Search results for: wireless network security
2002 Aligning Cultural Practices through Information Exchange: A Taxonomy in Global Manufacturing Industry
Authors: Hung Nguyen
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With the rise of global supply chain network, the choice of supply chain orientation is critical. The alignment between cultural similarity and supply chain information exchange could help identify appropriate supply chain orientations, which would differentiate the stronger competitors and performers from the weaker ones. Through developing a taxonomy, this study examined whether the choices of action programs and manufacturing performance differ depending on the levels of attainment cultural similarity and information exchange. This study employed statistical tests on a large-scale dataset consisting of 680 manufacturing plants from various cultures and industries. Firms need to align cultural practices with the level of information exchange in order to achieve good overall business performance. There appeared to be consistent three major orientations: the Proactive, the Initiative and the Reactive. Firms are experiencing higher payoffs from various improvements are the ones successful alignment in both information exchange and cultural similarity The findings provide step-by-step decision making for supply chain information exchange and offer guidance especially for global supply chain managers. In including both cultural similarity and information exchange, this paper adds greater comprehensiveness and richness to the supply chain literature.Keywords: culture, information exchange, supply chain orientation, similarity
Procedia PDF Downloads 3572001 Leasing Revisited: Mastering the Digital Transformation with Traditional Financing
Authors: Tobias Huttche, Marco Canipa-Valdez, Corinne Mühlebach
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This article discusses the role of leasing on the digital transformation process of companies and corresponding economic effects. Based on the traditional mechanisms of leasing, this article focuses in particular on the benefits of leasing as financing instrument with regard to the innovation potential of companies. Practical examples demonstrate how leasing can become an integral part of new business models. Especially, with regard to the digital transformation and corresponding investments in know-how and infrastructure, leasing can play an important role. Furthermore, findings of an empirical survey are presented dealing with the usage of leasing in Switzerland in an international context. The survey shows not only the benefits of leasing against the backdrop of digital transformation but gives guidance on how other countries can benefit from promoting leasing in their legislation and economy. Based on a simulation model for Switzerland, the economic effect of an increase in leasing volume is being calculated. Again, the respective results underline the substantial growth potential. This holds true especially for economies where asset-based lending is rarely used because of a lack of entrepreneurial or private security of the borrower (cash-based financing for developing and emerging countries). Overall, the authors found that leasing using companies are more productive and tend to grow faster than companies using less or none leasing. The positive effects of leasing on emerging digital challenges for companies and entire economies should encourage other countries to facilitate access to leasing as financing instrument by decreasing legal-, tax- and accounting-related requirements in the respective jurisdiction.Keywords: Cash-Based financing, digital transformation, financing instruments, growth, innovation, leasing
Procedia PDF Downloads 2552000 Ophthalmic Hashing Based Supervision of Glaucoma and Corneal Disorders Imposed on Deep Graphical Model
Authors: P. S. Jagadeesh Kumar, Yang Yung, Mingmin Pan, Xianpei Li, Wenli Hu
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Glaucoma is impelled by optic nerve mutilation habitually represented as cupping and visual field injury frequently with an arcuate pattern of mid-peripheral loss, subordinate to retinal ganglion cell damage and death. Glaucoma is the second foremost cause of blindness and the chief cause of permanent blindness worldwide. Consequently, all-embracing study into the analysis and empathy of glaucoma is happening to escort deep learning based neural network intrusions to deliberate this substantial optic neuropathy. This paper advances an ophthalmic hashing based supervision of glaucoma and corneal disorders preeminent on deep graphical model. Ophthalmic hashing is a newly proposed method extending the efficacy of visual hash-coding to predict glaucoma corneal disorder matching, which is the faster than the existing methods. Deep graphical model is proficient of learning interior explications of corneal disorders in satisfactory time to solve hard combinatoric incongruities using deep Boltzmann machines.Keywords: corneal disorders, deep Boltzmann machines, deep graphical model, glaucoma, neural networks, ophthalmic hashing
Procedia PDF Downloads 2491999 Islamic Credit Risk Management in Murabahah Financing: The Study of Islamic Banking in Malaysia
Authors: Siti Nor Amira Bt. Mohamad, Mohamad Yazis B. Ali Basah, Muhammad Ridhwan B. Ab. Aziz, Khairil Faizal B. Khairi, Mazlynda Bt. Md. Yusuf, Hisham B. Sabri
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The understanding of risk and the concept of it occurs associated in Islamic financing was well-known in the financial industry by the using of Profit-and-Loss Sharing (PLS). It was presently in any Islamic financial transactions in order to comply with shariah rules. However, the existence of risk in Murabahah contract of financing is an ability that the counterparty is unable to complete its obligations within the agreed terms. Therefore, it is called as credit or default risk. Credit risk occurs when the client fails to make timely payment after the bank makes complete delivery of assets. Thus, it affects the growth of the bank as the banking business is in no position to have appropriate measures to cover the risk. Therefore, the bank may impose penalty on the outstanding balance. This paper aims to highlight the credit risk determinant and issues surrounding in Islamic bank in Malaysia in terms of Murabahah financing and how to manage it by using the proper techniques. Finally, it explores the credit risk management concept that might solve the problems arise. The study found that the credit risk can be managed properly by improving the use of comprehensive reference checklist of business partners on their character and past performance as well as their comprehensive database. Besides that, prevention of credit risk can be done by using collateral as security against the risk and we also argue on the Shariah guidelines and procedures should be implement coherently by the banking business because so that the risk would be control by having an effective instrument for Islamic modes of financing.Keywords: Islamic banking, credit risk, Murabahah financing, risk mitigation
