Search results for: nano on-chip network

Authors: Behzad Niknam, Kourosh Shahriar, Hassan Madani

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This paper demonstrates the applicability of Hybrid Neural Networks that combine with back propagation networks (BPN) and Genetic Algorithms (GAs) for predicting the flame length of tunnel fire A hybrid neural network model has been developed to predict the flame length of tunnel fire based parameters such as Fire Heat Release rate, air velocity, tunnel width, height and cross section area. The network has been trained with experimental data obtained from experimental work. The hybrid neural network model learned the relationship for predicting the flame length in just 3000 training epochs. After successful learning, the model predicted the flame length.

Keywords: tunnel fire, flame length, ANN, genetic algorithm

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Authors: A. Hakimiyan, H. Namazi

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Human behavior is defined as a range of behaviors exhibited by humans who are influenced by different internal or external sources. Human behavior is the subject of much research in different areas of psychology and neuroscience. Despite some advances in studies related to forecasting of human behavior, there are not many researches which consider the effect of the time delay between the presence of stimulus and the related human response. Analysis of EEG signal as a fractal time series is one of the major tools for studying the human behavior. In the other words, the human brain activity is reflected in his EEG signal. Artificial Neural Network has been proved useful in forecasting of different systems’ behavior especially in engineering areas. In this research, a time delay neural network is trained and tested in order to forecast the human EEG signal and subsequently human behavior. This neural network, by introducing a time delay, takes care of the lagging time between the occurrence of the stimulus and the rise of the subsequent action potential. The results of this study are useful not only for the fundamental understanding of human behavior forecasting, but shall be very useful in different areas of brain research such as seizure prediction.

Keywords: human behavior, EEG signal, time delay neural network, prediction, lagging time

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Authors: Byung-Ik Kim, Hong-Koo Kang, Tae-Jin Lee, Hae-Ryong Park

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Cyber terrors against specific enterprises or countries have been increasing recently. Such attacks against specific targets are called advanced persistent threat (APT), and they are giving rise to serious social problems. The malicious behaviors of APT attacks mostly affect websites and penetrate enterprise networks to perform malevolent acts. Although many enterprises invest heavily in security to defend against such APT threats, they recognize the APT attacks only after the latter are already in action. This paper discusses the characteristics of APT attacks at each step as well as the strengths and weaknesses of existing malicious code detection technologies to check their suitability for detecting APT attacks. It then proposes a network-based malicious behavior detection algorithm to protect the enterprise or national networks.

Keywords: Advanced Persistent Threat (APT), malware, network security, network packet, exploit kits

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Authors: Jiawen Wang, Qijun Chen

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The performance of most machine-learning methods for image inpainting depends on the quantity and quality of the training samples. However, it is very expensive or even impossible to obtain a great number of training samples in many scenarios. In this paper, an image inpainting model based on a generative adversary network (GAN) is constructed for the cases when the number of training samples is small. Firstly, a feature extraction network (F-net) is incorporated into the GAN network to utilize the available information of the inpainting image. The weighted sum of the extracted feature and the random noise acts as the input to the generative network (G-net). The proposed network can be trained well even when the sample size is very small. Secondly, in the phase of the completion for each damaged image, a genetic algorithm is designed to search an optimized noise input for G-net; based on this optimized input, the parameters of the G-net and F-net are further learned (Once the completion for a certain damaged image ends, the parameters restore to its original values obtained in the training phase) to generate an image patch that not only can fill the missing part of the damaged image smoothly but also has visual semantics.

Keywords: image inpainting, generative adversary nets, genetic algorithm, small-sample size

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Authors: Khamael M. Abualnaja, Lidija Šiller, Benjamin R. Horrocks

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Metal-enhanced luminescence of silicon nano crystals (SiNCs) was determined using two different particle sizes of silver nano particles (AgNPs). SiNCs have been characterized by scanning electron microscopy (SEM), high resolution transmission electron microscopy (HRTEM), Fourier transform infrared spectroscopy (FTIR) and X-ray photo electron spectroscopy (XPS). It is found that the SiNCs are crystalline with an average diameter of 65 nm and FCC lattice. AgNPs were synthesized using photochemical reduction of AgNO3 with sodium dodecyl sulphate (SDS). The enhanced luminescence of SiNCs by AgNPs was evaluated by confocal Raman microspectroscopy. Enhancement up to ×9 and ×3 times were observed for SiNCs that mixed with AgNPs which have an average particle size of 100 nm and 30 nm, respectively. Silver NPs-enhanced luminescence of SiNCs occurs as a result of the coupling between the excitation laser light and the plasmon bands of AgNPs; thus this intense field at AgNPs surface couples strongly to SiNCs.

