Search results for: scalable architectures

Authors: Emiliano Lustrissimi, Bonifacio Bianco, Sebastiano Caravaggi, Antonio Rosato

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A mathematical framework has been designed to enhance the configuration of an end-of-production-line (EOL) test bench. This system can be used to assess the performance of electric motors or axles intended for electric vehicles. The model has been developed to predict the behaviour of EOL test benches and electric motors/axles under various boundary conditions, eliminating the need for extensive physical testing and reducing the corresponding power consumption. The suggested model is versatile, capable of being utilized across various types of electric motors or axles, and adaptable to accommodate varying power ratings of electric motors or axles. The maximum performance to be guaranteed by the EMs according to the car maker's specifications are taken as inputs in the model. Then, the required performance of each main EOL test bench component is calculated, and the corresponding systems available on the market are selected based on manufacturers’ catalogues. In this study, an EOL test bench has been designed according to the proposed model outputs for testing a low-power (about 22 kW) electric axle. The performance of the designed EOL test bench has been measured and used to validate the proposed model and assess both the consistency of the constraints as well as the accuracy of predictions in terms of electric demands. The comparison between experimental and predicted data exhibited a reasonable agreement, allowing to demonstrate that, despite some discrepancies, the model gives an accurate representation of the EOL test benches' performance.

Keywords: electric motors, electric vehicles, end-of-production-line test bench, mathematical model, field tests

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Authors: Neeraj Kumar Mishra, In Su Kim

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The isoindoline, indazole and indole heterocycles are ubiquitous structural motif found in heterocyclic compounds as they exhibit biological and medicinal applications. For example, isoindoline motif is present in molecules that act as endothelin-A receptor antagonists and dipeptidyl peptidase inhibitors. Moreover, isoindoline derivatives are very crucial constituents in the field of materials science as attractive candidates for organic light-emitting devices. However, compounds containing the indazole motif are known to exhibit to a variety of biological activities, such as estrogen receptor, HIV protease inhibition and anti-tumor activity. The prevalence of indazoles and indoles has led to the development of many useful methods for their preparation. Thus, isoindoline, indazole and indole heterocycles can be new candidates for the next generation of pharmaceuticals. Therefore, the development of highly efficient strategies for the formation of these heterocyclic architectures is an area of great interest in organic synthesis. The past years, transition-metal-catalyzed C−H activation followed by annulation reaction has been frequently used as a powerful tool to construct various heterocycles. Herein, we describe our recent achievements about the transition-metal-catalyzed tandem cyclization reactions of N-benzyltriflamides, 1,2-disubstituted arylhydrazines, acetanilides, etc. via C−H bond activation to access the corresponding bioactive heterocylic scaffolds.

Keywords: biologically active, C-H activation, heterocyclic compounds, transition-metal catalysts

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Authors: Charles L. Sigmund, M. A. Aed, Lissa Graciela Rivera Picado

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One critical component of the training development process is the evaluation of the impact and value of the program. Oftentimes, however, learning organizations bypass this phase either because they are unfamiliar with effective methods for measuring the success or effect of the training or because they believe the effort to be too time-consuming or cumbersome. As a result, most organizations that do conduct evaluation limit their scope to Kirkpatrick L1 (reaction) and L2 (learning), or at most carry through to L4 (results). In 2021 Microsoft made a strategic decision to assess the measurable and monetized impact for all training launches and designed a scalable and program-agnostic tool for providing full-scale L5 return on investment (ROI) estimates for each. In producing this measurement tool, the learning and development organization built a framework for making business prioritizations and resource allocations that is based on the projected ROI of a course. The analysis and measurement posed by this process use a combination of training data and operational metrics to calculate the effective net benefit derived from a given training effort. Business experts in the learning field generally consider a 10% ROI to be an outstanding demonstration of the value of a project. Initial findings from this work applied to a critical customer-facing program yielded an estimated ROI of more than 49%. This information directed the organization to make a more concerted and concentrated effort in this specific line of business and resulted in additional investment in the training methods and technologies being used.

Keywords: evaluation, measurement, return on investment, value

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Authors: Leonardo A. Ambrosio, Carlos. H. Silva Santos, Ivan E. L. Rodrigues, Ayumi K. de Campos, Leandro A. Machado

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In this work, we propose an algorithm developed under Python language for the modeling of ordinary scalar Bessel beams and their discrete superpositions and subsequent calculation of optical forces exerted over dielectric spherical particles. The mathematical formalism, based on the generalized Lorenz-Mie theory, is implemented in Python for its large number of free mathematical (as SciPy and NumPy), data visualization (Matplotlib and PyJamas) and multiprocessing libraries. We also propose an approach, provided by a synchronized Software as Service (SaaS) in cloud computing, to develop a user interface embedded on a mobile application, thus providing users with the necessary means to easily introduce desired unknowns and parameters and see the graphical outcomes of the simulations right at their mobile devices. Initially proposed as a free Android-based application, such an App enables data post-processing in cloud-based architectures and visualization of results, figures and numerical tables.

