Search results for: passive optical networks (PONs)

Authors: Michael Karnes, Alper Yilmaz

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This paper presents the application of the omni-modeler towards pedestrian redetection. The pedestrian redetection task creates several challenges when applying deep neural networks (DNN) due to the variety of pedestrian appearance with camera position, the variety of environmental conditions, and the specificity required to recognize one pedestrian from another. DNNs require significant training sets and are not easily adapted for changes in class appearances or changes in the set of classes held in its knowledge domain. Pedestrian redetection requires an algorithm that can actively manage its knowledge domain as individuals move in and out of the scene, as well as learn individual appearances from a few frames of a video. The Omni-Modeler is a dynamically learning few-shot visual recognition algorithm developed for tasks with limited training data availability. The Omni-Modeler adapts the knowledge domain of pre-trained deep neural networks to novel concepts with a calculated localized language encoder. The Omni-Modeler knowledge domain is generated by creating a dynamic dictionary of concept definitions, which are directly updatable as new information becomes available. Query images are identified through nearest neighbor comparison to the learned object definitions. The study presented in this paper evaluates its performance in re-identifying individuals as they move through a scene in both single-camera and multi-camera tracking applications. The results demonstrate that the Omni-Modeler shows potential for across-camera view pedestrian redetection and is highly effective for single-camera redetection with a 93% accuracy across 30 individuals using 64 example images for each individual.

Keywords: dynamic learning, few-shot learning, pedestrian redetection, visual recognition

Procedia PDF Downloads 78

Authors: Mohammad Arabi

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The development of advanced technologies in the field of signal processing and vibration analysis has enabled more accurate analysis and fault detection in electrical systems. This research investigates the application of temporal and frequency features in detecting faults in electric motor bearings, aiming to enhance fault detection accuracy and prevent unexpected failures. The use of methods such as deep learning algorithms and neural networks in this process can yield better results. The main objective of this research is to evaluate the efficiency and accuracy of methods based on temporal and frequency features in identifying faults in electric motor bearings to prevent sudden breakdowns and operational issues. Additionally, the feasibility of using techniques such as machine learning and optimization algorithms to improve the fault detection process is also considered. This research employed an experimental method and random sampling. Vibration signals were collected from electric motors under normal and faulty conditions. After standardizing the data, temporal and frequency features were extracted. These features were then analyzed using statistical methods such as analysis of variance (ANOVA) and t-tests, as well as machine learning algorithms like artificial neural networks and support vector machines (SVM). The results showed that using temporal and frequency features significantly improves the accuracy of fault detection in electric motor bearings. ANOVA indicated significant differences between normal and faulty signals. Additionally, t-tests confirmed statistically significant differences between the features extracted from normal and faulty signals. Machine learning algorithms such as neural networks and SVM also significantly increased detection accuracy, demonstrating high effectiveness in timely and accurate fault detection. This study demonstrates that using temporal and frequency features combined with machine learning algorithms can serve as an effective tool for detecting faults in electric motor bearings. This approach not only enhances fault detection accuracy but also simplifies and streamlines the detection process. However, challenges such as data standardization and the cost of implementing advanced monitoring systems must also be considered. Utilizing temporal and frequency features in fault detection of electric motor bearings, along with advanced machine learning methods, offers an effective solution for preventing failures and ensuring the operational health of electric motors. Given the promising results of this research, it is recommended that this technology be more widely adopted in industrial maintenance processes.

Keywords: electric motor, fault detection, frequency features, temporal features

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Authors: Shubham Gogri, Lucia Florescu

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Medical diagnosis and radiotherapy treatment planning using Computed Tomography (CT) rely on the quantitative accuracy and quality of the CT images. At the same time, requirements for CT imaging include reducing the radiation dose exposure to patients and minimizing scanning time. A solution to this is the sparse-view CT technique, based on a reduced number of projection views. This, however, introduces a new problem— the incomplete projection data results in lower quality of the reconstructed images. To tackle this issue, deep learning methods have been applied to enhance the quality of the sparse-view CT images. A first approach involved employing Mir-Net, a dedicated deep neural network designed for image enhancement. This showed promise, utilizing an intricate architecture comprising encoder and decoder networks, along with the incorporation of the Charbonnier Loss. However, this approach was computationally demanding. Subsequently, a specialized Generative Adversarial Network (GAN) architecture, rooted in the Pix2Pix framework, was implemented. This GAN framework involves a U-Net-based Generator and a Discriminator based on Convolutional Neural Networks. To bolster the GAN's performance, both Charbonnier and Wasserstein loss functions were introduced, collectively focusing on capturing minute details while ensuring training stability. The integration of the perceptual loss, calculated based on feature vectors extracted from the VGG16 network pretrained on the ImageNet dataset, further enhanced the network's ability to synthesize relevant images. A series of comprehensive experiments with clinical CT data were conducted, exploring various GAN loss functions, including Wasserstein, Charbonnier, and perceptual loss. The outcomes demonstrated significant image quality improvements, confirmed through pertinent metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the corrected images and the ground truth. Furthermore, learning curves and qualitative comparisons added evidence of the enhanced image quality and the network's increased stability, while preserving pixel value intensity. The experiments underscored the potential of deep learning frameworks in enhancing the visual interpretation of CT scans, achieving outcomes with SSIM values close to one and PSNR values reaching up to 76.

