Search results for: language performance

Authors: Ebenezer Joseph, Veena Easvaradoss, S. Sundar Manoharan, David Chandran, Sumathi Chandrasekaran, T. R. Uma

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Perceptual reasoning is the ability that incorporates fluid reasoning, spatial processing, and visual motor integration. Several theories of cognitive functioning emphasize the importance of fluid reasoning. The ability to manipulate abstractions and rules and to generalize is required for reasoning tasks. This study, funded by the Cognitive Science Research Initiative, Department of Science and Technology, Government of India, analyzed the effect of 1-year chess training on the perceptual reasoning of children. A pretest–posttest with control group design was used, with 43 (28 boys, 15 girls) children in the experimental group and 42 (26 boys, 16 girls) children in the control group. The sample was selected from children studying in two private schools from South India (grades 3 to 9), which included both the genders. The experimental group underwent weekly 1-hour chess training for 1 year. Perceptual reasoning was measured by three subtests of WISC-IV INDIA. Pre-equivalence of means was established. Further statistical analyses revealed that the experimental group had shown statistically significant improvement in perceptual reasoning compared to the control group. The present study clearly establishes a correlation between chess learning and perceptual reasoning. If perceptual reasoning can be enhanced in children, it could possibly result in the improvement of executive functions as well as the scholastic performance of the child.

Keywords: chess, cognition, intelligence, perceptual reasoning

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Authors: Tasir Khan, Yejuan Wan, Kalim Ullah

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Hydrological frequency analysis has been conducted to estimate the minimum flow elevation of the Indus River in Pakistan to protect the ecosystem. The Maximum likelihood estimation (MLE) technique is used to estimate the best-fitted distribution for Minimum Ecological Flows at nine stations of the Indus River in Pakistan. The four selected distributions, Generalized Extreme Value (GEV) distribution, Generalized Logistics (GLO) distribution, Generalized Pareto (GPA) distribution, and Pearson type 3 (PE3) are fitted in all sites, usually used in hydro frequency analysis. Compare the performance of these distributions by using the goodness of fit tests, such as the Kolmogorov Smirnov test, Anderson darling test, and chi-square test. The study concludes that the Maximum Likelihood Estimation (MLE) method recommended that GEV and GPA are the most suitable distributions which can be effectively applied to all the proposed sites. The quantiles are estimated for the return periods from 5 to 1000 years by using MLE, estimations methods. The MLE is the robust method for larger sample sizes. The results of these analyses can be used for water resources research, including water quality management, designing irrigation systems, determining downstream flow requirements for hydropower, and the impact of long-term drought on the country's aquatic system.

Keywords: minimum ecological flow, frequency distribution, indus river, maximum likelihood estimation

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Authors: S. Obregon-Cano, R. Moreno-Rojas, E. Cartea-Gonzalez, A. De Haro-Bailon

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The potential of near-infrared spectroscopy (NIRS) for screening the total glucosinolate (t-GSL) content, and also, the aliphatic glucosinolates gluconapin (GNA), progoitrin (PRO) and glucobrassicanapin (GBN) in turnip greens and turnip tops was assessed. This crop is grown for edible leaves and stems for human consumption. The reference values for glucosinolates, as they were obtained by high performance liquid chromatography on the vegetable samples, were regressed against different spectral transformations by modified partial least-squares (MPLS) regression (calibration set of samples n= 350). The resulting models were satisfactory, with calibration coefficient values from 0.72 (GBN) to 0.98 (tGSL). The predictive ability of the equations obtained was tested using a set of samples (n=70) independent of the calibration set. The determination coefficients and prediction errors (SEP) obtained in the external validation were: GNA=0.94 (SEP=3.49); PRO=0.41 (SEP=1.08); GBN=0.55 (SEP=0.60); tGSL=0.96 (SEP=3.28). These results show that the equations developed for total glucosinolates, as well as for gluconapin can be used for screening these compounds in the leaves and stems of this species. In addition, the progoitrin and glucobrassicanapin equations obtained can be used to identify those samples with high, medium and low contents. The calibration equations obtained were accurate enough for a fast, non-destructive and reliable analysis of the content in GNA and tGSL directly from NIR spectra. The equations for PRO and GBN can be employed to identify samples with high, medium and low contents.

Keywords: brassica rapa, glucosinolates, gluconapin, NIRS, turnip greens

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Authors: Phan Nghiem Vu, Le Tuan Vu, Ta Quang Tai

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The optimal construction design used during the execution of a construction project is a key factor in determining high productivity and customer satisfaction, however, this management process sometimes is carried out without care and the systematic method that it deserves, bringing negative consequences. This study proposes a knowledge management (KM) approach that will enable the intelligent use of experienced and acknowledged engineers to improve the management of construction design works for a project. Then a knowledge-based application to support this decision-making process is proposed and described. To define and design the system for the application, semi-structured interviews were conducted within five construction consulting organizations with the purpose of studying the way that the method’ optimizing process is implemented in practice and the knowledge supported with it. A system of an optimizing construction design works (OCDW) based on knowledge was developed then validated with construction experts. The OCDW was liked as a valuable tool for construction design works’ optimization, by supporting organizations to generate a corporate memory on this issue, reducing the reliance on individual knowledge and also the subjectivity of the decision-making process. The benefits are described as provided by the performance support system, reducing costs and time, improving product design quality, satisfying customer requirements, expanding the brand organization.

