Search results for: high relative accuracy

Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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Authors: Mitra Assadi, Md. Faan

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Background: Autism Spectrum Disorder (ASD) in a common neurodevelopmental disorder with limited pharmacological interventions. Transcranial Magnetic Stimulation (rTMS) has produced promising results in ASD, although there is no consensus regarding optimal targets or stimulation paradigms. A prevailing theory in ASD attributes the core deficits to dysfunction of the mirror neurons located in the inferior parietal lobule (IPL) and inferior frontal gyrus (IFG). Methods: Thus far, 11 subjects with ASD, 10 boys and 1 girl with the mean age of 13.36 years have completed the study by receiving 10 session of high frequency rTMS to the IPL. The subjects were randomized to receive stimulation on the left or right IPL and sham stimulation to the opposite side. The outcome measures included the Social Responsiveness Scale – Second Edition (SRS-2) and Delis-Kaplan Executive Function System (D-KEFS) Verbal Fluency task. Results: None of the 11 subjects experienced any adverse effects. The rTMS did not produce any improvement in verbal fluency, nor there was any statistically significant difference between the right versus left sided stimulation. Analysis of social awareness on SRS-2 (SRS-AWR) indicated a close to significant effect of the treatment with a small to medium effect size. After removing a single subject with Level 3 ASD, we demonstrated a close to significant improvement on SRS-AWR with a large effect size. The analysis of the data 3-month post TMS demonstrated return of the SRS-AWR values to baseline. Conclusion: This preliminary analysis of the 11 subjects who have completed our study thus far shows a favorable response to high frequency rTMS stimulation of the mirror neurons/IPL on social awareness. While the decay of the response noted during the 3-month follow-up may be considered a limitation of rTMS, the presence of the improvement, especially the effect size despite the small sample size, is indicative of the efficacy of this technique.

Keywords: rTMS, autism, scoial cognition, mirror neurons

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Authors: Anas Rao, Hao Duan, Fanhua Ma

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The dependency on the fossil fuels can be minimized by using the hydrogen enriched compressed natural gas (HCNG) in the transportation vehicles. However, the NOx emissions of HCNG engines are significantly higher, and this turned to be its major drawback. Therefore, the study of NOx emission of HCNG engines is a very important area of research. In this context, the experiments have been performed at the different hydrogen percentage, ignition timing, air-fuel ratio, manifold-absolute pressure, load and engine speed. Afterwards, the simulation has been accomplished by the quasi-dimensional combustion model of HCNG engine. In order to investigate the NOx emission, the NO mechanism has been coupled to the quasi-dimensional combustion model of HCNG engine. The three NOx mechanism: the thermal NOx, prompt NOx and N2O mechanism have been used to predict NOx emission. For the validation purpose, NO curve has been transformed into NO packets based on the temperature difference of 100 K for the lean-burn and 60 K for stoichiometric condition. While, the width of the packet has been taken as the ratio of crank duration of the packet to the total burnt duration. The combustion chamber of the engine has been divided into three zones, with the zone equal to the product of summation of NO packets and space. In order to check the accuracy of the model, the percentage error of NOx emission has been evaluated, and it lies in the range of ±6% and ±10% for the lean-burn and stoichiometric conditions respectively. Finally, the percentage contribution of each NO formation has been evaluated.

Keywords: quasi-dimensional combustion , thermal NO, prompt NO, NO packet

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Authors: Mahdi Fakoor, Nabi Mehri Khansari, Ahmadreza Farokhi

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Evaluation of mode II fracture toughness (KIIC) in composite materials is very hard problem to be solved, since it can be affected by many mechanisms of dissipation. Furthermore, non-linearity in its behavior can offer an extra difficulty to obtain accuracy in the results. Different reported values for KIIC in various references can prove the mentioned assertion. In this research, some solutions proposed based on the form of necessary corrections that should be executed on the common test fixtures. Due to the fact that the common test fixtures are not able to active toughening mechanisms in pure Mode II correctly, we have employed some structural modifications on common fixtures. Particularly, the Iosipescu test is used as start point. The tests are applied on graphite/epoxy; PMMA and Western White Pine Wood. Also, mixed mode I/II fracture limit curves are used to indicate the scattering in test results are really relevant to the creation of Fracture Process Zone (FPZ). In the present paper, shear load consideration applied at the predicted shear zone by considering some significant structural amendments that can active mode II toughening mechanisms. Indeed, the employed empirical method causes significant developing in repeatability and reproducibility as well. Moreover, a 3D Finite Element (FE) is performed for verification of the obtained results. Eventually, it is figured out that, a remarkable precision can be obtained in common test fixture in comparison with the previous one.

Keywords: FPZ, shear test fixture, mode II fracture toughness, composite material, FEM

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Authors: Ainoa Guinart, Maria Korpidou, Daniel Doellerer, Cornelia Palivan, Ben L. Feringa

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Stimuli responsive systems arise from the need to meet unsolved needs of current molecular drugs. Our study presents the design of a delivery system with high spatiotemporal control and tuneable release profiles. We study the incorporation of a hydrophobic synthetic molecular motor into PDMS-b-PMOXA block copolymer vesicles to create a self-assembled system. We prove their successful incorporation and selective activation by low powered visible light (λ 430 nm, 6.9 mW). We trigger the release of a fluorescent dye with high release efficiencies over sequential cycles (up to 75%) with the ability to turn on and off the release behaviour on demand by light irradiation. Low concentrations of photo-responsive units are proven to trigger release down to 1 mol% of molecular motor. Finally, we test our system in relevant physiological conditions using a lung cancer cell line and the encapsulation of an approved drug. Similar levels of cell viability are observed compared to the free-given drugshowing the potential of our platform to deliver functional drugs on demand with the same efficiency and lower toxicity.

