Search results for: networks and supply chain

Authors: Gerard R. Lekhema, Willie A Cronje, Ian Korir

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The objective of this research work is to investigate the use of a micro-grid system to improve the reliability and availability of emergency electrical power in a nuclear facility. The nuclear facility is a safety-critical application that requires reliable electrical power for safe startup, operation and normal or emergency shutdown conditions. The majority of the nuclear facilities around the world utilize diesel generators as emergency power supply during loss of offsite power events. This study proposes the micro-grid system with distributed energy sources and energy storage systems for use as emergency power supply. The systems analyzed include renewable energy sources, decay heat recovery system and large scale energy storage system. The configuration of the micro-grid system is realized with guidelines of nuclear safety standards and requirements. The investigation results presented include performance analysis of the micro-grid system in terms of reliability and availability.

Keywords: emergency power supply, micro-grid, nuclear facility, renewable energy sources

Procedia PDF Downloads 378

Authors: Sharanya C. H., Pragathi M., Vathsala R. S., Theja K. V., Yashaswini S.

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Identifying counterfeit products have become increasingly important in the product manufacturing industries in recent decades. This current ongoing product issue of counterfeiting has an impact on company sales and profits. To address the aforementioned issue, a functional blockchain technology was implemented, which effectively prevents the product from being counterfeited. By utilizing the blockchain technology, consumers are no longer required to rely on third parties to determine the authenticity of the product being purchased. Blockchain is a distributed database that stores data records known as blocks and several databases known as chains across various networks. Counterfeit products are identified using a QR code reader, and the product's QR code is linked to the blockchain management system. It compares the unique code obtained from the customer to the stored unique code to determine whether or not the product is original.

Keywords: blockchain, ethereum, QR code

Procedia PDF Downloads 155

Authors: Cesar Hernández, Diego Giral, Ingrid Páez

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This article proposes a hybrid algorithm for spectrum allocation in cognitive radio networks based on the algorithms Analytical Hierarchical Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to improve the performance of the spectrum mobility of secondary users in cognitive radio networks. To calculate the level of performance of the proposed algorithm a comparative analysis between the proposed AHP-TOPSIS, Grey Relational Analysis (GRA) and Multiplicative Exponent Weighting (MEW) algorithm is performed. Four evaluation metrics is used. These metrics are the accumulative average of failed handoffs, the accumulative average of handoffs performed, the accumulative average of transmission bandwidth, and the accumulative average of the transmission delay. The results of the comparison show that AHP-TOPSIS Algorithm provides 2.4 times better performance compared to a GRA Algorithm and, 1.5 times better than the MEW Algorithm.

Keywords: cognitive radio, decision making, hybrid algorithm, spectrum handoff, wireless networks

Procedia PDF Downloads 520

Authors: Priti Kumari, Tricha Anjali

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Body Area Networks (BANs) have emerged as the most promising technology for pervasive health care applications. Since they facilitate communication of very sensitive health data, information leakage in such networks can put human life at risk, and hence security inside BANs is a critical issue. Safe distribution and periodic refreshment of cryptographic keys are needed to ensure the highest level of security. In this paper, we focus on the key distribution techniques and how they are categorized for BAN. The state-of-art pre-shared key distribution algorithms are surveyed. Possible attacks on algorithms are demonstrated with examples.

Keywords: attacks, body area network, key distribution, key refreshment, pre-shared keys

Procedia PDF Downloads 343

Authors: J. A. Ageeva, Z. S. Zavyalova

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The article considers social media as a tool for business promotion. We analyze and compare the SMM experience in the western countries and Russia. A short review of Russian social networks are given including their peculiar features, and the main problems and perspectives of Russian SMM are described.

