Search results for: hybrid inventory

Authors: Sidi Mohamed Mesli, Mohamed Habchi, Arslane Boudghene Stambouli, Rafik Benallal

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The BaMnMF7 (M=Fe,V, transition metal fluoride glass, assuming isomorphous replacement) have been structurally studied through the simultaneous simulation of their neutron diffraction patterns by reverse Monte Carlo (RMC) and by the Hybrid Reverse Monte Carlo (HRMC) analysis. This last is applied to remedy the problem of the artificial satellite peaks that appear in the partial pair distribution functions (PDFs) by the RMC simulation. The HRMC simulation is an extension of the RMC algorithm, which introduces an energy penalty term (potential) in acceptance criteria. The idea of this work is to apply the Buckingham potential at the title glass by ignoring the van der Waals terms, in order to make a fit of the partial pair distribution functions and give the most possible realistic features. When displaying the partial PDFs, we suggest that the Buckingham potential is useful to describe average correlations especially in similar interactions.

Keywords: fluoride glasses, RMC simulation, hybrid RMC simulation, Buckingham potential, partial pair distribution functions

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Authors: Kevin W. Zobrist, Patricia A. Townsend, Nora M. Haider

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Advanced Hardwood Biofuels Northwest (AHB) is a consortium funded by the United States Department of Agriculture (USDA) to research the potential for a system to produce advanced biofuels (jet fuel, diesel, and gasoline) from hybrid poplar in the Pacific Northwest region of the U.S. An Extension team was established as part of the project to examine community readiness and willingness to adopt hybrid as a purpose-grown bioenergy crop. The Extension team surveyed key stakeholder groups, including growers, Extension professionals, policy makers, and environmental groups, to examine attitudes and concerns about growing hybrid poplar for biofuels. The surveys found broad skepticism about the viability of such a system. The top concern for most stakeholder groups was economic viability and the availability of predictable markets. Growers had additional concerns stemming from negative past experience with hybrid poplar as an unprofitable endeavor for pulp and paper production. Additional barriers identified included overall land availability and the availability of water and water rights for irrigation in dry areas of the region. Since the beginning of the project, oil and natural gas prices have plummeted due to rapid increases in domestic production. This has exacerbated the problem with economic viability by making biofuels even less competitive than fossil fuels. However, the AHB project has identified intermediate market opportunities to use poplar as a renewable source for other biochemicals produced by petroleum refineries, such as acetic acid, ethyl acetate, ethanol, and ethylene. These chemicals can be produced at a lower cost with higher yields and higher, more-stable prices. Despite these promising market opportunities, the survey results suggest that it will still be challenging to induce growers to adopt hybrid poplar. Early adopters will be needed to establish an initial feedstock supply for a budding industry. Through demonstration sites and outreach events to various stakeholder groups, the project attracted interest from wastewater treatment facilities, since these facilities are already growing hybrid poplar plantations for applying biosolids and treated wastewater for further purification, clarification, and nutrient control through hybrid poplar’s phytoremediation capabilities. Since these facilities are already using hybrid poplar, selling the wood as feedstock for a biorefinery would be an added bonus rather than something requiring a high rate of return to compete with other crops and land uses. By holding regional workshops and conferences with wastewater professionals, AHB Extension has found strong interest from wastewater treatment operators. In conclusion, there are several significant barriers to developing a successful system for producing biofuels from hybrid poplar, with the largest barrier being economic viability. However, there is potential for wastewater treatment facilities to serve as early adopters for hybrid poplar production for intermediate biochemicals and eventually biofuels.

Keywords: hybrid poplar, biofuels, biochemicals, wastewater treatment

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Authors: Vishnu Goyal, Basant Agarwal

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Sentiment analysis research provides methods for identifying the people’s opinion written in blogs, reviews, social networking websites etc. Sentiment analysis is to understand what opinion people have about any given entity, object or thing. Sentiment analysis research can be broadly categorised into three types of approaches i.e. semantic orientation, machine learning and lexicon based approaches. Feature selection methods improve the performance of the machine learning algorithms by eliminating the irrelevant features. Information gain feature selection method has been considered best method for sentiment analysis; however, it has the drawback of selection of threshold. Therefore, in this paper, we propose a hybrid feature selection methods comprising of information gain and proposed feature selection method. Initially, features are selected using Information Gain (IG) and further more noisy features are eliminated using the proposed feature selection method. Experimental results show the efficiency of the proposed feature selection methods.

Keywords: feature selection, sentiment analysis, hybrid feature selection

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Authors: C. Manjula, Lilly Florence

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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.

