Search results for: passive optical networks (PON)

Authors: P. S. Jagadeesh Kumar, Yang Yung, Mingmin Pan, Xianpei Li, Wenli Hu

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Glaucoma is impelled by optic nerve mutilation habitually represented as cupping and visual field injury frequently with an arcuate pattern of mid-peripheral loss, subordinate to retinal ganglion cell damage and death. Glaucoma is the second foremost cause of blindness and the chief cause of permanent blindness worldwide. Consequently, all-embracing study into the analysis and empathy of glaucoma is happening to escort deep learning based neural network intrusions to deliberate this substantial optic neuropathy. This paper advances an ophthalmic hashing based supervision of glaucoma and corneal disorders preeminent on deep graphical model. Ophthalmic hashing is a newly proposed method extending the efficacy of visual hash-coding to predict glaucoma corneal disorder matching, which is the faster than the existing methods. Deep graphical model is proficient of learning interior explications of corneal disorders in satisfactory time to solve hard combinatoric incongruities using deep Boltzmann machines.

Keywords: corneal disorders, deep Boltzmann machines, deep graphical model, glaucoma, neural networks, ophthalmic hashing

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Authors: T. M. L. Hoang, G. Tan, S. D. Bhowmik, B. Williams, A. Johnson, M. R. Karbaschi, Y. Cheng, H. Long, S. G. Mundree

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Iron deficiency is a worldwide problem affecting both developed and developing countries. Currently, two major approaches namely iron supplementation and food fortification have been used to combat this issue. These measures, however, are limited by the economic status of the targeted demographics. Iron biofortification through genetic modification to enhance the inherent iron content and bioavailability of crops has been employed recently. Several important crops such as rice, wheat, and banana were reported successfully improved iron content via this method, but there is no known study in legumes. Chickpea (Cicer arietinum) is an important leguminous crop that is widely consumed, particularly in India where iron deficiency anaemia is prevalent. Chickpea is also an ideal pulse in the formulation of complementary food between pulses and cereals to improve micronutrient contents. This project aims at generating enhanced ion accumulation and bioavailability chickpea through the exogenous expression of genes related to iron transport and iron homeostasis in chickpea plants. Iron-Regulated Transport (IRT) and Ferritin genes in combination were transformed into chickpea half-embryonic axis by agrobacterium–mediated transformation. Transgenic independent event was confirmed by Southern Blot analysis. T3 leaves and seeds of transgenic chickpea were assessed for iron contents using LA-ICP-MS (Laser Ablation – Inductively Coupled Plasma Mass Spectrometry) and ICP-OES (Inductively Coupled Plasma Optical Emission Spectrometry). The correlation between transgene expression levels and iron content in T3 plants and seeds was assessed using qPCR. Results show that iron content in transgenic chickpea expressing the above genes significantly increased compared to that in non-transgenic controls.

Keywords: iron biofortification, chickpea, IRT, ferritin, Agrobacterium-mediated transformation, LA-ICP-MS, ICP-OES

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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Gliomas are most challenging and aggressive type of tumors which appear in different sizes, locations, and scattered boundaries. CNN is most efficient deep learning approach with outstanding capability of solving image analysis problems. A fully automatic deep learning based 2D-CNN model for brain tumor segmentation is presented in this paper. We used small convolution filters (3 x 3) to make architecture deeper. We increased convolutional layers for efficient learning of complex features from large dataset. We achieved better results by pushing convolutional layers up to 16 layers for HGG model. We achieved reliable and accurate results through fine-tuning among dataset and hyper-parameters. Pre-processing of this model includes generation of brain pipeline, intensity normalization, bias correction and data augmentation. We used the BRATS-2015, and Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.81 for complete, 0.79 for core, 0.80 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, HGG

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Authors: Najib Al-Fadhali, Huda Majid

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In this article, a substrate integrated waveguide cavity slot antenna was designed using a computer simulation technology software tool to address the specific design challenges for millimeter-wave communications posed by future satellite communications. Due to the symmetrical structure, a high-order mode is generated in SIW, which yields high gain and high efficiency with a compact feed structure. The antenna has dimensions of 20 mm x 20 mm x 1.34 mm. The proposed antenna bandwidth ranges from 45 GHz to 50 GHz, covering a Q-band application such as satellite communication. Antenna efficiency is above 80% over the operational frequency range. The gain of the antenna is above 9 dB with a peak value of 9.4 dB at 47.5 GHz. The proposed antenna is suitable for various millimeter-wave applications such as sensing, body imaging, indoor scenarios, new generations of wireless networks, and future satellite communications. The simulated results show that the SIW antenna resonates throughout the bands of 45 to 50 GHz, making this new antenna cover all applications within this range. The reflection coefficients are below 10 dB in most ranges from 45 to 50 GHz. The compactness, integrity, reliability, and performance at various operating frequencies make the proposed antenna a good candidate for future satellite communications.