Keywords: Bessel Beams and Frozen Waves, Generalized Lorenz-Mie Theory, Numerical Methods, optical forces

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Authors: Amir Ahmad Dehghani, Morteza Nabizadeh

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This paper presents the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to flood hydrograph modeling of Shahid Rajaee reservoir dam located in Iran. This was carried out using 11 flood hydrographs recorded in Tajan river gauging station. From this dataset, 9 flood hydrographs were chosen to train the model and 2 flood hydrographs to test the model. The different architectures of neuro-fuzzy model according to the membership function and learning algorithm were designed and trained with different epochs. The results were evaluated in comparison with the observed hydrographs and the best structure of model was chosen according the least RMSE in each performance. To evaluate the efficiency of neuro-fuzzy model, various statistical indices such as Nash-Sutcliff and flood peak discharge error criteria were calculated. In this simulation, the coordinates of a flood hydrograph including peak discharge were estimated using the discharge values occurred in the earlier time steps as input values to the neuro-fuzzy model. These results indicate the satisfactory efficiency of neuro-fuzzy model for flood simulating. This performance of the model demonstrates the suitability of the implemented approach to flood management projects.

Keywords: adaptive neuro-fuzzy inference system, flood hydrograph, hybrid learning algorithm, Shahid Rajaee reservoir dam

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Authors: A. Chtourou, K. Ben Youssef, M. Friel, T. Leicht

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These Place attributes and destination images associated with tourism destinations are often crucial important for tourist travel decisions and choice behavior. Understanding the interactions between them is fundamental for developing sustainable place brands. Despite their extensive use on an empirical ground, little research has been done in terms of analyzing the constructs that determine the sense of place in the marketing of cultural heritage sites and on how tourist experiences at such places influence tourist motivations to revisit destinations. By referring to the Italian city of Vicenza, internationally renowned for its gold jewelry production and for the Palladian architectures and buildings which have been recognized World Heritage by the UNESCO, the paper aims to identify how destination image, place familiarity and travel satisfaction influence tourists’ motivations to revisit Vicenza. After an introduction and literature review, the paper investigates the importance of the core constructs that determine the sense of place in the tourist practice. In accordance with previous research, the results provide evidence that favorable travel experiences influence revisit intentions positively. The managerial implications and recommendations for the city of Vicenza are discussed.

Keywords: consumer behavior, heritage tourism, sense of place, place branding, territorial marketing

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Authors: Adria Kajenski, Guinevere Strack, Edward Kingsley, Shahriar Khushrushahi, Alkim Akyurtlu

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Radio Frequency (RF) metasurfaces are arrangements of subwavelength elements interacting with electromagnetic radiation. These arrangements affect polarization state, amplitude, and phase of impinged radio waves; for example, metasurface designs are used to produce functional passband and stopband filters. Recent advances in additive manufacturing techniques have enabled the low-cost, rapid fabrication of ultra-thin metasurface elements on flexible substrates such as plastic films, paper, and textiles. Furthermore, scalable manufacturing processes promote the integration of fabric-based RF metasurfaces into the market of sensors and devices within the Internet of Things (IoT). The design and fabrication of metasurfaces on textiles require a multidisciplinary team with expertise in i) textile and materials science, ii) metasurface design and simulation, and iii) metasurface fabrication and testing. In this presentation, we will discuss RF metasurfaces on fabric with an emphasis on how the materials, including fabric and inks, along with fabrication techniques, affect the RF performance. We printed metasurfaces using a direct-write approach onto various woven and non-woven fabrics, as well as on fabrics coated with either thermoplastic or thermoset coatings. Our team also performed a range of tests on the printed structures, including different inks and their curing parameters, wash durability, abrasion resistance, and RF performance over time.

Keywords: electronic textiles, metasurface, printed electronics, flexible

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Authors: M. Srilatha, R. Hemalatha, T. Sri Aditya

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Communication of today world is dominated by wireless technology. This is mainly due to the revolutionary development of new wireless communication system generations. The evolving new generations of wireless systems are accommodating the demand through better resource management including improved transmission technologies with optimized communication devices. To keep up with the evolution of technologies, the communication systems must be designed to optimize transparent insertion of newly evolved technologies virtually at all stages of their life cycle. After the insertion of new technologies, the upgraded devices should continue the communication without squalor in quality. The concern of improving spectrum access and spectrum efficiency combined with both the introduction of Software Defined Radios (SDR) and the possibility of the software application to radios has led to an evolution of wireless radio research. The software defined radio term was coined in the 1970s to overcome the problems in the application of software to wireless radios which eliminates the requirement of hardware changes. SDR has become the prime theme of research since it eliminates the drawbacks associated with conventional wireless communication systems implementation. This paper identifies and discusses key enabling technologies and possibility of research and development in SDRs. In addition transmitter and receiver architectures of SDR are also discussed along with their feasibility for reconfigurable radio application.

