Search results for: network on chip

Authors: Maath M. Musleh

Abstract:

This research aims to study recent trends in the Palestinian feminist movement through the case study of Tal3at. The study uses social network analysis as its primary method to analyze Twitter data. It attempts to interpret results through the lens of network theories and Parson’s AGIL paradigm. The study reveals major structural weaknesses in the Tal3at network. Our findings suggest that the movement will decline soon as sentiments of alienation amongst Palestinian women increases. These findings were validated by a couple of central actors in the network. This study contributes an SNA approach to the understanding of the understudied Palestinian feminism.

Keywords: feminism, Palestine, social network analysis, Tal3at

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Authors: Abdulqader Rasool Feqi Mohammed, Ergun Erçelebi̇

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A large number of hospitals from developed countries are adopting hospital information system to bring efficiency in hospital information system. The purpose of this project is to research on new network security techniques in order to enhance the current network security structure of save a hospital information system (HIS). This is very important because, it will avoid the system from suffering any attack. Security architecture was optimized but there are need to keep researching on best means to protect the network from future attacks. In this final project research, security techniques were uncovered to produce best network security results when implemented in an integrated framework.

Keywords: hospital information system, HIS, network security techniques, internet protocol, IP, network

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Authors: Sina Saadati

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Multiprocessors Systems-On-Chips (MPSOCs) are used widely on modern computers to execute sophisticated software and applications. These systems include different processors for distinct aims. Most of the proposed task schedulers attempt to improve energy consumption. In some schedulers, the processor's temperature is considered to increase the system's reliability and performance. In this research, we have proposed a new method for thermal-aware task scheduling which is based on an artificial neural network (ANN). This method enables us to consider a variety of factors in the scheduling process. Some factors like ambient temperature, season (which is important for some embedded systems), speed of the processor, computing type of tasks and have a complex relationship with the final temperature of the system. This Issue can be solved using a machine learning algorithm. Another point is that our solution makes the system intelligent So that It can be adaptive. We have also shown that the computational complexity of the proposed method is cheap. As a consequence, It is also suitable for battery-powered systems.

Keywords: task scheduling, MOSOC, artificial neural network, machine learning, architecture of computers, artificial intelligence

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Authors: Ibrahim Aly, Manal Ahmed, Mahmoud M. El-Shall

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Filariasis is a parasitic disease caused by small roundworms. The filarial worms are transmitted and spread by blood-feeding black flies and mosquitoes. Lymphatic filariasis (Elephantiasis) is caused by Wuchereriabancrofti, Brugiamalayi, and Brugiatimori. Elimination of Lymphatic filariasis necessitates an increasing demand for valid, reliable, and rapid diagnostic kits. Nanodiagnostics involve the use of nanotechnology in clinical diagnosis to meet the demands for increased sensitivity, specificity, and early detection in less time. The aim of this study was to evaluate the nano-based enzymelinked immunosorbent assay (ELISA) and novel nano-chip card as a rapid test for detection of filarial antigen in serum samples of human filariasis in comparison with traditional -ELISA. Serum samples were collected from an infected human with filarial gathered across Egypt's governorates. After receiving informed consenta total of 45 blood samples of infected individuals residing in different villages in Gharbea governorate, which isa nonendemic region for bancroftianfilariasis, healthy persons living in nonendemic locations (20 persons), as well as sera from 20 other parasites, affected patients were collected. The microfilaria was checked in thick smears of 20 µl night blood samples collected during 20-22 hrs. All of these individuals underwent the following procedures: history taking, clinical examination, and laboratory investigations, which included examination of blood samples for microfilaria using thick blood film and serological tests for detection of the circulating filarial antigen using polyclonal antibody- ELISA, nano-based ELISA, and nano-chip card. In the present study, a recently reported polyoclonal antibody specific to tegumental filarial antigen was used in developing nano-chip card and nano-ELISA compared to traditional ELISA for the detection of circulating filarial antigen in sera of patients with bancroftianfilariasis. The performance of the ELISA was evaluated using 45 serum samples. The ELISA was positive with sera from microfilaremicbancroftianfilariasis patients (n = 36) with a sensitivity of 80 %. Circulating filarial antigen was detected in 39/45 patients who were positive for circulating filarial antigen using nano-ELISA with a sensitivity of 86.6 %. On the other hand, 42 out of 45 patients were positive for circulating filarial antigen using nano-chip card with a sensitivity of 93.3%.In conclusion, using a novel nano-chip assay could potentially be a promising alternative antigen detection test for bancroftianfilariasis.

