Search results for: data infrastructure

Authors: Walid Cherif

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Data mining has, over recent years, seen big advances because of the spread of internet, which generates everyday a tremendous volume of data, and also the immense advances in technologies which facilitate the analysis of these data. In particular, classification techniques are a subdomain of Data Mining which determines in which group each data instance is related within a given dataset. It is used to classify data into different classes according to desired criteria. Generally, a classification technique is either statistical or machine learning. Each type of these techniques has its own limits. Nowadays, current data are becoming increasingly heterogeneous; consequently, current classification techniques are encountering many difficulties. This paper defines new measure functions to quantify the resemblance between instances and then combines them in a new approach which is different from actual algorithms by its reliability computations. Results of the proposed approach exceeded most common classification techniques with an f-measure exceeding 97% on the IRIS Dataset.

Keywords: data mining, knowledge discovery, machine learning, similarity measurement, supervised classification

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Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

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In this paper, we focus on the importance of scalable architecture for data centers and buildings in general to help an enterprise achieve environmental sustainability. The scalable architecture helps in many ways, such as adaptability to the business and user requirements, promotes high availability and disaster recovery solutions that are cost effective and low maintenance. The scalable architecture also plays a vital role in three core areas of sustainability: economy, environment, and social, which are also known as the 3 pillars of a sustainability model. If the architecture is scalable, it has many advantages. A few examples are that scalable architecture helps businesses and industries to adapt to changing technology, drive innovation, promote platform independence, and build resilience against natural disasters. Most importantly, having a scalable architecture helps industries bring in cost-effective measures for energy consumption, reduce wastage, increase productivity, and enable a robust environment. It also helps in the reduction of carbon emissions with advanced monitoring and metering capabilities. Scalable architectures help in reducing waste by optimizing the designs to utilize materials efficiently, minimize resources, decrease carbon footprints by using low-impact materials that are environmentally friendly. In this paper we also emphasize the importance of cultural shift towards the reuse and recycling of natural resources for a balanced ecosystem and maintain a circular economy. Also, since all of us are involved in the use of computers, much of the scalable architecture we have studied is related to data centers.

Keywords: scalable architectures, sustainability, application design, disruptive technology, machine learning and natural language processing, AI, social media platform, cloud computing, advanced networking and storage devices, advanced monitoring and metering infrastructure, climate change

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Authors: Ankur Mundhra, Shubhadeep Chakraborty, Y. R. Singh, Vishal Das

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Seismic data scaling affects the dynamic range of a data and with present day lower costs of storage and higher reliability of Hard Disk data, scaling is not suggested. However, in dealing with data of different vintages, which perhaps were processed in 16 bits or even 8 bits and are need to be processed with 32 bit available data, scaling is performed. Also, scaling amplifies low amplitude events in deeper region which disappear due to high amplitude shallow events that saturate amplitude scale. We have focused on significance of scaling data to aid interpretation. This study elucidates a proper seismic loading procedure in workstations without using default preset parameters as available in most software suites. Differences and distribution of amplitude values at different depth for seismic data are probed in this exercise. Proper loading parameters are identified and associated steps are explained that needs to be taken care of while loading data. Finally, the exercise interprets the un-certainties which might arise when correlating scaled and unscaled versions of seismic data with synthetics. As, seismic well tie correlates the seismic reflection events with well markers, for our study it is used to identify regions which are enhanced and/or affected by scaling parameter(s).

