Search results for: Power Transfer Applications.

Authors: Maryam Vafadar, Alireza Behrad, Saeed Akbari

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Nowadays, with the emerging of the new applications like robot control in image processing, artificial vision for visual servoing is a rapidly growing discipline and Human-machine interaction plays a significant role for controlling the robot. This paper presents a new algorithm based on spatio-temporal volumes for visual servoing aims to control robots. In this algorithm, after applying necessary pre-processing on video frames, a spatio-temporal volume is constructed for each gesture and feature vector is extracted. These volumes are then analyzed for matching in two consecutive stages. For hand gesture recognition and classification we tested different classifiers including k-Nearest neighbor, learning vector quantization and back propagation neural networks. We tested the proposed algorithm with the collected data set and results showed the correct gesture recognition rate of 99.58 percent. We also tested the algorithm with noisy images and algorithm showed the correct recognition rate of 97.92 percent in noisy images.

Keywords: Back propagation neural network, Feature vector, Hand gesture recognition, k-Nearest Neighbor, Learning vector quantization neural network, Robot control, Spatio-temporal volume, Visual servoing

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Authors: Shaila Ahmed, Raghu Prasad Rao Metpally, Sreedhara Sangadala, Boojala Vijay B Reddy

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Bone growth factors, such as Bone Morphogenic Protein-2 (BMP-2) have been approved by the FDA to replace grafting for some surgical interventions, but the high dose requirement limits its use in patients. Noggin, an extracellular protein, blocks the effect of BMP-2 by binding to BMP. Preventing the BMP-2/noggin interaction will help increase the free concentration of BMP-2 and therefore should enhance its efficacy to induce bone formation. The work presented here involves computational design of novel small molecule inhibitory agents of BMP-2/noggin interaction, based on our current understanding of BMP-2, and its known putative ligands (receptors and antagonists). A successful acquisition of such an inhibitory agent of BMP-2/noggin interaction would allow clinicians to reduce the dose required of BMP-2 protein in clinical applications to promote osteogenesis. The available crystal structures of the BMPs, its receptors, and the binding partner noggin were analyzed to identify the critical residues involved in their interaction. In presenting this study, LUDI de novo design method was utilized to perform virtual screening of a large number of compounds from a commercially available library against the binding sites of noggin to identify the lead chemical compounds that could potentially block BMP-noggin interaction with a high specificity.

Keywords: Transforming growth factor-beta, Bone morphogenic proteins, Noggin, LUDI de novo design method, CAP small molecules.

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Authors: A. Aravind, M. Vetrivel, P. Abhimanyu, C. A. Akaash Emmanuel Raj, K. Sundararaj, V. R. S. Kumar

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The choice of high-speed, low budget hatchback car with diversified options is increasing for meeting the new generation buyers trend. This paper is aimed to augment the current speed of the hatchback cars through the aerodynamic drag reduction technique. The inverted airfoils are facilitated at the bottom of the car for generating the downward force for negating the lift while increasing the current speed range for achieving a better road performance. The numerical simulations have been carried out using a 2D steady pressure-based    k-ɛ realizable model with enhanced wall treatment. In our numerical studies, Reynolds-averaged Navier-Stokes model and its code of solution are used. The code is calibrated and validated using the exact solution of the 2D boundary layer displacement thickness at the Sanal flow choking condition for adiabatic flows. We observed through the parametric analytical studies that the inverted airfoil integrated with the bottom surface at various predesigned locations of Hatchback cars can improve its overall aerodynamic efficiency through drag reduction, which obviously decreases the fuel consumption significantly and ensure an optimum road performance lucratively with maximum permissible speed within the framework of the manufactures constraints.

Keywords: Aerodynamics of commercial cars, downward force, hatchback car, inverted airfoil.

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Authors: A. Majeed, P. Ali

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Before designing an electrical system, the estimation of load is necessary for unit sizing and demand-generation balancing. The system could be a stand-alone system for a village or grid connected or integrated renewable energy to grid connection, especially as there are non–electrified villages in developing countries. In the classical model, the energy demand was found by estimating the household appliances multiplied with the amount of their rating and the duration of their operation, but in this paper, information exists for electrified villages could be used to predict the demand, as villages almost have the same life style. This paper describes a method used to predict the average energy consumed in each two months for every consumer living in a village by Artificial Neural Network (ANN). The input data are collected using a regional survey for samples of consumers representing typical types of different living, household appliances and energy consumption by a list of information, and the output data are collected from administration office of Piramagrun for each corresponding consumer. The result of this study shows that the average demand for different consumers from four villages in different months throughout the year is approximately 12 kWh/day, this model estimates the average demand/day for every consumer with a mean absolute percent error of 11.8%, and MathWorks software package MATLAB version 7.6.0 that contains and facilitate Neural Network Toolbox was used.

