Abstract: Lightweight construction became more and more important over the last decades in several applications, e.g. in the automotive or aircraft sector. This is the result of economic and ecological constraints on the one hand and increasing safety and comfort requirements on the other hand. In the field of lightweight design, different approaches are used due to specific requirements towards the technical systems. The use of endless carbon fiber reinforced plastics (CFRP) offers the largest weight saving potential of sometimes more than 50% compared to conventional metal-constructions. However, there are very limited industrial applications because of the cost-intensive manufacturing of the fibers and production technologies. Other disadvantages of pure CFRP-structures affect the quality control or the damage resistance. One approach to meet these challenges is hybrid materials. This means CFRP and sheet metal are combined on a material level. Therefore, new opportunities for innovative process routes are realizable. Hybrid lightweight design results in lower costs due to an optimized material utilization and the possibility to integrate the structures in already existing production processes of automobile manufacturers. In recent and current research, the advantages of two-layered hybrid materials have been pointed out, i.e. the possibility to realize structures with tailored mechanical properties or to divide the curing cycle of the epoxy resin into two steps. Current research work at the Chair for Automotive Lightweight Design (LiA) at the Paderborn University focusses on production processes for fiber-metal-laminates. The aim of this work is the development and qualification of a large-scale production process for high-performance fiber-metal-laminates (FML) for industrial applications in the automotive or aircraft sector. Therefore, the prepreg-press-technology is used, in which pre-impregnated carbon fibers and sheet metals are formed and cured in a closed, heated mold. The investigations focus e.g. on the realization of short process chains and cycle times, on the reduction of time-consuming manual process steps, and the reduction of material costs. This paper gives an overview over the considerable steps of the production process in the beginning. Afterwards experimental results are discussed. This part concentrates on the influence of different process parameters on the mechanical properties, the laminate quality and the identification of process limits. Concluding the advantages of this technology compared to conventional FML-production-processes and other lightweight design approaches are carried out.
Abstract: In this paper, we consider CCL-N (Cooperative Cross Layer Network) topology based on the cross layer (both centralized and distributed) environment to form network communities. Various performance metrics related to the IEEE 802.16 networks are discussed to design CCL-N Topology. In CCL-N topology, nodes are classified as master nodes (Master Base Station [MBS]) and serving nodes (Relay Station [RS]). Nodes communities are organized based on the networking terminologies. Based on CCL-N Topology, various simulation analyses for both transparent and non-transparent relays are tabulated and throughput efficiency is calculated. Weighted load balancing problem plays a challenging role in IEEE 802.16 network. CoTS (Concurrent Transmission Scheduling) Scheme is formulated in terms of three aspects – transmission mechanism based on identical communities, different communities and identical node communities. CoTS scheme helps in identifying the weighted load balancing problem. Based on the analytical results, modularity value is inversely proportional to that of the error value. The modularity value plays a key role in solving the CoTS problem based on hop count. The transmission mechanism for identical node community has no impact since modularity value is same for all the network groups. In this paper three aspects of communities based on the modularity value which helps in solving the problem of weighted load balancing and CoTS are discussed.
Abstract: This research paper presents a framework for classifying Magnetic Resonance Imaging (MRI) images for Dementia. Dementia, an age-related cognitive decline is indicated by degeneration of cortical and sub-cortical structures. Characterizing morphological changes helps understand disease development and contributes to early prediction and prevention of the disease. Modelling, that captures the brain’s structural variability and which is valid in disease classification and interpretation is very challenging. Features are extracted using Gabor filter with 0, 30, 60, 90 orientations and Gray Level Co-occurrence Matrix (GLCM). It is proposed to normalize and fuse the features. Independent Component Analysis (ICA) selects features. Support Vector Machine (SVM) classifier with different kernels is evaluated, for efficiency to classify dementia. This study evaluates the presented framework using MRI images from OASIS dataset for identifying dementia. Results showed that the proposed feature fusion classifier achieves higher classification accuracy.
