Search results for: generative adversarial networks

Authors: Muhammad Fanseem E. M., Rama Satya Satish Kumar, Indrajeet Bhausaheb Bhavar, Deepak M.

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Keeping the right balance of electricity between the supply and demand sides of the grid is one of the most important objectives of electrical grid operation. Power generation and demand forecasting are the core of power management and generation scheduling. Large, centralized producing units were used in the construction of conventional power systems in the past. A certain level of balance was possible since the generation kept up with the power demand. However, integrating renewable energy sources into power networks has proven to be a difficult challenge due to its intermittent nature. The power imbalance caused by rising demands and peak loads is negatively affecting power quality and dependability. Demand side management and demand response were one of the solutions, keeping generation the same but altering or rescheduling or shedding completely the load or demand. However, shedding the load or rescheduling is not an efficient way. There comes the significance of virtual power plants. The virtual power plant integrates distributed generation, dispatchable load, and distributed energy storage organically by using complementing control approaches and communication technologies. This would eventually increase the utilization rate and financial advantages of distributed energy resources. Most of the writing on virtual power plant models ignored technical limitations, and modeling was done in favor of a financial or commercial viewpoint. Therefore, this paper aims to address the modeling intricacies of VPPs and their technical limitations, shedding light on a holistic understanding of this innovative power management approach.

Keywords: cost optimization, distributed energy resources, dynamic modeling, model quality tests, power system modeling

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Authors: Unity Chipfupa, Aluwani Tagwi, Edilegnaw Wale

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Climate change adaptation studies are challenged by a limited understanding of how non-cognitive factors such as psychological capital affect adaptation decisions of smallholder farmers. The concept of psychological capital has not been fully applied in the empirical literature on climate change adaptation strategies. Hence, the study was meant to assess how psychological capital endowment affects climate change adaptation among smallholder farmers. A multivariate probit regression model was estimated using data collected from 328 smallholder farmers in KwaZulu-Natal, South Africa. The findings indicate that, among other factors, self-confidence and hope or aspirations in farming influence climate change adaptation decisions of smallholders. The psychological capital theory proved to be comprehensive in identifying specific psychological dimensions associated with adaptation decisions. However, the non-alignment of approaches for measuring non-cognitive factors made it difficult to compare results among different studies. In conclusion, the study recommends the need for practical ways for enhancing smallholders’ endowment with key non-cognitive abilities. Researchers should develop and agree on a comprehensive framework for assessing non-cognitive factors critical for climate change adaptation. This will improve the use of positive psychology theories to advance the literature on climate change adaptation. Other key recommendations include targeted support for communities facing higher risks of climate change, improving smallholders’ ability to adapt, promotion of social networks and the inclusion of farming objectives as an important indicator in climate change adaptation research.

Keywords: adaptive capacity, climate change adaptation, psychological capital, multivariate probit, non-cognitive factors.

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Authors: Tatsiana Haiden

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The role of the translator in the publishing process has been underestimated for centuries. Any translation is produced in a certain socio-political context by agents with different background, interests, and opinions, i.e., no translation is neutral. Any translation goes beyond the text; it is not only an interlingual transfer of signs but a social phenomenon. The case study shows how Jewish social networks influence publishing translations and aims to explain the unexpected success of the Jewish publishing house in pre-Anschluss Austria. The research shows that translators play a central role (‘Translator’s visibility’ - Pym, ‘Activist turn’ - Wolf, ‘Translator studies’ - Chesterman) in choosing what has to be translated and establishing communication between the author and the publisher. The concept of Translationskultur of Prunc is being historized and applied to the publishing house for the first time by analyzing business correspondence between the main actors of translation (publisher-translator-author). The translation studies project has become interdisciplinary –it encompasses sociology (concepts of Bourdieu’s ‘Field theory’ are used) and history. The historical research method Histoire croiseé is being used to avoid subjectivity and to introduce a new ‘translator-oriented’ vision in translation studies instead of the author-oriented one. In the course of the archival research, it was established that Jewish background plays an essential role in the destiny of the translators and the publishing house, so the Jewish studies have been added to the project. The study goes beyond the Austrian translational culture; it can be used as an example of dealing with publishing houses policies, publishing translations, and translator studies.

Keywords: history of translation, Jewish studies, publishing translations, translation sociology, translator studies, translators as actors

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Authors: Nick Weir, Robert Stevens, Alan Hargreaves, Martin McGinnity, Chris Tinsley

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Hydrophobic materials have previously demonstrated the ability to elevate cell-cell interactions and promote the formation of neural networks whilst aligned nanofibers demonstrate the ability to induce extensive neurite outgrowth in an aligned manner. Hydrophobic materials typically elicit an immune response upon implantation and thus materials used for implantation are typically hydrophilic. Poly-L-lactic acid (PLLA) is a hydrophobic, non-immunogenic, FDA approved material that can be electrospun to form aligned nanofibers. Primary rat cortical neurons cultured for 10 days on aligned PLLA nanofibers formed 3D cell clusters, approximately 800 microns in diameter. Neurites that extended from these clusters were highly aligned due to the alignment of the nanofibers they were cultured upon and fasciculation was also evident. Plasma treatment of the PLLA nanofibers prior to seeding of cells significantly reduced the hydrophobicity and abolished the cluster formation and neurite fasciculation, whilst reducing the extent and directionality of neurite outgrowth; it is proposed that hydrophobicity induces the changes to cellular behaviors. Aligned PLLA nanofibers induced the formation of a structure that mimics the grey-white matter compartmentalization that is observed in vivo and thus represents a step forward in generating organoids or biomaterial-based implants. Upon implantation into the brain, the biomaterial architectures described here may provide a useful platform for both brain repair and brain remodeling initiatives.

