Search results for: wireless senor networks
836 Mobile and Hot Spot Measurement with Optical Particle Counting Based Dust Monitor EDM264
Authors: V. Ziegler, F. Schneider, M. Pesch
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With the EDM264, GRIMM offers a solution for mobile short- and long-term measurements in outdoor areas and at production sites. For research as well as permanent areal observations on a near reference quality base. The model EDM264 features a powerful and robust measuring cell based on optical particle counting (OPC) principle with all the advantages that users of GRIMM's portable aerosol spectrometers are used to. The system is embedded in a compact weather-protection housing with all-weather sampling, heated inlet system, data logger, and meteorological sensor. With TSP, PM10, PM4, PM2.5, PM1, and PMcoarse, the EDM264 provides all fine dust fractions real-time, valid for outdoor applications and calculated with the proven GRIMM enviro-algorithm, as well as six additional dust mass fractions pm10, pm2.5, pm1, inhalable, thoracic and respirable for IAQ and workplace measurements. This highly versatile instrument performs real-time monitoring of particle number, particle size and provides information on particle surface distribution as well as dust mass distribution. GRIMM's EDM264 has 31 equidistant size channels, which are PSL traceable. A high-end data logger enables data acquisition and wireless communication via LTE, WLAN, or wired via Ethernet. Backup copies of the measurement data are stored in the device directly. The rinsing air function, which protects the laser and detector in the optical cell, further increases the reliability and long term stability of the EDM264 under different environmental and climatic conditions. The entire sample volume flow of 1.2 L/min is analyzed by 100% in the optical cell, which assures excellent counting efficiency at low and high concentrations and complies with the ISO 21501-1standard for OPCs. With all these features, the EDM264 is a world-leading dust monitor for precise monitoring of particulate matter and particle number concentration. This highly reliable instrument is an indispensable tool for many users who need to measure aerosol levels and air quality outdoors, on construction sites, or at production facilities.Keywords: aerosol research, aerial observation, fence line monitoring, wild fire detection
Procedia PDF Downloads 142835 Analyzing Perceptions of Leadership Capacities After a Year-Long Leadership Development Training: An Exploratory Study of School Leaders in South Africa
Authors: Norma Kok, Diemo Masuko, Thandokazi Dlongwana, Komala Pillay
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CONTEXT: While many school principals have been outstanding teachers and have inherent leadership potential, many have not had access to the quality of leadership development or support that empowers them to produce high-quality education outcomes in extremely challenging circumstances. Further, school leaders in under-served communities face formidable challenges arising from insufficient infrastructure, overcrowded classrooms, socio-economic challenges within the community, and insufficient parental involvement, all of which put a strain on principals’ ability to lead their schools effectively. In addition few school leaders have access to other supportive networks, and many do not know how to build and leverage social capital to create opportunities for their schools and learners. Moreover, we know that fostering parental involvement in their children’s learning improves a child’s morale, attitude, and academic achievement across all subject areas, and promotes better behaviour and social adjustment. Citizen Leader Lab facilitates the Partners for Possibility (PfP) programme to provide leadership development and support to school leaders serving under-resourced communities in South Africa to create effective environments of learning. This is done by creating partnerships between school leaders and private-sector business leaders over a 12-month period. (185) OBJECTIVES: To explore school leaders’ perceptions of their leadership capacities and changes at their schools after being exposed to a year-long leadership development training programme. METHODS: School leaders gained new leadership capacities e.g. resilience, improved confidence, communication and conflict resolution skills - catalysing into improved cultures of collaborative decision-making and environments for enhanced teaching and learningprogramme based on the 70:20:10 model whereby: 10% of learning comes from workshops, 20% of learning takes place through peer learning and 70% of learning occurs through experiential learning as partnerships work together to identify and tackle challenges in targeted schools. Participants completed a post-programme questionnaire consisting of structured and unstructured questions and semi-structured interviews were conducted with them and their business leader. The interviews were audio-recorded, transcribed and thematic content analysis was undertaken. The analysis was inductive and emerging themes were identified. A code list was generated after coding was undertaken using computer software (Dedoose). Quantitative data gathered from surveys was aggregated and analysed. RESULTS: School leadership found the programme interesting and rewarding. They gained new leadership capacities such as resilience, improved confidence, communication and conflict resolution skills - catalyzing into improved cultures of collaborative decision-making and environments for enhanced teaching and learning. New networks resulted in tangible outcomes such as upgrades to school infrastructure, water and sanitation, vegetable gardens at schools resulting in nutrition for learners and/or intangible outcomes such as skills for members of school management teams (SMTs). Collaborative leadership led to SMTs being more aligned, efficient, and cohesive; and teachers being more engaged and motivated. Notable positive changes at the school inspired parents and community members to become more actively involved in the school and in their children’s education. CONCLUSION: The PfP programme leads to improved leadership capacities and improved school culture which leads to improved teaching and learning and new resources for schools.Keywords: collaborative decision-making, collaborative leadership, community involvement, confidence