Keywords: generative adversarial networks, sparse view computed tomography, CT image correction, Mir-Net

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Authors: Daniel Y. Abebe, Jaehyouk Choi

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There are several types of metal-based devices conceived as dampers for the seismic energy absorber whereby damages to the major structural components could be minimized for both new and existing structures. This paper aimed to develop and evaluate structural performance of slit circular shear panel damper for passive seismic energy protection by inelastic deformation. Structural evaluation was done using commercially available nonlinear FE simulation program. The main parameters considered are: diameter-to-thickness (D/t) ratio and slit length-to-width ratio (l/w). Depending on these parameters three different buckling modes and hysteretic behaviors were found: yielding prior to buckling without strength degradation, yielding prior to buckling with strength degradation, and yielding with buckling and strength degradation which forms pinching at initial displacement. The susceptible location at which the possible crack is initiated is also identified for selected specimens using rupture index.

Keywords: slit circular shear panel damper, hysteresis characteristics, slip length-to-width ratio, D/t ratio, FE analysis

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Authors: M. K. Manoj, V. Pancholi, S. K. Nath

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Microalloyed dual phase steels have been prepared by intercritical austenitisation (ICA) treatment of normalized steel at different temperature and time. Water quenching wad carried to obtain different martensite volume fraction (MVF) in DP steels. DP steels and normalized steels have been characterized by optical and scanning electron microscopy, Vickers hardness measurements and tensile properties determination. The effect of MVF and martensite morphology on mechanical properties and fracture behavior of microalloyed dual phase steels have been explained in the present work.

Keywords: dual phase steel, martensite morphology, hardness, tensile strength

Procedia PDF Downloads 330

Authors: Emanuel Teixeira, Anderson Ramos, Marisa Lourenço, Fernando J. Velez, Jon M. Peha

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This article discusses the benefit cost analysis aspects of millimetre wavebands (mmWaves) and Super High Frequency (SHF). The devaluation along the distance of the carrier-to-noise-plus-interference ratio with the coverage distance is assessed by considering two different path loss models, the two-slope urban micro Line-of-Sight (UMiLoS) for the SHF band and the modified Friis propagation model, for frequencies above 24 GHz. The equivalent supported throughput is estimated at the 5.62, 28, 38, 60 and 73 GHz frequency bands and the influence of carrier-to-noise-plus-interference ratio in the radio and network optimization process is explored. Mostly owing to the lessening caused by the behaviour of the two-slope propagation model for SHF band, the supported throughput at this band is higher than at the millimetre wavebands only for the longest cell lengths. The benefit cost analysis of these pico-cellular networks was analysed for regular cellular topologies, by considering the unlicensed spectrum. For shortest distances, we can distinguish an optimal of the revenue in percentage terms for values of the cell length, R ≈ 10 m for the millimeter wavebands and for longest distances an optimal of the revenue can be observed at R ≈ 550 m for the 5.62 GHz. It is possible to observe that, for the 5.62 GHz band, the profit is slightly inferior than for millimetre wavebands, for the shortest Rs, and starts to increase for cell lengths approximately equal to the ratio between the break-point distance and the co-channel reuse factor, achieving a maximum for values of R approximately equal to 550 m.

Keywords: millimetre wavebands, SHF band, SINR, cost benefit analysis, 5G

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Authors: Tala Toonsi, Marah Alagha, Lina Alnowaiser, Hala Rajab

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This report is about the Photomath app, which is an AI application that uses image recognition technology, specifically optical character recognition (OCR) algorithms. The (OCR) algorithm translates the images into a mathematical equation, and the app automatically provides a step-by-step solution. The application supports decimals, basic arithmetic, fractions, linear equations, and multiple functions such as logarithms. Testing was conducted to examine the usage of this app, and results were collected by surveying ten participants. Later, the results were analyzed. This paper seeks to answer the question: To what level the artificial intelligence features are accurate and the speed of process in this app. It is hoped this study will inform about the efficiency of AI in Photomath to the users.

Keywords: photomath, image recognition, app, OCR, artificial intelligence, mathematical equations.