Procedia PDF Downloads 4541998 AI-Based Autonomous Plant Health Monitoring and Control System with Visual Health-Scoring Models
Authors: Uvais Qidwai, Amor Moursi, Mohamed Tahar, Malek Hamad, Hamad Alansi
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This paper focuses on the development and implementation of an advanced plant health monitoring system with an AI backbone and IoT sensory network. Our approach involves addressing the critical environmental factors essential for preserving a plant’s well-being, including air temperature, soil moisture, soil temperature, soil conductivity, pH, water levels, and humidity, as well as the presence of essential nutrients like nitrogen, phosphorus, and potassium. Central to our methodology is the utilization of computer vision technology, particularly a night vision camera. The captured data is then compared against a reference database containing different health statuses. This comparative analysis is implemented using an AI deep learning model, which enables us to generate accurate assessments of plant health status. By combining the AI-based decision-making approach, our system aims to provide precise and timely insights into the overall health and well-being of plants, offering a valuable tool for effective plant care and management.Keywords: deep learning image model, IoT sensing, cloud-based analysis, remote monitoring app, computer vision, fuzzy control
Procedia PDF Downloads 531997 The Impact of Artificial Intelligence on Human Rights Legislations and Evolution
Authors: Nawal Yacoub Halim Abdelmasih
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The intersection between development and human rights has been the factor of scholarly debate for a long term. therefore, some of standards, which enlarge from the proper to development to the human rights-based totally method to development, had been adopted to apprehend the dynamics among the two standards. no matter these attempts, the exact relationship among improvement and human rights has not been completely determined but. however, the inevitable interdependence between the two notions and the idea that improvement efforts ought to be undertaken with the aid of giving due regard to human rights ensures has won momentum in recent years. then again, the emergence of sustainable development as a extensively common technique in development dreams and policies makes this unsettled convergence even extra complicated. The vicinity of sustainable improvement in human rights regulation discourse and the function of the latter in making sure the sustainability of development applications name for a scientific observe. as a result, this newsletter seeks to discover the relationship among development and human rights, particularly focusing at the location given to sustainable development principles in international human proper regulation. it'll similarly quest whether or not there is a proper to sustainable improvement diagnosed therein. as a result, the item asserts that the ideas of sustainable improvement are immediately or circuitously diagnosed in diverse human rights contraptions, which affords an affirmative response to the question raised hereinabove. This paintings, therefore, will make expeditions via international and regional human rights devices in addition to case legal guidelines and interpretative hints of human rights bodies to show this speculation.Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security
Procedia PDF Downloads 291996 A Bayesian Network Approach to Customer Loyalty Analysis: A Case Study of Home Appliances Industry in Iran
Authors: Azam Abkhiz, Abolghasem Nasir
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To achieve sustainable competitive advantage in the market, it is necessary to provide and improve customer satisfaction and Loyalty. To reach this objective, companies need to identify and analyze their customers. Thus, it is critical to measure the level of customer satisfaction and Loyalty very carefully. This study attempts to build a conceptual model to provide clear insights of customer loyalty. Using Bayesian networks (BNs), a model is proposed to evaluate customer loyalty and its consequences, such as repurchase and positive word-of-mouth. BN is a probabilistic approach that predicts the behavior of a system based on observed stochastic events. The most relevant determinants of customer loyalty are identified by the literature review. Perceived value, service quality, trust, corporate image, satisfaction, and switching costs are the most important variables that explain customer loyalty. The data are collected by use of a questionnaire-based survey from 1430 customers of a home appliances manufacturer in Iran. Four scenarios and sensitivity analyses are performed to run and analyze the impact of different determinants on customer loyalty. The proposed model allows businesses to not only set their targets but proactively manage their customer behaviors as well.Keywords: customer satisfaction, customer loyalty, Bayesian networks, home appliances industry
Procedia PDF Downloads 1381995 A Systematic Mapping of the Use of Information and Communication Technology (ICT)-Based Remote Agricultural Extension for Women Smallholders
Authors: Busiswa Madikazi
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This systematic mapping study explores the underrepresentation of women's contributions to farming in the Global South within the development of Information and Communication Technologies (ICT)-based extension methods. Despite women farmers constituting 70% of the agricultural labour force, their productivity is hindered by various constraints, including illiteracy, household commitments, and limited access to credit and markets. A systematic mapping approach was employed with the aim of identifying evidence gaps in existing ICT extension for women farmers. The data collection protocol follows a structured approach, incorporating key criteria for inclusion, exclusion, search strategy, and coding and the PICO strategy (Population, Intervention, Comparator, and Outcome). The results yielded 119 articles that qualified for inclusion. The findings highlight that mobile phone apps (WhatsApp) and radio/television programming are the primary extension methods employed while integrating ICT with training, field visits, and demonstrations are underutilized. Notably, the study emphasizes the inadequate attention to critical issues such as food security, gender equality, and attracting youth to farming within ICT extension efforts. These findings indicate a significant policy and practice gap, neglecting community-driven approaches that cater to women's specific needs and enhance their agricultural production. Map highlights the importance of refocusing ICT extension efforts to address women farmers’ unique challenges, thereby contributing to their empowerment and improving agricultural practices.Keywords: agricultural extension, ICT, women farmers, smallholders