Keywords: decision tree, genetic algorithm, machine learning, software defect prediction

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Authors: Teresa Caswell

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Throughout the United States and within a myriad of demographic contexts, students of color experience the results of systemic inequities as an academic outcome. These disparities continue despite the increased resources provided to students and ongoing instruction-focused professional learning received by teachers. The researcher postulated that lower levels of educator cultural competency are an underlying factor of why resource and instructional interventions are less effective than desired. Before implementing any type of intervention, however, cultural competency needed to be confirmed as a factor in schools demonstrating academic disparities between racial subgroups. A needs assessment was designed to measure levels of individual beliefs, including cultural competency, in both principals and teachers at three neighboring schools verified to have academic disparities. The resulting mixed method study utilized the Optimal Theory Applied to Identity Development (OTAID) model to measure cultural competency quantitatively, through self-identity inventory survey items, with teachers and qualitatively, through one-on-one interviews, with each school’s principal. A joint display was utilized to see combined data within and across school contexts. Each school was confirmed to have misalignments between principal and teacher levels of cultural competency beliefs while also indicating that a number of participants in the self-identity inventory survey may have intentionally skipped items referencing the term oppression. Additional use of the OTAID model and self-identity inventory in future research and across contexts is needed to determine transferability and dependability as cultural competency measures.

Keywords: cultural competency, identity development, mixed-method analysis, needs assessment

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Authors: Imran Ullah Imran

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Language contact is a familiar concept in the present global world. Across the globe, languages get mixed up at different levels. Borrowing, code-switching are some of the means through which languages interact. This study examines Pashto-English contact at word and syllable levels. By recording the speech of 30 Pashto native speakers, selected via 'social network' sampling, the study located a number of Pashto-English compound words, which is a unique contact of its kind. In data analysis, tokens were categorized on the basis of their pattern and morphological structure. The study shows that Pashto-English Bilingual Compound words (BCWs) are very prevalent in the Pashto language. The study also found that the BCWs in Pashto are completely productive and have their own meanings. It also shows that the dominant pattern of hybrid words in Pashto is the conjugation of an independent English root word followed by a Pashto inflectional morpheme, which contributes to the core semantic content of the construction. The BCWs construction shows that how both the languages are closer to each other. Pashto-English contact results into bilingual compound and hybrid words, which forms a considerable number of tokens in the present-day spoken Pashto. On the basis of these findings, the study assumes that the same phenomenon may increase with the passage of time that would, in turn, result in the formation of more bilingual compound or hybrid words.

Keywords: code-mixing, bilingual compound words, pashto-english contact, hybrid words, inflectional lexical morpheme

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Authors: Ahmadali Tahmasebimoradi, Chetra Mang, Xavier Lorang

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Thanks to the additive manufacturing process, lattice structures are replacing the traditional structures in aeronautical and automobile industries. In order to evaluate the mechanical response of the lattice structures, one has to resort to numerical techniques. Ansys is a globally well-known and trusted commercial software that allows us to model the lattice structures and analyze their mechanical responses using either solid or beam elements. In this software, a script may be used to systematically generate the lattice structures for any size. On the one hand, solid elements allow us to correctly model the contact between the substrates (the supports of the lattice structure) and the lattice structure, the local plasticity, and the junctions of the microbeams. However, their computational cost increases rapidly with the size of the lattice structure. On the other hand, although beam elements reduce the computational cost drastically, it doesn’t correctly model the contact between the lattice structures and the substrates nor the junctions of the microbeams. Also, the notion of local plasticity is not valid anymore. Moreover, the deformed shape of the lattice structure doesn’t correspond to the deformed shape of the lattice structure using 3D solid elements. In this work, motivated by the pros and cons of the 3D and beam models, a numerically hybrid model is presented for the lattice structures to reduce the computational cost of the simulations while avoiding the aforementioned drawbacks of the beam elements. This approach consists of the utilization of solid elements for the junctions and beam elements for the microbeams connecting the corresponding junctions to each other. When the global response of the structure is linear, the results from the hybrid models are in good agreement with the ones from the 3D models for body-centered cubic with z-struts (BCCZ) and body-centered cubic without z-struts (BCC) lattice structures. However, the hybrid models have difficulty to converge when the effect of large deformation and local plasticity are considerable in the BCCZ structures. Furthermore, the effect of the junction’s size of the hybrid models on the results is investigated. For BCCZ lattice structures, the results are not affected by the junction’s size. This is also valid for BCC lattice structures as long as the ratio of the junction’s size to the diameter of the microbeams is greater than 2. The hybrid model can take into account the geometric defects. As a demonstration, the point clouds of two lattice structures are parametrized in a platform called LATANA (LATtice ANAlysis) developed by IRT-SystemX. In this process, for each microbeam of the lattice structures, an ellipse is fitted to capture the effect of shape variation and roughness. Each ellipse is represented by three parameters; semi-major axis, semi-minor axis, and angle of rotation. Having the parameters of the ellipses, the lattice structures are constructed in Spaceclaim (ANSYS) using the geometrical hybrid approach. The results show a negligible discrepancy between the hybrid and 3D models, while the computational cost of the hybrid model is lower than the computational cost of the 3D model.