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Authors: Mingmei Zhang, Xinyong Li

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AgInS₂/SnS₂ (AIS) nanocomposites were synthesized by a simple hydrothermal method. The morphology and composition of the fabricated AIS nanocomposites were investigated by field-emission scanning electron microscopy (SEM), X-ray diffraction (XRD), high resolution transmission electron microscopy (HRTEM) and X-ray photoelectron spectroscopy (XPS). Moreover, the as-prepared AIS photocatalysts exhibited excellent photocatalytic activities for the degradation of Norfloxacin (NOR), mainly due to its high optical absorption and separation efficiency of photogenerated electron-hole pairs, as evidenced by UV–vis diffusion reflection spectra (DRS) and Surface photovoltage (SPV) spectra. Furthermore, the interfacial charges transfer mechanism was also discussed by DFT calculations.

Keywords: AIS nanocomposites, electron-hole pairs, charges transfer, DFTcaculations

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Authors: Monica Plechero

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Many firms belonging to Italian industrial districts faced a crisis starting from 2000 and upsurging during 2008-2014. To remain competitive in the global market, these firms and their local systems need to renovate their traditional competitive advantages, strengthen their link with global flows of knowledge. This may be particularly relevant in sectors such as the mechatronics, that combine traditional knowledge domain with new knowledge domains (e.g. mechanics, electronics, and informatics). This sector is nowadays one of the key sectors within the so-called ‘smart specialization strategy’ that can lead part of the Italian traditional industry towards new economic developmental opportunities. This paper, by investigating the mechatronics district of the Veneto region, wants to shed new light on how firms of a local system can gain from the globalization of innovation and innovation networks. Methodologically, the paper relies on primary data collected through a survey targeting firms of the local system, as well as on a number of qualitative case studies. The relevant role of medium size companies in the district emerges as evident, as they have wider opportunities to be involved in different processes of globalization of innovation. Indeed, with respect to small companies, the size of medium firms allows them to exploit strategically international markets and globally distributed knowledge. Supporting medium firms’ global innovation strategies, and incentivizing their role as district gatekeepers, may strengthen the competitive capability of the local system and provide new opportunities to positively face global competition.

Keywords: global innovation network, industrial district, internationalization, innovation, mechatronics, Veneto region

Procedia PDF Downloads 231

Authors: M. Moayeri, A. Kaflou

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Decreasing the size of heat exchangers in industries is favorable due to a reduction in the initial costs and maintenance. This can be achieved generally by increasing the heat transfer coefficient, which can be done by increasing tube surface by passive methods named “porous coat”. Since these coatings are often in contact with the fluid, mechanical strength of coatings should be considered as main concept beside permeability and porosity in design, especially in high velocity services. Powder shape affected mechanical property more than other factors. So in this study, the Copper powder with three different shapes (spherical, dendritic and irregular) was coated on Cu-Ni base metal with thickness of ~300µm in a reduction atmosphere (5% H2-N2) and programmable furnace. The morphology and physical properties of coatings, such as porosity, permeability and mechanical strength were investigated. Results show although irregular particle have maximum porosity and permeability but strength level close to spherical powder, in addition, mentioned particle has low production cost, so for creating porous coats in high velocity services these powder recommended.

Keywords: porous coat, permeability, mechanical strength, porosity

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Authors: Xiaojie Jiang, Wei Cai, Yinxiao Xiang, Ni Zhang, Mengxin Ren, Xinzheng Zhang, Jingjun Xu

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Reflection phase of graphene plasmons (GPs) at an abrupt interface is very important, which determines the plasmon resonance of graphene structures of deep sub-wavelength scales. However, at an abrupt graphene edge, the reflection phase is always a constant, ΦR ≈ π/4. In this work, we show that the reflection phase of GPs can be efficiently changed through substrate design. Reflection phase of graphene plasmons (GPs) at an abrupt interface is very important, which determines the plasmon resonance of graphene structures of deep sub-wavelength scales. However, at an abrupt graphene edge, the reflection phase is always a constant, ΦR ≈ π/4. In this work, we show that the reflection phase of GPs can be efficiently changed through substrate design. Specifically, the reflection phase is no longer π/4 at the interface formed by placing a graphene sheet on different substrates. Moreover, tailorable reflection phase of GPs up to 2π variation can be further achieved by scattering GPs at a junction consisting of two such dielectric interfaces with various gap width acting as a Fabry-Perot cavity. Besides, the evolution of plasmon mode in graphene ribbons based on the interface reflection phase tuning is predicted, which is expected to be observed in near-field experiments with scattering-type scanning near-field optical microscopy (s-SNOM). Our work provides another way for in-plane plasmon control, which should find applications for integrated plasmon devices design using graphene.Specifically, the reflection phase is no longer π/4 at the interface formed by placing a graphene sheet on different substrates. Moreover, tailorable reflection phase of GPs up to 2π variation can be further achieved by scattering GPs at a junction consisting of two such dielectric interfaces with various gap width acting as a Fabry-Perot cavity. Besides, the evolution of plasmon mode in graphene ribbons based on the interface reflection phase tuning is predicted, which is expected to be observed in near-field experiments with scattering-type scanning near-field optical microscopy (s-SNOM). Our work provides a new way for in-plane plasmon control, which should find applications for integrated plasmon devices design using graphene.