Procedia PDF Downloads 601994 Risk Analysis of Leaks from a Subsea Oil Facility Based on Fuzzy Logic Techniques
Authors: Belén Vinaixa Kinnear, Arturo Hidalgo López, Bernardo Elembo Wilasi, Pablo Fernández Pérez, Cecilia Hernández Fuentealba
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The expanded use of risk assessment in legislative and corporate decision-making has increased the role of expert judgement in giving data for security-related decision-making. Expert judgements are required in most steps of risk assessment: danger recognizable proof, hazard estimation, risk evaluation, and examination of choices. This paper presents a fault tree analysis (FTA), which implies a probabilistic failure analysis applied to leakage of oil in a subsea production system. In standard FTA, the failure probabilities of items of a framework are treated as exact values while evaluating the failure probability of the top event. There is continuously insufficiency of data for calculating the failure estimation of components within the drilling industry. Therefore, fuzzy hypothesis can be used as a solution to solve the issue. The aim of this paper is to examine the leaks from the Zafiro West subsea oil facility by using fuzzy fault tree analysis (FFTA). As a result, the research has given theoretical and practical contributions to maritime safety and environmental protection. It has been also an effective strategy used traditionally in identifying hazards in nuclear installations and power industries.Keywords: expert judgment, probability assessment, fault tree analysis, risk analysis, oil pipelines, subsea production system, drilling, quantitative risk analysis, leakage failure, top event, off-shore industry
Procedia PDF Downloads 1901993 Conceptual Model Providing More Information on the Contact Situation between Crime Victim and the Police
Authors: M. Inzunza
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In contemporary society, victims of crime has been given more recognition, which have contributed to advancing the knowledge on the effects of crime. There exists a complexity of who gets the status of victim and that the typology of good versus bad can interfere with the contact situation of the victim with the police. The aim of this study is to identify the most central areas affecting the contact situation between crime victims and the police to develop a conceptual model to be useful empirically. By considering previously documented problem areas and different theoretical domains, a conceptual model has been developed. Preliminary findings suggest that an area that should be given attention is to get a better understanding of the victim, not only in terms of demographics but also in terms of risk behavior and social network. This area has been considered to influence the status of the crime victim. Another domain of value is the type of crime and the context of the incident in more detail. The police officer approach style in the contact situation is also a pertinent area that is influenced by how the police based victim services are organized and how individual police officers are suited for the mission. Suitability includes constructs from empathy models adapted to the police context and especially focusing on sub-constructs such as perspective taking. Discussion will focus on how these findings can be operationalized in practice and how they are used in ongoing empirical studies.Keywords: empathy, perspective taking, police contact, victim of crime
Procedia PDF Downloads 1361992 Study of Self-Assembled Photocatalyst by Metal-Terpyridine Interactions in Polymer Network
Authors: Dong-Cheol Jeong, Jookyung Lee, Yu Hyeon Ro, Changsik Song
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The design and synthesis of photo-active polymeric systems are important in regard to solar energy harvesting and utilization. In this study, we synthesized photo-active polymer, thin films, and polymer gel via iterative self-assembly using reversible metal-terpyridine (M-tpy) interactions. The photocurrent generated in the polymeric thin films with Zn(II) was much higher than those of other films. Apparent diffusion rate constant (kapp) was measured for the electron hopping process via potential-step chronoamperometry. As a result, the kapp for the polymeric thin films with Zn(II) was almost two times larger than those with other metal ions. We found that the anodic photocurrents increased with the inclusion of the multi-walled carbon nanotube (MWNT) layer. Inclusion of MWNTs can provide efficient electron transfer pathways. In addition, polymer gel based on interactions between terpyridine and metal ions was shown the photocatalytic activity. Interestingly, in the Mg-terpyridine gel, the reaction rate of benzylamine to imine photo-oxidative coupling was faster than Fe-terpyridine gel because the Mg-terpyridine gel has two steps electron transfer pathway but Fe-terpyridine gel has three steps electron transfer pathway.Keywords: terpyridine, photocatalyst, self-assebly, metal-ligand
Procedia PDF Downloads 3081991 Exploring the Dynamics in the EU-Association of Southeast Asia Nations Interregional Relationship, 2012-2017
Authors: Xuechen Chen
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The EU-ASEAN relations which can be dated back to 1972 represents one of the oldest group-to-group relationship in international politics. Despite a longstanding dialogue partnership, the EU and ASEAN have long been reluctant to forge deeper and substantial cooperation in political and security domains. However, the year of 2012 witnessed a salient shift in EU-ASEAN relations, with the EU significantly elevating ASEAN's profile in its external relations. Given the limited scholarly attention that has been devoted to this change in ASEAN-EU relations, this article explores why there has been a greater level of engagement and approximation between the EU and ASEAN. In particular, it asks why the EU, which had long been reluctant to recognize ASEAN as a strategic partner, has changed its policy towards ASEAN. Drawing on social constructivism, this article argues that the EU’s and ASEAN’s evolving identity-formation processes have played a significant role in reshaping their mutual perceptions, which subsequently leads to the modification of the interregional policies of both actors. The methodology of this study is based on content analysis of a wide range of official documents and policy papers from the EU and ASEAN, as well as more than 20 in-depth elite interviews with diplomats and experts working on the EU-ASEAN relationship from both organisations. Departing from the existing works which mainly adopt a Eurocentric perspective when analysing the EU-ASEAN interregionalism, this study suggests that the approximation of the EU-ASEAN relationship between 2012 and 2017 is driven by both actors’ adjustment of international identities, together with the internal dynamics and systematic changes within both regions.Keywords: Association of Southeast Asia Nations, European Union, EU foreign policy, interregionalism