Keywords: clipping, compression, resolution, seismic scaling

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Authors: Berhanu Keno Terfa

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Flash floods are among the most dangerous natural disasters that pose a significant threat to human existence. They occur frequently and can cause extensive damage to homes, infrastructure, and ecosystems while also claiming lives. Although flash floods can happen anywhere in the world, their impact is particularly severe in developing countries due to limited financial resources, inadequate drainage systems, substandard housing options, lack of early warning systems, and insufficient preparedness. To address these challenges, a comprehensive study has been undertaken to analyze and map flood inundation using Geographic Information System (GIS) techniques by considering various factors that contribute to flash flood resilience and developing effective mitigation strategies. Key factors considered in the analysis include slope, drainage density, elevation, Curve Number, rainfall patterns, land-use/cover classes, and soil data. These variables were computed using ArcGIS software platforms, and data from the Sentinel-2 satellite image (with a 10-meter resolution) were utilized for land-use/cover classification. Additionally, slope, elevation, and drainage density data were generated from the 12.5-meter resolution of the ALOS Palsar DEM, while other relevant data were obtained from the Ethiopian Meteorological Institute. By integrating and regularizing the collected data through GIS and employing the analytic hierarchy process (AHP) technique, the study successfully delineated flash flood hazard zones (FFHs) and generated a suitable land map for urban agriculture. The FFH model identified four levels of risk in Bishoftu City: very high (2106.4 ha), high (10464.4 ha), moderate (1444.44 ha), and low (0.52 ha), accounting for 15.02%, 74.7%, 10.1%, and 0.004% of the total area, respectively. The results underscore the vulnerability of many residential areas in Bishoftu City, particularly the central areas that have been previously developed. Accurate spatial representation of flood-prone areas and potential agricultural zones is crucial for designing effective flood mitigation and agricultural production plans. The findings of this study emphasize the importance of flood risk mapping in raising public awareness, demonstrating vulnerability, strengthening financial resilience, protecting the environment, and informing policy decisions. Given the susceptibility of Bishoftu City to flash floods, it is recommended that the municipality prioritize urban agriculture adaptation, proper settlement planning, and drainage network design.

Keywords: remote sensing, flush flood hazards, Bishoftu, GIS.

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Authors: Kuo Chieh Chao, Thishani Amarathunga, Sangam Shrestha

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Rainfall induced slope failures are one of the most damaging and disastrous natural hazards which occur frequently in the world. This type of sliding mainly occurs in the zone above the groundwater level in silty/sandy soils. When the rainwater begins to infiltrate into the vadose zone of the soil, the negative pore-water pressure tends to decrease and reduce the shear strength of soil material. Climate change has resulted in excessive and unpredictable rainfall in all around the world, resulting in landslides with dire consequences to human lives and infrastructure. Such problems could be overcome by examining in detail the causes for such slope failures and recommending effective repair plans for vulnerable locations by considering future climatic change. The selected area for this study is located in the road rehabilitation section from Maubara to Mota Ain road in Timor-Leste. Slope failures and cracks have occurred in 2013 and after repairs reoccurred again in 2017 subsequent to heavy rains. Both observed and future predicted climate data analyses were conducted to understand the severe precipitation conditions in past and future. Observed climate data were collected from NOAA global climate data portal. CORDEX data portal was used to collect Regional Climate Model (RCM) future predicted climate data. Both observed and RCM data were extracted to location-based data using ArcGIS Software. Linear scaling method was used for the bias correction of future data and bias corrected climate data were assigned to GeoStudio Software. Precipitations of wet seasons (December to March ) in 2007 to 2013 is higher than 2001-2006 period and it is more than nearly 40% higher precipitation than usual monthly average precipitation of 160mm.The results of seepage analyses which were carried out using SEEP/W model with observed climate, clearly demonstrated that the pore water pressure within the fill slope was significantly increased due to the increase of the infiltration during the wet season of 2013.One main Regional Climate Models (RCM) was analyzed in order to predict future climate variation under two Representative Concentration Pathways (RCPs).In the projected period of 76 years ahead from 2014, shows that the amount of precipitation is considerably getting higher in the future in both RCP 4.5 and RCP 8.5 emission scenarios. Critical pore water pressure conditions during 2014-2090 were used in order to recommend appropriate remediation methods. Results of slope stability analyses indicated that the factor of safety of the fill slopes was reduced from 1.226 to 0.793 during the dry season to wet season in 2013.Results of future slope stability which were obtained using SLOPE/W model for the RCP emissions scenarios depict that, the use of tieback anchors and geogrids in slope protection could be effective in increasing the stability of slopes to an acceptable level during the wet seasons. Moreover, methods and procedures like monitoring of slopes showing signs or susceptible for movement and installing surface protections could be used to increase the stability of slopes.

Keywords: climate change, precipitation, SEEP/W, SLOPE/W, unsaturated soil

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Authors: Diego Rodrigues, Marcelo Lisboa, Elismar Batista, Marcos Dias

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Based on data on child labor, this work arises questions about how to understand and locate the factors that make up the child labor rates, and which properties are important to analyze these cases. Using data mining techniques to discover valid patterns on Brazilian social databases were evaluated data of child labor in the State of Tocantins (located north of Brazil with a territory of 277000 km2 and comprises 139 counties). This work aims to detect factors that are deterministic for the practice of child labor and their relationships with financial indicators, educational, regional and social, generating information that is not explicit in the government database, thus enabling better monitoring and updating policies for this purpose.