Keywords: optimizing construction design work, construction consultant organization, knowledge management, knowledge-based application

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Authors: Chen-Sheng Chen, Tsung-Yi Huang, Pi-Chang Sun

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Chronic stroke patients often have complaints about hand dysfunction due to flexor hypertonia and extensor weakness, which makes it difficult to open their affected hand for functional grasp. Hand rehabilitation after stroke is essential for restoring functional independence. Constraint-induced movement therapy has shown to be a successful treatment for patients who have acquired certain level of wrist and finger extension. The goal of this study was to investigate the feasibility of task-oriented approach incorporating 3D-printed dynamic hand device by evaluating hand functional performance. This study manufactured a hand device using 3d printer for chronic stroke. The experimental group engaged task-oriented approach with dynamic hand device, but the control group only received task-oriented approach. Outcome measurements include palmar pinch force (PPF), lateral pinch force (LPF), grip force (GF), and Box and Blocks Test (BBT). The results of study revealed the improvement of PPF in experimental group but not in control group. Meanwhile, improvement in LPF, GF and BBT can be found in both groups. This study demonstrates that the 3D-printed dynamic hand device is an effective therapeutic assistive device to improve pinch force, grasp force, and dexterity and facilitate motivation during home program in individuals with chronic stroke.

Keywords: 3D printing, biomechanics, hand orthosis, stroke

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Authors: A. T. Laiche, M. L. Tlil, Benine B., S. Bechoua

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The aim of this study is to isolate and select, from camel milk from El-Oued region in Algeria, a strains of lactic acid bacteria and possessing probiotic properties ; and to evaluate their potential effect on intestinal disorders in Wistar ratsmThe results relating to the selection of probiotic strains confirms that the Thermophilic streptococcus exhibits the best probiotic activity performance, with a resistance important to different degrees of pH and to bile salts, and a remarkable antibacterial activity and resistance to antibiotics compared to the other four isolated strains. In the in vivo study, diseases are induced in rats at the level of the digestive system, it was reported that the administration of Escherichia coli and castor oil caused an intestinal disorders. The microscopic observation of the histological section of the intestine showed a damaged intestinal structure and some symptoms of its irritation, including a decrease in the height of the villi and the presence of others destroyed cells, and after treatment with Streptococcus thermophilus, the microscopic observation of the cut of the histological section of the intestine showed almost complete disappearance of the mentioned symptoms, The dosage of the hematological parameters by complete blood count (CBC) is in agreement with the results of the histological sections.

Keywords: camel milk, probiotic, pathogenic bacteria, intestinal disorders, lactic acid bacteria

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Authors: Klaus Peter Scherer, Daniel Knöll, Constantin Rieder

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Problem and Purpose: Intelligent systems are available and helpful to support the human being decision process, especially when complex surgical eye interventions are necessary and must be performed. Normally, such a decision support system consists of a knowledge-based module, which is responsible for the real assistance power, given by an explanation and logical reasoning processes. The interview based acquisition and generation of the complex knowledge itself is very crucial, because there are different correlations between the complex parameters. So, in this project (semi)automated self-learning methods are researched and developed for an enhancement of the quality of such a decision support system. Methods: For ophthalmic data sets of real patients in a hospital, advanced data mining procedures seem to be very helpful. Especially subgroup analysis methods are developed, extended and used to analyze and find out the correlations and conditional dependencies between the structured patient data. After finding causal dependencies, a ranking must be performed for the generation of rule-based representations. For this, anonymous patient data are transformed into a special machine language format. The imported data are used as input for algorithms of conditioned probability methods to calculate the parameter distributions concerning a special given goal parameter. Results: In the field of knowledge discovery advanced methods and applications could be performed to produce operation and patient related correlations. So, new knowledge was generated by finding causal relations between the operational equipment, the medical instances and patient specific history by a dependency ranking process. After transformation in association rules logically based representations were available for the clinical experts to evaluate the new knowledge. The structured data sets take account of about 80 parameters as special characteristic features per patient. For different extended patient groups (100, 300, 500), as well one target value as well multi-target values were set for the subgroup analysis. So the newly generated hypotheses could be interpreted regarding the dependency or independency of patient number. Conclusions: The aim and the advantage of such a semi-automatically self-learning process are the extensions of the knowledge base by finding new parameter correlations. The discovered knowledge is transformed into association rules and serves as rule-based representation of the knowledge in the knowledge base. Even more, than one goal parameter of interest can be considered by the semi-automated learning process. With ranking procedures, the most strong premises and also conjunctive associated conditions can be found to conclude the interested goal parameter. So the knowledge, hidden in structured tables or lists can be extracted as rule-based representation. This is a real assistance power for the communication with the clinical experts.

