Search results for: production-living-ecology spatial network

Authors: An-Jui. Li, Kelvin Lim, Chien-Kuo Chiu, Benson Hsiung

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This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.

Keywords: landslide, limit analysis, artificial neural network, soil properties

Procedia PDF Downloads 204

Authors: J. K Adedeji, O. H Olowomofe, C. O Alo, S.T Ijatuyi

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The issue of high blood sugar level, the effects of which might end up as diabetes mellitus, is now becoming a rampant cardiovascular disorder in our community. In recent times, a lack of awareness among most people makes this disease a silent killer. The situation calls for urgency, hence the need to design a device that serves as a monitoring tool such as a wrist watch to give an alert of the danger a head of time to those living with high blood glucose, as well as to introduce a mechanism for checks and balances. The neural network architecture assumed 8-15-10 configuration with eight neurons at the input stage including a bias, 15 neurons at the hidden layer at the processing stage, and 10 neurons at the output stage indicating likely symptoms cases. The inputs are formed using the exclusive OR (XOR), with the expectation of getting an XOR output as the threshold value for diabetic symptom cases. The neural algorithm is coded in Java language with 1000 epoch runs to bring the errors into the barest minimum. The internal circuitry of the device comprises the compatible hardware requirement that matches the nature of each of the input neurons. The light emitting diodes (LED) of red, green, and yellow colors are used as the output for the neural network to show pattern recognition for severe cases, pre-hypertensive cases and normal without the traces of diabetes mellitus. The research concluded that neural network is an efficient Accu-Chek design tool for the proper monitoring of high glucose levels than the conventional methods of carrying out blood test.

Keywords: Accu-Check, diabetes, neural network, pattern recognition

Procedia PDF Downloads 143

Authors: Kyugneun Lee, Ikjin Lee

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Parameter estimation with inverse problem often suffers from unfavorable conditions in the real world. Useless data and many input parameters make the problem complicated or insoluble. Data refinement and reformulation of the problem can solve that kind of difficulties. In this research, a method to solve the rank deficient inverse problem is suggested. A multi-physics system which has rank deficiency caused by response correlation is treated. Impeditive information is removed and the problem is reformulated to sequential estimations using Bayesian network (BN) and subset groups. At first, subset grouping of the responses is performed. Feature selection with singular value decomposition (SVD) is used for the grouping. Next, BN inference is used for sequential conditional estimation according to the group hierarchy. Directed acyclic graph (DAG) structure is organized to maximize the estimation ability. Variance ratio of response to noise is used to pairing the estimable parameters by each response.

Keywords: Bayesian network, feature selection, rank deficiency, statistical inverse analysis

Procedia PDF Downloads 309

Authors: Jacob Wahl, Jane Zhang

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This paper describes the development and characterization of a prototype IoT network for use with agricultural imaging and monitoring applications. The sensor and gateway nodes are designed using the ESP32 SoC with integrated Bluetooth Low Energy 4.2 and Wi-Fi. A development board, the Arducam IoTai ESP32, is used for prototyping, testing, and power measurements. Google’s Firebase is used as the cloud storage site for image data collected by the sensor. The sensor node captures images using the OV2640 2MP camera module and transmits the image data to the gateway via Bluetooth Low Energy. The gateway then uploads the collected images to Firebase via a known nearby Wi-Fi network connection. This image data can then be processed and analyzed by computer vision and machine learning pipelines to assess crop growth or other needs. The sensor node achieves a wireless transmission data throughput of 220kbps while consuming 150mA of current; the sensor sleeps at 162µA. The sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day based on the development board power measurements. This network can be utilized by any application that requires high data rates, low power consumption, short-range communication, and large amounts of data to be transmitted at low-frequency intervals.

Keywords: Bluetooth low energy, ESP32, firebase cloud, IoT, smart farming

Procedia PDF Downloads 134

Authors: Rahman Mofidi, Sina Rahimi, Farnoosh Darban

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Communication plays a key role in today’s world, and to support it, the quality of service has the highest priority. It is very important to differentiate between traffic based on priority level. Some traffic classes should be a higher priority than other classes. It is also necessary to give high priority to customers who have more payment for better service, however, without influence on other customers. So to realize that, we will require effective quality of service methods. To ensure the optimal performance of the network in accordance with the quality of service is an important goal for all operators in the mobile network. In this work, we propose an algorithm based on control parameters which it’s based on user feedback that aims at minimizing the access to system transmit power and thus improving the network key performance indicators and increasing the quality of service. This feedback that is known as channel quality indicator (CQI) indicates the received signal level of the user. We aim at proposing an algorithm in control parameter criterion to study improving the quality of service and throughput in a cellular network at the simulated environment. In this work we tried to parameter values have close to their actual level. Simulation results show that the proposed algorithm improves the system throughput and thus satisfies users' throughput and improves service to set up a successful call.