Keywords: graphene plasmons, reflection phase tuning, plasmon mode tuning, Fabry-Perot cavity

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Authors: R. Geetha, J. Arunkumar, P. Gopal, D. Loganathan, K. Pavithra, C. Vikashini

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Mobile Number Portability is an attempt to switch over from one network to another network facility for mobile based on applications. This facility is currently not available for mobile handsets. This application is intended to assist the mobile network and its service customers in understanding the criteria; this will serve as a universal set of requirements which must be met by the customers. This application helps the user's network portability. Accessing permission from the network provider to enable services to the user and utilizing the available network signals. It is enabling the user to make a temporary switch over to other network. The main aim of this research work is to adapt multiple networks at the time of no network coverage. It can be accessed at rural and geographical areas. This can be achieved by this mobile application. The application is capable of temporary switch over between various networks. With this application both the service provider and the network user are benefited. The service provider is benefited by charging a minimum cost for utilizing other network. It provides security in terms of password that is unique to avoid unauthorized users and to prevent loss of balance. The goal intended to be attained is a complete utilization of available network at significant situations and to provide feature that satisfy the customer needs. The temporary switch over is done to manage emergency calls when user is in rural or geographical area, where there will be a very low network coverage. Since people find it trend in using Android mobile, this application is designed as an Android applications, which can be freely downloaded and installed from Play store. In the current scenario, the service provider enables the user to change their network without shifting their mobile network. This application affords a clarification for users while they are jammed in a critical situation. This application is designed by using Android 4.2 and SQLite Version3.

Keywords: mobile number, random number, alarm, imei number, call

Procedia PDF Downloads 364

Authors: M. K. Wijayarathna, S. M. Buddika Harshanath

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Monitoring student engagement has become a crucial part of the educational process and a reliable indicator of the capacity to retain information. As online learning classrooms are now more common these days, students' attention levels have become increasingly important, making it more difficult to check each student's concentration level in an online classroom setting. To profile student attention to various gradients of engagement, a study is a plan to conduct using machine learning models. Using a convolutional neural network, the findings and confidence score of the high accuracy model are obtained. In this research, convolutional neural networks are using to help discover essential emotions that are critical in defining various levels of participation. Students' attention levels were shown to be influenced by emotions such as calm, enjoyment, surprise, and fear. An improved virtual learning system was created as a result of these data, which allowed teachers to focus their support and advise on those students who needed it. Student participation has formed as a crucial component of the learning technique and a consistent predictor of a student's capacity to retain material in the classroom. Convolutional neural networks have a plan to implement the platform. As a preliminary step, a video of the pupil would be taken. In the end, researchers used a convolutional neural network utilizing the Keras toolkit to take pictures of the recordings. Two convolutional neural network methods are planned to use to determine the pupils' attention level. Finally, those predicted student attention level results plan to display on the graphical user interface of the System.

Keywords: HTML5, JavaScript, Python flask framework, AI, graphical user

Procedia PDF Downloads 101

Authors: Gunasekaran Raja, Ramkumar Jayaraman

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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.

Keywords: cross layer network topology, concurrent scheduling, modularity value, network communities and weighted load balancing

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Authors: Demet Ozgur-Unluakin, Busenur Turkali, Ayse Karacaorenli

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Maintenance strategies can be classified into two types, which are reactive and proactive, with respect to the time of the failure and maintenance. If the maintenance activity is done after a breakdown, it is called reactive maintenance. On the other hand, proactive maintenance, which is further divided as preventive and predictive, focuses on maintaining components before a failure occurs to prevent expensive halts. Recently, the number of interacting components in a system has increased rapidly and therefore, the structure of the systems have become more complex. This situation has made it difficult to provide the right maintenance decisions. Herewith, determining effective decisions has played a significant role. In multi-component systems, many methodologies and strategies can be applied when a component or a system has already broken down or when it is desired to identify and avoid proactively defects that could lead to future failure. This study focuses on the comparison of various maintenance strategies on a multi-component dynamic system. Components in the system are hidden, although there exists partial observability to the decision maker and they deteriorate in time. Several predefined policies under corrective, preventive and predictive maintenance strategies are considered to minimize the total maintenance cost in a planning horizon. The policies are simulated via Dynamic Bayesian Networks on a multi-component system with different policy parameters and cost scenarios, and their performances are evaluated. Results show that when the difference between the corrective and proactive maintenance cost is low, none of the proactive maintenance policies is significantly better than the corrective maintenance. However, when the difference is increased, at least one policy parameter for each proactive maintenance strategy gives significantly lower cost than the corrective maintenance.