Keywords: an expert system, knowledge-based support, ophthalmic decision support, self-learning methods

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Authors: Osama Abdallah Mohammed Enan, Amin Babiker A/Nabi Mustafa

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The aim of this study is to evaluate and analyze different parameters of WCDMA (wideband code division multiplication). Moreover, this study also incorporates brief yet throughout analysis of WCDMA’s components as well as its internal architecture. This study also examines different power controls. These power controls may include open loop power control, closed or inner group loop power control and outer loop power control. Different handover techniques or methods of WCDMA are also illustrated in this study. These handovers may include hard handover, inter system handover and soft and softer handover. Different duplexing techniques are also described in the paper. This study has also presented an idea about different parameters of WCDMA that leads the system towards QoS issues. This may help the operator in designing and developing adequate network configuration. In addition to this, the study has also investigated various parameters including Bit Energy per Noise Spectral Density (Eb/No), Noise rise, and Bit Error Rate (BER). After simulating these parameters, using MATLAB environment, it was investigated that, for a given Eb/No value the system capacity increase by increasing the reuse factor. Besides that, it was also analyzed that, noise rise is decreasing for lower data rates and for lower interference levels. Finally, it was examined that, BER increase by using one type of modulation technique than using other type of modulation technique.

Keywords: duplexing, handover, loop power control, WCDMA

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Authors: Rajneesh, Priyanka Singh

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Biomass resources have been one of the main energy sources for mankind since the dawn of civilization. There is a vast scope to convert these energy sources into biogas which is a clean, low carbon technology for efficient management and conversion of fermentable organic wastes into a cheap and versatile fuel and bio/organic manure. Thus, in order to enhance the performance of anaerobic digester, an optimizing analysis of resultant parameters (organic dry matter (oDM) content, methane percentage, and biogas yield) has been done for a plug flow anaerobic digester having mesophilic conditions (20-40°C) with the wet fermentation process. Based on the analysis, correlations for oDM, methane percentage, and biogas yield are derived using multiple regression analysis. A statistical model is developed to correlate the operating variables using the design of experiment approach by selecting central composite design (CCD) of a response surface methodology. Results shown in the paper indicates that as the operating temperature increases the efficiency of digester gets improved provided that the pH and hydraulic retention time (HRT) remains constant. Working in an optimized range of carbon-nitrogen ratio for the plug flow digester, the output parameters show a positive change with the variation of dry matter content (DM).

Keywords: biogas, digester efficiency, design of experiment, plug flow digester

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Authors: Jeanne Grace, Shereen Currie

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Background: Obesity associated comorbidities increase the risk of morbidity and mortality among employees in the workplace. Objectives: The study aimed to determine the prevalence of obesity and comorbidities like diabetes, hypertension, and hypercholesterolemia associated with obesity within the workplace in South Africa. Methods: A total of 17359 male (n = 8561) and female (n = 8798) employees, aged between 18-64 years (40.8 ± 11.0), from various corporate and industrial companies in South Africa participated in the study. Subjects were assigned to one of five body mass index (BMI) categories, according to their BMI: normal weight, BMI of 18.5‒24.9 kg/m² (n = 7338); overweight, BMI of 25.0‒29.9 kg/m² (n = 6323); obese class I, BMI of 30.0-34.9 kg/m² (n = 2552); obese class II, BMI of 35.0-39.9 kg/m² (n = 782); and obese class III, BMI of ≥ 40 kg/m² (n = 364). Height, weight, blood pressure, random blood glucose, and total cholesterol were measured. Results: The prevalence of normal weight men was 29.2% and women 55.0%; overweight men 46.4% and women 26.7%, obese men 24.4% and women 18.3%. A significant association (p<0.01) of BMI with diabetes, systolic and diastolic hypertension, and hypercholesterolemia were noted. Conclusion: Obesity is strongly associated with adverse comorbidities that may impact employees’ quality of life and performance. If unaddressed, it can increase comorbidities, not only affecting the bottom line of companies but causing morbidity and mortality, including sudden death.