Keywords: quality of service, key performance indicators, control parameter, channel quality indicator

Procedia PDF Downloads 199

Authors: Safayat Ali Shaikh

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Software has been developed for optimal cropping pattern in an irrigation project considering land constraint, water availability constraint and pick up flow constraint using modified Simplex Algorithm. Artificial Neural Network Models (ANN) have been developed to predict rainfall. AR (1) model used to generate 1000 years rainfall data to train the ANN. Simulation has been done with expected rainfall data. Eight number crops and three types of soil class have been considered for optimization model. Area under each crop and each soil class have been quantified using Modified Simplex Algorithm to get optimum net return. Efficacy of the software has been tested using data of large irrigation project in India.

Keywords: artificial neural network, large irrigation project, modified simplex algorithm, optimal cropping pattern

Procedia PDF Downloads 200

Authors: Wassim Jerbi, Abderrahmen Guermazi, Hafedh Trabelsi

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The optimum use of coverage in wireless sensor networks (WSNs) is very important. LEACH protocol called Low Energy Adaptive Clustering Hierarchy, presents a hierarchical clustering algorithm for wireless sensor networks. LEACH is a protocol that allows the formation of distributed cluster. In each cluster, LEACH randomly selects some sensor nodes called cluster heads (CHs). The selection of CHs is made with a probabilistic calculation. It is supposed that each non-CH node joins a cluster and becomes a cluster member. Nevertheless, some CHs can be concentrated in a specific part of the network. Thus, several sensor nodes cannot reach any CH. to solve this problem. We created an O-LEACH Orphan nodes protocol, its role is to reduce the sensor nodes which do not belong the cluster. The cluster member called Gateway receives messages from neighboring orphan nodes. The gateway informs CH having the neighboring nodes that not belong to any group. However, Gateway called (CH') attaches the orphaned nodes to the cluster and then collected the data. O-Leach enables the formation of a new method of cluster, leads to a long life and minimal energy consumption. Orphan nodes possess enough energy and seeks to be covered by the network. The principal novel contribution of the proposed work is O-LEACH protocol which provides coverage of the whole network with a minimum number of orphaned nodes and has a very high connectivity rates.As a result, the WSN application receives data from the entire network including orphan nodes. The proper functioning of the Application requires, therefore, management of intelligent resources present within each the network sensor. The simulation results show that O-LEACH performs better than LEACH in terms of coverage, connectivity rate, energy and scalability.

Keywords: WSNs; routing; LEACH; O-LEACH; Orphan nodes; sub-cluster; gateway; CH’

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Authors: Barbara Roosen, Oswald Devisch

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Spatial projects are often contested. Despite participatory trajectories in official spatial development processes, citizens engage often by their power to say no. Participatory mapping helps to produce more legible and democratic ways of decision-making. It has proven its value in producing a multitude of knowledges and views, for individuals and community groups and local stakeholders to imagine desired and undesired futures and to give them the rhetorical power to present their views throughout the development process. From this perspective, mapping works as a social process in which individuals and groups share their knowledge, learn from each other and negotiate their relationship with each other as well as with space and power. In this way, these processes eventually aim to activate communities to intervene in cooperation in real problems. However, these are fragile and bumpy processes, sometimes leading to (local) conflict and intractable situations. Heterogeneous subjectivities and knowledge that become visible during the mapping process and which are contested by members of the community, is often the first trigger. This paper discusses a participatory mapping project conducted in a residential subdivision in Flanders to provide a deeper understanding of how or under which conditions the mapping process could moderate discordant situations amongst inhabitants, local organisations and local authorities, towards a more constructive outcome. In our opinion, this implies a thorough documentation and presentation of the different steps of the mapping process to design and moderate an open and transparent dialogue. The mapping project ‘Make the Neighbourhood’, is set up in the aftermath of a socio-spatial design intervention in the neighbourhood that led to polarization within the community. To start negotiation between the diverse claims that came to the fore, we co-create a desired future map of the neighbourhood together with local organisations and inhabitants as a way to engage them in the development of a new spatial development plan for the area. This mapping initiative set up a new ‘common’ goal or concern, as a first step to bridge the gap that we experienced between different sociocultural groups, bottom-up and top-down initiatives and between professionals and non-professionals. An atlas of elements (materials), an atlas of actors with different roles and an atlas of ways of cooperation and organisation form the work and building material of the future neighbourhood map, assembled in two co-creation sessions. Firstly, we will consider how the mapping procedures articulate the plurality of claims and agendas. Secondly, we will elaborate upon how social relations and spatialities are negotiated and reproduced during the different steps of the map making. Thirdly, we will reflect on the role of the rules, format, and structure of the mapping process in moderating negotiations between much divided claims. To conclude, we will discuss the challenges of visualizing the different steps of mapping process as a strategy to moderate tense negotiations in a more constructive direction in the context of spatial development processes.