Keywords: ultra-wideband, Q-band, SIW, mm-wave, satellite communications

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Authors: Farida Mellah, Abdelhak Boutaleb, Bachir Henni, Dalila Berdous, Abdelhamid Mellah

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Context/Purpose: One of the largest mining operations for lead and zinc deposits in northwestern Algeria in more than thirty years, El Abed is now the abandoned mine that has been inactive since 2004, leaving large amounts of accumulated mining waste under the influence of Wind, erosion, rain, and near agricultural lands. Materials & Methods: This study aims to verify the concentrations and sources of heavy metals for surface samples containing randomly taken soil. Chemical analyses were performed using iCAP 7000 Series ICP-optical emission spectrometer, using a set of environmental quality indicators by calculating the enrichment factor using iron and aluminum references, geographic accumulation index and geographic information system (GIS). On the basis of the spatial distribution. Results: The results indicated that the average metal concentration was: (As = 30,82),(Pb = 1219,27), (Zn = 2855,94), (Cu = 5,3), mg/Kg,based on these results, all metals except Cu passed by GBV in the Earth's crust. Environmental quality indicators were calculated based on the concentrations of trace metals such as lead, arsenic, zinc, copper, iron and aluminum. Interpretation: This study investigated the concentrations and sources of trace metals, and by using quality indicators and statistical methods, lead, zinc, and arsenic were determined from human sources, while copper was a natural source. And based on the spatial analysis on the basis of GIS, many hot spots were identified in the El-Abed region. Conclusion: These results could help in the development of future treatment strategies aimed primarily at eliminating materials from mining waste.

Keywords: soil contamination, trace metals, geochemical indices, El Abed mine, Algeria

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Authors: Lucie Bielská, Lucia Škulcová, Martina Hvězdová, Jakub Hofman, Zdeněk Šimek

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The currently used pesticides represent a broad group of chemicals with various physicochemical and environmental properties which input has reached 2×106 tons/year and is expected to even increases. From that amount, only 1% directly interacts with the target organism while the rest represents a potential risk to the environment and human health. Despite being authorized and approved for field applications, the effects of pesticides in the environment can differ from the model scenarios due to the various pesticide-soil interactions and resulting modified fate and behavior. As such, a direct monitoring of pesticide residues and evaluation of their impact on soil biota, aquatic environment, food contamination, and human health should be performed to prevent environmental and economic damages. The present project focuses on fluvisols as they are intensively used in the agriculture but face to several environmental stressors. Fluvisols develop in the vicinity of rivers by the periodic settling of alluvial sediments and periodic interruptions to pedogenesis by flooding. As a result, fluvisols exhibit very high yields per area unit, are intensively used and loaded by pesticides. Regarding the floods, their regular contacts with surface water arise from serious concerns about the surface water contamination. In order to monitor pesticide residues and assess their environmental and biological impact within this project, 70 fluvisols were sampled over the Czech Republic and analyzed for the total and bioaccessible amounts of 40 various pesticides. For that purpose, methodologies for the pesticide extraction and analysis with liquid chromatography-mass spectrometry technique were developed and optimized. To assess the biological risks, both the earthworm bioaccumulation tests and various types of passive sampling techniques (XAD resin, Chemcatcher, and silicon rubber) were optimized and applied. These data on chemical analysis and bioavailability were combined with the results of soil analysis, including the measurement of basic physicochemical soil properties as well detailed characterization of soil organic matter with the advanced method of diffuse reflectance infrared spectrometry. The results provide unique data on the residual levels of pesticides in the Czech Republic and on the factors responsible for increased pesticide residue levels that should be included in the modeling of pesticide fate and effects.

Keywords: currently used pesticides, fluvisoils, bioavailability, Quechers, liquid-chromatography-mass spectrometry, soil properties, DRIFT analysis, pesticides

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Authors: Albert Alexander Stonier

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Due to the fossil fuel exhaustion and environmental pollution, renewable energy sources especially solar photovoltaic system plays a predominant role in providing energy to the consumers. It has been estimated that by 2050 the renewable energy sources will satisfy 50% of the total energy requirement of the world. In this context, the faults in the conversion process require a special attention which is considered as a major problem. A fault which remains even for a few seconds will cause undesirable effects to the system. The presentation comprises of the analysis, causes, effects and mitigation methods of various faults occurring in the entire solar photovoltaic energy conversion process. In order to overcome the faults in the system, an intelligent based artificial neural networks and fuzzy logic are proposed which can significantly mitigate the faults. Hence the presentation intends to find the problem in renewable energy and provides the possible solution to overcome it with simulation and experimental results. The work performed in a 3kWp solar photovoltaic plant whose results cites the improvement in reliability, availability, power quality and fault tolerant ability.

Keywords: solar photovoltaic, power electronics, power quality, PWM

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Authors: Krishan Kumar, Mohit Mittal, Pramod Kumar

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Wireless sensor network is one of the most promising communication networks for monitoring remote environmental areas. In this network, all the sensor nodes are communicated with each other via radio signals. The sensor nodes have capability of sensing, data storage and processing. The sensor nodes collect the information through neighboring nodes to particular node. The data collection and processing is done by data aggregation techniques. For the data aggregation in sensor network, clustering technique is implemented in the sensor network by implementing self-organizing feature map (SOFM) neural network. Some of the sensor nodes are selected as cluster head nodes. The information aggregated to cluster head nodes from non-cluster head nodes and then this information is transferred to base station (or sink nodes). The aim of this paper is to manage the huge amount of data with the help of SOM neural network. Clustered data is selected to transfer to base station instead of whole information aggregated at cluster head nodes. This reduces the battery consumption over the huge data management. The network lifetime is enhanced at a greater extent.