Keywords: molecular motor, polymer, drug delivery, light-responsive, cancer, selfassembly

Procedia PDF Downloads 138

Authors: Yang Li, Mingkai Liu, Qiong Rao, Zhongrui Gai, Ying Pan, Hongguang Jin

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Hydrogen is an ideal and potential energy carrier due to its high energy efficiency and low pollution. An alternative and promising approach to hydrogen generation is the chemical looping steam reforming of methane (CL-SRM) over iron-based oxygen carriers. However, the process faces challenges such as high reaction temperature (>850 ℃) and low methane conversion. We demonstrate that Ni-mixed Fe-based oxygen carrier particles have significantly improved the methane conversion and hydrogen production rate in the range of 450-600 ℃ under atmospheric pressure. The effect on the reaction reactivity of oxygen carrier particles mixed with different Ni-based particle mass ratios has been determined in the continuous unit. More than 85% of methane conversion has been achieved at 600 ℃, and hydrogen can be produced in both reduction and oxidation steps. Moreover, the iron-based oxygen carrier particles exhibited good cyclic performance during 150 consecutive redox cycles at 600 ℃. The mid-temperature iron-based oxygen carrier particles, integrated with a moving-bed chemical looping system, might provide a powerful approach toward more efficient and scalable hydrogen production.

Keywords: chemical looping, hydrogen production, mid-temperature, oxygen carrier particles

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Authors: Misbah Javaid, Vladimir Estivill-Castro, Rene Hexel

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The field of robotics is advancing rapidly to the point where robots have become an integral part of the modern society. These robots collaborate and contribute productively with humans and compensate some shortcomings from human abilities and complement them with their skills. Effective teamwork of humans and robots demands to investigate the critical issue of trust. The field of human-computer interaction (HCI) has already examined trust humans place in technical systems mostly on issues like reliability and accuracy of performance. Early work in the area of expert systems suggested that automatic generation of explanations improved trust and acceptability of these systems. In this work, we augmented a robot with the user-invoked explanation generation proficiency. To measure explanations effect on human’s level of trust, we collected subjective survey measures and behavioral data in a human-robot team task into an interactive, adversarial and partial information environment. The results showed that with the explanation capability humans not only understand and recognize robot as an expert team partner. But, it was also observed that human's learning and human-robot team performance also significantly improved because of the meaningful interaction with the robot in the human-robot team. Moreover, by observing distinctive outcomes, we expect our research outcomes will also provide insights into further improvement of human-robot trustworthy relationships.

Keywords: explanation interface, adversaries, partial observability, trust building

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Authors: Salima Bouadjela, Fatima Zohra Abdoune, Lahcene Mechernene

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PDLCs are currently considered as promising materials for specific applications such as creation of window blinds controlled by electric field, fog simulators, UV protective glasses, high data storage device etc. We know that the electrical field inside the liquid crystal is low compare with the external electric field [1,2]. An addition of high magnetic and electrical, properties containing compounds to the polymer dispersed liquid crystal (PDLC) will enhance the electrical, optical, and magnetic properties of the PDLC [3,4]. Low Concentration of inorganic nanoparticles TiO2 added to nematic liquid crystals (E7) and also combined with monomers (TPGDA) and cured monomer/LC mixture to elaborate polymer-LC-NP dispersion. The presence of liquid crystal and nanoparticles in TPGDA matrix were conformed and the modified properties of PDLC due to doped nanoparticle were studied and explained by the results of FTIR, POM, UV. Incorporation of nanoparticles modifies the structure of PDLC and thus it makes increase the amount of droplets and decrease in droplet size. we found that the presence of TiO2 nanoparticles leads to a shift the nematic-isotropic transition temperature TNI.

Keywords: nanocomposites, PDLC, phases diagram, TiO2

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Authors: Alesandro Romero, Inaki Maulida Hakim

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This research was conducted in an automotive company in Indonesia to overcome the problem of high logistics cost. The problem causes high of additional truck delivery. From the breakdown of the problem, chosen one route, which has the highest gap value, namely for RE-04. Research methodology will be started from calculating the ideal condition, making simulation, calculating the ideal logistic cost, and proposing an improvement. From the calculation of the ideal condition, box arrangement was done on the truck; the average efficiency was 97,4 % with three trucks delivery per day. Route simulation making uses Tecnomatix Plant Simulation software as a visualization for the company about how the system is occurred on route RE-04 in ideal condition. Furthermore, from the calculation of logistics cost of the ideal condition, it brings savings of Rp53.011.800,00 in a month. The last step is proposing improvements on the area of route RE-04. The route arrangement is done by Saving Method and sequence of each supplier with the Nearest Neighbor. The results of the proposed improvements are three new route groups, where was expected to decrease logistics cost Rp3.966.559,40 per day, and increase the average of the truck efficiency 8,78% per day.

