Search results for: passive optical networks (PON)

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

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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

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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

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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: Emineh Tsegahun Gedif

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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: Teja Koduru

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

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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

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Authors: Seyedeh Mozhgan Seyed Talebi, Chih -Hao Lee

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With an abrupt rise in the power conservation efficiency (PCE) of perovskite solar cells (PSCs) within a short span of time, the toxicity of lead was raised as a major hurdle in the path toward their commercialization. In the present research, a systematic investigation of the electrical and optical characteristics of the all-inorganic CsSnI₃ perovskite absorber layer was performed with the Vienna Ab Initio Simulation Package (VASP) using the projector-augmented wave method. The presence of inorganic halide perovskite offers the advantages of enhancing the degradation resistance of the device, reducing the cost of cells, and minimizing the recombination of generated carriers. The simulated standard device using a 1D simulator like solar cell capacitance simulator (SCAPS) version 3308 involves FTO/n-TiO₂/CsSnI₃ Perovskite absorber/Spiro OmeTAD HTL/Au contact layer. The variation in the device design key parameters such as the thickness and defect density of perovskite absorber, hole transport layer and electron transport layer and interfacial defects are examined with their impact on the photovoltaic characteristic parameters. The effect of an increase in operating temperature from 300 K to 400 K on the performance of CsSnI3-based perovskite devices is also investigated. The optimized standard device at room temperature shows the highest PCE of 25.18 % with FF of 75.71 %, Voc of 0.96 V, and Jsc of 34.67 mA/cm². The outcomes and interpretation of different inorganic Cu-based HTLs presence, such as CuSCN, Cu₂O, CuO, CuI, SrCu₂O₂, and CuSbS₂, here represent a critical avenue for the possibility of fabricating high PCE perovskite devices made of stable, low-cost, efficient, safe, and eco-friendly all-inorganic materials like CsSnI₃ perovskite light absorber.

Keywords: CsSnI₃, hole transporting layer (HTL), lead-free perovskite solar cell, SCAPS-1D software

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Authors: Dehni Abdellatif, Lounis Mourad

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The new approach of applied spatial geostatistics in materials sciences, agriculture accuracy, agricultural statistics, permitted an apprehension of managing and monitoring the water and groundwater qualities in a relationship with salt-affected soil. The anterior experiences concerning data acquisition, spatial-preparation studies on optical and multispectral data has facilitated the integration of correction models of electrical conductivity related with soils temperature (horizons of soils). For tomography apprehension, this physical parameter has been extracted from calibration of the thermal band (LANDSAT ETM+6) with a radiometric correction. Our study area is Oran region (Northern West of Algeria). Different spectral indices are determined such as salinity and sodicity index, the Combined Spectral Reflectance Index (CSRI), Normalized Difference Vegetation Index (NDVI), emissivity, Albedo, and Sodium Adsorption Ratio (SAR). The approach of geostatistical modeling of electrical conductivity (salinity), appears to be a useful decision support system for estimating corrected electrical resistivity related to the temperature of surface soils, according to the conversion models by substitution, the reference temperature at 25°C (where hydrochemical data are collected with this constraint). The Brightness temperatures extracted from satellite reflectance (LANDSAT ETM+) are used in consistency models to estimate electrical resistivity. The confusions that arise from the effects of salt stress and water stress removed followed by seasonal application of the geostatistical analysis in Geographic Information System (GIS) techniques investigation and monitoring the variation of the electrical conductivity in the alluvial aquifer of Es-Sénia for the salt-affected soil.

Keywords: geostatistical modelling, landsat, brightness temperature, conductivity

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Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

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Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

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Authors: KumarShashvat, ArshpreetKaur, RajeshKumar, Raman Chadha

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Wireless sensor networks have principal characteristic of having restricted energy and with limitation that energy of the nodes cannot be replenished. To increase the lifetime in this scenario WSN route for data transmission is opted such that utilization of energy along the selected route is negligible. For this energy efficient network, dandy infrastructure is needed because it impinges the network lifespan. Clustering is a technique in which nodes are grouped into disjoints and non–overlapping sets. In this technique data is collected at the cluster head. In this paper, Adaptive-PSO algorithm is proposed which forms energy aware clusters by minimizing the cost of locating the cluster head. The main concern is of the suitability of the swarms by adjusting the learning parameters of PSO. Particle Swarm Optimization converges quickly at the beginning stage of the search but during the course of time, it becomes stable and may be trapped in local optima. In suggested network model swarms are given the intelligence of the spiders which makes them capable enough to avoid earlier convergence and also help them to escape from the local optima. Comparison analysis with traditional PSO shows that new algorithm considerably enhances the performance where multi-dimensional functions are taken into consideration.

