Search results for: collaborative networks

Authors: Sylvie Michel, François Cocula

Abstract:

Digital agriculture is an approach that exploits information and communication technologies. These encompass data acquisition tools like mobile applications, satellites, sensors, connected devices, and smartphones. Additionally, it involves transfer and storage technologies such as 3G/4G coverage, low-bandwidth terrestrial or satellite networks, and cloud-based systems. Furthermore, embedded or remote processing technologies, including drones and robots for process automation, along with high-speed communication networks accessible through supercomputers, are integral components of this approach. While farm-level adoption studies regarding digital agricultural technologies have emerged in recent years, they remain relatively limited in comparison to other agricultural practices. To bridge this gap, this study delves into understanding farmers' intention to adopt digital tools, employing the technology, organization, environment framework. A qualitative research design encompassed semi-structured interviews, totaling fifteen in number, conducted with key stakeholders both prior to and following the 2020-2021 COVID-19 lockdowns in France. Subsequently, the interview transcripts underwent thorough thematic content analysis, and the data and verbatim were triangulated for validation. A coding process aimed to systematically organize the data, ensuring an orderly and structured classification. Our research extends its contribution by delineating sub-dimensions within each primary dimension. A total of nine sub-dimensions were identified, categorized as follows: perceived usefulness for communication, perceived usefulness for productivity, and perceived ease of use constitute the first dimension; technological resources, financial resources, and human capabilities constitute the second dimension, while market pressure, institutional pressure, and the COVID-19 situation constitute the third dimension. Furthermore, this analysis enriches the TOE framework by incorporating entrepreneurial orientation as a moderating variable. Managerial orientation emerges as a pivotal factor influencing adoption intention, with producers acknowledging the significance of utilizing digital sales support tools to combat "greenwashing" and elevate their overall brand image. Specifically, it illustrates that producers recognize the potential of digital tools in time-saving and streamlining sales processes, leading to heightened productivity. Moreover, it highlights that the intent to adopt digital sales support tools is influenced by a market mimicry effect. Additionally, it demonstrates a negative association between the intent to adopt these tools and the pressure exerted by institutional partners. Finally, this research establishes a positive link between the intent to adopt digital sales support tools and economic fluctuations, notably during the COVID-19 pandemic. The adoption of sales support tools in agriculture is a multifaceted challenge encompassing three dimensions and nine sub-dimensions. The research delves into the adoption of digital farming technologies at the farm level through the TOE framework. This analysis provides significant insights beneficial for policymakers, stakeholders, and farmers. These insights are instrumental in making informed decisions to facilitate a successful digital transition in agriculture, effectively addressing sector-specific challenges.

Keywords: adoption, digital agriculture, e-commerce, TOE framework

Procedia PDF Downloads 43

Authors: Guiheng Zhang, Wei Zhang, Jun Fu, Yudong Wang

Abstract:

A 900 MHz three-stage SiGe power amplifier (PA) with high power gain is presented in this paper. Volterra Series is applied to analyze nonlinearity sources of SiGe HBT device model clearly. Meanwhile, the influence of operating current to IMD3 is discussed. Then a β-helper current mirror bias circuit is applied to improve linearity, since the β-helper current mirror bias circuit can offer stable base biasing voltage. Meanwhile, it can also work as predistortion circuit when biasing voltages of three bias circuits are fine-tuned, by this way, the power gain and operating current of PA are optimized for best linearity. The three power stages which fabricated by 0.18 μm SiGe technology are bonded to the printed circuit board (PCB) to obtain impedances by Load-Pull system, then matching networks are done for best linearity with discrete passive components on PCB. The final measured three-stage PA exhibits 21.1 dBm of output power at 1 dB compression point (OP1dB) with power added efficiency (PAE) of 20.6% and 33 dB power gain under 3.3 V power supply voltage.

Keywords: high gain power amplifier, linearization bias circuit, SiGe HBT model, Volterra series

Procedia PDF Downloads 316

Authors: Joel Weymouth, Ramesh K. Karne, Alexander L. Wijesinha

Abstract:

Bare Machine Internet is part of the Bare Machine Computing (BMC) paradigm. It is used in programming application ns to run directly on a device. It is software that runs directly against the hardware using CPU, Memory, and I/O. The software application runs without an Operating System and resident mass storage. An important part of the BMC paradigm is the Bare Machine Internet. It utilizes an Application Development model software that interfaces directly with the hardware on a network server and file server. Because it is “bare,” it is a powerful teaching and research tool that can readily display the internals of the network protocols, software, and hardware of the applications running on the Bare Server. It was also demonstrated that the bare server was accessible by laptop and by smartphone/android. The purpose was to show the further practicality of Bare Internet in Computer Engineering and Computer Science Education and Research. It was also to show that an undergraduate student could take advantage of a bare server with any device and any browser at any release version connected to the internet. This paper presents the Bare Web Server as an educational tool. We will discuss possible applications of this paradigm.

