Search results for: network resources
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9325

Search results for: network resources

7705 Performance Study of ZigBee-Based Wireless Sensor Networks

Authors: Afif Saleh Abugharsa

Abstract:

The IEEE 802.15.4 standard is designed for low-rate wireless personal area networks (LR-WPAN) with focus on enabling wireless sensor networks. It aims to give a low data rate, low power consumption, and low cost wireless networking on the device-level communication. The objective of this study is to investigate the performance of IEEE 802.15.4 based networks using simulation tool. In this project the network simulator 2 NS2 was used to several performance measures of wireless sensor networks. Three scenarios were considered, multi hop network with a single coordinator, star topology, and an ad hoc on demand distance vector AODV. Results such as packet delivery ratio, hop delay, and number of collisions are obtained from these scenarios.

Keywords: ZigBee, wireless sensor networks, IEEE 802.15.4, low power, low data rate

Procedia PDF Downloads 411
7704 The Optimization of Sexual Health Resource Information and Services for Persons with Spinal Cord Injury

Authors: Nasrin Nejatbakhsh, Anita Kaiser, Sander Hitzig, Colleen McGillivray

Abstract:

Following spinal cord injury (SCI), many individuals experience anxiety in adjusting to their lives, and its impacts on their sexuality. Research has demonstrated that regaining sexual function is a very high priority for individuals with SCI. Despite this, sexual health is one of the least likely areas of focus in rehabilitating individuals with SCI. There is currently a considerable gap in appropriate education and resources that address sexual health concerns and needs of people with spinal cord injury. Furthermore, the determinants of sexual health in individuals with SCI are poorly understood and thus poorly addressed. The purpose of this study was to improve current practices by informing a service delivery model that rehabilitation centers can adopt for appropriate delivery of their services. Methodology: We utilized qualitative methods in the form of a semi-structured interview containing open-ended questions to assess 1) sexual health concerns, 2) helpful strategies in current resources, 3) unhelpful strategies in current resources, and 4) Barriers to obtaining sexual health information. In addition to the interviews, participants completed surveys to identify socio-demographic factors. Data gathered was coded and evaluated for emerging themes and subthemes through a ‘code-recode’ technique. Results: We have identified several robust themes that are important for SCI sexual health resource development. Through analysis of these themes and their subthemes, several important concepts have emerged that could provide agencies with helpful strategies for providing sexual health resources. Some of the important considerations are that services be; anonymous, accessible, frequent, affordable, mandatory, casual and supported by peers. Implications: By incorporating the perspectives of individuals with SCI, the finding from this study can be used to develop appropriate sexual health services and improve access to information through tailored needs based program development.

Keywords: spinal cord injury, sexual health, determinants of health, resource development

Procedia PDF Downloads 238
7703 Neural Network Modelling for Turkey Railway Load Carrying Demand

Authors: Humeyra Bolakar Tosun

Abstract:

The transport sector has an undisputed place in human life. People need transport access to continuous increase day by day with growing population. The number of rail network, urban transport planning, infrastructure improvements, transportation management and other related areas is a key factor affecting our country made it quite necessary to improve the work of transportation. In this context, it plays an important role in domestic rail freight demand planning. Alternatives that the increase in the transportation field and has made it mandatory requirements such as the demand for improving transport quality. In this study generally is known and used in studies by the definition, rail freight transport, railway line length, population, energy consumption. In this study, Iron Road Load Net Demand was modeled by multiple regression and ANN methods. In this study, model dependent variable (Output) is Iron Road Load Net demand and 6 entries variable was determined. These outcome values extracted from the model using ANN and regression model results. In the regression model, some parameters are considered as determinative parameters, and the coefficients of the determinants give meaningful results. As a result, ANN model has been shown to be more successful than traditional regression model.

Keywords: railway load carrying, neural network, modelling transport, transportation

Procedia PDF Downloads 134
7702 Turbulent Channel Flow Synthesis using Generative Adversarial Networks

Authors: John M. Lyne, K. Andrea Scott

Abstract:

In fluid dynamics, direct numerical simulations (DNS) of turbulent flows require large amounts of nodes to appropriately resolve all scales of energy transfer. Due to the size of these databases, sharing these datasets amongst the academic community is a challenge. Recent work has been done to investigate the use of super-resolution to enable database sharing, where a low-resolution flow field is super-resolved to high resolutions using a neural network. Recently, Generative Adversarial Networks (GAN) have grown in popularity with impressive results in the generation of faces, landscapes, and more. This work investigates the generation of unique high-resolution channel flow velocity fields from a low-dimensional latent space using a GAN. The training objective of the GAN is to generate samples in which the distribution of the generated samplesis ideally indistinguishable from the distribution of the training data. In this study, the network is trained using samples drawn from a statistically stationary channel flow at a Reynolds number of 560. Results show that the turbulent statistics and energy spectra of the generated flow fields are within reasonable agreement with those of the DNS data, demonstrating that GANscan produce the intricate multi-scale phenomena of turbulence.

