Search results for: green infrastructure network

Authors: Mohammad F. Fauzi, Nurul H. Shahba M. Shahrun, Nurul W. Hamzah, Mohd Noah A. Rahman, Afzaal H. Seyal

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In this paper, we proposed a simulation system using Wireless Sensor Network (WSN) that will be distributed around the forest for early forest fire detection and to locate the areas affected. In Brunei Darussalam, approximately 78% of the nation is covered by forest. Since the forest is Brunei’s most precious natural assets, it is very important to protect and conserve our forest. The hot climate in Brunei Darussalam can lead to forest fires which can be a fatal threat to the preservation of our forest. The process consists of getting data from the sensors, analyzing the data and producing an alert. The key factors that we are going to analyze are the surrounding temperature, wind speed and wind direction, humidity of the air and soil.

Keywords: forest fire monitor, humidity, wind direction, wireless sensor network

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Authors: Bin Ji, Kai Xu, Shunyu Yao, Jingjing Liu, Ye Pan

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Human pose estimation is a popular research area in computer vision for its important application in human-machine interface. In recent years, 2D human pose estimation based on convolution neural network has got great progress and development. However, in more and more practical applications, people often need to deal with tasks based on video. It’s not far-fetched for us to consider how to combine the spatial and temporal information together to achieve a balance between computing cost and accuracy. To address this issue, this study proposes a new spatiotemporal model, namely Spatiotemporal Net (STNet) to combine both temporal and spatial information more rationally. As a result, the predicted keypoints heatmap is potentially more accurate and spatially more precise. Under the condition of ensuring the recognition accuracy, the algorithm deal with spatiotemporal series in a decoupled way, which greatly reduces the computation of the model, thus reducing the resource consumption. This study demonstrate the effectiveness of our network over the Penn Action Dataset, and the results indicate superior performance of our network over the existing methods.

Keywords: convolutional long short-term memory, deep learning, human pose estimation, spatiotemporal series

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Authors: Hugo Badia

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This research answers which is the most suitable transit network structure to serve specific demand requirements in an increasing urban dispersion process. Two main approaches of network design are found in the literature. On the one hand, a traditional answer, widespread in our cities, that develops a high number of lines to connect most of origin-destination pairs by direct trips; an approach based on the idea that users averse to transfers. On the other hand, some authors advocate an alternative design characterized by simple networks where transfer is essential to complete most of trips. To answer which of them is the best option, we use a two-step methodology. First, by means of an analytical model, three basic network structures are compared: a radial scheme, starting point for the other two structures, a direct trip-based network, and a transfer-based one, which represent the two alternative transit network designs. The model optimizes the network configuration with regard to the total cost for each structure. For a scenario of dispersion, the best alternative is the structure with the minimum cost. This dispersion degree is defined in a simple way considering that only a central area attracts all trips. If this area is small, we have a high concentrated mobility pattern; if this area is too large, the city is highly decentralized. In this first step, we can determine the area of applicability for each structure in function to that urban dispersion degree. The analytical results show that a radial structure is suitable when the demand is so centralized, however, when this demand starts to scatter, new transit lines should be implemented to avoid transfers. If the urban dispersion advances, the introduction of more lines is no longer a good alternative, in this case, the best solution is a change of structure, from direct trips to a network based on transfers. The area of applicability of each network strategy is not constant, it depends on the characteristics of demand, city and transport technology. In the second step, we translate analytical results to a real case study by the relationship between the parameters of dispersion of the model and direct measures of dispersion in a real city. Two dimensions of the urban sprawl process are considered: concentration, defined by Gini coefficient, and centralization by area based centralization index. Once it is estimated the real dispersion degree, we are able to identify in which area of applicability the city is located. In summary, from a strategic point of view, we can obtain with this methodology which is the best network design approach for a city, comparing the theoretical results with the real dispersion degree.

Keywords: analytical network design model, network structure, public transport, urban dispersion

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Authors: Troy A. Tyre

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Organizational behavior and organizational change are elements of the ever-changing global business environment. Leadership and organizational behavior are 21st century disciplines. Network marketing organizations need to understand the ever-changing nature of global business and be ready and willing to adapt to the environment. Network marketing organizations have a challenge keeping up with a rapid escalation in global growth. Network marketing growth has been steady and global. Network marketing organizations have been slow to develop a 21st century global strategy to manage the rapid escalation of growth degrading organizational behavior, job satisfaction, increasing attrition, and degrading customer service. Development of an organizational behavior and leadership theory for the 21st century to help network marketing develops a global business strategy to manage the rapid escalation in growth that affects organizational behavior. Managing growth means organizational leadership must develop and adapt to the organizational environment. Growth comes with an open mind and one’s departure from the comfort zone. Leadership growth operates in the tacit dimension. Systems thinking and adaptation of mental models can help shift organizational behavior. Shifting the organizational behavior requires organizational learning. Organizational learning occurs through single-loop, double-loop, and triple-loop learning. Triple-loop learning is the most difficult, but the most rewarding. Tools such as theory U can aid in developing a landscape for organizational behavioral development. Additionally, awareness to espoused and portrayed actions is imperatives. Theories of motivation, cross-cultural diversity, and communications are instrumental in founding an organizational behavior suited for the 21st century.