Abstract: In the study, we present a conceptual framework for developing a scheduling system that can generate self-explanatory and easy-understanding schedules. To this end, a user interface is conceived to help planners record factors that are considered crucial in scheduling, as well as internal and external sources relating to such factors. A hybrid approach combining machine learning and constraint programming is developed to generate schedules and the corresponding factors, and accordingly display them on the user interface. Effects of the proposed system on scheduling are discussed, and it is expected that scheduling efficiency and system understandability will be improved, compared with previous scheduling systems.
Abstract: In this paper, the classical bearing capacity problem is re-considered from discrete element analysis. In the discrete element approach, the bearing capacity problem is considered from the elastic stage to plastic stage to rupture stage (large displacement). The bearing capacity failure mechanism of a strip footing on soil is investigated, and the influence of micro-parameters on the bearing capacity of soil is also observed. It is found that the distinct element method (DEM) gives very good visualized results, and basically coincides well with that derived by the classical methods.
Abstract: At Istituto Nazionale di Fisica Nucleare – Laboratorio Nazionale del Sud (INFN-LNS), a broad experience in the design, construction and commissioning of ECR and microwave ion sources is available. The AISHa ion source has been designed by taking into account the typical requirements of hospital-based facilities, where the minimization of the mean time between failures (MTBF) is a key point together with the maintenance operations, which should be fast and easy. It is intended to be a multipurpose device, operating at 18 GHz, in order to achieve higher plasma densities. It should provide enough versatility for future needs of the hadron therapy, including the ability to run at larger microwave power to produce different species and highly charged ion beams. The source is potentially interesting for any hadron therapy facility using heavy ions. In this paper, we analyzed the dimensional test and electrical test about an innovative solution for the containment chamber that allows us to solve our isolation and structural problems.
Abstract: One of the major problems facing education in Nigeria is the provision of quality Science and Technology education. Inadequate teaching facilities, non-usage of innovative teaching strategies, ineffective classroom management, lack of students’ motivation and poor integration of ICT has resulted in the increase in percentage of students who failed Basic Science and Technology in Junior Secondary Certification Examination for National Examination Council in Nigeria. To address these challenges, the Federal Government came up with a road map on education. This was with a view of enhancing quality education through integration of modern technology into teaching and learning, enhancing quality assurance through proper monitoring and introduction of innovative methods of teaching. This led the researcher to investigate how MOODLE LMS could be used to enhance students’ learning outcomes in BST. A sample of 120 students was purposively selected from four secondary schools in Ogbomoso. The experimental group was taught using MOODLE LMS, while the control group was taught using the conventional method. Data obtained were analyzed using mean, standard deviation and t-test. The result showed that MOODLE LMS was an effective learning platform in teaching BST in junior secondary schools (t=4.953, P
Abstract: Enterprise growth is generally considered as a key driver of competitiveness, employment, economic development and social inclusion. As such, it is perceived to be a highly desirable outcome of entrepreneurship for scholars and decision makers. The huge academic debate resulted in the multitude of theoretical frameworks focused on explaining growth stages, determinants and future prospects. It has been widely accepted that enterprise growth is most likely nonlinear, temporal and related to the variety of factors which reflect the individual, firm, organizational, industry or environmental determinants of growth. However, factors that affect growth are not easily captured, instruments to measure those factors are often arbitrary, causality between variables and growth is elusive, indicating that growth is not easily modeled. Furthermore, in line with heterogeneous nature of the growth phenomenon, there is a vast number of measurement constructs assessing growth which are used interchangeably. Differences among various growth measures, at conceptual as well as at operationalization level, can hinder theory development which emphasizes the need for more empirically robust studies. In line with these highlights, the main purpose of this paper is twofold. Firstly, to compare structure and performance of three growth prediction models based on the main growth measures: Revenues, employment and assets growth. Secondly, to explore