Keywords: decision making, dynamic Bayesian networks, maintenance, multi-component systems, reliability

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Authors: Zhou Xiaowen China, Zhang Sanming China

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Neighbourhood space as a very important part of city spaces, is an organic combination of material environment and spiritual achievement in people’ daily life, and has a real impact upon the sustainable development of the whole city. Looking back on the past 2014 World Architecture Festival (WAF), 4 out of 35winning buildings were neighbourhood designs, and all of them mentioned about space-sharing and sustainable development. In this paper, three award-winning cases were studied, including the world building of the year—the chapel (Vietnam, A21 studio), The Carve (Norway, A-Lab) and House for Trees (Vietnam, Vo Trong Nghia Architects). Urban context, planning, space construction and sustainable technology were discussed. Based on those, it was discovered that passive energy-saving technologies have been paid more and more attention, sharing space has been designed ingeniously, and the architectural forms of them reflect social inclusion and equity. This paper is aimed at summarizing the excellent works on the Festival and providing reference for the future design.

Keywords: neighbourhood design, 2014 World Architecture Festival (WAF), sustainable development, space-sharing

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Authors: Mao Li, Yuguang Ma, Katsuhiko Ariga

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The performance of functional materials is governed by their ability to interact with surrounding environments in a well-defined and controlled manner. Layer-by-Layer (LbL) assembly is one of the most widely used technologies for coating both planar and particulate substrates in a diverse range of fields, including optics, energy, catalysis, separations, and biomedicine. Herein, we introduce electrochemical-coupling layer-by-layer assembly as a novel fabrication methodology for preparing layered thin films. This assembly method not only determines the process properties (such as the time, scalability, and manual intervention) but also directly control the physicochemical properties of the films (such as the thickness, homogeneity, and inter- and intra-layer film organization), with both sets of properties linked to application-specific performance.

Keywords: layer by layer assembly, electropolymerization, carbazole, optical thin film, electronics

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Authors: Johannes Dregger, Michael Schmidt, Christian Prasse, Michael ten Hompel

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Most of the today’s companies face increasing need to operate efficiently. Driven by global trends like shorter product cycles, mass customization and the rising speed of delivery, manufacturing value chains are becoming more and more distributed. Manufacturing processes are becoming highly integrated, e.g. 3D printing. All these changes are affecting companies´ organization. They are leading towards individual, small scale, and ad-hoc logistics processes and structures, and finally, towards a significant increase in the importance of logistics itself since traditional value chains transform into agile value networks. In the past logistics has been following manufacturing but in the future industry, this role allocation might change. With this increase in the logistics practice of companies and businesses, the relevance of logistics research as the methodological foundation of logistics networks and processes is gaining importance. Logistics research is evolving into a central and highly interdisciplinary science for the future industry. Using the example of Germany, this paper discusses ways to establish logistics as a central scientific discipline of the future industry. About three million people work in the logistics sector in Germany. Only automotive and retail industry have more employees. Even though there is a bunch of logistics degree programs at more than 100 institutions of higher education, a common understanding of logistics as a research discipline is missing. In this paper an innovative approach will be presented, including; identified perspectives on logistics, such as process orientation, IT orientation or employees orientation, relevant scientific disciplines for logistics science, a concept for interdisciplinary research approaches to unify the perspectives of the different scientific disciplines on logistics and the methodological base of logistics science.

Keywords: logistics, logistics science, logistics management, future challenges

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Authors: Jayashree Das, V. V. Srinivasu , D. K. Mishra, A. Maity