Keywords: global, leadership, network marketing, organizational behavior

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Authors: Hossain A., Chowdhury S. I.

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Introduction: The use of a gamma camera is a standard procedure in nuclear medicine facilities or hospitals to diagnose chronic kidney disease (CKD), but the gamma camera does not precisely stage the disease. The authors sought to determine whether they could use an artificial neural network to determine whether CKD was in normal or abnormal stages based on GFR values (ANN). Method: The 250 kidney patients (Training 188, Testing 62) who underwent an ultrasonography test to diagnose a renal test in our nuclear medical center were scanned using a gamma camera. Before the scanning procedure, the patients received an injection of ⁹⁹ᵐTc-DTPA. The gamma camera computes the pre- and post-syringe radioactive counts after the injection has been pushed into the patient's vein. The artificial neural network uses the softmax function with cross-entropy loss to determine whether CKD is normal or abnormal based on the GFR value in the output layer. Results: The proposed ANN model had a 99.20 % accuracy according to K-fold cross-validation. The sensitivity and specificity were 99.10 and 99.20 %, respectively. AUC was 0.994. Conclusion: The proposed model can distinguish between normal and abnormal stages of CKD by using an artificial neural network. The gamma camera could be upgraded to diagnose normal or abnormal stages of CKD with an appropriate GFR value following the clinical application of the proposed model.

Keywords: artificial neural network, glomerular filtration rate, stages of the kidney, gamma camera

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Authors: Wei-Hao Lee, Ta-Wui Cheng, Yung-Chin Ding, Tai-Tien Wang

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The purpose of this study is trying to use marble wastes as the raw material to fabricate geopolymer green mortar / concrete. Experiment results show that using marble to make geopolymer mortar and concrete, the compressive strength after 28 days curing can reach 35 MPa and 25 MPa, respectively. The characteristics of marble-based geopolymer green mortar and concrete will keep testing for a long term in order to understand the effect parameters. The study is based on resource recovery and recycling. Its basic characteristics are low consumption, low carbon dioxide emission and high efficiency that meet the international tendency 'Circular Economy.' By comparing with Portland cement mortar and concrete, production 1 ton of marble-based geopolymer mortar and concrete, they can be saved around 50.3% and 49.6% carbon dioxide emission, respectively. Production 1 m3 of marble-based geopolymer concrete costs about 62 USD that cheaper than that of traditional Portland concrete. It is proved that the marble-based geopolymer concrete has great potential for further engineering development.

Keywords: marble, geopolymer, geopolymer concrete, CO₂ emission

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Authors: Sahar Elkaee Behjati

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Air pollution, particularly with dust, is one of the biggest issues Tehran is dealing with, and the city's green space which consists of trees has a critical role in absorption of it. The question this study aimed to investigate was which tree species the highest uptake capacity of the dust and carbon have suspended in the air. On this basis, 30 samples of trees from two different districts in Tehran were collected, and after washing and centrifuging, the samples were oven dried. The results of the study revealed that Ulmus minor had the highest amount of deposited dust in both districts. In addition, it was found that in Chamran district Ailanthus altissima and in Gandi district Ulmus minor has had the highest absorption of deposited carbon. Therefore, it could be argued that decision making on the selection of species for urban green spaces should take the above-mentioned parameters into account.