Keywords: additive manufacturing, Ansys, geometric defects, hybrid finite element model, lattice structure

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Authors: Golnush Masghati-Amoli, Paul Chin

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Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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Authors: Nazia Mustafa, Aneela Maqsood

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Pediatric Quality of Life Inventory is the most widely used instrument for assessing children and adolescent health-related quality of life and has shown excellent markers of reliability and validity. The current study was carried out with the objectives of translation and cross-language validation along with the determination of factor Structure and psychometric properties of the Urdu version. It was administered on 154 Primary School Children with age range 10 to12 years (M= 10.86, S.D = 0.62); including boys (n=92) and girls (n = 62). The sample was recruited from two randomly selected schools from the Rawalpindi district of Pakistan. Results of the pilot phase revealed that the instrument had good reliability (Urdu Version α = 0.798; English Version α = 0.795) as well as test-retest correlation coefficients over a period of 15 days (r = 0.85). Exploratory factor analysis (EFA) resulted in three factorial structures; Social/School Functioning (k = 8), Psychological Functioning (k = 7) and Physical Functioning (k = 6) considered suitable for our sample instead of four factors. Bartlett's test of sphericity showed inter-correlation between variables. However, factor loadings for items 22 and 23 of the School Functioning subscale were problematic. The model was fit to the data after their removal with Cronbach’s Alpha Reliability coefficient of the scale (k = 21) as 0.87 and for subscales as 0.75, 0.77 and 0.73 for Social/School Scale, Psychological subscale and Physical subscale, respectively. These results supported the feasibility and reliability of the Urdu version of the Pediatric Quality of Life Inventory as a reliable and effective tool for the measurement of quality of life among Pediatrics Pakistani population.

Keywords: primary school children, paediatric quality of life, exploratory factor analysis, Pakistan

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Authors: Hina Iqbal, Mustansar Ali Ghazanfar, Sandor Szedmak

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Recommender systems uses artificial intelligence practices for filtering obscure information and can predict if a user likes a specified item. Kernel mapping Recommender systems have been proposed which are accurate and state-of-the-art algorithms and resolve recommender system’s design objectives such as; long tail, cold-start, and sparsity. The aim of research is to propose hybrid framework that can efficiently integrate different versions— namely item-based and user-based KMR— of KMR algorithm. We have proposed various heuristic algorithms that integrate different versions of KMR (into a unified framework) resulting in improved accuracy and elimination of problems associated with conventional recommender system. We have tested our system on publically available movies dataset and benchmark with KMR. The results (in terms of accuracy, precision, recall, F1 measure and ROC metrics) reveal that the proposed algorithm is quite accurate especially under cold-start and sparse scenarios.

Keywords: Kernel Mapping Recommender Systems, hybrid recommender systems, cold start, sparsity, long tail

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Authors: Juan Portoviejo Brito, Daniel Icaza Alvarez, Christian Castro Samaniego

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In this article, we present the modeling, simulations, and energy conversion analysis of the solar-wind system for the Quingeo Heritage Center in Ecuador. A numerical model was constructed based on the 19 equations, it was coded in MATLAB R2017a, and the results were compared with the experimental data of the site. The model is built with the purpose of using it as a computer development for the optimization of resources and designs of hybrid systems in the Parish of Quingeo and its surroundings. The model obtained a fairly similar pattern compared to the data and curves obtained in the field experimentally and detailed in manuscript. It is important to indicate that this analysis has been carried out so that in the near future one or two of these power generation systems can be exploited in a massive way according to the budget assigned by the Parish GAD of Quingeo or other national or international organizations with the purpose of preserving this unique colonial helmet in Ecuador.

Keywords: hybrid system, wind turbine, modeling, simulation, Smart Grid, Quingeo Azuay Ecuador

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Authors: M. H. Yee, J. Md Yunos, W. Othman, R. Hassan, T. K. Tee, M. M. Mohamad

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The generation of an idea that goes through several phases is affected by individual factors, interests, preferences and motivation. The purpose of this research was to analyze the difference in difficulties of generating ideas according to individual learning styles. A total of 375 technical students from four technical universities in Malaysia were randomly selected as samples. The Kolb Learning Styles Inventory and a set of developed questionnaires were used in this research. The results showed that the most dominant learning style is among technical students is Doer. A total of 319 (85.1%) technical students faced difficulties in solving individual assignments. Most of the problem faced by technical students is the difficulty of generating ideas for solving individual assignments. There was no significant difference in difficulties of generating ideas according to students’ learning styles. Therefore, students need to learn higher order thinking skills enabling students to generate ideas and consequently complete assignments.