Keywords: Artificial neural network, load estimation, regional survey, rural electrification.

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Authors: Fernanda T. Orsati, Julie Causton

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Discursive practices enacted by educators in kindergarten create a blueprint for how the educational trajectories of students with disabilities are constructed. This two-year ethnographic case study critically examines educators’ relationships with students considered to present challenging behaviors in one kindergarten classroom located in a predominantly White middle class school district in the Northeast of the United States. Focusing on the language and practices used by one special education teacher and three teaching assistants, this paper analyzes how teacher responses to students’ behaviors constructs and positions students over one year of kindergarten education. Using a critical discourse analysis it shows that educators understand students’ behaviors as deficit and needing consequences. This study highlights how educators’ responses reflect students' individual characteristics including family background, socioeconomics and ability status. This paper offers in depth analysis of two students’ stories, which evidenced that the language used by educators amplifies the social positioning of students within the classroom and creates a foundation for who they are constructed to be. Through exploring routine language and practices, this paper demonstrates that educators outlined a blueprint of kindergartners, which positioned students as learners in ways that became the ground for either a limited or a promising educational pathway for them.

Keywords: Behavior, early education, special education, critical discourse analysis.

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Authors: Abhimanyu Pati, Krishna Kumar Veluri

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The paper intends to bring out a real life experience encountered during actual implementation of a large scale Tier-1 Enterprise Resource Planning (ERP) system in a multi-location, discrete manufacturing organization in India, involved in manufacturing of auto components and aggregates. The business complexities, prior to the implementation of ERP, include multi-product with hierarchical product structures, geographically distributed multiple plant locations with disparate business practices, lack of inter-plant broadband connectivity, existence of disparate legacy applications for different business functions, and non-standardized codifications of products, machines, employees, and accounts apart from others. On the other hand, the manufacturing environment consisted of processes like Assemble-to-Order (ATO), Make-to-Stock (MTS), and Engineer-to-Order (ETO) with a mix of discrete and process operations. The paper has highlighted various business plan areas and concerns, prior to the implementation, with specific focus on strategic issues and objectives. Subsequently, it has dealt with the complete process of ERP implementation, starting from strategic planning, project planning, resource mobilization, and finally, the program execution. The step-by-step process provides a very good learning opportunity about the implementation methodology. At the end, various organizational challenges and lessons emerged, which will act as guidelines and checklist for organizations to successfully align and implement ERP and achieve their business objectives.

Keywords: ERP, ATO, MTS, ETO, discrete manufacturing, strategic planning.

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Authors: Emre Kara, Metehan Demir, Şura Karakuzu, Kadir Koç, Ahmet F. Geylan, Halil Aykul

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While the polymeric foam cored sandwiches have been realized for many years, recently there is a growing and outstanding interest on the use of sandwiches consisting of aluminum foam core because of their some of the distinct mechanical properties such as high bending stiffness, high load carrying and energy absorption capacities. These properties make them very useful in the transportation industry (automotive, aerospace, shipbuilding industry), where the "lightweight design" philosophy and the safety of vehicles are very important aspects. Therefore, in this study, the sandwich panels with aluminum alloy foam core and various types and thicknesses of glass fiber reinforced polymer (GFRP) skins produced via Vacuum Assisted Resin Transfer Molding (VARTM) technique were obtained by using a commercial toughened epoxy based adhesive with two components. The aim of this contribution was the analysis of the bending response of sandwiches with various glass fiber reinforced polymer skins. The three point bending tests were performed on sandwich panels at different values of support span distance using a universal static testing machine in order to clarify the effects of the type and thickness of the GFRP skins in terms of peak load, energy efficiency and absorbed energy values. The GFRP skins were easily bonded to the aluminum alloy foam core under press machine with a very low pressure. The main results of the bending tests are: force-displacement curves, peak force values, absorbed energy, collapse mechanisms and the influence of the support span length and GFRP skins. The obtained results of the experimental investigation presented that the sandwich with the skin made of thicker S-Glass fabric failed at the highest load and absorbed the highest amount of energy compared to the other sandwich specimens. The increment of the support span distance made the decrease of the peak force and absorbed energy values for each type of panels. The common collapse mechanism of the panels was obtained as core shear failure which was not affected by the skin materials and the support span distance.