Keywords: bare machine computing, online research, network technology, visualizing network internals

Procedia PDF Downloads 153

Authors: Seung Yoon Hyun, Hyeong Seung An, Myeong Ho Choi, Sung Hwan Bae, Yu Jong Sim

Abstract:

In 2015, the southern part of the Korean Peninsula has 8.6 million poles, 1.25 million km power lines, and 2 million transformers, etc. It is the massive amount of distribution equipments which could cover a round-trip distance from the earth to the moon and 11 turns around the earth. These distribution equipments are spread out like capillaries and supplying power to every corner of the Korean Peninsula. In order to manage these huge power facility efficiently, KEPCO use DAS (Distribution Automation System) to operate distribution power system since 1997. DAS is integrated system that enables to remotely supervise and control breakers and switches on distribution network. Using DAS, we can reduce outage time and power loss. KEPCO has about 160,000 switches, 50%(about 80,000) of switches are automated, and 41 distribution center monitoring&control these switches 24-hour 365 days to get the best efficiency of distribution networks. However, the rapid increasing renewable energy sources become the problem in the efficient operation of distributed power system. (currently 2,400 MW, 75,000 generators operate in distribution power system). In this paper, it suggests the way to interconnect between renewable energy source and distribution power system.

Keywords: distribution, renewable, connect, DAS (Distribution Automation System)

Procedia PDF Downloads 602

Authors: Mallikarjun B. Channappagoudar, Pallapa Venkataram

Abstract:

The dynamic nature of Mobile adhoc network (MANET) due to mobility and disconnection of mobile nodes, leads to various problems in predicting the movement of nodes and their location information updation, for efficient interaction among the application specific nodes. Location management is one of the main challenges to be considered for an efficient service provision to the applications of a MANET. In this paper, we propose a location management protocol, for locating the nodes of a MANET and to maintain uninterrupted high-quality service for distributed applications by intelligently anticipating the change of location of its nodes. The protocol predicts the node movement and application resource scarcity, does the replacement with the chosen nodes nearby which have less mobility and rich in resources, with the help of both static and mobile agents, and maintains the application continuity by providing required network resources. The protocol has been simulated using Java Agent Development Environment (JADE) Framework for agent generation, migration and communication. It consumes much less time (response time), gives better location accuracy, utilize less network resources, and reduce location management overhead.

Keywords: mobile agent, location management, distributed applications, mobile adhoc network

Procedia PDF Downloads 377

Authors: N. Mahon, I. Crute, M. Di Bonito, E. Simmons, M. M. Islam

Abstract:

Growing interest in the concept of the sustainable intensification (SI) of agriculture has been shown by, national governments, transnational agribusinesses, intergovernmental organizations and research institutes, amongst others. This interest may be because SI is seen as a ‘third way’ for agricultural development, between the seemingly disparate paradigms of ‘intensive’ agriculture and more ‘sustainable’ forms of agriculture. However, there is a lack of consensus as to what SI means in practice and how it should be measured using indicators of change. This has led to growing confusion, disagreement and skepticism regarding the concept, especially amongst civil society organizations, both in the UK and other countries. This has prompted the need for bottom-up, participatory approaches to identify indicators of SI. Our aim is to identify the views of British stakeholders regarding the areas of agreement and disagreement as to what SI is and how it should be measured in the UK using indicators of change. Data for this investigation came from 32 semi-structured interviews, conducted between 2015 and 2016, with stakeholders from throughout the UK food system. In total 110 indicators of SI were identified. These indicators covered a wide variety of subjects including biophysical, social and political considerations. A number of indicators appeared to be widely applicable and were similar to those suggested in the global literature. These include indicators related to the management of the natural resources on which agriculture relies e.g., ‘Soil organic matter’, ‘Number of pollinators per hectare’ and ‘Depth of water table’. As well as those related to agricultural externalities, e.g., ‘Greenhouse gas emissions’ and ‘Concentrations of agro-chemicals in waterways’. However, many of the indicators were much more specific to the context of the UK. These included, ‘Areas of high nature value farmland’, ‘Length of hedgerows per hectare’ and ‘Age of farmers’. Furthermore, tensions could be seen when participants considered the relative importance of agricultural mechanization versus levels of agricultural employment, the pros and cons of intensive, housed livestock systems and value of wild biodiversity versus the desire to increase agricultural yields. These areas of disagreement suggest the need to carefully consider the trade-offs inherent in the concept. Our findings indicate that in order to begin to resolve the confusions surrounding SI it needs to be considered in a context specific manner, rather than as a single uniform concept. Furthermore, both the environmental and the social parameters in which agriculture operates need to be considered in order to operationalize SI in a meaningful way. We suggest that participatory approaches are key to this process, facilitating dialogue and collaborative-learning between all the stakeholders, allowing them to reach a shared vision for the future of agricultural development.

Keywords: agriculture, indicators, participatory approach, sustainable intensification

Procedia PDF Downloads 210

Authors: A. Al-Juboori, D. Wexler, H. Li, H. Zhu, C. Lu, A. McCusker, J. McLeod, S. Pannila, Z. Wang

Abstract:

Squats are a type railhead defect related to rolling contact fatigue (RCF) damage and are considered serious problem affecting a wide range of railway networks across the world. Squats can lead to partial or complete rail failure. Formation mechanics of squats on the surface of rail steel is still a matter of debate. In this work, structural and microstructural observations from ex-service damaged rail both confirms the phases present in white etching layer (WEL) regions and relationship between cracking in WEL and squat defect formation. XRD synchrotron results obtained from the top surfaces of rail regions containing both WEL and squat defects reveal that these regions contain both martensite and retained austenite. Microstructural analysis of these regions revealed the occurrence cracks extending from WEL down into the rail through the squat region. These findings obtained from field rail specimen support the view that WEL contains regions of austenite and martensitic transformation product, and that cracks in this brittle surface layer propagate deeper into the rail as squats originate and grow.