Keywords: social data, government decision making, association of social data, data mining

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Authors: Sadam Alwadi

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Outlier values become a problem that frequently occurs in the data observation or recording process. Thus, the need for data imputation has become an essential matter. In this work, it will make use of the methods described in the prior work to detect the outlier values based on a collection of stock market data. In order to implement the detection and find some solutions that maybe helpful for investors, real closed price data were obtained from the Amman Stock Exchange (ASE). Tukey and Maximum Overlapping Discrete Wavelet Transform (MODWT) methods will be used to impute the detect the outlier values.

Keywords: outlier values, imputation, stock market data, detecting, estimation

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Authors: P. Jayashree, S. Rajkumar

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With social networks and smart devices generating a multitude of data, effective data management is the need of the hour for networks and cloud applications. Some applications need effective storage while some other applications need effective communication over networks and data reduction comes as a handy solution to meet out both requirements. Most of the data compression techniques are based on data statistics and may result in either lossy or lossless data reductions. Though lossy reductions produce better compression ratios compared to lossless methods, many applications require data accuracy and miniature details to be preserved. A variety of data compression algorithms does exist in the literature for different forms of data like text, image, and multimedia data. In the proposed work, a generic progressive compression algorithm, based on probabilistic encoding, called PEINS is projected as an enhancement over irrational number stored coding technique to cater to storage issues of increasing data volumes as a cost effective solution, which also offers data security as a secondary outcome to some extent. The proposed work reveals cost effectiveness in terms of better compression ratio with no deterioration in compression time.

Keywords: compression ratio, generic compression, irrational number storage, probabilistic encoding

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Authors: Femi Elegbeleye, Omobayo Esan, Muienge Mbodila, Patrick Bowe

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This paper focused on cost effective storage architecture using fog and cloud data storage gateway and presented the design of the framework for the data privacy model and data analytics framework on a real-time analysis when using machine learning method. The paper began with the system analysis, system architecture and its component design, as well as the overall system operations. The several results obtained from this study on data privacy model shows that when two or more data privacy model is combined we tend to have a more stronger privacy to our data, and when fog storage gateway have several advantages over using the traditional cloud storage, from our result shows fog has reduced latency/delay, low bandwidth consumption, and energy usage when been compare with cloud storage, therefore, fog storage will help to lessen excessive cost. This paper dwelt more on the system descriptions, the researchers focused on the research design and framework design for the data privacy model, data storage, and real-time analytics. This paper also shows the major system components and their framework specification. And lastly, the overall research system architecture was shown, its structure, and its interrelationships.

Keywords: IoT, fog, cloud, data analysis, data privacy

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Authors: Ajay Kumar

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Using data from census of India, sample registration system and national family health survey (NFHS-3), this paper traces spatial pattern, trends and the factors which have played their role differently in fertility transition in Uttar Pradesh and Tamil Nadu. For the purpose spatial variation analysis, trend line and binary logistic regression analysis has been carried out. There exist considerable regional disparities in terms of fertility decline in northern and southern states. The pace of fertility decline has been faster in southern and coastal regions, and at a slow pace in backward northern state. In Tamil Nadu fertility declined substantially among the women of lower and higher age groups in comparison to Uttar Pradesh characterized by low literacy, low female age at marriage, poor health infrastructure and low status of women. The Study shows that Fertility rates have been higher among the most vulnerable and deprived sections of the society like Illiterate women, women belong to scheduled caste, scheduled tribe and women residing in rural areas.