Procedia PDF Downloads 78834 Exploring the Role of Humorous Dialogues in Advertisements of Pakistani Network Companies: Analysis of Discourses through Multi-Modal Critical Approach
Authors: Jane E. Alam Solangi
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The contribution of the study is to explore the important part of humorous dialogues in cellular network advertisements. This promotes the message of valuable construction and promotion of network companies in Pakistan that employ different and broad techniques to give promotion to selling products. It merely instigates the consumers to buy it. The results of the study after analysis of its collected data gives a vision that advertisers of network advertisements use humorous dialogues as a significant device to the greater level. The source of entertainment in the advertisement is accompanied by the texts and humorous discourses to influence buying decisions of the consumers. Therefore, it tends to neutralize personal and social based values. The earlier contribution of scholars presented that the technical employment of humorous devices leads to the successful market of the relevant products. In order to analyze the humorous discourse devices, the approach of multi-modality of Fairclough (1989) is used. It is accompanied by the framework of Kress and van Leeuwen’s (1996). It analyzes the visual graph of the grammar. The overall findings in the study verified the role of humorous devices in the captivation of consumers’ decision to buy the product that interests them. Therefore, the role of humor acts as a breaker of the monotonous rhythm of advertisements.Keywords: advertisements, devices, humorous, multi-modality, networks, Pakistan
Procedia PDF Downloads 92833 Deep Reinforcement Learning Model Using Parameterised Quantum Circuits
Authors: Lokes Parvatha Kumaran S., Sakthi Jay Mahenthar C., Sathyaprakash P., Jayakumar V., Shobanadevi A.
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With the evolution of technology, the need to solve complex computational problems like machine learning and deep learning has shot up. But even the most powerful classical supercomputers find it difficult to execute these tasks. With the recent development of quantum computing, researchers and tech-giants strive for new quantum circuits for machine learning tasks, as present works on Quantum Machine Learning (QML) ensure less memory consumption and reduced model parameters. But it is strenuous to simulate classical deep learning models on existing quantum computing platforms due to the inflexibility of deep quantum circuits. As a consequence, it is essential to design viable quantum algorithms for QML for noisy intermediate-scale quantum (NISQ) devices. The proposed work aims to explore Variational Quantum Circuits (VQC) for Deep Reinforcement Learning by remodeling the experience replay and target network into a representation of VQC. In addition, to reduce the number of model parameters, quantum information encoding schemes are used to achieve better results than the classical neural networks. VQCs are employed to approximate the deep Q-value function for decision-making and policy-selection reinforcement learning with experience replay and the target network.Keywords: quantum computing, quantum machine learning, variational quantum circuit, deep reinforcement learning, quantum information encoding scheme
Procedia PDF Downloads 118832 Real-Time Recognition of Dynamic Hand Postures on a Neuromorphic System
Authors: Qian Liu, Steve Furber
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To explore how the brain may recognize objects in its general,accurate and energy-efficient manner, this paper proposes the use of a neuromorphic hardware system formed from a Dynamic Video Sensor~(DVS) silicon retina in concert with the SpiNNaker real-time Spiking Neural Network~(SNN) simulator. As a first step in the exploration on this platform a recognition system for dynamic hand postures is developed, enabling the study of the methods used in the visual pathways of the brain. Inspired by the behaviours of the primary visual cortex, Convolutional Neural Networks (CNNs) are modeled using both linear perceptrons and spiking Leaky Integrate-and-Fire (LIF) neurons. In this study's largest configuration using these approaches, a network of 74,210 neurons and 15,216,512 synapses is created and operated in real-time using 290 SpiNNaker processor cores in parallel and with 93.0% accuracy. A smaller network using only 1/10th of the resources is also created, again operating in real-time, and it is able to recognize the postures with an accuracy of around 86.4% -only 6.6% lower than the much larger system. The recognition rate of the smaller network developed on this neuromorphic system is sufficient for a successful hand posture recognition system, and demonstrates a much-improved cost to performance trade-off in its approach.Keywords: spiking neural network (SNN), convolutional neural network (CNN), posture recognition, neuromorphic system
Procedia PDF Downloads 459831 JaCoText: A Pretrained Model for Java Code-Text Generation
Authors: Jessica Lopez Espejel, Mahaman Sanoussi Yahaya Alassan, Walid Dahhane, El Hassane Ettifouri
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Pretrained transformer-based models have shown high performance in natural language generation tasks. However, a new wave of interest has surged: automatic programming language code generation. This task consists of translating natural language instructions to a source code. Despite the fact that well-known pre-trained models on language generation have achieved good performance in learning programming languages, effort is still needed in automatic code generation. In this paper, we introduce JaCoText, a model based on Transformer neural network. It aims to generate java source code from natural language text. JaCoText leverages the advantages of both natural language and code generation models. More specifically, we study some findings from state of the art and use them to (1) initialize our model from powerful pre-trained models, (2) explore additional pretraining on our java dataset, (3) lead experiments combining the unimodal and bimodal data in training, and (4) scale the input and output length during the fine-tuning of the model. Conducted experiments on CONCODE dataset show that JaCoText achieves new state-of-the-art results.Keywords: java code generation, natural language processing, sequence-to-sequence models, transformer neural networks