Keywords: conflict, documentation, participatory mapping, residential subdivision

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Authors: Harshit Mittal, Neeraj Garg

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Hand symbol recognition is a pivotal component in the domain of computer vision, with far-reaching applications spanning sign language interpretation, human-computer interaction, and accessibility. This research paper discusses the approach with the integration of the Canny Edge algorithm and convolutional neural network. The significance of this study lies in its potential to enhance communication and accessibility for individuals with hearing impairments or those engaged in gesture-based interactions with technology. In the experiment mentioned, the data is manually collected by the authors from the webcam using Python codes, to increase the dataset augmentation, is applied to original images, which makes the model more compatible and advanced. Further, the dataset of about 6000 coloured images distributed equally in 5 classes (i.e., 1, 2, 3, 4, 5) are pre-processed first to gray images and then by the Canny Edge algorithm with threshold 1 and 2 as 150 each. After successful data building, this data is trained on the Convolutional Neural Network model, giving accuracy: 0.97834, precision: 0.97841, recall: 0.9783, and F1 score: 0.97832. For user purposes, a block of codes is built in Python to enable a window for hand symbol recognition. This research, at its core, seeks to advance the field of computer vision by providing an advanced perspective on hand sign recognition. By leveraging the capabilities of the Canny Edge algorithm and convolutional neural network, this study contributes to the ongoing efforts to create more accurate, efficient, and accessible solutions for individuals with diverse communication needs.

Keywords: hand symbol recognition, computer vision, Canny edge algorithm, convolutional neural network

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Authors: Chun-Shien Lu

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Privacy-preserving query has recently received considerable attention in the signal processing and multimedia community. It is also a critical step in wireless sensor network for retrieval of sensitive data. The purposes of privacy-preserving query in both the areas of signal processing and sensor network are the same, but the similarity and difference of the adopted technologies are not fully explored. In this paper, we first review the recently developed methods of privacy-preserving query, and then describe in a comprehensive manner what we can learn from the mutual of both areas.

Keywords: encryption, privacy-preserving, search, security

Procedia PDF Downloads 253

Authors: Chompunut Jantarasorn, Chutima Prommak

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This paper presents an intensive measurement studying of the network performance analysis when IEEE 802.11g Wireless Local Area Networks (WLAN) coexisting with IEEE 802.15.4 Wireless Personal Area Network (WPAN). The measurement results show that the coexistence between both networks could increase the Frame Error Rate (FER) of the IEEE 802.15.4 networks up to 60% and it could decrease the throughputs of the IEEE 802.11g networks up to 55%.

Keywords: wireless performance analysis, coexistence analysis, IEEE 802.11g, IEEE 802.15.4

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Authors: Jing Zhang

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To reduce the carbon footprint of mankind and become more sustainable is one of the major challenges in our era. Internet of Things (IoT) mainly resolves three problems: Things to Things (T2T), Human to Things, H2T), and Human to Human (H2H). Borrowing the classification of IoT, we can find carbon prints of industries also can be divided in these three ways. Therefore, monitoring the routes of generation and circulation of products may help calculate product carbon print. This paper does not consider any technique used by IoT itself, but the ideas of it look at the connection of products. Carbon prints are like a gene or mark of a product from raw materials to the final products, which never leave the products. The contribution of this paper is to combine the characteristics of IoT and the methodology of network science to find a way to calculate the product's carbon footprint. Life cycle assessment, LCA is a traditional and main tool to calculate the carbon print of products. LCA is a traditional but main tool, which includes three kinds.

Keywords: product carbon footprint, Internet of Things, network science, life cycle assessment

Procedia PDF Downloads 114

Authors: Sanaz Kavianpour, Zuraini Ismail, Bharanidharan Shanmugam

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Social Network Sites (SNSs) can be served as an invaluable platform to transfer the information across a large number of individuals. A substantial component of communicating and managing information is to identify which individual will influence others in propagating information and also whether dissemination of information in the absence of social signals about that information will be occurred or not. Classifying the final audience of social data is difficult as controlling the social contexts which transfers among individuals are not completely possible. Hence, undesirable information diffusion to an unauthorized individual on SNSs can threaten individuals’ privacy. This paper highlights the information diffusion in SNSs and moreover it emphasizes the most significant privacy issues to individuals of SNSs. The goal of this paper is to propose a privacy-preserving model that has urgent regards with individuals’ data in order to control availability of data and improve privacy by providing access to the data for an appropriate third parties without compromising the advantages of information sharing through SNSs.