Keywords: silver nanoparticles, surface enhanced raman spectroscopy (SERS), silicon nanocrystals, luminescence

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Authors: Khalaf Khatatneh, Nabeel Al-Milli, Amjad Hudaib, Monther Ali Tarawneh

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Software fault prediction identify potential faults in software modules during the development process. In this paper, we present a novel approach for software fault prediction by combining a feedforward neural network with particle swarm optimization (PSO). The PSO algorithm is employed as a feature selection technique to identify the most relevant metrics as inputs to the neural network. Which enhances the quality of feature selection and subsequently improves the performance of the neural network model. Through comprehensive experiments on software fault prediction datasets, the proposed hybrid approach achieves better results, outperforming traditional classification methods. The integration of PSO-based feature selection with the neural network enables the identification of critical metrics that provide more accurate fault prediction. Results shows the effectiveness of the proposed approach and its potential for reducing development costs and effort by detecting faults early in the software development lifecycle. Further research and validation on diverse datasets will help solidify the practical applicability of the new approach in real-world software engineering scenarios.

Keywords: feature selection, neural network, particle swarm optimization, software fault prediction

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Authors: Nihit Madireddi, P. A. Mahanwar

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We have aimed to produce a self-cleaning transparent polymer coating with polyurethane (PU) matrix as the latter is highly solvent, chemical and weather resistant having good mechanical properties. Nano-silica modified by 1H, 1H, 2H, 2H-perflurooctyltriethoxysilane was incorporated into the PU matrix for attaining self-cleaning ability through hydrophobicity. The modification was confirmed by particle size analysis and scanning electron microscopy (SEM). Thermo-gravimetric (TGA) studies were carried to ascertain the grafting of silane onto the silica. Several coating formulations were prepared by varying the silica loading content and compared to a commercial equivalent. The effect of dispersion and the morphology of the coated films were assessed by SEM analysis. All coating standardized tests like solvent resistance, adhesion, flexibility, acid, alkali, gloss etc. have been performed as per ASTM standards. Water contact angle studies were conducted to analyze the hydrophobic character of the coating. In addition, the coatings were also subjected to salt spray and accelerated weather testing to analyze the durability of the coating.

Keywords: FAS, nano-silica, PU clear coat, self-cleaning

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Authors: D. Bikiaris, M. Nerantzaki, I. Koliakou, A. Francone, N. Kehagias

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In the present study, the formation of structures in poly(lactic acid) (PLA) has been investigated with respect to producing areas of regular, superficial features with dimensions comparable to those of cells or biological macromolecules. Nanoimprint lithography, a method of pattern replication in polymers, has been used for the production of features ranging from tens of micrometers, covering areas up to 1 cm², down to hundreds of nanometers. Both micro- and nano-structures were faithfully replicated. Potentially, PLA has wide uses within biomedical fields, from implantable medical devices, including screws and pins, to membrane applications, such as wound covers, and even as an injectable polymer for, for example, lipoatrophy. The possibility of fabricating structured PLA surfaces, with structures of the dimensions associated with cells or biological macro- molecules, is of interest in fields such as cellular engineering. Imprint-based technologies have demonstrated the ability to selectively imprint polymer films over large areas resulting in 3D imprints over flat, curved or pre-patterned surfaces. Here, we compare nano-patterned with nano-patterned by nanoimprint lithography (NIL) PLA film. A silicon nanostructured stamp (provided by Nanotypos company) having positive and negative protrusions was used to pattern PLA films by means of thermal NIL. The polymer film was heated from 40°C to 60°C above its Tg and embossed with a pressure of 60 bars for 3 min. The stamp and substrate were demolded at room temperature. Scanning electron microscope (SEM) images showed good replication fidelity of the replicated Si stamp. Contact-angle measurements suggested that positive microstructuring of the polymer (where features protrude from the polymer surface) produced a more hydrophilic surface than negative micro-structuring. The ability to structure the surface of the poly(lactic acid), allied to the polymer’s post-processing transparency and proven biocompatibility. Films produced in this were also shown to enhance the aligned attachment behavior and proliferation of Wharton’s Jelly Mesenchymal Stem cells, leading to the observed growth contact guidance. The bacterial attachment patterns of some bacteria, highlighted that the nano-patterned PLA structure can reduce the propensity for the bacteria to attach to the surface, with a greater bactericidal being demonstrated activity against the Staphylococcus aureus cells. These biocompatible, micro- and nanopatterned PLA surfaces could be useful for polymer– cell interaction experiments at dimensions at, or below, that of individual cells. Indeed, post-fabrication modification of the microstructured PLA surface, with materials such as collagen (which can further reduce the hydrophobicity of the surface), will extend the range of applications, possibly through the use of PLA’s inherent biodegradability. Further study is being undertaken to examine whether these structures promote cell growth on the polymer surface.