Keywords: squat, white etching layer, rolling contact fatigue, synchrotron diffraction

Procedia PDF Downloads 315

Authors: Kuei-Ling Sun, Emily Chia-Yu Su

Abstract:

Allergy is a hypersensitive overreaction of the immune system to environmental stimuli, and a major health problem. These overreactions include rashes, sneezing, fever, food allergies, anaphylaxis, asthmatic, shock, or other abnormal conditions. Allergies can be caused by food, insect stings, pollen, animal wool, and other allergens. Their development of allergies is due to both genetic and environmental factors. Allergies involve immunoglobulin E antibodies, a part of the body’s immune system. Immunoglobulin E antibodies will bind to an allergen and then transfer to a receptor on mast cells or basophils triggering the release of inflammatory chemicals such as histamine. Based on the increasingly serious problem of environmental change, changes in lifestyle, air pollution problem, and other factors, in this study, we both collect allergens and non-allergens from several databases and use several machine learning methods for classification, including logistic regression (LR), stepwise regression, decision tree (DT) and neural networks (NN) to do the model comparison and determine the permutations of allergen amino acid’s sequence.

Keywords: allergy, classification, decision tree, logistic regression, machine learning

Procedia PDF Downloads 286

Authors: Christine Winberg, James Garraway

Abstract:

Many key university documents, such as vision and mission statements and strategic plans, are aspirational and future-oriented. There is a wide range of future-oriented methods that are used in planning applications, ranging from mathematical modelling to expert opinions. Many of these methods have limitations, and planners using these tools might, for example, make the technical-rational assumption that their plans will unfold in a logical and inevitable fashion, thus underestimating the many complex forces that are at play in planning for an unknown future. This is the issue that this study addresses. The overall project aim was to assist a new university of technology in developing appropriate responses to its social responsibility, graduate employability and research missions in its strategic plan. The specific research question guiding the research activities and approach was: how might the use of innovative future-oriented planning tools enable or constrain a strategic planning process? The research objective was to engage collaborating groups in the use of an innovative tool to develop and assess future scenarios, for the purpose of developing deeper understandings of possible futures and their challenges. The scenario planning tool chosen was ‘fictive scripting’, an analytical technique derived from Technology Forecasting and Innovation Studies. Fictive scripts are future projections that also take into account the present shape of the world and current developments. The process thus began with a critical diagnosis of the present, highlighting its tensions and frictions. The collaborative groups then developed fictive scripts, each group producing a future scenario that foregrounded different institutional missions, their implications and possible consequences. The scripts were analyzed with a view to identifying their potential contribution to the university’s strategic planning exercise. The unfolding fictive scripts revealed a number of insights in terms of unexpected benefits, unexpected challenges, and unexpected consequences. These insights were not evident in previous strategic planning exercises. The contribution that this study offers is to show how better choices can be made and potential pitfalls avoided through a systematic foresight exercise. When universities develop strategic planning documents, they are looking into the future. In this paper it is argued that the use of appropriate tools for future-oriented exercises, can help planners to understand more fully what achieving desired outcomes might entail, what challenges might be encountered, and what unexpected consequences might ensue.

Keywords: fictive scripts, scenarios, strategic planning, technological forecasting

Procedia PDF Downloads 107

Authors: Hardi Alunaza, Mauidhotu Rofiq

Abstract:

This research is attempted to describe the role of KontraS as track-6 on multi track diplomacy for conflict resolution in Myanmar in 2015. The researcher took the specific interest on multi track diplomacy and transnational advocacy concepts to analyze the phenomena. Furthermore, this essay is using the descriptive method with a qualitative approach. The data collection technique is literature study consisting of books, journals, and including data from the reliable website in supporting the explanation of this research. The result of this research is divided into two important points in explaining the role of KontraS in cases of human rights crisis in Myanmar. First, KontraS as human rights NGO in Indonesia was able to advocate against human rights violence that occurred in other countries by encouraging Indonesian Government to take part in the resolution of human rights issues affecting the Rohingya people in Burma. Also, KontraS take advantages of transnational advocacy networks as a form of politics and accountabilities responsibility of Non-Governmental Organization against human rights crisis in other countries.

Keywords: conflict resolution, human rights crisis, multi track diplomacy, transnational advocacy

Procedia PDF Downloads 307

Authors: Abdulaziz Afandi

Abstract:

Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: neural network, LSTM, MLP, forecasting demand, inventory management

Procedia PDF Downloads 109

Authors: Gamze Uslu, Sebnem Baydere, Alper K. Demir

Abstract:

In this study, data loss tolerance of Support Vector Machines (SVM) based activity recognition model and multi activity classification performance when data are received over a lossy wireless sensor network is examined. Initially, the classification algorithm we use is evaluated in terms of resilience to random data loss with 3D acceleration sensor data for sitting, lying, walking and standing actions. The results show that the proposed classification method can recognize these activities successfully despite high data loss. Secondly, the effect of differentiated quality of service performance on activity recognition success is measured with activity data acquired from a multi hop wireless sensor network, which introduces high data loss. The effect of number of nodes on the reliability and multi activity classification success is demonstrated in simulation environment. To the best of our knowledge, the effect of data loss in a wireless sensor network on activity detection success rate of an SVM based classification algorithm has not been studied before.