Keywords: anonymization algorithm, classification algorithm, information diffusion, privacy, social network sites

Procedia PDF Downloads 318

Authors: A. Ejah Umraeni Salam, M. Tola, M. Selintung, F. Maricar

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Clean water is an essential and fundamental human need. Therefore, its supply must be assured by maintaining the quality, quantity and water pressure. However the fact is, on its distribution system, leakage happens and becomes a common world issue. One of the technical causes of the leakage is a leaking pipe. The purpose of the research is how to use the Radial Basis Function Neural (RBFNN) model to detect the location and the magnitude of the pipeline leakage rapidly and efficiently. In this study the RBFNN are trained and tested on data from EPANET hydraulic modeling system. Method of Radial Basis Function Neural Network is proved capable to detect location and magnitude of pipeline leakage with of the accuracy of the prediction results based on the value of RMSE (Root Meant Square Error), comparison prediction and actual measurement approaches 0.000049 for the whole pipeline system.

Keywords: radial basis function neural network, leakage pipeline, EPANET, RMSE

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Authors: Lazhar Belkhiri, Ammar Tiri, Lotfi Mouni

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Water resources present to the public order of the world a very important problem for the protection and management of water quality given the complexity of water quality data sets. In this study, the water quality index (WQI) and irrigation water quality index (IWQI) were calculated in order to evaluate the surface water quality for drinking and irrigation purposes based on nine hydrochemical parameters. In order to separate the variables that are the most responsible for the spatial differentiation, the discriminant analysis (DA) was applied. The results show that the surface water quality for drinking is poor quality and very poor quality based on WQI values, however, the values of IWQI reflect that this water is acceptable for irrigation with a restriction for sensitive plants. Consequently, the discriminant analysis DA method has shown that the following parameters pH, potassium, chloride, sulfate, and bicarbonate are significant discrimination between the different stations with the spatial variation of the surface water quality, therefore, the results obtained in this study provide very useful information to decision-makers

Keywords: surface water quality, drinking and irrigation purposes, water quality index, discriminant analysis

Procedia PDF Downloads 82

Authors: Ali Reza Sattarzadeh, Ronny J. Kutadinata, Pubudu N. Pathirana, Van Thanh Huynh

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Traffic congestion has become a severe worldwide problem, affecting everyday life, fuel consumption, time, and air pollution. The primary causes of these issues are inadequate transportation infrastructure, poor traffic signal management, and rising population. Traffic flow forecasting is one of the essential and effective methods in urban congestion and traffic management, which has attracted the attention of researchers. With the development of technology, undeniable progress has been achieved in existing methods. However, there is a possibility of improvement in the extraction of temporal and spatial features to determine the importance of traffic flow sequences and extraction features. In the proposed model, we implement the convolutional neural network (CNN) and long short-term memory (LSTM) deep learning models for mining nonlinear correlations and their effectiveness in increasing the accuracy of traffic flow prediction in the real dataset. According to the experiments, the results indicate that implementing Conv-LSTM networks increases the productivity and accuracy of deep learning models for traffic flow prediction.

Keywords: deep learning algorithms, intelligent transportation systems, spatiotemporal features, traffic flow prediction

Procedia PDF Downloads 169

Authors: I. Touaїbia, E. Azzag, O. Narjes

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Power supply networks are growing continuously and their reliability is getting more important than ever. The complexity of the whole network comprises numerous components that can fail and interrupt the power supply for the end user. Underground distribution systems are normally exposed to permanent faults, due to specific construction characteristics. In these systems, visual inspection cannot be performed. In order to enhance service restoration, accurate fault location techniques must be applied. This paper describes the different faults that affect the underground distribution system of SONELGAZ (National Society of Electricity and Gas of Algeria), and cable fault location procedure with impulse reflection method (TDR), based in the analyses of the cable response of the electromagnetic impulse, allows cable fault prelocation. The results are obtained from real test in the underground distribution feeder from electrical network of energy distribution company of Souk-Ahras, in order to know the influence of cable characteristics in the types and frequency of faults.