Keywords: Aluminum foam, collapse mechanisms, light-weight structures, transport application

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Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

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Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD, as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches, such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: Autism spectrum disorder, clustering, optimization, unsupervised machine learning.

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Authors: Maziar Ahmad Sharbafi, Caro Lucas, Abolfazel Toroghi Haghighat, Omid AmirGhiasvand, Omid Aghazade

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RoboCup Rescue simulation as a large-scale Multi agent system (MAS) is one of the challenging environments for keeping coordination between agents to achieve the objectives despite sensing and communication limitations. The dynamicity of the environment and intensive dependency between actions of different kinds of agents make the problem more complex. This point encouraged us to use learning-based methods to adapt our decision making to different situations. Our approach is utilizing reinforcement leaning. Using learning in rescue simulation is one of the current ways which has been the subject of several researches in recent years. In this paper we present an innovative learning method implemented for Police Force (PF) Agent. This method can cope with the main difficulties that exist in other learning approaches. Different methods used in the literature have been examined. Their drawbacks and possible improvements have led us to the method proposed in this paper which is fast and accurate. The Brain Emotional Learning Based Intelligent Controller (BELBIC) is our solution for learning in this environment. BELBIC is a physiologically motivated approach based on a computational model of amygdale and limbic system. The paper presents the results obtained by the proposed approach, showing the power of BELBIC as a decision making tool in complex and dynamic situation.

Keywords: Emotional learning, rescue, simulation environment, RoboCup, multi-agent system.

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Authors: Rodolfo Lorbieski, Silvia Modesto Nassar

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Many supervised machine learning tasks require decision making across numerous different classes. Multi-class classification has several applications, such as face recognition, text recognition and medical diagnostics. The objective of this article is to analyze an adapted method of Stacking in multi-class problems, which combines ensembles within the ensemble itself. For this purpose, a training similar to Stacking was used, but with three levels, where the final decision-maker (level 2) performs its training by combining outputs from the tree-based pair of meta-classifiers (level 1) from Bayesian families. These are in turn trained by pairs of base classifiers (level 0) of the same family. This strategy seeks to promote diversity among the ensembles forming the meta-classifier level 2. Three performance measures were used: (1) accuracy, (2) area under the ROC curve, and (3) time for three factors: (a) datasets, (b) experiments and (c) levels. To compare the factors, ANOVA three-way test was executed for each performance measure, considering 5 datasets by 25 experiments by 3 levels. A triple interaction between factors was observed only in time. The accuracy and area under the ROC curve presented similar results, showing a double interaction between level and experiment, as well as for the dataset factor. It was concluded that level 2 had an average performance above the other levels and that the proposed method is especially efficient for multi-class problems when compared to binary problems.

Keywords: Stacking, multi-layers, ensemble, multi-class.

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Authors: Chethana K., Guru Prasad A. S., Vikranth H. N., Varun H., Omkar S. N., Asokan S.

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This paper describes a novel application of Fiber Braggs Grating (FBG) sensors in the assessment of human postural stability and balance on an unstable platform. In this work, FBG sensor Stability Analyzing Device (FBGSAD) is developed for measurement of plantar strain to assess the postural stability of subjects on unstable platforms during different stances in eyes open and eyes closed conditions on a rocker board. The studies are validated by comparing the Centre of Gravity (CG) variations measured on the lumbar vertebra of subjects using a commercial accelerometer. The results obtained from the developed FBGSAD depict qualitative similarities with the data recorded by commercial accelerometer. The advantage of the FBGSAD is that it measures simultaneously plantar strain distribution and postural stability of the subject along with its inherent benefits like non-requirement of energizing voltage to the sensor, electromagnetic immunity and simple design which suits its applicability in biomechanical applications. The developed FBGSAD can serve as a tool/yardstick to mitigate space motion sickness, identify individuals who are susceptible to falls and to qualify subjects for balance and stability, which are important factors in the selection of certain unique professionals such as aircraft pilots, astronauts, cosmonauts etc.

Keywords: Biomechanics, Fiber Bragg Gratings, Plantar Strain Measurement, Postural Stability Analysis.

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Authors: Mohd. Noor Md. Sap, A. Majid Awan

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Intelligent systems based on machine learning techniques, such as classification, clustering, are gaining wide spread popularity in real world applications. This paper presents work on developing a software system for predicting crop yield, for example oil-palm yield, from climate and plantation data. At the core of our system is a method for unsupervised partitioning of data for finding spatio-temporal patterns in climate data using kernel methods which offer strength to deal with complex data. This work gets inspiration from the notion that a non-linear data transformation into some high dimensional feature space increases the possibility of linear separability of the patterns in the transformed space. Therefore, it simplifies exploration of the associated structure in the data. Kernel methods implicitly perform a non-linear mapping of the input data into a high dimensional feature space by replacing the inner products with an appropriate positive definite function. In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering the data. The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting the yield.