the prospects of financial indicators, set as exact, visible, standardized and accessible variables, to serve as determinants of enterprise growth. Finally, to contribute to the understanding of the implications on research results and recommendations for growth caused by different growth measures. The models include a range of financial indicators as lag determinants of the enterprises’ performances during the 2008-2013, extracted from the national register of the financial statements of SMEs in Croatia. The design and testing stage of the modeling used the logistic regression procedures. Findings confirm that growth prediction models based on different measures of growth have different set of predictors. Moreover, the relationship between particular predictors and growth measure is inconsistent, namely the same predictor positively related to one growth measure may exert negative effect on a different growth measure. Overall, financial indicators alone can serve as good proxy of growth and yield adequate predictive power of the models. The paper sheds light on both methodology and conceptual framework of enterprise growth by using a range of variables which serve as a proxy for the multitude of internal and external determinants, but are unlike them, accessible, available, exact and free of perceptual nuances in building up the model. Selection of the growth measure seems to have significant impact on the implications and recommendations related to growth. Furthermore, the paper points out to potential pitfalls of measuring and predicting growth. Overall, the results and the implications of the study are relevant for advancing academic debates on growth-related methodology, and can contribute to evidence-based decisions of policy makers.
Abstract: Wireless Sensor Networks (WSNs) have many advantages. Their deployment is easier and faster than wired sensor networks or other wireless networks, as they do not need fixed infrastructure. Nodes are partitioned into many small groups named clusters to aggregate data through network organization. WSN clustering guarantees performance achievement of sensor nodes. Sensor nodes energy consumption is reduced by eliminating redundant energy use and balancing energy sensor nodes use over a network. The aim of such clustering protocols is to prolong network life. Low Energy Adaptive Clustering Hierarchy (LEACH) is a popular protocol in WSN. LEACH is a clustering protocol in which the random rotations of local cluster heads are utilized in order to distribute energy load among all sensor nodes in the network. This paper proposes Connected Dominant Set (CDS) based cluster formation. CDS aggregates data in a promising approach for reducing routing overhead since messages are transmitted only within virtual backbone by means of CDS and also data aggregating lowers the ratio of responding hosts to the hosts existing in virtual backbones. CDS tries to increase networks lifetime considering such parameters as sensors lifetime, remaining and consumption energies in order to have an almost optimal data aggregation within networks. Experimental results proved CDS outperformed LEACH regarding number of cluster formations, average packet loss rate, average end to end delay, life computation, and remaining energy computation.
Abstract: Mobile applications are being used to perform a wide variety of tasks in day-to-day life, ranging from checking email to controlling your home heating. Application developers have recognized the potential to transform a smart device into a medical device, by using a mobile medical application i.e. a mobile phone or a tablet. When initially conceived these mobile medical applications performed basic functions e.g. BMI calculator, accessing reference material etc.; however, increasing complexity offers clinicians and patients a range of functionality. As this complexity and functionality increases, so too does the potential risk associated with using such an application. Examples include any applications that provide the ability to inflate and deflate blood pressure cuffs, as well as applications that use patient-specific parameters and calculate dosage or create a dosage plan for radiation therapy. If an unapproved mobile medical application is marketed by a medical device organization, then they face significant penalties such as receiving an FDA warning letter to cease the prohibited activity, fines and possibility of facing a criminal conviction. Regulatory bodies have finalized guidance intended for mobile application developers to establish if their applications are subject to regulatory scrutiny. However, regulatory controls appear contradictory with the approaches taken by mobile application developers who generally work with short development cycles and very little documentation and as such, there is the potential to stifle further improvements due to these regulations. The research presented as part of this paper details how by adopting development techniques, such as agile software development, mobile medical application developers can meet regulatory requirements whilst still fostering innovation.