Keywords: body mass index, cholesterol, blood glucose, workplace

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Authors: O. Rozita, N. M. Nik Aziz

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High-density planting is usually recommended for a small area of planting in order to increase production. The normal planting distance for cocoa (Theobroma cacao L.) in Malaysia is 3 m x 3 m. The study was conducted at Cocoa Research and Development Centre, Malaysia Cocoa Board, Jengka, Pahang with the objectives to evaluate the suitability of seven cocoa clones under four different planting densities and to study the interaction between cocoa clones and planting densities. The study was arranged in the split plot with randomized complete block design and replicated three times. The cocoa clone was assigned as the main plot and planting density was assigned as a subplot. The clones used in this study were PBC 123, PBC 112, MCBC4, MCBC 5, QH 1003, QH 22, and BAL 244. The planting distance were 3 m x 3 m (1000 stands/ha), 3 m x 1.5 m (2000 stands/ha), 3 m x 1 m (3000 stands/ha) and (1.5 m x 1.5 m) x 3 m (3333 stands/ha). Evaluation on yield performance was carried out for seven years. Clones of PBC 123, QH 1003, and QH 22 obtained the higher yield, meanwhile MCBC 4, MCBC 5, and BAL 244 obtained the lowest yield. In general, high-density planting can increase cocoa production with good management practices. Among the cocoa management practices, the selection of suitable clones with small branching habits and moderately vigorous and proper pruning activity were the most important factor in high-density planting.

Keywords: clones, management, planting density, Theobroma cacao, yield

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Authors: Qiao Mao

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There is a growing number of studies concerning STEM (Science, Technology, Engineering, and Mathematics) and STEAM (Science, Technology, Engineering, Arts, and Mathematics). However, the research is little on STEAM competitions from Arts' perspective. This study takes the annual PowerTech STEAM competition in Taiwan as an example. In this activity, students are asked to make wooden bionic mechanical beasts on the spot and participate in a model and speed competition. This study aims to explore how Arts influences STEM after it involves in the making of mechanical beasts. A case study method is adopted. Through expert sampling, five prize winners in the PowerTech Youth Science and Technology Creation Competition and their supervisors are taken as the research subjects. Relevant data which are collected, sorted out, analyzed and interpreted afterwards, derive from observations, interview and document analyses, etc. The results of the study show that in the PowerTech Youth Science and Technology Creation Competition, when Arts involves in STEM, (1) it has an impact on the athletic performance, balance, stability and symmetry of mechanical beasts; (2) students become more interested and more creative in making STEAM mechanical beasts, which can promote students' learning of STEM; (3) students encounter more difficulties and problems when making STEAM mechanical beasts, and need to have more systematic thinking and design thinking to solve problems.

Keywords: PowerTech, STEAM contest, mechanical beast, arts' role

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Authors: S. J. Shahidzadeh Tabatabaei, A. M. Fattahi

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Modal analysis of an FGM plate containing the ceramic phase of Al2O3 and metal phase of stainless steel 304 was performed using ABAQUS, with the assumptions that the material has an elastic mechanical behavior and its Young modulus and density are varying in thickness direction. For this purpose, a subroutine was written in FORTRAN and linked with ABAQUS. First, a simulation was performed in accordance to other researcher’s model, and then after comparing the obtained results, the accuracy of the present study was verified. The obtained results for natural frequency and mode shapes indicate good performance of user-written subroutine as well as FEM model used in present study. After verification of obtained results, the effect of clamping condition and the material type (i.e. the parameter n) was investigated. In this respect, finite element analysis was carried out in fully clamped condition for different values of n. The results indicate that the natural frequency decreases with increase of n, since with increase of n, the amount of ceramic phase in FGM plate decreases, while the amount of metal phase increases, leading to decrease of the plate stiffness and hence, natural frequency, as the Young modulus of Al2O3 is equal to 380 GPa and the Young modulus of stainless steel 304 is equal to 207 GPa.

Keywords: FGM plates, modal analysis, natural frequency, finite element method

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Authors: Bayar Shahab

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The fast development of technology that has advanced neuroscience and human interaction with computers has enabled solutions to various problems, and issues of this new era have been found and are being found like no other time in history. Brain-computer interface so-called BCI has opened the door to several new research areas and have been able to provide solutions to critical and important issues such as supporting a paralyzed patient to interact with the outside world, controlling a robot arm, playing games in VR with the brain, driving a wheelchair or even a car and neurotechnology enabled the rehabilitation of the lost memory, etc. This review work presents state-of-the-art methods and improvements of canonical correlation analyses (CCA), which is an SSVEP-based BCI method. These are the methods used to extract EEG signal features or, to be said in a different way, the features of interest that we are looking for in the EEG analyses. Each of the methods from oldest to newest has been discussed while comparing their advantages and disadvantages. This would create a great context and help researchers to understand the most state-of-the-art methods available in this field with their pros and cons, along with their mathematical representations and usage. This work makes a vital contribution to the existing field of study. It differs from other similar recently published works by providing the following: (1) stating most of the prominent methods used in this field in a hierarchical way (2) explaining pros and cons of each method and their performance (3) presenting the gaps that exist at the end of each method that can open the understanding and doors to new research and/or improvements.