Keywords: social media, social networks, marketing, SMM

Procedia PDF Downloads 532

Authors: Changiz Valmohammadi

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The main purpose of this study is to explore the perception of Iranian experts and executive managers of sample organizations on the benefits and barriers of Internet of Things (IoT) solutions implementation. Based on the review of the related literature and web sites, benefits and barriers of successful implementation to IoT solutions were identified. Through a self-administered questionnaire which was collected from 67 Iranian organizations the ranking and importance of benefits and barriers of IoT solutions implementation were determined based on the perception of the experts of the surveyed organizations. Analysis of data and the obtained results revealed that “improved customer experience” and “Supply chain optimization and responsiveness” are the most important benefits that the survey organizations expect to reap as a result of IoT solutions implementation. Also,” Integration challenges" and “cannot find right suppliers” were ranked as the most challenging barriers to IoT solutions implementation.

Keywords: internet of things (IoT), exploratory study, benefits, barriers, Iran

Procedia PDF Downloads 501

Authors: Ahmad M. Awwad, Jehad Al-Sadi

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The star network is one of the promising interconnection networks for future high speed parallel computers, it is expected to be one of the future-generation networks. The star network is both edge and vertex symmetry, it was shown to have many gorgeous topological proprieties also it is owns hierarchical structure framework. Although much of the research work has been done on this promising network in literature, it still suffers from having enough algorithms for load balancing problem. In this paper we try to work on this issue by investigating and proposing an efficient algorithm for load balancing problem for the star network. The proposed algorithm is called Star Clustered Dimension Exchange Method SCDEM to be implemented on the star network. The proposed algorithm is based on the Clustered Dimension Exchange Method (CDEM). The SCDEM algorithm is shown to be efficient in redistributing the load balancing as evenly as possible among all nodes of different factor networks.

Keywords: load balancing, star network, interconnection networks, algorithm

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Authors: L. Parisi

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In this research work, neural networks were applied to classify two types of hip joint implants based on the relative hip joint implant side speed and three components of each ground reaction force. The condition of walking gait at normal velocity was used and carried out with each of the two hip joint implants assessed. Ground reaction forces’ kinetic temporal changes were considered in the first approach followed but discarded in the second one. Ground reaction force components were obtained from eighteen patients under such gait condition, half of which had a hip implant type I-II, whilst the other half had the hip implant, defined as type III by Orthoload®. After pre-processing raw gait kinetic data and selecting the time frames needed for the analysis, the ground reaction force components were used to train a MLP neural network, which learnt to distinguish the two hip joint implants in the abovementioned condition. Further to training, unknown hip implant side and ground reaction force components were presented to the neural networks, which assigned those features into the right class with a reasonably high accuracy for the hip implant type I-II and the type III. The results suggest that neural networks could be successfully applied in the performance assessment of hip joint implants.

Keywords: kinemic gait data, neural networks, hip joint implant, hip arthroplasty, rehabilitation engineering

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Authors: Skiker Kaoutar, Mounir Maouene

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Neuroimaging studies have shown that animal and tool concepts rely on distinct networks of brain areas. Animal concepts depend predominantly on temporal areas while tool concepts rely on fronto-temporo-parietal areas. However, the origin of this neurofunctional distinction for processing animal and tool concepts remains still unclear. Here, we address this question from a network perspective suggesting that the neural distinction between animals and tools might reflect the differences in their structural semantic networks. We build semantic networks for animal and tool concepts derived from Mc Rae and colleagues’s behavioral study conducted on a large number of participants. These two networks are thus analyzed through a large number of graph theoretical measures for small-worldness: centrality, clustering coefficient, average shortest path length, as well as resistance to random and targeted attacks. The results indicate that both animal and tool networks have small-world properties. More importantly, the animal network is more vulnerable to targeted attacks compared to the tool network a result that correlates with brain lesions studies.

Keywords: animals, tools, network, semantics, small-world, resilience to damage

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Authors: Chanyuan Gu, Shouming Zhong

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Synchronization is a fundamental phenomenon that enables coherent behavior in networks as a result of interactions. The purpose of this research had been to investigate the problem of anti-phase synchronization for complex delayed dynamical networks with output coupling. The coupling configuration is general, with the coupling matrix not assumed to be symmetric or irreducible. The amount of the coupling variables between two connected nodes is flexible, the nodes in the drive and response systems need not to be identical and there is not any extra constraint on the coupling matrix. Some pinning controllers are designed to make the drive-response system achieve the anti-phase synchronization. For the convenience of description, we applied the matrix Kronecker product. Some new criteria are proposed based on the Lyapunov stability theory, linear matrix inequalities (LMI) and Schur complement. Lastly, some simulation examples are provided to illustrate the effectiveness of our proposed conditions.