Keywords: dust, leaves, uptake total carbon, Tehran, tree species

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Authors: Mehrdad Shafiei Dizaji, Hoda Azari

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The research explores the pioneering integration of Physics-Informed Neural Networks (PINNs) into the domain of Ground-Penetrating Radar (GPR) data prediction, akin to advancements in medical imaging for tracking tumor progression in the human body. This research presents a detailed development framework for a specialized PINN model proficient at interpreting and forecasting GPR data, much like how medical imaging models predict tumor behavior. By harnessing the synergy between deep learning algorithms and the physical laws governing subsurface structures—or, in medical terms, human tissues—the model effectively embeds the physics of electromagnetic wave propagation into its architecture. This ensures that predictions not only align with fundamental physical principles but also mirror the precision needed in medical diagnostics for detecting and monitoring tumors. The suggested deep learning structure comprises three components: a CNN, a spatial feature channel attention (SFCA) mechanism, and ConvLSTM, along with temporal feature frame attention (TFFA) modules. The attention mechanism computes channel attention and temporal attention weights using self-adaptation, thereby fine-tuning the visual and temporal feature responses to extract the most pertinent and significant visual and temporal features. By integrating physics directly into the neural network, our model has shown enhanced accuracy in forecasting GPR data. This improvement is vital for conducting effective assessments of bridge deck conditions and other evaluations related to civil infrastructure. The use of Physics-Informed Neural Networks (PINNs) has demonstrated the potential to transform the field of Non-Destructive Evaluation (NDE) by enhancing the precision of infrastructure deterioration predictions. Moreover, it offers a deeper insight into the fundamental mechanisms of deterioration, viewed through the prism of physics-based models.

Keywords: physics-informed neural networks, deep learning, ground-penetrating radar (GPR), NDE, ConvLSTM, physics, data driven

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Authors: Anna Keuchenius

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Broadly speaking, scientific development is studied in either a qualitative manner with a focus on the behavior and interpretations of academics, such as the sociology of science and science studies or in a quantitative manner with a focus on the analysis of publications, such as scientometrics and bibliometrics. Both come with a different set of methodologies and few cross-references. This paper contributes to the bridging of this divide, by on the on hand approaching the process of scientific progress from a qualitative sociological angle and using on the other hand quantitative and computational techniques. As a case study, we analyze the diffusion of Granovetter's hypothesis from his 1973 paper 'On The Strength of Weak Ties.' A network is constructed of all scientists that have referenced this particular paper, with directed edges to all other researchers that are concurrently referenced with Granovetter's 1973 paper. Studying the structure and growth of this network over time, it is found that Granovetter's hypothesis is used by distinct communities of scientists, each with their own key-narrative into which the hypothesis is fit. The diffusion within the communities shares similarities with the diffusion of an innovation in which innovators, early adopters, and an early-late majority can clearly be distinguished. Furthermore, the network structure shows that each community is clustered around one or few hub scientists that are disproportionately often referenced and seem largely responsible for carrying the hypothesis into their scientific subfield. The larger implication of this case study is that the diffusion of scientific hypotheses and ideas are not the spreading of well-defined objects over a network. Rather, the diffusion is a process in which the object itself dynamically changes in concurrence with its spread. Therefore it is argued that the methodology presented in this paper has potential beyond the scientific domain, in the study of diffusion of other not well-defined objects, such as opinions, behavior, and ideas.

Keywords: diffusion of innovations, network analysis, scientific development, sociology of science

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Authors: Arbnor Pajaziti, Hasan Cana

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In this paper, the structural genetic algorithm is used to optimize the neural network to control the joint movements of robotic arm. The robotic arm has also been modeled in 3D and simulated in real-time in MATLAB. It is found that Neural Networks provide a simple and effective way to control the robot tasks. Computer simulation examples are given to illustrate the significance of this method. By combining Genetic Algorithm optimization method and Neural Networks for the given robotic arm with 5 D.O.F. the obtained the results shown that the base joint movements overshooting time without controller was about 0.5 seconds, while with Neural Network controller (optimized with Genetic Algorithm) was about 0.2 seconds, and the population size of 150 gave best results.

Keywords: robotic arm, neural network, genetic algorithm, optimization

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Authors: Sumanpreet Kaur, Harjit Pal Singh, Vikas Khullar

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In Wireless Sensor Network (WSN), the sensor containing motes (nodes) incorporate batteries that can lament at some extent. To upgrade the energy utilization, clustering is one of the prototypical approaches for split sensor motes into a number of clusters where one mote (also called as node) proceeds as a Cluster Head (CH). CH selection is one of the optimization techniques for enlarging stability and network lifespan. Deterministic Stable Election Protocol (DSEP) is an effectual clustering protocol that makes use of three kinds of nodes with dissimilar residual energy for CH election. Fuzzy Logic technology is used to expand energy level of DSEP protocol by using fuzzy inference system. This paper presents protocol DSEP using Fuzzy Logic (DSEP-FL) CH by taking into account four linguistic variables such as energy, concentration, centrality and distance to base station. Simulation results show that our proposed method gives more effective results in term of a lifespan of network and stability as compared to the performance of other clustering protocols.