Keywords: Particle Swarm Optimization, adaptive – PSO, comparison between PSO and A-PSO, energy efficient clustering

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Authors: K. Gomathi

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Mobile Ad hoc Networks (MANET) is defined as collection of routable wireless mobile nodes with no centralized administration and communicate each other using radio signals. Especially MANETs deployed in hostile environments where hackers will try to disturb the secure data transfer and drain the valuable network resources. Since MANET is battery operated network, preserving the network resource is essential one. For resource constrained computation, efficient routing and to increase the network stability, the network is divided into smaller groups called clusters. The clustering architecture consists of Cluster Head(CH), ordinary node and gateway. The CH is responsible for inter and intra cluster routing. CH election is a prominent research area and many more algorithms are developed using many different metrics. The CH with longer life sustains network lifetime, for this purpose Secondary Cluster Head(SCH) also elected and it is more economical. To nominate efficient CH, a Enhanced Distributed Weighted Clustering Algorithm (EDWCA) has been proposed. This approach considers metrics like battery power, degree difference and speed of the node for CH election. The proficiency of proposed one is evaluated and compared with existing algorithm using Network Simulator(NS-2).

Keywords: MANET, EDWCA, clustering, cluster head

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Authors: Shreyansh Jain Jeetmal, Shobith P. Chadaga, Shreyas H. Srinivas

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Internet of Things (IoT) is seen as the next major step in the ongoing revolution in the Information Age. It is predicted that in the near future billions of embedded devices will be communicating with each other to perform a plethora of tasks with or without human intervention. One of the major ongoing hotbed of research activity in IoT is Human Computer Interaction (HCI). HCI is used to facilitate communication between an intelligent system and a user. An intelligent system typically comprises of a system consisting of various sensors, actuators and embedded controllers which communicate with each other to monitor data collected from the environment. Communication by the user to the system is typically done using voice. One of the major ongoing applications of HCI is in home automation as a personal assistant. The prime objective of our project is to implement a use case of HCI for home automation. Our system is designed to detect and recognize the users and personalize the appliances in the house according to their individual preferences. Our HCI system is also capable of speaking with the user when certain commands are spoken such as searching on the web for information and controlling appliances. Our system can also monitor the environment in the house such as air quality and gas leakages for added safety.

Keywords: human computer interaction, internet of things, computer vision, sensor networks, speech to text, text to speech, android

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Authors: Abdullahi Marshal Idris, Murtala Mohammed Alamai, Adama Jummai Idris, Bello Mohammed Gwagwada

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The technological revolution of the 1990s have brought about many new opportunities and challenges for the tourism and hospitality industries mostly in Nigeria and with tourism having global industry information as its life-blood and technology becoming fundamental to the ability of the industry to operate effectively and competitively. The whole system of information technologies is being rapidly diffused throughout the tourism industry and no player will escape information technologies impacts. The paper gives an insight into the importance of destination branding and the application of information technologies and the use of Internet in tourism and hospitality industries in Nigeria giving strategic frameworks, providing analysis of the Internet and its impact on these sectors. It also aims to show how technological innovations and information system can be beneficial for destinations companies like game reserves national parks, and other resorts by using the literature of existing efforts in global industry players as well as documented evidences where recommendations for destinations and companies is made to seek to foster the development of this connection by investing considerable resources in marketing activities on social networks and by reinforcing the trust of users, because credibility and reliability are still critical in this area.

Keywords: branding, marketing, technology, tourism product

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Authors: Ali Reza Sattarzadeh, Ronny J. Kutadinata, Pubudu N. Pathirana, Van Thanh Huynh

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Traffic congestion has become a severe worldwide problem, affecting everyday life, fuel consumption, time, and air pollution. The primary causes of these issues are inadequate transportation infrastructure, poor traffic signal management, and rising population. Traffic flow forecasting is one of the essential and effective methods in urban congestion and traffic management, which has attracted the attention of researchers. With the development of technology, undeniable progress has been achieved in existing methods. However, there is a possibility of improvement in the extraction of temporal and spatial features to determine the importance of traffic flow sequences and extraction features. In the proposed model, we implement the convolutional neural network (CNN) and long short-term memory (LSTM) deep learning models for mining nonlinear correlations and their effectiveness in increasing the accuracy of traffic flow prediction in the real dataset. According to the experiments, the results indicate that implementing Conv-LSTM networks increases the productivity and accuracy of deep learning models for traffic flow prediction.