Keywords: Pattern analysis, clustering, kernel methods, spatial data, crop yield

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Authors: Kari Björn, Mikael Soini

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Higher Education system reforms, especially Finnish system of Universities of Applied Sciences in 2014 are discussed. The new steering model is based on major legislative changes, output-oriented funding and open information. The governmental steering reform, especially the financial model and the resulting institutional level responses, such as a curriculum reforms are discussed, focusing especially in engineering programs. The paper is motivated by management need to establish objective steering-related performance indicators and to apply them consistently across all educational programs. The close relationship to governmental steering and funding model imply that internally derived indicators can be directly applied. Metropolia University of Applied Sciences (MUAS) as a case institution is briefly introduced, focusing on engineering education in Information and Communications Technology (ICT), and its related programs. The reform forced consolidation of previously separate smaller programs into fewer units of student application. New curriculum ICT students have a common first year before they apply for a Major. A framework of parallel and longitudinal comparisons is introduced and used across Majors in two campuses. The new externally introduced performance criteria are applied internally on ICT Majors using data ex-ante and ex-post of program merger.  A comparative performance of the Majors after completion of joint first year is established, focusing on previously omitted Majors for completeness of analysis. Some new research questions resulting from transfer of Majors between campuses and quota setting are discussed. Practical orientation identifies best practices to share or targets needing most attention for improvement. This level of analysis is directly applicable at student group and teaching team level, where corrective actions are possible, when identified. The analysis is quantitative and the nature of the corrective actions are not discussed. Causal relationships and factor analysis are omitted, because campuses, their staff and various pedagogical implementation details contain still too many undetermined factors for our limited data. Such qualitative analysis is left for further research. Further study must, however, be guided by the relevance of the observations.

Keywords: Engineering education, integrated curriculum, learning outcomes, performance measurement.

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Authors: W. T. A. Mohammed, M. Eltaeb, R. Kashani

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The first bending modes of tall asymmetric structures in the two lateral X and Y-directions have two different natural frequencies. To add tuned damping to these bending modes, one needs to either a) use two pendulum-tuned mass dampers (PTMDs) with one tuning frequency, each PTMD targeting one of the bending modes, or b) use one PTMD with two tuning frequencies (one in each lateral directions). Option (a), being more massive, requiring more space, and being more expensive, is less attractive than option (b). Considering that the tuning frequency of a pendulum depends mainly on the pendulum length, one way of realizing option (b) is by constraining the swinging length of the pendulum in one direction but not in the other; such PTMD is dubbed passive Bi-PTMD. Alternatively, option (b) can be realized by actively setting the tuning frequencies of the PTMD in the two directions. In this work, accurate physical models of passive Bi-PTMD and active PTMD are developed and incorporated into the numerical model of a tall asymmetric structure. The model of PTMDs plus structure is used for a) synthesizing such PTMDs for particular applications and b) evaluating their damping effectiveness in mitigating the dynamic lateral responses of their target asymmetric structures, perturbed by wind load in X and Y-directions. Depending on how elaborate the control scheme is, the active PTMD can either be made to yield the same damping effectiveness as the passive Bi-PTMD of the same size or the passive Bi-TMD twice as massive as the active PTMD.

Keywords: Active tuned mass damper, high-rise building, multi-frequency tuning, vibration control.

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Authors: Asma Perveen, M. P. Jahan

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Ni alloys have managed to cover wide range of applications such as automotive industries, oil gas industries, and aerospace industries. However, these alloys impose challenges while using conventional machining technologies. On the other hand, Micro-Electro-Discharge machining (micro-EDM) is a non-conventional machining method that uses controlled sparks energy to remove material irrespective of the materials hardness. There has been always a huge interest from the industries for developing optimum methodology and parameters in order to enhance the productivity of micro-EDM in terms of reducing machining time and tool wear for different alloys. Therefore, the aims of this study are to investigate the effects of the micro-EDM process parameters, in order to find their optimal values. The input process parameters include voltage, capacitance, and electrode rotational speed, whereas the output parameters considered are machining time, entrance diameter of hole, overcut, tool wear, and crater size. The surface morphology and element characterization are also investigated with the use of SEM and EDX analysis. The experimental result indicates the reduction of machining time with the increment of discharge energy. Discharge energy also contributes to the enlargement of entrance diameter as well as overcut. In addition, tool wears show reduction with the increase of discharge energy. Moreover, crater size is found to be increased in size along with the increment of discharge energy.