Abstract: In recent years, increasing the usage of railway transportations especially in developing countries caused more attention to control systems railway vehicles. Consequently, designing and implementing the modern control systems to improve the operating performance of trains and locomotives become one of the main concerns of researches. Dynamic braking systems is an important safety system which controls the amount of braking torque generated by traction motors, to keep the adhesion coefficient between the wheel-sets and rail road in optimum bound. Adhesion force has an important role to control the braking distance and prevent the wheels from slipping during the braking process. Cascade control structure is one of the best control methods for the wide range of industrial plants in the presence of disturbances and errors. This paper presents cascade control structure based on two forward simple controllers with two feedback loops to control the slip ratio and braking torque. In this structure, the inner loop controls the angular velocity and the outer loop control the longitudinal velocity of the locomotive that its dynamic is slower than the dynamic of angular velocity. This control structure by controlling the torque of DC traction motors, tries to track the desired velocity profile to access the predefined braking distance and to control the slip ratio. Simulation results are employed to show the effectiveness of the introduced methodology in dynamic braking system.
Abstract: Tikhonov regularization and reproducing kernels are the
most popular approaches to solve ill-posed problems in computational
mathematics and applications. And the Fourier multiplier operators
are an essential tool to extend some known linear transforms
in Euclidean Fourier analysis, as: Weierstrass transform, Poisson
integral, Hilbert transform, Riesz transforms, Bochner-Riesz mean
operators, partial Fourier integral, Riesz potential, Bessel potential,
etc. Using the theory of reproducing kernels, we construct a simple
and efficient representations for some class of Fourier multiplier
operators Tm on the Paley-Wiener space Hh. In addition, we give
an error estimate formula for the approximation and obtain some
convergence results as the parameters and the independent variables
approaches zero. Furthermore, using numerical quadrature integration
rules to compute single and multiple integrals, we give numerical
examples and we write explicitly the extremal function and the
corresponding Fourier multiplier operators.
Abstract: Organizations today need to invest in software in order to run their businesses, and to the organizations’ objectives, the software should be in line with the business process. This research presents an approach for linking process models and system models. Particularly, the new approach aims to synthesize sequence diagram based on role activity diagram (RAD) model. The approach includes four steps namely: Create business process model using RAD, identify computerized activities, identify entities in sequence diagram and identify messages in sequence diagram. The new approach has been validated using the process of student registration in University of Petra as a case study. Further research is required to validate the new approach using different domains.
Abstract: There is a widespread belief in everyday discourse that science subjects (physics, chemistry and biology) are, along with math, the most difficult school subjects in the education of an individual. This assumption is usually justified by the following facts: low GPA in these subjects, the number of pupils who fail these subjects is high in comparison to other subjects, and the number of pupils interested in continuing their studies in the fields with a focus on science subjects is lower compared to non-science-oriented fields. From that perspective, the project: “Could it be different? How do children explore it?” becomes extremely interesting because it is focused on young children and on the introduction of new methods, with aim of arousing interest in scientific literacy development in 10 kindergartens by applying the methodology of an action research, with an ethnographic approach. We define scientific literacy as a process of encouraging and nurturing the research and explorative spirit in children, as well as their natural potential and abilities that represent an object of scientific research: to learn about exploration by conducting exploration. Upon project completion, an evaluation questionnaire was created for the parents of the children who had participated in the project, as well as for those whose children had not been involved in the project. The purpose of the first questionnaire was to examine the level of satisfaction with the project implementation and its outcomes among those parents whose children had been involved in the project (N=142), while the aim of the second questionnaire was to find out how much the parents of the children not involved (N=154) in this activity were interested in this topic.
