Search results for: fault location analysis

Authors: Hesham Hamdy Abdelmohsen, Ahmed Shawky Abdul Azizb, Mona Fawzy Aldaghma

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Helical piles have earned considerable attention as an effective deep foundation alternative due to their rapid installation process and their dual purpose in compression and tension. These piles find common uses as foundations for structures like solar panels, wind turbines, offshore platforms, and some kinds of retaining walls. These structures usually transfer different combinations of loads to their helical-pile foundations in the form of axial and lateral loads. Extensive research has been conducted to investigate and understand the behavior of these piles under the influence of either axial or lateral loads. However, the impacts of loading patterns that may act on the helical piles as combinations of axial compression and lateral loads still need more efforts of research work. This paper presents the results of an experimental (Lab tests) and numerical (PLAXIS-3D) study performed on vertical helical-pile groups under the action of combined loads as axial compression (bearing loads), acting successively with lateral (horizontal) loads. The study aims to clarify the effects of key factors, like helix location and direction of lateral load, on the lateral capacity of helical-pile groups and, consequently, on group efficiency. Besides the variation of helix location and lateral load direction, three patterns of successive bearing combined loads were considered, in which the axial vertical compression load was either zero, V1 or V2, whereas the lateral horizontal loads were varied under each vertical compression load. The study concluded that the lateral capacity of the helical-pile group is significantly affected by helix location within the length of the pile shaft. The optimal lateral performance is achieved with helices at a depth ratio of H/L = 0.4. Furthermore, groups of rectangular plan distribution exhibit greater lateral capacity if subjected to lateral horizontal load in the direction of its long axis. Additionally, the research emphasizes that the presence of vertical compression loading can enhance the lateral capacity of the group. This enhancement depends on the value of the vertical compression load, lateral load direction, and helix location, which highlights the complex interaction effect of these factors on the efficiency of helical-pile groups.

Keywords: helical piles, experimental, numerical, lateral loading, group efficiency

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Authors: Amrita Anil Agashe, Sumant Tapas, Ajay Verma Yogesh Sonavane, Sourabh Yeravar

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Due to advancement in MEMS technology today wireless sensors network has gained a lot of importance. The wide range of its applications includes environmental and habitat monitoring, object localization, target tracking, security surveillance etc. Wireless sensor networks consist of tiny sensor devices called as motes. The constrained computation power, battery power, storage capacity and communication bandwidth of the tiny motes pose challenging problems in the design and deployment of such systems. In this paper, we propose a ubiquitous framework for Real-Time Tracking, Sensing and Management System using IITH motes. Also, we explain the algorithm that we have developed for location management in wireless sensor networks with the aspect of mobility. Our developed framework and algorithm can be used to detect emergency events and safety threats and provides warning signals to handle the emergency.

Keywords: mobility management, motes, multihop, wireless sensor networks

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Authors: Farhad Nouparast

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For more production we need more capital formation. Capital formation in each country should be based on comparative advantages in different economic sectors due to the different production possibility curves. In regional planning, recognizing the relative advantages and consequently investing in more production requires identifying areas with the necessary capabilities and location of each region compared to other regions. In this article, ranking of Iran's provinces is done according to the specific and given variables as the best investment position in agricultural activity. So we can provide the necessary background for investment analysis in different regions of the country to formulate national and regional planning and execute investment projects. It is used factor analysis technique and numerical taxonomy analysis to do this in thisarticle. At first, the provinces are homogenized and graded according to the variables using cross-sectional data obtained from the agricultural census and population and housing census of Iran as data matrix. The results show that which provinces have the most potential for capital formation in agronomy sub-sector. Taxonomy classifies organisms based on similar genetic traits in biology and botany. Numerical taxonomy using quantitative methods controls large amounts of information and get the number of samples and categories and take them based on inherent characteristics and differences indirectly accommodates. Numerical taxonomy is related to multivariate statistics.