Keywords: anti-phase synchronization, complex networks, output coupling, pinning control

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Authors: Abhishek Kumar Gupta

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Atomistic Molecular Dynamics (MD) Simulations have been performed to study the effect of monovalent salt i.e. NaCl concentration (Cs) and chain degree of neutralization (f) on the structure and dynamics of anionic poly(methacrylic acid) (PMA) in dilute aqueous solutions. In the present study, the attention is to unveil the conformational structure, hydrogen-bonding, local polyion-counterion structure, h-bond dynamics, chain dynamics and thermodynamic enthalpy of solvation of a-PMA in dilute aqueous solutions as a function of salt concentration, Cs and f. The results have revealed that at low salt concentration, the conformational radius of gyration (Rg) increases and then decreases reaching a maximum in agreement with the reported light scattering experimental results. The Rg at f = 1 shows a continual decrease and acquire a plateau value at higher salt concentration in agreement with results obtained by light scattering experiments. The radial distribution functions between PMA, salt and water atoms has been computed with respect to atom and centre-of-mass to understand the intermolecular structure in detail. The results pertaining to PMA chain conformations and hydrogen bond autocorrelation function showcasing the h-bond dynamics will be presented. The results pertaining to chain dynamics will be presented. The results pertaining to counterion condensation on the PMA chain shows greater condensation of Na+ ions on to the carboxylate ions with increase in salt concentration. Moreover, the solvation enthalpy of the system as a function of salt concentration will be presented.

Keywords: conformations, molecular dynamics simulations, NaCl concentration, radial distribution functions

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Authors: Shiva Kumar, G. S. Vijay, Srinivas Pai P., Shrinivasa Rao B. R.

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In the present study RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tech and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.

Keywords: radial basis function networks, emissions, performance parameters, fuzzy c means

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Authors: Keith Dominic T. Li

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The soaring prices of residential properties in Hong Kong has become a social problem that even the middle class is having dif?iculties in purchasing homes. In making policies to curb the prices, it is important to determine the factors that contribute to the property in?lation. Many researches attribute this in?lation to macroeconomic factors especially the interest rate. However, it is important to remember that Hong Kong is under a Currency Board system which makes its interest rate exogenously determined. This research aims to show the signi?icance of the money supply on Hong Kong residential property prices in post-1997 Asian Financial Crisis period. Using money supply data, macroeconomic fundamentals, and demographic variables from 2000Q1 to 2013Q2, the factors contributed to residential property price in?lation are estimated to calculate the share of each explanatory variable in disparity. It is found that the Hong Kong property market is mainly driven by investment and that the in?lation on Hong Kong residential property prices can explained by the increase in the Hang Seng Index and in the money supply M2.

Keywords: real estate, Hong Kong, property market, monetary economics, monetary policy

Procedia PDF Downloads 518

Authors: Qiming Wang

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Dynamic polymer networks (DPNs) crosslinked by dynamic bonds have received intensive attention because of their special crack-healing capability. Diverse DPNs have been synthesized using a number of dynamic bonds, including dynamic covalent bond, hydrogen bond, ionic bond, metal-ligand coordination, hydrophobic interaction, and others. Despite the promising success in the polymer synthesis, the fundamental understanding of their self-healing mechanics is still at the very beginning. Especially, a general analytical model to understand the interfacial self-healing behaviors of DPNs has not been established. Here, we develop polymer-network based analytical theories that can mechanistically model the constitutive behaviors and interfacial self-healing behaviors of DPNs. We consider that the DPN is composed of interpenetrating networks crosslinked by dynamic bonds. bonds obey a force-dependent chemical kinetics. During the self-healing process, we consider the The network chains follow inhomogeneous chain-length distributions and the dynamic polymer chains diffuse across the interface to reform the dynamic bonds, being modeled by a diffusion-reaction theory. The theories can predict the stress-stretch behaviors of original and self-healed DPNs, as well as the healing strength in a function of healing time. We show that the theoretically predicted healing behaviors can consistently match the documented experimental results of DPNs with various dynamic bonds, including dynamic covalent bonds (diarylbibenzofuranone and olefin metathesis), hydrogen bonds, and ionic bonds. We expect our model to be a powerful tool for the self-healing community to invent, design, understand, and optimize self-healing DPNs with various dynamic bonds.