Keywords: software defined radios, wireless communication, reconfigurable, reconfigurable transmitter, reconfigurable receivers, FPGA, DSP

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Authors: Bipasha Sen, Aditya Agarwal

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Multilingual automatic speech recognition (ASR) system is a single entity capable of transcribing multiple languages sharing a common phone space. Performance of such a system is highly dependent on the compatibility of the languages. State of the art speech recognition systems are built using sequential architectures based on recurrent neural networks (RNN) limiting the computational parallelization in training. This poses a significant challenge in terms of time taken to bootstrap and validate the compatibility of multiple languages for building a robust multilingual system. Complex architectural choices based on self-attention networks are made to improve the parallelization thereby reducing the training time. In this work, we propose Reed, a simple system based on 1D convolutions which uses very short context to improve the training time. To improve the performance of our system, we use raw time-domain speech signals directly as input. This enables the convolutional layers to learn feature representations rather than relying on handcrafted features such as MFCC. We report improvement on training and inference times by atleast a factor of 4x and 7.4x respectively with comparable WERs against standard RNN based baseline systems on SpeechOcean's multilingual low resource dataset.

Keywords: convolutional neural networks, language compatibility, low resource languages, multilingual automatic speech recognition

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Authors: Mithil Pandey, Ragunathan Bala Subramanian

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One of the major conversion technologies in the oil refinery industry is Fluid catalytic cracking (FCC) which produces the majority of the world’s gasoline. Some useful products are generated from the vacuum gas oil, heavy gas oil and residue feedstocks by the FCC unit in an oil refinery. Moreover, Zeolite catalysts (zeo-catalysts) have found widespread applications and have proved to be substantial and paradigmatic in oil refining and petrochemical processes, such as FCC because of their porous features. Several famous zeo-catalysts have been fabricated and applied in industrial processes as milestones in history, and have brought on huge changes in petrochemicals. So far, more than twenty types of zeolites have been industrially applied, and their versatile porous architectures with their essential features have contributed to affect the catalytic efficiency. This poster depicts the evolution of pore models in zeolite catalysts which are accompanied by an increase in environmental and demands. The crucial roles of modulating pore models are outlined for zeo-catalysts for the enhancement of their catalytic performances in various industrial processes. The development of industrial processes for the FCC process, aromatic conversions and olefin production, makes it obvious that the pore architecture plays a very important role in zeo-catalysis processes. By looking at the different necessities of industrial processes, rational construction of the pore model is critically essential. Besides, the pore structure of the zeolite would have a substantial and direct effect on the utilization efficiency of the zeo-catalyst.

Keywords: catalysts, fluid catalytic cracking, industrial processes, zeolite

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Authors: Maryam Kiani

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This study focuses on the development of composite nanomaterials based on SiO2 and carbon black for oxygen reduction reaction (ORR) electrocatalysts in batteries and fuel cells. The aim was to explore the potential of these composite materials as efficient catalysts for ORR, which is a critical process in energy conversion devices. The SiO2/carbon black composite nanomaterials were synthesized using a facile and scalable method. The morphology, structure, and electrochemical properties of the materials were characterized using various techniques, including scanning electron microscopy (SEM), X-ray diffraction (XRD), and electrochemical measurements. The results demonstrated that the incorporation of SiO2 into the carbon black matrix enhanced the ORR performance of the composite material. The composite nanomaterials exhibited improved electrocatalytic activity, enhanced stability, and increased durability compared to pure carbon black. The presence of SiO2 facilitated the formation of active sites, improved electron transfer, and increased the surface area available for ORR. This study contributes to the advancement of battery and fuel cell technology by offering a promising approach for the development of high-performance ORR electrocatalysts. The SiO2/carbon black composite nanomaterials show great potential for improving the efficiency and durability of energy conversion devices, leading to more sustainable and efficient energy solutions.

Keywords: oxygen reduction reaction, batteries, fuel cells, electrrocatalyst

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Authors: Araceli Martínez Ortiz

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An educational research effort is analyzed using systems theory to document the power of collective impact when addressing multiple factors contributing towards the retention of students majoring in science, technology, engineering and mathematics (STEM) academic programs. This research promotes understanding on how networked communities may work effectively toward a shared vision and mutually aligned activities that result in sustained, large scale change. The actions of a team of researchers in their third year of collaboration are presented to describe a model that positively aligns work efforts resulting in greater total gains. The goals of the multiple programs managed by the funded program team are to: 1) expand the number of students who choose to study a STEM field of study; 2) promote student collaborative learning; 3) support faculty understanding of the funds of knowledge of diverse students and 4) establish innovative and robust STEM education research that will lead to the development of nationally replicable, scalable models for broadening participation in STEM. The impacts of this research effort are measured through quantitative statistical analysis of the changes in second-year STEM undergraduate student retention rates and representation rates of women, Hispanics and African American STEM majors.