Keywords: hydrophobicity, nanofibers, neurite fasciculation, neurite outgrowth, PLLA

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Authors: Vivian Isaac, A. T. Joteeshwaran, Craig McLachlan

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The University of New South Wales (UNSW) Rural Clinical School has a strategic collaborative focus on chronic disease and public health. Our objectives are to understand rural environmental and biological interactions in vulnerable community populations. The UNSW Rural Clinical School translational model is a spoke and hub network. This spoke and hub model connects rural data and biological specimens with city based collaborative public health research networks. Similar spoke and hub models are prevalent across research centers in India. The Australia-India Council grant was awarded so we could establish sustainable public health and community research collaborations. As part of the collaborative network we are developing strategies around data and biological sharing platforms between Indian Institute of Public Health, Public Health Foundation of India (PHFI), Hyderabad and Rural Clinical School UNSW. The key objective is to understand how research collaborations are conducted in India and also how data can shared and tracked with external collaborators such as ourselves. A framework to improve data sharing for research collaborations, including DNA was proposed as a project outcome. The complexities of sharing biological data has been investigated via a visit to India. A flagship sustainable project between Rural Clinical School UNSW and PHFI would illustrate a model of data sharing platforms.

Keywords: data sharing, collaboration, public health research, chronic disease

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Authors: S. Jalilzadeh, S. M. Mohseni Bonab

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Solar and battery energy storage systems are very useful for consumers who live in deprived areas and do not have access to electricity distribution networks. Nowadays one of the problems that photo voltaic systems (PV) have changing of output power in temperature and irradiance variations, which directly affects the load that is connected to photo voltaic systems. In this paper, with considering the fact that the solar array varies with change in temperature and solar power radiation, a voltage stabilizer system of a load connected to photo voltaic array is designed to stabilize the load voltage and to transfer surplus power of the battery. Also, in proposed hybrid system, the needed load power amount is supplemented considering the voltage stabilization in standalone operation for supplying unbalanced AC load. Electrical energy storage system for voltage control and improvement of the performance of PV by a DC/DC converter is connected to the DC bus. The load is also feed by an AC/DC converter. In this paper, when the voltage increases in its reference limit, the battery gets charged by the photo voltaic array and when it decreases in its defined limit, the power gets injected to the DC bus by this battery. The constant of DC bus Voltage is the cause for the reduced harmonics generated by the inverter. In addition, a series of filters are provided in the inverter output in to reduced harmonics. The inverter control circuit is designed that the voltage and frequency of the load remain almost constant at different load conditions. This paper has focused on controlling strategies of converters to improve their performance.

Keywords: photovoltaic array (PV), DC/DC Boost converter, battery converter, inverters control

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Authors: George Mahalu

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The Chua diode has been configured over time in various ways, using electronic structures like operational amplifiers (AOs) or devices with gas or semiconductors. When discussing the use of semiconductor devices, tunnel diodes (Esaki diodes) are most often considered, and more recently, transistorized configurations such as lambda diodes. The paperwork proposed here uses in the modeling a lambda diode type configuration consisting of two junction field effect transistors (JFET). The original scheme is created in the MULTISIM electronic simulation environment and is analyzed in order to identify the conditions for the appearance of evolutionary unpredictability specific to nonlinear dynamic systems with chaos-induced behavior. The chaotic deterministic oscillator is one autonomous type, a fact that places it in the class of Chua’s type oscillators, the only significant and most important difference being the presence of a nonlinear device like the one mentioned structure above. The chaotic behavior is identified both by means of strange attractor-type trajectories and visible during the simulation and by highlighting the hypersensitivity of the system to small variations of one of the input parameters. The results obtained through simulation and the conclusions drawn are useful in the further research of ways to implement such constructive electronic solutions in theoretical and practical applications related to modern small signal amplification structures, to systems for encoding and decoding messages through various modern ways of communication, as well as new structures that can be imagined both in modern neural networks and in those for the physical implementation of some requirements imposed by current research with the aim of obtaining practically usable solutions in quantum computing and quantum computers.