Keywords: self-healing polymers, dynamic covalent bonds, hydrogen bonds, ionic bonds

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Authors: Salah Gariani, Islam Shyha, Fawad Inam, Dehong Huo

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A controlled cutting fluid impinging supply system (CUT-LIST) was developed to deliver an accurate amount of cutting fluid into the machining zone via well-positioned coherent nozzles based on a calculation of the heat generated. The performance of the CUT-LIST was evaluated against a conventional flood cutting fluid supply system during step shoulder milling of Ti-6Al-4V using vegetable oil-based cutting fluid. In this paper, the micro-hardness of the machined surface was used as the main criterion to compare the two systems. CUT-LIST provided significant reductions in cutting fluid consumption (up to 42%). Both systems caused increased micro-hardness value at 100 µm from the machined surface, whereas a slight reduction in micro-hardness of 4.5% was measured when using CUL-LIST. It was noted that the first 50 µm is the soft sub-surface promoted by thermal softening, whereas down to 100 µm is the hard sub-surface caused by the cyclic internal work hardening and then gradually decreased until it reached the base material nominal hardness. It can be concluded that the CUT-LIST has always given lower micro-hardness values near the machined surfaces in all conditions investigated.

Keywords: impinging supply system, micro-hardness, shoulder milling, Ti-6Al-4V, vegetable oil-based cutting fluid

Procedia PDF Downloads 267

Authors: Sungkyung Kim, Jee-Hyeon Na, Dong-Seung Kwon

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Future mobile networks following 5th generation will be characterized by one thousand times higher gains in capacity; connections for at least one hundred billion devices; user experience capable of extremely low latency and response times. To be close to the capacity requirements and higher reliability, advanced technologies have been studied, such as multiple connectivity, small cell enhancement, heterogeneous networking, and advanced interference and mobility management. This paper is focused on the multiple connectivity in heterogeneous cellular networks. We investigate the performance of coverage and user throughput in several deployment scenarios. Using the stochastic geometry approach, the SINR distributions and the coverage probabilities are derived in case of dual connection. Also, to compare the user throughput enhancement among the deployment scenarios, we calculate the spectral efficiency and discuss our results.

Keywords: heterogeneous networks, multiple connectivity, small cell enhancement, stochastic geometry

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Authors: Joo-Hyung Oh

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The number of service users of 4G VoLTE (voice over LTE) using LTE data networks is rapidly growing. VoLTE based on all-IP network enables clearer and higher-quality voice calls than 3G. It does, however, pose new challenges; a voice call through IP networks makes it vulnerable to security threats such as wiretapping and forged or falsified information. And in particular, stealing other users’ phone numbers and forging or falsifying call request messages from outgoing voice calls within VoLTE result in considerable losses that include user billing and voice phishing to acquaintances. This paper focuses on the threats of caller phone number spoofing in the VoLTE and countermeasure technology as safety measures for mobile communication networks.

Keywords: LTE, 4G, VoLTE, phone number spoofing

Procedia PDF Downloads 414

Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

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In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

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Authors: Karolin Bauer, Anna Brinkmann

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Vulnerabilities in critical infrastructure can cause significant difficulties for the affected population during crises. Securing the food supply as part of the critical infrastructure in crisis situations is an essential part of public services and a ground stone for a successful concept of civil protection. In most industrialized countries, there are currently no comparative studies regarding the food supply of the population during crisis and disaster events. In order to mitigate the potential impact in case of major disasters in Germany, it is absolutely necessary to investigate how the food supply can be secured. The research project aims to provide in-depth research on the experiences gathered during past large-scale disasters in the 34 OECD member countries in order to discover alternatives for an updated civil protection system in Germany. The basic research question is: "Which international approaches and structures of civil protection have been proven and would be useful to modernize the German civil protection with regards to the critical infrastructure and food supply?" Research findings should be extracted from an extensive literature review covering the entire research period as well as from personal and online-based interviews with experts and responsible persons from involved institutions. The capability of the research project insists on the deliberate choice to investigate previous large-scale disasters to formulate important and practical approaches to modernize civil protection in Germany.