Keywords: efficiency, logistic cost, milkrun, saving methode, simulation

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Authors: Haruna Saidu, Sulaiman Mohammed, Abdulkarim Ali Deba, Shaza Eva Mohamad

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Determining the diversity of the indigenous microorganisms in Palm Oil Mill Effluent (POME) could allow their wider application for the treatment of recalcitrant agro-based wastewater discharge into the environment. Many research studies mainly determined the efficiency of microorganism or their co-cultivation with microalgae for enhanced treatment of wastewater, suggesting a limited emphasis on the application of microbial diversity. In this study, the microorganism was cultured in POME for a period of 15 days using microalgae as a source of carbon. Pyrosequencing analysis reveals a diversity of microbial community in 20% (v/v) culture than the control experiment. Most of the bacterial species identified in POME belong to the families of Bacillaceae, Paenibacillaceae, Enterococcaceae, Clostridiaceae, Peptostreptococcaceae, Caulobacteraceae, Enterobacteriaceae, Moraxellaceae, and Pseudomonadaceae. Alpha (α) diversity analysis reveals the high composition of the microbial community of 52 in both samples. Beta (β) diversity index indicated the occurrence of similar species of microorganisms in unweighted uni fra than the weighted uni fra of both samples. It is therefore suggested that bacteria found in these families could have a potential for synergistic treatment of high-strength wastewater generated from the palm oil industry.

Keywords: diversity, microorganism, wastewater, pyrosequencing, palm oil mill effluent

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Authors: B. J. Babalola, M. B. Shongwe

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Spark Plasma Sintering technique is a novel processing method that produces limited grain growth and highly dense variety of materials; alloys, superalloys, and carbides just to mention a few. However, initial particle size and spark plasma sintering parameters are factors which influence the grain growth and mechanical properties of sintered materials. Ni-Cr alloys are regarded as the most promising alloys for aerospace turbine blades, owing to the fact that they meet the basic requirements of desirable mechanical strength at high temperatures and good resistance to oxidation. The conventional method of producing this alloy often results in excessive grain growth and porosity levels that are detrimental to its mechanical properties. The effect of sintering temperature was evaluated on the microstructure and mechanical properties of the nanostructured Ni-17Cr alloy. Nickel and chromium powder were milled using high energy ball milling independently for 30 hours, milling speed of 400 revs/min and ball to powder ratio (BPR) of 10:1. The milled powders were mixed in the composition of Nickel having 83 wt % and chromium, 17 wt %. This was sintered at varied temperatures from 800°C, 900°C, 1000°C, 1100°C and 1200°C. The structural characteristics such as porosity, grain size, fracture surface and hardness were analyzed by scan electron microscopy and X-ray diffraction, Archimedes densitometry, micro-hardness tester. The corresponding results indicated an increase in the densification and hardness property of the alloy as the temperature increases. The residual porosity of the alloy reduces with respect to the sintering temperature and in contrast, the grain size was enhanced. The study of the mechanical properties, including hardness, densification shows that optimum properties were obtained for the sintering temperature of 1100°C. The advantages of high sinterability of Ni-17Cr alloy using milled powders and microstructural details were discussed.

Keywords: densification, grain growth, milling, nanostructured materials, sintering temperature

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Authors: Ayat E. Ali, Christeen R. Aziz, Merna A. Helmy, Mohammed M. Malek, Sherif H. El-Gohary

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Goal: Purpose of the project was to make a plastic surgery prediction by using pre-operative images for the plastic surgeries’ patients and to show this prediction on a screen to compare between the current case and the appearance after the surgery. Methods: To this aim, we implemented a software which used data from the internet for facial skin diseases, skin burns, pre-and post-images for plastic surgeries then the post- surgical prediction is done by using K-nearest neighbor (KNN). So we designed and fabricated a smart mirror divided into two parts a screen and a reflective mirror so patient's pre- and post-appearance will be showed at the same time. Results: We worked on some skin diseases like vitiligo, skin burns and wrinkles. We classified the three degrees of burns using KNN classifier with accuracy 60%. We also succeeded in segmenting the area of vitiligo. Our future work will include working on more skin diseases, classify them and give a prediction for the look after the surgery. Also we will go deeper into facial deformities and plastic surgeries like nose reshaping and face slim down. Conclusion: Our project will give a prediction relates strongly to the real look after surgery and decrease different diagnoses among doctors. Significance: The mirror may have broad societal appeal as it will make the distance between patient's satisfaction and the medical standards smaller.

Keywords: k-nearest neighbor (knn), face detection, vitiligo, bone deformity

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Authors: Rabih O. Al-Kaysi, Lingyan Zhu, Muhannah K. Al-Muhannah, Christopher J. Bardeen

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(E)-3-(Anthracen-9-yl)acrylic acid (9-AYAA) 1 exhibits a strong photomechanical response in bulk crystals but is challenging to grow in microcrystalline form. High quality microcrystals of this molecule could not be grown using techniques like sublimation, reprecipitation, and the floating drop method. If the tertbutyl ester of 9-AYAA is used as a starting material, however, high quality, size-uniform microwires could be grown via acid catalyzed hydrolysis. 9-AYAA microwires with uniform length and thickness were produced after a suspension of (E)-tert-butyl 3-(anthracen-9-yl)acrylate ester 2 microparticles was tumble-mixed in a mixture of phosphoric acid and sodium dodecyl sulfate at 35 °C. The dependence of the results on temperature, surfactant and precursor concentration, and mixing mode was investigated. This chemical reaction-growth method was extended to grow microplates of 9-anthraldehyde 3 using the corresponding acylal 4 as the starting material. Under 475 nm irradiation, the 9-AYAA microwires undergo a photoinduced coiling–uncoiling transition, while the 9-anthraldehyde microplates undergo a folding–unfolding transition.