Keywords: poly(lactic acid), nano-imprint lithography, anti-bacterial properties, PLA

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Authors: Seyed Mahdi Rafiaei

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In this investigation, firstly Eu3+ doped YVO4 phosphor was synthesized using solid-state method. Then silica was coated on the surface of particles via sol-gel method. To study the influence of SiO2 addition on microstructure and photoluminescence characteristics of YVO4:4% Eu3+ phosphor materials, we employed X-ray Diffraction (XRD), Field Emission Scanning Electron Microscope (FESEM), High-Resolution Transmitted Electron Microscope (HRTEM), Focused Ion Beam (FIB), Brunauer Emmett Teller (BET), Inductively coupled plasma (ICP), Electron Spin Resonance (ESR) and Photoluminescence (PL) equipments. The XPS characterization confirmed the formation of Y–O–Si and V-O-Si bondings between YVO4:Eu3+ phosphor particle and SiO2 coating. In addition, it was found that although the amounts of added SiO2 were not remarkable, but it resulted in enhancement of emission intensity of the phosphors. Finally by employing ESR analysis, it was shown that surface oxygen vacancies, result in reduction of V5+ to the lower valence state of V4+.

Keywords: solid state, sol-gel, silica, coating, photoluminescence

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Authors: Trupti Chavan, Ramachandra Guda, Kameshwar Rao

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The lack of data is a pain problem in medical image analysis using a convolutional neural network (CNN). This work uses various spatial transformation techniques to address the medical image augmentation issue for knee detection and localization using an enhanced single shot detector (SSD) network. The spatial transforms like a negative, histogram equalization, power law, sharpening, averaging, gaussian blurring, etc. help to generate more samples, serve as pre-processing methods, and highlight the features of interest. The experimentation is done on the OpenKnee dataset which is a collection of knee images from the openly available online sources. The CNN called enhanced single shot detector (SSD) is utilized for the detection and localization of the knee joint from a given X-ray image. It is an enhanced version of the famous SSD network and is modified in such a way that it will reduce the number of prediction boxes at the output side. It consists of a classification network (VGGNET) and an auxiliary detection network. The performance is measured in mean average precision (mAP), and 99.96% mAP is achieved using the proposed enhanced SSD with spatial transformations. It is also seen that the localization boundary is comparatively more refined and closer to the ground truth in spatial augmentation and gives better detection and localization of knee joints.

Keywords: data augmentation, enhanced SSD, knee detection and localization, medical image analysis, openKnee, Spatial transformations

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Authors: Radhiyatul Hikmah Binti Abu, Zukhairi Bin Md Rahim, Siti Ujila Binti Masuri, Nur Ismarrubie Binti Zahari, Mohd Zobir Hussein

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This paper describes the synthesis of Calcium Diethylenetriamine-penta (Ca-DTPMP) Scale Inhibitor (SI) and the effect of temperature on its adsorption onto the mineral surfaces. Nanosized particles of Ca-DTPMP SI were synthesized and TEM result shows that the sizes of the synthesized particles are ranged from 10 nm to 30 nm. This synthesized nano SI was then used in static adsorption/precipitation test with various temperatures (37°C, 60°C and 100°C) to determine the effect of temperature on its adsorption ability. The performance of the SI was measured by their diffusion capability, which can be inferred by weighing the metal-SI that successfully adsorbed onto the kaolinite (mineral) surface. The kaolinite samples were analyzed using Scanning Electron Microscope (SEM) and the results show the reduction of pores on kaolinite surface as temperature increases. This indicates higher adsorption of the SI particles onto the mineral surface. Furthermore, EDX analysis shows the presence of Phosphorus (P) and Magnesium (Mg2+) on kaolinite particle surface, hence reaffirming the fact that adsorption took place on the kaolinite surface.