Keywords: food supply, vulnerabilty, critical infratstructure, large-scale disaster

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Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos

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This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.

Keywords: metaphor detection, deep learning, representation learning, embeddings

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Authors: Bojan Najdenov, Danco Davcev

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Reduction of traffic congestions and the effects of pollution and waste of resources that come with them has been a big challenge in the past decades. Having reliable systems to facilitate the process of modeling and prediction of traffic conditions would not only reduce the environmental pollution, but will also save people time and money. Social networks play big role of people’s lives nowadays providing them means of communicating and sharing thoughts and ideas, that way generating huge knowledge bases by crowdsourcing. In addition to that, crowdsourcing as a concept provides mechanisms for fast and relatively reliable data generation and also many services are being used on regular basis because they are mainly powered by the public as main content providers. In this paper we present the Social-NETS-Traffic-Control System (SNTCS) that should serve as a facilitator in the process of modeling and prediction of traffic congestions. The main contribution of our system is to integrate data from social networks as Twitter and also implements a custom created crowdsourcing subsystem with which users report traffic conditions using an android application. Our first experience of the usage of the system confirms that the integrated approach allows easy extension of the system with other social networks and represents a very useful tool for traffic control.

Keywords: traffic, congestion reduction, crowdsource, social networks, twitter, android

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Authors: A. Melka, N. Slater, A. Mualem, Y. Louzoun

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Networks are often presented as containing a “core” and a “periphery.” The existence of a core suggests that some vertices are central and form the skeleton of the network, to which all other vertices are connected. An alternative view of graphs is through communities. Multiple measures have been proposed for dense communities in graphs, the most classical being k-cliques, k-cores, and k-plexes, all presenting groups of tightly connected vertices. We here show that the edge number thresholds for such communities to emerge and for their percolation into a single dense connectivity component are very close, in all networks studied. These percolating cliques produce a natural core and periphery structure. This result is generic and is tested in configuration models and in real-world networks. This is also true for k-cores and k-plexes. Thus, the emergence of this connectedness among communities leading to a core is not dependent on some specific mechanism but a direct result of the natural percolation of dense communities.

Keywords: cliques, core structure, percolation, phase transition

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Authors: E. Chakwizira, D. J. Moot, M. Andrews, E. Teixeira

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Partitioning of macro-nutrients in wheat (Triticum aestivum L.) plant organs have not been extensively studied, particularly for modern genotypes grown under contrasting N supply. Nutrient accumulation and partitioning of phosphorus, potassium, calcium, magnesium and sulphur (P, K, Ca, Mg and S) were determined for six wheat genotypes [12S2-2021, 12S3-3019, 13S3-2026, Discovery, Duchess and Reliance] grown with (200 kg/ha) or without (0 kg/ha) nitrogen (N), in a fully irrigated field experiment in 2017-18 season at Lincoln, New Zealand. Data were collected at three growth stages (GS): tillering (GS21), anthesis (GS60) and grain maturity (GS92). Grain yield varied with both N and genotype; from 6-7.5 t/ha for the 0 kg N/ha crops and 8.1-9.3 t/ha for the 200 kg N/ha treatments. Plant nutrient uptake at maturity responded to both N supply and genotype for all nutrients, except S which did not differ among the genotypes. For example, total P uptake averaged 13.5 (12.4-14.3) kg/ha for the 0 kg N/ha treatments and 17.8 (15.1-19.7) kg/ha when 200 kg N/ha was applied. Similarly, K uptake increased from an average of 23 (21.6-25.3) for the 0 kg N/ha treatments to 34.3 (32.4-40.8) kg/ha when 200 kg N/ha was applied. Similar trends were observed for Ca and Mg. The S content only responded to N supply but not to genotype, increasing from 7.9 kg/ha for the 0 kg N treatments to 12.8 kg/ha when 200 kg N was applied. Relative nutrient content at anthesis compared with those at maturity were 30% for P, 100% for both K and Ca and 34% of Mg. Sulphur content at anthesis decreased 29% with N supply and was highest for genotypes 12S2-2021 compared with the other five genotype. At grain maturity, the ratio of nutrients in grain to total plant nutrient, defined as the nutrient harvest index (NHI) varied with both N supply and genotype. Averaged across treatments, the NHI was 0.96 for P, 0.53 for K, 0.58 for Ca, 0.90 for Mg and 0.85 for S. These results suggest that Ca and K should be provided earlier in the season as there is limited or no uptake after anthesis. These results also show that Ca and K are important for structural functions, while P, Mg and S are remobilised to the grains and become important for quality.