Keywords: difference, difficulties, generating idea, learning styles, Kolb Learning Styles Inventory

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Authors: Fasanmi Samuel Sunday

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This study investigated the influence of gender and personality traits on emotional distress among awaiting trial inmates in Nigeria. Participants were three hundred and twenty (320) awaiting trial inmates, drawn from three main correctional centres in Northeast Nigeria, namely: Gashua Correctional Centre, Postiskum Correctional Centre, and Bauchi Correctional Centre. Expo facto research design was adopted. Questionnaires such as the Big Five Inventory and the Perceived Emotional Distress Inventory (PEDI) were used to measure the variables of the study. Three hypotheses were tested. Logistic regression was used for data analysis. Results of the analysis indicated that conscientiousness significantly predicted emotional distress among awaiting trial inmates. However, most of the identified personality traits did not significantly predict emotional distress among awaiting trial inmates. There was no significant gender difference in emotional distress among awaiting-trial inmates. The implications of the study were discussed.

Keywords: personality traits, emotional distress, awaiting-trial inmates, gender

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Authors: Afifa Hafidh, Fathi Touati, Ahmed Hichem Hamzaoui, Sayda Somrani

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The objective of the present study has been to synthesize and to characterize silica hybrid materials using sol-gel technic and to investigate their properties. Silica materials were successfully fabricated using various bi-functional 1,3,4-thiadiazoles and tetraethoxysilane (TEOS) as co-precursors via a facile one-pot sol-gel pathway. TEOS was introduced at room temperature with 1,3,4-thiadiazole 2,5-difunctiunal adducts, in ethanol as solvent and using HCl acid as catalyst. The sol-gel process lead to the formation of monolithic, coloured and transparent gels. TEOS was used as a principal network forming agent. The incorporation of 1,3,4-thiadiazole molecules was realized by attachment of these later onto a silica matrix. This allowed covalent linkage between organic and inorganic phases and lead to the formation of Si-N and Si-S bonds. The prepared hybrid materials were characterized by Fourier transform infrared, NMR ²⁹Si and ¹³C, scanning electron microscopy and nitrogen absorption-desorption measurements. The optic and magnetic properties of hybrids are studied respectively by ultra violet-visible spectroscopy and electron paramagnetic resonance. It was shown in this work, that heterocyclic moieties were successfully attached in the hybrid skeleton. The formation of the Si-network composed of cyclic units (Q3 structures) connected by oxygen bridges (Q4 structures) was proved by ²⁹Si NMR spectroscopy. The Brunauer-Elmet-Teller nitrogen adsorption-desorption method shows that all the prepared xerogels have isotherms type IV and are mesoporous solids. The specific surface area and pore volume of these materials are important. The obtained results show that all materials are paramagnetic semiconductors. The data obtained by Nuclear magnetic resonance ²⁹Si and Fourier transform infrared spectroscopy, show that Si-OH and Si-NH groups existing in silica hybrids can participate in adsorption interactions. The obtained materials containing reactive centers could exhibit adsorption properties of metal ions due to the presence of OH and NH functionality in the mesoporous frame work. Our design of a simple method to prepare hybrid materials may give interest of the development of mesoporous hybrid systems and their use within the domain of environment in the future.

Keywords: hybrid materials, sol-gel process, 1, 3, 4-thiadaizole, TEOS

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Authors: Radesh Palakurthi

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The purpose of this study was to determine the impact of experiential learning on learning outcomes in hospitality education. This paper presents the results of an online survey of students from the U.S. studying abroad and their self-reported change in learning outcomes as assessed using the Core Competencies Model for the Hospitality Industry developed by Employment and Training Development Office of the U.S. Department of Labor. The impact of student learning styles on learning outcomes is also evaluated in this study. Kolb’s Learning Styles Inventory Model was used to assess students’ learning style. The results show that students reported significant improvements in their learning outcomes because of engaging in study abroad experiential learning programs. The learning styles of the students had significant effect on one of core learning outcomes- personal effectiveness.

Keywords: hospitality competencies, hospitality education, Kolb’s learning style inventory, learning outcomes, study abroad

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Authors: Bahattin Abay

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Thin film of polycyclic aromatic hydrocarbon rubrene, C₄₂H₂₈ (5,6,11,12-tetraphenyltetracene), has been surfaced on Moderately Doped (MD) n-InP substrate as an interfacial layer by means of spin coating technique for the electronic modification of Au/MD n-InP structure. Ex situ annealing has been carried out at 150 °C for three minutes under a brisk flow of nitrogen for the better adhesion of the deposited film with the substrate surface. Room temperature electrical characterization has been performed on the C₄₂H₂₈/MD n-InP hybrid junctions by current-voltage (I-V) and capacitance-voltage (C-V) measurement in the dark. It has been seen that the C₄₂H₂₈/MD n-InP structure demonstrated extraordinary rectifying behavior. An effective barrier height (BH) as high as 0.743 eV, along with an ideality factor very close to unity (n=1.203), has been achieved for C₄₂H₂₈/n-InP organic/inorganic device. A thin C₄₂H₂₈ interfacial layer between Au and MD n-InP also reduce the reverse leakage current by almost four orders of magnitude and enhance the BH about 0.278 eV. This good performance of the device is ascribed to the passivation effect of organic interfacial layer between Au and n-InP. By using C-V measurement, in addition, the value of BH of the C₄₂H₂₈/n-InP organic/inorganic hybrid junctions have been obtained as 0.796 eV. It has been seen that both of the BH value (0.743 and 0.796 eV) for the organic/inorganic hybrid junction obtained I-V and C-V measurement, respectively are significantly larger than that of the conventional Au/n-InP structure (0.465 and 0.503 eV). It was also seen that the device had good sensitivity to the light under 100 mW/cm² illumination conditions. The obtained results indicated that modification of the interfacial potential barrier for Metal/n-InP junctions might be attained using polycyclic aromatic hydrocarbon thin interlayer C₄₂H₂₈.