Keywords: age specific fertility rate, fertility transition, replacement level, total fertility rate

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Authors: Fulufhelo Oscar Makananise

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Digital technologies have played a significant role in bridging the information gap between the haves and the have nots in society. In developing countries such as South Africa, historically marginalised groups such as women in rural communities have an opportunity to use digital technologies to network among themselves as well as interact with their government, thereby enhancing prospects for poverty eradication, political participation, community development and democracy. However, the extent to which these goals can be achieved in a developing context through harnessing digital technologies is not quite clear, particularly given the fact that access to these technologies is not evenly distributed and the fact that women’s access to digital technologies is hampered by factors that go beyond the question of infrastructure. Informed by the technological dependency theory, this paper is about how female youth in rural South Africa are deploying digital media tools for socio-economic empowerment. In particular, the study investigated the extent to which female youth in Limpopo province, South Africa access and use digital media platforms and gadgets and the extent to which those technologies are breaking down barriers that stand in the way of female youth empowerment. Data were gathered using a self-administered questionnaire disseminated to selected 100 female youth in Limpopo Province, South Africa. The data were analysed using SPSS version 9, and the results were analysed using descriptive statistics. The paper argues that wider and constant access to digital media by female youth in rural areas is indicative of the great potential for empowering female youth in rural areas through harnessing digital media. The study established that the majority of female youth had access to digital media technologies and used them to share valuable information among themselves. The study further established that female youth are active users of digital media in South Africa, which is the significant driver for socio-economic empowerment.

Keywords: digital technologies, empowerment, female youth, South Africa, survey, technological dependency

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Authors: Nordila Ahmad, Thamer Mohammad, Bruce W. Melville, Zuliziana Suif

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Current methods for predicting local scour at wide bridge piers, were developed on the basis of laboratory studies and very limited scour prediction were tested with field data. Laboratory wide pier scour equation from previous findings with field data were presented. A wide range of field data were used and it consists of both live-bed and clear-water scour. A method for assessing the quality of the data was developed and applied to the data set. Three other wide pier-scour equations from the literature were used to compare the performance of each predictive method. The best-performing scour equation were analyzed using statistical analysis. Comparisons of computed and observed scour depths indicate that the equation from the previous publication produced the smallest discrepancy ratio and RMSE value when compared with the large amount of laboratory and field data.

Keywords: field data, local scour, scour equation, wide piers

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Authors: Sajjad Shukur Ullah, Syed Shujaa Safdar Gardezi

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Road infrastructure plays a vital role in the economic activities of any economy. Besides derived benefits from these facilities, the utilization of extensive energy resources, fuels, and materials results in a negative impact on the environment in terms of carbon footprint; carbon footprint is the overall amount of greenhouse gas (GHG) generated from any action. However, this aspect of environmental impact from road structure is not seriously considered during such developments, thus undermining a critical factor of sustainable development, which usually remains unaddressed, especially in developing countries. The current work investigates the carbon footprint impact of a small road project (0.8 km, dual carriageway) initiated for traffic management in an urban centre. Life cycle assessment (LCA) with boundary conditions of cradle to the site has been adopted. The only construction phase of the life cycle has been assessed at this stage. An impact of 10 ktons-CO2 (6260 ton-CO2/km) has been assessed. The rigid pavement dominated the contributions as compared to a flexible component. Among the structural elements, the underpass works shared the major portion. Among the materials, the concrete and steel utilized for various structural elements resulted in more than 90% of the impact. The earth-moving equipment was dominant in operational carbon. The results have highlighted that road infrastructure projects pose serious threats to the environment during their construction and which need to be considered during the approval stages. This work provides a guideline for supporting sustainable development that could only be ensured when such endeavours are properly assessed by industry professionals and decide various alternative environmental conscious solutions for the future.

Keywords: construction waste management, kiloton, life cycle assessment, rigid pavement

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Authors: N. Ali, S. Nakayama, H. Yamaguchi, M. Nadeem

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Traffic congestion is a matter of prime concern in developing countries. This can be primarily attributed due to poor design practices and biased allocation of resources based on political will neglecting the technical feasibilities in infrastructure design. During the last decade, Lahore has expanded at an unprecedented rate as compared to surrounding cities due to more funding and resource allocation by the previous governments. As a result of this, people from surrounding cities and areas moved to the Lahore city for better opportunities and quality of life. This migration inflow inherited the city with an increased population yielding the inefficiency of the existing infrastructure to accommodate enhanced traffic demand. This leads to traffic congestion on major arterial roads of the city. In this simulation study, a major arterial road was selected to evaluate the performance of the five intersections by changing the geometry of the intersections or signal control type. Simulations were done in two software; Highway Capacity Software (HCS) and Synchro Studio and Sim Traffic Software. Some of the traffic management strategies that were employed include actuated-signal control, semi-actuated signal control, fixed-time signal control, and roundabout. The most feasible solution for each intersection in the above-mentioned traffic management techniques was selected with the least delay time (seconds) and improved Level of Service (LOS). The results showed that Jinnah Hospital Intersection and Akbar Chowk Intersection improved 92.97% and 92.67% in delay time reduction, respectively. These results can be used by traffic planners and policy makers for decision making for the expansion of these intersections keeping in mind the traffic demand in future years.