Keywords: Capital Formation, Factor Analysis, Multivariate statistics, Numerical Taxonomy Analysis, Production, Ranking, Spatial Planning

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

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

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

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Authors: M. A. Adejumobi, J. O. Ojediran

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The aim of irrigation is to recharge the available water in the soil. Quality of irrigation water is essential for the yield and quality of crops produced, maintenance of soil productivity and protection of the environment. The analysis of irrigation water arises as a need to know the impact of irrigation water on the yield of crops, the effect, and the necessary control measures to rectify the effect of this for optimum production and yield of crops. This study was conducted to assess the quality of irrigation water with its performance on crop planted, in Josepdam irrigation scheme Bacita, Nigeria. Field visits were undertaken to identify and locate water supply sources and collect water samples from these sources; X1 Drain, Oshin, River Niger loop and Ndafa. Laboratory experiments were then undertaken to determine the quality of raw water from these sources. The analysis was carried for various parameters namely; physical and chemical analyses after water samples have been taken from four sources. The samples were tested in laboratory. Results showed that the raw water sources shows no salinity tendencies with SAR values less than 1me/l and Ecvaules at Zero while the pH were within the recommended range by FAO, there are increase in potassium and sulphate content contamination in three of the location. From this, it is recommended that there should be proper monitoring of the scheme by conducting analysis of water and soil in the environment, preferable test should be carried out at least one year to cover the impact of seasonal variations and to determine the physical and chemical analysis of the water used for irrigation at the scheme.

Keywords: irrigation, salinity, raw water quality, scheme

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Authors: Slavka Zeković, Miodrag Vujošević, Tamara Maričić

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The paper provides a comprehensive analysis of the sustainable development in the Belgrade Metropolitan Region - BMA (level NUTS 2) preliminary evaluating the three chosen components: 1) economic growth and developmental changes; 2) competitiveness; and 3) territorial concentration and industrial specialization. First, we identified the main results of development changes and economic growth by applying Shift-share analysis on the metropolitan level. Second, the empirical evaluation of competitiveness in the BMA is based on the analysis of absolute and relative values of eight indicators by Spider method. Paper shows that the consideration of the national share, industrial mix and metropolitan/regional share in total Shift share of the BMA, as well as economic/functional specialization of the BMA indicate very strong process of deindustrialization. Allocative component of the BMA economic growth has positive value, reflecting the above-average sector productivity compared to the national average. Third, the important positive role of metropolitan/regional component in decomposition of the BMA economic growth is highlighted as one of the key results. Finally, comparative analysis of the industrial territorial concentration in the BMA in relation to Serbia is based on location quotient (LQ) or Balassa index as a valid measure. The results indicate absolute and relative differences in decrease of industry territorial concentration as well as inefficiency of utilizing territorial capital in the BMA. Results are important for the increase of regional competitiveness and territorial distribution in this area as well as for improvement of sustainable metropolitan and sector policies, planning and governance on this level.

Keywords: Belgrade Metropolitan Area (BMA), comprehensive analysis / evaluation, economic growth, competitiveness, sustainable development

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Authors: Amitha Puranik, V. S. Binu, Seena Biju

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Missing data is a common problem in spatial analysis especially at the aggregate level. Missing can either occur in covariate or in response variable or in both in a given location. Many missing data techniques are available to estimate the missing data values but not all of these methods can be applied on spatial data since the data are autocorrelated. Hence there is a need to develop a method that estimates the missing values in both response variable and covariates in spatial data by taking account of the spatial autocorrelation. The present study aims to develop a model to estimate the missing data points at the aggregate level in spatial data by accounting for (a) Spatial autocorrelation of the response variable (b) Spatial autocorrelation of covariates and (c) Correlation between covariates and the response variable. Estimating the missing values of spatial data requires a model that explicitly account for the spatial autocorrelation. The proposed model not only accounts for spatial autocorrelation but also utilizes the correlation that exists between covariates, within covariates and between a response variable and covariates. The precise estimation of the missing data points in spatial data will result in an increased precision of the estimated effects of independent variables on the response variable in spatial regression analysis.

Keywords: spatial regression, missing data estimation, spatial autocorrelation, simulation analysis

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Authors: Angela Maria Fasnacht

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Detection of anomalies due to contaminants’ presence, also known as early detection systems in water treatment plants, has become a critical point that deserves an in-depth study for their improvement and adaptation to current requirements. The design of these systems requires a detailed analysis and processing of the data in real-time, so it is necessary to apply various statistical methods appropriate to the data generated, such as Spearman’s Correlation, Factor Analysis, Cross-Correlation, and k-fold Cross-validation. Statistical analysis and methods allow the evaluation of large data sets to model the behavior of variables; in this sense, statistical treatment or analysis could be considered a vital step to be able to develop advanced models focused on machine learning that allows optimized data management in real-time, applied to early detection systems in water treatment processes. These techniques facilitate the development of new technologies used in advanced sensors. In this work, these methods were applied to identify the possible correlations between the measured parameters and the presence of the glyphosate contaminant in the single-pass system. The interaction between the initial concentration of glyphosate and the location of the sensors on the reading of the reported parameters was studied.