Keywords: computational fluid dynamics, channel flow, turbulence, generative adversarial network

Procedia PDF Downloads 187
7701 Learning Object Repositories as Developmental Resources for Educational Institutions in the 21st Century

Authors: Hanan A. Algamdi, Huda Y. Alyami

Abstract:

Learning object repositories contribute to developing educational process through its advantages; as they employ technology effectively, and use it to create new resources for effective learning, as well as they provide opportunities for collaboration in content through providing the ability for editing, modifying and developing it. This supports the relationships between communities that benefit from these repositories, and reflects positively on the content quality. Therefore, this study aims at exploring the most prominent learning topics in the 21st century, which should be included in learning object repositories, and identifying the necessary set of learning skills that the repositories should develop among today students. For conducting this study, the analytical descriptive method will be employed, and study sample will include a group of leaders, experts, and specialists in curricula and e-learning at ministry of education in Kingdom of Saudi Arabia.

Keywords: learning object, repositories, 21st century, quality

Procedia PDF Downloads 290
7700 GRCNN: Graph Recognition Convolutional Neural Network for Synthesizing Programs from Flow Charts

Authors: Lin Cheng, Zijiang Yang

Abstract:

Program synthesis is the task to automatically generate programs based on user specification. In this paper, we present a framework that synthesizes programs from flow charts that serve as accurate and intuitive specification. In order doing so, we propose a deep neural network called GRCNN that recognizes graph structure from its image. GRCNN is trained end-to-end, which can predict edge and node information of the flow chart simultaneously. Experiments show that the accuracy rate to synthesize a program is 66.4%, and the accuracy rates to recognize edge and node are 94.1% and 67.9%, respectively. On average, it takes about 60 milliseconds to synthesize a program.

Keywords: program synthesis, flow chart, specification, graph recognition, CNN

Procedia PDF Downloads 108
7699 Identification of Rice Quality Using Gas Sensors and Neural Networks

Authors: Moh Hanif Mubarok, Muhammad Rivai

Abstract:

The public's response to quality rice is very high. So it is necessary to set minimum standards in checking the quality of rice. Most rice quality measurements still use manual methods, which are prone to errors due to limited human vision and the subjectivity of testers. So, a gas detection system can be a solution that has high effectiveness and subjectivity for solving current problems. The use of gas sensors in testing rice quality must pay attention to several parameters. The parameters measured in this research are the percentage of rice water content, gas concentration, output voltage, and measurement time. Therefore, this research was carried out to identify carbon dioxide (CO₂), nitrous oxide (N₂O) and methane (CH₄) gases in rice quality using a series of gas sensors using the Neural Network method.

Keywords: carbon dioxide, dinitrogen oxide, methane, semiconductor gas sensor, neural network

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7698 6D Posture Estimation of Road Vehicles from Color Images

Authors: Yoshimoto Kurihara, Tad Gonsalves

Abstract:

Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.

Keywords: 6D posture estimation, image recognition, deep learning, AlexNet

Procedia PDF Downloads 133
7697 Strategic Planning in South African Higher Education

Authors: Noxolo Mafu

Abstract:

This study presents an overview of strategic planning in South African higher education institutions by tracing its trends and mystique in order to identify its impact. Over the democratic decades, strategic planning has become integral to institutional survival. It has been used as a potent tool by several institutions to catch up and surpass counterparts. While planning has always been part of higher education, strategic planning should be considered different. Strategic planning is primarily about development and maintenance of a strategic fitting between an institution and its dynamic opportunities. This presupposes existence of sets of stages that institutions pursue of which, can be regarded for assessment of the impact of strategic planning in an institution. The network theory serves guides the study in demystifying apparent organisational networks in strategic planning processes.

Keywords: network theory, strategy, planning, strategic planning, assessment, impact

Procedia PDF Downloads 537
7696 A Comparative Study on Automatic Feature Classification Methods of Remote Sensing Images

Authors: Lee Jeong Min, Lee Mi Hee, Eo Yang Dam

Abstract:

Geospatial feature extraction is a very important issue in the remote sensing research. In the meantime, the image classification based on statistical techniques, but, in recent years, data mining and machine learning techniques for automated image processing technology is being applied to remote sensing it has focused on improved results generated possibility. In this study, artificial neural network and decision tree technique is applied to classify the high-resolution satellite images, as compared to the MLC processing result is a statistical technique and an analysis of the pros and cons between each of the techniques.