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Owing to the important potential applications over decades, transition metal (TM: Mn, Fe, Ni, Cu, Cr, V etc.) doped ZnO-based diluted magnetic semiconductors (DMS) always attract research attention for more and newer investigations. One of the interesting aspects of these materials is to study and understand the magnetic property at room temperature properly, which is very crucial to select a material for any related application. In this regard, Electron spin resonance (ESR) study has been proven to be a powerful technique to investigate the spin dynamics of electrons inside the system, which are responsible for the magnetic behaviour of any system. ESR as well as the Raman and Photoluminescence spectroscopy studies are also helpful to study the defects present or created inside the system in the form of oxygen vacancy or cluster instrumental in determining the room temperature ferromagnetic property of transition metal doped ZnO system, which can be controlled through varying dopant concentration, appropriate synthesis technique and sintering of the samples. For our investigation, we synthesised Cu-doped ZnO nanocrystalline samples with composition Zn1-xCux ( 0.005< x < 0.05) by pyrophoric method and sintered at a low temperature of 650 0C. The microwave absorption is studied by the Electron Spin Resonance (ESR) of X-band (9.46 GHz) at room temperature. Systematic analysis of the obtained ESR spectra reveals that all the compositions of Cu-doped ZnO samples exhibit resonance signals of appreciable line widths and g value ~ 2.2, typical characteristic of ferromagnetism in the sample. Raman scattering and the photoluminescence study performed on the samples clearly indicated the presence of pronounced defect related peaks in the respective spectra. Cu doping in ZnO with varying concentration also observed to affect the optical band gap and the respective absorption edges in the UV-Vis spectra. FTIR spectroscopy reveals the Cu doping effect on the stretching bonds of ZnO. To probe into the structural and morphological changes incurred by Cu doping, we have performed XRD, SEM and EDX study, which confirms adequate Cu substitution without any significant impurity phase formation or lattice disorder. With proper explanation, we attempt to correlate the results observed for the structural optical and magnetic behaviour of the Cu-doped ZnO samples. We also claim that our result can be instrumental for appropriate applications of transition metal doped ZnO based DMS in the field of optoelectronics and Spintronics.

Keywords: diluted magnetic semiconductors, electron spin resonance, raman scattering, spintronics.

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Authors: Alaa Allakany, Koji Okamura

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Multicast technology is an efficient and scalable technology for data distribution in order to optimize network resources. However, in the IP network, the responsibility for management of multicast groups is distributed among network routers, which causes some limitations such as delays in processing group events, high bandwidth consumption and redundant tree calculation. Software Defined Networking (SDN) represented by OpenFlow presented as a solution for many problems, in SDN the control plane and data plane are separated by shifting the control and management to a remote centralized controller, and the routers are used as a forwarder only. In this paper we will proposed fast switching mechanism for solving the problem of link failure in multicast tree based on Tabu Search heuristic algorithm and modifying the functions of OpenFlow switch to fasts switch to the pack up sub tree rather than sending to the controller. In this work we will implement multicasting OpenFlow controller, this centralized controller is a core part in our multicasting approach, which is responsible for 1- constructing the multicast tree, 2- handling the multicast group events and multicast state maintenance. And finally modifying OpenFlow switch functions for fasts switch to pack up paths. Forwarders, forward the multicast packet based on multicast routing entries which were generated by the centralized controller. Tabu search will be used as heuristic algorithm for construction near optimum multicast tree and maintain multicast tree to still near optimum in case of join or leave any members from multicast group (group events).

Keywords: multicast tree, software define networks, tabu search, OpenFlow

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Authors: Eyyüp Murat Karakurt, Yan Huang, Mehmet Kaya, Hüseyin Demirtaş, Alper İncesu

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In this study, Ti-(x) Nb (at. %) master alloys (x:10, 20, and 30) were fabricated following a standard powder metallurgy route and were sintered at 1200 ˚C for 6h, under 300 MPa by powder metallurgy method. The effect of the Nb concentration in Ti matrix and porosity level was examined experimentally. For metallographic examination, the alloys were analysed by optical microscopy and energy dispersive spectrometry analysis. In addition, X-ray diffraction was performed on the alloys to determine which compound formed in the microstructure. The compression test was applied to the alloys to understand the mechanical behaviors of the alloys. According to Nb concentration in Ti matrix, the β phase increased. Also, porosity level played a crucial role on the mechanical performance of the alloys.

Keywords: Nb concentration, porosity level, powder metallurgy, The β phase

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Authors: Brahim Bellali, Fatima Bellali

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The integration of information technology systems (ITS) into a company's human resources processes seems to be the appropriate solution to the problem of evolving and adapting its human resources management practices in order to be both more strategic and more efficient in terms of costs and service quality. In this context, the aim of this work is to study the impact of information technology systems (ITS) on the recruitment process. In this study, we targeted candidates who had recruited using IT tools. The target population consists of 34 candidates based in Casablanca, Morocco. In order to collect the data, a questionnaire had to be drawn up. The survey is based on a data sheet and a questionnaire that is divided into several sections to make it more structured and comprehensible. The results show that the majority of respondents say that companies are making greater use of online CV libraries and social networks as digital solutions during the recruitment process. The results also show that 50% of candidates say that the use of digital tools by companies would not slow them down when applying for a job and that these IT tools improve manual recruitment processes, while 44.1% think that they facilitate recruitment without any human intervention. The majority of respondents (52.9%) think that social networks are the digital solutions most often used by recruiters in the sourcing phase. The constraints of digital recruitment encountered are the dehumanization of human resources (44.1%) and the limited interaction during remote interviews (44.1%), which leaves no room for informal exchanges. Digital recruitment can be a highly effective strategy for finding qualified candidates in a variety of fields. Here are a few recommendations for optimizing your digital recruitment process: (1) Use online recruitment platforms: LinkedIn, Twitter, and Facebook ; (2) Use applicant tracking systems (ATS) ; (3) Develop a content marketing strategy.