Keywords: photomechanical, surfactant, organic crystals, uniform

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Authors: Boukhadia Karima

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The fluid mechanics is the study of fluid motion laws and their interaction with solid bodies, this project leads to illustrate this interaction with depth studies and approved by experiments on the wind tunnel TE44, ensuring the efficiency, accuracy and reliability of these tests on a NACA0015 profile. A symmetric NACA0015 was placed in a subsonic wind tunnel, and measurements were made of the pressure on the upper and lower surface of the wing and of the velocity across the vortex trailing downstream from the tip of the wing. The aim of this work is to investigate experimentally the scattered pressure profile in a free airflow and the aerodynamic forces acting on this profile. The addition of around-lateral edge to the wing tip was found to eliminate the secondary vortex near the wing tip, but had little effect on the downstream characteristics of the trailing vortex. The increase in wing lift near the tip because of the presence of the trailing vortex was evident in the surface pressure, but was not captured by circulation-box measurements. The circumferential velocity within the vortex was found to reach free-stream values and produce core rotational speeds. Near the wing, the trailing vortex is asymmetric and contains definite zones where the stream wise velocity both exceeds and falls behind the free-stream value. When referenced to the free stream velocity, the maximum vertical velocity of the vortex is directly dependent on α and is independent of Re. A numerical study was conducted through a CFD code called FLUENT 6.0, and the results are compared with experimental.

Keywords: CFD code, NACA Profile, detachment, angle of incidence, wind tunnel

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Authors: Abdullah Al-Nassri, Ahmed Al-Alawi

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Seaweeds are classified into three groups: red, green, and brown. Each group of seaweeds consists of several types that have differences in composition. Even at the species level, there are differences in some ingredients, although in general composition, they are the same. Environmental conditions, availability of nutrients, and maturity stage are the main reasons for composition differences. In this study, two red seaweed species, Melanothamnus somalensis & Gelidium omanense, were collected in September 2021 from Sadh (Dhofar governorate, Oman). Five organic solvents were used sequentially to achieve extraction. The solvents were applied in the following order: hexane, dichloromethane, ethyl acetate, acetone, and methanol. Preparative HPLC (PrepLC) was performed to fraction the extracts. The chemical composition was measured; also, total phenols, flavonoids, and tannins were investigated. The structure of the extracts was analyzed by Fourier-transform infrared spectroscopy (FTIR). Seaweeds demonstrated high differences in terms of chemical composition, total phenolic content (TPC), total flavonoid content (TFC), and total tannin content (TTC). Gelidium omanense showed high moisture content, lipid content and carbohydrates (9.8 ± 0.15 %, 2.29 ± 0.09 % and 70.15 ± 0.42 %, respectively) compared to Melanothamnus somalensis (6.85 ± 0.01 %, 2.05 ± 0.12 % and 52.7 ± 0.36 % respectively). However, Melanothamnus somalensis showed high ash content and protein (27.68 ± 0.40 % and 52.7 ± 0.36 % respectively) compared to Gelidium omanense (8.07 ± 0.39 % and 9.70 ± 0.22 % respectively). Melanothamnus somalensis showed higher elements and minerals content, especially sodium and potassium. This is attributed to the jelly-like structure of Melanothamnus somalensis, which allows storage of more solutes compared to the leafy-like structure of Gelidium omanense. Furthermore, Melanothamnus somalensis had higher TPC in all fractions except the hexane fraction than Gelidium omanense. Except with hexane, TFC in the other solvents’ extracts was significantly different between Gelidium omanense and Melanothamnus somalensis. In all fractions, except dichloromethane and ethyl acetate fractions, there were no significant differences in TTC between Gelidium omanense and Melanothamnus somalensis. FTIR spectra showed variation between fractions, which is an indication of different functional groups.

Keywords: chemical composition, organic extract, Omani seaweeds, biological activity, FTIR

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Authors: Taysir Soliman

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One of the current popular clustering techniques is Spectral Clustering (SC) because of its advantages over conventional approaches such as hierarchical clustering, k-means, etc. and other techniques as well. However, one of the disadvantages of SC is the time consuming process because it requires computing the eigenvectors. In the past to overcome this disadvantage, a number of attempts have been proposed such as the Power Iteration Clustering (PIC) technique, which is one of versions from SC; some of PIC advantages are: 1) its scalability and efficiency, 2) finding one pseudo-eigenvectors instead of computing eigenvectors, and 3) linear combination of the eigenvectors in linear time. However, its worst disadvantage is an inter-class collision problem because it used only one pseudo-eigenvectors which is not enough. Previous researchers developed Deflation-based Power Iteration Clustering (DPIC) to overcome problems of PIC technique on inter-class collision with the same efficiency of PIC. In this paper, we developed Parallel DPIC (PDPIC) to improve the time and memory complexity which is run on apache spark framework using sparse matrix. To test the performance of PDPIC, we compared it to SC, ESCG, ESCALG algorithms on four small graph benchmark datasets and nine large graph benchmark datasets, where PDPIC proved higher accuracy and better time consuming than other compared algorithms.