Keywords: remote sensing, artificial neural network, decision tree, maximum likelihood classification

Procedia PDF Downloads 335
7695 Balance of Natural Resources to Manage Land Use Changes in Subosukawonosraten Area

Authors: Sri E. Wati, D. Roswidyatmoko, N. Maslahatun, Gunawan, Andhika B. Taji

Abstract:

Natural resource is the main sources to fulfill human needs. Its utilization must consider not only human prosperity but also sustainability. Balance of natural resources is a tool to manage natural wealth and to control land use change. This tool is needed to organize land use planning as stated on spatial plan in a certain region. Balance of natural resources can be calculated by comparing two-series of natural resource data obtained at different year. In this case, four years data period of land and forest were used (2010 and 2014). Land use data were acquired through satellite image interpretation and field checking. By means of GIS analysis, its result was then assessed with land use plan. It is intended to evaluate whether existing land use is suitable with land use plan. If it is improper, what kind of efforts and policies must be done to overcome the situation. Subosukawonosraten is rapid developed areas in Central Java Province. This region consists of seven regencies/cities which are Sukoharjo Regency, Boyolali Regency, Surakarta City, Karanganyar Regency, Wonogiri Regency, Sragen Regency, and Klaten Regency. This region is regarding to several former areas under Karasidenan Surakarta and their location is adjacent to Surakarta. Balance of forest resources show that width of forest area is not significantly changed. Some land uses within the area are slightly changed. Some rice field areas are converted into settlement (0.03%) whereas water bodies become vacant areas (0.09%). On the other hand, balance of land resources state that there are many land use changes in this region. Width area of rice field decreases 428 hectares and more than 50% of them have been transformed into settlement area and 11.21% is converted into buildings such as factories, hotels, and other infrastructures. It occurs mostly in Sragen, Sukoharjo, and Karanganyar Regency. The results illustrate that land use change in this region is mostly influenced by increasing of population number. Some agricultural lands have been converted into built-up area since demand of settlement, industrial area, and other infrastructures also increases. Unfortunately, recent utilization of more than a half of total area is not appropriate with land use plan declared in spatial planning document. It means, local government shall develop a strict regulation and law enforcement related to any violation in land use management.

Keywords: balance, forest, land, spatial plan

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7694 The Effects of Street Network Layout on Walking to School

Authors: Ayse Ozbil, Gorsev Argin, Demet Yesiltepe

Abstract:

Data for this cross-sectional study were drawn from questionnaires conducted in 10 elementary schools (1000 students, ages 12-14) located in Istanbul, Turkey. School environments (1600 meter buffers around the school) were evaluated through GIS-based land-use data (parcel level land use density) and street-level topography. Street networks within the same buffers were evaluated by using angular segment analysis (Integration and Choice) implemented in Depthmap as well as two segment-based connectivity measures, namely Metric and Directional Reach implemented in GIS. Segment Angular Integration measures how accessible each space from all the others within the radius using the least angle measure of distance. Segment Angular Choice which measures how many times a space is selected on journeys between all pairs of origins and destinations. Metric Reach captures the density of streets and street connections accessible from each individual road segment. Directional Reach measures the extent to which the entire street network is accessible with few direction changes. In addition, socio-economic characteristics (annual income, car ownership, education-level) of parents, obtained from parental questionnaires, were also included in the analysis. It is shown that surrounding street network configuration is strongly associated with both walk-mode shares and average walking distances to/from schools when controlling for parental socio-demographic attributes as well as land-use compositions and topographic features in school environments. More specifically, findings suggest that the scale at which urban form has an impact on pedestrian travel is considerably larger than a few blocks around the school.

Keywords: Istanbul, street network layout, urban form, walking to/from school

Procedia PDF Downloads 392
7693 Prediction of Temperature Distribution during Drilling Process Using Artificial Neural Network

Authors: Ali Reza Tahavvor, Saeed Hosseini, Nazli Jowkar, Afshin Karimzadeh Fard

Abstract:

Experimental & numeral study of temperature distribution during milling process, is important in milling quality and tools life aspects. In the present study the milling cross-section temperature is determined by using Artificial Neural Networks (ANN) according to the temperature of certain points of the work piece and the points specifications and the milling rotational speed of the blade. In the present work, at first three-dimensional model of the work piece is provided and then by using the Computational Heat Transfer (CHT) simulations, temperature in different nods of the work piece are specified in steady-state conditions. Results obtained from CHT are used for training and testing the ANN approach. Using reverse engineering and setting the desired x, y, z and the milling rotational speed of the blade as input data to the network, the milling surface temperature determined by neural network is presented as output data. The desired points temperature for different milling blade rotational speed are obtained experimentally and by extrapolation method for the milling surface temperature is obtained and a comparison is performed among the soft programming ANN, CHT results and experimental data and it is observed that ANN soft programming code can be used more efficiently to determine the temperature in a milling process.