Keywords: DSEP, fuzzy logic, energy model, WSN

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Authors: Fangzheng Li, Xiong Li

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Significant differences in urban greening have occurred in Chinese cities, which accompanied with China's rapid urbanization. However, few studies focused on the spatial differentiation of urban greening in China with large amounts of data. The spatial differentiation pattern, spatial correlation characteristics and the distribution shape of urban green space ratio, urban green coverage rate and public green area per capita were calculated and analyzed, using Global and Local Moran's I using data from 289 cities in 2014. We employed Spatial Lag Model and Spatial Error Model to assess the impacts of urbanization process on urban greening of China. Then we used Geographically Weighted Regression to estimate the spatial variations of the impacts. The results showed: 1. a significant spatial dependence and heterogeneity existed in urban greening values, and the differentiation patterns were featured by the administrative grade and the spatial agglomeration simultaneously; 2. it revealed that urbanization has a negative correlation with urban greening in Chinese cities. Among the indices, the the proportion of secondary industry, urbanization rate, population and the scale of urban land use has significant negative correlation with the urban greening of China. Automobile density and per capita Gross Domestic Product has no significant impact. The results of GWR modeling showed that the relationship between urbanization and urban greening was not constant in space. Further, the local parameter estimates suggested significant spatial variation in the impacts of various urbanization factors on urban greening.

Keywords: China’s urbanization, geographically weighted regression, spatial differentiation pattern, urban greening

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Authors: M. Asato, C. Liu, N. Fujima, T. Hoshino, Y. Chen, T. Mohri

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We study the temperature dependence of the interaction energies (IEs) of X (=Ru, Rh) impurities in Pd, due to the Fermi-Dirac (FD) distribution and the thermal vibration effect by the Debye-Grüneisen model. The n-body (n=2~4) IEs among X impurities in Pd, being used to calculate the internal energies in the free energies of the Pd-rich PdX alloys, are determined uniquely and successively from the lower-order to higher-order, by the full-potential Korringa-Kohn-Rostoker Green’s function method (FPKKR), combined with the generalized gradient approximation in the density functional theory. We found that the temperature dependence of IEs due to the FD distribution, being usually neglected, is very important to reproduce the X-concentration dependence of the observed solvus temperatures of the Pd-rich PdX (X=Ru, Rh) alloys.

Keywords: full-potential KKR-green’s function method, Fermi-Dirac distribution, GGA, phase diagram of Pd-rich PdX (X=Ru, Rh) alloys, thermal vibration effect

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Authors: Khamael Abualnaja, Hala M. Abo-Dief

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Silver nanoparticles (AgNPs) are the subject of important recent interest, present in a large range of applications such as electronics, catalysis, chemistry, energy, and medicine. Metallic nanoparticles are traditionally synthesized by wet chemical techniques, where the chemicals used are quite often toxic and flammable. In this work, we describe an effective and environmental-friendly technique of green synthesis of silver nanoparticles. Silver nanoparticles (AgNPs) synthesized using silver nitrate solution and the extract of mint, basil, orange peel and Tangerines peel which used as reducing agents. Silver Nanoparticles were characterized using Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and UV–Vis absorption spectroscopy. SEM analysis showed the average particle size of mint, basil, orange peel, Tangerines peel are 30, 20, 12, 10 nm respectively. This is for the first time that any plant extract was used for the synthesis of nanoparticles.

Keywords: silver nanoparticles, green synthesis, scanning electron microscopy, plants

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Authors: Suk-Hyun Yu, Heeyong Kwon

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Recently PM-10 has become a social and global issue. It is one of major air pollutants which affect human health. Therefore, it needs to be forecasted rapidly and precisely. However, PM-10 comes from various emission sources, and its level of concentration is largely dependent on meteorological and geographical factors of local and global region, so the forecasting of PM-10 concentration is very difficult. Neural network model can be used in the case. But, there are few cases of high concentration PM-10. It makes the learning of the neural network model difficult. In this paper, we suggest a simple input balancing method when the data distribution is uneven. It is based on the probability of appearance of the data. Experimental results show that the input balancing makes the neural networks’ learning easy and improves the forecasting rates.

Keywords: artificial intelligence, air quality prediction, neural networks, pattern recognition, PM-10

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Authors: Ugwu O. C., Mamah R. O., Awudu W. S.