Keywords: Micro EDM, Ni alloy, discharge energy, micro-holes.

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Authors: Jenny Paola Forero Pachón, Sonia Cristina Gamboa Sarmiento, Luis Carlos Gómez Flórez

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The Colombian government has defined an e-government strategy to take advantage of Information Technologies (IT) in order to contribute to the building of a more efficient, transparent and participative State that provides better services to citizens and businesses. In this regard, the Justice sector is one of the government sectors where IT has generated more expectation considering that the country has a judicial processes backlog. This situation has led to the search for alternative forms of access to justice that speed up the process while providing a low cost for citizens. To this end, the Colombian government has authorized the use of Alternative Dispute Resolution methods (ADR), a remedy where disputes can be resolved more quickly compared to judicial processes while facilitating greater communication between the parties, without recourse to judicial authority. One of these methods is conciliation, which includes a special modality that takes advantage of IT for the development of itself known as virtual conciliation. With this option the conciliation is supported by information systems, applications or platforms and communications are provided through it. This paper evaluates the level of maturity in how the service of virtual conciliation is under the framework of this strategy. This evaluation is carried out considering Shahkooh's 5-phase model for e-government. As a result, it is evident that in the context of conciliation, maturity does not reach the necessary level in the model so that it can be considered as virtual conciliation; therefore, it is necessary to define strategies to maximize the potential of IT in this context.

Keywords: Alternative dispute resolution, e-government, evaluation of maturity, Shahkooh model, virtual conciliation.

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Authors: Zheni S. Stefanova, Kandethody M. Ramachandran

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With the increasing dependency on our computer devices, we face the necessity of adequate, efficient and effective mechanisms, for protecting our network. There are two main problems that Intrusion Detection Systems (IDS) attempt to solve. 1) To detect the attack, by analyzing the incoming traffic and inspect the network (intrusion detection). 2) To produce a prompt response when the attack occurs (intrusion prevention). It is critical creating an Intrusion detection model that will detect a breach in the system on time and also challenging making it provide an automatic and with an acceptable delay response at every single stage of the monitoring process. We cannot afford to adopt security measures with a high exploiting computational power, and we are not able to accept a mechanism that will react with a delay. In this paper, we will propose an intrusion response mechanism that is based on artificial intelligence, and more precisely, reinforcement learning techniques (RLT). The RLT will help us to create a decision agent, who will control the process of interacting with the undetermined environment. The goal is to find an optimal policy, which will represent the intrusion response, therefore, to solve the Reinforcement learning problem, using a Q-learning approach. Our agent will produce an optimal immediate response, in the process of evaluating the network traffic.This Q-learning approach will establish the balance between exploration and exploitation and provide a unique, self-learning and strategic artificial intelligence response mechanism for IDS.

Keywords: Intrusion prevention, network security, optimal policy, Q-learning.

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Authors: L. Almulla

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Native plants are better adapted to the local environment providing a more natural effect on landscape projects; their use will both conserve natural resources and produce sustainable greenery. Continuation of evaluation of additional native plants is essential to increase diversity of plant resources for greenery projects. Therefore, in this project an effort was made to study the mass multiplication of further native plants for greenery applications. Standardization of vegetative propagation methods is essential for conservation and sustainable utilization of native plants in restoration projects. Moreover, these simple propagation methods can be readily adapted by the local nursery sector in Kuwait. In the present study, various treatments were used to mass multiply selected plants using vegetative parts to secure maximum rooting and initial growth. Soft or semi-hardwood cuttings of selected native plants were collected from mother plants and subjected to different treatments. Pennisetum divisum can be vegetatively propagated by cuttings/off-shoots. However, Tamarix aucheriana showed maximum number of rooted cuttings and stronger vigor seedlings with the lowest growth hormone concentration. Standardizing the propagation techniques for the native plant species will add to the rehabilitation and landscape revegetation projects in Kuwait.

Keywords: Kuwait desert, landscape, rooting percentage vegetative propagation.