Keywords: distribution networks, fault location, TDR, underground cable

Procedia PDF Downloads 526

Authors: Sagwata A. Manyike, Hulisani Magada

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The South African National Biodiversity Institute is in the process of developing a guideline which sets out how biodiversity can be incorporated into land use (zoning) schemes. South Africa promulgated its Spatial Planning and Land Use Management Act in 2015 and the act seeks, amongst other things, to bridge the gap between spatial planning and land use management within the country. In addition, the act requires local governments to develop wall-to-wall land use schemes for their entire jurisdictions as they had previously only developed them for their urban areas. At the same time, South Africa has a rich history of systematic conservation planning whereby Critical Biodiversity Areas and Ecological Support Areas have been spatially delineated at a scale appropriate for spatial planning and land use management at the scale of local government. South Africa is also in the process of spatially delineating ecological infrastructure which is defined as naturally occurring ecosystems which provide valuable services to people such as water and climate regulation, soil formation, disaster risk reduction, etc. The Biodiversity and Land Use Project, which is funded by the Global Environmental Facility through the United Nations Development Programme is seeking to explore ways in which biodiversity information and ecological infrastructure can be incorporated into the spatial planning and land use management systems of local governments. Towards this end, the Biodiversity and Land Use Project have developed a guideline which sets out how local governments can integrate biodiversity into their land-use schemes as a way of not only ensuring sustainable development but also as a way helping them prepare for climate change. In addition, by incorporating biodiversity into land-use schemes, the project is exploring new ways of protecting biodiversity through land use schemes. The Guideline for Incorporating Biodiversity into Land Use Schemes was developed as a response to the fact that the National Land Use Scheme Guidelines only indicates that local governments needed to incorporate biodiversity without explaining how this could be achieved. The Natioanl Guideline also failed to specify which biodiversity-related layers are compatible with which land uses or what the benefits of incorporating biodiversity into the schemes will be for that local government. The guideline, therefore, sets out an argument for why biodiversity is important in land management processes and proceeds to provide a step by step guideline for how schemes can integrate priority biodiversity layers. This guideline will further be added as an addendum to the National Land Use Guidelines. Although the planning act calls for local government to have wall to wall schemes within 5 years of its enactment, many municipalities will not meet this deadline and so this guideline will support them in the development of their new schemes.

Keywords: biodiversity, climate change, land use schemes, local government

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Authors: Wissal Ben Arfi, Lubica Hikkerova, Jean-Michel Sahut

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This study examines interfirm networks in the digital transformation era, and in particular, how tacit knowledge codification affects innovation success within digital platforms. Hence, one of the most important features of digital transformation and innovation process outcomes is the emergence of digital platforms, as an interfirm network, at the heart of open innovation. This research aims to illuminate how digital platforms influence inter-organizational innovation through virtual team interactions and knowledge sharing practices within an interfirm network. Consequently, it contributes to the respective strategic management literature on new product development (NPD), open innovation, industrial management, and its emerging interfirm networks’ management. The empirical findings show, on the one hand, that knowledge conversion may be enhanced, especially by the socialization which seems to be the most important phase as it has played a crucial role to hold the virtual team members together. On the other hand, in the process of socialization, the tacit knowledge codification is crucial because it provides the structure needed for the interfirm network actors to interact and act to reach common goals which favor the emergence of open innovation. Finally, our results offer several conditions necessary, but not always sufficient, for interfirm managers involved in NPD and innovation concerning strategies to increasingly shape interconnected and borderless markets and business collaborations. In the digital transformation era, the need for adaptive and innovative business models as well as new and flexible network forms is becoming more significant than ever. Supported by technological advancements and digital platforms, companies could benefit from increased market opportunities and creating new markets for their innovations through alliances and collaborative strategies, as a mode of reducing or eliminating uncertainty environments or entry barriers. Consequently, an efficient and well-structured interfirm network is essential to create network capabilities, to ensure tacit knowledge sharing, to enhance organizational learning and to foster open innovation success within digital platforms.

Keywords: interfirm networks, digital platform, virtual teams, open innovation, knowledge sharing

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Authors: Nicolás Clavijo Buriticá, Laura Viviana Triana Sanchez

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This research develops a productive context associated with the aquaculture industry in northern Tolima-Colombia, specifically in the town of Lerida. Strategic aspects of chain of fish Production-Distribution, especially those related to supply network design of an association devoted to cultivating, farming, processing and marketing of fish are addressed. This research is addressed from a special approach of Supply Chain Management (SCM) which guides management objectives to the system sustainability; this approach is called Sustainable Supply Chain Management (SSCM). The network design of fish production-distribution system is obtained for the case study by two mathematical programming models that aims to maximize the economic benefits of the chain and minimize total supply chain costs, taking into account restrictions to protect the environment and its implications on system productivity. The results of the mathematical models validated in the productive situation of the partnership under study, called Asopiscinorte shows the variation in the number of open or closed locations in the supply network that determines the final network configuration. This proposed result generates for the case study an increase of 31.5% in the partial productivity of storage and processing, in addition to possible favorable long-term implications, such as attending an agile or not a consumer area, increase or not the level of sales in several areas, to meet in quantity, time and cost of work in progress and finished goods to various actors in the chain.

Keywords: Sustainable Supply Chain, mathematical programming, aquaculture industry, Supply Chain Design, Supply Chain Configuration