Keywords: BCI, CCA, SSVEP, EEG

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Authors: Azadeh Jafari, Mohammad Taghi Karimi, Azadeh Nadi

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Background: Scoliosis is the lateral curvature of the spine which may influence the abilities of the subjects during standing and walking. Most of the scoliotic subjects use orthosis to reduce the curve and to decrease the risk of curve progression. There was lack of information regarding the effects of orthosis on kinematic and joint contact force. Therefore, this research was done to highlight the effects of orthosis on the aforementioned parameters. Method: 5 scoliotic subjects were recruited in this study, with single curve less than 40 (females with age 13.2 ± 1.7). They were asked to walk with and without orthosis. The kinematic of the joints, force applied on the legs, moments transmitted through the joints and joint contact forces were evaluated in this study. Moreover, the lengths of muscles were determined by use of computer muscle control approach in OpenSim. Results: There was a significant difference between the second peak of vertical ground reaction force while walking with and without orthosis (p-value < 0.05). There was no difference between spatiotemporal gait parameters while walking with and without orthosis (P-value > 0.05). The mean values of joint contact forces (vertical component) increased by the use of orthosis, but the difference was not significant (p-value > 0.05). Conclusion: Although the kinematic of most of the body joints was not influenced by the use of orthosis, the joint contact force may be increased by orthosis. The increase in joint contact force may be due to the performance of orthosis which restricts the motions of pelvic and increases compensatory mechanism used by the subjects to decrease the side effects of the orthosis.

Keywords: scoliosis, joint contact force, kinetic, kinematic

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Authors: Abdelmajid Timoumi, Salah Alamri, Hatem Alamri

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TiO₂ Graphene Oxide (TiO₂-GO) nanocomposite was prepared using the spin coating technique of suspension of Graphene Oxide (GO) nanosheets and Titanium Tetra Isopropoxide (TIP). The prepared nanocomposites samples were characterized by X-ray diffractometer, Scanning Electron Microscope and Atomic Force Microscope to examine their structures and morphologies. UV-vis transmittance and reflectance spectroscopy was employed to estimate band gap energies. From the TiO₂-GO samples, a 0.25 μm thin layer on a piece of glass 2x2 cm was created. The X-ray diffraction analysis revealed that the as-deposited layers are amorphous in nature. The surface morphology images demonstrate that the layers grew in distributed with some spherical/rod-like and partially agglomerated TiGO on the surface of the composite. The Atomic Force Microscopy indicated that the films are smooth with slightly larger surface roughness. The analysis of optical absorption data of the layers showed that the values of band gap energy decreased from 3.46 eV to 1.40 eV, depending on the grams of GO doping. This reduction might be attributed to electron and/or hole trapping at the donor and acceptor levels in the TiO₂ band structure. Observed results have shown that the inclusion of GO in the TiO₂ matrix have exhibited significant and excellent properties, which would be promising for application in the photovoltaic application.

Keywords: titanium dioxide, graphene oxide, thin films, solar cells

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Authors: Emie A. Salamangkit-Mirasol, Rinlee Butch M. Cervera

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Rice hull or rice husk (RH) is an agricultural waste obtained from milling rice grains. Since RH has no commercial value and is difficult to use in agriculture, its volume is often reduced through open field burning which is an environmental hazard. In this study, amorphous nanosilica from Philippine waste RH was prepared via acid precipitation method. The synthesized samples were fully characterized for its microstructural properties. X-ray diffraction pattern reveals that the structure of the prepared sample is amorphous in nature while Fourier transform infrared spectrum showed the different vibration bands of the synthesized sample. Scanning electron microscopy (SEM) and particle size analysis (PSA) confirmed the presence of agglomerated silica particles. On the other hand, transmission electron microscopy (TEM) revealed an amorphous sample with grain sizes of about 5 to 20 nanometer range and has about 95 % purity according to EDS analyses. The elemental mapping also suggests that leaching of rice hull ash effectively removed the metallic impurity such as potassium element in the material. Hence, amorphous nanosilica was successfully prepared via a low-cost acid precipitation method from Philippine waste rice hull. In addition, initial electrode performance of the synthesized samples as an anode material in Lithium Battery have been investigated.

Keywords: agricultural waste, anode material, nanosilica, rice hull

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Authors: Retno A. S. Lestari, Wahyudi B. Sediawan, Siti Syamsiah, Sarto

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Sulfur-oxidizing bacteria were isolated and then grown on snakefruits seeds forming biofilm. Their performance in sulfide removal were experimentally observed. Snakefruit seeds were then used as packing material in a cylindrical tube. Biological treatment of hydrogen sulfide from biogas was investigated using biofilm on packed bed of snakefruits seeds. Biogas containing 27,9512 ppm of hydrogen sulfide was flown through the bed. Then the hydrogen sulfide concentrations in the outlet at various times were analyzed. A set of simple kinetics model for the rate of the sulfide removal and the bacterial growth was proposed. The axial sulfide concentration gradient in the flowing liquid are assumed to be steady-state. Mean while the biofilm grows on the surface of the seeds and the oxidation takes place in the biofilm. Since the biofilm is very thin, the sulfide concentration in the biofilm is assumed to be uniform. The simultaneous ordinary differential equations obtained were then solved numerically using Runge-Kutta method. The acuracy of the model proposed was tested by comparing the calcultion results using the model with the experimental data obtained. It turned out that the model proposed can be applied to describe the removal of sulfide liquid using bio-filter in packed bed. The values of the parameters were also obtained by curve-fitting. The biofilter could remove 89,83 % of the inlet of hydrogen sulfide from biogas for 2.5 h, and optimum loading of 8.33 ml/h.