Keywords: lymphatic filariasis, nanotechnology, rapid diagnosis, elisa technique

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Authors: Ahmed Jedidi, Mesfer Mohammed Alshamrani, Alwi Mohammad A. Bamhdi

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Optical performance monitoring and optical network management are essential in building a reliable, high-capacity, and service-differentiation enabled all-optical network. One of the serious problems in this network is the fact that optical crosstalk is additive, and thus the aggregate effect of crosstalk over a whole AON may be more nefarious than a single point of crosstalk. As results, we note a huge degradation of the Quality of Service (QoS) in our network. For that, it is necessary to identify and monitor the impairments in whole network. In this way, this paper presents new system to identify and monitor crosstalk in AONs in real-time fashion. particular, it proposes a new technique to manage intra-crosstalk in objective to relax QoS of the network.

Keywords: all-optical networks, optical crosstalk, optical cross-connect, crosstalk, monitoring crosstalk

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Authors: Sidra Shabbir, Ayesha Manzoor, Mehreen Sirshar

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The use of the network communication has imposed serious threats to the security of assets over the network. Network security is getting more prone to active and passive attacks which may result in serious consequences to data integrity, confidentiality and availability. Various cryptographic techniques have been proposed in the past few years to combat with the concerned problem by ensuring quality but in order to have a fully secured network; a framework of new cryptosystem was needed. This paper discusses certain cryptographic techniques which have shown far better improvement in the network security with enhanced quality assurance. The scope of this research paper is to cover the security pitfalls in the current systems and their possible solutions based on the new cryptosystems. The development of new cryptosystem framework has paved a new way to the widespread network communications with enhanced quality in network security.

Keywords: cryptography, network security, encryption, decryption, integrity, confidentiality, security algorithms, elliptic curve cryptography

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Authors: Feng-jie Xie, Jian-hong Yan

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Based on the complex network theory, we construct the air cargo network of the Belt and Road area, analyze its regional distribution and structural characteristics, measure the robustness of the network. The regional distribution results show that Southeast Asia and China have the most prominent development in the air cargo network of the Belt and Road area, Central Asia is the least developed. The structure characteristics found that the air cargo network has obvious small-world characteristics; the degree distribution has single-scale property; it shows a significant rich-club phenomenon simultaneously. The network robustness is measured by two attack strategies of degree and betweenness, but the betweenness of network nodes has a greater impact on network connectivity. And identified 24 key cities that have a large impact on the robustness of the network under the two attack strategies. Based on these results, recommendations are given to maintain the air cargo network connectivity in the Belt and Road area.

Keywords: air cargo, complex network, robustness, structure properties, The Belt and Road

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Authors: Jin Xu

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5G network developers need to satisfy the necessary requirements of additional capacity from massive users and spectrally efficient wireless technologies. Therefore, the significant amount of underutilized spectrum in network is motivating operators to combine long-term evolution (LTE) with intelligent spectrum management technology. This new LTE intelligent spectrum management in unlicensed band (LTE-U) has the physical layer topology to access spectrum, specifically the 5-GHz band. We proposed a new intelligent cloud RAN for 5G.

Keywords: cloud radio access network, wireless network, cloud computing, multi-agent

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Authors: V. Andal Priyadharshini, Anumalasetty Yashwanth Nath

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Network automation has evolved into a solution that ensures efficiency in all areas. The age-old technique to configure common software-defined networking protocols is inefficient as it requires a box-by-box approach that needs to be repeated often and is prone to manual errors. Network automation assists network administrators in automating and verifying the protocol configuration to ensure consistent configurations. This paper implemented network automation using Python and Ansible to configure different protocols and configurations in the container lab virtual environment. Ansible can help network administrators minimize human mistakes, reduce time consumption, and enable device visibility across the network environment.