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This work is aimed at enhancing signal reception on a mobile radio network and minimizing outage probability in a mobile radio network using adaptive beamforming antenna arrays. In this research work, an empirical real-time drive measurement was done in a cellular network of Globalcom Nigeria Limited located at Ikeja, the headquarters of Lagos State, Nigeria, with reference base station number KJA 004. The empirical measurement includes Received Signal Strength and Bit Error Rate which were recorded for exact prediction of the signal strength of the network as at the time of carrying out this research work. The Received Signal Strength and Bit Error Rate were measured with a spectrum monitoring Van with the help of a Ray Tracer at an interval of 100 meters up to 700 meters from the transmitting base station. The distance and angular location measurements from the reference network were done with the help Global Positioning System (GPS). The other equipment used were transmitting equipment measurements software (Temsoftware), Laptops and log files, which showed received signal strength with distance from the base station. Results obtained were about 11% from the real-time experiment, which showed that mobile radio networks are prone to signal failure and can be minimized using an Adaptive Beamforming Antenna Array in terms of a significant reduction in Bit Error Rate, which implies improved performance of the mobile radio network. In addition, this work did not only include experiments done through empirical measurement but also enhanced mathematical models that were developed and implemented as a reference model for accurate prediction. The proposed signal models were based on the analysis of continuous time and discrete space, and some other assumptions. These developed (proposed) enhanced models were validated using MATLAB (version 7.6.3.35) program and compared with the conventional antenna for accuracy. These outage models were used to manage the blocked call experience in the mobile radio network. 20% improvement was obtained when the adaptive beamforming antenna arrays were implemented on the wireless mobile radio network.

Keywords: beamforming algorithm, adaptive beamforming, simulink, reception

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Authors: Mokhlisur Rahman

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Consumers' understanding of the products depends on what levels of information the advertisement contains. Consumers' attitudes vary widely depending on factors such as their level of environmental awareness, their perception of the company's motives, and the perceived effectiveness of the advertising campaign. Considering the growing eco-consciousness among consumers and their concern for the environment, strategies for green advertising have become equally significant for companies to attract new consumers. It is important to understand consumers' habits of purchasing, knowledge, and attitudes regarding eco-friendly products depending on promotion because of the limitless options of the products in the market. Additionally, encouraging consumers to buy sustainable products requires a platform that can message the world that being a stakeholder in sustainability is possible if consumers show eco-friendly behavior on a larger scale. Social media platforms provide an excellent atmosphere to promote companies' sustainable efforts to be connected engagingly with their potential consumers. The unique strategies of green advertising use techniques to carry information and rewards for the consumers. This study aims to understand the consumer behavior and effectiveness of green advertising by experimenting in collaboration with three companies in promoting their eco-friendly products using green designs on the products. The experiment uses three sustainable personalized offerings, Nike shoes, H&M t-shirts, and Patagonia school bags. The experiment uses a pretest and posttest design. 300 randomly selected participants take part in this experiment and survey through Facebook, Twitter, and Instagram. Nike, H&M, and Patagonia share the post of the experiment on their social media homepages with a video advertisement for the three products. The consumers participate in a pre-experiment online survey before making a purchase decision to assess their attitudes and behavior toward eco-friendly products. The audio-only feature explains the product's information, like their use of recycled materials, their manufacturing methods, sustainable packaging, and their impact on the environment during the purchase while the consumer watches the product video. After making a purchase, consumers take a post-experiment survey to know their perception and behavior toward eco-friendly products. For the data analysis, descriptive statistical tools mean, standard deviation, and frequencies measure the pre- and post-experiment survey data. The inferential statistical tool paired sample t-test measures the difference in consumers' behavior and attitudes between pre-purchase and post-experiment survey results. This experiment provides consumers ample time to consider many aspects rather than impulses. This research provides valuable insights into how companies can adopt sustainable and eco-friendly products. The result set a target for the companies to achieve a sustainable production goal that ultimately supports companies' profit-making and promotes consumers' well-being. This empowers consumers to make informed choices about the products they purchase and support their companies of interest.

Keywords: green-advertising, sustainability, consumer-behavior, social media

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Authors: R. Padmini, G. V. Manoj Kumar

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Structural insulated panels (SIPs) are a high-performance building system for residential and light commercial construction. The panels consist of an insulating foam core sandwiched between two structural facings, typically oriented strand board (OSB). SIPs are manufactured under factory controlled conditions and can be fabricated to fit nearly any building design. The result is a building system that is extremely strong, energy efficient and cost effective. Building with SIPs will save you time, money and labor. Building with SIPs generally costs about the same as building with wood frame construction when you factor in the labor savings resulting from shorter construction time and less job-site waste. Other savings are realized because smaller heating and cooling systems are required with SIP construction. Structural insulated panels (SIPs) are one of the most airtight and well-insulated building systems available, making them an inherently green product. An airtight SIP building will use less energy to heat and cool, allow for better control over indoor environmental conditions, and reduce construction waste. Green buildings use less energy, reducing carbon dioxide emissions and playing an important role in combating global climate change. Buildings also use a tremendous amount of natural resources to construct and operate. Constructing green buildings that use these resources more efficiently, while minimizing pollution that can harm renewable natural resources, is crucial to a sustainable future.