Keywords: traffic congestion, traffic simulation, traffic management, congestion problems

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Authors: Inkyu Kim, SangMan Moon

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This IEEE 802.11b protocol provides up to 11Mbps data rate, whereas aerospace industry wants to seek higher data rate COTS data link system in the UAV. The Total Maximum Throughput (TMT) and delay time are studied on many researchers in the past years This paper provides theoretical data throughput performance of UAV formation flight data link using the existing 802.11b performance theory. We operate the UAV formation flight with more than 30 quad copters with 802.11b protocol. We may be predicting that UAV formation flight numbers have to bound data link protocol performance limitations.

Keywords: UAV datalink, UAV formation flight datalink, UAV WLAN datalink application, UAV IEEE 802.11b datalink application

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Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

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Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: genetic data, Pinzgau cattle, supervised learning, machine learning

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Authors: Nidhi Gopal

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Routing is the process of moving a packet of data from source to destination and enables messages to pass from one computer to another and eventually reach the target machine. A router is a networking device that forwards data packets between computer networks. It is connected to two or more data lines from different networks (as opposed to a network switch, which connects data lines from one single network). This paper mainly emphasizes upon the study of router device, its top level architecture, and how various sub-modules of router i.e. Register, FIFO, FSM and Synchronizer are synthesized, and simulated and finally connected to its top module.

Keywords: data packets, networking, router, routing

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Authors: Nebiat Lemenih Lenger

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Today, the digital economy is evolving faster than ever in Ethiopia. Platforms that provide a ride-hailing service are growing fast in the country. The market welcomed them as they disrupt it with quality services and lower prices. This revolution is, however, not without challenges. These include cybersecurity breaches, facilitating illegal economic activities, and challenging concepts of privacy. To mitigate the risks and utilize the benefits, appropriate regulation should be introduced in the economy. By identifying legal and institutional gaps in Ethiopia`s digital economy, this research work assists the government`s effort to create a better digital economy. Moreover, this study, being a pioneer study in the area, will be an input for further studies in academia. The research employs a qualitative legal research method and analyzes various legal and policy instruments in Ethiopia in comparison with best international experiences. As this research applies a qualitative research method, a grounded theory method of data analysis is used. The research concluded that Ethiopia is far from designing appropriate legal and regulatory infrastructures. Due to the government monopoly of the sector, there is poor digital infrastructure in the country. The existing labor laws have no specific provisions on the rights and obligations of gig workers.

Keywords: Ethiopia, gig economy, digital, ride-hailing, regulation

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Authors: M. Shahab Uddin, Pennung Warnitchai

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Currently more than half of the world’s populations are living in cities, and the number and sizes of cities are growing faster than ever. Cities rely on the effective functioning of complex and interdependent critical infrastructures networks to provide public services, enhance the quality of life, and save the community from hazards and disasters. In contrast, complex connectivity and interdependency among the urban critical infrastructures bring management challenges and make the urban system prone to the domino effect. Unplanned rapid growth, increased connectivity, and interdependency among the infrastructures, resource scarcity, and many other socio-political factors are affecting the typical state of an urban system and making it susceptible to numerous sorts of diversion. In addition to internal vulnerabilities, urban systems are consistently facing external threats from natural and manmade hazards. Cities are not just complex, interdependent system, but also makeup hubs of the economy, politics, culture, education, etc. For survival and sustainability, complex urban systems in the current world need to manage their vulnerabilities and hazardous incidents more wisely and more interactively. Coordinated management in such systems makes for huge potential when it comes to absorbing negative effects in case some of its components were to function improperly. On the other hand, ineffective management during a similar situation of overall disorder from hazards devastation may make the system more fragile and push the system to an ultimate collapse. Following the quantum, the current research hypothesizes that a hazardous event starts its journey as an emergency, and the system’s internal vulnerability and response capacity determine its destination. Connectivity and interdependency among the urban critical infrastructures during this stage may transform its vulnerabilities into dynamic damaging force. An emergency may turn into a disaster in the absence of effective management; similarly, mismanagement or lack of management may lead the situation towards a catastrophe. Situation awareness and factual decision-making is the key to win a battle. The current research proposed a contextual decision support system for an urban critical infrastructure system while integrating three different models: 1) Damage cascade model which demonstrates damage propagation among the infrastructures through their connectivity and interdependency, 2) Restoration model, a dynamic restoration process of individual infrastructure, which is based on facility damage state and overall disruptions in surrounding support environment, and 3) Optimization model that ensures optimized utilization and distribution of available resources in and among the facilities. All three models are tightly connected, mutually interdependent, and together can assess the situation and forecast the dynamic outputs of every input. Moreover, this integrated model will hold disaster managers and decision makers responsible when it comes to checking all the alternative decision before any implementation, and support to produce maximum possible outputs from the available limited inputs. This proposed model will not only support to reduce the extent of damage cascade but will ensure priority restoration and optimize resource utilization through adaptive and collaborative management. Complex systems predictably fail but in unpredictable ways. System understanding, situation awareness, and factual decisions may significantly help urban system to survive and sustain.