Keywords: spectral clustering, power iteration clustering, deflation-based power iteration clustering, Apache spark, large graph

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Authors: Loai AbdAllah, Mahmoud Kaiyal

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Missing values in real-world datasets are a common problem. Many algorithms were developed to deal with this problem, most of them replace the missing values with a fixed value that was computed based on the observed values. In our work, we used a distance function based on Bhattacharyya distance to measure the distance between objects with missing values. Bhattacharyya distance, which measures the similarity of two probability distributions. The proposed distance distinguishes between known and unknown values. Where the distance between two known values is the Mahalanobis distance. When, on the other hand, one of them is missing the distance is computed based on the distribution of the known values, for the coordinate that contains the missing value. This method was integrated with Wikaya, a digital health company developing a platform that helps to improve prevention of chronic diseases such as diabetes and cancer. In order for Wikaya’s recommendation system to work distance between users need to be measured. Since there are missing values in the collected data, there is a need to develop a distance function distances between incomplete users profiles. To evaluate the accuracy of the proposed distance function in reflecting the actual similarity between different objects, when some of them contain missing values, we integrated it within the framework of k nearest neighbors (kNN) classifier, since its computation is based only on the similarity between objects. To validate this, we ran the algorithm over diabetes and breast cancer datasets, standard benchmark datasets from the UCI repository. Our experiments show that kNN classifier using our proposed distance function outperforms the kNN using other existing methods.

Keywords: missing values, incomplete data, distance, incomplete diabetes data

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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In recent years, there has been a desire to forecast student academic achievement prior to graduation. This is to help them improve their grades, particularly for individuals with poor performance. The goal of this study is to employ supervised learning techniques to construct a predictive model for student academic achievement. Many academics have already constructed models that predict student academic achievement based on factors such as smoking, demography, culture, social media, parent educational background, parent finances, and family background, to name a few. This feature and the model employed may not have correctly classified the students in terms of their academic performance. This model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester as a prerequisite to predict if the student will perform well in future on related courses. The model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost, returning a 96.7% accuracy. This model is available as a desktop application, allowing both instructors and students to benefit from user-friendly interfaces for predicting student academic achievement. As a result, it is recommended that both students and professors use this tool to better forecast outcomes.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: Makhan Maharjan, Mani Ulaganathan, Vanchiappan Aravindan, Srinivasan Madhavi, Jing-Yuan Wang, Tuti Mariana Lim

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There is great interest to exploit sustainable, low-cost, renewable resources as carbon precursors for energy storage applications. Research on development of energy storage devices has been growing rapidly due to mismatch in power supply and demand from renewable energy sources This paper reported the synthesis of porous activated carbon from biomass waste and evaluated its performance in supercapicators. In this work, we employed orange peel (waste material) as the starting material and synthesized activated carbon by pyrolysis of KOH impregnated orange peel char at 800 °C in argon atmosphere. The resultant orange peel-derived activated carbon (OP-AC) exhibited a high BET surface area of 1,901 m2 g-1, which is the highest surface area so far reported for the orange peel. The pore size distribution (PSD) curve exhibits the pores centered at 11.26 Å pore width, suggesting dominant microporosity. The OP-AC was studied as positive electrode in combination with different negative electrode materials, such as pre-lithiated graphite (LiC6) and Li4Ti5O12 for making different hybrid capacitors. The lithium ion capacitor (LIC) fabricated using OP-AC with pre-lithiated graphite delivered a high energy density of ~106 Wh kg–1. The energy density for OP-AC||Li4Ti5O12 capacitor was ~35 Wh kg–1. For comparison purpose, configuration of OP-AC||OP-AC capacitors were studied in both aqueous (1M H2SO4) and organic (1M LiPF6 in EC-DMC) electrolytes, which delivered the energy density of 6.6 Wh kg-1 and 16.3 Wh kg-1, respectively. The cycling retentions obtained at current density of 1 A g–1 were ~85.8, ~87.0 ~82.2 and ~58.8% after 2500 cycles for OP-AC||OP-AC (aqueous), OP-AC||OP-AC (organic), OP-AC||Li4Ti5O12 and OP-AC||LiC6 configurations, respectively. In addition, characterization studies were performed by elemental and proximate composition, thermogravimetry, field emission-scanning electron microscopy, Raman spectra, X-ray diffraction (XRD) pattern, Fourier transform-infrared, X-ray photoelectron spectroscopy (XPS) and N2 sorption isotherms. The morphological features from FE-SEM exhibited well-developed porous structures. Two typical broad peaks observed in the XRD framework of the synthesized carbon implies amorphous graphitic structure. The ratio of 0.86 for ID/IG in Raman spectra infers high degree of graphitization in the sample. The band spectra of C 1s in XPS display the well resolved peaks related to carbon atoms in various chemical environments; for instances, the characteristics binding energies appeared at ~283.83, ~284.83, ~286.13, ~288.56, and ~290.70 eV which correspond to sp2 -graphitic C, sp3 -graphitic C, C-O, C=O and π-π*, respectively. Characterization studies revealed the synthesized carbon to be promising electrode material towards the application for energy storage devices. The findings opened up the possibility of developing high energy LICs from abundant, low-cost, renewable biomass waste.