Keywords: I-V and C-V measurements, heterojunction, n-InP, rubrene, surface passivation

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Authors: Mary Ann Cristine R. Olgado

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Diversity in the classroom might make it difficult to promote individualized learning, but differentiated instruction that caters to students' various learning preferences may prove to be beneficial. Hence, this study examined the effectiveness of Hybrid-Differentiated Mathematics Instruction (HDMI) in improving the students’ academic performance in Mathematics. It employed the quasi-experimental research design by using a comparative analysis of the two variables: the experimental and control groups. The learning styles of the students were identified using the Grasha-Riechmann Student Learning Style Scale (GRSLSS), which served as the basis for designing differentiated action plans in Mathematics. In addition, adapted survey questionnaires, pre-tests, and post-tests were used to gather information and were analyzed using descriptive and correlational statistics to find the relationship between variables. The experimental group received differentiated instruction for a month, while the control group received traditional teaching instruction. The study found that Hybrid-Differentiated Mathematics Instruction (HDMI) improved the academic performance of Grade 11-TVL students, with the experimental group performing better than the control group. This program has effectively tailored the teaching methods to meet the diverse learning needs of the students, fostering and enhancing a deeper understanding of mathematical concepts in Statistics & Probability, both within and beyond the classroom.

Keywords: differentiated instruction, hybrid, learning styles, academic performance

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Authors: Abdullah M. Almeshal, Mohammad R. Alenezi, Talal H. Alzanki

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This paper presents a hybrid fuzzy logic control strategy for a unicycle trajectory following robot on irregular terrains. In literature, researchers have presented the design of path tracking controllers of mobile robots on non-frictional surface. In this work, the robot is simulated to drive on irregular terrains with contrasting frictional profiles of peat and rough gravel. A hybrid fuzzy logic controller is utilised to stabilise and drive the robot precisely with the predefined trajectory and overcome the frictional impact. The controller gains and scaling factors were optimised using spiral dynamics optimisation algorithm to minimise the mean square error of the linear and angular velocities of the unicycle robot. The robot was simulated on various frictional surfaces and terrains and the controller was able to stabilise the robot with a superior performance that is shown via simulation results.

Keywords: fuzzy logic control, mobile robot, trajectory tracking, spiral dynamic algorithm

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Authors: Usama Abdulwahab, Mohammed Wahab

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This paper presents the application of uncapacitated facility location problems (UFLP) and 1-median problems to support decision making in blood supply chain networks. A plethora of factors make blood supply-chain networks a complex, yet vital problem for the regional blood bank. These factors are rapidly increasing demand; criticality of the product; strict storage and handling requirements; and the vastness of the theater of operations. As in the UFLP, facilities can be opened at any of $m$ predefined locations with given fixed costs. Clients have to be allocated to the open facilities. In classical location models, the allocation cost is the distance between a client and an open facility. In this model, the costs are the allocation cost, transportation costs, and inventory costs. In order to address this problem the median algorithm is used to analyze inventory, evaluate supply chain status, monitor performance metrics at different levels of granularity, and detect potential problems and opportunities for improvement. The Euclidean distance data for some Ontario cities (demand nodes) are used to test the developed algorithm. Sitation software, lagrangian relaxation algorithm, and branch and bound heuristics are used to solve this model. Computational experiments confirm the efficiency of the proposed approach. Compared to the existing modeling and solution methods, the median algorithm approach not only provides a more general modeling framework but also leads to efficient solution times in general.