Keywords: activity recognition, support vector machines, acceleration sensor, wireless sensor networks, packet loss

Procedia PDF Downloads 456

Authors: Fisayo G. Ojo, Shamala K. Subramaniam, Zuriati Ahmad Zukarnain

Abstract:

As technology is advancing and wireless applications are becoming dependable sources, while the physical layer of the applications are been embedded into tiny layer, so the more the problem on energy efficiency and consumption. This paper reviews works done in recent years in wireless applications and distributed computing, we discovered that applications are becoming dependable, and resource allocation sharing with other applications in distributed computing. Applications embedded in distributed system are suffering from power stability and efficiency. In the reviews, we also prove that discrete event simulation has been left behind untouched and not been adapted into distributed system as a simulation technique in scheduling of each event that took place in the development of distributed computing applications. We shed more lights on some researcher proposed techniques and results in our reviews to prove the unsatisfactory results, and to show that more work still have to be done on issues of energy efficiency in wireless applications, and congestion in distributed computing.

Keywords: discrete event simulation (DES), distributed computing, energy efficiency (EE), internet of things (IOT), quality of service (QOS), user equipment (UE), wireless mesh network (WMN), wireless sensor network (wsn), worldwide interoperability for microwave access x (WiMAX)

Procedia PDF Downloads 175

Authors: Heather Fulford, Melanie Liddell

Abstract:

The recruitment and retention of high quality employees can prove to be challenging for social enterprises, particularly in some of the core business support functions such as marketing, communications, IT and finance. This holds true for social enterprises in urban contexts, where roles with more attractive remuneration in these business functions can often be found quite readily in the private sector. For social enterprises situated in rural locations, the challenges of staff recruitment and retention are even more acute. Such challenges can lead to a skills deficit in rural social enterprises, which can, at best, hinder their growth potential, and worse, jeopardise their chances of survival. This in turn, can have a negative impact on the sustainability and resilience of the surrounding rural community in which the social enterprise is located. The purpose of this paper is to report on aspects of a collaborative initiative established to stimulate innovation and business growth in remote rural businesses in Scotland. Launched in 2010, this initiative was designed to attract young students and graduates from the region to stay in the region upon completion of their studies, and to attract others from outside the region to re-locate there post-university. To facilitate this, SMEs in the region were offered wage subsidies to encourage them to recruit a student or graduate on a work placement for up to one year to participate in an innovation or business growth-oriented project. A number of the employers offering work placements were social enterprises. Through analysis of the placement project and role specifications devised by the participating social enterprises, an overview is provided of their business development needs and the skills they require to stimulate innovation and growth. Scrutiny of the reflective accounts compiled by the students and graduates at the close of their work placements highlights the benefits they derived from being able to put their academic knowledge and skills into action within a social enterprise. Examination of interviews conducted with a sample of placement employers reveals the contribution the students and graduates made during the business development projects with the social enterprises. The challenges of hosting such placements are also discussed. The paper concludes with indications of the lessons learned and an outline of the wider implications for other remote rural locations in which social enterprises play an important role in the local economy and life of the community.

Keywords: resilience, rural development, regeneration, regional development, recruitment, resource management, retention, remuneration

Procedia PDF Downloads 303

Authors: Kulsoom S. Bughio, Naeem K. Janjua, Gordana Dermody, Leslie F. Sikos, Shamsul Islam

Abstract:

The advancement in information and communication technologies (ICT) and wireless sensor networks have played a pivotal role in the design and development of real-time healthcare solutions, mainly targeting the elderly living in health-assistive smart homes. Such smart homes are equipped with sensor technologies to detect and record activities of daily living (ADL). This survey reviews and evaluates existing approaches and techniques based on real-time sensor-based modeling and reasoning in single-user and multi-user environments. It classifies the approaches into three main categories: learning-based, knowledge-based, and hybrid, and evaluates how they handle temporal relations, granularity, and uncertainty. The survey also highlights open challenges across various disciplines (including computer and information sciences and health sciences) to encourage interdisciplinary research for the detection and recognition of ADLs and discusses future directions.

Keywords: daily living activities, smart homes, single-user environment, multi-user environment

Procedia PDF Downloads 123

Authors: Said Rabah Azzam, Andrew Graham

Abstract:

Fragmentation of packets caused by encryption applied on the network layer of the IOS model in Internet Protocol version 4 (IPv4) networks as well as the possibility of using fragmentation and Access Control Lists (ACLs) as a method of restricting network access to certain hosts or areas of a network.Using default settings, fragmentation is expected to occur and each fragment to be reassembled at the other end. If this does not occur then a high number of ICMP messages should be generated back towards the source host indicating that the packet is too large and that it needs to be made smaller. This result is also expected when the MTU is changed for certain links between devices.When using ACLs and packet fragments to restrict access to hosts or network segments it is possible that ACLs cannot be set up in this way. If ACLs cannot be setup to allow only fragments then it is a limitation of the hardware’s firmware holding back this particular method. If the ACL on the restricted switch can be set up in such a way to allow only fragments then a connection that forces packets to fragment should be allowed to pass through the ACL. This should then make a network connection to the destination machine allowing data to be sent to and from the destination machine. ICMP messages from the restricted access switch and host should also be blocked from being sent back across the link which will be shown in an SSH session into the switch.