Keywords: Python network automation, Ansible configuration, container lab deployment, software-defined networking, networking lab

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Authors: Chun-Ming Huang, Yi-Jun Liu, Yi-Jie Hsieh, Jin-Ju Chue, Wei-Lin Lai, Chun-Yu Chen, Chih-Chyau Yang, Chien-Ming Wu

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The market of wearable devices has been growing rapidly in two years. The integration of sensors and wearable devices has become the trend of the next technology products. Thus, the academics and industries are eager to cultivate talented persons in sensing technology. Currently, academic and industries have more and more demands on the integrations of versatile sensors and applications, especially for the teams who focus on the development of sensor circuit architectures. These teams tape-out many MEMs sensors chips through the chip fabrication service from National Chip Implementation Center (CIC). However, most of these teams are only able to focus on the circuit design of MEMs sensors; they lack the key support of further system demonstration. This paper follows the CIC’s main mission of promoting the chip/system advanced design technology and aims to establish the environments of the modularized sensing system platform and the system design flow with the measurement and calibration technology. These developed environments are used to support these research teams and help academically advanced sensor designs to perform the system demonstration. Thus, the research groups can promote and transfer their advanced sensor designs to industrial and further derive the industrial economic values. In this paper, the modularized sensing platform is proposed to enable the system demonstration for advanced sensor chip design. The environment of sensor measurement and calibration is established for academic to achieve an accurate sensor result. Two reference sensor designs cooperated with the modularized sensing platform are given to show the sensing system integration and demonstration. These developed environments and platforms are currently provided to academics in Taiwan, and so that the academics can obtain a better environment to perform the system demonstration and improve the research and teaching quality.

Keywords: modularized sensing platform, sensor design and calibration, sensor system, sensor system design flow

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Authors: Ahmed Moulay, Mariia Zhuldybina, Mirko Torres, Mike Rozel, Ngoc Duc Trinh, Chloé Bois

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Hybrid printed electronics technology (HPE) provides innovative opportunities to enhance conventional electronics applications, which are often based on printed circuit boards (PCB). By combining the best of both performance from conventional electronic components and the flexibility from printed circuits makes it possible to manufacture HPE at high volumes using roll-to-roll printing processes. However, several challenges must be overcome in order to accurately integrate an electronic component on a printed circuit. In this presentation, we will demonstrate the integration process of electronic components from the lab scale to the industrialization. Both the printing quality and the integration technique must be studied to define the optimal conditions. To cover the parameters that influence the print quality of the printed circuit, different printing processes, flexible substrates, and conductive inks will be used to determine the optimized printing process/ink/substrate system. After the systems is selected, an electronic component of 2.5 mm2 chip size will be integrated to validate the functionality of the printed, electronic circuit. Critical information such as the conductive adhesive, the curing conditions, and the chip encapsulation will be determined. Thanks to these preliminary results, we are able to demonstrate the chip integration on a printed circuit using industrial equipment, showing the potential of industrialization, compatible using roll-to-roll printing and integrating processes.

Keywords: flat bed screen-printing, hybrid printed electronics, integration, large-scale production, roll-to-roll printing, rotary screen printing

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Authors: Nashrawan Naser Taha, Andrew M. Cox

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In a multi-cultural learning context, where ties are weak and dynamic, combining qualitative with quantitative research methods may be more effective. Such a combination may also allow us to answer different types of question, such as about people’s perception of the network. In this study the use of observation, interviews and photos were explored as ways of enhancing data from social network questionnaires. Integrating all of these methods was found to enhance the quality of data collected and its accuracy, also providing a richer story of the network dynamics and the factors that shaped these changes over time.

Keywords: mixed methods, social network analysis, multi-cultural learning, social network dynamics

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Authors: Vadanasundari Vedarethinam, Kun Qian