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Authors: A. O. Abulibdeh

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The aim of this study is to investigate and compare the changes in the Land Surface Temperature (LST) as a function of urbanization, particularly land use/land cover changes, in three cities in the UAE, mainly Abu Dhabi, Dubai, and Al Ain. The scale of this assessment will be at the macro- and micro-levels. At the macro-level, a comparative assessment will take place to compare between the four cities in the UAE. At the micro-level, the study will compare between the effects of different land use/land cover on the LST. This will provide a clear and quantitative city-specific information related to the relationship between urbanization and local spatial intra-urban LST variation in three cities in the UAE. The main objectives of this study are 1) to investigate the development of LST on the macro- and micro-level between and in three cities in the UAE over two decades time period, 2) to examine the impact of different types of land use/land cover on the spatial distribution of LST. Because these three cities are facing harsh arid climate, it is hypothesized that (1) urbanization is affecting and connected to the spatial changes in LST; (2) different land use/land cover have different impact on the LST; and (3) changes in spatial configuration of land use and vegetation concentration over time would control urban microclimate on a city scale and control macroclimate on the country scale. This study will be carried out over a 20-year period (1996-2016) and throughout the whole year. The study will compare between two distinct periods with different thermal characteristics which are the cool/cold period from November to March and warm/hot period between April and October. The best practice research method for this topic is to use remote sensing data to target different aspects of natural and anthropogenic systems impacts. The project will follow classical remote sensing and mapping techniques to investigate the impact of urbanization, mainly changes in land use/land cover, on LST. The investigation in this study will be performed in two stages. Stage one remote sensing data will be used to investigate the impact of urbanization on LST on a macroclimate level where the LST and Urban Heat Island (UHI) will be compared in the three cities using data from the past two decades. Stage two will investigate the impact on microclimate scale by investigating the LST and UHI using a particular land use/land cover type. In both stages, an LST and urban land cover maps will be generated over the study area. The outcome of this study should represent an important contribution to recent urban climate studies, particularly in the UAE. Based on the aim and objectives of this study, the expected outcomes are as follow: i) to determine the increase or decrease of LST as a result of urbanization in these four cities, ii) to determine the effect of different land uses/land covers on increasing or decreasing the LST.

Keywords: land use/land cover, global warming, land surface temperature, remote sensing

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Authors: Hassam Muazzam

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This paper devises an autonomous self-driven vehicle that is capable of taking a disabled person to his/her desired location using three different power sources (gasoline, solar, electric) without any control from the user, avoiding the obstacles in the way. The GPS co-ordinates of the desired location are sent to the main processing board via a GSM module. After the GPS co-ordinates are sent, the path to be followed by the vehicle is devised by Pythagoras theorem. The distance and angle between the present location and the desired location is calculated and then the vehicle starts moving in the desired direction. Meanwhile real-time data from ultrasonic sensors is fed to the board for obstacle avoidance mechanism. Ultrasonic sensors are used to quantify the distance of the vehicle from the object. The distance and position of the object is then used to make decisions regarding the direction of vehicle in order to avoid the obstacles using artificial neural network which is implemented using ATmega1280. Also the vehicle provides the feedback location at remote location.

Keywords: autonomous self-driven vehicle, obstacle avoidance, desired location, pythagoras theorem, neural network, remote location

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Authors: J. S. Saini, P. P. K. Sandhu

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The multi-hop nature of Wireless Mesh Networks and the hasty progression of throughput demands results in multi- channels and multi-radios structures in mesh networks, but the main problem of co-channels interference reduces the total throughput, specifically in multi-hop networks. Quality of Service mentions a vast collection of networking technologies and techniques that guarantee the ability of a network to make available desired services with predictable results. Quality of Service (QoS) can be directed at a network interface, towards a specific server or router's performance, or in specific applications. Due to interference among various transmissions, the QoS routing in multi-hop wireless networks is formidable task. In case of multi-channel wireless network, since two transmissions using the same channel may interfere with each other. This paper has considered the Destination Sequenced Distance Vector (DSDV) routing protocol to locate the secure and optimised path. The proposed technique also utilizes the Lempel–Ziv–Welch (LZW) based lossless data compression and intra cluster data aggregation to enhance the communication between the source and the destination. The use of clustering has the ability to aggregate the multiple packets and locates a single route using the clusters to improve the intra cluster data aggregation. The use of the LZW based lossless data compression has ability to reduce the data packet size and hence it will consume less energy, thus increasing the network QoS. The MATLAB tool has been used to evaluate the effectiveness of the projected technique. The comparative analysis has shown that the proposed technique outperforms over the existing techniques.

Keywords: WMNS, QOS, flooding, collision avoidance, LZW, congestion control

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Authors: Ondrej Slach, Jan Machacek, Jan Zenka, Lucie Hyllova, Petr Rumpel

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The aim of the paper is to identify and asses different trajectories of two fashionable urban policies –creative and smart cities– in specific post-socialistic context. Drawing on the case of Czechia, we employ the concept of policy mobility research. More specifically, we employ a discourse analysis in order to identify the so-called 'infrastructure' of both policies (such as principal actors, journals, conferences, events), with the special focus on 'agents of transfer' in a multiscale perspective. The preliminary results indicate faster and more aggressive spatial penetration of smart cities policy compared to creative cities policy in Czechia. Further, it seems that existed translation and implementation of smart cities policy into the national and urban context resulted in deliberated fragmented policy of smart cities in Czechia (pure technocratic view), which might be a threat for the future development of social sustainability, especially in cities that are facing increasing social polarisation. Last but not least, due to the fast spatial penetration of the concept and policies of smart cities, it seems that creative cities policy has almost been crowded out of the Czech urban agenda.