Keywords: deep learning algorithms, intelligent transportation systems, spatiotemporal features, traffic flow prediction

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Authors: Binoun Chaki Hagar

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Studies have investigated grandparents' perceptions relating to their grandchildren with disabilities. Literature on grandparenthood focuses on the Western grandparents. Autism within the Arab populations has also being investigated. Moreover, the Bedouin population can also be seen in various studies related to different experiences and different perceptions about disabilities in general and among children in particular. However, as far as we know, no studies were found on grand parenting a child with autism in Bedouin society. This study combines three areas of knowledge, to create another knowledge domain. The aim of this study was to learn about the experience of grand parenting an autistic child in the Bedouin Arab society, to examine how it affects the grandparents' relationships, feelings, and functioning within the family, and as individuals, as well as to examine their coping mechanisms and their social support networks. This study is significant and as it examines autism and grandparents among the Bedouin Arab population in Israel, a population that has unique socio-demographic, cultural and traditional characteristics. The study revealed three themes concerning the meaning of grandparenthood to be associated with family continuity, how autism is perceived, and the importance of religion. It also suggests another category – the status of the elderly in the Arab-Bedouin family. It is recognized that the role of the elderly is held in high esteem, and can be affected by the grandchild’s’ autism.

Keywords: Arab–Bedouin family, autism, grandparents, family relationships

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Authors: Olga Maksakova

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A work with unconscious patients after acute brain damages besides special knowledge and practical skills of all the participants requires a very specific organization. A lot of said about team approach in neurorehabilitation, usually as for outpatient mode. Rehabilitologists deal with fixed patient problems or deficits (motion, speech, cognitive or emotional disorder). Team-building means superficial paradigm of management psychology. Linear mode of teamwork fits casual relationships there. Cases with deep altered states of consciousness (vegetative states, coma, and confusion) require non-linear mode of teamwork: recovery of consciousness might not be the goal due to phenomenon uncertainty. Rehabilitation team as Semi-open Complex System includes the patient as a part. Patient's response pattern becomes formed not only with brain deficits but questions-stimuli, context, and inquiring person. Teamwork is sourcing of phenomenology knowledge of patient's processes as Third-person approach is replaced with Second- and after First-person approaches. Here is a chance for real-time change. Patient’s contacts with his own body and outward things create a basement for restoration of consciousness. The most important condition is systematic feedbacks to any minimal movement or vegetative signal of the patient. Up to now, recovery work with the most severe contingent is carried out in the mode of passive physical interventions, while an effective rehabilitation team should include specially trained psychologists and psychotherapists. It is they who are able to create a network of feedbacks with the patient and inter-professional ones building up the team. Characteristics of ‘Team-Patient’ system (TPS) are energy, entropy, and complexity. Impairment of consciousness as the absence of linear contact appears together with a loss of essential functions (low energy), vegetative-visceral fits (excessive energy and low order), motor agitation (excessive energy and excessive order), etc. Techniques of teamwork are different in these cases for resulting optimization of the system condition. Directed regulation of the system complexity is one of the recovery tools. Different signs of awareness appear as a result of system self-organization. Joint meetings are an important part of teamwork. Regular or event-related discussions form the language of inter-professional communication, as well as the patient's shared mental model. Analysis of complex communication process in TPS may be useful for creation of the general theory of consciousness.

Keywords: rehabilitation team, urgent rehabilitation, severe brain damage, consciousness disorders, complex system theory

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Authors: Kuang-Hsiung Tan, Chih-Chan Hu, Chien-Wu Lan, Shih-Sung Lin, Te-Jen Chang

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An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.