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Authors: Rui Magalhães, Sohel Rana, Raul Fangueiro, Clara Gonçalves, Pedro Nunes, Gustavo Dias

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Auxetic fibrous structures and composites with negative Poisson’s ratio (NPR) have huge potential for application in ballistic protection due to their high energy absorption and excellent impact resistance. In the present research, re-entrant lozenge auxetic fibrous structures were produced through weft knitting technology using high performance polyamide and para-aramid fibres. Fabric structural parameters (e.g. loop length) and machine parameters (e.g. take down load) were varied in order to investigate their influence on the auxetic behaviours of the produced structures. These auxetic structures were then impregnated with two types of polymeric resins (epoxy and polyester) to produce composite materials, which were subsequently characterized for the auxetic behaviour. It was observed that the knitted fabrics produced using the polyamide yarns exhibited NPR over a wide deformation range, which was strongly dependant on the loop length and take down load. The polymeric composites produced from the auxetic fabrics also showed good auxetic property, which was superior in case of the polyester matrix. The experimental results suggested that these composites made from the auxetic fibrous structures can be properly designed to find potential use in the body amours for personal protection applications.

Keywords: Auxetic fabrics, high performance, composites, impact resistance, energy absorption.

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Authors: H. Ozbasaran

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Lateral torsional buckling is a global buckling mode which should be considered in design of slender structural members under flexure about their strong axis. It is possible to compute the load which causes lateral torsional buckling of a beam by finite element analysis, however, closed form equations are needed in engineering practice for calculation ease which can be obtained by using energy method. In lateral torsional buckling applications of energy method, a proper function for the critical lateral torsional buckling mode should be chosen which can be thought as the variation of twisting angle along the buckled beam. Accuracy of the results depends on how close is the chosen function to the exact mode. Since critical lateral torsional buckling mode of the cantilever I-beams varies due to material properties, section properties and loading case, the hardest step is to determine a proper mode function in application of energy method. This paper presents an approximate function for critical lateral torsional buckling mode of doubly symmetric cantilever I-beams. Coefficient matrices are calculated for concentrated load at free end, uniformly distributed load and constant moment along the beam cases. Critical lateral torsional buckling modes obtained by presented function and exact solutions are compared. It is found that the modes obtained by presented function coincide with differential equation solutions for considered loading cases.

Keywords: Buckling mode, cantilever, lateral-torsional buckling, I-beam.

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Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

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Artificial Intelligence (AI), specifically Reinforcement Learning (RL), has proven helpful in many control path planning technologies by maximizing and enhancing their performance, such as navigation systems. Since it learns from experience by interacting with the environment to determine the optimal policy, the optimal policy takes the best action in a particular state, accounting for the long-term rewards. Most navigation systems focus primarily on "arriving faster," overlooking safety and efficiency while estimating the optimum path, as safety and efficiency are essential factors when planning for a long-distance journey. This paper represents an RL control model that proposes a control mechanism for improving navigation systems. Also, the model could be applied to other control path planning applications because it is adjustable and can accept different properties and parameters. However, the navigation system application has been taken as a case and evaluation study for the proposed model. The model utilized a Q-learning algorithm for training and updating the policy. It allows the agent to analyze the quality of an action made in the environment to maximize rewards. The model gives the ability to update rewards regularly based on safety and efficiency assessments, allowing the policy to consider the desired safety and efficiency benefits while making decisions, which improves the quality of the decisions taken for path planning compared to the conventional RL approaches.

Keywords: Artificial intelligence, control system, navigation systems, reinforcement learning.

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Authors: Idil Kanter Otcu

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Nowadays, due to the growing problems of energy supply and the drastic reduction of natural non-renewable resources, the development of new applications in the energy sector and steps towards greater efficiency in energy consumption are required. Since buildings account for a large share of energy consumption, increasing the structural density of buildings causes an increase in energy consumption. This increase in energy consumption means that energy efficiency approaches to building design and the integration of new systems using emerging technologies become necessary in order to curb this consumption. As new systems for productive usage of generated energy are developed, buildings that require less energy to operate, with rational use of resources, need to be developed. One solution for reducing the energy requirements of buildings is through landscape planning, design and application. Requirements such as heating, cooling and lighting can be met with lower energy consumption through planting design, which can help to achieve more efficient and rational use of resources. Within this context, rather than a planting design which considers only the ecological and aesthetic features of plants, these considerations should also extend to spatial organization whereby the relationship between the site and open spaces in the context of climatic elements and planting designs are taken into account. In this way, the planting design can serve an additional purpose. In this study, a landscape design which takes into consideration location, local climate morphology and solar angle will be illustrated on a sample building project.

Keywords: Energy efficiency, landscape design, plant design, xeriscape landscape.