Keywords: fragmentation, encryption, security, switch

Procedia PDF Downloads 312

Authors: Sunita Boro, Saurabh Kumar Dixit

Abstract:

Terroir, an intricate fusion of geography, climate, soil, and human expertise, has long been acknowledged as a defining factor in the character of wines and foods. This research embarks on an exploration of terroir's profound influence on gastronomic tourism, shedding light on the intricate interplay between the physical environment and culinary artistry. Delving into the intricate science of terroir, we scrutinize its role in shaping the sensory profiles of wines and foods, emphasizing the profound impact of specific regions on flavor, aroma, and texture. We deploy a multifaceted methodology, amalgamating sensory analysis, chemical profiling, geographical information systems, and qualitative interviews to unearth the nuanced nuances of terroir expression. Through an exhaustive review of the literature, we elucidate the historical roots of terroir, unveil the intricate cultural dimensions shaping it, and provide a comprehensive examination of prior studies in the field. Our findings underscore the pivotal role of terroir in promoting regional identities, enhancing the economic viability of locales, and attracting gastronomic tourists. The paper also dissects the marketing strategies employed to promote terroir-driven food and wine experiences. We elucidate the utilization of storytelling, branding, and collaborative endeavors in fostering a robust terroir-based tourism industry. This elucidates both the potential for innovation and the challenges posed by oversimplification or misrepresentation of terroir. Our research spotlights the intersection of terroir and sustainability, emphasizing the significance of environmentally conscious practices in terroir-driven productions. We discern the harmonious relationship between sustainable agriculture, terroir preservation, and responsible tourism, encapsulating the essence of ecological integrity in gastronomic tourism. Incorporating compelling case studies of regions and businesses excelling in the terroir-based tourism realm, we offer in-depth insights into successful models and strategies, with an emphasis on their replicability and adaptability to various contexts. Ultimately, this paper not only contributes to the scholarly understanding of terroir's role in the world of food and wine tourism but also provides actionable recommendations for stakeholders to leverage terroir's allure, preserve its authenticity, and foster sustainable and enriching culinary tourism experiences.

Keywords: terroir, food tourism, wine tourism, sustainability

Procedia PDF Downloads 44

Authors: Kaleem Kashif, Tayyaba Anam, Yizhi Wu

Abstract:

This paper introduces a methodology for advancing Italian speech vowels landmark detection within the distinctive feature-based speech recognition domain. Leveraging the legacy tool 'xkl' by integrating combined convolutional neural networks (CNNs) and recurrent neural networks (RNNs), the study presents a comprehensive enhancement to the 'xkl' legacy software. This integration incorporates re-assigned spectrogram methodologies, enabling meticulous acoustic analysis. Simultaneously, our proposed model, integrating combined CNNs and RNNs, demonstrates unprecedented precision and robustness in landmark detection. The augmentation of re-assigned spectrogram fusion within the 'xkl' software signifies a meticulous advancement, particularly enhancing precision related to vowel formant estimation. This augmentation catalyzes unparalleled accuracy in landmark detection, resulting in a substantial performance leap compared to conventional methods. The proposed model emerges as a state-of-the-art solution in the distinctive feature-based speech recognition systems domain. In the realm of deep learning, a synergistic integration of combined CNNs and RNNs is introduced, endowed with specialized temporal embeddings, harnessing self-attention mechanisms, and positional embeddings. The proposed model allows it to excel in capturing intricate dependencies within Italian speech vowels, rendering it highly adaptable and sophisticated in the distinctive feature domain. Furthermore, our advanced temporal modeling approach employs Bayesian temporal encoding, refining the measurement of inter-landmark intervals. Comparative analysis against state-of-the-art models reveals a substantial improvement in accuracy, highlighting the robustness and efficacy of the proposed methodology. Upon rigorous testing on a database (LaMIT) speech recorded in a silent room by four Italian native speakers, the landmark detector demonstrates exceptional performance, achieving a 95% true detection rate and a 10% false detection rate. A majority of missed landmarks were observed in proximity to reduced vowels. These promising results underscore the robust identifiability of landmarks within the speech waveform, establishing the feasibility of employing a landmark detector as a front end in a speech recognition system. The synergistic integration of re-assigned spectrogram fusion, CNNs, RNNs, and Bayesian temporal encoding not only signifies a significant advancement in Italian speech vowels landmark detection but also positions the proposed model as a leader in the field. The model offers distinct advantages, including unparalleled accuracy, adaptability, and sophistication, marking a milestone in the intersection of deep learning and distinctive feature-based speech recognition. This work contributes to the broader scientific community by presenting a methodologically rigorous framework for enhancing landmark detection accuracy in Italian speech vowels. The integration of cutting-edge techniques establishes a foundation for future advancements in speech signal processing, emphasizing the potential of the proposed model in practical applications across various domains requiring robust speech recognition systems.

Keywords: landmark detection, acoustic analysis, convolutional neural network, recurrent neural network

Procedia PDF Downloads 40

Authors: Zeynep Genel

Abstract:

The concept of reputation in corporate development comes to the fore as one of the most frequently discussed topics in recent years. Many organizations, which make worldwide investments, make effort in order to adapt themselves to the topics within the scope of this concept and to promote the name of the organization through the values that might become prominent. The stakeholder groups are considered as the most important actors determining the reputation. Even, the effect of stakeholders is not evaluated as a direct factor; it is signed as indirect effects of their perception are a very strong on ultimate reputation. It is foreseen that the parallelism between the projected reputation and the perceived c reputation, which is established as a result of communication experiences perceived by the stakeholders, has an important effect on achieving these objectives. In assessing the efficiency of these efforts, the opinions of stakeholders are widely utilized. In other words, the projected reputation, in which the positive and/or negative reflections of corporate communication play effective role, is measured through how the stakeholders perceptively position the organization. From this perspective, it is thought that the interaction and cooperation of corporate communication professionals with different stakeholder groups during the reputation positioning efforts play significant role in achieving the targeted reputation or in sustainability of this value. The governmental stakeholders having intense communication with mass stakeholder groups are within the most effective stakeholder groups of organization. The most important reason of this is that the organizations, regarding which the governmental stakeholders have positive perception, inspire more confidence to the mass stakeholders. At this point, the organizations carrying out joint projects with governmental stakeholders in parallel with sustainable communication approach come to the fore as the organizations having strong reputation, whereas the reputation of organizations, which fall behind in this regard or which cannot establish the efficiency from this aspect, is thought to be perceived as weak. Similarly, the social responsibility campaigns, in which the governmental stakeholders are involved and which play efficient role in strengthening the reputation, are thought to draw more attention. From this perspective, the role and effect of governmental stakeholders on the reputation positioning is discussed in this study. In parallel with this objective, it is aimed to reveal perspectives of seven governmental stakeholders towards the cooperation in reputation positioning. The sample group representing the governmental stakeholders is examined under the lights of results obtained from in-depth interviews with the executives of different ministries. It is asserted that this study, which aims to express the importance of stakeholder participation in corporate reputation positioning especially in Turkey and the effective role of governmental stakeholders in strong reputation, might provide a new perspective on measuring the corporate reputation, as well as establishing an important source to contribute to the studies in both academic and practical domains.

Keywords: collaborative communications, reputation management, stakeholder engagement, ultimate reputation

Procedia PDF Downloads 213

Authors: Peng Li, Luan Wang, Haifeng Fei, Renhong Xie, Yibin Rui, Shanhong Guo

Abstract:

The applications of satellite-based automatic identification system (S-AIS) pave the road for wide-range maritime traffic monitoring and management. But the coverage of satellite’s view includes multiple AIS self-organizing networks, which leads to the collision of AIS signals from different cells. The contribution of this work is to propose an improved multi-channel blind source separation algorithm based on Artificial Bee Colony (ABC) and advanced stochastic optimization to perform separation of the mixed AIS signals. The proposed approach adopts modified ABC algorithm to get an optimized initial separating matrix, which can expedite the initialization bias correction, and utilizes the Adaptive Moment Estimation (Adam) to update the separating matrix by adjusting the learning rate for each parameter dynamically. Simulation results show that the algorithm can speed up convergence and lead to better performance in separation accuracy.

Keywords: satellite-based automatic identification system, blind source separation, artificial bee colony, adaptive moment estimation

Procedia PDF Downloads 168

Authors: Tharntip Tawnie Chutikulrungsee, Oliver Kisalay Burmeister, Maumita Bhattacharya, Dragana Calic

Abstract:

Sharing on social network sites (SNSs) has rapidly emerged as a new social norm and has become a global phenomenon. Billions of users reveal not only their own information (self disclosure) but also information about others (other-generated disclosure), resulting in a risk and a serious threat to either personal or informational privacy. Self-disclosure (SD) has been extensively researched in the literature, particularly regarding control of individual and existing privacy management. However, far too little attention has been paid to other-generated disclosure (OGD), especially by insiders. OGD has a strong influence on self-presentation, self-image, and electronic word of mouth (eWOM). Moreover, OGD is more credible and less likely manipulated than SD, but lacks privacy control and legal protection to some extent. This article examines OGD in depth, ranging from motivation to both online and offline impacts, based upon lived experiences from both ‘the disclosed’ and ‘the discloser’. Using purposive sampling, this phenomenological study involves an online survey and in-depth interviews. The findings report the influence of peer disclosure as well as users’ strategies to mitigate privacy issues. This article also calls attention to the challenge of OGD privacy and inadequacies in the law related to privacy protection in the digital domain.

Keywords: facebook, online privacy, other-generated disclosure, social networks sites (SNSs)

Procedia PDF Downloads 233

Authors: Vanaja Rao

Abstract:

In the recent times, the need for the integration of Renewable Energy Sources (RES) in a Smart Grid is on the rise. As a result of this, associated energy storage systems are known to play important roles in sustaining the efficient operation of such RES like wind power and solar power. This paper investigates the importance of location selection of Energy Storage Systems (ESSs) in a Smart Grid. Three scenarios of ESS location is studied and analyzed in a Smart Grid, which are – 1. Near the generation/source, 2. In the middle of the Grid and, 3. Near the demand/consumption. This is explained with the aim of assisting any Distribution Network Operator (DNO) in deploying the ESSs in a power network, which will significantly help reduce the costs and time of planning and avoid any damages incurred as a result of installing them at an incorrect location of a Smart Grid. To do this, the outlined scenarios mentioned above are modelled and analyzed with the National Grid’s datasets of energy generation and consumption in the UK power network. As a result, the outcome of this analysis aims to provide a better overview for the location selection of the ESSs in a Smart Grid. This ensures power system stability and security along with the optimum usage of the ESSs.