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The metabolic analysis is more distal over proteomics and genomics engaging in clinics and needs rationally distinct techniques, designed materials, and device for clinical diagnosis. Conventional techniques such as spectroscopic techniques, biochemical analyzers, and electrochemical have been used for metabolic diagnosis. Currently, there are four major challenges including (I) long-term process in sample pretreatment; (II) difficulties in direct metabolic analysis of biosamples due to complexity (III) low molecular weight metabolite detection with accuracy and (IV) construction of diagnostic tools by materials and device-based platforms for real case application in biomedical applications. Development of chips with nanomaterial is promising to address these critical issues. Mass spectroscopy (MS) has displayed high sensitivity and accuracy, throughput, reproducibility, and resolution for molecular analysis. Particularly laser desorption/ ionization mass spectrometry (LDI MS) combined with devices affords desirable speed for mass measurement in seconds and high sensitivity with low cost towards large scale uses. We developed a plasmonic chip for clinical metabolic fingerprinting as a hot carrier in LDI MS by series of chips with gold nanoshells on the surface through controlled particle synthesis, dip-coating, and gold sputtering for mass production. We integrated the optimized chip with microarrays for laboratory automation and nanoscaled experiments, which afforded direct high-performance metabolic fingerprinting by LDI MS using 500 nL of serum, urine, cerebrospinal fluids (CSF) and exosomes. Further, we demonstrated on-chip direct in-vitro metabolic diagnosis of early-stage lung cancer patients using serum and exosomes without any pretreatment or purifications. To our best knowledge, this work initiates a bionanotechnology based platform for advanced metabolic analysis toward large-scale diagnostic use.

Keywords: plasmonic chip, metabolic fingerprinting, LDI MS, in-vitro diagnostics

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Authors: Mohsen Dourandish

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Iran has a huge pipeline network in every state of country which is the longest and vastest pipeline network after Russia and USA (360,000 Km high pressure pipelines and 250,000 Km distribution networks). Furthermore in recent years National Iranian Gas Company is planning to develop natural gas network to cover all cities and villages above 20 families, in a way that 97 percent of Iran population will be gas consumer by 2020. In this condition, network resiliency will be the first priority of NIGC and due to that several planning for increasing resiliency of gas network is under construction. The most important strategy of NIGC is converting tree form pattern network to loop gas networks and developing underground gas storage near main gas consuming centers. In this regard NIGC is planning for construction of over 3500 km high-pressure pipeline and also 10 TCM gas storage capacities in UGSs.

Keywords: Iranian gas network, peak shaving, resiliency, underground gas storage

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Authors: R. C. Law, Shirley Kang, T. Y. Hin, M. Z. Abdullah

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LED technology has been evolving aggressively in recent years from incandescent bulb during older days to as small as chip scale package. It will continue to stay bright in future. As such, there is tremendous pressure to stay competitive in the market by optimizing products to next level of performance and reliability with the shortest time to market. This changes the conventional way of product design and development to virtual prototyping by means of Computer Aided Engineering (CAE). It comprises of the deployment of Finite Element Method (FEM) and Computational Fluid Dynamic (CFD). FEM accelerates the investigation for early detection of failures such as crack, improve the thermal performance of system and enhance solder joint reliability. CFD helps to simulate the flow pattern of molding material as a function of different temperature, molding parameters settings to evaluate failures like voids and displacement. This paper will briefly discuss the procedures and applications of FEM in thermal stress, solder joint reliability and CFD of compression molding in LED CSP. Integration of virtual prototyping in product development had greatly reduced the time to market. Many successful achievements with minimized number of evaluation iterations required in the scope of material, process setting, and package architecture variant have been materialized with this approach.

Keywords: LED, chip scale packaging (CSP), computational fluid dynamic (CFD), virtual prototyping

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Authors: Ashfaq Khan, Aftab Khan, Mushtaq Khan, Sarem Sattar, Mohammad A Sheikh, Lin Li

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Chip removal processes are one of key processes of the manufacturing industry where chip removal is conducted by tool inserts of exceptionally hard materials. Tungsten carbide has been extensively used as tool insert for machining processes involving chip removal processes. These hard materials are generally fabricated by single step sintering process as further modification after fabrication in these materials cannot be done easily. Advances in tool surface modification have revealed that advantages such as improved tribological properties and extended tool life can be harnessed from the same tool by texturing the tool rake surface. Moreover, it has been observed that the shape and location of the texture also influences the behavior. Although texturing offers plentiful advantages the challenge lies in the generation of textures on the tool surface. Extremely hard material such as diamond is required to process tungsten carbide. Laser is unique processing tool that does not have a physical contact with the material and thus does not wear. In this research the potential of utilizing laser for texturing of tungsten carbide to develop custom features would be studied. A parametric study of texturing of Tungsten Carbide with a femtosecond laser would be conducted to investigate the process parameters and establish the feasible processing window. The effect of fluence, scan speed and number of repetition would be viewed in detail. Moreover, the mechanism for the generation of features would also be reviewed.