Keywords: approximate dynamic programming, facility location, perishable product, inventory model, blood platelet, P-median problem

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Authors: Adamu S. Salawu, Ibrahim O. Isah

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Direct solution to several forms of fourth-order ordinary differential equations is not easily obtained without first reducing them to a system of first-order equations. Thus, numerical methods are being developed with the underlying techniques in the literature, which seeks to approximate some classes of fourth-order initial value problems with admissible error bounds. Multistep methods present a great advantage of the ease of implementation but with a setback of several functions evaluation for every stage of implementation. However, hybrid methods conventionally show a slightly higher order of truncation for any k-step linear multistep method, with the possibility of obtaining solutions at off mesh points within the interval of solution. In the light of the foregoing, we propose the continuous form of a hybrid multistep method with Chebyshev polynomial as a basis function for the numerical integration of fourth-order initial value problems of ordinary differential equations. The basis function is interpolated and collocated at some points on the interval [0, 2] to yield a system of equations, which is solved to obtain the unknowns of the approximating polynomial. The continuous form obtained, its first and second derivatives are evaluated at carefully chosen points to obtain the proposed block method needed to directly approximate fourth-order initial value problems. The method is analyzed for convergence. Implementation of the method is done by conducting numerical experiments on some test problems. The outcome of the implementation of the method suggests that the method performs well on problems with oscillatory or trigonometric terms since the approximations at several points on the solution domain did not deviate too far from the theoretical solutions. The method also shows better performance compared with an existing hybrid method when implemented on a larger interval of solution.

Keywords: Chebyshev polynomial, collocation, hybrid multistep method, initial value problems, interpolation

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Authors: Oluwagbenga B. Fatile, Felix U. Idu, Olajide T. Sanya

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This paper reports the viability of developing Zn-27Al alloy matrix hybrid composites reinforced with alumina, graphite and fly ash (a solid waste byproduct of coal in thermal power plants). This research work was aimed at developing low cost-high performance Zn-27Al matrix composite with low density. Alumina particulates (Al2O3), graphite added with 0, 2, 3, 4, and 5 wt% fly ash were utilized to prepare 10wt% reinforcing phase with Zn-27Al alloy as matrix using two-step stir casting method. Density measurement estimated percentage porosity, tensile testing, micro hardness measurement, and optical microscopy were used to assess the performance of the composites produced. The results show that the hardness, ultimate tensile strength, and percent elongation of the hybrid composites decrease with increase in fly ash content. The maximum decrease in hardness and ultimate tensile strength of 13.72% and 15.25% respectively were observed for composite grade containing 5wt% fly ash. The percentage elongation of composite sample without fly ash is 8.9% which is comparable with that of the sample containing 2wt% fly ash with percentage elongation of 8.8%. The fracture toughness of the fly ash containing composites was, however, superior to those of composites without fly ash with 5wt% fly ash containing composite exhibiting the highest fracture toughness. The results show that fly ash can be utilized as complementary reinforcement in ZA-27 alloy matrix composite to reduce cost.

Keywords: fly ash, hybrid composite, mechanical behaviour, stir-cast

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Authors: Dinesh Pathaka, Tomas Wagnera, J. M. Nunzib

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We investigated blends of MdPVV.PCBM.AIS for photovoltaic application. AgInSe2 powder was synthesized by sealing and heating the stoichiometric constituents in evacuated quartz tube ampule. Fine grinded AIS powder was dispersed in MD-MOPVV and PCBM with and without surfactant. Different concentrations of these particles were suspended in the polymer solutions and spin casted onto ITO glass. Morphological studies have been performed by atomic force microscopy and optical microscopy. The blend layers were also investigated by various techniques like XRD, UV-VIS optical spectroscopy, AFM, PL, after a series of various optimizations with polymers/concentration/deposition/ suspension/surfactants etc. XRD investigation of blend layers shows clear evidence of AIS dispersion in polymers. Diode behavior and cell parameters also revealed it. Bulk heterojunction hybrid photovoltaic device Ag/MoO3/MdPVV.PCBM.AIS/ZnO/ITO was fabricated and tested with standard solar simulator and device characterization system. The best performance and photovoltaic parameters we obtained was an open-circuit voltage of about Voc 0.54 V and a photocurrent of Isc 117 micro A and an efficiency of 0.2 percent using a white light illumination intensity of 23 mW/cm2. Our results are encouraging for further research on the fourth generation inorganic organic hybrid bulk heterojunction photovoltaics for energy. More optimization with spinning rate/thickness/solvents/deposition rates for active layers etc. need to be explored for improved photovoltaic response of these bulk heterojunction devices.

Keywords: thin films, photovoltaic, hybrid systems, heterojunction

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Authors: S. Adhirai Subramaniyam, Paramjit Singh

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This paper presents major issues in cloud computing. The paper describes different cloud computing deployment models and cloud service models available in the field of cloud computing. The paper then concentrates on various issues in the field. The issues such as cloud compatibility, compliance of the cloud, standardizing cloud technology, monitoring while on the cloud and cloud security are described. The paper suggests solutions for these issues and concludes that hybrid cloud infrastructure is a real boon for organizations.