Keywords: IT systems, recruitment, challenges, constraints

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Authors: Chapman Eze Nnadozie

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Cloud computing, a technology that is made possible through virtualization within networks represents a shift from the traditional ownership of infrastructure and other resources by distinct organization to a more scalable pattern in which computer resources are rented online to organizations on either as a pay-as-you-use basis or by subscription. In other words, cloud computing entails the renting of computing resources (such as storage space, memory, servers, applications, networks, etc.) by a third party to its clients on a pay-as-go basis. It is a new innovative technology that is globally embraced because of its renowned benefits, profound of which is its cost effectiveness on the part of organizations engaged with its services. In Nigeria, the services are provided either directly to companies mostly by the key IT players such as Microsoft, IBM, and Google; or in partnership with some other players such as Infoware, Descasio, and Sunnet. This action enables organizations to rent IT resources on a pay-as-you-go basis thereby salvaging them from wastages accruable on acquisition and maintenance of IT resources such as ownership of a separate data centre. This paper intends to appraise the challenges of cloud computing adoption in Nigeria, bearing in mind the country’s peculiarities’ in terms of infrastructural development. The methodologies used in this paper include the use of research questionnaires, formulated hypothesis, and the testing of the formulated hypothesis. The major findings of this paper include the fact that there are some addressable challenges to the adoption of cloud computing in Nigeria. Furthermore, the country will gain significantly if the challenges especially in the area of infrastructural development are well addressed. This is because the research established the fact that there are significant gains derivable by the adoption of cloud computing by organizations in Nigeria. However, these challenges can be overturned by concerted efforts in the part of government and other stakeholders.

Keywords: cloud computing, data centre, infrastructure, it resources, virtualization

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Authors: Muhammet Baldan, Emel Timuçin

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Molecular solubility prediction plays a crucial role in various fields, such as drug discovery, environmental science, and material science. In this study, we compare the performance of five machine learning algorithms—linear regression, support vector machines (SVM), random forests, gradient boosting machines (GBM), and neural networks—for predicting molecular solubility using the AqSolDB dataset. The dataset consists of 9981 data points with their corresponding solubility values. MACCS keys (166 bits), RDKit properties (20 properties), and structural properties(3) features are extracted for every smile representation in the dataset. A total of 189 features were used for training and testing for every molecule. Each algorithm is trained on a subset of the dataset and evaluated using metrics accuracy scores. Additionally, computational time for training and testing is recorded to assess the efficiency of each algorithm. Our results demonstrate that random forest model outperformed other algorithms in terms of predictive accuracy, achieving an 0.93 accuracy score. Gradient boosting machines and neural networks also exhibit strong performance, closely followed by support vector machines. Linear regression, while simpler in nature, demonstrates competitive performance but with slightly higher errors compared to ensemble methods. Overall, this study provides valuable insights into the performance of machine learning algorithms for molecular solubility prediction, highlighting the importance of algorithm selection in achieving accurate and efficient predictions in practical applications.

Keywords: random forest, machine learning, comparison, feature extraction

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Authors: Caroline Jones

Abstract:

Research over the last decade suggests that there have been distinct changes in both women’s sexual behaviour and attitudes towards female sexuality in the UK. Areas such as discussing sex, participating in sexual activity outside of traditional monogamous relationships, and engaging in boudoir photography have all been explored by researchers. Women’s participation in tantric practices, however, is a relatively unexplored area of sexuality, despite an increasing number of Tantra schools opening in the UK. Tantra is a practice in which women are considered to have a higher consciousness than men, where the sexual role of women is deemed to be very different to a traditional Western sexually passive role. This research looks at this area, and is based on in-depth, semi-structured, thematically analysed interviews with women who have participated in tantric workshops and/or retreats across the country. The interviews investigate why women engage with such practices, what they feel they gain from the experience, and how shifting notions of appropriate sexual roles for women impact on their sexuality and life generally. While Tantra is still a minority activity in the UK, the findings shed light on not only these areas but also on women’s constructions of their sexuality, their relationships with their bodies and sexualities, and ways in which they express and engage with changing notions of female sexuality.

Keywords: sexuality, Tantra, gender, Shakti

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Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

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Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: fake news detection, natural language processing, machine learning, classification techniques.