Keywords: adsorption, diffusivity, scale, scale inhibitor

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Authors: A. Belayadi, A. Mougari, L. Ait-Gougam, F. Mekideche-Chafa

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The artificial neural network is one of the interesting techniques that have been advantageously used to deal with modeling problems. In this study, the computing with artificial neural network (CANN) is proposed. The model is applied to modulate the information processing of one-dimensional task. We aim to integrate a new method which is based on a new coding approach of generating the input-output mapping. The latter is based on increasing the neuron unit in the last layer. Accordingly, to show the efficiency of the approach under study, a comparison is made between the proposed method of generating the input-output set and the conventional method. The results illustrated that the increasing of the neuron units, in the last layer, allows to find the optimal network’s parameters that fit with the mapping data. Moreover, it permits to decrease the training time, during the computation process, which avoids the use of computers with high memory usage.

Keywords: neural network computing, continuous functions generating the input-output mapping, decreasing the training time, machines with big memories

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Authors: Dorota Galeza

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This paper argues that networks, such as the ECN and the American network, are affected by certain small events which are inherent to path dependence and preclude the full evolution towards efficiency. It is advocated that the American network is superior to the ECN in many respects due to its greater flexibility and longer history. This stems in particular from the creation of the American network, which was based on a small number of cases. Such structure encourages further changes and modifications which are not necessarily radical. The ECN, by contrast, was established by legislative action, which explains its rigid structure and resistance to change. It might be the case that the ECN is subject not so much to path dependence but to past dependence. It might have to be replaced, as happened to its predecessor. This paper is an attempt to transpose the superiority of the American network on to the ECN. It looks at concepts such as judicial cooperation, harmonization of procedure, peer review and regulatory impact assessments (RIAs), and dispute resolution procedures. The aim is to adopt these concepts into the EU setting without recourse to legal transplantation. The major difficulty is that many of these concepts have been tested only in the US and it is difficult to tell whether they could be modified to meet EU standards. Concepts such as judicial cooperation might be difficult due to different language traditions in EU member states. It is hoped that greater flexibility, as in the American network, would boost legitimacy and transparency.

Keywords: ECN, networks, regulation, competition

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Authors: Debajyoti Mukherjee, Arathy B. S., Arpita Sahu, Saranga P. Pogula

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A functional model to mimic the functional correctness of a neural network compute accelerator IP is very crucial for design validation. Neural network workloads are based on a Brain Floating Point (BF-16) data type. The major challenge we were facing was the incompatibility of GCC compilers to the BF-16 datatype, which we addressed with a native BF-16 generator integrated into our functional model. Moreover, working with big GEMM (General Matrix Multiplication) or SpMM (Sparse Matrix Multiplication) Work Loads (Dense or Sparse) and debugging the failures related to data integrity is highly painstaking. In this paper, we are addressing the quality challenge of such a complex neural network accelerator design by proposing a functional model-based scoreboard or software model using SystemC. The proposed functional model executes the assembly code based on the ISA of the processor IP, decodes all instructions, and executes as expected to be done by the DUT. The said model would give a lot of visibility and debug capability in the DUT, bringing up micro-steps of execution.

Keywords: ISA, neural network, Brain Float-16, DUT

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Authors: Edward P. Guillen, A. Karina Martinez Barliza

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Powerline Communications (PLC) as last mile solution to provide communication services, has the advantage of transmitting over channels already used for electrical distribution. However these channels have been not designed with this purpose, for that reason telecommunication companies in Colombia want to know how good would be using PLC in costs and network performance in comparison to cable modem or DSL. This paper analyzes PLC throughput for residential complex scenarios using a PLC network scenarios and some statistical results are shown.