Keywords: distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone

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Authors: Julian Jaegers, Siegmar Wirtz, Viktor Scherer

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Wood pellets belong to the most established trade formats of wood-based fuels. Especially, because of the transportability and the storage properties, but also due to low moisture content, high energy density, and the homogeneous particle size and shape, wood pellets are well suited for power generation in power plants and for the use in automated domestic firing systems. Before they are thermally converted, wood pellets pass various transport and storage procedures. There they undergo different mechanical impacts, which leads to pellet breakage and abrasion and to an increase in fines. The fines lead to operational problems during storage, charging, and discharging of pellets, they can increase the risk of dust explosions and can lead to pollutant emissions during combustion. In the current work, the dependence of the formation of fines caused by breakage during pneumatic transport is analyzed experimentally and numerically. The focus lies on the influence of conveying velocity, pellet loading, pipe diameter, and the shape of pipe components like bends or couplings. A test rig has been built, which allows the experimental evaluation of the pneumatic transport varying the above-mentioned parameters. Two high-speed cameras are installed for the quantitative optical access to the particle-particle and particle-wall contacts. The particle size distribution of the bulk before and after a transport process is measured as well as the amount of fines produced. The experiments will be compared with results of corresponding DEM/CFD simulations to provide information on contact frequencies and forces. The contribution proposed will present experimental results and report on the status of the DEM/CFD simulations. The final goal of the project is to provide a better insight into pellet breakage during pneumatic transport and to develop guidelines ensuring a more gentle transport.

Keywords: DEM/CFD-simulation of pneumatic conveying, mechanical impact on wood pellets during transportation, pellet breakage, pneumatic transport of wood pellets

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Authors: N. M. G. Al-Saidi, K. A. Kadhim, N. A. Rajab

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Over the past decades, computer networks and data communication system has been developing fast, so, the necessity to protect a transmitted data is a challenging issue, and data security becomes a serious problem nowadays. A secret sharing scheme is a method which allows a master key to be distributed among a finite set of participants, in such a way that only certain authorized subsets of participants to reconstruct the original master key. To create a secret sharing scheme, many mathematical structures have been used; the most widely used structure is the one that is based on graph theory (graph access structure). Subsequently, many researchers tried to find efficient schemes based on graph access structures. In this paper, we propose a novel efficient construction of a perfect secret sharing scheme for uniform access structure. The dominating set of vertices in a regular graph is used for this construction in the following way; each vertex represents a participant and each minimum independent dominating subset represents a minimal qualified subset. Some relations between dominating set, graph order and regularity are achieved, and can be used to demonstrate the possibility of using dominating set to construct a secret sharing scheme. The information rate that is used as a measure for the efficiency of such systems is calculated to show that the proposed method has some improved values.

Keywords: secret sharing scheme, dominating set, information rate, access structure, rank

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Authors: Shubham Sharma, Sandra Barkauskaite, Brendan Duffy, Swarna Jaiswal, Amit K. Jaiswal

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Food packaging protects food from temperature, light, and humidity; preserves food and guarantees the safety and the integrity of the food. Advancement in packaging research leads to development of active packaging system with numerous properties such as oxygen scavengers, carbon-dioxide generating systems, antimicrobial active packaging, moisture control packaging, ethylene scavengers etc. In the active packaging, several additives such as essential oils, polyphenols etc. are incorporated into packaging film or within the packaging material to achieve the desired properties. This study investigates the effect on the structural, thermal and functional properties of different poly(lactide) – poly (butylene adipate-co-terephthalate) (PLA-PBAT) blend films incorporated with clove essential oil. The PLA-PBAT films were prepared by a solution casting method and then characterized based on their optical, mechanical properties, surface hydrophobicity, chemical composition, antimicrobial activity against S. aureus and E. coli, and inhibition of biofilm formation of E. coli. Results showed that, the developed packaging film containing clove oil has significant UV-blocking property (80%). However, incorporation of clove oil resulted in reduced transparency and tensile strength of the film as the concentration of clove oil increased. The surface hydrophobicity of packaging film was improved with the increasing concentration of essential oil. Similarly, thickness of the clove oil containing films increased from 36.71 µm to 106.67 µm as the concentration increases. The antimicrobial activity and biofilm inhibition study showed that the clove-incorporated PLA-PBAT composite film was effective against tested bacteria E. coli and S. aureus. This study showed that the PLA-PBAT – Clove oil composite film has significant antimicrobial and UV-blocking properties and can be used as an active food packaging film.