Procedia PDF Downloads 1451990 Identifying Metabolic Pathways Associated with Neuroprotection Mediated by Tibolone in Human Astrocytes under an Induced Inflammatory Model
Authors: Daniel Osorio, Janneth Gonzalez, Andres Pinzon
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In this work, proteins and metabolic pathways associated with the neuroprotective response mediated by the synthetic neurosteroid tibolone under a palmitate-induced inflammatory model were identified by flux balance analysis (FBA). Three different metabolic scenarios (‘healthy’, ‘inflamed’ and ‘medicated’) were modeled over a gene expression data-driven constructed tissue-specific metabolic reconstruction of mature astrocytes. Astrocyte reconstruction was built, validated and constrained using three open source software packages (‘minval’, ‘g2f’ and ‘exp2flux’) released through the Comprehensive R Archive Network repositories during the development of this work. From our analysis, we predict that tibolone executes their neuroprotective effects through a reduction of neurotoxicity mediated by L-glutamate in astrocytes, inducing the activation several metabolic pathways with neuroprotective actions associated such as taurine metabolism, gluconeogenesis, calcium and the Peroxisome Proliferator Activated Receptor signaling pathways. Also, we found a tibolone associated increase in growth rate probably in concordance with previously reported side effects of steroid compounds in other human cell types.Keywords: astrocytes, flux balance analysis, genome scale metabolic reconstruction, inflammation, neuroprotection, tibolone
Procedia PDF Downloads 2221989 A Machine Learning Approach for Intelligent Transportation System Management on Urban Roads
Authors: Ashish Dhamaniya, Vineet Jain, Rajesh Chouhan
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Traffic management is one of the gigantic issue in most of the urban roads in al-most all metropolitan cities in India. Speed is one of the critical traffic parameters for effective Intelligent Transportation System (ITS) implementation as it decides the arrival rate of vehicles on an intersection which are majorly the point of con-gestions. The study aimed to leverage Machine Learning (ML) models to produce precise predictions of speed on urban roadway links. The research objective was to assess how categorized traffic volume and road width, serving as variables, in-fluence speed prediction. Four tree-based regression models namely: Decision Tree (DT), Random Forest (RF), Extra Tree (ET), and Extreme Gradient Boost (XGB)are employed for this purpose. The models' performances were validated using test data, and the results demonstrate that Random Forest surpasses other machine learning techniques and a conventional utility theory-based model in speed prediction. The study is useful for managing the urban roadway network performance under mixed traffic conditions and effective implementation of ITS.Keywords: stream speed, urban roads, machine learning, traffic flow
Procedia PDF Downloads 691988 Evolution and Obstacles Encountered in the Realm of Sports Tourism in Pakistan
Authors: Muhammad Saleem
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Tourism stands as one of the swiftly expanding sectors globally, contributing to 10% of the overall worldwide GDP. It holds a vital role in generating income, fostering employment opportunities, alleviating poverty, facilitating foreign exchange earnings, and advancing intercultural understanding. This industry encompasses a spectrum of activities, encompassing transportation, communication, hospitality, catering, entertainment, and advertising. The objective of this study is to assess the evolution and obstacles encountered by sports tourism in Pakistan. In pursuit of this objective, relevant literature has been scrutinized, while data has been acquired from 60 respondents, employing a simple random sampling approach for analysis. The survey comprised close-ended inquiries directed towards all participants. Analytical tools such as mean, mode, median, graphs, and percentages have been employed for data analysis. The findings revealed through robust analysis, indicate that the mean, mode, and median tools consistently yield results surpassing the 70% mark, underscoring that heightened development within sports tourism significantly augments its progress. Effective governance demonstrates a favorable influence on sports tourism, with increased government-provided safety and security potentially amplifying its expansion, thus attracting a higher number of tourists and consequently propelling the growth of the sports tourism sector. This study holds substantial significance for both academic scholars and industry practitioners within Pakistan's tourism landscape, as previous explorations in this realm have been relatively limited.Keywords: obstacles-spots, evolution-tourism, sports-pakistan, sports-obstacles-pakistan
Procedia PDF Downloads 541987 Spontaneous and Posed Smile Detection: Deep Learning, Traditional Machine Learning, and Human Performance
Authors: Liang Wang, Beste F. Yuksel, David Guy Brizan
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A computational model of affect that can distinguish between spontaneous and posed smiles with no errors on a large, popular data set using deep learning techniques is presented in this paper. A Long Short-Term Memory (LSTM) classifier, a type of Recurrent Neural Network, is utilized and compared to human classification. Results showed that while human classification (mean of 0.7133) was above chance, the LSTM model was more accurate than human classification and other comparable state-of-the-art systems. Additionally, a high accuracy rate was maintained with small amounts of training videos (70 instances). The derivation of important features to further understand the success of our computational model were analyzed, and it was inferred that thousands of pairs of points within the eyes and mouth are important throughout all time segments in a smile. This suggests that distinguishing between a posed and spontaneous smile is a complex task, one which may account for the difficulty and lower accuracy of human classification compared to machine learning models.Keywords: affective computing, affect detection, computer vision, deep learning, human-computer interaction, machine learning, posed smile detection, spontaneous smile detection