Keywords: cloud, cloud computing, mobile cloud computing, private cloud, public cloud, hybrid cloud, SAAS, PAAS, IAAS, cloud security

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Authors: Nitin Singh, Meng Ling, Talha Ahmed, Tianxia Zhao, Reinier van de Pol

Abstract:

We propose the use of reinforcement learning (RL) as a viable alternative for optimizing supply chain management, particularly in scenarios with stochasticity in product demands. RL’s adaptability to changing conditions and its demonstrated success in diverse fields of sequential decision-making makes it a promising candidate for addressing supply chain problems. We investigate the impact of demand fluctuations in a multi-product supply chain system and develop RL agents with learned generalizable policies. We provide experimentation details for training RL agents and statistical analysis of the results. We study the generalization ability of RL agents for different demand uncertainty scenarios and observe superior performance compared to the agents trained with fixed demand curves. The proposed methodology has the potential to lead to cost reduction and increased profit for companies dealing with frequent inventory movement between supply and demand nodes.

Keywords: inventory management, reinforcement learning, supply chain optimization, uncertainty

Procedia PDF Downloads 86

Authors: Morteza Rahbar Taramsari, Arya Mahdavi Baramchi, Mercedeh Enshaei, Ghazaleh Keshavarzi Baramchi

Abstract:

Introduction: Malingering is one of the most challenging issues in the forensic psychology and imposes a heavy financial burden on health care and legal systems. It seems that some mental and personality abnormalities might have a crucial role in developing this condition. Materials and Methods: In this cross-sectional study, we aimed to assess 100 malingering clients of Gilan province general office of forensic medicine, all filled the related questionnaires. The data about some psychometric characteristics were collected through the 71-items version- short form- of Minnesota Multiphasic Personality Inventory (MMPI) questionnaire and the personality traits were assessed by NEO Personality Inventory-Revised (NEO PI-R) - including 240 items- as a reliable and accurate measure of the five domains of personality. Results: The 100 malingering clients (55 males and 45 females) ranged from 23 to 45 (32+/- 5.6) years old. Regarding marital status, 36% were single, 57% were married and 7% were divorced. Almost two-thirds of the participants (64%) were unemployed, 21% were self-employed and the rest of them were employed. The data of MMPI clinical scales revealed that the mean (SD) T score of Hypochondrias (Hs) was 67(9.2), Depression (D) was 87(7.9), Hysteria (Hy) was 74(5.8), Psychopathic Deviate (Pd) was 62(8.5), Masculinity-Feminity (MF) was 76(8.4), Paranoia (Pa) was 62(4.5), Psychasthenia (Pt) was 80(7.9), Schizophrenia (Sc) was 69(6.8), Hypomania (Ma) was 64(5.9)and Social Introversion (Si) was 58(4.3). NEO PI-R test showed five domains of personality. The mean (SD) T score of Neuroticism was 65(9.2), Extraversion was 51(7.9), Openness was 43(5.8), Agreeableness was 35(3.4) and Conscientiousness was 42(4.9). Conclusion: According to MMPI test in our malingering clients, Hypochondriasis (Hs), depression (D), Hysteria (Hy), Muscularity-Feminity (MF), Psychasthenia (Pt) and Schizophrenia (Sc) had high scores (T >= 65) which means pathological range and psychological significance. Based on NEO PI-R test Neuroticism was in high range, on the other hand, Openness, Agreeableness, and Conscientiousness were in low range. Extroversion was in average range. So it seems that malingerers require basic evaluations of different psychological fields. Additional research in this area is needed to provide stronger evidence of the possible positive effects of the mentioned factors on malingering.

Keywords: malingerers, mental profile, MMPI, NEO PI-R, personality profile

Procedia PDF Downloads 235

Authors: S. Koul, Joshua Adedamola

Abstract:

Currently, the global concerning fact about electromagnetic pollution (EMP) is that it not only adversely affects human health but rather projects the malfunctioning of sensitive equipment both locally and at a global level. The market offers many incumbent technologies to solve the issues, but still, a processable sustainable material solution with acceptable limits for GHG emission is still at an exploratory stage. The present work offers a sustainable material solution with a wide range of processability in terms of a polymeric resin matrix and shielding operational efficiency across the electromagnetic spectrum, covering both ionizing and non-ionizing electromagnetic radiations. The present work offers an in-situ synthesized conducting polyaniline (PANI) in the presence of the hybrid dual dopant system with tuned conductivity and high shielding efficiency between 89 to 92 decibels, depending upon the EMI frequency range. The conductive polymer synthesized in the presence of a hybrid dual dopant system via the in-situ emulsion polymerization method offers a higher surface resistance of 1.0 ohms/cm with thermal stability up to 2450C in their powder form. This conductive polymer with a hybrid dual dopant system was used as a filler material with different polymeric thermoplastic resin systems for the preparation of conductive composites. Intrinsically Conductive polymeric (ICP) composites based on hybrid dual dopant systems were prepared using melt blending, extrusion, and finally by, compression molding processing techniques. ICP composites with hybrid dual dopant systems offered good mechanical, thermal, structural, weathering, and stable surface resistivity properties over a period of time. The preliminary shielding behavior for ICP composites between frequency levels of 10 GHz to 24GHZ offered a shielding efficiency of more than 90 dB.