Keywords: lithium-ion capacitors, orange peel, pre-lithiated graphite, supercapacitors

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Authors: Afiq Mohd Fahmi, Tony Gutierrez, Sebastian Hennige

Abstract:

Increasing amounts of CO₂ entering the marine environment, also known as ocean acidification, is documented as having harmful impacts on a variety of marine organisms. When considering the future risk of hydrocarbon pollution, which is generally detrimental to marine life as well, this needs to consider how OA-induced changes to microbial communities will compound this since hydrocarbon degradation is influenced by the community-level microbial response. This study aims to evaluate the effects of increased atmospheric CO₂ conditions and oil enrichment on the phytoplankton-associated bacterial communities. Faroe Shetland Channel (FSC) is a subarctic region in the northeast Atlantic where crude oil extraction has recently been expanded. In the event of a major oil spill in this region, it is vital that we understand the response of the bacterial community and its consequence on primary production within this region—some phytoplankton communities found in the ocean harbor hydrocarbon-degrading bacteria that are associated with its psychosphere. Surface water containing phytoplankton and bacteria from FSC were cultured in ambient and elevated atmospheric CO₂ conditions for 4 days of acclimation in microcosms before introducing 1% (v/v) of crude oil into the microcosms to simulate oil spill conditions at sea. It was found that elevated CO₂ conditions do not significantly affect the chl a concentration, and exposure to crude oil detrimentally affected chl a concentration up to 10 days after exposure to crude oil. The diversity and richness of the bacterial community were not significantly affected by both CO₂ treatment and oil enrichment. The increase in the relative abundance of known hydrocarbon degraders such as Oleispira, Marinobacter and Halomonas indicates potential for biodegradation of crude oil, while the resilience of dominant taxa Colwellia, unclassified Gammaproteobacteria, unclassified Rnodobacteria and unclassified Halomonadaceae could be associated with the recovery of microalgal community 13 days after oil exposure. Therefore, the microbial community from the subsurface of FSC has the potential to recover from crude oil pollution even under elevated CO₂ (750 ppm) conditions.

Keywords: phytoplankton, bacteria, crude oil, ocean acidification

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Authors: Illyas Md Isa, Sharifah Norain Mohd Sharif, Norhayati Hashim

Abstract:

A mercury(II) sensor was developed by using multi-walled carbon nano tubes (MWCNTs) paste electrode modified with Zn/Al layered double hydroxide-3(4-methoxyphenyl) propionate nano composite (Zn/Al-HMPP). The optimum conditions by cyclic voltammetry were observed at electrode composition 2.5% (w/w) of Zn/Al-HMPP/MWCNTs, 0.4 M potassium chloride, pH 4.0, and scan rate of 100 mVs-1. The sensor exhibited wide linear range from 1x10-3 M to 1x10-7 M Hg2+ and 1x10-7 M to 1x10-9 M Hg2+, with a detection limit of 1 x 10-10 M Hg2+. The high sensitivity of the proposed electrode towards Hg(II) was confirmed by double potential-step chronocoulometry which indicated these values; diffusion coefficient 1.5445 x 10-9 cm2 s-1, surface charge 524.5 µC s-½ and surface coverage 4.41 x 10-2 mol cm-2. The presence of 25-fold concentration of most metal ions had no influence on the anodic peak current. With characteristics such as high sensitivity, selectivity and repeatability the electrode was then proposed as the appropriate alternative for the determination of mercury.

Keywords: Cyclic voltammetry, Mercury(II), Modified carbon paste electrode, Nanocomposite

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Authors: Dechrit Maneetham

Abstract:

Pick and place task is one among the most important tasks in industrial field handled by 'Selective Compliance Assembly Robot Arm' (SCARA). Repeatability with high-speed movement in a horizontal plane is a remarkable feature of this type of manipulator. The challenge of design SCARA is the difficulty of achieving stability of high-speed movement with the long length of links. Shorter links arm can move more stable. This condition made the links should be considered restrict then followed by restriction of operation area (workspace). In this research, authors demonstrated on expanding SCARA robot’s workspace in horizontal area via linear sliding actuator that embedded to base link of the robot arm. With one additional prismatic joint, the previous robot manipulator with 3 degree of freedom (3-DOF), 2 revolute joints and 1 prismatic joint becomes 4-DOF PRRP manipulator. This designation increased workspace of robot from 0.5698m² performed by the previous arm (without linear actuator) to 1.1281m² by the proposed arm (with linear actuator). The increasing rate was about 97.97% of workspace with the same links' lengths. The result of experimentation also indicated that the operation time spent to reach object position was also reduced.

Keywords: kinematics, linear sliding actuator, manipulator, control system

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Authors: H. Parameshwar Naik, Shripad Kulkarni

Abstract:

Powdery mildew is a serious disease among the fungal in high humid areas with varied temperature conditions. In recent days disease becomes very severe due to uncertain weather conditions and unique character of the disease is, it produces white mycelia growth on upper and lower leaf surfaces and in severe conditions it leads to defoliation. Results of the experiment revealed that sowing of crop in the I fortnight (FN) of July recorded the minimum mean disease severity (7.96 %) followed by crop sown in II FN of July (13.19 %) as against the crop sown in II FN of August (41.44 %) and I FN of September (33.78 %) and the I fortnight of October (33.77 %). In the first date of sowing infection started at 45 DAS and progressed till 73 DAS and it was up to 14.66 Percent and in second date of sowing disease progressed up to 22.66 percent and in the third date of sowing, it was up to 59.35 percent. Afterward, the disease started earlier and progressed up to 66.15 percent and in sixth and seventh date of sowing disease progressed up to 43.15 percent and 59.85 percent respectively. Disease progress is very fast after 45 days after sowing and highest disease incidence was noticed at 73 DAS irrespective of dates of sowing. From the results of the present study, it is very clear that disease development will be very high if crop sown in between 1st fortnight of August and the 1st fortnight of September.