Keywords: disaster prevention, decision support system, emergency response, urban critical infrastructure system

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Authors: Julius Onyancha, Valentina Plekhanova

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One of the significant issues facing web users is the amount of noise in web data which hinders the process of finding useful information in relation to their dynamic interests. Current research works consider noise as any data that does not form part of the main web page and propose noise web data reduction tools which mainly focus on eliminating noise in relation to the content and layout of web data. This paper argues that not all data that form part of the main web page is of a user interest and not all noise data is actually noise to a given user. Therefore, learning of noise web data allocated to the user requests ensures not only reduction of noisiness level in a web user profile, but also a decrease in the loss of useful information hence improves the quality of a web user profile. Noise Web Data Learning (NWDL) tool/algorithm capable of learning noise web data in web user profile is proposed. The proposed work considers elimination of noise data in relation to dynamic user interest. In order to validate the performance of the proposed work, an experimental design setup is presented. The results obtained are compared with the current algorithms applied in noise web data reduction process. The experimental results show that the proposed work considers the dynamic change of user interest prior to elimination of noise data. The proposed work contributes towards improving the quality of a web user profile by reducing the amount of useful information eliminated as noise.

Keywords: web log data, web user profile, user interest, noise web data learning, machine learning

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Authors: Abdulkarim Yusuf

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Motivation: The Nigerian economy has seen significant macroeconomic instability, fuelled mostly by an overreliance on fluctuating oil revenues. The rising disparity between tax receipts and government spending in Nigeria necessitates government borrowing to fund the anticipated pace of economic growth. Rising public debt and fiscal sustainability are limiting the government's ability to invest in key infrastructure that promotes private investment and growth in Nigeria. Objective: This paper fills an empirical research vacuum by examining the impact of public debt on fiscal sustainability in Nigeria, given the significance of fiscal stability in decreasing poverty and the constraints that an unsustainable debt burden imposes on it. Data and method: Annual time series data covering the period 1980 to 2022 exposed to conventional and structural breaks stationarity tests and the Autoregressive Distributed Lag estimation approach were adopted for this study. Results: The results reveal that domestic debt stock, debt service payment, foreign reserve stock, exchange rate, and private investment all had a major adverse effect on fiscal stability in the long and short run, corroborating the debt overhang and crowding-out hypothesis. External debt stock, prime lending rate, and degree of trade openness, which boosted fiscal stability in the long run, had a major detrimental effect on fiscal stability in the short run, whereas foreign direct investment inflows had an important beneficial impact on fiscal stability in both the long and short run. Implications: The results indicate that fiscal measures that inspire domestic resource mobilization, sustainable debt management techniques, and dependence on external debt to boost deficit financing will improve fiscal stability and drive growth.

Keywords: ARDL co-integration, debt overhang, debt servicing, fiscal stability, public debt

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Authors: Naif Albelwi, Alan Kwan, Yacine Rezgui

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Cities with rapid growth face tremendous challenges not only to provide services to meet this growth but also to assure that this growth occurs in a sustainable way. The consumption of material, energy, and water resources is inextricably linked to population growth with a unique impact in urban areas, especially in light of significant investments in infrastructure to support urban development. Urban Metabolism (UM) is becoming popular as it provides a framework accounting the mass and energy flows through a city. The objective of this study is to determine the energy and material flows of Riyadh, Saudi Arabia using locally generated data from 1996 and 2012 and analyzing the temporal trends of energy and material flows. Preliminary results show that while the population of Riyadh grew 90% since 1996, the input and output flows have increased at higher rate. Results also show increasing in energy mobile consumption from 61k TJ in 1996 to 157k TJ in 2012 which points to Riyadh’s inefficient urban form. The study findings highlight the importance to develop effective policies for improving the use of resources.