Keywords: chua, diode, memristor, chaos

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Authors: Saad M. Darwish, Adel A. El-Zoghabi, Moustafa F. Ashry

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The popularity of the Internet and the availability of powerful computers and high-speed networks as low-cost commodity components are changing the way we use computers today. These technical opportunities have led to the possibility of using geographically distributed and multi-owner resources to solve large-scale problems in science, engineering, and commerce. Recent research on these topics has led to the emergence of a new paradigm known as Grid computing. To achieve the promising potentials of tremendous distributed resources, effective and efficient load balancing algorithms are fundamentally important. Unfortunately, load balancing algorithms in traditional parallel and distributed systems, which usually run on homogeneous and dedicated resources, cannot work well in the new circumstances. In this paper, the concept of a fast fractal transform in heterogeneous grid computing based on R-tree and the domain-range entropy is proposed to improve fault tolerance and load balancing algorithm by improve connectivity, communication delay, network bandwidth, resource availability, and resource unpredictability. A novel two-dimension figure of merit is suggested to describe the network effects on load balance and fault tolerance estimation. Fault tolerance is enhanced by adaptively decrease replication time and message cost while load balance is enhanced by adaptively decrease mean job response time. Experimental results show that the proposed method yields superior performance over other methods.

Keywords: Grid computing, load balancing, fault tolerance, R-tree, heterogeneous systems

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Authors: Sophia Shi

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Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

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Authors: A. Hadadi, M. Abdollahi, A. Dustmohammadi

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The growing use of DGs in distribution networks provide many advantages and also cause new problems which should be anticipated and be solved with appropriate solutions. One of the problems is transient voltage drop and short circuit in the electrical network, in the presence of distributed generation - which can lead to instability. The appearance of the short circuit will cause loss of generator synchronism, even though if it would be able to recover synchronizing mode after removing faulty generator, it will be stable. In order to increase system reliability and generator lifetime, some strategies should be planned to apply even in some situations which a fault prevent generators from separation. In this paper, one fault current limiter is installed due to prevent DGs separation from the grid when fault occurs. Furthermore, an innovative objective function is applied to determine the impedance optimal amount of fault current limiter in order to improve transient stability of distributed generation. Fault current limiter can prevent generator rotor's sudden acceleration after fault occurrence and thereby improve the network transient stability by reducing the current flow in a fast and effective manner. In fact, by applying created impedance by fault current limiter when a short circuit happens on the path of current injection DG to the fault location, the critical fault clearing time improve remarkably. Therefore, protective relay has more time to clear fault and isolate the fault zone without any instability. Finally, different transient scenarios of connection plan sustainability of small scale synchronous generators to the distribution network are presented.

Keywords: critical clearing time, fault current limiter, synchronous generator, transient stability, transient states

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Authors: Xiaoping Su, Gabriel G. Malouf

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Introduction: Breast cancer is a heterogeneous disease that can be classified in 4 subgroups using transcriptional profiling. The role of lncRNA expression in human breast cancer biology, prognosis, and molecular classification remains unknown. Methods and results: Using an integrative comprehensive analysis of lncRNA, mRNA and DNA methylation in 900 breast cancer patients from The Cancer Genome Atlas (TCGA) project, we unraveled the molecular portraits of 1,700 expressed lncRNA. Some of those lncRNAs (i.e, HOTAIR) are previously reported and others are novel (i.e, HOTAIRM1, MAPT-AS1). The lncRNA classification correlated well with the PAM50 classification for basal-like, Her-2 enriched and luminal B subgroups, in contrast to the luminal A subgroup which behaved differently. Importantly, estrogen receptor (ESR1) expression was associated with distinct lncRNA networks in lncRNA clusters III and IV. Gene set enrichment analysis for cis- and trans-acting lncRNA showed enrichment for breast cancer signatures driven by breast cancer master regulators. Almost two third of those lncRNA were marked by enhancer chromatin modifications (i.e., H3K27ac), suggesting that lncRNA expression may result in increased activity of neighboring genes. Differential analysis of gene expression profiling data showed that lncRNA HOTAIRM1 was significantly down-regulated in basal-like subtype, and DNA methylation profiling data showed that lncRNA HOTAIRM1 was highly methylated in basal-like subtype. Thus, our integrative analysis of gene expression and DNA methylation strongly suggested that lncRNA HOTAIRM1 should be a tumor suppressor in basal-like subtype. Conclusion and significance: Our study depicts the first lncRNA molecular portrait of breast cancer and shows that lncRNA HOTAIRM1 might be a novel tumor suppressor.

Keywords: lncRNA profiling, breast cancer, HOTAIRM1, tumor suppressor

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Authors: Omaima N. Ahmad AL-Allaf

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Over communication networks, images can be easily copied and distributed in an illegal way. The copyright protection for authors and owners is necessary. Therefore, the digital watermarking techniques play an important role as a valid solution for authority problems. Digital image watermarking techniques are used to hide watermarks into images to achieve copyright protection and prevent its illegal copy. Watermarks need to be robust to attacks and maintain data quality. Therefore, we discussed in this paper two approaches for image watermarking, first is based on Particle Swarm Optimization (PSO) and the second approach is based on Genetic Algorithm (GA). Discrete wavelet transformation (DWT) is used with the two approaches separately for embedding process to cover image transformation. Each of PSO and GA is based on co-relation coefficient to detect the high energy coefficient watermark bit in the original image and then hide the watermark in original image. Many experiments were conducted for the two approaches with different values of PSO and GA parameters. From experiments, PSO approach got better results with PSNR equal 53, MSE equal 0.0039. Whereas GA approach got PSNR equal 50.5 and MSE equal 0.0048 when using population size equal to 100, number of iterations equal to 150 and 3×3 block. According to the results, we can note that small block size can affect the quality of image watermarking based PSO/GA because small block size can increase the search area of the watermarking image. Better PSO results were obtained when using swarm size equal to 100.