Keywords: artificial neural networks, milling process, rotational speed, temperature

Procedia PDF Downloads 385
7692 Designing a Socio-Technical System for Groundwater Resources Management, Applying Smart Energy and Water Meter

Authors: S. Mahdi Sadatmansouri, Maryam Khalili

Abstract:

World, nowadays, encounters serious water scarcity problem. During the past few years, by advent of Smart Energy and Water Meter (SEWM) and its installation at the electro-pumps of the water wells, one had believed that it could be the golden key to address the groundwater resources over-pumping issue. In fact, implementation of these Smart Meters managed to control the water table drawdown for short; but it was not a sustainable approach. SEWM has been considered as law enforcement facility at first; however, for solving a complex socioeconomic problem like shared groundwater resources management, more than just enforcement is required: participation to conserve common resources. The well owners or farmers, as water consumers, are the main and direct stakeholders of this system and other stakeholders could be government sectors, investors, technology providers, privet sectors or ordinary people. Designing a socio-technical system not only defines the role of each stakeholder but also can lubricate the communication to reach the system goals while benefits of each are considered and provided. Farmers, as the key participators for solving groundwater problem, do not trust governments but they would trust a fair system in which responsibilities, privileges and benefits are clear. Technology could help this system remained impartial and productive. Social aspects provide rules, regulations, social objects and etc. for the system and help it to be more human-centered. As the design methodology, Design Thinking provides probable solutions for the challenging problems and ongoing conflicts; it could enlighten the way in which the final system could be designed. Using Human Centered Design approach of IDEO helps to keep farmers in the center of the solution and provides a vision by which stakeholders’ requirements and needs are addressed effectively. Farmers would be considered to trust the system and participate in their groundwater resources management if they find the rules and tools of the system fair and effective. Besides, implementation of the socio-technical system could change farmers’ behavior in order that they concern more about their valuable shared water resources as well as their farm profit. This socio-technical system contains nine main subsystems: 1) Measurement and Monitoring system, 2) Legislation and Governmental system, 3) Information Sharing system, 4) Knowledge based NGOs, 5) Integrated Farm Management system (using IoT), 6) Water Market and Water Banking system, 7) Gamification, 8) Agribusiness ecosystem, 9) Investment system.

Keywords: human centered design, participatory management, smart energy and water meter (SEWM), social object, socio-technical system, water table drawdown

Procedia PDF Downloads 282
7691 Purification of Zr from Zr-Hf Resources Using Crystallization in HF-HCl Solvent Mixture

Authors: Kenichi Hirota, Jifeng Wang, Sadao Araki, Koji Endo, Hideki Yamamoto

Abstract:

Zirconium (Zr) has been used as a fuel cladding tube for nuclear reactors, because of the excellent corrosion resistance and the low adsorptive material for neutron. Generally speaking, the natural resource of Zr is often containing Hf that has similar properties. The content of Hf in the Zr resources is about 2~4 wt%. In the industrial use, the content of Hf in Zr resources should be lower than the 100 ppm. However, the separation of Zr and Hf is not so easy, because of similar chemical and physical properties such as melting point, boiling point and things. Solvent extraction method has been applied for the separation of Zr and Hf from Zr natural resources. This method can separate Hf with high efficiency (Hf < 100ppm), however, it needs much amount of organic solvents for solvent extraction and the cost of its disposal treatment is high. Therefore, we attached attention for the fractional crystallization. This separation method depends on the solubility difference of Zr and Hf in the solvent. In this work, hexafluorozirconate (hafnate) (K2Zr(Hf)F6) was used as model compound. Solubility of K2ZrF6 in water showed lower than that of K2HfF6. By repeating of this treatment, it is possible to purify Zr, practically. In this case, 16-18 times of recrystallization stages were needed for its high purification. The improvement of the crystallization process was carried out in this work. Water, hydrofluoric acid (HF) and hydrofluoric acid (HF) +hydrochloric acid (HCl) mixture were chosen as solvent for dissolution of Zr and Hf. In the experiment, 10g of K2ZrF6 was added to each solvent of 100mL. Each solution was heated for 1 hour at 353K. After 1h of this operation, they were cooled down till 293K, and were held for 5 hours at 273K. Concentration of Zr or Hf was measured using ICP analysis. It was found that Hf was separated from Zr-Hf mixed compound with high efficiency, when HF-HCl solution was used for solvent of crystallization. From the comparison of the particle size of each crystal by SEM, it was confirmed that the particle diameter of the crystal showed smaller size with decreasing of Hf content. This paper concerned with purification of Zr from Zr-Hf mixture using crystallization method.

Keywords: crystallization, zirconium, hafnium, separation

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7690 Application of Remote Sensing and GIS for Delineating Groundwater Potential Zones of Ariyalur, Southern Part of India

Authors: G. Gnanachandrasamy, Y. Zhou, S. Venkatramanan, T. Ramkumar, S. Wang

Abstract:

The natural resources of groundwater are the most precious resources around the world that balances are shrinking day by day. In connection, there is an urgency need for demarcation of potential groundwater zone. For these rationale integration of geographical information system (GIS) and remote sensing techniques (RS) for the hydrological studies have become a dramatic change in the field of hydrological research. These techniques are provided to locate the potential zone of groundwater. This research has been made to indent groundwater potential zone in Ariyalur of the southern part of India with help of GIS and remote sensing techniques. To identify the groundwater potential zone used by different thematic layers of geology, geomorphology, drainage, drainage density, lineaments, lineaments density, soil and slope with inverse distance weighting (IDW) methods. From the overall result reveals that the potential zone of groundwater in the study area classified into five classes named as very good (12.18 %), good (22.74 %), moderate (32.28 %), poor (27.7 %) and very poor (5.08 %). This technique suggested that very good potential zone of groundwater occurred in patches of northern and central parts of Jayamkondam, Andimadam and Palur regions in Ariyalur district. The result exhibited that inverse distance weighting method offered in this research is an effective tool for interpreting groundwater potential zones for suitable development and management of groundwater resources in different hydrogeological environments.