Keywords: cucumber, India, Karnataka, powdery mildew

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Authors: Koushik Roy, Sourav Gur, Sudib K. Mishra

Abstract:

Evidence of pulse type features in near-fault ground motions has raised serious concern to the structural engineering community, in view of their possible implications on the behavior of structures located on the fault regions. Studies in the recent past explore the effects of pulse type ground motion on the special structures, such as transmission towers in view of their high flexibility. Identically, long period sloshing of liquid in the storage tanks under dynamic loading might increase their failure vulnerability under near-fault pulses. Therefore, the behavior of the elevated liquid storage tank is taken up in this study. Simple lumped mass model is considered, with the bilinear force-deformation hysteresis behavior. Set of near-fault seismic ground acceleration time histories are adopted for this purpose, along with the far-field records for comparison. It has been demonstrated that pulse type motions lead to significant increase of the responses; in particular, sloshing of the fluid mass could be as high as 5 times, then the far field counterpart. For identical storage capacity, slender tanks are found to be more vulnerable than the broad ones.

Keywords: far-field motion, hysteresis, liquid storage tank, near fault earthquake, sloshing

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Authors: Felix Olajide Ibikunle

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Introductory Statement: Sustainable participation of teenagers in sport requires deliberate and concerted plan and managerial policy rooted in the “philosophy of catch them young”. At risk, teenagers need proper integration into societal aspiration: This direction will go a long way to streamline them into the security breach and attractive nuisance free lifestyles. Basic Methodology: The population consists of children within 13-19 years old. A proportionate sampling size technique of 60% was adopted to select seven zones out of 11 geo-political zones in the Ibadan metropolis. Qualitative information and interview were used to collect needed information. Majority of the teenagers were out of school, street hawkers, motor pack, touts, and unserious vocation apprentices. These groups have the potentials of security breaches in the metropolis and beyond. Five hundred and thirty-four (534) respondents were used for the study. They were drawn from Ojoo, Akingbile, and Moniya axis = 72, Agbowo, Ajibode, and Apete axis = 74; Akobo, Basorun, and Idi-ape axis 79; Wofun, Monatan, and Iyana-Church axis = 78; Molete, Oke-ado and Oke-Bola axis = 75; Beere, Odinjo, Elekuro axis = 77; Eleyele, Ologuneru, and Alesinloye axis = 79. Major Findings: Multiple regression was used to analyze the independent variables and percentage. The respondents average age was 15.6 years old, and with 100% male. The instrument(questionnaire) used yielded; sport preference (r = 0.72); intervention (r = 0.68) and the sustainable participation (r = 0.70).The relative contributions of sport preference on participation of at risk teenagers was (F-ratio = 1.067); Intervention contribution of sport on participation of at risk teenagers = produced (F-ratio of 12.095) was significant while sustainable participation of at risk teenager produced (F-ratio = 1.062) was significant. Closing Statement: The respondents’ sport preference stimulated their participation in sport. The intervention exposed at risk-teenagers to coaching, which activated their interest and participation in sport. While sustainable participation contributed positively to evolve at risk teenagers participation in their preferred sport.

Keywords: sport, preference, intervention, teenagers, sustainable, participation and risk teenagers

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Authors: S. Jain, R. Savalia, V. Saini

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A simple, accurate, precise, sensitive and specific RP-HPLC method was developed and validated for simultaneous estimation of Metoprolol Succinate and Olmesartan Medoxomil in bulk and tablet dosage form. The RP-HPLC method has shown adequate separation for Metoprolol Succinate and Olmesartan Medoxomil from its degradation products. The separation was achieved on a Phenomenex luna ODS C18 (250mm X 4.6mm i.d., 5μm particle size) with an isocratic mixture of acetonitrile: 50mM phosphate buffer pH 4.0 adjusted with glacial acetic acid in the ratio of 55:45 v/v. The mobile phase at a flow rate of 1.0ml/min, Injection volume 20μl and wavelength of detection was kept at 225nm. The retention time for Metoprolol Succinate and Olmesartan Medoxomil was 2.451±0.1min and 6.167±0.1min, respectively. The linearity of the proposed method was investigated in the range of 5-50μg/ml and 2-20μg/ml for Metoprolol Succinate and Olmesartan Medoxomil, respectively. Correlation coefficient was 0.999 and 0.9996 for Metoprolol Succinate and Olmesartan Medoxomil, respectively. The limit of detection was 0.2847μg/ml and 0.1251μg/ml for Metoprolol Succinate and Olmesartan Medoxomil, respectively and the limit of quantification was 0.8630μg/ml and 0.3793μg/ml for Metoprolol and Olmesartan, respectively. Proposed methods were validated as per ICH guidelines for linearity, accuracy, precision, specificity and robustness for estimation of Metoprolol Succinate and Olmesartan Medoxomil in commercially available tablet dosage form and results were found to be satisfactory. Thus the developed and validated stability indicating method can be used successfully for marketed formulations.