Keywords: active packaging, clove oil, poly(butylene adipate-co-terephthalate), poly(lactide)

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Authors: Yuya Tanigami, Naoaki Yamanaka, Satoru Okamoto

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Economic losses due to delays in traffic congestion regarding urban transportation networks have become a more serious social problem as traffic volume increases. Platooning has recently been attracting attention from many researchers to alleviate traffic jams, especially on the highway. On highways, platooning can have positive effects, such as reducing inter-vehicular distance and reducing air resistance. However, the impacts of platooning on urban roads have not been addressed in detail since traffic lights may break the platoons. In this study, we propose a platooning method using L2 norm and cosine similarity to form a platoon with highly similar routes. Also, we investigate the sorting method within a platoon according to each vehicle’s straightness. Our proposed sorting platoon method, which uses two lanes, eliminates Head of Line Blocking at the intersection and improves throughput at intersections. This paper proposes a cyber-physical system (CPS) approach to collaborative urban platoon control. We conduct simulations using the traffic simulator SUMO and the road network, which imitates Manhattan Island. Results from the SUMO confirmed that our method shortens the average travel time by 10-20%. This paper shows the validity of forming a platoon based on destination vectors and sorting vehicles within a platoon.

Keywords: CPS, platooning, connected car, vector correlation

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Authors: Vivek B. Ravindran, Aravind Surapaneni, Rebecca Traub, Sarvesh K. Soni, Andrew S. Ball

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Parasitic diseases have a devastating, long-term impact on human health and welfare. More than two billion people are infected with soil-transmitted helminths (STHs), including the roundworms (Ascaris), hookworms (Necator and Ancylostoma) and whipworm (Trichuris) with majority occurring in the tropical and subtropical regions of the world. Despite its low prevalence in developed countries, the removal of STHs from wastewater remains crucial to allow the safe use of sludge or recycled water in agriculture. Conventional methods such as incubation and optical microscopy are cumbersome; consequently, the results drastically vary from person-to-person observing the ova (eggs) under microscope. Although PCR-based methods are an alternative to conventional techniques, it lacks the ability to distinguish between viable and non-viable helminth ova. As a result, wastewater treatment industries are in major need for radically new and innovative tools to detect and quantify STHs eggs with precision, accuracy and being cost-effective. In our study, we focus on the following novel and innovative techniques: -Recombinase polymerase amplification and Surface enhanced Raman spectroscopy (RPA-SERS) based detection of helminth ova. -Use of metal nanoparticles and their relative nanozyme activity. -Colorimetric detection, differentiation and enumeration of genera of helminth ova using hydrolytic enzymes (chitinase and lipase). -Propidium monoazide (PMA)-qPCR to detect viable helminth ova. -Modified assay to recover and enumerate helminth eggs from fresh raw sewage. -Transcriptome analysis of ascaris ova in fresh raw sewage. The aforementioned techniques have the potential to replace current conventional and molecular methods thereby producing a standard protocol for the determination and enumeration of helminth ova in sewage sludge.

Keywords: colorimetry, helminth, PMA-QPCR, nanoparticles, RPA, viable

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Authors: Adekunle Taiwo Adenike, I. K. Ogundoyin

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Lassa fever is a neglected tropical virus that has become a significant public health issue in Nigeria, with the country having the greatest burden in Africa. This paper presents a Geo-Computational Model for Analysis and Prediction of Lassa Fever Dynamics and Outbreaks in Nigeria. The model investigates the dynamics of the virus with respect to environmental factors and human populations. It confirms the role of the rodent host in virus transmission and identifies how climate and human population are affected. The proposed methodology is carried out on a Linux operating system using the OSGeoLive virtual machine for geographical computing, which serves as a base for spatial ecology computing. The model design uses Unified Modeling Language (UML), and the performance evaluation uses machine learning algorithms such as random forest, fuzzy logic, and neural networks. The study aims to contribute to the control of Lassa fever, which is achievable through the combined efforts of public health professionals and geocomputational and machine learning tools. The research findings will potentially be more readily accepted and utilized by decision-makers for the attainment of Lassa fever elimination.