Procedia PDF Downloads 265830 Potential of Tourism Logistic Service Business in the Border Areas of Chong Anma, Chong Sa-Ngam, and Chong Jom Checkpoints in Thailand to Increase Competitive Efficiency among the ASEAN Community
Authors: Pariwat Somnuek
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This study focused on tourism logistic services in the border areas of Thailand by an analysis and comparison of the opinions of tourists, villagers, and entrepreneurs of these services. Sample representatives of this study were a total of 600 villagers and 15 entrepreneurs in the three border areas consisting of Chong Anma, Chong Sa-Ngam, and Chong Jom checkpoints. For methodology, survey questionnaires, situation analysis, TOWS matrix, and focus group discussions were used for data collection, as well as descriptive analysis and statistics such as arithmetic means and standard deviations, were employed for data analysis. The findings revealed that business potential was at the medium level and entrepreneurs were satisfied with their turnovers. However, perspectives of transportation and tourism services provided for tourists need to be immediately improved. Recommendations for the potential development included promotion of border tourism destinations and foreign investments into accommodation, restaurants, and transport, as well as the establishment of business networks between Thailand and Cambodia, along with the introduction of new tourism destinations by co-operation between entrepreneurs in both countries. These initiatives may lead to increased visitors, collaboration of security offices, and an improved image of tourism security.Keywords: business potential, potential development, tourism logistics, services
Procedia PDF Downloads 302829 Dynamic Risk Model for Offshore Decommissioning Using Bayesian Belief Network
Authors: Ahmed O. Babaleye, Rafet E. Kurt
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The global oil and gas industry is beginning to witness an increase in the number of installations moving towards decommissioning. Decommissioning of offshore installations is a complex, costly and hazardous activity, making safety one of the major concerns. Among existing removal options, complete and partial removal options pose the highest risks. Therefore, a dynamic risk model of the accidents from the two options is important to assess the risks on an overall basis. In this study, a risk-based safety model is developed to conduct quantitative risk analysis (QRA) for jacket structure systems failure. Firstly, bow-tie (BT) technique is utilised to model the causal relationship between the system failure and potential accident scenarios. Subsequently, to relax the shortcomings of BT, Bayesian Belief Networks (BBNs) were established to dynamically assess associated uncertainties and conditional dependencies. The BBN is developed through a similitude mapping of the developed bow-tie. The BBN is used to update the failure probabilities of the contributing elements through diagnostic analysis, thus, providing a case-specific and realistic safety analysis method when compared to a bow-tie. This paper presents the application of dynamic safety analysis to guide the allocation of risk control measures and consequently, drive down the avoidable cost of remediation.Keywords: Bayesian belief network, offshore decommissioning, dynamic safety model, quantitative risk analysis
Procedia PDF Downloads 272828 Optoelectronic Hardware Architecture for Recurrent Learning Algorithm in Image Processing
Authors: Abdullah Bal, Sevdenur Bal
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This paper purposes a new type of hardware application for training of cellular neural networks (CNN) using optical joint transform correlation (JTC) architecture for image feature extraction. CNNs require much more computation during the training stage compare to test process. Since optoelectronic hardware applications offer possibility of parallel high speed processing capability for 2D data processing applications, CNN training algorithm can be realized using Fourier optics technique. JTC employs lens and CCD cameras with laser beam that realize 2D matrix multiplication and summation in the light speed. Therefore, in the each iteration of training, JTC carries more computation burden inherently and the rest of mathematical computation realized digitally. The bipolar data is encoded by phase and summation of correlation operations is realized using multi-object input joint images. Overlapping properties of JTC are then utilized for summation of two cross-correlations which provide less computation possibility for training stage. Phase-only JTC does not require data rearrangement, electronic pre-calculation and strict system alignment. The proposed system can be incorporated simultaneously with various optical image processing or optical pattern recognition techniques just in the same optical system.Keywords: CNN training, image processing, joint transform correlation, optoelectronic hardware
Procedia PDF Downloads 500827 Preparation and Struggle of Two Generations for Future Care: A Study of Intergenerational Care Planning among Mainland Immigrant Ageing Families in Hong Kong
Authors: Xue Bai, Ranran He, Chang Liu
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Care planning before the onset of intensive care needs can benefit older adults’ psychological well-being and increases families’ ability to manage caregiving crises and cope with care transitions. Effective care planning requires collaborative ‘team-work’ in families. However, future care planning has not been substantially examined in intergenerational or family contexts, let alone among immigrant families who have to face particular challenges in parental caregiving. From a family systems perspective, this study intends to explore the extent, processes, and contents of intergenerational care planning of Mainland immigrant ageing families in Hong Kong and to examine the intergenerational congruence and discrepancies in the care planning process. Adopting a qualitative research design, semi-structured in-depth interviews were conducted with 17 adult child-older parent pairs and another 33 adult children. In total, 50 adult children who migrated to Hong Kong after the age of 18 with more than three years’ work experience in Hong Kong had at least one parent aged over 55 years old who was not a Hong Kong resident and considered his/herself as the primary caregiver of the parent were recruited. Seventeen ageing parents of the