement is influenced by four predictors: CGPA, Specialization in PG, Specialization in UG and Gender. © BEIESP