Keywords: image watermarking, genetic algorithm, particle swarm optimization, discrete wavelet transform

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Authors: Leili Nekounazar

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Since 2009, when the Green movement, Iran’s most significant political uprising in post-Islamic revolution materialized, the term 'soft war' has become an integral part of the Iranian regime’s lexicon when addressing the media propaganda waged by the west and the regime’s so-called 'enemies'. Iran’s authorities describe soft war as a western campaign aiming at undermining the revolutionary values by covert activities, deploying cultural tools and purposeful dissemination of information. With this respect, Internet and in particular, the social media networks, and oppositional radio-television broadcasts have been considered as the west’s soft war conduits. With the rising of the underground fashion industry in the past couple of years that does not conform to the compulsory dress codes prescribed by the state, the Islamic regime expands the soft war narrative to include any undesired fashion-related activities and frames the rising fashion industry as a cultural war intoxicating the Iranian-Islamic identity. Accordingly, fashion products created by the Iranian fashion intermediators have been attributed to the westerners and outsiders and are regarded as the matter of national security. This study examines the reactive and proactive measures deployed by the Iranian regime to control the rise of fashion industry. It further puts under the scrutiny how the state as a part of its proactive measure shapes the narrative of 'soft war' in relation to fashion in Iran and explores how the notion of soft war has been articulated in relation to the modeling and fashion in the state’s political rhetoric. Through conducting a content analysis of the authorities’ statements, it describes how the narrative of soft war assists the state policing the fashion industry.

Keywords: censorship, fashion, Iran, soft war

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Authors: Yili Wang, Jarmo Kinos, Tuire Palonen, Tarja-Riitta Hurme

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This longitudinal study aims to examine how five- and six-year-old children’s peer relationships are formed and fostered during one preschool year in a southwestern Finnish preschool. All 16 kindergarteners participated in the study (at dyad level N=240; i.e., 16 x 15 relationships among the children). The children were divided into four daily groups, based on the table order during the daily routines, and four intervention groups, based on the teachers’ pedagogical plan. During the intervention, one iPad was given to each group in order to stimulate interaction among peers and, thus, enable the children to form new peer relationships. In the data gathering, sociometric nomination techniques were used to investigate the nature (i.e., stability and mutuality) of the peer relationships. The data was collected five times during the year to see what kind of peer relationship changes occurred at the dyad level and the group level, i.e., in establishing and losing friendship ties among the children. Social network analyses were used to analyze the data. The results indicate that the children’s preference for gender segregation was strong compared to age preference and intervention. In all, the number of reciprocal friendship ties and the mutual absence of friendship ties increased towards the end of the year, whereas the number of unilateral friendship ties decreased. This indicates that children’s nominations narrow down; thus, the group structure becomes more crystalized. Instead of extending their friendship networks, children seek stable and mutual relationships with their peers in their middle childhood years. The intervention only had a slightly negative influence on children’s peer relationships.

Keywords: intervention study, peer relationship, preschool education, social network analysis, sociometric ratings

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Authors: Sohail Ahmed, Ke Xing

Abstract:

This research theoretically explored the evolution mechanism of enterprise technological innovation capability system (ETICS) from the perspective of complex adaptive systems (CAS). This research proposed an analytical framework for ETICS, its concepts, and theory by integrating CAS methodology into the management of the technological innovation capability of enterprises and discusses how to use the principles of complexity to analyze the composition, evolution, and realization of the technological innovation capabilities in complex dynamic environments. This paper introduces the concept and interaction of multi-agent, the theoretical background of CAS, and summarizes the sources of technological innovation, the elements of each subject, and the main clusters of adaptive interactions and innovation activities. The concept of multi-agents is applied through the linkages of enterprises, research institutions, and government agencies with the leading enterprises in industrial settings. The study was exploratory and based on CAS theory. Theoretical model is built by considering technological and innovation literature from foundational to state of the art projects of technological enterprises. On this basis, the theoretical model is developed to measure the evolution mechanism of the enterprise's technological innovation capability system. This paper concludes that the main characteristics for evolution in technological systems are based on the enterprise’s research and development personnel, investments in technological processes, and innovation resources are responsible for the evolution of enterprise technological innovation performance. The research specifically enriched the application process of technological innovation in institutional networks related to enterprises.