Keywords: GIS, groundwater potential zone, hydrology, remote sensing

Procedia PDF Downloads 182
7689 Enhancing Scalability in Ethereum Network Analysis: Methods and Techniques

Authors: Stefan K. Behfar

Abstract:

The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

Procedia PDF Downloads 56
7688 Empowering Nigerian Rural Women through Ownership of Productive Resources

Authors: Sidiqat A. Aderinoye-Abdulwahab, Lateef L. Adefalu, Rashid S. Adisa, Felix O. Oladipo, Tawakalitu A. Dolapo

Abstract:

This study investigates whether the rural women in Nigeria have access to productive resources such as land, livestock, and capital in order to determine their level of socio-economic empowerment. The study adopted a case study design while employing qualitative and quantitative methods of data collection. A multi-stage sampling technique was used to identify 7 locations, where 88 women were selected based on simple random sampling technique. Focus group discussions and questionnaire were used to elicit information. Gender analysis framework was used to explore and analyse the data generated for the study. The study found that the rural women desire to engage in gainful economic activities. However, cultural barriers prevent them from adequately exploring livelihood-improving opportunities. It was established that ownership of productive resources such as land and livestock can enhance their livelihoods provided cultural and governance issues do not deter them from accessing the services. It was therefore recommended that appropriate policies that will favour the access and ownership of assets by women so as to empower them need to be in place. The study provides a nuanced perspective on the influence and relevance of possession of physical assets in enhancing women’s livelihood diversification and overall development of rural livelihoods.

Keywords: livelihoods, productivity, development, economic activities, socio-economic empowerment

Procedia PDF Downloads 242
7687 Dynamic Economic Load Dispatch Using Quadratic Programming: Application to Algerian Electrical Network

Authors: A. Graa, I. Ziane, F. Benhamida, S. Souag

Abstract:

This paper presents a comparative analysis study of an efficient and reliable quadratic programming (QP) to solve economic load dispatch (ELD) problem with considering transmission losses in a power system. The proposed QP method takes care of different unit and system constraints to find optimal solution. To validate the effectiveness of the proposed QP solution, simulations have been performed using Algerian test system. Results obtained with the QP method have been compared with other existing relevant approaches available in literatures. Experimental results show a proficiency of the QP method over other existing techniques in terms of robustness and its optimal search.

Keywords: economic dispatch, quadratic programming, Algerian network, dynamic load

Procedia PDF Downloads 546
7686 Sustainable Water Resource Management and Challenges in Indian Agriculture

Authors: Rajendra Kumar Isaac, Monisha Isaac

Abstract:

India, having a vast cultivable area and regional climatic variability, encounters water Resource Management Problems at various levels. The agricultural production of India needs to be increased to meet out projected population growth. Sustainable water resource is the only option to ensure food security, especially in northern Indian states, where the ground and surface water resources are fast depleting. Various tools and technologies available for management of scarce water resources have been discussed. It was concluded that multiple use of water, adopting latest water management options, identification of climate adoptable cropping and farming systems, can enhance water productivity and would encounter the fast growing water management and water shortage problems in Indian agriculture.

Keywords: water resource management, sustainable, water management technologies, water productivity, agriculture

Procedia PDF Downloads 385
7685 Evaluation of the Internal Quality for Pineapple Based on the Spectroscopy Approach and Neural Network

Authors: Nonlapun Meenil, Pisitpong Intarapong, Thitima Wongsheree, Pranchalee Samanpiboon

Abstract:

In Thailand, once pineapples are harvested, they must be classified into two classes based on their sweetness: sweet and unsweet. This paper has studied and developed the assessment of internal quality of pineapples using a low-cost compact spectroscopy sensor according to the Spectroscopy approach and Neural Network (NN). During the experiments, Batavia pineapples were utilized, generating 100 samples. The extracted pineapple juice of each sample was used to determine the Soluble Solid Content (SSC) labeling into sweet and unsweet classes. In terms of experimental equipment, the sensor cover was specifically designed to install the sensor and light source to read the reflectance at a five mm depth from pineapple flesh. By using a spectroscopy sensor, data on visible and near-infrared reflectance (Vis-NIR) were collected. The NN was used to classify the pineapple classes. Before the classification step, the preprocessing methods, which are Class balancing, Data shuffling, and Standardization were applied. The 510 nm and 900 nm reflectance values of the middle parts of pineapples were used as features of the NN. With the Sequential model and Relu activation function, 100% accuracy of the training set and 76.67% accuracy of the test set were achieved. According to the abovementioned information, using a low-cost compact spectroscopy sensor has achieved favorable results in classifying the sweetness of the two classes of pineapples.