Keywords: artificial neural network, data clustering, self organization feature map, wireless sensor network

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Authors: Min Jin Kwon, Seung Won Kim, Eui Yeon Kim, Haeyoung Lee

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Numerous anonymous chat apps that help people to connect with random strangers have been released in South Korea. However, they become a serious problem for young people since young people often use them for channels of prostitution or sexual violence. Although ISPs in South Korea are responsible for making inappropriate content inaccessible on their networks, they do not block traffic of random chat apps since 1) the use of random chat apps is entirely legal. 2) it is reported that they use HTTP proxy blocking so that non-HTTP traffic cannot be blocked. In this paper, we propose a service model that can block random chat apps at home routers. A service provider manages a blacklist that contains blocked apps’ information. Home routers that subscribe the service filter the traffic of the apps out using deep packet inspection. We have implemented a prototype of the proposed model, including a centralized server providing the blacklist, a Raspberry Pi-based home router that can filter traffic of the apps out, and an Android app used by the router’s administrator to locally customize the blacklist.

Keywords: deep packet inspection, internet filtering, juvenile protection, technical blocking

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Authors: Jigar Shaileshumar Halpati, Aravind Kumar Chandiran

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Vacancy ordered double perovskites (VOPs) have been significantly attracting researchers due to their chemical structure diversity and interesting optoelectronic properties. Some VOPs have been recently reported to be suitable photoelectrodes for photoelectrochemical water-splitting reactions due to their high stability and panchromatic absorption. In this work, we systematically synthesized mixed tetravalent VOPs based on Cs₂RuₘPt₁-ₘX₆ (X = Cl-, Br-) and reported their structural, optical, electrochemical and photoelectrochemical properties. The structural characterization confirms that the mixed tetravalent site intermediates formed their own phases. The parent materials, as well as their intermediates, were found to be stable in ambient conditions for over 1 year and also showed incredible stability in harsh pH media ranging from pH 1 to pH 11. Moreover, these materials showed panchromatic absorption with onset up to 1000 nm depending upon the mixture stoichiometry. The extraordinary stability and excellent absorption properties make them suitable materials for photoelectrochemical water-splitting applications. PEC studies of these series of materials showed a high water oxidation photocurrent of 0.56 mA cm-² for Cs₂Ru₀.₅Pt₀.₅Cl₆. Fundamental investigation from photoelectrochemical reactions revealed that the intrinsic ruthenium-based VOP showed enhanced hole transfer to the electrolyte, while the intrinsic platinum-based VOP showed higher photovoltage. The mix of these end members at the tetravalent site showed a synergic effect of reduced charge transfer resistance from the material to the electrolyte and increased photovoltage, which led to increased PEC performance of the intermediate materials.

Keywords: solar water splitting, photo electrochemistry, photo absorbers, material characterization, device characterization, green hydrogen

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Authors: Joseph Wolff, Jeffrey Eilbott

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Autism Spectrum Disorders (ASD) are a spectrum of social disorders characterized by deficits in social communication, verbal ability, and interaction that can vary in severity. In recent years, researchers have used magnetic resonance imaging (MRI) to help detect how neural patterns in individuals with ASD differ from those of neurotypical (NT) controls for classification purposes. This study analyzed the classification of ASD within males and females using functional MRI data. Functional connectivity (FC) correlations among brain regions were used as feature inputs for machine learning algorithms. Analysis was performed on 558 cases from the Autism Brain Imaging Data Exchange (ABIDE) I dataset. When trained specifically on females, the algorithm underperformed in classifying the ASD subset of our testing population. Although the subject size was relatively smaller in the female group, the manual matching of both male and female training groups helps explain the algorithm’s bias, indicating the altered sex abnormalities in functional brain networks compared to typically developing peers. These results highlight the importance of taking sex into account when considering how generalizations of findings on males with ASD apply to females.

Keywords: autism spectrum disorder, machine learning, neuroimaging, sex differences

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Authors: Yichao Ma, Chengsiong Chin, Wailok Woo

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Since the last decade, there has been a rapid growth in digital multimedia, such as high-resolution media files and three-dimentional movies. Hence, there is a need for large digital storage such as Hard Disk Drive (HDD). As such, users expect to have a quieter HDD in their laptop. In this paper, a jury test has been conducted on a group of 34 people where 17 of them are students who is the potential consumer, and the remaining are engineers who know the HDD. A total 13 HDD sound samples have been selected from over hundred HDD noise recordings. These samples are selected based on an agreed subjective feeling. The samples are played to the participants using head acoustic playback system which enabled them to experience as similar as possible the same environment as have been recorded. Analysis has been conducted and the obtained results have indicated different group has different perception over the noises. Two neural network-based acoustic annoyance models are established based on back propagation neural network. Four psychoacoustic metrics, loudness, sharpness, roughness and fluctuation strength, are used as the input of the model, and the subjective evaluation results are taken as the output. The developed models are reasonably accurate in simulating both training and test samples.