Keywords: high performance, under factory controlled, wood frame, carbon dioxide emissions, natural resources

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Authors: Manuel Meranza-Castillon, Rolando Diaz-Castillo, Adrian Arellano-Delgado, Cesar Cruz-Hernandez, Rosa Martha Lopez-Gutierrez

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In this work, we deal with experimental network synchronization of chaotic nodes with different topologies. Our approach is based on complex system theory, and we use a master-slave configuration to couple the nodes in the networks. In particular, we design and implement electronically complex dynamical networks composed by nine coupled chaotic Chua’s circuits with topologies: in nearest-neighbor, small-world, open ring, star, and global. Also, network synchronization is evaluated according to a particular coupling strength for each topology. This study is important by the possible applications to private transmission of information in a chaotic communication network of multiple users.

Keywords: complex networks, Chua's circuit, experimental synchronization, multiple users

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Authors: Yasemin Kavdir, Ugur Gozel

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This study was conducted to determine the nematicidal activity of green walnut husk (GWH) and olive pomace (OP) extracts against root-knot nematode (Meloidogyne incognita). Aqueous extracts of GWH and OP were mixed with sandy loam soil at the rates of 0, 6,12,18,24, 60 and 120 ml kg-1. All pots were arranged in a randomized complete block design and replicated four times under controlled atmosphere conditions. Tomato seedlings were grown in sterilized soil then they were transplanted to pots. Inoculation was done by pouring the 20 ml suspension including 1000 M. incognita juvenile pot-1 into 3 cm deep hole made around the base of the plant root. Tomato root and shoot growth and nematode populations have been determined. In general, both GWH and OP extracts resulted in better growth parameters compared to the control plants. However, GWH extract was the most effective in improving growth parameters. Applications of 24 ml kg-1 OP extract enhanced plant growth compared to other OP treatments while 60 ml kg-1 application rate had the lowest nematode number and root galling. In this study, applications of GWH and OP extracts reduced the number of Meloidogyne incognita and root galling compared to control soils. Additionally GWH and OP extracts can be used safely for tomato growth. It could be concluded that OP and GWH extracts used as organic amendments showed promising nematicidal activity in the control of M. incognita. This research was supported by TUBİTAK Grant Number 214O422.

Keywords: olive pomace, green walnut husk, Meloidogyne incognita, tomato, soil, extract

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Authors: Lingzhi Li, Jiankun Zhang, Tiantian Gu

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Hazard management that can prevent fatal accidents and property losses is a fundamental process during the buildings’ construction stage. However, due to lack of safety supervision resources and operational pressures, the conduction of hazard management is poor and ineffective in China. In order to improve the quality of construction safety management, it is critical to explore the use of information technologies to ensure that the process of hazard management is efficient and effective. After exploring the existing problems of construction hazard management in China, this paper develops the griddization management model for construction hazard management. First, following the knowledge grid infrastructure, the griddization computing infrastructure for construction hazards management is designed which includes five layers: resource entity layer, information management layer, task management layer, knowledge transformation layer and application layer. This infrastructure will be as the technical support for realizing grid management. Second, this study divides the construction hazards into grids through city level, district level and construction site level according to grid principles. Last, a griddization management process including hazard identification, assessment and control is developed. Meanwhile, all stakeholders of construction safety management, such as owners, contractors, supervision organizations and government departments, should take the corresponding responsibilities in this process. Finally, a case study based on actual construction hazard identification, assessment and control is used to validate the effectiveness and efficiency of the proposed griddization management model. The advantage of this designed model is to realize information sharing and cooperative management between various safety management departments.

Keywords: construction hazard, griddization computing, grid management, process

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Authors: W. Hashim, H. Burok, N. Ghazaly, H. Ahmad Nasir, N. Mohamad Anas, A. F. Ismail, K. L. Yau

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Future communication networks require devices that are able to work on a single platform but support heterogeneous operations which lead to service diversity and functional flexibility. This paper proposes two cognitive mechanisms termed cognitive hybrid function which is applied in multiple broadband user terminals in order to maintain reliable connectivity and preventing unnecessary interferences. By employing such mechanisms especially for future hyper-dense network, we can observe their performances in terms of optimized speed and power saving efficiency. Results were obtained from several empirical laboratory studies. It was found that selecting reliable network had shown a better optimized speed performance up to 37% improvement as compared without such function. In terms of power adjustment, our evaluation of this mechanism can reduce the power to 5dB while maintaining the same level of throughput at higher power performance. We also discuss the issues impacting future telecommunication standards whenever such devices get in place.