recruited adult children were invited for dyadic interviews. Scarcity of caregiving resources in the context of cross-border migration, intergenerational discrepancies in care planning stages, both generations’ struggle and ambivalence toward filial care, intergenerational transmission of care values, and facilitating role of accumulated family capital in care preparation were primary themes concluded from participants’ narratives. Compared with ageing parents, immigrant adult children generally displayed lower levels of care planning. Although with a strong awareness of parents’ future care needs, few adult children were found engaged in concrete planning activities. This is largely due to their uncertainties toward future life and career, huge work and living pressure, the relatively good health status of their parents, and restrictions of public welfare policies in the receiving society. By contrast, children’s cross-border migration encouraged ageing parents to have early and clear preparation for future care. Ageing parents mostly expressed low filial care expectations when realizing the scarcity of family caregiving resources in the cross-border context. Even though they prefer in-person support from children, most of them prepare themselves for independent ageing to prioritize the next generation’s needs or choose to utilize paid services, welfare systems, friend networks, or extended family networks in their sending society. Adult children were frequently found caught in the dilemma of desiring to provide high quality and in-person support for their parents but lacking sufficient resources. Notably, a salient pattern of intergenerational transmission in terms of family and care values and ideal care arrangement emerged from intergenerational care preparation. Moreover, the positive role of accumulated family capital generated by a reunion in care preparation and joint decision-making were also identified. The findings of the current study will enhance professionals’ and service providers’ awareness of intergenerational care planning in cross-border migration contexts, inform services to alleviate unpreparedness for elderly care and intergenerational discrepancies concerning care arrangements and broaden family services to encompass intergenerational care planning interventions. Acknowledgment: This study is supported by a General Research Grant from the Research Grants Council of the HKSAR, China (Project Number: 15603818).Keywords: intergenerational care planning, mainland immigrants in Hong Kong, migrant family, older adults
Procedia PDF Downloads 107826 Design and Control of a Knee Rehabilitation Device Using an MR-Fluid Brake
Authors: Mina Beheshti, Vida Shams, Mojtaba Esfandiari, Farzaneh Abdollahi, Abdolreza Ohadi
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Most of the people who survive a stroke need rehabilitation tools to regain their mobility. The core function of these devices is a brake actuator. The goal of this study is to design and control a magnetorheological brake which can be used as a rehabilitation tool. In fact, the fluid used in this brake is called magnetorheological fluid or MR that properties can change by variation of the magnetic field. The braking properties can be set as control by using this feature of the fluid. In this research, different MR brake designs are first introduced in each design, and the dimensions of the brake have been determined based on the required torque for foot movement. To calculate the brake dimensions, it is assumed that the shear stress distribution in the fluid is uniform and the fluid is in its saturated state. After designing the rehabilitation brake, the mathematical model of the healthy movement of a healthy person is extracted. Due to the nonlinear nature of the system and its variability, various adaptive controllers, neural networks, and robust have been implemented to estimate the parameters and control the system. After calculating torque and control current, the best type of controller in terms of error and control current has been selected. Finally, this controller is implemented on the experimental data of the patient's movements, and the control current is calculated to achieve the desired torque and motion.Keywords: rehabilitation, magnetorheological fluid, knee, brake, adaptive control, robust control, neural network control, torque control
Procedia PDF Downloads 141825 Malware Beaconing Detection by Mining Large-scale DNS Logs for Targeted Attack Identification
Authors: Andrii Shalaginov, Katrin Franke, Xiongwei Huang
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One of the leading problems in Cyber Security today is the emergence of targeted attacks conducted by adversaries with access to sophisticated tools. These attacks usually steal senior level employee system privileges, in order to gain unauthorized access to confidential knowledge and valuable intellectual property. Malware used for initial compromise of the systems are sophisticated and may target zero-day vulnerabilities. In this work we utilize common behaviour of malware called ”beacon”, which implies that infected hosts communicate to Command and Control servers at regular intervals that have relatively small time variations. By analysing such beacon activity through passive network monitoring, it is possible to detect potential malware infections. So, we focus on time gaps as indicators of possible C2 activity in targeted enterprise networks. We represent DNS log files as a graph, whose vertices are destination domains and edges are timestamps. Then by using four periodicity detection algorithms for each pair of internal-external communications, we check timestamp sequences to identify the beacon activities. Finally, based on the graph structure, we infer the existence of other infected hosts and malicious domains enrolled in the attack activities.Keywords: malware detection, network security, targeted attack, computational intelligence
Procedia PDF Downloads 252824 Understanding the Selectional Preferences of the Twitter Mentions Network
Authors: R. Sudhesh Solomon, P. Y. K. L. Srinivas, Abhay Narayan, Amitava Das