Keywords: anthesis, genotype, nutrient harvests index, NHI, Triticum aestivum L.

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Authors: Mahdi Jalili

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Functional connectivity in the human brain can be represented as a network using electroencephalography (EEG) signals. Network representation of EEG time series can be an efficient vehicle to understand the underlying mechanisms of brain function. Brain functional networks – whose nodes are brain regions and edges correspond to functional links between them – are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which graph theory metrics are sex dependent. To this end, EEGs from 24 healthy female subjects and 21 healthy male subjects were recorded in eyes-closed resting state conditions. The connectivity matrices were extracted using correlation analysis and were further binarized to obtain binary functional networks. Global and local efficiency measures – as graph theory metrics– were computed for the extracted networks. We found that male brains have a significantly greater global efficiency (i.e., global communicability of the network) across all frequency bands for a wide range of cost values in both hemispheres. Furthermore, for a range of cost values, female brains showed significantly greater right-hemispheric local efficiency (i.e., local connectivity) than male brains.

Keywords: EEG, brain, functional networks, network science, graph theory

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Authors: R. Byler

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Innovation, particularly in technology development, is a crucial aspect of nanotechnology R&D and, although several approaches to effective innovation management exist, organizational structures that promote knowledge exchange have been found to be most effect in supporting new and emerging technologies. This paper discusses Integrated Knowledge Networks (IKNs) and evaluates its use within nanotechnology R&D to increase technology innovation. Specifically, this paper reviews the role of IKNs in bolstering national and international nanotechnology development and in enhancing nanotechnology innovation. Both physical and virtual IKNs, particularly IT-based network platforms for community-based innovation, offer strategies for enhanced technology innovation, interdisciplinary cooperation, and enterprise development. Effectively creating and managing technology R&D networks can facilitate successful knowledge exchange, enhanced innovation, commercialization, and technology transfer. As such, IKNs are crucial to technology development processes and, thus, in increasing the quality and access to new, innovative nanoscience and technologies worldwide.

Keywords: community-based innovation, integrated knowledge networks, nanotechnology, technology innovation

Procedia PDF Downloads 389

Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

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In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: consensus, curse of correlation, imbalance classification, rank-based chain-mode ensemble

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Authors: Nazmul Shahadat, Anthony S. Maida

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In recent years, hypercomplex inspired neural networks improved deep CNN architectures due to their ability to share weights across input channels and thus improve cohesiveness of representations within the layers. The work described herein studies the effect of replacing existing layers in an Axial Attention ResNet with their quaternion variants that use cross-channel weight sharing to assess the effect on image classification. We expect the quaternion enhancements to produce improved feature maps with more interlinked representations. We experiment with the stem of the network, the bottleneck layer, and the fully connected backend by replacing them with quaternion versions. These modifications lead to novel architectures which yield improved accuracy performance on the ImageNet300k classification dataset. Our baseline networks for comparison were the original real-valued ResNet, the original quaternion-valued ResNet, and the Axial Attention ResNet. Since improvement was observed regardless of which part of the network was modified, there is a promise that this technique may be generally useful in improving classification accuracy for a large class of networks.