Keywords: dense network, intelligent network selection, multiple networks, transmit power adjustment

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Authors: Elise Machline

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In the late 1980’s, sustainable urban development emerged in Europe. Sustainable neighborhoods are one attempt to implement sustainable urban energy planning in the city. So, for twenty years, projects of sustainable neighborhoods (or ‘eco-neighborhoods’) have emerged in Europe. Debates about sustainability no longer restrict it to environmental concerns (to limit greenhouse gas emissions), but rather extend to the economic and social dimensions. A growing number of empirical studies demonstrate that sustainable urbanism yield rental/sale premia, as well as higher occupancy rates and thus higher asset values. For example, European eco neighborhood projects usually focus on the middle to upper classes, given the costs involved in renting or buying the dwellings built in such projects. As a result sustainable residential buildings are not affordable and their construction tends to have a gentrifying effect. An increasing number of countries are institutionalizing green strategies for affordable housing. In France, the sustainable neighborhoods ‘ecoquartier’ must meet environmental performance criteria, have a potential for economic development and, provide social and functional diversity. The issue of social diversity trough the provision of affordable housing has emerged as a dimension of public housing policies. Thus, the ecoquartier residential buildings must be both energy efficient and affordable. Through the Parisian example our study considers how the concept of social diversity and other elements of sustainability are illustrated in the ecoquartiers and whether the authorities have been able to avoid gentrification when implementing a sustainable urban policy.

Keywords: sustainable neighborhoods, social diversity, social housing policies, green buildings

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Authors: Mehdi Moeinaddini, Zohreh Asadi-Shekari, Muhammad Zaly Shah, Amran Hamzah

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Currently, planners try to have more green travel options to decrease economic, social and environmental problems. Therefore, this study tries to find significant urban travel factors to be used to increase the usage of alternative urban travel modes. This paper attempts to identify the relationship between prominent urban mobility indicators and daily trips by public transport in 30 cities from various parts of the world. Different travel modes, infrastructures and cost indicators were evaluated in this research as mobility indicators. The results of multi-linear regression analysis indicate that there is a significant relationship between mobility indicators and the daily usage of public transport.

Keywords: green travel modes, urban travel indicators, daily trips by public transport, multi-linear regression analysis

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Authors: K. Y. Chen, H. Chua, C. W. Kan

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In this study, we will analyze Germany’s environmental situation such as water and air quality and review its environmental policy. In addition, we will collect the yearly environmental data as well as information concerning public environmental investment. Based on the data collect, we try to find out the relationship between public environmental investment and sustainable development in Germany. In addition, after comparing the trend of environmental quality and situation of environmental policy and investment, we may have some conclusions and learnable aspects to refer to. Based upon the data collected, it was revealed that Germany has established a well-developed institutionalization of environmental education. And the ecological culture at school is dynamic and continuous renewal. The booming of green markets in Germany is a very successful experience for learning. The green market not only creates a number of job opportunities, but also helps the government to improve and protect the environment. Acknowledgement: Authors would like to thank the financial support from the Hong Kong Polytechnic University for this work.

Keywords: Germany, public environmental investment, environment quality, sustainable development

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Authors: Samy M. Shaban, Ismail Aiad, Mohamed M. El-Sukkary, E. A. Soliman, Moshira Y. El-Awady

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In situ and green synthesis of cubic and spherical silver nanoparticles were developed using sun light as reducing agent in the presence of newly prepared cationic surfactant which acting as capping agents. The morphology of prepared silver nanoparticle was estimated by transmission electron microscope (TEM) and the size distribution determined by dynamic light scattering (DLS). The hydrophobic chain length of the prepared surfactant effect on the stability of the prepared silver nanoparticles as clear from zeta-potential values. Also by increasing chain length of the used capping agent the amount of formed nanoparticle increase as indicated by increasing the absorbance. Both prepared surfactants and surfactants capping silver nanoparticles showed high antimicrobial activity against gram positive and gram-negative bacteria.