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Users in social networks either unicast or broadcast their messages. At mention is the popular way of unicasting for Twitter whereas general tweeting could be considered as broadcasting method. Understanding the information flow and dynamics within a Social Network and modeling the same is a promising and an open research area called Information Diffusion. This paper seeks an answer to a fundamental question - understanding if the at-mention network or the unicasting pattern in social media is purely random in nature or is there any user specific selectional preference? To answer the question we present an empirical analysis to understand the sociological aspects of Twitter mentions network within a social network community. To understand the sociological behavior we analyze the values (Schwartz model: Achievement, Benevolence, Conformity, Hedonism, Power, Security, Self-Direction, Stimulation, Traditional and Universalism) of all the users. Empirical results suggest that values traits are indeed salient cue to understand how the mention-based communication network functions. For example, we notice that individuals possessing similar values unicast among themselves more often than with other value type people. We also observe that traditional and self-directed people do not maintain very close relationship in the network with the people of different values traits.Keywords: information diffusion, personality and values, social network analysis, twitter mentions network
Procedia PDF Downloads 368823 Conventional Four Steps Travel Demand Modeling for Kabul New City
Authors: Ahmad Mansoor Stanikzai, Yoshitaka Kajita
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This research is a very essential towards transportation planning of Kabul New City. In this research, the travel demand of Kabul metropolitan area (Existing and Kabul New City) are evaluated for three different target years (2015, current, 2025, mid-term, 2040, long-term). The outcome of this study indicates that, though currently the vehicle volume is less the capacity of existing road networks, Kabul city is suffering from daily traffic congestions. This is mainly due to lack of transportation management, the absence of proper policies, improper public transportation system and violation of traffic rules and regulations by inhabitants. On the other hand, the observed result indicates that the current vehicle to capacity ratio (VCR) which is the most used index to judge traffic status in the city is around 0.79. This indicates the inappropriate traffic condition of the city. Moreover, by the growth of population in mid-term (2025) and long-term (2040) and in the case of no development in the road network and transportation system, the VCR value will dramatically increase to 1.40 (2025) and 2.5 (2040). This can be a critical situation for an urban area from an urban transportation perspective. Thus, by introducing high-capacity public transportation system and the development of road network in Kabul New City and integrating these links with the existing city road network, significant improvements were observed in the value of VCR.Keywords: Afghanistan, Kabul new city, planning, policy, urban transportation
Procedia PDF Downloads 324822 The Transient Reactive Power Regulation Capability of SVC for Large Scale WECS Connected to Distribution Networks
Authors: Y. Ates, A. R. Boynuegri, M. Uzunoglu, A. Karakas
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The recent interest in alternative and renewable energy systems results in increased installed capacity ratio of such systems in total energy production of the world. Specifically, wind energy conversion systems (WECS) draw significant attention among possible alternative energy options, recently. On the contrary of the positive points of penetrating WECS in all over the world in terms of environment protection, energy independence of the countries, etc., there are significant problems to be solved for the grid connection of large scale WECS. The reactive power regulation, voltage variation suppression, etc. can be presented as major issues to be considered in this regard. Thus, this paper evaluates the application of a Static VAr Compensator (SVC) unit for the reactive power regulation and operation continuity of WECS during a fault condition. The system is modeled employing the IEEE 13 node test system. Thus, it is possible to evaluate the system performance with an overall grid simulation model close to real grid systems. The overall simulation model is developed in MATLAB/Simulink/SimPowerSystems® environments and the obtained results effectively match the target of the provided study.Keywords: IEEE 13 bus distribution system, reactive power regulation, static VAr compensator, wind energy conversion system
Procedia PDF Downloads 727821 An Enhanced SAR-Based Tsunami Detection System
Authors: Jean-Pierre Dubois, Jihad S. Daba, H. Karam, J. Abdallah
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Tsunami early detection and warning systems have proved to be of ultimate importance, especially after the destructive tsunami that hit Japan in March 2012. Such systems are crucial to inform the authorities of any risk of a tsunami and of the degree of its danger in order to make the right decision and notify the public of the actions they need to take to save their lives. The purpose of this research is to enhance existing tsunami detection and warning systems. We first propose an automated and miniaturized model of an early tsunami detection and warning system. The model for the operation of a tsunami warning system is simulated using the data acquisition toolbox of Matlab and measurements acquired from specified internet pages due to the lack of the required real-life sensors, both seismic and hydrologic, and building a graphical user interface for the system. In the second phase of this work, we implement various satellite image filtering schemes to enhance the acquired synthetic aperture radar images of the tsunami affected region that are masked by speckle noise. This enables us to conduct a post-tsunami damage extent study and calculate the percentage damage. We conclude by proposing improvements to the existing telecommunication infrastructure of existing warning tsunami systems using a migration to IP-based networks and fiber optics links.Keywords: detection, GIS, GSN, GTS, GPS, speckle noise, synthetic aperture radar, tsunami, wiener filter
Procedia PDF Downloads 382820 Effective Leadership Styles Influence on Knowledge Sharing Behaviour among Employees of SME's in Nigeria
Authors: Christianah Oyelekan Oyewole, Adeniyi Temitope Adetunji