Procedia PDF Downloads 1241986 A Different Approach to Smart Phone-Based Wheat Disease Detection System Using Deep Learning for Ethiopia
Authors: Nathenal Thomas Lambamo
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Based on the fact that more than 85% of the labor force and 90% of the export earnings are taken by agriculture in Ethiopia and it can be said that it is the backbone of the overall socio-economic activities in the country. Among the cereal crops that the agriculture sector provides for the country, wheat is the third-ranking one preceding teff and maize. In the present day, wheat is in higher demand related to the expansion of industries that use them as the main ingredient for their products. The local supply of wheat for these companies covers only 35 to 40% and the rest 60 to 65% percent is imported on behalf of potential customers that exhaust the country’s foreign currency reserves. The above facts show that the need for this crop in the country is too high and in reverse, the productivity of the crop is very less because of these reasons. Wheat disease is the most devastating disease that contributes a lot to this unbalance in the demand and supply status of the crop. It reduces both the yield and quality of the crop by 27% on average and up to 37% when it is severe. This study aims to detect the most frequent and degrading wheat diseases, Septoria and Leaf rust, using the most efficiently used subset of machine learning technology, deep learning. As a state of the art, a deep learning class classification technique called Convolutional Neural Network (CNN) has been used to detect diseases and has an accuracy of 99.01% is achieved.Keywords: septoria, leaf rust, deep learning, CNN
Procedia PDF Downloads 741985 An Adaptive Neuro-Fuzzy Inference System (ANFIS) Modelling of Bleeding
Authors: Seyed Abbas Tabatabaei, Fereydoon Moghadas Nejad, Mohammad Saed
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The bleeding prediction of the asphalt is one of the most complex subjects in the pavement engineering. In this paper, an Adaptive Neuro Fuzzy Inference System (ANFIS) is used for modeling the effect of important parameters on bleeding is trained and tested with the experimental results. bleeding index based on the asphalt film thickness differential as target parameter,asphalt content, temperature depth of two centemeter, heavy traffic, dust to effective binder, Marshall strength, passing 3/4 sieves, passing 3/8 sieves,passing 3/16 sieves, passing NO8, passing NO50, passing NO100, passing NO200 as input parameters. Then, we randomly divided empirical data into train and test sections in order to accomplish modeling. We instructed ANFIS network by 72 percent of empirical data. 28 percent of primary data which had been considered for testing the approprativity of the modeling were entered into ANFIS model. Results were compared by two statistical criterions (R2, RMSE) with empirical ones. Considering the results, it is obvious that our proposed modeling by ANFIS is efficient and valid and it can also be promoted to more general states.Keywords: bleeding, asphalt film thickness differential, Anfis Modeling
Procedia PDF Downloads 2691984 Hydroinformatics of Smart Cities: Real-Time Water Quality Prediction Model Using a Hybrid Approach
Authors: Elisa Coraggio, Dawei Han, Weiru Liu, Theo Tryfonas
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Water is one of the most important resources for human society. The world is currently undergoing a wave of urban growth, and pollution problems are of a great impact. Monitoring water quality is a key task for the future of the environment and human species. In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for environmental monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the artificial intelligence algorithm. This study derives the methodology and demonstrates its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for the environment monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a new methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the Artificial Intelligence algorithm. This study derives the methodology and demonstrate its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.Keywords: artificial intelligence, hydroinformatics, numerical modelling, smart cities, water quality
Procedia PDF Downloads 1851983 Experiences of Marital Relationship of Middle-Aged Couples in Hong Kong: Implications for Services Interventions
Authors: Wai M. Shum
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There was evidence that the change of marital quality satisfaction was related to the different stages of the family life cycle. Research studies have been largely based on western contexts, which found a curvilinear U-shaped trend in changes of marital satisfaction over the course of a marriage, but little is known about the marital experiences of Hong Kong couples. Through in-depth interviews, this qualitative study explored the marital relationship of middle-aged couples in a satisfying marriage and to identify how couples maintain a satisfying relationship in the local context. Findings from this study suggested twelve themes with some showing consistency with previous literature, such as communication, companionship, trust, and fidelity. The affective aspects of empathetic understanding and perceived empathy were found to have an enormous effect on couples’ bondedness. The high level of differentiation and security served as a basis for unconditional contribution, acceptance, and adjustment to unsolvable issues such that negative emotion would not be escalated. The manifestations of intimacy and commitment in the triangular theory of love were more frequently addressed than passion in striving for marital longevity in the local context. This study challenged the curvilinear trend of marital satisfaction throughout marriage, with couples showing different pathways of marital satisfaction. The study gave insights on martial enrichment, such as facilitating couples to disclose their vulnerabilities, desire for physical intimacy, and passion in the pursuit of enduring marriage instead of an emphasis on skills training on communication and conflict resolution.Keywords: intimacy, marital relationship, marital satisfaction, middle-aged
Procedia PDF Downloads 1131982 Diversification of Sweet Potato Blends and Utilization for Malnutrition and Poverty Alleviation
Authors: Ladele Ademola A., Nkiru T. Meludu, Olufunke Ezekiel, Olaoye Taye F., Okanlowan Oluwatoyin M.