Keywords: neural network, pineapple, soluble solid content, spectroscopy

Procedia PDF Downloads 56
7684 Conventional Four Steps Travel Demand Modeling for Kabul New City

Authors: Ahmad Mansoor Stanikzai, Yoshitaka Kajita

Abstract:

This research is a very essential towards transportation planning of Kabul New City. In this research, the travel demand of Kabul metropolitan area (Existing and Kabul New City) are evaluated for three different target years (2015, current, 2025, mid-term, 2040, long-term). The outcome of this study indicates that, though currently the vehicle volume is less the capacity of existing road networks, Kabul city is suffering from daily traffic congestions. This is mainly due to lack of transportation management, the absence of proper policies, improper public transportation system and violation of traffic rules and regulations by inhabitants. On the other hand, the observed result indicates that the current vehicle to capacity ratio (VCR) which is the most used index to judge traffic status in the city is around 0.79. This indicates the inappropriate traffic condition of the city. Moreover, by the growth of population in mid-term (2025) and long-term (2040) and in the case of no development in the road network and transportation system, the VCR value will dramatically increase to 1.40 (2025) and 2.5 (2040). This can be a critical situation for an urban area from an urban transportation perspective. Thus, by introducing high-capacity public transportation system and the development of road network in Kabul New City and integrating these links with the existing city road network, significant improvements were observed in the value of VCR.

Keywords: Afghanistan, Kabul new city, planning, policy, urban transportation

Procedia PDF Downloads 316
7683 RV-YOLOX: Object Detection on Inland Waterways Based on Optimized YOLOX Through Fusion of Vision and 3+1D Millimeter Wave Radar

Authors: Zixian Zhang, Shanliang Yao, Zile Huang, Zhaodong Wu, Xiaohui Zhu, Yong Yue, Jieming Ma

Abstract:

Unmanned Surface Vehicles (USVs) are valuable due to their ability to perform dangerous and time-consuming tasks on the water. Object detection tasks are significant in these applications. However, inherent challenges, such as the complex distribution of obstacles, reflections from shore structures, water surface fog, etc., hinder the performance of object detection of USVs. To address these problems, this paper provides a fusion method for USVs to effectively detect objects in the inland surface environment, utilizing vision sensors and 3+1D Millimeter-wave radar. MMW radar is complementary to vision sensors, providing robust environmental information. The radar 3D point cloud is transferred to 2D radar pseudo image to unify radar and vision information format by utilizing the point transformer. We propose a multi-source object detection network (RV-YOLOX )based on radar-vision fusion for inland waterways environment. The performance is evaluated on our self-recording waterways dataset. Compared with the YOLOX network, our fusion network significantly improves detection accuracy, especially for objects with bad light conditions.

Keywords: inland waterways, YOLO, sensor fusion, self-attention

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7682 Sustainable Rehabilitation of Concrete Buildings in Iran: Harnessing Sunlight and Navigating Limited Water Resources

Authors: Amin Khamoosh, Hamed Faramarzifar

Abstract:

In the capital of Iran, Tehran, numerous buildings constructed when extreme climates were not prevalent now face the need for rehabilitation, typically within their first decade. Our data delves into the performance metrics and economic advantages of sustainable rehabilitation practices compared to traditional methods. With a focus on the scarcity of water resources, we specifically scrutinize water-efficient techniques throughout construction, rehabilitation, and usage. Examining design elements that optimize natural light while efficiently managing heat transmission is crucial, given the reliance on water for cooling devices in this region. The data aims to present a comprehensive strategy, addressing immediate structural concerns while harmonizing with Iran's unique environmental conditions.

Keywords: sustainable rehabilitation, concrete buildings, iran, solar energy, water-efficient techniques

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7681 Non-intrusive Hand Control of Drone Using an Inexpensive and Streamlined Convolutional Neural Network Approach

Authors: Evan Lowhorn, Rocio Alba-Flores

Abstract:

The purpose of this work is to develop a method for classifying hand signals and using the output in a drone control algorithm. To achieve this, methods based on Convolutional Neural Networks (CNN) were applied. CNN's are a subset of deep learning, which allows grid-like inputs to be processed and passed through a neural network to be trained for classification. This type of neural network allows for classification via imaging, which is less intrusive than previous methods using biosensors, such as EMG sensors. Classification CNN's operate purely from the pixel values in an image; therefore they can be used without additional exteroceptive sensors. A development bench was constructed using a desktop computer connected to a high-definition webcam mounted on a scissor arm. This allowed the camera to be pointed downwards at the desk to provide a constant solid background for the dataset and a clear detection area for the user. A MATLAB script was created to automate dataset image capture at the development bench and save the images to the desktop. This allowed the user to create their own dataset of 12,000 images within three hours. These images were evenly distributed among seven classes. The defined classes include forward, backward, left, right, idle, and land. The drone has a popular flip function which was also included as an additional class. To simplify control, the corresponding hand signals chosen were the numerical hand signs for one through five for movements, a fist for land, and the universal “ok” sign for the flip command. Transfer learning with PyTorch (Python) was performed using a pre-trained 18-layer residual learning network (ResNet-18) to retrain the network for custom classification. An algorithm was created to interpret the classification and send encoded messages to a Ryze Tello drone over its 2.4 GHz Wi-Fi connection. The drone’s movements were performed in half-meter distance increments at a constant speed. When combined with the drone control algorithm, the classification performed as desired with negligible latency when compared to the delay in the drone’s movement commands.

Keywords: classification, computer vision, convolutional neural networks, drone control

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7680 The Potential Fresh Water Resources of Georgia and Sustainable Water Management

Authors: Nana Bolashvili, Vakhtang Geladze, Tamazi Karalashvili, Nino Machavariani, George Geladze, Davit Kartvelishvili, Ana Karalashvili

Abstract:

Fresh water is the major natural resource of Georgia. The average perennial sum of the rivers' runoff in Georgia is 52,77 km³, out of which 9,30 km³ inflows from abroad. The major volume of transit river runoff is ascribed to the Chorokhi river. Average perennial runoff in Western Georgia is 41,52 km³, in Eastern Georgia 11,25 km³. The indices of Eastern and Western Georgia were calculated with 50% and 90% river runoff respectively, while the same index calculation for other countries is based on a 50% river runoff. Out of total volume of resources, 133,2 m³/sec (4,21 km³) has been geologically prospected by the State Commission on Reserves and Acknowledged as reserves available for exploitation, 48% (2,02 km³) of which is in Western Georgia and 2,19 km³ in Eastern Georgia. Considering acknowledged water reserves of all categories per capita water resources accounts to 2,2 m³/day, whereas high industrial category -0. 88 m³ /day fresh drinking water. According to accepted norms, the possibility of using underground water reserves is 2,5 times higher than the long-term requirements of the country. The volume of abundant fresh-water reserves in Georgia is about 150 m³/sec (4,74 km³). Water in Georgia is consumed mostly in agriculture for irrigation purposes. It makes 66,4% around Georgia, in Eastern Georgia 72,4% and 38% in Western Georgia. According to the long-term forecast provision of population and the territory with water resources in Eastern Georgia will be quite normal. A bit different is the situation in the lower reaches of the Khrami and Iori rivers which could be easily overcome by corresponding financing. The present day irrigation system in Georgia does not meet the modern technical requirements. The overall efficiency of their majority varies between 0,4-0,6. Similar is the situation in the fresh water and public service water consumption. Organization of the mentioned systems, installation of water meters, introduction of new methods of irrigation without water loss will substantially increase efficiency of water use. Besides new irrigation norms developed from agro-climatic, geographical and hydrological angle will significantly reduce water waste. Taking all this into account we assume that for irrigation agricultural lands in Georgia is necessary 6,0 km³ water, 5,5 km³ of which goes to Eastern Georgia on irrigation arable areas. To increase water supply in Eastern Georgian territory and its population is possible by means of new water reservoirs as the runoff of every river considerably exceeds the consumption volume. In conclusion, we should say that fresh water resources by which Georgia is that rich could be significant source for barter exchange and investment attraction. Certain volume of fresh water can be exported from Western Georgia quite trouble free, without bringing any damage to population and hydroecosystems. The precise volume of exported water per region/time and method/place of water consumption should be defined after the estimation of different hydroecosystems and detailed analyses of water balance of the corresponding territories.

Keywords: GIS, management, rivers, water resources

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7679 Marketing Practices of the Urban and Recycled Wood Industry in the United States

Authors: Robert Smith, Omar Espinoza, Anna Pitta

Abstract:

In the United States, trees felled in urban areas and wood generated through construction and demolition are primarily disposed of as low-value resources, such as biomass for energy, landscaping mulch, composting, or landfilled. An emerging industry makes use of these underutilized resources to produce high value-added products, with associated benefits for the environment, the local economy, and consumers. For the circular economy to be successful, markets must be created for sustainable, reusable natural materials. Research was carried out to increase the understanding of the marketing practices of urban and reclaimed wood industries. This paper presents the results of a nationwide survey of these companies. The results indicate that a majority of companies in this industry are small firms, operating for less than 10 years, which produce mostly to order and sell their products at comparatively higher prices than competing products made from virgin natural resources. Promotional messages included quality, aesthetics, and customization, conveyed through company webpages, word of mouth, and social media. Distribution channels used include direct sales, online sales, and retail sales. Partnerships are critical for effective raw material procurement. Respondents indicated optimistic growth expectations, despite barriers associated with urban and reclaimed wood materials and production.