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Earlier researchers acknowledge the significance of knowledge sharing among employees in improving their responsiveness when dealing with unpredicted situations. Effective leadership styles have been known to impact employee knowledge-sharing behavior within an organisation positively. The role of influential leaders in knowledge sharing is accomplished through enhanced social networks and technology. However, preliminary research pointed to a lack of clear conclusions from recently published studies on the impact of effective leadership styles on knowledge-sharing behaviour among employees. The present study addressed this problem through a structured literature review. The review demonstrated that knowledge managers incorporate incentives and reward systems with their leadership styles to influence knowledge-sharing behaviour among employees positively. There was ample evidence that rational, innovative, stable and participatory organisational cultures combined with supportive and command leadership enhance employee intention for knowledge sharing in the organisation. The analysis revealed that transformational, transactional, and mentor leadership styles enhance employees’ knowledge-sharing behavior. Overall, it was resolved that the relationship between knowledge-sharing behavior among employees and leadership styles is mediated by the ability of the organisation to prioritize employee development.Keywords: leadership styles, knowledge sharing, transactional leadership, transformational leadership, mentor leadership, team performance, team productivity, motivation, and creativity
Procedia PDF Downloads 72819 Using Crowdsourced Data to Assess Safety in Developing Countries, The Case Study of Eastern Cairo, Egypt
Authors: Mahmoud Ahmed Farrag, Ali Zain Elabdeen Heikal, Mohamed Shawky Ahmed, Ahmed Osama Amer
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Crowdsourced data refers to data that is collected and shared by a large number of individuals or organizations, often through the use of digital technologies such as mobile devices and social media. The shortage in crash data collection in developing countries makes it difficult to fully understand and address road safety issues in these regions. In developing countries, crowdsourced data can be a valuable tool for improving road safety, particularly in urban areas where the majority of road crashes occur. This study is the first to develop safety performance functions using crowdsourced data by adopting a negative binomial structure model and Full Bayes model to investigate traffic safety for urban road networks and provide insights into the impact of roadway characteristics. Furthermore, as a part of the safety management process, network screening has been undergone through applying two different methods to rank the most hazardous road segments: PCR method (adopted in the Highway Capacity Manual HCM) as well as a graphical method using GIS tools to compare and validate. Lastly, recommendations were suggested for policymakers to ensure safer roads.Keywords: crowdsourced data, road crashes, safety performance functions, Full Bayes models, network screening
Procedia PDF Downloads 20818 Intelligent Transport System: Classification of Traffic Signs Using Deep Neural Networks in Real Time
Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma
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Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.Keywords: multiclass classification, convolution neural network, OpenCV
Procedia PDF Downloads 165817 A Biomechanical Perfusion System for Microfluidic 3D Bioprinted Structure
Authors: M. Dimitri, M. Ricci, F. Bigi, M. Romiti, A. Corvi
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Tissue engineering has reached a significant milestone with the integration of 3D printing for the creation of complex bioconstructs equipped with vascular networks, crucial for cell maintenance and growth. This study aims to demonstrate the effectiveness of a portable microperfusion system designed to adapt dynamically to the evolving conditions of cell growth within 3D-printed bioconstructs. The microperfusion system was developed to provide a constant and controlled flow of nutrients and oxygen through the integrated vessels in the bioconstruct, replicating in vivo physiological conditions. Through a series of preliminary experiments, we evaluated the system's ability to maintain a favorable environment for cell proliferation and differentiation. Measurements of cell density and viability were performed to monitor the health and functionality of the tissue over time. Preliminary results indicate that the portable microperfusion system not only supports but optimizes cell growth, effectively adapting to changes in metabolic needs during the bioconstruct maturation process. This research opens perspectives in tissue engineering, demonstrating that a portable microperfusion system can be successfully integrated into 3D-printed bioconstructs, promoting sustainable and uniform cell growth. The implications of this study are far-reaching, with potential applications in regenerative medicine and pharmacological research, providing a platform for the development of functional and complex tissues.Keywords: biofabrication, microfluidic perfusion system, 4D bioprinting
Procedia PDF Downloads 8816 SCNet: A Vehicle Color Classification Network Based on Spatial Cluster Loss and Channel Attention Mechanism
Authors: Fei Gao, Xinyang Dong, Yisu Ge, Shufang Lu, Libo Weng
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Vehicle color recognition plays an important role in traffic accident investigation. However, due to the influence of illumination, weather, and noise, vehicle color recognition still faces challenges. In this paper, a vehicle color classification network based on spatial cluster loss and channel attention mechanism (SCNet) is proposed for vehicle color recognition. A channel attention module is applied to extract the features of vehicle color representative regions and reduce the weight of nonrepresentative color regions in the channel. The proposed loss function, called spatial clustering loss (SC-loss), consists of two channel-specific components, such as a concentration component and a diversity component. The concentration component forces all feature channels belonging to the same class to be concentrated through the channel cluster. The diversity components impose additional constraints on the channels through the mean distance coefficient, making them mutually exclusive in spatial dimensions. In the comparison experiments, the proposed method can achieve state-of-the-art performance on the public datasets, VCD, and VeRi, which are 96.1% and 96.2%, respectively. In addition, the ablation experiment further proves that SC-loss can effectively improve the accuracy of vehicle color recognition.Keywords: feature extraction, convolutional neural networks, intelligent transportation, vehicle color recognition