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Value addition to agricultural produce is of possible potential in reducing poverty, improving food security and malnutrition, therefore the need to develop small and micro-enterprises of sweet potato production. The study was carried out in Nigeria to determine the acceptability of blends sweet potato (Ipomea batatas) and commodities yellow maize (Zea mays), millet (Pennisetum glaucum), soybean (Glycine max), bambara groundnut (Vigna subterranean), guinea corn (Sorghum vulgare), wheat (Triticum aestivum), and roselle (Hibiscus sabdariffa) through sensory evaluation. Sweet potato (Ipomea batatas) roots were processed using two methods. The first method involved the use of a fabricated gas powered cabinet dryer to dry sulphited chips and the second method was the use of traditional sun drying method without the addition of the chemical. The blends were also assessed in terms of functional, chemical and color properties. Most acceptable blends include BAW (80:20 of sweet potato/wheat), BBC (80:20 of sweet potato/guinea corn), AAB (60:40 of sweet potato/guinea corn), YTE (100% soybean), TYG (100% sweet potato), KTN (100% wheat flour), XGP (80:20 of sweet potato/soybean), XAX (60:40 of sweet potato/wheat), LSS (100% Roselle), CHK (100% Guinea corn), and ABC (60:40% of sweet potato/ yellow maize). In addition, chemical analysis carried out revealed that sweet potato has high percentage of vitamins A and C, potassium (K), manganese (Mn), calcium (Ca), magnesium (Mg) and iron (Fe) and fibre content. There is also an increase of vitamin A and Iron in the blended products.Keywords: blends, diversification, sensory evaluation, sweet potato, utilization
Procedia PDF Downloads 5051981 Urban Citizenship in a Sensor Rich Society
Authors: Mike Dee
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Urban public spaces are sutured with a range of surveillance and sensor technologies that claim to enable new forms of ‘data based citizen participation’, but also increase the tendency for ‘function-creep’, whereby vast amounts of data are gathered, stored and analysed in a broad application of urban surveillance. This kind of monitoring and capacity for surveillance connects with attempts by civic authorities to regulate, restrict, rebrand and reframe urban public spaces. A direct consequence of the increasingly security driven, policed, privatised and surveilled nature of public space is the exclusion or ‘unfavourable inclusion’ of those considered flawed and unwelcome in the ‘spectacular’ consumption spaces of many major urban centres. In the name of urban regeneration, programs of securitisation, ‘gentrification’ and ‘creative’ and ‘smart’ city initiatives refashion public space as sites of selective inclusion and exclusion. In this context of monitoring and control procedures, in particular, children and young people’s use of space in parks, neighbourhoods, shopping malls and streets is often viewed as a threat to the social order, requiring various forms of remedial action. This paper suggests that cities, places and spaces and those who seek to use them, can be resilient in working to maintain and extend democratic freedoms and processes enshrined in Marshall’s concept of citizenship, calling sensor and surveillance systems to account. Such accountability could better inform the implementation of public policy around the design, build and governance of public space and also understandings of urban citizenship in the sensor saturated urban environment.Keywords: citizenship, public space, surveillance, young people
Procedia PDF Downloads 4481980 Plasma Properties Effect on Fluorescent Tube Plasma Antenna Performance
Authors: A. N. Dagang, E. I. Ismail, Z. Zakaria
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This paper presents the analysis on the performance of monopole antenna with fluorescent tubes. In this research, the simulation and experimental approach is conducted. The fluorescent tube with different length and size is designed using Computer Simulation Technology (CST) software and the characteristics of antenna parameter are simulated throughout the software. CST was used to simulate antenna parameters such as return loss, resonant frequency, gain and directivity. Vector Network Analyzer (VNA) was used to measure the return loss of plasma antenna in order to validate the simulation results. In the simulation and experiment, the supply frequency is set starting from 1 GHz to 10 GHz. The results show that the return loss of plasma antenna changes when size of fluorescent tubes is varied, correspond to the different plasma properties. It shows that different values of plasma properties such as plasma frequency and collision frequency gives difference result of return loss, gain and directivity. For the gain, the values range from 2.14 dB to 2.36 dB. The return loss of plasma antenna offers higher value range from -22.187 dB to -32.903 dB. The higher the values of plasma frequency and collision frequency, the higher return loss can be obtained. The values obtained are comparative to the conventional type of metal antenna.Keywords: plasma antenna, fluorescent tube, CST, plasma parameters
Procedia PDF Downloads 3851979 A Review of Current Trends in Grid Balancing Technologies
Authors: Kulkarni Rohini D.