Keywords: policy mobility, smart cities, creative cities, Czechia

Procedia PDF Downloads 162

Authors: Shashank Gupta, Iteash Agarwal, Vijayalaxmi Mogiligidda, Rajesh Kumar Krishnan, Sruthi Chennuri, Deepika Aggarwal, Anwesha Hoodati, Sheroy Cooper, Ranjan, Mohammad Bilal Sheik, Bhavya K. M., Manasa Hegde, M. Naveen Krishna, Amit Kumar Chauhan, Mallikarjun Korrapati, Sumit Singh, J. B. Singh, Sunil Sud, Sunil Gupta, Sidhartha Pant, Sankar, Neha Agrawal, Ashish Ranjan, Piyush Mohapatra, Roopak T., Arsh Ahmad, Nanjunda M., Dilip Singh

Abstract:

Major research interests on quantum key distribution (QKD) are primarily focussed on increasing 1. point-to-point transmission distance (1000 Km), 2. secure key rate (Mbps), 3. security of quantum layer (device-independence). It is great to push the boundaries on these fronts, but these isolated approaches are neither scalable nor cost-effective due to the requirements of specialised hardware and different infrastructure. Current and future QKD network requires addressing different sets of challenges apart from distance, key rate, and quantum security. In this regard, we present ChaQra -a sub-quantum network with core features as 1) Crypto agility (integration in the already deployed telecommunication fibres), 2) Software defined networking (SDN paradigm for routing different nodes), 3) reliability (addressing denial-of-service with hybrid quantum safe cryptography), 4) upgradability (modules upgradation based on scientific and technological advancements), 5) Beyond QKD (using QKD network for distributed computing, multi-party computation etc). Our results demonstrate a clear path to create and accelerate quantum secure Indian subcontinent under the national quantum mission.

Keywords: quantum network, quantum key distribution, quantum security, quantum information

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Authors: Wei Ting Han, Shiann-Far Kung

Abstract:

In the early time, most of the arable land is dry farming and using rainfall as water sources for irrigation in Tainan county. After the Chia-nan Irrigation System (CIS) was completed in 1930, Chia-nan Plain was more efficient allocation of limited water sources or irrigation, because of the benefit from irrigation systems, drainage systems, and land improvement projects. The problem of long-term drought, flood and salt damage in the past were also improved by CIS. The canal greatly improved the paddy field area and agricultural output, Tainan county has become one of the important agricultural producing areas in Taiwan. With the development of water conservancy facilities, affected by national policies and other factors, many agricultural communities and settlements are formed indirectly, also promoted the change of settlement patterns and internal structures. With the development of historical geographic information system (HGIS), Academia Sinica developed the WebGIS theme with the century old maps of Taiwan which is the most complete historical map of database in Taiwan. It can be used to overlay historical figures of different periods, present the timeline of the settlement change, also grasp the changes in the natural environment or social sciences and humanities, and the changes in the settlements presented by the visualized areas. This study will explore the historical development and spatial characteristics of the settlements in various areas of Tainan County. Using of large-scale areas to explore the settlement changes and spatial patterns of the entire county, through the dynamic time and space evolution from Japanese rule to the present day. Then, digitizing the settlement of different periods to perform overlay analysis by using Taiwan historical topographic maps in 1904, 1921, 1956 and 1989. Moreover, using document analysis to analyze the temporal and spatial changes of regional environment and settlement structure. In addition, the comparison analysis method is used to classify the spatial characteristics and differences between the settlements. Exploring the influence of external environments in different time and space backgrounds, such as government policies, major construction, and industrial development. This paper helps to understand the evolution of the settlement space and the internal structural changes in Tainan County.

Keywords: historical geographic information system, overlay analysis, settlement change, Tainan County

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Authors: P. L. Cheng, I. N. Umar

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Online discussion forum is a popular e-learning technique that allows participants to interact and construct knowledge. This study aims to examine the levels of participation, categories of participants and the structure of their interactions in a forum. A convenience sampling of one course coordinator and 23 graduate students was selected in this study. The forums’ log file and the Social Network Analysis software were used in this study. The analysis reveals 610 activities (including viewing forum’s topic, viewing discussion thread, posting a new thread, replying to other participants’ post, updating an existing thread and deleting a post) performed by them in this forum, with an average of 3.83 threads posted. Also, this forum consists of five at-risk participants, six bridging participants, four isolated participants and five leaders of information. In addition, the network density value is 0.15 and there exist five reciprocal interactions in this forum. The closeness value varied between 28 and 68 while the eigen vector centrality value varied between 0.008 and 0.39. The finding indicates that the participants tend to listen more rather than express their opinions in the forum. It was also revealed that those who actively provide supports in the discussion forum were not the same people who received the most responses from their peers. This study found that cliques do not exist in the forum and the participants are not selective to whom they response to, rather, it was based on the content of the posts made by their peers. Based upon the findings, further analysis with different method and population, larger sample size and a longer time frame are recommended.