Keywords: hdd noise, jury test, neural network model, psychoacoustic annoyance

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Authors: Musaab Salman Sultan

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The surface and bulk magnetization behavior of template released isolated ferromagnetic Ni₆₀Fe₄₀ nanowires of relatively thick diameters (~200 nm), deposited from a dilute suspension onto pre-patterned insulating chips have been investigated experimentally, using a highly sensitive Magneto-Optical Ker Effect (MOKE) magnetometry and Magneto-Resistance (MR) measurements, respectively. The MR data were consistent with the theoretical predictions of the anisotropic magneto-resistance (AMR) effect. The MR measurements, in all the angles of investigations, showed large features and a series of nonmonotonic "continuous small features" in the resistance profiles. The extracted switching fields from these features and from MOKE loops were compared with each other and with the switching fields reported in the literature that adopted the same analytical techniques on the similar compositions and dimensions of nanowires. A large difference between MOKE and MR measurments was noticed. The disparate between MOKE and MR results is attributed to the variance in the micro-magnetic structure of the surface and the bulk of such ferromagnetic nanowires. This result was ascertained using micro-magnetic simulations on an individual: cylindrical and rectangular cross sections NiFe nanowires, with the same diameter/thickness of the experimental wires, using the Object Oriented Micro-magnetic Framework (OOMMF) package where the simulated loops showed different switching events, indicating that such wires have different magnetic states in the reversal process and the micro-magnetic spin structures during switching behavior was complicated. These results further supported the difference between surface and bulk magnetization behavior in these nanowires. This work suggests that a combination of MOKE and MR measurements is required to fully understand the magnetization behavior of such relatively thick isolated cylindrical ferromagnetic nanowires.

Keywords: MOKE magnetometry, MR measurements, OOMMF package, micromagnetic simulations, ferromagnetic nanowires, surface magnetic properties

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Authors: Tahani Amutairi, Paul May, Neil Allan

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Many properties of semiconductor materials (mechanical, electronic, magnetic, and optical) can be significantly modified by introducing a point defect. Diamond offers extraordinary properties as a semiconductor, and doping seems to be a viable method of solving the problem associated with the fabrication of diamond-based electronic devices in order to exploit those properties. The dopants are believed to play a significant role in reducing the energy barrier to conduction and controlling the mobility of the carriers and the resistivity of the film. Although it has been proven that the n-type diamond semiconductor can be obtained with phosphorus doping, the resulting ionisation energy and mobility are still inadequate for practical application. Theoretical studies have revealed that this is partly because the effects of the many phosphorus atoms incorporated in the diamond lattice are compensated by acceptor states. Using spin-polarised hybrid density functional theory and a supercell approach, we explored the effects of bonding one N atom to a P in adjacent substitutional sites in diamond. A range of hybrid functional, including HSE06, B3LYP, PBE0, PBEsol0, and PBE0-13, were used to calculate the formation, binding, and ionisation energies, in order to explore the solubility and stability of the point defect. The equilibrium geometry and the magnetic and electronic structures were analysed and presented in detail. The defect introduces a unique reconstruction in a diamond where one of the C atoms coordinated with the N atom involved in the elongated C-N bond and creates a new bond with the P atom. The simulated infrared spectra of phosphorus-nitrogen defects were investigated with different supercell sizes and found to contain two sharp peaks at the edges of the spectrum, one at a high frequency 1,379 cm⁻¹ and the second appearing at the end range, 234 cm⁻¹, as obtained with the largest supercell (216).

Keywords: DFT, HSE06, B3LYP, PBE0, PBEsol0, PBE0-13

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Authors: P. Viduthalai, A. K. Divakar, V. Natarajan

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Media is one of the powerful tools that manipulate the world in numerous aspects especially in the form of a communication process. For instance, the concept of the public sphere, which was earlier represented by landlords and elites has now transformed into a virtual public sphere, which is also represented by marginalized people. Unfortunately, this acquisition is still paradoxical. Though the media proliferation and its effects are humongous, still it has not been the same throughout the world. Inequality in access to media has created a technological divide among people. Finally, globalization and approach by the government towards using media for development communication has significantly changed the way in which the media reaches every nook and corner. Monarchy, oligarchy, republic and democracy together form the basis of most governments of the world. Of which, democracy is the one with the highest involvement and participation of the people. Ideally, the participation of the people is what, that keeps the democracy running. A healthy democracy is possible only when people are able to access information that makes citizens responsible and serves to check the functioning of their elected representatives. On one side the media consumption of people plays a crucial role in the formation of the public sphere, and on the other side, big media conglomerates are a serious threat to community participation, which is a goal that the media should strive for in a country like India. How different people consume these different media, differs greatly from length and breadth of the country. Another aspect of this media consumption is that it isn’t passive. People usage and consumption of media are related with the gratification that they derive from the particular media. This aspect varies from person to person and from society to society according to both internal and external factors. This article sets out from the most underlying belief that Malayali Tribes have adopted television and becomes a part of daily life and a day never passes without it especially after the introduction of Free Television Scheme by the past state government. Though they are living in hilly and socially isolated places, they too have started accessing media for understanding about the people of the plains and their culture, dictated by their interest. Many of these interests appear to have a social and psychological origin. The present research attempts to study how gratification of these needs lead Malayali Tribes to form such a virtual public sphere where they could communicate with people of the plains. Data was collected through survey method, from 300 respondents on “Exposure towards Television and their perception”. Conventional anthropological methods like unstructured interviews were also used to supplement the data collection efforts in the three taluks namely Yercaud, Pethanayankkanpalayam and Panamaraththuppatty in Salem district of TamilNadu. The results highlight the role of Television in gratifying needs of the Malayali Tribes.