Procedia PDF Downloads 167815 A Mechanical Diagnosis Method Based on Vibration Fault Signal down-Sampling and the Improved One-Dimensional Convolutional Neural Network
Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui
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Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN
Procedia PDF Downloads 123814 Elucidation of the Sequential Transcriptional Activity in Escherichia coli Using Time-Series RNA-Seq Data
Authors: Pui Shan Wong, Kosuke Tashiro, Satoru Kuhara, Sachiyo Aburatani
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Functional genomics and gene regulation inference has readily expanded our knowledge and understanding of gene interactions with regards to expression regulation. With the advancement of transcriptome sequencing in time-series comes the ability to study the sequential changes of the transcriptome. This method presented here works to augment existing regulation networks accumulated in literature with transcriptome data gathered from time-series experiments to construct a sequential representation of transcription factor activity. This method is applied on a time-series RNA-Seq data set from Escherichia coli as it transitions from growth to stationary phase over five hours. Investigations are conducted on the various metabolic activities in gene regulation processes by taking advantage of the correlation between regulatory gene pairs to examine their activity on a dynamic network. Especially, the changes in metabolic activity during phase transition are analyzed with focus on the pagP gene as well as other associated transcription factors. The visualization of the sequential transcriptional activity is used to describe the change in metabolic pathway activity originating from the pagP transcription factor, phoP. The results show a shift from amino acid and nucleic acid metabolism, to energy metabolism during the transition to stationary phase in E. coli.Keywords: Escherichia coli, gene regulation, network, time-series
Procedia PDF Downloads 363813 Agile Methodology for Modeling and Design of Data Warehouses -AM4DW-
Authors: Nieto Bernal Wilson, Carmona Suarez Edgar
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The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects. Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.Keywords: data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse
Procedia PDF Downloads 396812 Gene Expression Profile Reveals Breast Cancer Proliferation and Metastasis
Authors: Nandhana Vivek, Bhaskar Gogoi, Ayyavu Mahesh
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Breast cancer metastasis plays a key role in cancer progression and fatality. The present study examines the potential causes of metastasis in breast cancer by investigating the novel interactions between genes and their pathways. The gene expression profile of GSE99394, GSE1246464, and GSE103865 was downloaded from the GEO data repository to analyze the differentially expressed genes (DEGs). Protein-protein interactions, target factor interactions, pathways and gene relationships, and functional enrichment networks were investigated. The proliferation pathway was shown to be highly expressed in breast cancer progression and metastasis in all three datasets. Gene Ontology analysis revealed 11 DEGs as gene targets to control breast cancer metastasis: LYN, DLGAP5, CXCR4, CDC6, NANOG, IFI30, TXP2, AGTR1, MKI67, and FTH1. Upon studying the function, genomic and proteomic data, and pathway involvement of the target genes, DLGAP5 proved to be a promising candidate due to it being highly differentially expressed in all datasets. The study takes a unique perspective on the avenues through which DLGAP5 promotes metastasis. The current investigation helps pave the way in understanding the role DLGAP5 plays in metastasis, which leads to an increased incidence of death among breast cancer patients.Keywords: genomics, metastasis, microarray, cancer
Procedia PDF Downloads 90811 Land Cover Remote Sensing Classification Advanced Neural Networks Supervised Learning
Authors: Eiman Kattan
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This study aims to evaluate the impact of classifying labelled remote sensing images conventional neural network (CNN) architecture, i.e., AlexNet on different land cover scenarios based on two remotely sensed datasets from different point of views such as the computational time and performance. Thus, a set of experiments were conducted to specify the effectiveness of the selected convolutional neural network using two implementing approaches, named fully trained and fine-tuned. For validation purposes, two remote sensing datasets, AID, and RSSCN7 which are publicly available and have different land covers features were used in the experiments. These datasets have a wide diversity of input data, number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in training, validation, and testing. As a result, the fully trained approach has achieved a trivial result for both of the two data sets, AID and RSSCN7 by 73.346% and 71.857% within 24 min, 1 sec and 8 min, 3 sec respectively. However, dramatic improvement of the classification performance using the fine-tuning approach has been recorded by 92.5% and 91% respectively within 24min, 44 secs and 8 min 41 sec respectively. The represented conclusion opens the opportunities for a better classification performance in various applications such as agriculture and crops remote sensing.Keywords: conventional neural network, remote sensing, land cover, land use
Procedia PDF Downloads 357810 Observer-Based Leader-Following Consensus of Nonlinear Fractional-Order Multi-Agent Systems
Authors: Ali Afaghi, Sehraneh Ghaemi