Keywords: home network, power line communication, throughput analysis, power factor, cost, last mile solution

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Authors: Johnson O. Adeogo, Ayodele S. Oluwole, O. Akinsanmi, Olawale J. Olaluyi

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In this 5G network, very high traffic density in densely populated areas, most especially in densely populated areas, is one of the key requirements. Radiation reduction becomes one of the major concerns to secure the future life of mobile network users in ultra-dense network areas using an improved coordinated multipoint technology. Coordinated Multi-Point (CoMP) is based on transmission and/or reception at multiple separated points with improved coordination among them to actively manage the interference for the users. Small cells have two major objectives: one, they provide good coverage and/or performance. Network users can maintain a good quality signal network by directly connecting to the cell. Two is using CoMP, which involves the use of multiple base stations (MBS) to cooperate by transmitting and/or receiving at the same time in order to reduce the possibility of electromagnetic radiation increase. Therefore, the influence of the screen guard with rubber condom on the mobile transceivers as one major piece of equipment radiating electromagnetic radiation was investigated by mobile network users amidst ultra-dense networks in 5g. The results were compared with the same mobile transceivers without screen guards and rubber condoms under the same network conditions. The 5 cm distance from the mobile transceivers was measured with the help of a ruler, and the intensity of Radio Frequency (RF) radiation was measured using an RF meter. The results show that the intensity of radiation from various mobile transceivers without screen guides and condoms was higher than the mobile transceivers with screen guides and condoms when call conversation was on at both ends.

Keywords: ultra-dense networks, mobile network users, 5g, coordinated multi-point.

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Authors: Aman Patidar, Dipankar Sarkar, Manish Pal

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Due to rapid development, increase in the traffic load, higher traffic volume and seasonal variation in temperature, asphalt pavement shows distresses like rutting, fatigue and thermal cracking etc. because of this pavement fails during service life so that bitumen needs to be modified with some additive. In this study VG30 grade bitumen modify with addition of nanosilica with 1% to 5% (increment of 1%) by weight of bitumen. Hot mix asphalt (HMA) have higher mixing, laying and rolling temperatures which leads to higher consumption of fuel. To address this issue, a nano material named ZycoTherm which is chemical warm mix asphalt (WMA) additive is added to bitumen. Nanosilica modification (NSMB) results in the increase in stability compared to unmodified bitumen (UMB). WMA modified mix shows slightly higher stability than UMB and NSMB in a lower bitumen content. The Retained stability and tensile strength ratio (TSR) is more than 75% and 80% respectively for both mixes. Nanosilica with WMA has more resistant to temperature susceptibility, moisture susceptibility and short term aging than NSMB.

Keywords: HMA, nanosilica, NSMB, temperature, TSR, UMB, WMA

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Authors: Harsh Sadawarti, Kamal Malik

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Humans are the unique and the most powerful creature on this planet just because of the high level of intelligence gifted by nature. Computational Intelligence is highly influenced by the term natural intelligence, neurosciences and mathematics. To deal with the in-depth study of computational intelligence and to utilize it in real-life applications, it is quite important to understand its simulation with the human brain. In this paper, the three important parts, Frontal Lobe, Occipital Lobe and Parietal Lobe of the human brain, are compared with the ANN(Artificial Neural Network), CNN(Convolutional Neural network), and RNN(Recurrent Neural Network), respectively. Intelligent computational systems are created by combining deductive reasoning, logical concepts and high-level algorithms with the simulation and study of the human brain. Human brain is a combination of Physiology, Psychology, emotions, calculations and many other parameters which are of utmost importance that determines the overall intelligence. To create intelligent algorithms, smart machines and to simulate the human brain in an effective manner, it is quite important to have an insight into the human brain and the basic concepts of biological neurosciences.