Keywords: glyphosate, emergent contaminants, machine learning, probes, sensors, predictive

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Authors: Nor Asrina Binti Ramlee

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Voltage sag, voltage swell, high-frequency noise and voltage transients are kinds of disturbances in power quality. They are also known as power quality events. Equipment used in the industry nowadays has become more sensitive to these events with the increasing complexity of equipment. This leads to the importance of distributing clean power quality to the consumer. To provide better service, the best analysis on power quality is very vital. Thus, this paper presents the events detection focusing on voltage sag and swell. The method is developed by applying time domain signal analysis using wavelet transform approach in MATLAB. Four types of mother wavelet namely Haar, Dmey, Daubechies, and Symlet are used to detect the events. This project analyzed real interrupted signal obtained from 22 kV transmission line in Skudai, Johor Bahru, Malaysia. The signals will be decomposed through the wavelet mothers. The best mother is the one that is capable to detect the time location of the event accurately.

Keywords: power quality, voltage sag, voltage swell, wavelet transform

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Authors: Paula Simões, Isabel Natário

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This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context.

Keywords: spatial data analysis, spatial econometrics, Bayesian hierarchical models, count data

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Authors: Susan Diamond

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Machine Learning workloads have traditionally been run in high-performance computing (HPC) environments, where users log in to dedicated machines and utilize the attached GPUs to run training jobs on huge datasets. Training of large neural network models is very resource intensive, and even after exploiting parallelism and accelerators such as GPUs, a single training job can still take days. Consequently, the cost of hardware is a barrier to entry. Even when upfront cost is not a concern, the lead time to set up such an HPC environment takes months from acquiring hardware to set up the hardware with the right set of firmware, software installed and configured. Furthermore, scalability is hard to achieve in a rigid traditional lab environment. Therefore, it is slow to react to the dynamic change in the artificial intelligent industry. Watson Deep Learning as a service, a cloud-based deep learning platform that mitigates the long lead time and high upfront investment in hardware. It enables robust and scalable sharing of resources among the teams in an organization. It is designed for on-demand cloud environments. Providing a similar user experience in a multi-tenant cloud environment comes with its own unique challenges regarding fault tolerance, performance, and security. Watson Deep Learning as a service tackles these challenges and present a deep learning stack for the cloud environments in a secure, scalable and fault-tolerant manner. It supports a wide range of deep-learning frameworks such as Tensorflow, PyTorch, Caffe, Torch, Theano, and MXNet etc. These frameworks reduce the effort and skillset required to design, train, and use deep learning models. Deep Learning as a service is used at IBM by AI researchers in areas including machine translation, computer vision, and healthcare. 

Keywords: deep learning, machine learning, cognitive computing, model training

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Authors: Jonghoon Chun, Insung Kim, Jonghyun Lim, Gun Ro

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We believe that it is possible to provide a solution to reduce patient safety accidents by displaying correct medical records and prescription information through interactive patient identification. Our system is based on the use of smart bands worn by patients and these bands communicate with the hybrid gateways which understand both BLE and Wifi communication protocols. Through the convergence of low-power Bluetooth (BLE) and hybrid gateway technology, which is one of short-range wireless communication technologies, we implement ‘Intelligent Patient Identification and Location Tracking System’ to prevent medical malfunction frequently occurring in medical institutions. Based on big data and IOT technology using MongoDB, smart band (BLE, NFC function) and hybrid gateway, we develop a system to enable two-way communication between medical staff and hospitalized patients as well as to store locational information of the patients in minutes. Based on the precise information provided using big data systems, such as location tracking and movement of in-hospital patients wearing smart bands, our findings include the fact that a patient-specific location tracking algorithm can more efficiently operate HIS (Hospital Information System) and other related systems. Through the system, we can always correctly identify patients using identification tags. In addition, the system automatically determines whether the patient is a scheduled for medical service by the system in use at the medical institution, and displays the appropriateness of the medical treatment and the medical information (medical record and prescription information) on the screen and voice. This work was supported in part by the Korea Technology and Information Promotion Agency for SMEs (TIPA) grant funded by the Korean Small and Medium Business Administration (No. S2410390).