Keywords: complex adaptive system, echo model, enterprise technological innovation capability system, research institutions, multi-agents

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Authors: Tzu-Yang Lin, Chuan-Ching Sue

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Sleep mechanisms are commonly used to ensure the energy efficiency of each optical network unit (ONU) that concerns a single class delay constraint in the Ethernet Passive Optical Network (EPON). How long the ONUs can sleep without violating the delay constraint has become a research problem. Particularly, we can derive an analytical model to determine the optimal sleep time of ONUs in every cycle without violating the maximum class delay constraint. The bandwidth allocation considering such optimal sleep time is called Green Bandwidth Allocation (GBA). Although the GBA mechanism guarantees that the different class delay constraints do not violate the maximum class delay constraint, packets with a more relaxed delay constraint will be treated as those with the most stringent delay constraint and may be sent early. This means that the ONU will waste energy in active mode to send packets in advance which did not need to be sent at the current time. Accordingly, we proposed a QoS-aware GBA using a novel intra-ONU scheduling to control the packets to be sent according to their respective delay constraints, thereby enhancing energy efficiency without deteriorating delay performance. If packets are not explicitly classified but with different packet delay constraints, we can modify the intra-ONU scheduling to classify packets according to their packet delay constraints rather than their classes. Moreover, we propose the switchable ONU architecture in which the ONU can switch the architecture according to the sleep time length, thus improving energy efficiency in the QoS-aware GBA. The simulation results show that the QoS-aware GBA ensures that packets in different classes or with different delay constraints do not violate their respective delay constraints and consume less power than the original GBA.

Keywords: Passive Optical Networks, PONs, Optical Network Unit, ONU, energy efficiency, delay constraint

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Authors: Manoj Sarda, Abhishek Agarwal, Juhi Kaushik, Vatsal Sanjay, Arup Kumar Das

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Railways in India remain primary mode of transport having one of the largest networks in the world and catering to billions of transits yearly. Catastrophic economic damage and loss to life is encountered over the past few decades due to fire to locomotives. Study of fire dynamics and fire propagation plays an important role in evacuation planning and reducing losses. Simulation based study of propagation of fire and soot inside an air conditioned coach of Indian locomotive is done in this paper. Finite difference based solver, Fire Dynamic Simulator (FDS) version 6 has been used for analysis. A single air conditioned 3 tier coupe closed to ambient surroundings by glass windows having occupancy for 8 people is the basic unit of the domain. A system of three such coupes combined is taken to be fundamental unit for the entire study to resemble effect to an entire coach. Analysis of flame and soot contours and concentrations is done corresponding to variations in heat release rate per unit volume (HRRPUA) of fire source, variations in conditioned air velocity being circulated inside coupes by vents and an alternate fire initiation and propagation mechanism via ducts. Quantitative results of fractional area in top and front view of the three coupes under fire and smoke are obtained using MATLAB (IMT). Present simulations and its findings will be useful for organizations like Commission of Railway Safety and others in designing and implementing safety and evacuation measures.

Keywords: air conditioned coaches, fire propagation, flame contour, soot flow, train fire

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Authors: Deyu Zhou, Xiao Xue, Lizhen Cui

Abstract:

With the increasing collaboration among various services and the growing complexity of user demands, there are more and more factors affecting the stable development of the cloud manufacturing service economic system (CMSE). This poses new challenges to the evolution analysis of the CMSE. Many researchers have modeled and analyzed the evolution process of CMSE from the perspectives of individual learning and internal factors influencing the system, but without considering other important characteristics of the system's individuals (such as heterogeneity, bounded rationality, etc.) and the impact of external environmental factors. Therefore, this paper proposes an integrated artificial social model for the cloud manufacturing service economic system, which considers both the characteristics of the system's individuals and the internal and external influencing factors of the system. The model consists of three parts: the Agent model, environment model, and rules model (Agent-Environment-Rules, AER): (1) the Agent model considers important features of the individuals, such as heterogeneity and bounded rationality, based on the adaptive behavior mechanisms of perception, action, and decision-making; (2) the environment model describes the activity space of the individuals (real or virtual environment); (3) the rules model, as the driving force of system evolution, describes the mechanism of the entire system's operation and evolution. Finally, this paper verifies the effectiveness of the AER model through computational and experimental results.

Keywords: cloud manufacturing service economic system (CMSE), AER model, artificial social modeling, integrated framework, computing experiment, agent-based modeling, social networks

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Authors: Sohail Ahmed, Ke Xing

Abstract:

This research theoretically explored the evolution mechanism of enterprise technological innovation capability system (ETICS) from the perspective of complex adaptive systems (CAS). Starting from CAS theory, this study proposed an analytical framework for ETICS, its concepts and theory by integrating CAS methodology into the management of technological innovation capability of enterprises and discusses how to use the principles of complexity to analyze the composition, evolution and realization of the technological innovation capabilities in complex dynamic environment. This paper introduces the concept and interaction of multi-agent, the theoretical background of CAS and summarizes the sources of technological innovation, the elements of each subject and the main clusters of adaptive interactions and innovation activities. The concept of multi-agents is applied through the linkages of enterprises, research institutions and government agencies with the leading enterprises in industrial settings. The study was exploratory based on CAS theory. Theoretical model is built by considering technological and innovation literature from foundational to state of the art projects of technological enterprises. On this basis, the theoretical model is developed to measure the evolution mechanism of enterprise technological innovation capability system. This paper concludes that the main characteristics for evolution in technological systems are based on enterprise’s research and development personal, investments in technological processes and innovation resources are responsible for the evolution of enterprise technological innovation performance. The research specifically enriched the application process of technological innovation in institutional networks related to enterprises.