Keywords: computational intelligence, neurosciences, convolutional neural network, recurrent neural network, artificial neural network, frontal lobe, occipital lobe, parietal lobe

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Authors: Teklu Urgessa, Joong Seek Lee

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Social media is becoming the primary choice of activists to make their voices heard. This fact is coupled by two main reasons. The first reason is the emergence web 2.0, which gave the users opportunity to become content creators than passive recipients. Secondly the control of the mainstream mass media outlets by the governments and individuals with their political and economic interests. This paper aimed at exploring twitter data of network actors talking about the marathon silver medalists on Rio2016, who showed solidarity with the Oromo protesters in Ethiopia on the marathon race finish line when he won silver. The aim is to discover important insight using social network analysis and mining. The hashtag #FeyisaLelisa was used for Twitter network search. The actors’ network was visualized and analyzed. It showed the central influencers during first 10 days in August, were international media outlets while it was changed to individual activist in September. The degree distribution of the network is scale free where the frequency of degrees decay by power low. Text mining was also used to arrive at meaningful themes from tweet corpus about the event selected for analysis. The semantic network indicated important clusters of concepts (15) that provided different insight regarding the why, who, where, how of the situation related to the event. The sentiments of the words in the tweets were also analyzed and indicated that 95% of the opinions in the tweets were either positive or neutral. Overall, the finding showed that Olympic stage protest of the marathoner brought the issue of Oromo protest to the global stage. The new research framework is proposed based for event-based social network analysis and mining based on the practical procedures followed in this research for event-based social media sense making.

Keywords: human rights, Olympics, social media, network analysis, social network ming

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Authors: Hossein Kabir, Mojtaba Sadeghi

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Nowadays, high-strength concrete is an integral element of a variety of high-rise buildings. On the other hand, finding a suitable aggregate size distribution is a great concern; hence, the concrete mix proportion is presented that has no coarse aggregate, which still withstands enough desirable strength. Nano Reactive Silica sand powder concrete (NRSSPC) is a type of concrete with no coarse material in its own composition. In this concrete, the only aggregate found in the mix design is silica sand powder with a size less than 150 mm that is infinitesimally small regarding the normal concrete. The research aim is to find the compressive strength of this particular concrete under the applied different conditions of curing and consolidation to compare the approaches. In this study, the young concrete specimens were compacted with a pressing or vibrating process. It is worthwhile to mention that in order to show the influence of temperature in the curing process, the concrete specimen was cured either in 20 ⁰C lime water or autoclaved in 90 ⁰C oven.

Keywords: reactive silica sand powder concrete (RSSPC), consolidation, compressive strength, normal curing, thermal accelerated curing

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Authors: Mohammad Shakir, Reshma Jolly, Mohammad Shoeb Khan, Noor-E-Iram

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A nanocomposite system incorporating dextrin into nano-hydroxyapatite/chitin matrix (n-HA/DX/CT) has been successfully synthesized via co-precipitation route at room temperature for the application in bone tissue engineering by investigating biocompatibility, cytotoxicity and mechanical properties. The FTIR spectra of n-HA/DX/CT nanocomposite indicated a considerable intermolecular interaction between the various components of the system. The results of XRD, TEM and TGA/DTA revealed that the crystallinity, size and thermal stability of the n-HA/DX/CT scaffold has decreased and increased respectively. The result of SEM image of the n-HA/DX/CT scaffold indicated that the incorporation of dextrin affected the surface morphology while considerable in-vitro bioactivity has been observed in n-HA/DX/CT based on SBF study, referring a step towards possibility of making direct bond to living bone if implanted. Moreover, MTT assay suggested the non-toxic nature of n-HA/DX/CT to murine fibroblast L929 cells. The swelling study of n-HA/DX/CT scaffold indicated the low swelling rate for n-HADX/CT. All these results have paved the way for n-HA/DX/CT to be used as a competent material for bone tissue engineering.

Keywords: autograft, chitin, dextrin, nanocomposite

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Authors: Parisa Amouzgar, Chan Eng Seng, Babak Salamatinia

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Pharmaceutical products are being increasingly detected in the environment. However, conventional treatment systems do not provide an adequate treatment for pharmaceutical drug elimination and still there is not a regulated standard for their limitation in water. Since decades before, pharmaceuticals have been in the water but only recently, their levels in the environment have been recognized and quantified as potentially hazardous to ecosystems. In this study chitosan with a bio-based NAC (Ct-NAC) were made as beads with extrusion dripping method and investigated for acetaminophen removal from water. The effects of beading parameters such as flow rate in dripping, the distance from dipping tip to the solution surface, concentration of chitosan and percentage of NAC were analyzed to find the optimum condition. Based on the results, the overall adsorption rate and removal efficiency increased during the time till the equilibrium rate which was 80% removal of acetaminophen. The maximum adsorption belonged to the beads with 1.75% chitosan, 60% NAC, flow-rate of 1.5 ml/min while the distance of dripping was 22.5 cm.