Keywords: democracy, gratification, Malayali Tribes and television, virtual public sphere

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Authors: A. Shebani, C. Pislaru

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Wear of materials is an everyday experience and has been observed and studied for long time. The prediction of wear is a fundamental problem in the industrial field, mainly correlated to the planning of maintenance interventions and economy. Pin-on-disc test is the most common test which is used to study the wear behaviour. In this paper, the pin-on-disc (AEROTECH UNIDEX 11) is used for the investigation of the effects of normal load and hardness of material on the wear under dry and sliding conditions. In the pin-on-disc rig, two specimens were used; one, a pin which is made of steel with a tip, is positioned perpendicular to the disc, where the disc is made of aluminium. The pin wear and disc wear were measured by using the following instruments: The Talysurf instrument, a digital microscope, and the alicona instrument; where the Talysurf profilometer was used to measure the pin/disc wear scar depth, and the alicona was used to measure the volume loss for pin and disc. After that, the Archard model, American Society for Testing and Materials model (ASTM), and neural network model were used for pin/disc wear modelling and the simulation results are implemented by using the Matlab program. This paper focuses on how the alicona can be considered as a powerful tool for wear measurements and how the neural network is an effective algorithm for wear estimation.

Keywords: wear modelling, Archard Model, ASTM Model, Neural Networks Model, Pin-on-disc Test, Talysurf, digital microscope, Alicona

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Authors: Abrar Al-Enzi

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This study investigates the role of the popular utilization of Wasta within Arab societies. Wasta, by definition, is a set of personal networks based on family or kinship ties in which power and influence are utilized to get things done. As Wasta evolved, it became intensely rooted in Arab cultures, which is considered as an intrinsic tool of the culture, a method of doing business transactions and as a family obligation. However, the consequences related to Wasta in business are substantial as it impacts organizational performance, employee’s perception of the organization and the atmosphere between employees. To date, there has been little in-depth organizational research on the impact of Wasta. Hence, the question that will be addressed is: Does Wasta influence human resource management, knowledge sharing and innovation in Kuwait, which in turn affects employees’ commitment within organizations? As a result, a mixed method sequential exploratory research design will be used to examine the mentioned subject, which consists of three phases: (1) Doing some initial exploratory interviews; (2) Developing a paper-based and online survey (Quantitative method) based on the findings; (3) Lastly, following up with semi-structured interviews (Qualitative method). The rationale behind this approach is that both qualitative and quantitative methods complement each other by providing a more complete picture of the subject matter.

Keywords: commitment, HRM practices, social capital, Wasta

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Authors: Ofoegbu Ositadinma Edward

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This research paper discusses a web based monitoring system that enables effective monitoring of fuel pump output and sales volume from distributed fuel stations under the domain of a single company/organization. The traditional method of operation by these organizations in Nigeria is non-automated and accounting for dispensed product is usually approximated and manual as there is little or no technology implemented to presently provide information relating to the state of affairs in the station both to on-ground staff and to supervisory staff that are not physically present in the station. This results in unaccountable losses in product and revenue as well as slow decision making. Remote monitoring technology as a vast research field with numerous application areas incorporating various data collation techniques and sensor networks can be applied to provide information relating to fuel pump status in distributed fuel stations reliably. Thus, the proposed system relies upon a microcontroller, keypad and pump to demonstrate the traditional fuel dispenser. A web-enabled PC with an accompanying graphic user interface (GUI) was designed using virtual basic which is connected to the microcontroller via the serial port which is to provide the web implementation.

Keywords: fuel pump, microcontroller, GUI, web

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Authors: Safa’ Abdelkarim Hammad

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The electrical power system is one of the main parts of the nation's infrastructure, and the availability and cost of electricity are critical factors in industrial competitiveness and strategy. Restructuring of the electricity supply industries is a very complex exercise based on national energy strategies and policies, macroeconomic developments, and national conditions, and its application varies from country to country. Electricity regulation of natural monopolies is a challenging task. Regulators face the problem of providing appropriate incentives for improvement of efficiency. Incentive regulation is often considered as an efficient regulatory tool to handle the problem, and it is widely applied in several countries. However, the exact regulation methodologies differ from one country to another. Network quantitative reliability evaluation is an essential factor with regard to the quality of supply. The main factors used to judge the reliability of supply is measured by the number and duration of interruptions experienced by customers. Several indicators are used to evaluate reliability in distribution networks. This paper addresses the impact of incentive regulation and performance benchmarking in the field of electricity distribution in Jordan. The theory of efficiency measurement and the most common models; NCSQS and DEA models are presented.

Keywords: incentive regulations, reliability, restructuring, Tarrif

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Authors: Yating Yang, Xue Zhang, Chengli Zhao

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Technology capability refers to the comprehensive ability that influences all factors of technological development. Among them, researchers’ resources serve as the foundation and driving force for technology capability, representing a significant manifestation of a country/region's technological capability. Therefore, the cross-border transfer behavior of researchers to some extent reflects changes in technological capability between countries/regions, providing a unique research perspective for technological capability assessment. This paper proposes a technological capability assessment model based on personnel transfer networks, which consists of a researchers' transfer network model and a country/region role evolution model. It evaluates the changes in a country/region's technological capability roles from the perspective of researcher transfers and conducts an analysis using artificial intelligence as a case study based on literature data. The study reveals that the United States, China, and the European Union are core nodes, and identifies the role evolution characteristics of several major countries/regions.