Keywords: collaborative impact, diversity, student retention, systems theory, STEM education

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Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

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Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: multiclass classification, convolution neural network, OpenCV

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Authors: C. M. Balaceanu, G. Suciu, C. S. Bosoc, O. Orza, C. Fernandez, Z. Viniczay

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The Internet of Things (IoT) represents the best option for smart vineyard applications, even if it is necessary to integrate the technologies required for the development. This article is based on the research and the results obtained in the DISAVIT project. For Smart Agriculture, the project aims to provide a trustworthy, intelligent, integrated vineyard management solution that is based on the IoT. To have interoperability through the use of a multiprotocol technology (being the future connected wireless IoT) it is necessary to adopt an agnostic approach, providing a reliable environment to address cyber security, IoT-based threats and traceability through blockchain-based design, but also creating a concept for long-term implementations (modular, scalable). The ones described above represent the main innovative technical aspects of this project. The DISAVIT project studies and promotes the incorporation of better management tools based on objective data-based decisions, which are necessary for agriculture adapted and more resistant to climate change. It also exploits the opportunities generated by the digital services market for smart agriculture management stakeholders. The project's final result aims to improve decision-making, performance, and viticulturally infrastructure and increase real-time data accuracy and interoperability. Innovative aspects such as end-to-end solutions, adaptability, scalability, security and traceability, place our product in a favorable situation over competitors. None of the solutions in the market meet every one of these requirements by a unique product being innovative.

Keywords: blockchain, IoT, smart agriculture, vineyard

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Authors: Irina Alexandra Paun, Mona Mihailescu, Marian Zamfirescu, Catalin Romeo Luculescu, Adriana Maria Acasandrei, Cosmin Catalin Mustaciosu, Roxana Cristina Popescu, Maria Dinescu

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A major concern in bone tissue engineering is to develop complex 3D architectures that mimic the natural cells environment, facilitate the cells growth in a defined manner and allow the flow transport of nutrients and metabolic waste. In particular, porous structures of controlled pore size and positioning are indispensable for growing human-like bone structures. Another concern is to monitor both the structures and the seeded cells with high spatial resolution and without interfering with the cells natural environment. The present approach relies on laser-based technologies employed for fabricating porous biomimetic structures that support the growth of osteoblast-like cells and for their non-invasive 3D imaging. Specifically, the porous structures were built by two photon polymerization –direct writing (2PP_DW) of the commercially available photoresists IL-L780, using the Photonic Professional 3D lithography system. The structures consist of vertical tubes with micrometer-sized heights and diameters, in a honeycomb-like spatial arrangement. These were fabricated by irradiating the IP-L780 photoresist with focused laser pulses with wavelength centered at 780 nm, 120 fs pulse duration and 80 MHz repetition rate. The samples were precisely scanned in 3D by piezo stages. The coarse positioning was done by XY motorized stages. The scanning path was programmed through a writing language (GWL) script developed by Nanoscribe. Following laser irradiation, the unexposed regions of the photoresist were washed out by immersing the samples in the Propylene Glycol Monomethyl Ether Acetate (PGMEA). The porous structures were seeded with osteoblast like MG-63 cells and their osteogenic potential was tested in vitro. The cell-seeded structures were analyzed in 3D using the digital holographic microscopy technique (DHM). DHM is a marker free and high spatial resolution imaging tool, where the hologram acquisition is performed non-invasively i.e. without interfering with the cells natural environment. Following hologram recording, a digital algorithm provided a 3D image of the sample, as well as information about its refractive index, which is correlated with the intracellular content. The axial resolution of the images went down to the nanoscale, while the temporal scales ranged from milliseconds up to hours. The hologram did not involve sample scanning and the whole image was available in one frame recorded going over 200μm field of view. The digital holograms processing provided 3D quantitative information on the porous structures and allowed a quantitative analysis of the cellular response in respect to the porous architectures. The cellular shape and dimensions were found to be influenced by the underlying micro relief. Furthermore, the intracellular content gave evidence on the beneficial role of the porous structures in promoting osteoblast differentiation. In all, the proposed laser-based protocol emerges as a promising tool for the fabrication and non-invasive imaging of porous constructs for bone tissue engineering. Acknowledgments: This work was supported by a grant of the Romanian Authority for Scientific Research and Innovation, CNCS-UEFISCDI, project PN-II-RU-TE-2014-4-2534 (contract 97 from 01/10/2015) and by UEFISCDI PN-II-PT-PCCA no. 6/2012. A part of this work was performed in the CETAL laser facility, supported by the National Program PN 16 47 - LAPLAS IV.

Keywords: biomimetic, holography, laser, osteoblast, two photon polymerization

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Authors: Olanrewaju B. Lasisi

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The position of Ijebu-Ode, the historical capital of the Ijebu Kingdom, at the center of gravity of Ijebu land is enclosed by the 180-km-long earthwork and suggests a centrally controlled project. This paper reflects on the first stratigraphic drawing of the banks and ditches of this earthwork, and place its construction mechanism in a chronological framework. Nine radiocarbon dates obtained at the site suggest that the earthwork was built in the late 14th or early 15th century. This suggests a relationship with the Ijebu Kingdom, which pre-existed the opening of the Atlantic trade but first became visible only in the Portuguese records in the 1480s. In June 2017, more earthworks were found but within the core of Ijebu Land. This most recent finding points to an extension of territory from the center to the outlying villages. One central question about this discovery of monumental architectures that was functional around the 14th century or before is in its mode of construction. Apparently, iron tools must have been used in the construction of ‘a 20m deep ditch that runs 180km in circumference.’ Thus, the discovery of iron-working sites around the vicinity of the earthwork is a pointer to this building process that is up till now shrouded in mystery. By comparing the chronology of Ijebu earthworks with the evidence of Iron working in south western Nigeria around the first half of the first millennium AD, it can be thought that the rise in polity triggered the knowledge of metallurgy in the region.