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While emerging as plausible sources of energy generation, new technologies, including photovoltaic (PV) solar panels, home battery energy storage systems, and electric vehicles (EVs), are exacerbating the operations of power distribution networks for distribution network operators (DNOs). Renewable energy production fluctuates, stemming in over- and under-generation energy, further complicating the issue of storing excess power and using it when necessary. Though renewable sources are non-exhausting and reoccurring, power storage of generated energy is almost as paramount as to its production process. Hence, to ensure smooth and efficient power storage at different levels, Grid balancing technologies are consequently the next theme to address in the sustainable space and growth sector. But, since hydrogen batteries were used in the earlier days to achieve this balance in power grids, new, recent advancements are more efficient and capable per unit of storage space while also being distinctive in terms of their underlying operating principles. The underlying technologies of "Flow batteries," "Gravity Solutions," and "Graphene Batteries" already have entered the market and are leading the race for efficient storage device solutions that will improve and stabilize Grid networks, followed by Grid balancing technologies.Keywords: flow batteries, grid balancing, hydrogen batteries, power storage, solar
Procedia PDF Downloads 691978 Superior Wear Performance of CoCrNi Matrix Composite Reinforced with Quasi-Continuously Networked Graphene Nanosheets and In-Situ Carbide
Authors: Wenting Ye
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The biological materials evolved in nature generally exhibit interpenetrating network structures, which may offer useful inspiration for the architectural design of wear-resistant composites. Here, a strategy for designing self-lubricating medium entropy alloy (MEA) composites with high strength and excellent anti-wear performance was proposed through quasi-continuously networked in-situ carbides and graphene nanosheets. The discontinuous coating of graphene on the MEA powder surface inhibits continuous metallurgy bonding of the MEA powders during sintering, generating the typical quasi-continuously networked architecture. A good combination of mechanical properties with high fracture strength over 2 GPa and large compressive plasticity over 30% benefits from metallurgy bonding that prevents crack initiation and extension. The wear rate of an order of 10-6 m3N-1m-1 ascribing to an amorphous-crystalline nanocomposite surface, tribo-film induced by graphene, as well as the gradient worn subsurface during friction was achieved by the MEA composite, which is an order of magnitude lower than the unreinforced MEA matrix.Keywords: in-situ carbide, tribological behavior, medium entropy alloy matrix composite, graphene
Procedia PDF Downloads 311977 Neural Networks for Distinguishing the Performance of Two Hip Joint Implants on the Basis of Hip Implant Side and Ground Reaction Force
Authors: L. Parisi
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In this research work, neural networks were applied to classify two types of hip joint implants based on the relative hip joint implant side speed and three components of each ground reaction force. The condition of walking gait at normal velocity was used and carried out with each of the two hip joint implants assessed. Ground reaction forces’ kinetic temporal changes were considered in the first approach followed but discarded in the second one. Ground reaction force components were obtained from eighteen patients under such gait condition, half of which had a hip implant type I-II, whilst the other half had the hip implant, defined as type III by Orthoload®. After pre-processing raw gait kinetic data and selecting the time frames needed for the analysis, the ground reaction force components were used to train a MLP neural network, which learnt to distinguish the two hip joint implants in the abovementioned condition. Further to training, unknown hip implant side and ground reaction force components were presented to the neural networks, which assigned those features into the right class with a reasonably high accuracy for the hip implant type I-II and the type III. The results suggest that neural networks could be successfully applied in the performance assessment of hip joint implants.Keywords: kinemic gait data, neural networks, hip joint implant, hip arthroplasty, rehabilitation engineering
Procedia PDF Downloads 3541976 Next-Generation Lunar and Martian Laser Retro-Reflectors
Authors: Simone Dell'Agnello
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There are laser retroreflectors on the Moon and no laser retroreflectors on Mars. Here we describe the design, construction, qualification and imminent deployment of next-generation, optimized laser retroreflectors on the Moon and on Mars (where they will be the first ones). These instruments are positioned by time-of-flight measurements of short laser pulses, the so-called 'laser ranging' technique. Data analysis is carried out with PEP, the Planetary Ephemeris Program of CfA (Center for Astrophysics). Since 1969 Lunar Laser Ranging (LLR) to Apollo/Lunokhod laser retro-reflector (CCR) arrays supplied accurate tests of General Relativity (GR) and new gravitational physics: possible changes of the gravitational constant Gdot/G, weak and strong equivalence principle, gravitational self-energy (Parametrized Post Newtonian parameter beta), geodetic precession, inverse-square force-law; it can also constraint gravitomagnetism. Some of these measurements also allowed for testing extensions of GR, including spacetime torsion, non-minimally coupled gravity. LLR has also provides significant information on the composition of the deep interior of the Moon. In fact, LLR first provided evidence of the existence of a fluid component of the deep lunar interior. In 1969 CCR arrays contributed a negligible fraction of the LLR error budget. Since laser station range accuracy improved by more than a factor 100, now, because of lunar librations, current array dominate the error due to their multi-CCR geometry. We developed a next-generation, single, large CCR, MoonLIGHT (Moon Laser Instrumentation for General relativity high-accuracy test) unaffected by librations that supports an improvement of the space segment of the LLR accuracy up to a factor 100. INFN also developed INRRI (INstrument for landing-Roving laser Retro-reflector Investigations), a microreflector to be laser-ranged by orbiters. Their performance is characterized at the SCF_Lab (Satellite/lunar laser ranging Characterization Facilities Lab, INFN-LNF, Frascati, Italy) for their deployment on the lunar surface or the cislunar space. They will be used to accurately position landers, rovers, hoppers, orbiters of Google Lunar X Prize and space agency missions, thanks to LLR observations from station of the International Laser Ranging Service in the USA, in France and in Italy. INRRI was launched in 2016 with the ESA mission ExoMars (Exobiology on Mars) EDM (Entry, descent and landing Demonstration Module), deployed on the Schiaparelli lander and is proposed for the ExoMars 2020 Rover. Based on an agreement between NASA and ASI (Agenzia Spaziale Italiana), another microreflector, LaRRI (Laser Retro-Reflector for InSight), was delivered to JPL (Jet Propulsion Laboratory) and integrated on NASA’s InSight Mars Lander in August 2017 (launch scheduled in May 2018). Another microreflector, LaRA (Laser Retro-reflector Array) will be delivered to JPL for deployment on the NASA Mars 2020 Rover. The first lunar landing opportunities will be from early 2018 (with TeamIndus) to late 2018 with commercial missions, followed by opportunities with space agency missions, including the proposed deployment of MoonLIGHT and INRRI on NASA’s Resource Prospectors and its evolutions. In conclusion, we will extend significantly the CCR Lunar Geophysical Network and populate the Mars Geophysical Network. These networks will enable very significantly improved tests of GR.Keywords: general relativity, laser retroreflectors, lunar laser ranging, Mars geodesy