Keywords: geo-computational model, lassa fever dynamics, lassa fever, outbreak prediction, nigeria

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Authors: Michael Dole, Pierre Ninin, Denis Raffourt

Abstract:

Most of the CERN’s facilities hosting particle accelerators are large, underground and radioactive areas. All fire detection systems installed in such areas, shall be carefully studied to cope with the particularities of this stringent environment. The detection equipment usually chosen by CERN to secure these underground facilities are based on air sampling technology. The electronic equipment is located in non-radioactive areas whereas air sampling networks are deployed in radioactive areas where fire detection is required. The air sampling technology provides very good detection performances and prevent the "radiation-to-electronic" effects. In addition, it reduces the exposure to radiations of maintenance workers and is permanently available during accelerator operation. In order to protect the Super Proton Synchrotron and its 7 km tunnels, a specific long distance aspirating smoke detector has been developed to detect smoke at up to 700 meters between electronic equipment and the last air sampling hole. This paper describes the architecture, performances and return of experience of the long distance fire detection system developed and installed to secure the CERN Super Proton Synchrotron tunnels.

Keywords: air sampling, fire detection, long distance, radioactive areas

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Authors: Andrew John Zeller, Artjoms Formulevics

Abstract:

Banking and financial services are rapidly transitioning from being monolithic structures focusing merely on their own financial offerings to becoming integrated players in multiple customer journeys and supply chains. Banks themselves are refocusing on being liquidity providers and underwriters in these networks, while the general concept of ‘embeddedness’ builds on the market readily available API (Application Programming Interface) architectures to flexibly deliver services to various requestors, i.e., online retailers who need finance and insurance products to better serve their customers, respectively. With this new flexibility come new requirements for enhanced cybersecurity. API structures are more decentralized and inherently prone to change. Unfortunately, this has not been comprehensively addressed in the literature. This paper tries to fill this gap by looking at security approaches and technologies relevant to API architectures found in embedded finance. After presenting the research methodology applied and introducing the major bodies of knowledge involved, the paper will discuss six dominating technology trends shaping high-level financial services architectures. Subsequently, embedded finance and the respective usage of API strategies will be described. Building on this, security considerations for APIs in financial and insurance services will be elaborated on before concluding with some ideas for possible further research.

Keywords: embedded finance, embedded banking strategy, cybersecurity, API management, data security, cybersecurity, IT management

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Authors: Fabio T. Costa, Sergio E. Moya, Marcelo H. Sousa

Abstract:

Nanocomposites designed by embedding magnetic nanoparticles into a polymeric matrix stand out as ideal magnetic-hybrid and magneto-responsive materials as sorbents for removal of pollutants in environmental applications. Covalent coupling is often desired for the immobilization of species on these nanocomposites, in order to keep them permanently bounded, not desorbing or leaching over time. Moreover, unwanted adsorbates can be separated by successive washes/magnetic separations, and it is also possible to recover the adsorbate covalently bound to the nanocomposite surface through detaching/cleavage protocols. Thus, in this work, we describe the preparation and characterization of highly-magnetizable chloromethylated polystyrene-based nanocomposite beads for selective covalent coupling in environmental applications. For synthesis optimization, acid resistant core-shelled maghemite (γ-Fe₂O₃) nanoparticles were coated with oleate molecules and directly incorporated into the organic medium during a suspension polymerization process. Moreover, the cross-linking agent ethylene glycol dimethacrylate (EGDMA) was utilized for co-polymerization with the 4-vinyl benzyl chloride (VBC) to increase the resistance of microbeads against leaching. After characterizing samples with XRD, ICP-OES, TGA, optical, SEM and TEM microscopes, a magnetic composite consisting of ~500 nm-sized cross-linked polymeric microspheres embedding ~8 nm γ-Fe₂O₃ nanoparticles was verified. This nanocomposite showed large room temperature magnetization (~24 emu/g) due to the high content in maghemite (~45 wt%) and resistance against leaching even in acidic media. Moreover, the presence of superficial chloromethyl groups, probed by FTIR and XPS spectroscopies and confirmed by an amination test can selectively adsorb molecules through the covalent coupling and be used in molecular separations as shown for the selective removal of 4-aminobenzoic acid from a mixture with benzoic acid.