Keywords: axial attention, representational networks, weight sharing, cross-channel correlations, quaternion-enhanced axial attention, deep networks

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Authors: Ezekiel Olukayode Akintunde

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There is a high level of inadequate methods at all levels of food supply in the global food industry. The inadequacies have led to vast wastages of food. Hence there is a need to curb the wastages that can later affect natural resources, water resources, and energy to avoid negative impacts on the climate and the environment. There is a need to engage multifaceted engineering packaging approaches for a sustainable food chain to ensure active packaging, intelligent packaging, new packaging materials, and a sustainable packaging system. Packaging can be regarded as an indispensable component approach that can be applied to solve major problems of sustainable food consumption globally; this is about controlling the environmental impact of packed food. The creative innovation will ensure that packaged foods are free from food-borne diseases and food chemical pollution. This paper evaluates the key shortcomings that must be addressed by innovative food packaging to ensure a safe, natural environment that will preserve energy and sustain water resources. Certain solutions, including fabricating microbial biodegradable chemical compounds/polymers from agro-food waste remnants, appear a bright path to ensure a strong and innovative waste-based food packaging system. Over the years, depletion in the petroleum reserves has brought about the emergence of biodegradable polymers as a proper replacement for traditional plastics; moreover, the increase in the production of traditional plastics has raised serious concerns about environmental threats. Biodegradable polymers have proven to be biocompatible, which can also be processed for other useful applications. Therefore, this study will showcase a workable guiding framework for designing a sustainable food packaging system that will not constitute a danger to our present society and that will surely preserve natural water resources. Various assessment methods will be deployed at different stages of the packaging design to enhance the package's sustainability. Every decision that will be made must be facilitated with methods that will be engaged per stage to allow for corrective measures throughout the cycle of the design process. Basic performance appraisal of packaging innovations. Food wastage can result in inimical environmental impacts, and ethical practices must be carried out for food loss at home. An examination in West Africa quantified preventable food wastage over the entire food value chain at almost 180kg per person per year. That is preventable food wastage, 35% of which originated at the household level. Many food losses reported, which happened at the harvesting, storage, transportation, and processing stages, are not preventable and are without much environmental impact because such wastage can be used for feeding. Other surveys have shown that 15%-20% of household food losses can be traced to food packaging. Therefore, new innovative packaging systems can lessen the environmental effect of food wastage to extend shelf‐life to lower food loss in the process distribution chain and at the household level.

Keywords: food packaging, biodegradable polymer, intelligent packaging, shelf-life

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Authors: Raya Hamed Hial Al Maamari

Abstract:

The gulf societies have been undergoing radical changes because of the technology transfer. It altered the humanities attitudes. Especially, youth habits so they become a fond of using social networking. This study aimed to find out the ratio of social networking in Directing youth to participate with government institutions in decision-making and improving their societies. The study considered a descriptive study, social survey method was used on a sample of 100 young men from different gulf countries, using an electronic questionnaire, with some interviews with famous leaders of youth groups. Finally, the researchers suggested many effective views to activate youth efforts using social networks as an effective manner to plan for the development policy and Implemented accurately in the community. The findings illustrated that social networks play a vital role in encouraging youth to participate Enthusiastically in providing the service. As it notices these networks contain large numbers of youth. Therefore, the influences become widely and feasible. Moreover, the study indicated the fact that most of youth teamwork started in these social networks. Then, it has been growing to the real society.

Keywords: social work, volunteering, youth, community

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Authors: Min Kyung An, Hyuk Cho

Abstract:

In this paper, we study the Minimum Latency Broadcast Scheduling (MLBS) problem in wireless sensor networks (WSNs). The main issue of the MLBS problem is to compute schedules with the minimum number of timeslots such that a base station can broadcast data to all other sensor nodes with no collisions. Unlike existing works that utilize the traditional omni-directional WSNs, we target the directional WSNs where nodes can collaboratively determine and orientate their antenna directions. We first develop a 7-approximation algorithm, adopting directional WSNs. Our ratio is currently the best, to the best of our knowledge. We then validate the performance of the proposed algorithm through simulation.

Keywords: broadcast, collision-free, directional antenna, approximation, wireless sensor networks

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