Keywords: photosynthesis, hexaonal shapes, zetapotential, biological activity

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Authors: Mehrdad Shahrbanozadeh, Gholam Abbas Barani, Saeed Shojaee

Abstract:

In this study, a finite element (Seep3D model) and an artificial neural network (ANN) model were developed to simulate flow through dam foundation. Seep3D model is capable of simulating three-dimensional flow through a heterogeneous and anisotropic, saturated and unsaturated porous media. Flow through the Shahid Abbaspour dam foundation has been used as a case study. The FEM with 24960 triangular elements and 28707 nodes applied to model flow through foundation of this dam. The FEM being made denser in the neighborhood of the curtain screen. The ANN model developed for Shahid Abbaspour dam is a feedforward four layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning. The water level elevations of the upstream and downstream of the dam have been used as input variables and the piezometric heads as the target outputs in the ANN model. The two models are calibrated and verified using the Shahid Abbaspour’s dam piezometric data. Results of the models were compared with those measured by the piezometers which are in good agreement. The model results also revealed that the ANN model performed as good as and in some cases better than the FEM.

Keywords: seepage, dam foundation, finite element method, neural network, seep 3D model

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Authors: Farrukh Jamil, Ala'A H. Al-Muhtaseb, Lamya Al-Haj, Mohab A. Al-Hinai

Abstract:

Environmental problems and the security of energy supply have motivated the attention in the expansion of alternatives for fossil based fuels. Biomass has been recognized as a capable resource because it is plentifully available and in principle carbon dioxide neutral. Present study focuses on utilization date seeds oil for synthesizing high value fuels formulations such as green diesel and jet fuel. The hydrodeoxygenation of date seeds oil occurred to be highly efficient at following operating conditions temperature 300°C pressure 10bar with continuous stirring at 500 rpm. Products characterization revealed the efficiency of hydrodeoxygenation by formation of linear hydrocarbons (paraffin) in larger fraction. Based on the type of components in product oil it was calculated that maximum fraction lies within the range of green diesel 72.78 % then jet fuel 28.25 % by using Pt/C catalyst. It can be concluded that waste date seeds oil has potential to be used for obtaining high value products.

Keywords: date seeds, hydrodeoxygenation, paraffin, deoxygenation

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Authors: Julien Romieux, Fabio Verdicchio

Abstract:

Wireless Sensor Networks (WSNs), which sense environmental data with battery-powered nodes, require multi-hop communication. This power-demanding task adds an extra workload that is unfairly distributed across the network. As a result, nodes run out of battery at different times: this requires an impractical individual node maintenance scheme. Therefore we investigate a new Cooperative Sensing approach that extends the WSN operational life and allows a more practical network maintenance scheme (where all nodes deplete their batteries almost at the same time). We propose a novel cooperative algorithm that derives a piecewise representation of the sensed signal while controlling approximation accuracy. Simulations show that our algorithm increases WSN operational life and spreads communication workload evenly. Results convey a counterintuitive conclusion: distributing workload fairly amongst nodes may not decrease the network power consumption and yet extend the WSN operational life. This is achieved as our cooperative approach decreases the workload of the most burdened cluster in the network.

Keywords: cooperative signal processing, signal representation and approximation, power management, wireless sensor networks

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Authors: John Dorrell, Matthew Ambrosia, Abilash

Abstract:

This paper employs econometric analysis to quantify the potential profit wind farms can receive by allocating excess wind energy to power bitcoin mining machines. Cryptocurrency mining consumes a substantial amount of electricity worldwide, and wind energy produces a significant amount of energy that is lost because of the intermittent nature of the resource. Supply does not always match consumer demand. By combining the weaknesses of these two technologies, we can improve efficiency and a sustainable path to mine cryptocurrencies. This paper uses historical wind energy from the ERCOT network in Texas and cryptocurrency data from 2000-2021, to create 4-year return on investment projections. Our research model incorporates the price of bitcoin, the price of the miner, the hash rate of the miner relative to the network hash rate, the block reward, the bitcoin transaction fees awarded to the miners, the mining pool fees, the cost of the electricity and the percentage of time the miner will be running to demonstrate that wind farms generate enough excess energy to mine bitcoin profitably. Excess wind energy can be used as a financial battery, which can utilize wasted electricity by changing it into economic energy. The findings of our research determine that wind energy producers can earn profit while not taking away much if any, electricity from the grid. According to our results, Bitcoin mining could give as much as 1347% and 805% return on investment with the starting dates of November 1, 2021, and November 1, 2022, respectively, using wind farm curtailment. This paper is helpful to policymakers and investors in determining efficient and sustainable ways to power our economic future. This paper proposes a practical solution for the problem of crypto mining energy consumption and creates a more sustainable energy future for Bitcoin.

Keywords: bitcoin, mining, economics, energy

Procedia PDF Downloads 37