Keywords: archaeology, earthworks, Ijebu, metallurgy

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Authors: L. Yu, W. K. Li, S. K. Ong, A. Y. C. Nee

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In this paper, a scalable augmented reality framework for handheld devices is presented. The presented framework is enabled by using a server-client data communication structure, in which the search for tracking targets among a database of images is performed on the server-side while pixel-wise 3D tracking is performed on the client-side, which, in this case, is a handheld mobile device. Image search on the server-side adopts a residual-enhanced image descriptors representation that gives the framework a scalability property. The tracking algorithm on the client-side is based on a gravity-aligned feature descriptor which takes the advantage of a sensor-equipped mobile device and an optimized intensity-based image alignment approach that ensures the accuracy of 3D tracking. Automatic content streaming is achieved by using a key-frame selection algorithm, client working phase monitoring and standardized rules for content communication between the server and client. The recognition accuracy test performed on a standard dataset shows that the method adopted in the presented framework outperforms the Bag-of-Words (BoW) method that has been used in some of the previous systems. Experimental test conducted on a set of video sequences indicated the real-time performance of the tracking system with a frame rate at 15-30 frames per second. The presented framework is exposed to be functional in practical situations with a demonstration application on a campus walk-around.

Keywords: augmented reality framework, server-client model, vision-based tracking, image search

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Authors: Bunakiye R. Japheth, Ogude U. Cyril

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Since the process of transforming user requirements to modeling constructs are not very well supported by domain-specific frameworks, it became necessary to integrate domain requirements with the specific architectures to achieve an integrated customizable solutions space via artifact orientation. Domain-specific modeling language specifications of model-driven engineering technologies focus more on requirements within a particular domain, which can be tailored to aid the domain expert in expressing domain concepts effectively. Modeling processes through domain-specific language formalisms are highly volatile due to dependencies on domain concepts or used process models. A capable solution is given by artifact orientation that stresses on the results rather than expressing a strict dependence on complicated platforms for model creation and development. Based on this premise, domain-specific methods for producing artifacts without having to take into account the complexity and variability of platforms for model definitions can be integrated to support customizable development. In this paper, we discuss methods for the integration capabilities and necessities within a common structure and semantics that contribute a metamodel for artifact-orientation, which leads to a reusable software layer with concrete syntax capable of determining design intents from domain expert. These concepts forming the language formalism are established from models explained within the oil and gas pipelines industry.

Keywords: control process, metrics of engineering, structured abstraction, semantic model

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Authors: Xin Zhao

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3D printing is used in creating bone grafts of various architectures by printing materials in a layer-by-layer manner. Traditionally, to make materials printable, heating up or dissolving materials in organic solvents have been used, compromising their capability in loading biomolecules. Photocrosslinkable materials which are initially liquid and printable, and solidified upon light exposure are therefore developed. However, the existing photocrosslinkable materials are either too soft to bear load or non-degradable with potential long-term biocompatibility problems. Here, photocrosslinkable nanocomposite ink is developed composed of poly (lactide-co-propylene glycol-co-lactide) dimethacrylate (PmLnDMA) and hydroxyethyl methacrylate-functionalized hydroxyapatite nanoparticles (nHAMA) mimicking the hairy setae of gecko that can strongly interact with its surroundings to bear high load. Incorporation of nHAMA into PmLnDMA endows the nanocomposite ink with several advantages in (1) improved organic/inorganic interfacial compatibility to increase mechanical strength, (2) readily modulated rheological behaviors, wettability, and biodegradation, (3) enhanced osteoconductivity and osteoinductivity. Moreover, the ink can be rapidly crosslinked upon light exposure, load, and long-term release growth factors, and be printed into 3D bone scaffolds of various shapes and structures according to the patients’ needs. Altogether, this innovation will benefit patients all over the world who suffer from bone fractures, tumors, infections.