Keywords: transfer network, technological capability assessment, central-peripheral structure, role evolution

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Authors: Bashir Abdu Muzakkari, Mohamad Afendee Mohamad, Mohd Fadzil Abdul Kadir

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Wireless Sensor Networks (WSNs) is an aggregation of several tiny, low-cost sensor nodes, spatially distributed to monitor physical or environmental status. WSN is constantly changing because of the rapid technological advancements in sensor elements such as radio, battery and operating systems. The Medium Access Control (MAC) protocols remain very vital in the WSN because of its role in coordinating communication amongst the sensors. Other than battery consumption, packet collision, network lifetime and latency are factors that largely depend on WSN MAC protocol and these factors have been widely treated in recent days. In this paper, we survey some latest proposed WSN Contention-based, Scheduling-based and Hybrid MAC protocols while presenting an examination, correlation of advantages and limitations of each protocol. Concentration is directed towards investigating the treatment of Quality of Service (QoS) performance metrics within these particular protocols. The result shows that majority of the protocols leaned towards energy conservation. We, therefore, believe that other performance metrics of guaranteed QoS such as latency, throughput, packet loss, network and bandwidth availability may play a critical role in the design of future MAC protocols for WSNs.

Keywords: WSN, QoS, energy consumption, MAC protocol

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Authors: Weiwei Cui, Dejian Lin, Leigang Zhang, Yao Wang, Zheng Sun, Lianfeng Li

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Built-in test (BIT) is an important technology in testability field, and it is widely used in state monitoring and fault diagnosis. With the improvement of modern equipment performance and complexity, the scope of BIT becomes larger, and it leads to the emergence of false alarm problem. The false alarm makes the health assessment unstable, and it reduces the effectiveness of BIT. The conventional false alarm suppression methods such as repeated test and majority voting cannot meet the requirement for a complicated system, and the intelligence algorithms such as artificial neural networks (ANN) are widely studied and used. However, false alarm has a very low frequency and small sample, yet a method based on ANN requires a large size of training sample. To recognize the false alarm, we propose a method based on multi-classification support vector machine (SVM) in this paper. Firstly, we divide the state of a system into three states: healthy, false-alarm, and faulty. Then we use multi-classification with '1 vs 1' policy to train and recognize the state of a system. Finally, an example of fault injection system is taken to verify the effectiveness of the proposed method by comparing ANN. The result shows that the method is reasonable and effective.

Keywords: false alarm, fault diagnosis, SVM, k-means, BIT

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Authors: R. Verwiebe, L. Seewann, M. Wolf

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This presentation addresses marginalization and discrimination as experienced by young academics with a migrant background in the Austrian labor market. Focusing on second generation academics of Central Eastern European and Turkish descent we explore two major issues. First, we ask whether their career-entry and everyday professional life entails origin-specific barriers. As educational residents, they show competences which, when lacking, tend to be drawn upon to explain discrimination: excellent linguistic skills, accredited high-level training, and networks. Second, we concentrate on how this group reacts to discrimination and overcomes experiences of marginalization. To answer these questions, we utilize recent sociological and social psychological theories that focus on the diversity of individual experiences. This distinguishes us from a long tradition of research that has dealt with the motives that inform discrimination, but has less often considered the effects on those concerned. Similarly, applied coping strategies have less often been investigated, though they may provide unique insights into current problematic issues. Building upon present literature, we follow recent discrimination research incorporating the concepts of ‘multiple discrimination’, ‘subtle discrimination’, and ‘visual social markers’. 21 problem-centered interviews are the empirical foundation underlying this study. The interviewees completed their entire educational career in Austria, graduated in different universities and disciplines and are working in their first post-graduate jobs (career entry phase). In our analysis, we combined thematic charting with a coding method. The results emanating from our empirical material indicated a variety of discrimination experiences ranging from barely perceptible disadvantages to directly articulated and overt marginalization. The spectrum of experiences covered stereotypical suppositions at job interviews, the disavowal of competencies, symbolic or social exclusion by new colleges, restricted professional participation (e.g. customer contact) and non-recruitment due to religious or ethnical markers (e.g. headscarves). In these experiences the role of the academics education level, networks, or competences seemed to be minimal, as negative prejudice on the basis of visible ‘social markers’ operated ‘ex-ante’. The coping strategies identified in overcoming such barriers are: an increased emphasis on effort, avoidance of potentially marginalizing situations, direct resistance (mostly in the form of verbal opposition) and dismissal of negative experiences by ignoring or ironizing the situation. In some cases, the academics drew into their specific competences, such as an intellectual approach of studying specialist literature, focus on their intercultural competences or planning to migrate back to their parent’s country of origin. Our analysis further suggests a distinction between reactive (i.e. to act on and respond to experienced discrimination) and preventative strategies (applied to obviate discrimination) of coping. In light of our results, we would like to stress that the tension between educational and professional success experienced by academics with a migrant background – and the barriers and marginalization they continue to face – are essential issues to be introduced to socio-political discourse. It seems imperative to publicly accentuate the growing social, political and economic significance of this group, their educational aspirations, as well as their experiences of achievement and difficulties.