Keywords: distribution networks, energy storage system, energy security, location planning, power stability, smart grid

Procedia PDF Downloads 283

Authors: Yosra Mefteh Rekik, Younes Boujelbene

Abstract:

We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

Procedia PDF Downloads 428

Authors: Geng Cui, Naoto Imura, Katsuhiro Nishinari, Takahiro Ezaki

Abstract:

The bullwhip effect, which refers to the amplification of demand variance as one moves up the supply chain, has been observed in various industries and extensively studied through analytic approaches. Existing methods to mitigate the bullwhip effect, such as decentralized demand information, vendor-managed inventory, and the Collaborative Planning, Forecasting, and Replenishment System, rely on the willingness and ability of supply chain participants to share their information. However, in practice, information sharing is often difficult to realize due to privacy concerns. The purpose of this study is to explore new ways to mitigate the bullwhip effect without the need for information sharing. This paper proposes a 'bullwhip absorption strategy' (BAS) to alleviate the bullwhip effect by absorbing it downstream in the supply chain. To achieve this, a two-stage supply chain system was employed, consisting of a single retailer and a single manufacturer. In each time period, the retailer receives an order generated according to an autoregressive process. Upon receiving the order, the retailer depletes the ordered amount, forecasts future demand based on past records, and places an order with the manufacturer using the order-up-to replenishment policy. The manufacturer follows a similar process. In essence, the mechanism of the model is similar to that of the beer game. The BAS is implemented at the retailer's level to counteract the bullwhip effect. This strategy requires the retailer to reduce the uncertainty in its orders, thereby absorbing the bullwhip effect downstream in the supply chain. The advantage of the BAS is that upstream participants can benefit from a reduced bullwhip effect. Although the retailer may incur additional costs, if the gain in the upstream segment can compensate for the retailer's loss, the entire supply chain will be better off. Two indicators, order variance and inventory variance, were used to quantify the bullwhip effect in relation to the strength of absorption. It was found that implementing the BAS at the retailer's level results in a reduction in both the retailer's and the manufacturer's order variances. However, when examining the impact on inventory variances, a trade-off relationship was observed. The manufacturer's inventory variance monotonically decreases with an increase in absorption strength, while the retailer's inventory variance does not always decrease as the absorption strength grows. This is especially true when the autoregression coefficient has a high value, causing the retailer's inventory variance to become a monotonically increasing function of the absorption strength. Finally, numerical simulations were conducted for verification, and the results were consistent with our theoretical analysis.

Keywords: bullwhip effect, supply chain management, inventory management, demand forecasting, order-to-up policy

Procedia PDF Downloads 55

Authors: Yin Yuanling

Abstract:

A Deep Feedback Recurrent Neural Network (DFRNN) and Bidirectional Long Short-Term Memory (BiLSTM) are designed to address the problem of low accuracy of traditional relationship extraction models. This method combines a deep feedback-based recurrent neural network (DFRNN) with a bi-directional long short-term memory (BiLSTM) approach. The method combines DFRNN, which extracts local features of text based on deep feedback recurrent mechanism, BiLSTM, which better extracts global features of text, and Self-Attention, which extracts semantic information. Experiments show that the method achieves an F1 value of 76.69% on the CEC dataset, which is 0.0652 better than the BiLSTM+Self-ATT model, thus optimizing the performance of the deep learning method in the event relationship extraction task.

Keywords: event relations, deep learning, DFRNN models, bi-directional long and short-term memory networks

Procedia PDF Downloads 116

Authors: Lisa Graham, Kathleen Grant

Abstract:

South Africa is a multicultural country with eleven official languages, yet most of the formal education at institutions of higher education in the country is in English. It is well known that many students, irrespective of their home language, struggle to grasp difficult scientific concepts and the same is true for students enrolled in the Extended Curriculum Programme at the Cape Peninsula University of Technology (CPUT), studying biomedical sciences. Today we are fortunate in that there is a plethora of resources available to students to research and better understand subject matter online. For example, the students often use YouTube videos to supplement the formal education provided in our course. Unfortunately, most of this material is presented in English. The rationale behind this project lies in that it is well documented that students think and grasp concepts easier in their home language and addresses the fact that the lingua franca of instruction in the field of biomedical science is English. A project aimed at addressing the lack of available resources in most of the South African languages is planned, where students studying Bachelor of Health Science in Medical Laboratory Science will collaborate with those studying Film and Video Technology to create educational videos, explaining scientific concepts in their home languages. These videos will then be published on our own YouTube channel, thereby making them accessible to fellow students, future students and anybody with interest in the subject. Research will be conducted to determine the benefit of the project as well as the published videos to the student community. It is suspected that the students engaged in making the videos will benefit in such a way as to gain further understanding of their course content, a broader appreciation of the discipline, an enhanced sense of civic responsibility, as well as greater respect for the different languages and cultures in our classes. Indeed, an increase in student engagement has been shown to play a central role in student success, and it is well noted that deeper learning and more innovative solutions take place in collaborative groups. We aim to make a meaningful contribution towards the production and repository of knowledge in multilingual teaching and learning for the benefit of the diverse student population and staff. This would strengthen language development, multilingualism, and multiculturalism at CPUT and empower and promote African languages as languages of science and education at CPUT, in other institutions of higher learning, and in South Africa as a whole.