Keywords: photocrosslinkable nanocomposite, 3D printing, bone ink, personalized medicine

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Authors: Rujia Chen, Ajit Narayanan

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Convolutional neural networks (CNN), as typically applied in deep learning, use layer-wise backpropagation (BP) to construct filters and kernels for feature extraction. Such filters are 2D or 3D groups of weights for constructing feature maps at subsequent layers of the CNN and are shared across the entire input. BP as a gradient descent algorithm has well-known problems of getting stuck at local optima. The use of genetic algorithms (GAs) for evolving weights between layers of standard artificial neural networks (ANNs) is a well-established area of neuroevolution. In particular, the use of crossover techniques when optimizing weights can help to overcome problems of local optima. However, the application of GAs for evolving the weights of filters and kernels in CNNs is not yet an established area of neuroevolution. In this paper, a GA-based filter development algorithm is proposed. The results of the proof-of-concept experiments described in this paper show the proposed GA algorithm can find filter weights through evolutionary techniques rather than BP learning. For some simple classification tasks like geometric shape recognition, the proposed algorithm can achieve 100% accuracy. The results for MNIST classification, while not as good as possible through standard filter learning through BP, show that filter and kernel evolution warrants further investigation as a new subarea of neuroevolution for deep architectures.

Keywords: neuroevolution, convolutional neural network, genetic algorithm, filters, kernels

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Authors: Rabaya Basori, Arup K. Raychaudhuri

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In recent years, a variety of semiconductor nanowires (NWs) has been synthesized and used as basic building blocks for the development of electronic and optoelectronic nanodevices. Dielectrophoresis (DEP) has been widely investigated as a scalable technique to trap and manipulate polarizable objects. This includes biological cells, nanoparticles, DNA molecules, organic or inorganic NWs and proteins using electric field gradients. In this article, we have used DEP force to localize nanowire growth by physical vapor deposition (PVD) method as well as control of NW diameter on field assisted growth of the NWs of CuTCNQ (Cu-tetracyanoquinodimethane); a metal-organic charge transfer complex material which is well known of resistive switching. We report a versatile analysis platform, based on a set of nanogap electrodes, for the controlled growth of nanowire. Non-uniform electric field and dielectrophoretic force is created in between two metal electrodes, patterned by electron beam lithography process. Suspended CuTCNQ nanowires have been grown laterally between two electrodes in the vicinity of electric field and dielectric force by applying external bias. Growth and diameter dependence of the nanowires on external bias has been investigated in the framework of these two forces by COMSOL Multiphysics simulation. This report will help successful in-situ nanodevice fabrication with constrained number of NW and diameter without any post treatment.

Keywords: nanowire, dielectrophoretic force, confined growth, controlled diameter, comsol multiphysics simulation

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Authors: Srinivasan Chandrasekaran, Thailammai Chithambaram, Shihas A. Khader

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The early-stage damage detection in offshore structures requires continuous structural health monitoring and for the large area the position of sensors will also plays an important role in the efficient damage detection. Determining the dynamic behavior of offshore structures requires dense deployment of sensors. The wired Structural Health Monitoring (SHM) systems are highly expensive and always needs larger installation space to deploy. Wireless sensor networks can enhance the SHM system by deployment of scalable sensor network, which consumes lesser space. This paper presents the results of wireless sensor network based Structural Health Monitoring method applied to a scaled experimental model of offshore structure that underwent wave loading. This method determines the serviceability of the offshore structure which is subjected to various environment loads. Wired and wireless sensors were installed in the model and the response of the scaled BLSRP model under wave loading was recorded. The wireless system discussed in this study is the Raspberry pi board with Arm V6 processor which is programmed to transmit the data acquired by the sensor to the server using Wi-Fi adapter, the data is then hosted in the webpage. The data acquired from the wireless and wired SHM systems were compared and the design of the wireless system is verified.

Keywords: condition assessment, damage detection, structural health monitoring, structural response, wireless sensor network

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Authors: Tinomuvonga Manenji Zhou, Eubert Mahofa, Tatenda Crispen Madzokere

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The nanostructured formulation can increase fertilizer efficacy and uptake ratio of the soil nutrients in agriculture production and save fertilizer resources. Controlled release modes have properties of both release rate and release pattern of nutrients, for fertilizers that are soluble in water might be correctly controlled. Nanoparticles can reduce the rate at which fertilizer nutrients are in the soil by leaching. A slow release NPK-hydroxyapatite nano hybrid fertilizer was synthesized using exfoliated bentonite as filler material. A simple, scalable method was used to synthesize the nitrogen-phosphorus hydroxyapatite nano fertilizer, where calcium hydroxide, phosphoric acid, and urea were used as precursor material, followed by the incorporation of potassium through a liquid grinding method. The product obtained was an NPK-hydroxyapatite nano hybrid fertilizer. A quantitative analysis was done to determine the percentage of nitrogen, phosphorus, and potassium in the hybrid fertilizer. AAS was used to determine the percentage of potassium in the fertilizer. An accelerated water test was conducted to compare the nutrient release behavior of nutrients between the synthesized NPK-hydroxyapatite nano hybrid fertilizer and commercial NPK fertilizer. The rate of release of Nitrogen, phosphorus, and potassium was significantly lower in the synthesized NPK hydroxyapatite nano hybrid fertilizer than in the convectional NPK fertilizer. The synthesized fertilizer was characterized using XRD. NPK hydroxyapatite nano hybrid fertilizer encapsulated in exfoliated bentonite thus prepared can be used as an environmentally friendly fertilizer formulation which could be extended to solve one of the major problems faced in the global fertilization of low nitrogen, phosphorus, and potassium use efficiency in agriculture.