Keywords: energy and water consumption, sustainability, urban development, urban metabolism

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Authors: Zeba Mahmood

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The modern business organizations are adopting technological advancement to achieve competitive edge and satisfy their consumer. The development in the field of Information technology systems has changed the way of conducting business today. Business operations today rely more on the data they obtained and this data is continuously increasing in volume. The data stored in different locations is difficult to find and use without the effective implementation of Data mining and Knowledge management techniques. Organizations who smartly identify, obtain and then convert data in useful formats for their decision making and operational improvements create additional value for their customers and enhance their operational capabilities. Marketers and Customer relationship departments of firm use Data mining techniques to make relevant decisions, this paper emphasizes on the identification of different data mining and Knowledge management techniques that are applied to different business industries. The challenges and issues of execution of these techniques are also discussed and critically analyzed in this paper.

Keywords: knowledge, knowledge management, knowledge discovery in databases, business, operational, information, data mining

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Authors: E. Mattio

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The aim of this project is to study the Chinese presence in Ethiopia, following the path of the last salt caravans from Danakil to Tigray region. Official estimates of the number of Chinese in Africa vary widely; on the continent, there are increasingly diverse groups of Chinese migrants in terms of language, dialect, class, education, and employment. Based on this and on a very general state of the art, it was decided to increase the studies on this phenomenon, documenting the extraction of salt and following the sellers in the north of the country. The project is unique and allows you to admire a landscape that will soon change, due to the construction of infrastructure that is changing the dynamics of movement and sales. To carry out this study, interdisciplinary investigation methods were integrated, such as landscape archeology, historiographic research, participatory anthropology, geopolitics, and cultural anthropology and ethnology. There are two main objectives of the research. The first was an analysis of risk perceptions to predict what will happen to these populations and how the territory will be modified, trying to monitor the growth of infrastructure in the country and the effects it will have on the population. Thanks to the use of GIS, some roads created by Chinese companies that worked in the area have been georeferenced. The second point was to document the life and rituals of Ethiopian populations, in order not to lose the aspects of uniqueness that risk being lost. The local interviews have garnered impressions and criticisms from the local population to understand whether the Chinese presence is perceived as a threat or a solution. Among the most exclusive interviews, there are those made to Afar leaders in the Logya area and some Coptic representatives in the Wukro area. To make this project even more unique, the Coptic rituals of Gennà and Timkat have been documented, unique expressions of a millennial tradition. The aim was to understand whether the Maoist presence began to influence the religious rites and forms of belief present in the country.

Keywords: China, Ethiopia, GIS, risk perceptions

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Authors: Vijaya Nhaloor, Suja Kumari Leela, Jose Devadasan

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Planning of neighbourhood development strategies in Tier 2 Indian city is highly significant when it has also been selected as a Smart city by the Ministry of Urban Development in India. Smart city mission of India proposes the development of infrastructure in a city in an inclusive way. Thiruvananthapuram, the capital city of Kerala state, India, has been selected as the city to conduct the research. The master plan for the city of Thiruvananthapuram envisions it as a Compact city and proposes densification as a tool for development. Densification may adversely affect the quality of life after a tipping point. This may lead to urban decay which in turn directly or indirectly affects the surrounding neighbourhoods also, thus spreading blight areas in the city. The author thinks that density in urban planning is not a well detailed subject in India, with respect to its varied links on infrastructure, quality of life, transportation, scope of vertical planning, affordability etc. Neighbourhoods are vital tissues of an urban area, and their development directly affects the development of the region. The methodology would involve skimming of proactive neighbourhood planning principles compatible with the Smart city mission in India. United Nations proposes sustainability as a way of planning development of a neighbourhood. After defining various terminologies involved, a framework shall be developed to analyse an existing neighbourhood and prepare planning guidelines in a sustainable manner. The framework shall comply with international and national policy guidelines. The research shall explore and identify a neighbourhood with the potential to meet the housing demand from the investment regions nearby and analyse its potential and weakness as per this framework. Later, a set of indicators shall be enlisted to guide the development of the neighbourhood, leading to recommendations that shall serve as a replicable model for the other neighbourhoods in the Smart city.