Keywords: complex adaptive system, echo model, enterprise knowledge system, research institutions, multi-agents.

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Authors: Manjitsingh Rajput

Abstract:

Visual communication plays an important role in artificial intelligence (AI) because it enables machines to understand and interpret visual information, similar to how humans do. This abstract explores the importance of visual communication in AI and emphasizes the importance of various applications such as computer vision, object emphasis recognition, image classification and autonomous systems. In going deeper, with deep learning techniques and neural networks that modify visual understanding, In addition to AI programming, the abstract discusses challenges facing visual interfaces for AI, such as data scarcity, domain optimization, and interpretability. Visual communication and other approaches, such as natural language processing and speech recognition, have also been explored. Overall, this abstract highlights the critical role that visual communication plays in advancing AI capabilities and enabling machines to perceive and understand the world around them. The abstract also explores the integration of visual communication with other modalities like natural language processing and speech recognition, emphasizing the critical role of visual communication in AI capabilities. This methodology explores the importance of visual communication in AI development and implementation, highlighting its potential to enhance the effectiveness and accessibility of AI systems. It provides a comprehensive approach to integrating visual elements into AI systems, making them more user-friendly and efficient. In conclusion, Visual communication is crucial in AI systems for object recognition, facial analysis, and augmented reality, but challenges like data quality, interpretability, and ethics must be addressed. Visual communication enhances user experience, decision-making, accessibility, and collaboration. Developers can integrate visual elements for efficient and accessible AI systems.

Keywords: visual communication AI, computer vision, visual aid in communication, essence of visual communication.

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Authors: Kenneth D. Aiello, M. Simeone, Manfred Laubichler

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It is increasingly difficult to analyze emerging scientific fields as contemporary scientific fields are more dynamic, their boundaries are more porous, and the relational possibilities have increased due to Big Data and new information sources. In biomedicine, where funding, medical categories, and medical jurisdiction are determined by distinct boundaries on biomedical research fields and definitions of concepts, ambiguity persists between the microbiome, metabolome, and metagenome research fields. This ambiguity continues despite efforts by institutions and organizations to establish parameters on the core concepts and research discourses. Further, the explosive growth of microbiome, metabolome, and metagenomic research has led to unknown variation and covariation making application of findings across subfields or coming to a consensus difficult. This study explores the evolution and variation of knowledge within the microbiome, metabolome, and metagenome research fields related to ambiguous scholarly language and commensurable theoretical frameworks via a semantic analysis of key concepts and narratives. A computational historical framework of cultural evolution and large-scale publication data highlight the boundaries and overlaps between the competing scientific discourses surrounding the three research areas. The results of this study highlight how discourse and language distribute power within scholarly and scientific networks, specifically the power to set and define norms, central questions, methods, and knowledge.

Keywords: biomedicine, conceptual change, history of science, philosophy of science, science of science, sociolinguistics, sociology of knowledge

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Authors: Siliang Luan, Zhongtai Jiang

Abstract:

The risk of highway incidents is commonly recognized as a major concern for transportation authorities due to the hazardous consequences and negative influence. It is crucial to respond to these unpredictable events as soon as possible faced by emergency management decision makers. In this paper, we focus on path planning for emergency vehicles, one of the most significant processes to avoid congestion and reduce rescue time. A Mixed-Integer Linear Programming with Semi-Soft Time Windows Model (MIPSSTWM) is conducted to plan an optimal routing respectively considering the time consumption of arcs and nodes of the urban road network and the highway network, especially in developing countries with an enormous population. Here, the arcs indicate the road segments and the nodes include the intersections of the urban road network and the on-ramp and off-ramp of the highway networks. An attempt in this research has been made to develop a comprehensive and executive strategy for emergency vehicle routing in heavy traffic conditions. The proposed Cuckoo Search (CS) algorithm is designed by imitating obligate brood parasitic behaviors of cuckoos and Lévy Flights (LF) to solve this hard and combinatorial problem. Using a Chinese city as our case study, the numerical results demonstrate the approach we applied in this paper outperforms the previous method without considering the nodes of the road network for a real-world situation. Meanwhile, the accuracy and validity of the CS algorithm also show better performances than the traditional algorithm.

Keywords: emergency vehicle, path planning, cs algorithm, urban traffic management and urban planning

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Authors: T. M. Tawfik, M. A. Badr, E. Y. El-Kady, O. E. Abdellatif

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Electric power shortage is a serious problem in remote rural communities in Egypt. Over the past few years, electrification of remote communities including efficient on-site energy resources utilization has achieved high progress. Remote communities usually fed from diesel generator (DG) networks because they need reliable energy and cheap fresh water. The main objective of this paper is to design an optimal economic power supply from hybrid standalone energy system (HSES) as alternative energy source. It covers energy requirements for reverse osmosis desalination unit (DU) located in National Research Centre farm in Noubarya, Egypt. The proposed system consists of PV panels, Wind Turbines (WT), Batteries, and DG as a backup for supplying DU load of 105.6 KWh/day rated power with 6.6 kW peak load operating 16 hours a day. Optimization of HSES objective is selecting the suitable size of each of the system components and control strategy that provide reliable, efficient, and cost-effective system using net present cost (NPC) as a criterion. The harmonization of different energy sources, energy storage, and load requirements are a difficult and challenging task. Thus, the performance of various available configurations is investigated economically and technically using iHOGA software that is based on genetic algorithm (GA). The achieved optimum configuration is further modified through optimizing the energy extracted from renewable sources. Effective minimization of energy charging the battery ensures that most of the generated energy directly supplies the demand, increasing the utilization of the generated energy.