Keywords: laser, texturing, femtosecond, tungsten carbide

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Authors: Motonobu Hattori

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In neural networks, when new patters are learned by a network, they radically interfere with previously stored patterns. This drawback is called catastrophic forgetting. We have already proposed a biologically inspired dual-network memory model which can much reduce this forgetting for static patterns. In this model, information is first stored in the hippocampal network, and thereafter, it is transferred to the neocortical network using pseudo patterns. Because, temporal sequence learning is more important than static pattern learning in the real world, in this study, we improve our conventional dual-network memory model so that it can deal with temporal sequences without catastrophic forgetting. The computer simulation results show the effectiveness of the proposed dual-network memory model.

Keywords: catastrophic forgetting, dual-network, temporal sequences, hippocampal

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Authors: Yu Qin

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In order to tackle the ever-growing problem of the lack of parking space, this paper presents the design and implementation of a smart unmanned parking system that is based on RFID (radio frequency identification) technology and Wireless communication technology. This system uses RFID technology to achieve the identification function (transmitted by 2.4 G wireless module) and is equipped with an STM32L053 micro controller as the main control chip of the smart vehicle. This chip can accomplish automatic parking (in/out), charging and other functions. On this basis, it can also help users easily query the information that is stored in the database through the Internet. Experimental tests have shown that the system has the features of low power consumption and stable operation, among others. It can effectively improve the level of automation control of the parking lot management system and has enormous application prospects.

Keywords: RFID, embedded system, unmanned, parking management

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Authors: Min Jindong, Wang Mingxia

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With the widespread use of artificial intelligence in life, computer vision, especially deep convolutional neural network models, has developed rapidly. With the increase of the complexity of the real visual target detection task and the improvement of the recognition accuracy, the target detection network model is also very large. The huge deep neural network model is not conducive to deployment on edge devices with limited resources, and the timeliness of network model inference is poor. In this paper, knowledge distillation is used to compress the huge and complex deep neural network model, and the knowledge contained in the complex network model is comprehensively transferred to another lightweight network model. Different from traditional knowledge distillation methods, we propose a novel knowledge distillation that incorporates multi-faceted features, called M-KD. In this paper, when training and optimizing the deep neural network model for target detection, the knowledge of the soft target output of the teacher network in knowledge distillation, the relationship between the layers of the teacher network and the feature attention map of the hidden layer of the teacher network are transferred to the student network as all knowledge. in the model. At the same time, we also introduce an intermediate transition layer, that is, an intermediate guidance layer, between the teacher network and the student network to make up for the huge difference between the teacher network and the student network. Finally, this paper adds an exploration module to the traditional knowledge distillation teacher-student network model. The student network model not only inherits the knowledge of the teacher network but also explores some new knowledge and characteristics. Comprehensive experiments in this paper using different distillation parameter configurations across multiple datasets and convolutional neural network models demonstrate that our proposed new network model achieves substantial improvements in speed and accuracy performance.

Keywords: object detection, knowledge distillation, convolutional network, model compression

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Authors: Gunasekaran Raja, Ramkumar Jayaraman, Rajakumar Arul, Kottilingam Kottursamy

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Broadband Wireless Network (BWN) is the promising technology nowadays due to the increased number of smartphones. Buffering scheme using network coding considers the reliability and proper degree distribution in Worldwide interoperability for Microwave Access (WiMAX) multi-hop network. Using network coding, a secure way of transmission is performed which helps in improving throughput and reduces the packet loss in the multicast network. At the outset, improved network coding is proposed in multicast wireless mesh network. Considering the problem of performance overhead, degree distribution makes a decision while performing buffer in the encoding / decoding process. Consequently, BuS (Buffer Scheme) based on network coding is proposed in the multi-hop network. Here the encoding process introduces buffer for temporary storage to transmit packets with proper degree distribution. The simulation results depend on the number of packets received in the encoding/decoding with proper degree distribution using buffering scheme.

Keywords: encoding and decoding, buffer, network coding, degree distribution, broadband wireless networks, multicast

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Authors: Iliya Musa Adamu

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This paper seeks to develop an expert system that would troubleshoot computer network and evaluate the network system performance so as to reduce the workload on technicians and increase the efficiency and effectiveness of solutions proffered to computer network problems. The platform of the system was developed using ASP.NET, whereas the codes are implemented in Visual Basic and integrated with SQL Server 2005. The knowledge base was represented using production rule, whereas the searching method that was used in developing the network troubleshooting expert system is the forward-chaining-rule-based-system. This software tool offers the advantage of providing an immediate solution to most computer network problems encountered by computer users.