Keywords: NPK hydroxyapatite nano hybrid fertilizer, bentonite, encapsulation, low release

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Authors: Marrone Silverio Melo Dantas Pedro Henrique Dreyer, Gabriel Fonseca Reis de Souza, Daniel Bezerra, Ricardo Souza, Silvia Lins, Judith Kelner, Djamel Fawzi Hadj Sadok

Abstract:

The creation of a dataset is time-consuming and often discourages researchers from pursuing their goals. To overcome this problem, we present and discuss two solutions adopted for the automation of this process. Both optimize valuable user time and resources and support video object segmentation with object tracking and 3D projection. In our scenario, we acquire images from a moving robotic arm and, for each approach, generate distinct annotated datasets. We evaluated the precision of the annotations by comparing these with a manually annotated dataset, as well as the efficiency in the context of detection and classification problems. For detection support, we used YOLO and obtained for the projection dataset an F1-Score, accuracy, and mAP values of 0.846, 0.924, and 0.875, respectively. Concerning the tracking dataset, we achieved an F1-Score of 0.861, an accuracy of 0.932, whereas mAP reached 0.894. In order to evaluate the quality of the annotated images used for classification problems, we employed deep learning architectures. We adopted metrics accuracy and F1-Score, for VGG, DenseNet, MobileNet, Inception, and ResNet. The VGG architecture outperformed the others for both projection and tracking datasets. It reached an accuracy and F1-score of 0.997 and 0.993, respectively. Similarly, for the tracking dataset, it achieved an accuracy of 0.991 and an F1-Score of 0.981.

Keywords: RJ45, automatic annotation, object tracking, 3D projection

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Authors: Saskya E. Carrera P., Ben Hankamer, Melanie Oey

Abstract:

The green alga C. reinhardtii provides a platform for the cheap, scalable, and safe production of complex proteins. Despite gene expression in photosynthetic organisms being tightly regulated by light, most expression studies have analysed chloroplast recombinant protein production under constant light. Here the influence of illumination time and intensity on GFP and a GFP-PlyGBS (bacterial-lysin) fusion protein expression was investigated. The expression of both proteins was strongly influenced by the light regime (6-24 hr illumination per day), the light intensity (0-450 E m⁻²s⁻¹) and growth condition (photoautotrophic, mixotrophic and heterotrophic). Heterotrophic conditions resulted in relatively low recombinant protein yields per unit volume, despite high protein yields per cell, due to low growth rates. Mixotrophic conditions exhibited the highest yields at 6 hrs illumination at 200µE m⁻²s⁻¹ and under continuous low light illumination (13-16 mg L⁻¹ GFP and 1.2-1.6 mg L⁻¹ GFP-PlyGBS), as these conditions supported good cell growth and cellular protein yields. A ~23-fold increase in protein accumulation per cell and ~9-fold increase L⁻¹ culture was observed compared to standard constant 24 hr illumination for GFP-PlyGBS. The highest yields under photoautotrophic conditions were obtained under 9 hrs illumination (6 mg L⁻¹ GFP and 2.1 mg L⁻¹ GFP-PlyGBS). This represents a ~4-fold increase in cellular protein accumulation for GFP-PlyGBS. On a volumetric basis the highest yield was at 15 hrs illumination (~2-fold increase L⁻¹ over the constant light for GFP-PlyGBS). Optimising illumination conditions to balance growth and protein expression can thus significantly enhance overall recombinant protein production in C. reinhardtii cultures.

Keywords: chlamydomonas reinhardtii, light, mixotrophic, recombinant protein

Procedia PDF Downloads 226

Authors: Simone Rondelli, Damiano Rondelli, Bishesh Poudyal, Juan Jose Cabrera-Lazarini

Abstract:

One of the main obstacles for Social Entrepreneurship is to find a business model that is financially sustainable. In other words, the captured value generates enough cash flow to ensure business continuity and reinvestment for growth. Providing Health Services in poor countries for the uninsured population affected by a high-cost chronical disease is not the exception for this challenge. As a prime example, cancer has become a high impact on a global disease not only because of the high morbidity but also of the financial impact on both the patient family and health services in underdeveloped countries. Therefore, it is relevant to find a Social Entrepreneurship Model that provides affordable treatment for this disease while maintaining healthy finances not only for the patient but also for the organization providing the treatment. Using the methodology of Constructive Research, this paper applied a Positive Theory and four business models of Social Entrepreneurship to a case of a Private Foundation model whose mission is to address the challenge previously described. It was found that the Foundation analyzed, in this case, is organized as an Embedded Business Model and complies with the four propositions of the Positive Theory considered. It is recommended for this Private Foundation to explore implementing the Integrated Business Model to ensure more robust sustainability in the long term. It evolves as a scalable model that can attract investors interested in contributing to expanding this initiative globally.