Keywords: BLE, hybrid gateway, patient identification, IoT, safety management, smart band

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Authors: Reza Behboodian

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Monitoring the structural health and diagnosing their damage in the early stages has always been one of the topics of concern. Nowadays, research on structural damage detection methods based on vibration analysis is very extensive. Moreover, these methods can be used as methods of permanent and timely inspection of structures and prevent further damage to structures. Non-destructive methods are the low-cost and economical methods for determining the damage of structures. In this research, a non-destructive method for detecting and identifying the failure location in structures based on dynamic responses resulting from time history analysis is proposed. When the structure is damaged due to the reduction of stiffness, and due to the applied loads, the displacements in different parts of the structure were increased. In the proposed method, the damage position is determined based on the calculation of the strain energy difference in each member of the damaged structure and the healthy structure at any time. Defective members of the structure are indicated by the amount of strain energy relative to the healthy state. The results indicated that the proper accuracy and performance of the proposed method for identifying failure in structures.

Keywords: failure, time history analysis, dynamic response, strain energy

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Authors: Usama Abdulwahab, Mohammed Wahab

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This paper presents the application of uncapacitated facility location problems (UFLP) and 1-median problems to support decision making in blood supply chain networks. A plethora of factors make blood supply-chain networks a complex, yet vital problem for the regional blood bank. These factors are rapidly increasing demand; criticality of the product; strict storage and handling requirements; and the vastness of the theater of operations. As in the UFLP, facilities can be opened at any of $m$ predefined locations with given fixed costs. Clients have to be allocated to the open facilities. In classical location models, the allocation cost is the distance between a client and an open facility. In this model, the costs are the allocation cost, transportation costs, and inventory costs. In order to address this problem the median algorithm is used to analyze inventory, evaluate supply chain status, monitor performance metrics at different levels of granularity, and detect potential problems and opportunities for improvement. The Euclidean distance data for some Ontario cities (demand nodes) are used to test the developed algorithm. Sitation software, lagrangian relaxation algorithm, and branch and bound heuristics are used to solve this model. Computational experiments confirm the efficiency of the proposed approach. Compared to the existing modeling and solution methods, the median algorithm approach not only provides a more general modeling framework but also leads to efficient solution times in general.

Keywords: approximate dynamic programming, facility location, perishable product, inventory model, blood platelet, P-median problem

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Authors: Mohammad Mokhtari, Mehdi Masoodi, Parvaneh Faridi

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history of tsunami generating earthquakes along the Makran Subduction Zone provides evidence of the potential tsunami hazard for the whole coastal area. In comparison with other subduction zone in the world, the Makran region of southern Pakistan and southeastern Iran remains low seismicity. Also, it is one of the least studied area in the northwest of the Indian Ocean regarding tsunami studies. We present a review of studies dealing with the historical /and ongoing palaeotsunamis supported by IGCP of UNESCO in the Makran Subduction Zone. The historical tsunami presented here includes about nine tsunamis in the Makran Subduction Zone, of which over 7 tsunamis occur in the eastern Makran. Tsunami is not as common in the western Makran as in the eastern Makran, where a database of historical events exists. The historically well-documented event is related to the 1945 earthquake with a magnitude of 8.1moment magnitude and tsunami in the western and eastern Makran. There are no details as to whether a tsunami was generated by a seismic event before 1945 off western Makran. But several potentially large tsunamigenic events in the MSZ before 1945 occurred in 325 B.C., 1008, 1483, 1524, 1765, 1851, 1864, and 1897. Here we will present new findings from a historical point of view, immediately, we would like to emphasize that the area needs to be considered with higher research investigation. As mentioned above, a palaeotsunami (geological evidence) is now being planned, and here we will present the first phase result. From a risk point of view, the study shows as preliminary achievement within 20 minutes the wave reaches to Iranian as well Pakistan and Oman coastal zone with very much destructive tsunami waves capable of inundating destructive effect. It is important to note that all the coastal areas of all states surrounding the MSZ are being developed very rapidly, so any event would have a devastating effect on this region. Although several papers published about modelling, seismology, tsunami deposits in the last decades; as Makran is a forgotten subduction zone, more data such as the main crustal structure, fault location, and its related parameter are required.

Keywords: historical tsunami, Indian ocean, makran subduction zone, palaeotsunami

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Authors: Maeng-Hwan Hyun, Dae-Man Do, Young-Bok Choi

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Around the world, there are frequent incidents of natural disasters, such as earthquakes, tsunamis, floods, and snowstorms, as well as man made disasters such as fires, arsons, and acts of terror. These diverse and unpredictable adversities have resulted in a number of fatalities and injuries. If disaster occurrence can be assessed quickly and information such as the exact location of the disaster and evacuation routes can be provided, victims can promptly move to safe locations, minimizing losses. This paper proposes a behavior analysis method based on a nine degrees-of-freedom (9-DOF) sensor that is effective for the emergency rescue evacuation support system (ERESS), which is being researched with an objective of providing evacuation support during disasters. Based on experiments performed using the acceleration sensor and the gyroscope sensor in the 9-DOF sensor, data are analyzed for human behavior regarding stationary position, walking, running, and during emergency situation to suggest guidelines for system judgment. Using the results of the experiments performed to determine disaster occurrence, it was confirmed that the proposed method quickly determines whether a disaster has occurred.