Procedia PDF Downloads 2691975 Application Reliability Method for Concrete Dams
Authors: Mustapha Kamel Mihoubi, Mohamed Essadik Kerkar
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Probabilistic risk analysis models are used to provide a better understanding of the reliability and structural failure of works, including when calculating the stability of large structures to a major risk in the event of an accident or breakdown. This work is interested in the study of the probability of failure of concrete dams through the application of reliability analysis methods including the methods used in engineering. It is in our case, the use of level 2 methods via the study limit state. Hence, the probability of product failures is estimated by analytical methods of the type first order risk method (FORM) and the second order risk method (SORM). By way of comparison, a level three method was used which generates a full analysis of the problem and involves an integration of the probability density function of random variables extended to the field of security using the Monte Carlo simulation method. Taking into account the change in stress following load combinations: normal, exceptional and extreme acting on the dam, calculation of the results obtained have provided acceptable failure probability values which largely corroborate the theory, in fact, the probability of failure tends to increase with increasing load intensities, thus causing a significant decrease in strength, shear forces then induce a shift that threatens the reliability of the structure by intolerable values of the probability of product failures. Especially, in case the increase of uplift in a hypothetical default of the drainage system.Keywords: dam, failure, limit-state, monte-carlo, reliability, probability, simulation, sliding, taylor
Procedia PDF Downloads 3241974 Contribution of Research to Innovation Management in the Traditional Fruit Production
Authors: Camille Aouinaït, Danilo Christen, Christoph Carlen
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Introduction: Small and Medium-sized Enterprises (SMEs) are facing different challenges such as pressures on environmental resources, the rise of downstream power, and trade liberalization. Remaining competitive by implementing innovations and engaging in collaborations could be a strategic solution. In Switzerland, the Federal Institute for Research in Agriculture (Agroscope), the Federal schools of technology (EPFL and ETHZ), Cantonal universities and Universities of Applied Sciences (UAS) can provide substantial inputs. UAS were developed with specific missions to match the labor markets and society needs. Research projects produce patents, publications and improved networks of scientific expertise. The study’s goal is to measure the contribution of UAS and research organization to innovation and the impact of collaborations with partners in the non-academic environment in Swiss traditional fruit production. Materials and methods: The European projects Traditional Food Network to improve the transfer of knowledge for innovation (TRAFOON) and Social Impact Assessment of Productive Interactions between science and society (SIAMPI) frame the present study. The former aims to fill the gap between the needs of traditional food producing SMEs and innovations implemented following European projects. The latter developed a method to assess the impacts of scientific research. On one side, interviews with market players have been performed to make an inventory of needs of Swiss SMEs producing apricots and berries. The participative method allowed matching the current needs and the existing innovations coming from past European projects. Swiss stakeholders (e.g. producers, retailers, an inter-branch organization of fruits and vegetables) directly rated the needs on a five-Likert scale. To transfer the knowledge to SMEs, training workshops have been organized for apricot and berries actors separately, on specific topics. On the other hand, a mapping of a social network is drawn to characterize the links between actors, with a focus on the Swiss canton of Valais and UAS Valais Wallis. Type and frequency of interactions among actors have identified thanks to interviews. Preliminary results: A list of 369 SMEs needs grouped in 22 categories was produced with 37 fulfilled questionnaires. Swiss stakeholders rated 31 needs very important. Training workshops on apricot are focusing on varietal innovations, storage, disease (bacterial blight), pest (Drosophila suzukii), sorting and rootstocks. Entrepreneurship was targeted through trademark discussions in berry production. The UAS Valais Wallis collaborated on a few projects with Agroscope along with industries, at European and national levels. Political and public bodies interfere with the central area of agricultural vulgarization that induces close relationships between the research and the practical side. Conclusions: The needs identified by Swiss stakeholders are becoming part of training workshops to incentivize innovations. The UAS Valais Wallis takes part in collaboration projects with the research environment and market players that bring innovations helping SMEs in their contextual environment. Then, a Strategic Research and Innovation Agenda will be created in order to pursue research and answer the issues facing by SMEs.Keywords: agriculture, innovation, knowledge transfer, university and research collaboration
Procedia PDF Downloads 3931973 Safe Zone: A Framework for Detecting and Preventing Drones Misuse
Authors: AlHanoof A. Alharbi, Fatima M. Alamoudi, Razan A. Albrahim, Sarah F. Alharbi, Abdullah M Almuhaideb, Norah A. Almubairik, Abdulrahman Alharby, Naya M. Nagy
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Recently, drones received a rapid interest in different industries worldwide due to its powerful impact. However, limitations still exist in this emerging technology, especially privacy violation. These aircrafts consistently threaten the security of entities by entering restricted areas accidentally or deliberately. Therefore, this research project aims to develop drone detection and prevention mechanism to protect the restricted area. Until now, none of the solutions have met the optimal requirements of detection which are cost-effectiveness, high accuracy, long range, convenience, unaffected by noise and generalization. In terms of prevention, the existing methods are focusing on impractical solutions such as catching a drone by a larger drone, training an eagle or a gun. In addition, the practical solutions have limitations, such as the No-Fly Zone and PITBULL jammers. According to our study and analysis of previous related works, none of the solutions includes detection and prevention at the same time. The proposed solution is a combination of detection and prevention methods. To implement the detection system, a passive radar will be used to properly identify the drone against any possible flying objects. As for the prevention, jamming signals and forceful safe landing of the drone integrated together to stop the drone’s operation. We believe that applying this mechanism will limit the drone’s invasion of privacy incidents against highly restricted properties. Consequently, it effectively accelerates drones‘ usages at personal and governmental levels.Keywords: detection, drone, jamming, prevention, privacy, RF, radar, UAV
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