Keywords: Sulfur-oxidizing bacteria, snakefruits seeds, biofilm, packing material, biogas

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Authors: Fatima Zohra Rahou, A. Guen Bouazza, B. Bouazza

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Multi-gate SOI MOSFETs has shown better results in subthreshold performances. The replacement of SiO2 by high-k dielectric can fulfill the requirements of Multi-gate MOSFETS with a scaling trend in device dimensions. The advancement in fabrication technology has also boosted the use of different high -k dielectric materials as oxide layer at different places in MOSFET structures. One of the most important multi-gate structures is square GAA SOI MOSFET that is a strong candidate for the next generation nanoscale devices; show an even stronger control of short channel effects. In this paper, GAA SOI MOSFET structure with using high -k dielectrics materials Al2O3 (k~9), HfO2 (k~20), La2O3 (k~30) and metal gate TiN are simulated by using 3-D device simulator DevEdit and Atlas of SILVACO TCAD tools. Square GAA SOI MOSFET transistor with High-k HfO2 gate dielectrics and TiN metal gate exhibits significant improvements performances compared to Al2O3 and La2O3 dielectrics for the same structure. Simulation results of GAA SOI MOSFET transistor with HfO2 dielectric show the increase in saturation current and Ion/Ioff ratio while leakage current, subthreshold slope and DIBL effect are decreased.

Keywords: technology SOI, short-channel effects (SCEs), multi-gate SOI MOSFET, square GAA SOI MOSFET, high-k dielectric, Silvaco software

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Authors: Regina Chua

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To reduce the costs of re-fielding a large survey, a Random Forest classifier was applied to measure the accuracy of classifying individuals into their assigned segments with the fewest possible questions. Given a long survey, one needed to determine the most predictive ten or fewer questions that would accurately assign new individuals to custom segments. Furthermore, the solution needed to be quick in its classification and usable in non-Python environments. In this paper, a supervised Random Forest classifier was modeled on a dataset with 7,000 individuals, 60 questions, and 254 features. The Random Forest consisted of an iterative collection of individual decision trees that result in a predicted segment with robust precision and recall scores compared to a single tree. A random 70-30 stratified sampling for training the algorithm was used, and accuracy trade-offs at different depths for each segment were identified. Ultimately, the Random Forest classifier performed at 87% accuracy at a depth of 10 with 20 instead of 254 features and 10 instead of 60 questions. With an acceptable accuracy in prioritizing feature selection, new tools were developed for non-Python environments: a worksheet with a formulaic version of the algorithm and an embedded function to predict the segment of an individual in real-time. Random Forest was determined to be an optimal classification model by its feature selection, performance, processing speed, and flexible application in other environments.

Keywords: machine learning, supervised learning, data science, random forest, classification, prediction, predictive modeling

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Authors: Amer Alzaidi

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Islamic banking is an alternative solution to those people who are worried about Riba (interest) in all forms of transaction while using banking services and products. Today, banks around the world have Islamic banking services and products the in one form or another. The use of Islamic banking is not only restricted to Muslims world but have reached to non-Muslim countries like UK, USA, Australia and Canada as well. Compared to conventional banking, the adoption rate of Islamic banking is low because of unawareness of customers, financial cost, and performance issues. The interest in Islamic banking by financial institutions as well as low adoption rate motivated us to look this matter into detail in order to identify Critical Success Factors, which are positively motivating customers to use Islamic banking services/ products and Critical Risk Factors, which have significantly negative effect on the adoption of Islamic banking. The CSFs and CRFs will be initially identified from the literature using methodology called Systematic Literature Review, followed by the empirical analysis of these factors using survey research method. Later, we will develop Islamic Banking Adoption Model (IBAM) to help banks to assess their Islamic banking strategic positioning and to improve their operational efficiency. The first potential contribution of this research study will be the development of IBAM protocol that will provide us guidelines for conducting our actual SLR. The second major contribution of this research will be the development of Islamic Banking Adoption Model (IBAM), and the third contribution of this research study will be the evaluation of the developed IBMA.