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Authors: G. S. Ayyappan, M. Raja Raghavan, R. Poonthalir, Kota Srinivas, B. Ramesh Babu

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Electrical energy demand in the World and particularly in India, is increasing drastically more than its production over a period of time. In order to reduce the demand-supply gap, conserving energy becomes mandatory. Induction motors are the main driving force in the industries and contributes to about half of the total plant energy consumption. By effective monitoring and control of induction motors, huge electricity can be saved. This paper deals about the design and development of such a system, which employs iLON Smart Server and motor performance monitoring nodes. These nodes will monitor the performance of induction motors on-line, on-site and in-situ in the industries. The node monitors the performance of motors by simply measuring the electrical power input and motor shaft speed; coupled to genetic algorithm to estimate motor efficiency. The nodes are connected to the iLON Server through RS485 network. The web server collects the motor performance data from nodes, displays online, logs periodically, analyzes, alerts, and generates reports. The system could be effectively used to operate the motor around its Best Operating Point (BOP) as well as to perform the Life Cycle Assessment of Induction motors used in the industries in continuous operation.

Keywords: Best operating point, iLON smart server, motor asset management, LONWORKS, Modbus RTU, motor performance.

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Authors: Greg Turner, Bin Lu, Cheer-Sun Yang

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As computing technology advances, smartphone applications can assist student learning in a pervasive way. For example, the idea of using mobile apps for the PA Common Trees, Pests, Pathogens, in the field as a reference tool allows middle school students to learn about trees and associated pests/pathogens without bringing a textbook. While working on the development of three heterogeneous mobile apps, we ran into numerous challenges. Both the traditional waterfall model and the more modern agile methodologies failed in practice. The waterfall model emphasizes the planning of the duration for each phase. When the duration of each phase is not consistent with the availability of developers, the waterfall model cannot be employed. When applying Agile Methodologies, we cannot maintain the high frequency of the iterative development review process, known as ‘sprints’. In this paper, we discuss the challenges and solutions. We propose a hybrid model known as the Relay Race Methodology to reflect the concept of racing and relaying during the process of software development in practice. Based on the development project, we observe that the modeling of the relay race transition between any two phases is manifested naturally. Thus, we claim that the RRM model can provide a de fecto rather than a de jure basis for the core concept in the software development model. In this paper, the background of the project is introduced first. Then, the challenges are pointed out followed by our solutions. Finally, the experiences learned and the future works are presented.

Keywords: Agile methods, mobile apps, software process model, waterfall model.

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Authors: Sayyed R Mousavi

Abstract:

The Far From Most Strings Problem (FFMSP) is to obtain a string which is far from as many as possible of a given set of strings. All the input and the output strings are of the same length, and two strings are said to be far if their hamming distance is greater than or equal to a given positive integer. FFMSP belongs to the class of sequences consensus problems which have applications in molecular biology. The problem is NP-hard; it does not admit a constant-ratio approximation either, unless P = NP. Therefore, in addition to exact and approximate algorithms, (meta)heuristic algorithms have been proposed for the problem in recent years. On the other hand, in the recent years, hybrid algorithms have been proposed and successfully used for many hard problems in a variety of domains. In this paper, a new metaheuristic algorithm, called Constructive Beam and Local Search (CBLS), is investigated for the problem, which is a hybridization of constructive beam search and local search algorithms. More specifically, the proposed algorithm consists of two phases, the first phase is to obtain several candidate solutions via the constructive beam search and the second phase is to apply local search to the candidate solutions obtained by the first phase. The best solution found is returned as the final solution to the problem. The proposed algorithm is also similar to memetic algorithms in the sense that both use local search to further improve individual solutions. The CBLS algorithm is compared with the most recent published algorithm for the problem, GRASP, with significantly positive results; the improvement is by order of magnitudes in most cases.

Keywords: Bioinformatics, Far From Most Strings Problem, Hybrid metaheuristics, Matheuristics, Sequences consensus problems.

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Authors: Wenjun Zhang, Yunqing Du, Steven W. Cranford, Ming L. Wang

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The beginning of 21st century has witnessed new advancements in the design and use of new materials for biosensing applications, from nano to macro, protein to tissue. Traditional analytical methods lack a complete toolset to describe the complexities introduced by living systems, pathological relations, discrete hierarchical materials, cross-phase interactions, and structure-property dependencies. Materiomics – via systematic molecular dynamics (MD) simulation – can provide structureprocess- property relations by using a materials science approach linking mechanisms across scales and enables oriented biosensor design. With this approach, DNA biosensors can be utilized to detect disease biomarkers present in individuals’ breath such as acetone for diabetes. Our wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) has successfully detected trace amount of various chemicals in vapor differentiated by pattern recognition. Here, we present how MD simulation can revolutionize the way of design and screening of DNA aptamers for targeting biomarkers related to oral diseases and oral health monitoring. It demonstrates great potential to be utilized to build a library of DNDA sequences for reliable detection of several biomarkers of one specific disease, and as well provides a new methodology of creating, designing, and applying of biosensors.