Keywords: coping strategies, discrimination, labor market, second generation university graduates

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Authors: Tiberiu Socaciu, Tudor Colomeischi, Eugenia Iancu

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Business failure affects in various proportions shareholders, managers, lenders (banks), suppliers, customers, the financial community, government and society as a whole. In the era in which we have telecommunications networks, exists an interdependence of markets, the effect of a failure of a company is relatively instant. To effectively manage risk exposure is thus require sophisticated support systems, supported by analytical tools to measure, monitor, manage and control operational risks that may arise. As we know, bankruptcy is a phenomenon that managers do not want no matter what stage of life is the company they direct / lead. In the analysis made by us, by the nature of economic models that are reviewed (Altman, Conan-Holder etc.), estimating the risk of bankruptcy of a company corresponds to some extent with its own business cycle tracing of the company. Various models for predicting bankruptcy take into account direct / indirect aspects such as market position, company growth trend, competition structure, characteristics and customer retention, organization and distribution, location etc. From the perspective of our research we will now review the economic models known in theory and practice for estimating the risk of bankruptcy; such models are based on indicators drawn from major accounting firms.

Keywords: Anglo-Saxon models, continental models, national models, statistical models

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Authors: M. S. Gadala, Khaled Ahmed, Elasadig Mahdi

Abstract:

In this paper, we introduced a gradient-based inverse solver to obtain the missing boundary conditions based on the readings of internal thermocouples. The results show that the method is very sensitive to measurement errors, and becomes unstable when small time steps are used. The artificial neural networks are shown to be capable of capturing the whole thermal history on the run-out table, but are not very effective in restoring the detailed behavior of the boundary conditions. Also, they behave poorly in nonlinear cases and where the boundary condition profile is different. GA and PSO are more effective in finding a detailed representation of the time-varying boundary conditions, as well as in nonlinear cases. However, their convergence takes longer. A variation of the basic PSO, called CRPSO, showed the best performance among the three versions. Also, PSO proved to be effective in handling noisy data, especially when its performance parameters were tuned. An increase in the self-confidence parameter was also found to be effective, as it increased the global search capabilities of the algorithm. RPSO was the most effective variation in dealing with noise, closely followed by CRPSO. The latter variation is recommended for inverse heat conduction problems, as it combines the efficiency and effectiveness required by these problems.

Keywords: inverse analysis, function specification, neural net works, particle swarm, run-out table

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Authors: Xiaodong Li, Peng Gao, Chao-Jung Huang, Shiying Hao, Xuefeng B. Ling, Yongxia Han, Yaqi Zhang, Le Zheng, Chengyin Ye, Modi Liu, Minjie Xia, Changlin Fu, Bo Jin, Karl G. Sylvester, Eric Widen

Abstract:

Predicting the risk of Pancreatic Adenocarcinoma (PA) in advance can benefit the quality of care and potentially reduce population mortality and morbidity. The aim of this study was to develop and prospectively validate a risk prediction model to identify patients at risk of new incident PA as early as 3 months before the onset of PA in a statewide, general population in Maine. The PA prediction model was developed using Deep Neural Networks, a deep learning algorithm, with a 2-year electronic-health-record (EHR) cohort. Prospective results showed that our model identified 54.35% of all inpatient episodes of PA, and 91.20% of all PA that required subsequent chemoradiotherapy, with a lead-time of up to 3 months and a true alert of 67.62%. The risk assessment tool has attained an improved discriminative ability. It can be immediately deployed to the health system to provide automatic early warnings to adults at risk of PA. It has potential to identify personalized risk factors to facilitate customized PA interventions.

Keywords: cancer prediction, deep learning, electronic health records, pancreatic adenocarcinoma

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Authors: S. S. Sree Sanker, K. N. Madhusoodanan

Abstract:

Optical biosensors are dominant alternative for traditional analytical methods, because of their small size, simple design and high sensitivity. Photonic sensing method is one of the recent advancing technology for biosensors. It measures the change in refractive index which is induced by the difference in molecular interactions due to the change in concentration of the analyte. Glucose is an aldosic monosaccharide, which is a metabolic source in many of the organisms. The terahertz waves occupies the space between infrared and microwaves in the electromagnetic spectrum. Terahertz waves are expected to be applied to various types of sensors for detecting harmful substances in blood, cancer cells in skin and micro bacteria in vegetables. We have designed glucose sensors using silicon based 1D and 2D photonic crystal pillar arrays in terahertz frequency range. 1D photonic crystal has rectangular pillars with height 100 µm, length 1600 µm and width 50 µm. The array period of the crystal is 500 µm. 2D photonic crystal has 5×5 cylindrical pillar array with an array period of 75 µm. Height and diameter of the pillar array are 160 µm and 100 µm respectively. Two samples considered in the work are blood and glucose solution, which are labelled as sample 1 and sample 2 respectively. The proposed sensor detects the concentration of glucose in the samples from 0 to 100 mg/dL. For this, the crystal was irradiated with 0.3 to 3 THz waves. By analyzing the obtained S parameter, the refractive index of the crystal corresponding to the particular concentration of glucose was measured using the parameter retrieval method. Refractive indices of the two crystals decreased gradually with the increase in concentration of glucose in the sample. For 1D photonic crystals, a gradual decrease in refractive index was observed at 1 THz. 2D photonic crystal showed this behavior at 2 THz. The proposed sensor was simulated using CST Microwave studio. This will enable us to develop a model which can be used to characterize a glucose sensor. The present study is expected to contribute to blood glucose monitoring.