Keywords: expert system, forward chaining rule based system, network, troubleshooting

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Authors: Zhaojunfeng

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Driven by the national policy of "East Data and Western Calculation", the computing first network will attract a new wave of development. As the foundation of the development of the computing first network, the computing force bearer network has become the key direction of technology research and development in the industry. This article will analyze typical computing force application scenarios and bearing requirements and sort out the SLA indicators of computing force applications. On this basis, this article carries out research and discussion on the key technologies of computing force bearer network in a slice packet network, and finally, gives evolution policy for SPN computing force bearer network to support the development of SPN computing force bearer network technology and network deployment.

Keywords: component-computing force bearing, bearing requirements of computing force application, dual-SLA indicators for computing force applications, SRv6, evolution strategies

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Authors: Abdelhadi Lotfi, Abdelkader Benyettou

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In this work, a training algorithm for probabilistic neural networks (PNN) is presented. The algorithm addresses one of the major drawbacks of PNN, which is the size of the hidden layer in the network. By using a cross-validation training algorithm, the number of hidden neurons is shrunk to a smaller number consisting of the most representative samples of the training set. This is done without affecting the overall architecture of the network. Performance of the network is compared against performance of standard PNN for different databases from the UCI database repository. Results show an important gain in network size and performance.

Keywords: classification, probabilistic neural networks, network optimization, pattern recognition

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Authors: Anca Radulescu, Danae Evans

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The relationship between a network’s hardwiring and its emergent dynamics are central to neuroscience. We study the principles of this correspondence in a canonical setup (in which network nodes exhibit well-studied complex quadratic dynamics), then test their universality in biological networks. By extending methods from discrete dynamics, we study the effects of network connectivity on temporal patterns, encapsulating long-term behavior into the rich topology of network Mandelbrot sets. Then elements of fractal geometry can be used to predict and classify network behavior.

Keywords: canonical model, complex dynamics, dynamic networks, fractals, Mandelbrot set, network connectivity

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Authors: Rawan Ashraf, Ahmed E. Gomaa, Gehan Safwat, Ayman Diab

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Background: Three-dimensional (3D) bio-printing has become a versatile and powerful method for generating a variety of biological constructs, including bone or extracellular matrix scaffolds endo- or epithelial, muscle tissue, as well as organoids. Aim of the study: Fabricate a low cost DIY 3D bio-printer to produce 3D bio-printed products such as anti-microbial packaging or multi-organs on chips. We demonstrate the alignment between two types of 3D printer technology (3D Bio-printer and DLP) on Multi-organ-on-a-chip (multi-OoC) devices fabrication. Methods: First, Design and Fabrication of the Syringe Unit for Modification of an Off-the-Shelf 3D Printer, then Preparation of Hydrogel based on natural polymers Sodium Alginate and Gelatin, followed by acquisition of the cell suspension, then modeling the desired 3D structure. Preparation for 3D printing, then Cell-free and cell-laden hydrogels went through the printing process at room temperature under sterile conditions and finally post printing curing process and studying the printed structure regards physical and chemical characteristics. The hard scaffold of the Organ on chip devices was designed and fabricated using the DLP-3D printer, following similar approaches as the Microfluidics system fabrication. Results: The fabricated Bio-Ink was based onHydrogel polymer mix of sodium alginate and gelatin 15% to 0.5%, respectively. Later the 3D printing process was conducted using a higher percentage of alginate-based hydrogels because of it viscosity and the controllable crosslinking, unlike the thermal crosslinking of Gelatin. The hydrogels were colored to simulate the representation of two types of cells. The adaption of the hard scaffold, whether for the Microfluidics system or the hard-tissues, has been acquired by the DLP 3D printers with fabricated natural bioactive essential oils that contain antimicrobial activity, followed by printing in Situ three complex layers of soft-hydrogel as a cell-free Bio-Ink to simulate the real-life tissue engineering process. The final product was a proof of concept for a rapid 3D cell culturing approaches that uses an engineered hard scaffold along with soft-tissues, thus, several applications were offered as products of the current prototype, including the Organ-On-Chip as a successful integration between DLP and 3D bioprinter. Conclusion: Multiple designs for the organ-on-a-chip (multi-OoC) devices have been acquired in our study with main focus on the low cost fabrication of such technology and the potential to revolutionize human health research and development. We describe circumstances in which multi-organ models are useful after briefly examining the requirement for full multi-organ models with a systemic component. Following that, we took a look at the current multi-OoC platforms, such as integrated body-on-a-chip devices and modular techniques that use linked organ-specific modules.