Keywords: energy management, hybrid system, renewable energy, remote area, optimization

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Authors: Nadeem Akhtar, An Ran, Cornelius B. Pratt

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China’s President Xi' vision of Belt and Road Initiative, an infrastructural project of development and connectivity, is attracting international students to Chinese universities, with Pakistan and India among the top-10 countries of origin of those students (Ministry of Education China, 2018). An additional factor in international students’ interest in Chinese universities is their improving global rankings of Chinese universities. Against that backdrop, this study addresses two overarching questions: (a) What factors explain South Asian students’ study-away experiences, particularly in their multicultural environments? and (b) What role do new media play in their adaptation to that environment? This study is guided by Stephen’s (2011) theoretical model, which suggests that social networks influence immigrants’ interactions with host and home culture. The present study used a structured questionnaire distributed through both WeChat and other online platforms to international students studying in Chinese universities. Preliminary results are threefold: (a) that the frequency of use of social media is a predictor of the level of adjustment of the students to their multicultural environment; (b) that social engagement with their international-student peers is a moderating factor in their experiential outcomes; and (c) length of stay in Chinese universities, surprisingly, was not a predictor of adaptation. A major implication of these findings is that, even though social media tend to be criticized for contributing to anomie and to diminishing social capital among youths and millennials, they can be poignant tools for cultural adaptation, particularly among international students in China. It remains to be seen if such outcomes occur among international students in other countries or world regions.

Keywords: adaptation, China's Belt and Road Initiative, international students, social media

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Authors: Morteza Ahmadpur, Ilgin Gokasar, Saman Ghaffarian

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That Transportation system plays an important role in management of societies is an undeniable fact and it is one of the most challenging issues in human beings routine life. But by increasing the population in urban areas, the demand for transportation modes also increase. Accordingly, it is obvious that more flexible and dynamic transportation system is required to satisfy peoples’ requirements. Nowadays, there is significant increase in number of environmental issues all over the world which is because of human activities. New technological achievements bring new horizons for humans and so they changed the life style of humans in every aspect of their life and transportation is not an exception. By using new technology, societies can modernize their transportation system and increase the feasibility of their system. Real–time Taxi sharing systems is one of the novel and most modern systems all over the world. For establishing this kind of system in an urban area it is required to use the most advanced technologies in a transportation system. GPS navigation devices, computers and social networks are just some parts of this kind of system. Like carpooling, real-time taxi sharing is one of the best ways to better utilize the empty seats in most cars and taxis, thus decreasing energy consumption and transport costs. It can serve areas not covered by a public transit system and act as a transit feeder service. Taxi sharing is also capable of serving one-time trips, not only recurrent commute trips or scheduled trips. In this study, we describe the requirements and parameters that we need to establish a useful real-time ride sharing system for an urban area. The parameters and requirements of this study can be used in any urban area.

Keywords: transportation, intelligent transportation systems, ride-sharing, taxi sharing

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Authors: Reuben Kinyuru Njuguna, Martin Mabuya Njuguna

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Digital platforms, such as The Internet, and the advent of digital marketing strategies, have led to many changes in the marketing of goods and services. These have resulted in improved service quality, enhanced customer relations, productivity gains, marketing transaction cost reductions, improved customer service and flexibility in fulfilling customers’ changing needs and lifestyles. Consequently, the purpose of this study was to determine the effect of digital marketing practices on the financial performance of mobile network operators in the telecommunications industry in Kenya. The objectives of the study were to establish how digital customer relationship management strategies on performance of mobile network operators in Kenya. The study used an explanatory cross-sectional survey research design, while the target population was made up of from the 4 major mobile network operators in Kenya, namely Safaricom Limited, Airtel Networks Kenya Limited, Finserve Africa Limited and Telkom Kenya Limited. Sampling strategy was stratified sampling with a sample size of 97 respondents. Digital customer relationship strategies were seen to influence firm performance, through enhancing convenience, building trust, encouraging growth in market share through creating sustainable relationships, building commitment with customers, enhancing customer retention and customer satisfaction. Digital customer relationship management were seen to maximize gross profits by increasing customer satisfaction, loyalty and retention. The study recommended upscaling the use of digital customer relationship management strategies to further enhance firm performance, given their great potential in this regard.