Keywords: behavior analysis, nine degrees of freedom sensor, emergency rescue, disaster

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Authors: Tauhidur Rahman, Kasturi Bhuyan

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In the present paper, Ground Response Analysis at the Rukni irrigation project has been thoroughly investigated. Surface level seismic hazard is mainly used by the practical Engineers for designing the important structures. Surface level seismic hazard can be obtained accounting the soil factor. Structures on soft soil will show more ground shaking than the structure located on a hard soil. The Surface level ground motion depends on the type of soil. Density and shear wave velocity is different for different types of soil. The intensity of the soil amplification depends on the density and shear wave velocity of the soil. Rukni irrigation project is located in the North Eastern region of India, near the Dauki fault (550 Km length) which has already produced earthquakes of magnitude (Mw= 8.5) in the past. There is a probability of a similar type of earthquake occuring in the future. There are several faults also located around the project site. There are 765 recorded strong ground motion time histories available for the region. These data are used to determine the soil amplification factor by incorporation of the engineering properties of soil. With this in view, three of soil bore holes have been studied at the project site up to a depth of 30 m. It has been observed that in Soil bore hole 1, the shear wave velocity vary from 99.44 m/s to 239.28 m/s. For Soil Bore Hole No 2 and 3, shear wave velocity vary from 93.24 m/s to 241.39 m/s and 93.24m/s to 243.01 m/s. In the present work, surface level seismic hazard at the project site has been calculated based on the Probabilistic seismic hazard approach accounting the soil factor.

Keywords: Ground Response Analysis, shear wave velocity, soil amplification, surface level seismic hazard

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Authors: Subhajit Das, Nirjhar Dhang

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Structural damage detection is a challenging work in the field of structural health monitoring (SHM). The damage detection methods mainly focused on the determination of the location and severity of the damage. Model updating is a well known method to locate and quantify the damage. In this method, an error function is defined in terms of difference between the signal measured from ‘experiment’ and signal obtained from undamaged finite element model. This error function is minimised with a proper algorithm, and the finite element model is updated accordingly to match the measured response. Thus, the damage location and severity can be identified from the updated model. In this paper, an error function is defined in terms of modal data viz. frequencies and modal assurance criteria (MAC). MAC is derived from Eigen vectors. This error function is minimized by teaching-learning-based optimization (TLBO) algorithm, and the finite element model is updated accordingly to locate and quantify the damage. Damage is introduced in the model by reduction of stiffness of the structural member. The ‘experimental’ data is simulated by the finite element modelling. The error due to experimental measurement is introduced in the synthetic ‘experimental’ data by adding random noise, which follows Gaussian distribution. The efficiency and robustness of this method are explained through three examples e.g., one truss, one beam and one frame problem. The result shows that TLBO algorithm is efficient to detect the damage location as well as the severity of damage using modal data.

Keywords: damage detection, finite element model updating, modal assurance criteria, structural health monitoring, teaching learning based optimization

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Authors: Shakir Ullah

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This article reviews social science understanding to explore the challenges megaprojects face before and after implementation. It also sheds light on the problems directly and indirectly caused by mega development projects in the project implemented areas. By Using a qualitative approach such as thematic analysis, the article uses recent literature such as published articles, government reports, and books to cite examples of different mega projects worldwide. The study report that mega development projects are a necessary element of the modern-day infrastructural development process as they represent the perfect example of urban socioeconomic development. They are introduced and implemented by multinational companies with the support of state authorities to produce the common good. However, they are not devoid of their critical challenges and bring implicit and explicit problems to the targeted localities. The article takes insights from social science research for suggestions on how to reduce the challenges faced by project implementers and problems received by local people due to the fault lines of such projects.

Keywords: development, mega-projects, challenges, problems

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Authors: Taegyoo Woo, Jong Kang Park, Jong Tae Kim

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Visible Light Communication (VLC) provides wireless communication features in illumination systems. One of the key applications is to recognize the user location by indoor illuminators such as light emitting diodes. For localization of individual receivers in these systems, we usually assume that receivers and transmitters are placed in parallel. However, it is difficult to satisfy this assumption because the receivers move randomly in real case. It is necessary to analyze the case when transmitter is not placed perfectly parallel to receiver. It is also important to identify changes on optical gain by the tilted angles and distances of them against the illuminators. In this paper, we simulate optical gain for various cases where the tilt of the receiver and the distance change. Then, we identified changing patterns of optical gains according to tilted angles of a receiver and distance. These results can help many VLC applications understand the extent of the location errors with regard to optical gains of the receivers and identify the root cause.