Keywords: e-learning, learning management system, online forum, social network analysis

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Authors: Yael Dubinsky, Orit Hazzan

Abstract:

There is a constant need for hi-tech innovation to be decentralized to peripheral regions. This work describes how we applied design science research (DSR) principles to define what we refer to as the Sea of Galilee (SoG) method. The goal of the SoG method is to harness existing and new technological initiatives in peripheral regions to create a socio-technological network that can initiate and maintain hi-tech activities. The SoG method consists of a set of principles, a stakeholder network, and actual hi-tech business initiatives, including their infrastructure and practices. The three cycles of DSR, the Relevance, Design, and Rigor cycles, layout a research framework to sharpen the requirements, collect data from case studies, and iteratively refine the SoG method based on the existing knowledge base. We propose that the SoG method can be deployed by regional authorities that wish to be considered smart regions (an extension of the notion of smart cities).

Keywords: design science research, socio-technological initiatives, Sea of Galilee method, periphery stakeholder network, hi-tech initiatieves

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Authors: Natalia Sypion-Dutkowska

Abstract:

Abstract — The main research objective of the paper is to discover the relationship between the age groups of residents and crime in particular districts of a large city. The basic analytical tool is specific crime rates, calculated not in relation to the total population, but for age groups in a different social situation - property, housing, work, and representing different generations with different behavior patterns. They are the communities from which criminals and victims of crimes come. The analysis of literature and national police reports gives rise to hypotheses about the ability of a given age group to generate crime as a source of offenders and as a group of victims. These specific indicators are spatially differentiated, which makes it possible to detect socio-demographic determinants of spatial patterns of urban crime. A multi-feature classification of districts was also carried out, in which specific crime rates are the diagnostic features. In this way, areas with a similar structure of socio-demographic determinants of spatial patterns on urban crime were designated. The case study is the city of Szczecin in Poland. It has about 400,000 inhabitants and its area is about 300 sq km. Szczecin is located in the immediate vicinity of Germany and is the economic, academic and cultural capital of the region. It also has a seaport and an airport. Moreover, according to ESPON 2007, Szczecin is the Transnational and National Functional Urban Area. Szczecin is divided into 37 districts - auxiliary administrative units of the municipal government. The population of each of them in 2015-17 was divided into 8 age groups: babes (0-2 yrs.), children (3-11 yrs.), teens (12-17 yrs.), younger adults (18-30 yrs.), middle-age adults (31-45 yrs.), older adults (46-65 yrs.), early older (66-80) and late older (from 81 yrs.). The crimes reported in 2015-17 in each of the districts were divided into 10 groups: fights and beatings, other theft, car theft, robbery offenses, burglary into an apartment, break-in into a commercial facility, car break-in, break-in into other facilities, drug offenses, property damage. In total, 80 specific crime rates have been calculated for each of the districts. The analysis was carried out on an intra-city scale, this is a novel approach as this type of analysis is usually carried out at the national or regional level. Another innovative research approach is the use of specific crime rates in relation to age groups instead of standard crime rates. Acknowledgments: This research was funded by the National Science Centre, Poland, registration number 2019/35/D/HS4/02942.

Keywords: age groups, determinants of crime, spatial crime pattern, urban crime

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Authors: Sandesh Achar

Abstract:

Personalized advertising holds greater potential for higher conversion rates compared to generic advertisements. However, its widespread application in the retail industry faces challenges due to complex implementation processes. These complexities impede the swift adoption of personalized advertisement on a large scale. Personalized advertisement, being a data-driven approach, necessitates consumer-related data, adding to its complexity. This paper introduces an innovative data-driven decision-making framework, D3Advert, which personalizes advertisements by analyzing personalities using a BiLSTM network. The framework utilizes the Myers–Briggs Type Indicator (MBTI) dataset for development. The employed BiLSTM network, specifically designed and optimized for D3Advert, classifies user personalities into one of the sixteen MBTI categories based on their social media posts. The classification accuracy is 86.42%, with precision, recall, and F1-Score values of 85.11%, 84.14%, and 83.89%, respectively. The D3Advert framework personalizes advertisements based on these personality classifications. Experimental implementation and performance analysis of D3Advert demonstrate a 40% improvement in impressions. D3Advert’s innovative and straightforward approach has the potential to transform personalized advertising and foster widespread personalized advertisement adoption in marketing.

Keywords: personalized advertisement, deep Learning, MBTI dataset, BiLSTM network, NLP.

Procedia PDF Downloads 40