Keywords: pharmaceuticals, water treatment, chitosan nano activated carbon beads, Acetaminophen

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Authors: Habtemariam Alemu

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It has been known that the performance of position and force control is highly affected by both robot dynamic and environment stiffness uncertainties. In this paper, joint space hybrid force and position control strategy with self-selecting matrix using artificial neural network compensator is proposed. The objective of the work is to improve controller robustness by applying a neural network technique in order to compensate the effect of uncertainties in the robot model. Simulation results for a 6 degree of freedom (6-DoF) manipulator and different types of environments showed the effectiveness of the suggested approach. 6-DoF Puma 560 family robot manipulator is chosen as industrial robot and its efficient dynamic model is designed using Matlab/SimMechanics library.

Keywords: robot manipulator, force/position control, artificial neural network, Matlab/Simulink

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Authors: J. Gochermann

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Due to complex markets and products, and increasing need to innovate, cooperation between small and medium size enterprises arose during the last decades, which are not prior driven by process optimization or sales enhancement. Especially small and medium sized enterprises (SME) collaborate increasingly in innovation and knowledge networks to enhance their knowledge and innovation potential, and to find strategic partners for product and market development. These networks are characterized by dual objectives, the superordinate goal of the total network, and the specific objectives of the network members, which can cause target conflicts. Moreover, most SMEs do not have structured innovation processes and they are not accustomed to collaborate in complex innovation projects in an open network structure. On the other hand, SMEs have suitable characteristics for promising networking. They are flexible and spontaneous, they have flat hierarchies, and the acting people are not anonymous. These characteristics indeed distinguish them from bigger concerns. Investigation of German SME networks have been done to identify success factors for SME innovation networks. The fundamental network principles, donation-return and confidence, could be confirmed and identified as basic success factors. Further factors are voluntariness, adequate number of network members, quality of communication, neutrality and competence of the network management, as well as reliability and obligingness of the network services. Innovation and knowledge networks with an appreciable number of members from science and technology institutions need also active sense-making to bring different disciplines into successful collaboration. It has also been investigated, whether and how the involvement in an innovation network impacts the innovation structure and culture inside the member companies. The degree of reaction grows with time and intensity of commitment.

Keywords: innovation and knowledge networks, SME, success factors, innovation structure and culture

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Authors: Dimitri Golenko-Ginzburg

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A CPM network project with deterministic activity durations, in which activities require homogenous resources with fixed capacities, is considered. The problem is to determine the optimal schedule of starting times for all network activities within their maximal allowable limits (in order not to exceed the network's critical time) to minimize the maximum required resources for the project at any point in time. In case when a non-critical activity may start only at discrete moments with the pregiven time span, the problem becomes NP-complete and an optimal solution may be obtained via a look-over algorithm. For the case when a look-over requires much computational time an approximate algorithm is suggested. The algorithm's performance ratio, i.e., the relative accuracy error, is determined. Experimentation has been undertaken to verify the suggested algorithm.

Keywords: resource smoothing problem, CPM network, lookover algorithm, lexicographical order, approximate algorithm, accuracy estimate

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Authors: Dae Il Kim, Jungho Moon, Tae Yun Chung

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This paper presents a car parking monitoring system using a wireless sensor network. The presented sensor network has a line-shaped topology and adopts a TDMA-based protocol for allowing multi-hop communications. Sensor nodes are deployed in the ground of an outdoor parking lot in such a way that a sensor node monitors a parking space. Each sensor node detects the availability of the associated parking space and transmits the detection result to a sink node via intermediate sensor nodes existing between the source sensor node and the sink node. We evaluate the feasibility of the presented sensor network and the TDMA-based communication protocol through experiments using 11 sensor nodes deployed in a real parking lot. The result shows that the presented car parking monitoring system is robust to changes in the communication environments and efficient for monitoring parking spaces of outdoor parking lots.