Keywords: Islamic banking, adoption model, protocol, technology

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Authors: Anindita Roy

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This paper offers a queer reading of the myth of Mohini and Ardhanarishvara in Indian mythology to explore the transformative capacity of gender performativity with a view to focusing on the notion of female and male as harmonious contributors in culture and nature. The qualitative study of these two narratives ponders on the issues of dualism in Indian mythology. These myths approach different queer experiences in different ways - the first, an incarnation of Vishnu into Mohini by body swapping and the latter, the myth of Ardhanarishvara in which one sacred body upholds two different biological identities together- male and female. Emphasizing on the transformation of sex, the present paper re-reads how these queer-transformations can become transformative in the society. The study is explained in three parts. The first one focuses on the two select myths to explore the idea of gender as performance and the concept of queer ecofeminism where nature/culture, heterosexuality/queer female/male dualism exist in a paradigm. The second segment analyzes whether these myths destabilize or promote the access of queer and the experience of ‘other’ in the society and resistance against domination. The third section inquires to rethink the whole world about the value and hierarchy of men over women, heterosexuality over queer, culture over nature to call for a recovery of the female/male, nature/culture principles as complementary. What the paper intends to investigate is if and how gender transformations in religious myths have the capacity to transform personal and social notions and practices of different hierarchies.

Keywords: dualism, Indian myth, queer, transformativity

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Authors: Maturos Chongchaikit, Sitthikorn Sumalee, Nopphawan Chimroylarp, Nongluck Manowaluilou, Thapanee Thammetha

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The 2015 Kasetsart University Research Plan, which was funded by the National Research Institutes: TRF – NRCT, comprises four sub-research projects on the development of three OER websites and on their usage study by students in international programs. The goals were to develop the open educational resources (OER) in the form of websites that will promote three key skills of quality learning and achievement: Academic English, Educational Research, and ICT Literacy, to graduate students in international programs of Thailand. The statistics from the Office of Higher Education showed that the number of foreign students who come to study in international higher education of Thailand has increased respectively by 25 percent per year, proving that the international education system and institutes of Thailand have been already recognized regionally and globally as meeting the standards. The output of the plan: the OER websites and their materials, and the outcome: students’ learning improvement due to lecturers’ readiness for open educational media, will ultimately lead the country to higher business capabilities for international education services in ASEAN Community in the future. The OER innovation is aimed at sharing quality knowledge to the world, with the adoption of Creative Commons Licenses that makes sharing be able to do freely (5Rs openness), without charge and leading to self and life-long learning. The research has brought the problems on the low usage of existing OER in the English language to develop the OER on three specific skills and try them out with the sample of 100 students randomly selected from the international graduate programs of top 10 Thai universities, according to QS Asia University Rankings 2014. The R&D process was used for product evaluation in 2 stages: the development stage and the usage study stage. The research tools were the questionnaires for content and OER experts, the questionnaires for the sample group and the open-ended interviews for the focus group discussions. The data were analyzed using frequency, percentage, mean and SD. The findings revealed that the developed websites were fully qualified as OERs by the experts. The students’ opinions and satisfaction were at the highest levels for both the content and the technology used for presentation. The usage manual and self-assessment guide were finalized during the focus group discussions. The direct participation according to the concept of 5Rs Openness Activities through the provided tools of OER models like MERLOT and OER COMMONS, as well as the development of usage manual and self-assessment guide, were revealed as a key approach to further extend the output widely and sustainably to the network of users in various higher education institutions.

Keywords: open educational resources, international education services business, academic English, educational research, ICT literacy, international graduate program, OER

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Authors: M. S. Said, J. A. Ghani, Izzati Osman, Z. A. Latiff, S. A .F. Syed Mohd

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Metal matrix composites have demand for light-weight structural and functional materials. MMCs have been shown to offer improvements in strength, rigidity, temperature stability, wear resistance, reliability and control of physical properties such as density and coefficient of thermal expansion, thereby providing improved engineering performance in comparison to the un-reinforced matrix. Experiment were conducted at various cutting speed, feed rate and difference cutting tools according to Taguchi method using a standard orthogonal array L9. The volume of AlN reinforced particle was 10% in MMC. The milling process was carried out under dry cutting condition using uncoated carbide, TiN and TiCN tool insert. The parameters used were the cutting speed of (230,300,370 m/min) the federate used were (0.4, 0.6, 0.8 mm/tooth) while the depth of cut is constant (0.3 mm). The tool diameter is 20mm. From the project, the surface roughness mechanism was investigated in detail using Mitutoyo portable surface roughness measurements surftest SJ-310. This machining will be fabricated on MMC with 150mm length, 100mm width and 30mm thick. The results showed using S/N ratio, concluded that a combination of low cutting speed, medium feed rate and uncoated insert give a remarkable surface finish. From the ANOVA result showed the feed rate was major contributing factor (43.76%) following type of insert (40.89%).