Abstract: The advanced information technology is becoming an important factor in the development of financial services industry, especially the banking industry. It has introduced new ways of delivering banking to the customer, such as Internet Banking. Banks began to look at electronic banking (e-banking) as a means to replace some of their traditional branch functions using the Internet as a new distribution channel. Some consumers have at least more than one account, and across banks, and access these accounts using e-banking services. To look at the current net worth position, customers have to login to each of their accounts and get the details and work on consolidation. This not only takes ample time but it is a repetitive activity at a specified frequency. To address this point, an account aggregation concept is added as a solution. E-banking account aggregation, as one of the e-banking types, appeared to build a stronger relationship with customers. Account Aggregation Service generally refers to a service that allows customers to manage their bank accounts maintained in different institutions through a common Internet banking operating a platform, with a high concern to security and privacy. This paper presents an overview of an e-banking account aggregation approach as a new service in the e-banking field.
Abstract: Active learning strategies have completely rewritten the concept of teaching and learning. Academicians have clocked back to Socratic approaches of questioning. Educators have started implementing active learning strategies for effective learning with the help of tools and technology. As Generation-Y learners are mostly visual, engaging them using visualization techniques play a vital role in their learning process. The facilitator has an important role in intrinsically motivating the learners using different approaches to create self-learning interests. Different visualization techniques were used along with lectures to help students understand and appreciate the concepts. Anonymous feedback was collected from learners. The consolidated report shows that majority of learners accepted the usage of visualization techniques was helpful in understanding concepts as well as create interest in learning the course. This study helps to understand, how the use of visualization techniques help the facilitator to engage learners effectively as well create and intrinsic motivation for their learning.
Abstract: Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.
Abstract: Ever increasing population growth of major urban centers and environmental challenges in siting new landfills have resulted in a growing trend in design of mega-landfills some with extraordinary heights and dangerously steep slopes. Landfill failure mobility risk analysis is one of the most uncertain types of dynamic rheology models due to very large inherent variabilities in the heterogeneous solid waste material shear strength properties. The waste flow of three historic dumpsite and two landfill failures were back-analyzed using run-out modeling with DAN-W model. The travel distances of the waste flow during landfill failures were calculated approach by taking into account variability in material shear strength properties. The probability distribution function for shear strength properties of the waste material were grouped into four major classed based on waste material compaction (landfills versus dumpsites) and composition (high versus low quantity) of high shear strength waste materials such as wood, metal, plastic, paper and cardboard in the waste. This paper presents a probabilistic method for estimation of the spatial extent of waste avalanches, after a potential landfill failure, to create maps of vulnerability scores to inform property owners and residents of the level of the risk.
Abstract: Given the increase in the number of students and administrators asking for online courses the author developed two partially online courses. One was a biology majors at genetics course while the other was a non-majors at biology course. The student body at Queensborough Community College is generally underprepared and has work and family obligations. As an educator, one has to be mindful about changing the pedagogical approach, therefore, special care was taken when designing the course material. Despite the initial concerns, both of these partially online courses were received really well by students. Lessons learnt were that student engagement is the key to success in an online course. Good practices to run a successful online course for underprepared students are discussed in this paper. Also discussed are the lessons learnt for making the eLearning environment better for all the students in the class, overachievers and underachievers alike.
Abstract: Due to increased pressure from global competitors, manufacturing organizations are switching over to lean philosophies from traditional mass production. Lean manufacturing is a manufacturing philosophy which focuses on elimination of various types of wastes and creates maximum value for the end customers. Lean thinking aims to produce high quality products and services at the lowest possible cost with maximum customer responsiveness. Indian Industry is facing lot of problems in this transformation from traditional mass production to lean production. Through this paper an attempt has been made to identify various lean implementation hurdles in Indian industries with the help of a structured survey. Identified hurdles are grouped with the help of factor analysis and rated by calculating descriptive statistics. To show the effect of lean implementation hurdles a hypothesis “Organizations having higher level of lean implementation hurdles will have poor (negative) performance” has been postulated and tested using correlation matrix between performance parameters of the organizations and identified hurdles. The findings of the paper will be helpful to prepare road map to identify and eradicate the lean implementation hurdles.