Keywords: visible light communication, incident angle, optical gain, light emitting diode

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Authors: Daramola Japheth, Tabiti S. Tabiti, Daramola Elizabeth Lara, Hussaini Yusuf Atulukwu

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Bida urban centre is faced with solid waste management problems which are evident in the processes of waste generation, onsite storage, collection, transfer and transport, processing and disposal of solid waste. As a result of this the urban centre is defaced with litters of garbage and offensive odours due to indiscriminate dumping of refuse within the neighborhood. The partial removal of the fuel subsidy by the Federal Government in January 2012 leads to the formation of Subsidy Reinvestment Programmes (SURE-P), the Federal Government’s share is 41 per cent of the savings while the States and Local Government shared the remaining 59 percent. The SURE-P Committee in carrying out the mandate entrusted upon it by the President by identifying few critical infrastructure and social Safety nets that will ameliorate the sufferings of Nigerians. Waste disposal programme as an aspect of Solid waste management is one of the areas of focus for Niger State SURE-programmes incorporated under Niger State Environmental Protection Agency. The emergence of this programme as related to waste management in Bida has left behind a huge refuse spots along major corridors leading to a serious state of mess. Major roads within the LGA is now turned to dumping site, thereby obstructing traffic movements, while the aesthetic nature of the town became something else with offensive odours all over. This paper however wishes to underscore the use of geographical Information System in identifying solid waste sports towards effective solid waste management in the Bida urban centre. The paper examined the spatial location of dumping points and its impact on the environment. Hand held Global Position System was use to pick the dumping points location; where a total number of 91 dumping points collected were uploaded to ArcGis 10.2 for analysis. Interview method was used to derive information from households living near the dumping site. It was discovered that the people now have to cope with offensive odours, rodents invasion, dog and cats coming around the house as a result of inadequate and in prompt collection of waste around the neighborhood. The researchers hereby recommend that more points needs to be created with prompt collections of waste within the neighborhood by the necessary SURE - P agencies.

Keywords: dumping site, neighborhood, refuse, waste

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Authors: Fouzi Harrou, Ying Sun, Sofiane Khadraoui

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Anomaly detection based on Principal Component Analysis (PCA) was studied intensively and largely applied to multivariate processes with highly cross-correlated process variables. Monitoring metrics such as the Hotelling's T2 and the Q statistics are usually used in PCA-based monitoring to elucidate the pattern variations in the principal and residual subspaces, respectively. However, these metrics are ill suited to detect small faults. In this paper, the Exponentially Weighted Moving Average (EWMA) based on the Q and T statistics, T2-EWMA and Q-EWMA, were developed for detecting faults in the process mean. The performance of the proposed methods was compared with that of the conventional PCA-based fault detection method using synthetic data. The results clearly show the benefit and the effectiveness of the proposed methods over the conventional PCA method, especially for detecting small faults in highly correlated multivariate data.

Keywords: data-driven method, process control, anomaly detection, dimensionality reduction

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Authors: Erika De Finis, Paola Gattinoni, Laura Scesi

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Massive rock avalanches formed some of the largest landslide deposits on Earth and they represent one of the major geohazards in high-relief mountains. This paper interprets a very large sedimentary fan (the Sernio fan, Valtellina, Northern Italy), located 20 Km SW from Val Pola Rock avalanche (1987), as the deposit of a partial collapse of a Deep Seated Gravitational Slope Deformation (DSGSD), afterwards eroded and buried by debris flows. The proposed emplacement sequence has been reconstructed based on geomorphological, structural and mechanical evidences. The Sernio fan is actually considered anomalous with reference to the very high ratio between the fan area (about 4.5km2) and the basin area (about 3km2). The morphology of the fan area is characterised by steep slopes (dip about 20%) and the fan apex is extended for 1.8 km inside the small catchment basin. This sedimentary fan was originated by a landslide that interested a part of a large deep-seated gravitational slope deformation, involving a wide area of about 55 km². The main controlling factor is tectonic and it is related to the proximity to regional fault systems and the consequent occurrence of fault weak rocks (GSI locally lower than 10 with compressive stress lower than 20MPa). Moreover, the fan deposit shows sedimentary evidences of recent debris flow events. The best current explanation of the Sernio fan involves an initial failure of some hundreds of Mm3. The run-out was quite limited because of the morphology of Valtellina’s valley floor, and the deposit filled the main valley forming a landslide dam, as confirmed by the lacustrine deposits detected upstream the fan. Nowadays the debris flow events represent the main hazard in the study area.