Keywords: 3d bio-printer, hydrogel, multi-organ on chip, bio-inks

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Authors: Mohamed Raouf Benmakrelouf, Wafa Karouche, Joseph Rynkiewicz

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In this paper, we propose an alternative method to construct a Bayesian Network (BN). This method relies on a convolutional neural network (CNN classifier), which determinates the edges of the network skeleton. We train a CNN on a normalized empirical probability density distribution (NEPDF) for predicting causal interactions and relationships. We have to find the optimal Bayesian network structure for causal inference. Indeed, we are undertaking a search for pair-wise causality, depending on considered causal assumptions. In order to avoid unreasonable causal structure, we consider a blacklist and a whitelist of causality senses. We tested the method on real data to assess the influence of education on the voting intention for the extreme right-wing party. We show that, with this method, we get a safer causal structure of variables (Bayesian Network) and make to identify a variable that satisfies the backdoor criterion.

Keywords: Bayesian network, structure learning, optimal search, convolutional neural network, causal inference

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Authors: Christopher Godwin Udomboso, Angela Unna Chukwu, Isaac Kwame Dontwi

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In selecting a Statistical Neural Network model, the Network Information Criterion (NIC) has been observed to be sample biased, because it does not account for sample sizes. The selection of a model from a set of fitted candidate models requires objective data-driven criteria. In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC), based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The analyses show that on a general note, the ANIC improves model selection in more sample sizes than does the NIC.

Keywords: statistical neural network, network information criterion, adjusted network, information criterion, transfer function

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Authors: Sherif K. El Dyasti, Esam A. Hagras, Adel E. El-Hennawy

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This paper addresses the performance of antenna array beam-forming on Chip-Interleaved Code Division Multiple Access (CI_CDMA) system based on Minimum Mean Square Error (MMSE) detector in aeronautical mobile radio channel. Multipath fading, Doppler shifts caused by the speed of the aircraft, and Multiple Access Interference (MAI) are the most important reasons that affect and reduce the performance of aeronautical system. In this paper, we suggested the CI-CDMA with antenna array to combat this fading and improve the bit error rate (BER) performance. We further evaluate the performance of the proposed system in the four standard scenarios in aeronautical mobile radio channel.

Keywords: aeronautical channel, CI-CDMA, beamforming, communication, information

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Authors: Navaneeth Krishnan, Chandan N. Bhagwat, Aparajit P. Utpat

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Cloud Computing provides us a means to upload data and use applications over the internet. As the number of devices connecting to the cloud grows, there is undue pressure on the cloud infrastructure. Fog computing or Network Based Computing or Edge Computing allows to move a part of the processing in the cloud to the network devices present along the node to the cloud. Therefore the nodes connected to the cloud have a better response time. This paper proposes a method of moving the computation from the cloud to the network by introducing an android like appstore on the networking devices.

Keywords: cloud computing, fog computing, network devices, appstore

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Authors: M. Kollar, A. Zieba

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In this paper, we present a method for a time synchronization between the two eNodeBs (eNBs) in E-UTRAN (Evolved Universal Terrestrial Radio Access) network. The two eNBs are cooperating in so-called inter eNB CA (Carrier Aggregation) case and connected via asymmetrical IP network. We solve the problem by using broadcasting signals generated in E-UTRAN as synchronization signals. The results show that the time synchronization with the proposed method is possible with the error significantly less than 1 ms which is sufficient considering the time transmission interval is 1 ms in E-UTRAN. This makes this method (with low complexity) more suitable than Network Time Protocol (NTP) in the mobile applications with generated broadcasting signals where time synchronization in asymmetrical network is required.

Keywords: IP scheduled throughput, E-UTRAN, Evolved Universal Terrestrial Radio Access Network, NTP, Network Time Protocol, assymetric network, delay

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