Keywords: urban and reclaimed wood, circular economy, marketing, wood products

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7678 Secured Cancer Care and Cloud Services in Internet of Things /Wireless Sensor Network Based Medical Systems

Authors: Adeniyi Onasanya, Maher Elshakankiri

Abstract:

In recent years, the Internet of Things (IoT) has constituted a driving force of modern technological advancement, and it has become increasingly common as its impacts are seen in a variety of application domains, including healthcare. IoT is characterized by the interconnectivity of smart sensors, objects, devices, data, and applications. With the unprecedented use of IoT in industrial, commercial and domestic, it becomes very imperative to harness the benefits and functionalities associated with the IoT technology in (re)assessing the provision and positioning of healthcare to ensure efficient and improved healthcare delivery. In this research, we are focusing on two important services in healthcare systems, which are cancer care services and business analytics/cloud services. These services incorporate the implementation of an IoT that provides solution and framework for analyzing health data gathered from IoT through various sensor networks and other smart devices in order to improve healthcare delivery and to help health care providers in their decision-making process for enhanced and efficient cancer treatment. In addition, we discuss the wireless sensor network (WSN), WSN routing and data transmission in the healthcare environment. Finally, some operational challenges and security issues with IoT-based healthcare system are discussed.

Keywords: IoT, smart health care system, business analytics, (wireless) sensor network, cancer care services, cloud services

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7677 A Hill Town in Nature to Urban Sprawl: Shimla (HP) India

Authors: Minakshi Jain, I. P. Singh

Abstract:

The mountain system makes the one fifth of the world’s landscape and is the home to the 600 million people. Though hills and mountains contain about 10 percent of the total population of the country, yet almost half of the country’s population living in or adjacent to the mountain areas depend directly or indirectly on the resources of the hills. Mountain environments are essential to the survival of the global ecosystems, as they sustain the economy of India through its perennial river system and precious forest wealth. Hill areas, with distinct climate, diverse vegetation and valuable flora & fauna are distinguished primarily by unique eco-system, rich both in bio-diversity and visual resources. These areas have special significance in terms of environment and economy. Still the irony is that these mountain ecosystems are fragile and highly susceptible to disturbance, with a low ability to rebound and heal after damage. Hills are home to endangered species, biological diversity and an essential part of the ecosystem. They are extremely sensitive to any human related development. Natural systems are the most ignored in the hills. The way the cities and towns have encroached them today has the serious repercussions on the climate. Amidst immense resources and constraints of nature, the town had a fantastic diversity of cultural and ethnic characteristics nurtured through ages along river basin and valley strung across the length and breadth of this Himalayan setting.

Keywords: eco-system, bio-diversity, urban sprawl, vernacular landscape

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7676 Dynamic Capability: An Exploratory Study Applied to Social Enterprise in South East Asia

Authors: Atiwat Khatpibunchai, Taweesak Kritjaroen

Abstract:

A social enterprise is the innovative hybrid organizations where its ultimate goal is to generate revenue and use it as a fund to solve the social and environmental problem. Although the evidence shows the clear value of economic, social and environmental aspects, the limitations of most of the social enterprises are the expanding impact of social and environmental aspects through the normal market mechanism. This is because the major sources of revenues of social enterprises derive from the business advocates who merely wish to support society and environment by using products and services of social enterprises rather than expect the satisfaction and the distinctive advantage of products and services. Thus, social enterprises cannot reach the achievement as other businesses do. The relevant concepts from the literature review revealed that dynamic capability is the ability to sense, integrate and reconfigure internal resources and utilize external resources to adapt to changing environments, create innovation and achieve competitive advantage. The objective of this research is to study the influence of dynamic capability that affects competitive advantage and sustainable performance, as well as to determine important elements of dynamic capability. The researchers developed a conceptual model from the related concepts and theories of dynamic capability. A conceptual model will support and show the influence of dynamic capability on competitive advantage and sustainable performance of social enterprises. The 230 organizations in South-East Asia served as participants in this study. The results of the study were analyzed by the structural equation model (SEM) and it was indicated that research model is consistent with empirical research. The results also demonstrated that dynamic capability has a direct and indirect influence on competitive advantage and sustainable performance. Moreover, it can be summarized that dynamic capability consists of the five elements: 1) the ability to sense an opportunity; 2) the ability to seize an opportunity; 3) the ability to integrate resources; 4) the ability to absorb resources; 5) the ability to create innovation. The study recommends that related sectors can use this study as a guideline to support and promote social enterprises. The focus should be pointed to the important elements of dynamic capability that are the development of the ability to transform existing resources in the organization and the ability to seize opportunity from changing market.

Keywords: dynamic capability, social enterprise, sustainable competitive advantage, sustainable performance

Procedia PDF Downloads 235