Keywords: customer relationship management, customer service delivery, performance, customer satisfaction

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Authors: Catriona Hilliard

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Food identity is synonymous with many national tourism destinations and perceptions in tourist source markets – stereotypes could include snails in France; beer in Britain and Germany; paella in Spain - and is an accepted element of national identity that can be incorporated into tourism experiences. Irish transatlantic food connections are culturally strong with diaspora subsequent generations in the US displaying an online interest in traditional Irish food, even with a twist. Back ‘home’, the value of the local indigenous experience was a specific element of the way The Gathering 2013 was promoted to the Irish diaspora, developing community interest and input to tourism. Over the past 20 years, Ireland has realized the value of its food industry to tourism. This has included the establishment of food development programmes for the hospitality industry; food festivals as a possible element of the tourist experience; and a programmes of food ambassadors to market Irish produce and to encourage service providers to understand; utilize and incorporate this into their offerings. Irish produce is being now actively marketed as part of the proposed tourism experience, to particular segment markets including transatlantic visitors. In addition, individual providers are becoming aware of the value of the market, and how to gain from it. Also, networks of food providers have developed collaborative structures of promoting their experiences to audiences, displaying a cluster approach of tourism development towards that sector. A power point presentation will look at how Irish produce contributes to tourism marketing and promotion of Ireland to America; how that may have assisted sustainable development of communities here; and hopes to elicit some discussion relating to longer term identification of Irish food, as part of tourism, for the potential benefit of the ‘locale’.

Keywords: Irish, USA, food, tourism

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Authors: Lokendra Kumar Devangan, Ajay Mishra

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This paper describes the implementation of a large-scale SAS/OR model with significant pre-processing, scenario analysis, and post-processing work done using SAS. A large cement manufacturer with ten geographically distributed manufacturing plants for two variants of cement, around 400 warehouses serving as transshipment points, and several thousand distributor locations generating demand needed to optimize this multi-echelon, multi-modal transport supply chain separately for planning and allocation purposes. For monthly planning as well as daily allocation, the demand is deterministic. Rail and road networks connect any two points in this supply chain, creating tens of thousands of such connections. Constraints include the plant’s production capacity, transportation capacity, and rail wagon batch size constraints. Each demand point has a minimum and maximum for shipments received. Price varies at demand locations due to local factors. A large mixed integer programming model built using proc OPTMODEL decides production at plants, demand fulfilled at each location, and the shipment route to demand locations to maximize the profit contribution. Using base SAS, we did significant pre-processing of data and created inputs for the optimization. Using outputs generated by OPTMODEL and other processing completed using base SAS, we generated several reports that went into their enterprise system and created tables for easy consumption of the optimization results by operations.

Keywords: production planning, mixed integer optimization, network model, network optimization

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Authors: Chun-Qing Li, Guoyang Fu, Wei Yang

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A significant portion of current water networks is made of cast iron pipes. Due to aging and deterioration with corrosion being the most predominant mechanism, the failure rate of cast iron pipes is very high. Although considerable research has been carried out in the past few decades, most are on the effect of corrosion on the structural capacity of pipes using strength theory as the failure criterion. This paper presents a reliability-based methodology for the assessment of corrosion affected cast iron pipe cracking failures. A nonlinear limit state function taking into account all three fracture modes is proposed for brittle metal pipes with mixed mode fracture. A stochastic model of the load effect is developed, and time-dependent reliability method is employed to quantify the probability of failure and predict the remaining service life. A case study is carried out using the proposed methodology, followed by sensitivity analysis to investigate the effects of the random variables on the probability of failure. It has been found that the larger the inclination angle or the Mode I fracture toughness is, the smaller the probability of pipe failure is. It has also been found that the multiplying and exponential coefficients k and n in the power law corrosion model and the internal pressure have the most influence on the probability of failure for cast iron pipes. The methodology presented in this paper can assist pipe engineers and asset managers in developing a risk-informed and cost-effective strategy for better management of corrosion-affected pipelines.

Keywords: corrosion, inclined surface cracks, pressurized cast iron pipes, stress intensity

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Authors: Nitish Suvarna, Anjali Awasthi

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In an era marked by rapid technological advancements, the integration of Autonomous Vehicles into supply chain networks represents a transformative shift, promising to redefine the paradigms of logistics and transportation. This thesis delves into a comprehensive assessment of the impact of autonomous vehicles on supply chain performance, with a particular focus on network design, operational efficiency, and environmental sustainability. Employing the advanced simulation capabilities of anyLogistix (ALX), the study constructs a digital twin of a conventional supply chain network, encompassing suppliers, production facilities, distribution centers, and customer endpoints. The research methodically integrates Autonomous Vehicles into this intricate network, aiming to unravel the multifaceted effects on transportation logistics including transit times, cost-efficiency, and sustainability. Through simulations and scenarios analysis, the study scrutinizes the operational resilience and adaptability of supply chains in the face of dynamic market conditions and disruptive technologies like Autonomous Vehicles. Furthermore, the thesis undertakes carbon footprint analysis, quantifying the environmental benefits and challenges associated with the adoption of Autonomous Vehicles in supply chain operations. The insights from this research are anticipated to offer a strategic framework for industry stakeholders, guiding the adoption of Autonomous Vehicles to foster a more efficient, responsive, and sustainable supply chain ecosystem. The findings aim to serve as a cornerstone for future research and practical implementations in the realm of intelligent transportation and supply chain management.

Keywords: autonomous vehicle, agri-food supply chain, ALX simulation, anyLogistix

Procedia PDF Downloads 75