Keywords: MMC, milling operation and surface roughness, Taguchi method

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Authors: Tahir Mehmood, Mumtaz Akhter

Abstract:

The global need for conflict management is greater now in the early 21st century than ever before. According to UNESCO, half of the world’s 195 countries will have to expand their stock of educationist significantly, some by tens of thousands, if the goal development targets are desired to achieve. Socioeconomic inequities, political instability, demographic changes and crises such as the HIV/AIDs epidemic have engendered huge shortfalls in teacher supply and low teacher quality in many developing countries. Education serves as back bone in development process. Open learning and distance education programs are serving as pivotal part of development process. It is now clear that ‘bricks and mortar’ approaches to expanding teacher education may not be adequate if the current and projected shortfalls in teacher supply and low teacher quality are to be properly addressed. The study is designed to measure the perceptions of teaching learning community about conflict management with special reference to open and distance learning. It was descriptive study which targeted teachers, students, community members and experts. Data analysis was carried out by using statistical techniques served by SPSS. Findings reflected that audience perceives open and distance learning as change agent and as development tool. It is noticed that target audience has driven prominent performance by using facility of open and distance learning.

Keywords: conflict management, open and distance learning, teachers, students

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Authors: Ashish Kumar, Munesh Raghuraj Varma, Nisarg Joshi, Gujjula Vishwa Teja, Srikanth Sambi, Arpit Awasthi

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Autonomous driving vehicles are revolutionizing the transportation system of the 21st century. This has been possible due to intensive research put into making a robust, reliable, and intelligent program that can perceive and understand its environment and make decisions based on the understanding. It is a very data-intensive task with data coming from multiple sensors and the amount of data directly reflects on the performance of the system. Researchers have to design the preprocessing pipeline for different datasets with different sensor orientations and alignments before the dataset can be fed to the model. This paper proposes a solution that provides a method to unify all the data from different sources into a uniform format using the intrinsic and extrinsic parameters of the sensor used to capture the data allowing the same pipeline to use data from multiple sources at a time. This also means easy adoption of new datasets or In-house generated datasets. The solution also automates the complete deep learning pipeline from preprocessing to post-processing for various tasks allowing researchers to design multiple custom end-to-end pipelines. Thus, the solution takes care of the input and output data handling, saving the time and effort spent on it and allowing more time for model improvement.

Keywords: augmentation, autonomous driving, camera, custom end-to-end pipeline, data unification, lidar, post-processing, preprocessing

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Authors: Tabiti S. Tabiti, A. M. Jinadu, Daramola Japheth

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Urban insecurity is among the challenges militating against sustainable urban governance; in the first place it distorts the peace of urban areas making them unsafe. On the other hand it hinders the effective performance of urban functions. Urban security challenges manifest in different forms such as, street violence, theft and robbery, accidents of different types kidnapping, killings etc.. Efforts to address urban security challenges in Nigeria have been concentrated in legislative, law enforcement and the use of community vigilante groups. However in this study, the place of physical planning strategy through effective neighbourhood renewal as practiced in Mokola is presented as an effective complementary approach for addressing urban insecurity. On this backdrop, the paper recommends the need for gradual rehabilitation of urban slum neighborhoods by the state government in collaboration with World Bank and other development financiers. The local governments should be made autonomy in Nigeria so as to make them more responsible to the people. Other recommendations suggested in the paper include creating enabling environment that will promote economic empowerment and public enlightment on personal and community sanitation. It is certain that if these recommendations are adopted the challenge of urban insecurity will reduce significantly in Nigerian cities.

Keywords: neighbourhood renewal, pilot project, slum upgrading, urban security

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Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

Abstract:

Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

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Authors: Murray Olowa

Abstract:

This article examines the studies investigating the Mathematical Knowledge for Teaching (MKT) of secondary preservice teachers in Papua New Guinea based on probabilities. This research was conducted due to the continuous issues faced in the country in both primary and secondary education, like changes in curriculum, emphasis on mathematics and science education, and a decline in mathematics performance. Moreover, the mathematics curriculum doesn’t capture Pedagogical Content Knowledge (PCK) or Subject Matter Knowledge (SMK). The two main domains that have been identified are SMK and PCK, which have been further sub-divided into Common Content Knowledge (CCK), Specialised Content Knowledge (SCK) and Horizon Content Knowledge (HCK), and Knowledge of Content and Students (KCS), Knowledge of Content and Teaching (KCT) and Knowledge of Content and Curriculum (KCC), respectively. The data collected from 15-_year-_ ones and 15-_year-_fours conducted at St Peter Chanel Secondary Teachers College revealed that there is no significant difference in subject matter knowledge between year one and year four since the P-value of 0.22>0.05. However, it was revealed that year fours have higher pedagogical content knowledge than year one since P-value was 0.007<0.05. Finally, the research has proven that year fours have higher MKT than year one. This difference occurred due to final year preservice teachers’ hard work and engagement in mathematics curriculum and teaching practice.

Keywords: mathematical knowledge for teaching, subject matter knowledge, pedagogical content knowledge, Papua New Guinea, preservice teachers, probability

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Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

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In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

Procedia PDF Downloads 45