Keywords: educational videos, multiculturalism, multilingualism, student engagement

Procedia PDF Downloads 140

Authors: Mustafa Sahin, İlkay Yavrucuk

Abstract:

This paper presents a wind turbine envelope protection control algorithm that protects Variable Speed Variable Pitch (VSVP) wind turbines from damage during operation throughout their below and above rated regions, i.e. from cut-in to cut-out wind speed. The proposed approach uses a neural network that can adapt to turbines and their operating points. An algorithm monitors instantaneous wind and turbine states, predicts a wind speed that would push the turbine to a pre-defined envelope limit and, when necessary, realizes an avoidance action. Simulations are realized using the MS Bladed Wind Turbine Simulation Model for the NREL 5 MW wind turbine equipped with baseline controllers. In all simulations, through the proposed algorithm, it is observed that the turbine operates safely within the allowable limit throughout the below and above rated regions. Two example cases, adaptations to turbine operating points for the below and above rated regions and protections are investigated in simulations to show the capability of the proposed envelope protection system (EPS) algorithm, which reduces excessive wind turbine loads and expectedly increases the turbine service life.

Keywords: adaptive envelope protection control, limit detection and avoidance, neural networks, ultimate load reduction, wind turbine power control

Procedia PDF Downloads 117

Authors: Adithya Jaikumar, Sudarsan Jayasingh

Abstract:

The dramatic technology led changes that continue to take place at the market place has led to the emergence and implication of online brand pages on social media networks. The Facebook brand page has become extremely popular among different brands. The primary aim of this study was to identify the impact of post formats and content type on customer engagement in Facebook brand pages. Methodology used for this study was to analyze and categorize 9037 content messages posted by 20 automobile brands in India during April 2014 to March 2015 and the customer activity it generated in return. The data was obtained from Fanpage karma- an online tool used for social media analytics. The statistical technique used to analyze the count data was negative binomial regression. The study indicates that there is a statistically significant relationship between the type of post and the customer engagement. The study shows that photos are the most posted format and highest engagement is found to be related to videos. The finding also reveals that social events and entertainment related content increases engagement with the message.

Keywords: content analysis, customer engagement, digital engagement, facebook brand pages, social media

Procedia PDF Downloads 304

Authors: Nirmal Kundu, Chandan Bhar, Visveswaran Pandurangan

Abstract:

Technology is the most valued possession for a country or an organization. The economic development depends not on stock of technology but on the capabilities how the technology is being exploited. The technology transfer is the best way how the developing countries have an access to state-of- the-art technology. Traditional technology transfer is a unidirectional phenomenon where technology is transferred from developed to developing countries. But now there is a change of wind. There is a general agreement that global shift of economic power is under way from west to east. As China and India are making the transition from users to producers, and producers to innovators, this has increasing important implications on economy, technology and policy of global trade. As a result, Reverse technology transfer has become a phenomenon and field of study in technology management. The term “Reverse Technology Transfer” is not well defined. Initially the concept of Reverse technology transfer was associated with the phenomenon of “Brain drain” from developing to developed countries. In the second phase, Reverse Technology Transfer was associated with the transfer of knowledge and technology from subsidiaries to multinationals. Finally, time has come now to extend the concept of reverse technology transfer to two different organizations or countries related or unrelated by traditional technology transfer but the transfer or has essentially received the technology through traditional mode of technology transfer. The objective of this paper is to study; 1) the present status of Reverse technology transfer, 2) the factors which are the enablers and barriers of Reverse technology transfer and 3) how the reverse technology transfer strategy can be integrated in the technology policy of a country which will give the countries an economic boost. The research methodology used in this study is a combination of literature review, case studies and key informant interviews. The literature review includes both published as well as unpublished sources of literature. In case study, attempt has been made to study the records of reverse technology transfer that have been occurred in developing countries. In case of key informant interviews, informal telephonic discussions have been carried out with the key executives of the organizations (industry, university and research institutions) who are actively engaged in the process of technology transfer- traditional as well as reverse. Reverse technology transfer is possible only by creating technological capabilities. Following four important enablers coupled with government active and aggressive action can help to build technology base to reach to the goal of Reverse technology transfer 1) Imitation to innovation, 2) Reverse engineering, 3) Collaborative R & D approach, and 4) Preventing reverse brain drain. The barriers that come in the way are the mindset of over dependence, over subordination and parent–child attitude (not adult attitude). Exploitation of these enablers and overcoming the barriers of reverse technology transfer, the developing countries like India and China can prove that going “reverse” is the best way to move forward and again establish themselves as leader of the future world.

Keywords: barriers of reverse technology transfer, enablers of reverse technology transfer, knowledge transfer, reverse technology transfer, technology transfer

Procedia PDF Downloads 386

Authors: Joseph Uzuazomaro Oju

Abstract:

The ease at which manipulated media can be created, and the increasing difficulty in identifying fake media makes it a great threat. Most of the applications used for the creation of these high-quality fake videos and images are built with deep learning. Hence, the use of deep learning in creating a detection mechanism cannot be overemphasized. Any successful fake media that is being detected before it reached the populace will save people from the self-doubt of either a content is genuine or fake and will ensure the credibility of videos and images. The methodology introduced in this paper approaches the manipulated media detection challenge using a combo of VGG-19 and a deep capsule network. In the case of videos, they are converted into frames, which, in turn, are resized and cropped to the face region. These preprocessed images/videos are fed to the VGG-19 network to extract the latent features. The extracted latent features are inputted into a deep capsule network enhanced with a 3D -convolution dynamic routing agreement. The 3D –convolution dynamic routing agreement algorithm helps to reduce the linkages between capsules networks. Thereby limiting the poor learning shortcoming of multiple capsule network layers. The resultant output from the deep capsule network will indicate a media to be either genuine or fake.

Keywords: deep capsule network, dynamic routing, fake media detection, manipulated media

Procedia PDF Downloads 116