Keywords: anomalous sedimentary fans, deep seated gravitational slope deformation, Italy, rock avalanche

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Authors: Khondaker Sakil Ahmed, Ang Kok Keng, Shah Md Muniruzzaman

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Spherical and Berkovich indentation tests are carried out numerically using finite element method for uniformly dispersed Carbon Nanotube (CNT) in the polymer matrix in which perfectly bonded CNT/matrix interface is considered. The Large strain elasto-plastic analysis is performed to investigate the actual scenario of nanoindentation test. This study investigates how the addition of CNT in polymer matrix influences the mechanical properties like hardness, elastic modulus of the nanocomposite. Since the wall thickness to radius ratio (t/r) is significantly small for SWCNT there is a huge possibility of lateral buckling which is a function of the location of indentation tip as well as the mechanical properties of matrix. Separate finite element models are constructed to compare the result with Berkovich indentation. This study also investigates the buckling behavior of different nanotube in a different polymer matrix.

Keywords: carbon nanotube, elasto-plastic, finite element model, nano-indentation

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Authors: Larifah Mohd Sidik, Anuar Kasa

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In recent years, the demands for raw water are increasing along with the growth of the economy and population. Hence, the need for the construction and operation of dams is one of the solutions for the management of water resources problems. The stability of the embankment should be taken into consideration to evaluate the safety of retaining water. The safety of the dam is mostly based on numerous measurable components, for instance, seepage flowrate, pore water pressure and deformation of the embankment. Seepage and slope stability is the primary and most important reason to ascertain the overall safety behavior of the dams. This research study was conducted to evaluate static condition seepage and slope stability performances of Batu dam which is located in Kuala Lumpur capital city. The numerical solution Geostudio-2012 software was employed to analyse the seepage using finite element method, SEEP/W and slope stability using limit equilibrium method, SLOPE/W for three different cases of reservoir level operations; normal and flooded condition. Results of seepage analysis using SEEP/W were utilized as parental input for the analysis of SLOPE/W. Sensitivity analysis on hydraulic conductivity of material was done and calibrated to minimize the relative error of simulation SEEP/W, where the comparison observed field data and predicted value were also carried out. In seepage analysis, such as leakage flow rate, pore water distribution and location of a phreatic line are determined using the SEEP/W. The result of seepage analysis shows the clay core effectively lowered the phreatic surface and no piping failure is shown in the result. Hence, the total seepage flux was acceptable and within the permissible limit.

Keywords: earth dam, dam safety, seepage, slope stability, pore water pressure

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Authors: Tapan Jain, Davender Singh Saini

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Clustering is a useful mechanism in wireless sensor networks which helps to cope with scalability and data transmission problems. The basic aim of our research work is to provide efficient clustering using Hierarchical agglomerative clustering (HAC). If the distance between the sensing nodes is calculated using their location then it’s quantitative HAC. This paper compares the various agglomerative clustering techniques applied in a wireless sensor network using the quantitative data. The simulations are done in MATLAB and the comparisons are made between the different protocols using dendrograms.

Keywords: routing, hierarchical clustering, agglomerative, quantitative, wireless sensor network

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Authors: Lei Zhou, Chao Li, Ruiqi Ren, Dan Li, Yali Wang, Daxin Ni, Zijian Feng, Qun Li

Abstract:

Background: Since the first human infection with avian influenza A(H7N9) case was reported in China on 31 March 2013, five epidemics have been observed in China through February 2013 and September 2017. Though the overall mortality rate of H7N9 has remained as high as around 40% throughout the five epidemics, the specific mortality rate in Mainland China varied by provinces. We conducted a descriptive analysis of mortality rates of H7N9 cases to explore the various severity features of the disease and then to provide clues of further analyses of potential factors associated with the severity of the disease. Methods: The data for analysis originated from the National Notifiable Infectious Disease Report and Surveillance System (NNIDRSS). The surveillance system and identification procedure for H7N9 infection have not changed in China since 2013. The definition of a confirmed H7N9 case is as same as previous reports. Mortality rates of H7N9 cases are described and compared by time and location of reporting, age and sex, and genetic features of H7N9 virus strains. Results: The overall mortality rate, the male and female specific overall rates of H7N9 is 39.6% (608/1533), 40.3% (432/1072) and 38.2% (176/461), respectively. There was no significant difference between the mortality rates of male and female. The age-specific mortality rates are significantly varied by age groups (χ²=38.16, p < 0.001). The mortality of H7N9 cases in the age group between 20 and 60 (33.17%) and age group of over 60 (51.16%) is much higher than that in the age group of under 20 (5.00%). Considering the time of reporting, the mortality rates of cases which were reported in the first (40.57%) and fourth (42.51%) quarters of each year are significantly higher than the mortality of cases which were reported in the second (36.02%) and third (27.27%) quarters (χ²=75.18, p < 0.001). The geographic specific mortality rates vary too. The mortality rates of H7N9 cases reported from the Northeast China (66.67%) and Westeast China (56.52%) are significantly higher than that of H7N9 cases reported from the remained area of mainland China. The mortality rate of H7N9 cases reported from the Central China is the lowest (34.38%). The mortality rates of H7N9 cases reported from rural (37.76%) and urban (38.96%) areas are similar. The mortality rate of H7N9 cases infected with the highly pathogenic avian influenza A(H7N9) virus (48.15%) is higher than the rate of H7N9 cases infected with the low pathogenic avian influenza A(H7N9) virus (37.57%), but the difference is not statistically significant. Preliminary analyses showed that age and some clinical complications such as respiratory failure, heart failure, and septic shock could be potential risk factors associated with the death of H7N9 cases. Conclusions: The mortality rates of H7N9 cases varied by age, sex, time of reporting and geographical location in mainland China. Further in-depth analyses and field investigations of the factors associated with the severity of H7N9 cases need to be considered.

Keywords: H7N9 virus, Avian Influenza, mortality, China

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Authors: Rıza Gürhan Korkut, Metin Çelik, Süleyman Özkaynak

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The early-stage design and development projects for the freight village initiatives require a comprehensive analysis of both qualitative and quantitative data. Considering the literature review on structural and operational management requirements, this study proposed an original taxonomy on criterion structure to assess freight village conceptualization. The potential challenges and uncertainties of the developed taxonomy are extended. Besides requirement analysis, this study is also expected to contribute to forthcoming research on benchmarking of freight villages in different regions. The methodology used in this research is a systematic review on several articles as per their modelling approaches, sustainability, entities and decisions made together with the uncertainties and features of their models taken into consideration. The major findings of the study that are the categories for assessing the projects attributes on their environmental, socio-economical, accessibility and location aspects.

Keywords: logistics centers, freight village, operational management, taxonomy

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Authors: DEVASHISH KHULBE, MANU PATHAK

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The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-temporal popularity of various cuisines can be analyzed. Tracking the popularity of food types and retail locations across space and time can also be useful for business owners and restaurant investors. In this work, we present an approach using off-the shelf machine learning techniques to identify trends and popularity of cuisine types in an area using geo-tagged data from social media, Google images and Yelp. After adjusting for time, we use the Kernel Density Estimation to get hot spots across the location and model the dependencies among food cuisines popularity using Bayesian Networks. We consider the Manhattan borough of New York City as the location for our analyses but the approach can be used for any area with social media data and information about retail businesses.

Keywords: Web Mining, Geographic Information Systems, Business popularity, Spatial Data Analyses

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Authors: H. S. Sathish, H. S. Jagadeesh, Skanda Kumar

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Journey time and delay study is used to evaluate the quality of service, the travel time and study can also be used to evaluate the quality of traffic movement along the route and to determine the location types and extent of traffic delays. Components of delay are boarding and alighting, issue of tickets, other causes and distance between each stops. This study investigates the total journey time required to travel along the stretch and the influence the delays. The route starts from Kempegowda Bus Station to Yelahanka Satellite Station of Bangalore City. The length of the stretch is 16.5 km. Modal split analysis has been done for this stretch. This stretch has elevated highway connecting to Bangalore International Airport and the extension of metro transit stretch. From the regression analysis of total journey time it is affected by delay due to boarding and alighting moderately, Delay due to issue of tickets affects the journey time to a higher extent. Some of the delay factors affecting significantly the journey time are evident from F-test at 10 percent level of confidence. Along this stretch work trips are more prevalent as indicated by O-D study. Modal shift analysis indicates about 70 percent of commuters are ready to shift from current system to Metro Rail System. Metro Rail System carries maximum number of trips compared to private mode. Hence Metro is a highly viable choice of mode for Bangalore Metropolitan City.

Keywords: delay, journey time, modal choice, regression analysis

Procedia PDF Downloads 490