Keywords: Biosensor, design, DNA, molecular dynamics simulation.

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Authors: C. Manjula, Lilly Florence

Abstract:

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: Hassan Yousif Ahmed, Ibrahima Faye, N.M.Saad, S.A. Aljined

Abstract:

Multi-user interference (MUI) is the main reason of system deterioration in the Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA) system. MUI increases with the number of simultaneous users, resulting into higher probability bit rate and limits the maximum number of simultaneous users. On the other hand, Phase induced intensity noise (PIIN) problem which is originated from spontaneous emission of broad band source from MUI severely limits the system performance should be addressed as well. Since the MUI is caused by the interference of simultaneous users, reducing the MUI value as small as possible is desirable. In this paper, an extensive study for the system performance specified by MUI and PIIN reducing is examined. Vectors Combinatorial (VC) codes families are adopted as a signature sequence for the performance analysis and a comparison with reported codes is performed. The results show that, when the received power increases, the PIIN noise for all the codes increases linearly. The results also show that the effect of PIIN can be minimized by increasing the code weight leads to preserve adequate signal to noise ratio over bit error probability. A comparison study between the proposed code and the existing codes such as Modified frequency hopping (MFH), Modified Quadratic- Congruence (MQC) has been carried out.

Keywords: FBG, MUI, PIIN, SAC-OCDMA, VCC.

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Authors: G. Aouf, D. Tabbal, A. Sabsabi, R. Aouf

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The aim of this study is to assess the viability of utilizing Municipal Solid Waste Incineration Fly Ash (MSWIFA) with Ordinary Portland cement as soil reinforcement materials for geotechnical engineering applications. A detailed experimental program is carried out followed by analysis of results. Soil samples were prepared by adding cement to MSWIFA-soil mix at different percentages. Then, a series of laboratory tests were performed namely: Sieve analysis, Atterberg limits tests, Unconfined compression test, and Proctor tests. A parametric study is conducted to investigate the effect of adding the cement at different percentages on the unconfined compression strength, maximum dry density (MDD), and optimum moisture content (OMC) of clayey soil-MSWIFA. The variations of admixtures’ contents were 10%, 20%, and 30% for MSWIFA by dry total weight of soil and 10%, 15%, and 20% for Portland cement by dry total weight of the mix. The test results reveal that adding MSWIFA to the soil up to 20% increased the MDD of the mixture and decreased the OMC, then an opposite trend for results were found when the percentage of MSWIFA exceeds 20%. This is due to the low specific gravity of MSWIFA and to the greater water absorption of MSWIFA. The laboratory tests also indicate that the Unconfined Compression Test values were found to be increased for all the mixtures with curing periods of 7, 14, and 28 days. It is also observed that the cement increased the strength of the finished product of the mix of soil and MSWIFA.

Keywords: Clayey soil, cement, Municipal Solid Waste Incineration Fly Ash, MSWIFA, unconfined compression strength.

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Authors: Dongwan Kang, Joohyung Oh, Chaetae Im

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Advancement of communication technologies and smart devices in the recent times is leading to changes into the integrated wired and wireless communication environments. Since early days, businesses had started introducing environments for mobile device application to their operations in order to improve productivity (efficiency) and the closed corporate environment gradually shifted to an open structure. Recently, individual user's interest in working environment using mobile devices has increased and a new corporate working environment under the concept of BYOD is drawing attention. BYOD (bring your own device) is a concept where individuals bring in and use their own devices in business activities. Through BYOD, businesses can anticipate improved productivity (efficiency) and also a reduction in the cost of purchasing devices. However, as a result of security threats caused by frequent loss and theft of personal devices and corporate data leaks due to low security, companies are reluctant about adopting BYOD system. In addition, without considerations to diverse devices and connection environments, there are limitations in detecting abnormal behaviors, such as information leaks, using the existing network-based security equipment. This study suggests a method to detect abnormal behaviors according to individual behavioral patterns, rather than the existing signature-based malicious behavior detection, and discusses applications of this method in BYOD environment.

Keywords: BYOD, Security, Anomaly Behavior Detection.

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