Keywords: affordable treatment, global healthcare, social entrepreneurship theory, sustainable business model

Procedia PDF Downloads 113

Authors: Azeez Shaik, Amit Salvi, B. P. Gautham

Abstract:

Fiber reinforced polymer resin composite materials are finding wide variety of applications in automotive and aerospace industry because of their high specific stiffness and specific strengths when compared to metals. New class of 2D and 3D textile and woven fabric composites offer excellent fracture toughens as they bridge the cracks formed during fracture. Due to complexity of their fiber architectures and its resulting composite microstructures, optimized design and analysis of these structures is very complicated. A traditional homogenization approach is typically used to analyze structures made up of these materials. This approach usually fails to predict damage initiation as well as damage propagation and ultimate failure of structure made up of woven and textile composites. This study demonstrates a methodology to analyze woven and textile composites by using the multi-level multi-scale modelling approach. In this approach, a geometric repetitive unit cell (RUC) is developed with all its constituents to develop a representative volume element (RVE) with all its constituents and their interaction modeled correctly. The structure is modeled based on the RUC/RVE and analyzed at different length scales with desired levels of fidelity incorporating the damage and failure. The results are passed across (up and down) the scales qualitatively as well as quantitatively from the perspective of material, configuration and architecture.

Keywords: cohesive zone, multi-scale modeling, rate dependency, RUC, woven textiles

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Authors: Sekkal Nawel

Abstract:

The Web of Things (WoT), integration of smart technologies from the Internet or network to Web architecture or application, is becoming more complex, larger, and dynamic. The WoT is associated with various elements such as sensors, devices, networks, protocols, data, functionalities, and architectures to perform services for stakeholders. These services operate in the context of the interaction of stakeholders and the WoT elements. Such context is becoming a key information source from which data are of various nature and uncertain, thus leading to complex situations. In this paper, we take interest in the development of intelligent Web services. The key ingredients of this “intelligent” notion are the context diversity, the necessity of a semantic representation to manage complex situations and the capacity to reason with uncertain data. In this perspective, we introduce a multi-layered architecture based on a generic intelligent Web service model dealing with various contexts, which proactively predict future situations and reactively respond to real-time situations in order to support decision-making. For semantic context data representation, we use PR-OWL, which is a probabilistic ontology based on Multi-Entity Bayesian Networks (MEBN). PR-OWL is flexible enough to represent complex, dynamic, and uncertain contexts, the key requirements of the development for the intelligent Web services. A case study was carried out using the proposed architecture for intelligent plant watering to show the role of proactive and reactive contextual reasoning in terms of WoT.

Keywords: smart web service, the web of things, context reasoning, proactive, reactive, multi-entity bayesian networks, PR-OWL

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Authors: Nathaniel Carpenter

Abstract:

Web-enabled systems for supporting youth mental health management in Australia are pioneering in their field; however, with their success, these systems are experiencing exponential growth in demand which is straining an already stretched service. Supporting youth mental is critical as the lack of support is associated with significant and lasting negative consequences. To meet this growing demand, and provide critical support, investigations are needed on evaluating and improving existing online support services. Improvements should focus on developing frameworks capable of augmenting and scaling service provisions. There are few investigations informing best-practice frameworks when implementing e-mental health support systems for youth mental health; there are fewer which implement machine learning or artificially intelligent systems to facilitate the delivering of services. This investigation will use a case study methodology to highlight the design features which are important for systems to enable young people to self-manage their mental health. The investigation will also highlight the current information system challenges, to include challenges associated with service quality, provisioning, and scaling. This work will propose methods of meeting these challenges through improved design, service augmentation and automation, service quality, and through artificially intelligent inspired solutions. The results of this study will inform a framework for supporting youth mental health with intelligent and scalable web-enabled technologies to support an ever-growing user base.

Keywords: artificial intelligence, information systems, machine learning, youth mental health

Procedia PDF Downloads 87

Authors: Amrutha Jayan

Abstract:

The cities are attractors of the human population, offering opportunities for economic activities for different linguistic, cultural, and ethnic groups. The urban form and design of the city impact the life of these people. Social and cultural exclusions result in spatial segregation and gentrification. The spaces provided in cities must be inclusive for all these communities for them to feel part of the city and contribute to society. Intercultural urbanism is a theory and practice of city building, planning, and design of urban spaces and architectures that are cognizant of the social impact of the built environment. The postulate acknowledges cultural differences and opportunities for cultural exchange. Literature on intercultural urbanism, culture and space, spatial justice, and cultural inclusion are analyzed to identify parameters contributing to intercultural placemaking. A qualitative study on Mattancherry shows how the precinct has sustained throughout the years with different communities living together within a radius of 5 km, creating a diverse and vibrant environment. The research identifies the urban elements that contribute to intercultural interactions and maintain the synergy between these communities. The public spaces, porous edges, built-form, streets, and accessibility contribute to chance encounters and intercultural interactivity. The research seeks to find the factors that contribute to intercultural placemaking.

Keywords: intercultural urbanism, cultural inclusion, spatial justice, public space

Procedia PDF Downloads 181