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Authors: Mohsen Yaghmoor, Sima Radmanesh, Ameneh Gholami

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Cities are the principal ground for manifestation of an information society. To create an entrepreneurial city, it is required that just and equal access to opportunities are provided for all segments of the city and technologies are intelligently employed. Furthermore, it is necessary for us to be electronically ready in all political, economic, social, cultural, and technological aspects. Also e-city creates enormous potentials and opportunities for development of the entrepreneurial city. After improvement of e-readiness for establishment of entrepreneurial e-city, potentials, and capitals of the city become productive and more suitable opportunities are offered to citizens, state sectors, and private sectors in order to become entrepreneurs. To create and develop an entrepreneurial city, we need to have readiness to detection and creation of entrepreneurial opportunities and finally exploitation of these opportunities which, in turn, lead to use of entrepreneurial events and their quality in the city. In this model, the quality of entrepreneurial events, the productivity of activities, the necessity of reducing the digital gap, positive and active attendance in information society and compatibility and aligning with the global society are emphasized. In an entrepreneurial city, citizens are not help seekers, private sector is not passive, and the government is entrepreneurial.

Keywords: e-city, e-readiness, entrepreneurial city, entrepreneurial events, technological entrepreneurship

Procedia PDF Downloads 386

Authors: Eusebio Jr. Lina, Ederlina Nocon

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Cyclic codes are a fundamental subclass of linear codes that enjoy a very interesting algebraic structure. The class of skew cyclic codes (or θ-cyclic codes) is a generalization of the notion of cyclic codes. This a very large class of linear codes which can be used to systematically search for codes with good properties. A linear code with complementary dual (LCD code) is a linear code C satisfying C ∩ C^⊥ = {0}. This subclass of linear codes provides an optimum linear coding solution for a two-user binary adder channel and plays an important role in countermeasures to passive and active side-channel analyses on embedded cryptosystems. This paper aims to identify LCD codes from the class of skew cyclic codes. Let F_q be a finite field of order q, and θ be an automorphism of F_q. Some conditions for a skew cyclic code to be LCD were given. To this end, the properties of a noncommutative skew polynomial ring F_q[x, θ] of automorphism type were revisited, and the algebraic structure of skew cyclic code using its skew polynomial representation was examined. Using the result that skew cyclic codes are left ideals of the ring F_q[x, θ]/〈x^n-1〉, a characterization of a skew cyclic LCD code of length n was derived. A necessary condition for a skew cyclic code to be LCD was also given.

Keywords: LCD cyclic codes, skew cyclic LCD codes, skew cyclic complementary dual codes, theta-cyclic codes with complementary duals

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Authors: Yasin Tadayonrad

Abstract:

Most of the supply chain networks have many nodes starting from the suppliers’ side up to the customers’ side that each node sends/receives the raw materials/products from/to the other nodes. One of the major concerns in this kind of supply chain network is finding the best schedule for loading /unloading the shipments through the whole network by which all the constraints in the source and destination nodes are met and all the shipments are delivered on time. One of the main constraints in this problem is loading/unloading capacity in each source/ destination node at each time slot (e.g., per week/day/hour). Because of the different characteristics of different products/groups of products, the capacity of each node might differ based on each group of products. In most supply chain networks (especially in the Fast-moving consumer goods industry), there are different planners/planning teams working separately in different nodes to determine the loading/unloading timeslots in source/destination nodes to send/receive the shipments. In this paper, a mathematical problem has been proposed to find the best timeslots for loading/unloading the shipments minimizing the overall delays subject to respecting the capacity of loading/unloading of each node, the required delivery date of each shipment (considering the lead-times), and working-days of each node. This model was implemented on python and solved using Python-MIP on a sample data set. Finally, the idea of a heuristic algorithm has been proposed as a way of improving the solution method that helps to implement the model on larger data sets in real business cases, including more nodes and shipments.

Keywords: supply chain management, transportation, multiple-multiple network, timeslots management, mathematical modeling, mixed integer programming

Procedia PDF Downloads 92

Authors: Amirreza Niktash, B. P. Huynh

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A windcatcher is a structure fitted on the roof of a building for providing natural ventilation by using wind power; it exhausts the inside stale air to the outside and supplies the outside fresh air into the interior space of the building working by pressure difference between outside and inside of the building and using ventilation principles of passive stacks and wind tower, respectively. In this paper, the effect of different heights of inlet/outlets’ ducts of a two-sided windcatcher on the flow rate, flow velocity and flow pattern through a three-dimensional room fitted with the windcatcher are investigated and analysed by using RANS CFD technique and applying standard K-ε turbulence model via a commercial computational fluid dynamics (CFD) software package. The achieved results show that the inlet/outlet ducts height strongly affects flow rate, flow velocity and flow pattern especially in the living area of the room when the wind velocity is not too low. The results are confirmed by the experimental test for constructed scaled model in the laboratory and it develops the two-sided windcatcher’s performance in ventilation applications.

Keywords: CFD, RANS, ventilation, windcatcher

Procedia PDF Downloads 431