Keywords: nanocomposite, magnetic nanoparticle, covalent separation, pollutant removal

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Authors: Adinarayana Badveeti, Mohammad Shafi Mir

Abstract:

In Srinagar City, in India, traffic congestion is a condition on transport networks that occurs as use increases and is characterized by slower speeds, longer trip times, and increased vehicular queuing. Traffic congestion is conventionally measured using indicators such as roadway level-of-service, the Travel Time Index and their variants. Several measures have been taken in order to counteract congestion like road pricing, car pooling, improved traffic management, etc. While new road construction can temporarily relieve congestion in the longer term, it simply encourages further growth in car traffic through increased travel and a switch away from public transport. The full paper report, on which this abstract is based, aims to provide policymakers and technical staff with the real-time data, conceptual framework and guidance on some of the engineering tools necessary to manage congestion in such a way as to reduce its overall impact on individuals, families, communities, and societies dynamic, affordable, liveable and attractive urban regions will never be free of congestion. Road transport policies, however, should seek to manage congestion on a cost-effective basis with the aim of reducing the burden that excessive congestion imposes upon travellers and urban dwellers throughout the urban road network.

Keywords: traffic congestion, modeling, traffic management, travel time index

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Authors: Ergin Kosa, Ali Göksenli

Abstract:

Erosion and abrasion are wear mechanisms reducing the lifetime of machine elements like valves, pump and pipe systems. Both wear mechanisms are acting at the same time, causing a “Synergy” effect, which leads to a rapid damage of the surface. Different parameters are effective on erosive abrasive wear rate. In this study effect of particle impact angle on wear rate and wear mechanism of ductile and brittle materials was investigated. A new slurry pot was designed for experimental investigation. As abrasive particle, silica sand was used. Particle size was ranking between 200-500 µm. All tests were carried out in a sand-water mixture of 20% concentration for four hours. Impact velocities of the particles were 4,76 m/s. As ductile material steel St 37 with Brinell Hardness Number (BHN) of 245 and quenched St 37 with 510 BHN was used as brittle material. After wear tests, morphology of the eroded surfaces were investigated for better understanding of the wear mechanisms acting at different impact angles by using optical microscopy and Scanning Electron Microscope. The results indicated that wear rate of ductile material was higher than brittle material. Maximum wear was observed by ductile material at a particle impact angle of 300. On the contrary wear rate increased by brittle materials by an increase in impact angle and reached maximum value at 450. High amount of craters were detected after observation on ductile material surface Also plastic deformation zones were detected, which are typical failure modes for ductile materials. Craters formed by particles were deeper according to brittle material worn surface. Amount of craters decreased on brittle material surface. Microcracks around craters were detected which are typical failure modes of brittle materials. Deformation wear was the dominant wear mechanism on brittle material. At the end it is concluded that wear rate could not be directly related to impact angle of the hard particle due to the different responses of ductile and brittle materials.

Keywords: erosive wear, particle impact angle, silica sand, wear rate, ductile-brittle material

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Authors: Snezana Lazic, Zarko Gacevic, Mark Holmes, Ekaterina Chernysheva, Marcus Müller, Peter Veit, Frank Bertram, Juergen Christen, Yasuhiko Arakawa, Enrique Calleja

Abstract:

The study reports how the pencil-like morphology of a homoepitaxially grown GaN nanowire can be exploited for the fabrication of a thin conformal InGaN nanoshell, hosting nonpolar, semipolar and polar single photon sources (SPSs). All three SPS types exhibit narrow emission lines (FWHM~0.35 - 2 meV) and high degrees of linear optical polarization (P > 70%) in the low-temperature micro-photoluminescence (µ-PL) experiments and are characterized by a pronounced antibunching in the photon correlation measurements (gcorrected(2)(0) < 0.3). The quantum-dot-like exciton localization centers induced by compositional fluctuations within the InGaN nanoshell are identified as the driving mechanism for the single photon emission. As confirmed by the low-temperature transmission electron microscopy combined with cathodoluminescence (TEM-CL) study, the crystal region (i.e. non-polar m-, semi-polar r- and polar c-facets) hosting the single photon emitters strongly affects their emission wavelength, which ranges from ultra-violet for the non-polar to visible for the polar SPSs. The photon emission lifetime is also found to be facet-dependent and varies from sub-nanosecond time scales for the non- and semi-polar SPSs to a few nanoseconds for the polar ones. These differences are mainly attributed to facet-dependent indium content and electric field distribution across the hosting InGaN nanoshell. The hereby reported pencil-like InGaN nanoshell is the first single nanostructure able to host all three types of single photon emitters and is thus a promising building block for tunable quantum light devices integrated into future photonic and optoelectronic circuits.

Keywords: GaN nanowire, InGaN nanoshell, linear polarization, nonpolar, semipolar, polar quantum dots, single-photon sources

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