Keywords: multi-hop communication, parking monitoring system, TDMA, wireless sensor network

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Authors: M. Masar, P. Janota, J. Sedlak, M. Machovsky, I. Kuritka

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Zinc oxide (ZnO) nano crystals assembled porous architecture was prepared by thermal decomposition of zinc oxalate precursor at various temperatures ranging from 400-900°C. The effect of calcining temperature on structure and morphology was examined by scanning electron microscopy (SEM), X-ray diffractometry, thermogravimetry, and BET adsorption analysis. The porous nano crystalline ZnO morphology was developed due to the release of volatile precursor products, while the overall shape of ZnO micro crystals was retained as a legacy of the precursor. The average crystallite size increased with increasing temperature of calcination from approximately 21 nm to 79 nm, while the specific surface area decreased from 30 to 1.7 m2g-1. The photo catalytic performance of prepared ZnO powders was evaluated by degradation of methyl violet 2B, a model compound. The significantly highest photo catalytic activity was achieved with powder calcined at 500°C. This may be attributed to the sufficiently well-developed crystalline arrangement, while the specific surface area is still high enough.

Keywords: ZnO, porous structure, photodegradation, methyl violet

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Authors: Sul-Ah Ahn, Youngim Jung

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The research activities of the computational scientists using high-performance computing are analyzed using bibliometric approaches. This study aims at providing computational scientists using high-performance computing and relevant policy planners with useful bibliometric results for an assessment of research activities. In order to achieve this purpose, we carried out a co-authorship network analysis of journal articles to assess the research activities of computational scientists using high-performance computing as a case study. For this study, we used journal articles of the Scopus database from Elsevier covering the time period of 2006-2015. We extracted the author rank in the computational science field using high-performance computing by the number of papers published during ten years from 2006. Finally, we drew the co-authorship network for 50 top-authors and their coauthors and described some features of the co-authorship network in relation to the author rank. Suggestions for further studies are discussed.

Keywords: co-authorship network analysis, computational science, high performance computing, research activity

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Authors: Dalu Zhang, Xiang Jin, Dejiang Zhou, Jianpeng Wang, Haiying Jiang

Abstract:

Traditional TCP/IP network is showing lots of shortages and research for future networks is becoming a hotspot. FIA (Future Internet Architecture) and FIA-NP (Next Phase) are supported by US NSF for future Internet designing. Moreover, virtual machine migration is a significant technique in cloud computing. As a network application, it should also be supported in XIA (expressive Internet Architecture), which is in both FIA and FIA-NP projects. This paper is an experimental study aims at verifying the feasibility of VM migration over XIA. We present three ways to maintain VM connectivity and communication states concerning DAG design and routing table modification. VM migration experiments are conducted intra-AD and inter-AD with KVM instances. The procedure is achieved by a migration control protocol which is suitable for the characters of XIA. Evaluation results show that our solutions can well supports full live VM migration over XIA network respectively, keeping services seamless.

Keywords: DAG, downtime, virtual machine migration, XIA

Procedia PDF Downloads 849

Authors: Sharjeel Abid, Tanveer Hussain, Ahsan Nazir, Abdul Zahir, Nabyl Khenoussi

Abstract:

Localized application of drug has various advantages and fewer side effects as compared with other methods. Burn patients suffer from swear pain and the major aspects that are considered for burn victims include pain and infection management. Nano-fibers (NFs) loaded with drug, applied on local wound area, can solve these problems. Therefore, this study dealt with the fabrication of drug loaded NFs for better pain management. Two layers of NFs were fabricated with different drugs. Contact layer was loaded with Gabapentin (a nerve painkiller) and the second layer with acetaminophen. The fabricated dressing was characterized using scanning electron microscope, Fourier Transform Infrared Spectroscopy, X-Ray Diffraction and UV-Vis Spectroscopy. The double layered based NFs dressing was designed to have both initial burst release followed by slow release to cope with pain for two days. The fabricated nanofibers showed diameter < 300 nm. The liquid absorption capacity of the NFs was also checked to deal with the exudate. The fabricated double layered dressing with dual drug loading and release showed promising results that could be used for dealing pain in burn victims. It was observed that by the addition of drug, the size of nanofibers was reduced, on the other hand, the crystallinity %age was increased, and liquid absorption decreased. The combination of fast nerve pain killer release followed by slow release of non-steroidal anti-inflammatory drug could be a good tool to reduce pain in a more secure manner with fewer side effects.

Keywords: pain management, burn wounds, nano-fibers, controlled drug release

Procedia PDF Downloads 247