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The coordination of the multi-agent systems has been one of the interesting topic in recent years, because of its potential applications in many branches of science and engineering such as sensor networks, flocking, underwater vehicles and etc. In the most of the related studies, it is assumed that the dynamics of the multi-agent systems are integer-order and linear and the multi-agent systems with the fractional-order nonlinear dynamics are rarely considered. However many phenomena in nature cannot be described within integer-order and linear characteristics. This paper investigates the leader-following consensus problem for a class of nonlinear fractional-order multi-agent systems based on observer-based cooperative control. In the system, the dynamics of each follower and leader are nonlinear. For a multi-agent system with fixed directed topology firstly, an observer-based consensus protocol is proposed based on the relative observer states of neighboring agents. Secondly, based on the property of the stability theory of fractional-order system, some sufficient conditions are presented for the asymptotical stability of the observer-based fractional-order control systems. The proposed method is applied on a five-agent system with the fractional-order nonlinear dynamics and unavailable states. The simulation example shows that the proposed scenario results in the good performance and can be used in many practical applications.Keywords: fractional-order multi-agent systems, leader-following consensus, nonlinear dynamics, directed graphs
Procedia PDF Downloads 385809 Formal Implementation of Routing Information Protocol Using Event-B
Authors: Jawid Ahmad Baktash, Tadashi Shiroma, Tomokazu Nagata, Yuji Taniguchi, Morikazu Nakamura
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The goal of this paper is to explore the use of formal methods for Dynamic Routing, The purpose of network communication with dynamic routing is sending a massage from one node to others by using pacific protocols. In dynamic routing connections are possible based on protocols of Distance vector (Routing Information Protocol, Border Gateway protocol), Link State (Open Shortest Path First, Intermediate system Intermediate System), Hybrid (Enhanced Interior Gateway Routing Protocol). The responsibility for proper verification becomes crucial with Dynamic Routing. Formal methods can play an essential role in the Routing, development of Networks and testing of distributed systems. Event-B is a formal technique consists of describing rigorously the problem; introduce solutions or details in the refinement steps to obtain more concrete specification, and verifying that proposed solutions are correct. The system is modeled in terms of an abstract state space using variables with set theoretic types and the events that modify state variables. Event-B is a variant of B, was designed for developing distributed systems. In Event-B, the events consist of guarded actions occurring spontaneously rather than being invoked. The invariant state properties must be satisfied by the variables and maintained by the activation of the events.Keywords: dynamic rout RIP, formal method, event-B, pro-B
Procedia PDF Downloads 395808 Critical Factors in the Formation, Development and Survival of an Eco-Industrial Park: A Systemic Understanding of Industrial Symbiosis
Authors: Iván González, Pablo Andrés Maya, Sebastián Jaén
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Eco-industrial parks (EIPs) work as networks for the exchange of by-products, such as materials, water, or energy. This research identifies the relevant factors in the formation of EIPs in different industrial environments around the world. Then an aggregation of these factors is carried out to reduce them from 50 to 17 and classify them according to 5 fundamental axes. Subsequently, the Vester Sensitivity Model (VSM) systemic methodology is used to determine the influence of the 17 factors on an EIP system and the interrelationship between them. The results show that the sequence of effects between factors: Trust and Cooperation → Business Association → Flows → Additional Income represents the “backbone” of the system, being the most significant chain of influences. In addition, the Organizational Culture represents the turning point of the Industrial Symbiosis on which it must act correctly to avoid falling into unsustainable economic development. Finally, the flow of Information should not be lost since it is what feeds trust between the parties, and the latter strengthens the system in the face of individual or global imbalances. This systemic understanding will enable the formulation of pertinent policies by the actors that interact in the formation and permanence of the EIP. In this way, it seeks to promote large-scale sustainable industrial development, integrating various community actors, which in turn will give greater awareness and appropriation of the current importance of sustainability in industrial production.Keywords: critical factors, eco-industrial park, industrial symbiosis, system methodology
Procedia PDF Downloads 110807 Energy Efficient Microgrid Design with Hybrid Power Systems
Authors: Pedro Esteban
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Today’s electrical networks, including microgrids, are evolving into smart grids. The smart grid concept brings the idea that the power comes from various sources (continuous or intermittent), in various forms (AC or DC, high, medium or low voltage, etc.), and it must be integrated into the electric power system in a smart way to guarantee a continuous and reliable supply that complies with power quality and energy efficiency standards and grid code requirements. This idea brings questions for the different players like how the required power will be generated, what kind of power will be more suitable, how to store exceeding levels for short or long-term usage, and how to combine and distribute all the different generation power sources in an efficient way. To address these issues, there has been lots of development in recent years on the field of on-grid and off-grid hybrid power systems (HPS). These systems usually combine one or more modes of electricity generation together with energy storage to ensure optimal supply reliability and high level of energy security. Hybrid power systems combine power generation and energy storage technologies together with real-time energy management and innovative power quality and energy efficiency improvement functionalities. These systems help customers achieve targets for clean energy generation, they add flexibility to the electrical grid, and they optimize the installation by improving its power quality and energy efficiency.Keywords: microgrids, hybrid power systems, energy storage, power quality improvement
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