Keywords: CST microwave studio, glucose sensor, photonic crystal, terahertz waves

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Authors: Teja Koduru

Abstract:

Untreated Lyme disease can lead to neurological, cardiac, and dermatological complications. Rapid diagnosis of the erythema migrans (EM) rash, a characteristic symptom of Lyme disease is therefore crucial to early diagnosis and treatment. In this study, we aim to utilize deep learning frameworks including Tensorflow and Keras to create deep convolutional neural networks (DCNN) to detect images of acute Lyme Disease from images of erythema migrans. This study uses a custom database of erythema migrans images of varying quality to train a DCNN capable of classifying images of EM rashes vs. non-EM rashes. Images from publicly available sources were mined to create an initial database. Machine-based removal of duplicate images was then performed, followed by a thorough examination of all images by a clinician. The resulting database was combined with images of confounding rashes and regular skin, resulting in a total of 683 images. This database was then used to create a DCNN with an accuracy of 93% when classifying images of rashes as EM vs. non EM. Finally, this model was converted into a web and mobile application to allow for rapid diagnosis of EM rashes by both patients and clinicians. This tool could be used for patient prescreening prior to treatment and lead to a lower mortality rate from Lyme disease.

Keywords: Lyme, untreated Lyme, erythema migrans rash, EM rash

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Authors: Emineh Tsegahun Gedif

Abstract:

Zinc oxide nanoparticles (ZnO NPs) have garnered significant attention due to their diverse applications encompassing catalytic, optical, photonic, and antibacterial properties. In this study, we successfully synthesized zinc oxide nanoparticles using a rapid, environmentally benign, and cost-effective method. Neem (Azadirachta indica) leaf extract served as the reducing agent for Zn (NO₃)₂.6H2O solution under optimized conditions (pH = 9). Qualitative screening techniques and FT-IR Spectroscopy confirmed the presence of active biomolecules such as flavonoids, phenolic groups, alkaloids, terpenoids, and tannins within the Neem leaf extract, both before and after reduction. The formation of ZnO NPs was visually evident through a distinct color change from colorless to light yellow. The biosynthesized nanoparticles underwent comprehensive characterization through UV-visible, FT-IR, and XRD spectroscopies. The reduction process proved to be straightforward and user-friendly, with UV-visible spectroscopy demonstrating a surface plasmon resonance (SPR) at 321 nm, unequivocally confirming the ZnO NP formation. X-ray diffraction analysis elucidated the crystal structure, revealing an average particle size of approximately 20 nm using Scherrer's equation based on the line width of the plane. Furthermore, the synthesized zinc oxide nanoparticles were evaluated for their antimicrobial properties against both Gram-positive and Gram-negative bacteria. The results showcased significant inhibitory activity, with the highest zone of inhibition observed against Escherichia coli (15 mm) and comparatively lower activity against Staphylococcus aureus. This research underscores the potential of Neem leaf extract-mediated synthesis of ZnO NPs as an eco-friendly and effective approach for various applications, including antibacterial agents.

Keywords: zinc oxide nanoparticles (ZnO NPs), bioreducing agent, green synthesis, antibacterial activity

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Authors: Ming-Hsiang Shih, Wen-Pei Sung, Shih-Heng Tung

Abstract:

Semi-active control system for structure under excitation of earthquake provides with the characteristics of being adaptable and requiring low energy. DSHD (Displacement Semi-Active Hydraulic Damper) was developed by our research team. Shake table test results of this DSHD installed in full scale test structure demonstrated that this device brought its energy-dissipating performance into full play for test structure under excitation of earthquake. The objective of this research is to develop a new AIC (Active Interaction Control Device) and apply shake table test to perform its dissipation of energy capability. This new proposed AIC is converting an improved DSHD (Displacement Semi-Active Hydraulic Damper) to AIC with the addition of an accumulator. The main concept of this energy-dissipating AIC is to apply the interaction function of affiliated structure (sub-structure) and protected structure (main structure) to transfer the input seismic force into sub-structure to reduce the structural deformation of main structure. This concept is tested using full-scale multi-degree of freedoms test structure, installed with this proposed AIC subjected to external forces of various magnitudes, for examining the shock absorption influence of predictive control, stiffness of sub-structure, synchronous control, non-synchronous control and insufficient control position. The test results confirm: (1) this developed device is capable of diminishing the structural displacement and acceleration response effectively; (2) the shock absorption of low precision of semi-active control method did twice as much seismic proof efficacy as that of passive control method; (3) active control method may not exert a negative influence of amplifying acceleration response of structure; (4) this AIC comes into being time-delay problem. It is the same problem of ordinary active control method. The proposed predictive control method can overcome this defect; (5) condition switch is an important characteristics of control type. The test results show that synchronism control is very easy to control and avoid stirring high frequency response. This laboratory results confirm that the device developed in this research is capable of applying the mutual interaction between the subordinate structure and the main structure to be protected is capable of transforming the quake energy applied to the main structure to the subordinate structure so that the objective of minimizing the deformation of main structural can be achieved.

Keywords: DSHD (Displacement Semi-Active Hydraulic Damper), AIC (Active Interaction Control Device), shake table test, full scale structure test, sub-structure, main-structure

Procedia PDF Downloads 495