Keywords: metoprolol succinate, olmesartan medoxomil, RP-HPLC method, validation, ICH

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Authors: Nahla H. Alaswadko, Rayya A. Hassan, Bayar N. Mohammed

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Empirical deterministic models have been developed to predict roughness progression of heavy duty spray sealed pavements for a dataset representing rural arterial roads. The dataset provides a good representation of the relevant network and covers a wide range of operating and environmental conditions. A sample with a large size of historical time series data for many pavement sections has been collected and prepared for use in multilevel regression analysis. The modelling parameters include road roughness as performance parameter and traffic loading, time, initial pavement strength, reactivity level of subgrade soil, climate condition, and condition of drainage system as predictor parameters. The purpose of this paper is to report the approaches adopted for models development and validation. The study presents multilevel models that can account for the correlation among time series data of the same section and to capture the effect of unobserved variables. Study results show that the models fit the data very well. The contribution and significance of relevant influencing factors in predicting roughness progression are presented and explained. The paper concludes that the analysis approach used for developing the models confirmed their accuracy and reliability by well-fitting to the validation data.

Keywords: roughness progression, empirical model, pavement performance, heavy duty pavement

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Authors: Nawang Chhunid, Gagnesh Kumar

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On-chip memories consume a significant portion of the overall die space and power in modern microprocessors. On-chip caches depend on Static Random-Access Memory (SRAM) cells and scaling of technology occurring as per Moore’s law. Unfortunately, the scaling is affecting stability, performance, and leakage power which will become major problems for future SRAMs in aggressive nanoscale technologies due to increasing device mismatch and variations. 3T1D Dynamic Random-Access Memory (DRAM) cell is a non-destructive read DRAM cell with three transistors and a gated diode. In 3T1D DRAM cell gated diode (D1) acts as a storage device and also as an amplifier, which leads to fast read access. Due to its high tolerance to process variation, high density, and low cost of memory as compared to 6T SRAM cell, it is universally used by the advanced microprocessor for on chip data and program memory. In the present paper, it has been shown that 3T1D DRAM cell can perform better in terms of fast read access as compared to 6T, 4T, 3T SRAM cells, respectively.

Keywords: DRAM Cell, Read Access Time, Retention Time, Average Power dissipation

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Authors: Alua Massalimova

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Situation analysis of Blood Service revealed that the strengths dominated over the weak 1.4 times. The possibilities dominate over the threats by 1.1 times. It follows that by using timely the possibility the Service, it is possible to strengthen its strengths and avoid threats. Priority directions of the resulting analysis are the use of subjective factors, such as personal management capacity managers of the Blood Center in the field of possibilities of legal activity of administrative decisions and the mobilization of stable staff in general market conditions. We have studied for the period 2011-2015 retrospectively indicators of Blood Service of Kazakhstan. Strengths of Blood Service of RK(Ps4,5): 1) indicators of donations for 1000 people is higher than in some countries of the CIS (in Russia 14, Kazakhstan - 17); 2) the functioning science centre of transfusiology; 3) the legal possibility of additional financing blood centers in the form of paid services; 4) the absence of competitors; 5) training on specialty Transfusiology; 6) the stable management staff of blood centers, a high level of competence; 7) increase in the incidence requiring transfusion therapy (oncohematology); 8) equipment upgrades; 9) the opening of a reference laboratory; 10) growth of the proportion of issued high-quality blood components; 11) governmental organization 'Drop of Life'; 12) the functioning bone marrow register; 13) equipped with modern equipment HLA-laboratory; 14) High categorization of average medical workers; 15) availability of own specialized scientific journal; 16) vivarium. The weaknesses (Ps = 3.5): 1) the incomplete equipping of blood centers and blood transfusion cabinets according to standards; 2) low specific weight of paid services of the CC; 3) low categorization of doctors; 4) high staff turnover; 5) the low scientific potential of industrial and clinical of transfusiology; 6) the low wages paid; 7) slight growth of harvested donor blood; 8) the weak continuity with offices blood transfusion; 9) lack of agitation work; 10) the formally functioning of Transfusion Association; 11) the absence of scientific laboratories; 12) high standard deviation from the average for donations in the republic. The possibilities (Ps = 2,7): 1): international grants; 2) organization of international seminars on clinical of transfusiology; 3) cross-sectoral cooperation; 4) to increase scientific research in the field of clinical of transfusiology; 5) reduce the share of donation unsuitable for transfusion and processing; 6) strengthening marketing management in the development of fee-based services; 7) advertising paid services; 8) strengthening the publishing of teaching aids; 9) team-building staff. The threats (Ps = 2.1): 1) an increase of staff turnover; 2) the risk of litigation; 3) reduction gemoprodukts based on evidence-based medicine; 4) regression of scientific capacity; 5) organization of marketing; 6) transfusiologist marketing; 7) reduction in the quality of the evidence base transfusions.

Keywords: blood service, healthcare, Kazakhstan, quantative swot analysis

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Authors: Raymond Xu, Cindy Jingru Wang

Abstract:

Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

Procedia PDF Downloads 267