Keywords: ICP, dopant, EMI, shielding

Procedia PDF Downloads 62

Authors: Majid Vafaeipour, Mohamed El Baghdadi, Florian Verbelen, Peter Sergeant, Joeri Van Mierlo, Kurt Stockman, Omar Hegazy

Abstract:

The Electrical Variable Transmission (EVT), an electromechanical device, can be considered as an alternative solution to the conventional transmission system utilized in Hybrid Electric Vehicles (HEVs). This study present comparisons in terms of fuel consumption, power split, and state of charge (SoC) of an HEV containing an EVT to a conventional parallel topology and a series topology. To this end, corresponding simulations of these topologies are all performed in presence of control strategies enabling battery charge-sustaining and efficient power split. The power flow through the components of the vehicle are attained, and fuel consumption results of the considered cases are compared. The investigation of the results indicates utilizing EVT can provide significant added values in HEV configurations. The outcome of the current research paves its path for implementation of design optimization approaches on such systems in further research directions.

Keywords: Electrical Variable Transmission (EVT), Hybrid Electric Vehicle (HEV), parallel, series, modeling

Procedia PDF Downloads 218

Authors: Jamil Hijazi, Stirling Howieson

Abstract:

Reducing energy consumption and CO₂ emissions are probably the greatest challenge now facing mankind. From considerations surrounding global warming and CO₂ production, it has to be recognized that oil is a finite resource and the KSA like many other oil-rich countries will have to start to consider a horizon where hydro-carbons are not the dominant energy resource. The employment of hybrid ground-cooling pipes in combination with the black body solar collection and radiant night cooling systems may have the potential to displace a significant proportion of oil currently used to run conventional air conditioning plant. This paper presents an investigation into the viability of such hybrid systems with the specific aim of reducing cooling load and carbon emissions while providing all year-round thermal comfort in a typical Saudi Arabian urban housing block. Soil temperatures were measured in the city of Jeddah. A parametric study then was carried out by computational simulation software (DesignBuilder) that utilized the field measurements and predicted the cooling energy consumption of both a base case and an ideal scenario (typical block retro-fitted with insulation, solar shading, ground pipes integrated with hypocaust floor slabs/stack ventilation and radiant cooling pipes embed in floor). Initial simulation results suggest that careful ‘ecological design’ combined with hybrid radiant and ground pipe cooling techniques can displace air conditioning systems, producing significant cost and carbon savings (both capital and running) without appreciable deprivation of amenity.

Keywords: cooling load, energy efficiency, ground pipe cooling, hybrid cooling strategy, hydronic radiant systems, low carbon emission, passive designs, thermal comfort

Procedia PDF Downloads 213

Authors: Azzedine Hamza, Chouaib Chakour, Messaoud Ramdani

Abstract:

Energy demand prediction plays a crucial role in achieving next-generation power systems for agricultural greenhouses. As a result, high prediction quality is required for efficient smart grid management and therefore low-cost energy consumption. The aim of this paper is to investigate the effectiveness of a hybrid data-driven model in day-ahead energy demand prediction. The proposed model consists of Discrete Wavelet Transform (DWT), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The DWT is employed to decompose the original signal in a set of subseries and then an ANFIS is used to generate the forecast for each subseries. The proposed hybrid method (DWT-ANFIS) was evaluated using a greenhouse energy demand data for a week and compared with ANFIS. The performances of the different models were evaluated by comparing the corresponding values of Mean Absolute Percentage Error (MAPE). It was demonstrated that discret wavelet transform can improve agricultural greenhouse energy demand modeling.

Keywords: wavelet transform, ANFIS, energy consumption prediction, greenhouse

Procedia PDF Downloads 64

Authors: Jinkoo Kim, Hyungoo Kang, Hyungjun Shin

Abstract:

In this study, a hybrid energy dissipation device is developed by combining a steel slit plate and friction pads to be used for seismic retrofit of structures, and its effectiveness is investigated by comparing the life cycle costs of the structure before and after the retrofit. The seismic energy dissipation capability of the dampers is confirmed by cyclic loading tests. The probabilities of reaching various damage states are obtained by fragility analysis, and the life cycle costs of the model structures are computed using the PACT (Performance Assessment Calculation Tool) program based on FEMA P-58 methodology. The fragility analysis shows that the probabilities of reaching limit states are minimized by the seismic retrofit with hybrid dampers and increasing column size. The seismic retrofit with increasing column size and hybrid dampers results in the lowest repair cost and shortest repair time.

Keywords: slit dampers, friction dampers, seismic retrofit, life cycle cost, FEMA P-58, PACT

Procedia PDF Downloads 307