Keywords: key indicators, neighbourhood planning, sustainability, smart city

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Authors: Adarsh Shroff

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Big data is a collection of dataset so large and complex that it becomes difficult to process using data base management tools. To perform operations like search, analysis, visualization on big data by using data mining; which is the process of extraction of patterns or knowledge from large data set. In recent years, the data mining applications become stale and obsolete over time. Incremental processing is a promising approach to refreshing mining results. It utilizes previously saved states to avoid the expense of re-computation from scratch. This project uses i2MapReduce, an incremental processing extension to Map Reduce, the most widely used framework for mining big data. I2MapReduce performs key-value pair level incremental processing rather than task level re-computation, supports not only one-step computation but also more sophisticated iterative computation, which is widely used in data mining applications, and incorporates a set of novel techniques to reduce I/O overhead for accessing preserved fine-grain computation states. To optimize the mining results, evaluate i2MapReduce using a one-step algorithm and three iterative algorithms with diverse computation characteristics for efficient mining.

Keywords: big data, map reduce, incremental processing, iterative computation

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Authors: Chika Ethel Esege

Abstract:

Electronic learning is learning facilitated by technology which has basically altered approaches globally, including the field of education. This trend is compelling educators to focus on approaches that improve classroom practices in order to enhance students’ learning and participation in a global digital society. However, e-learning is not fully utilized across subject disciplines particularly in the field of humanities, in the context of Nigerian secondary education. This study focused on the use of e-learning to enhance the development of digital skills, particularly, collaboration and communication in secondary school students in Nigeria. The study adopted an ‘action research’ involving 210 students and 7 teachers, who utilised the e-learning platform designed by the researcher for the survey. Mixed methods- qualitative and quantitative- were used for data collection including questionnaire, observation, interview, and analysis of statutory documents. The data were presented using frequency counts for questionnaire responses and figures of screenshots for learning tasks. The VOD Burner software was also used to analyse interviews and video recordings. The study showed that the students acquired collaboration and communication skills through e-learning intervention lesson, and demonstrated satisfaction with this approach. However, the study further revealed that the traditional teaching approach could not provide digital education or develop the digital skills of the students. Based on these findings, recommendations were made that the Nigerian Government should incorporate digital content across subject disciplines into secondary school education curricular and provide adequate infrastructure in order to enable educators to adopt relevant approaches necessary for the enhancement of students’ learning especially in a technologically evolving and advancing world.

Keywords: developing collaboration and communication skills, electronic learning, improving classroom teaching, secondary schools in Nigeria

Procedia PDF Downloads 119

Authors: Jerry Q. Cheng

Abstract:

Currently, in analyzing large-scale recurrent event data, there are many challenges such as memory limitations, unscalable computing time, etc. In this research, a divide-and-conquer method is proposed using parametric frailty models. Specifically, the data is randomly divided into many subsets, and the maximum likelihood estimator from each individual data set is obtained. Then a weighted method is proposed to combine these individual estimators as the final estimator. It is shown that this divide-and-conquer estimator is asymptotically equivalent to the estimator based on the full data. Simulation studies are conducted to demonstrate the performance of this proposed method. This approach is applied to a large real dataset of repeated heart failure hospitalizations.

Keywords: big data analytics, divide-and-conquer, recurrent event data, statistical computing

Procedia PDF Downloads 147

Authors: Vaidehi Raipat

Abstract:

A city is an expression of coexistence between its users and built environment. The way in which its spaces are animated signify the quality of this coexistence. Urban sustainability is the ability of a city to respond efficiently towards its people, culture, environment, visual image, history, visions and identity. The quality of built environment determines the quality of our lifestyles, but poor ability of the built environment to adapt and sustain itself through the changes leads to degradation of cities. Ranchi was created in November 2000, as the capital of the newly formed state Jharkhand, located on eastern side of India. Before this Ranchi was known as summer capital of Bihar and was a little larger than a town in terms of development. But since then it has been vigorously expanding in size, infrastructure as well as population. This sudden expansion has created a stress on existing built environment. The large forest covers, agricultural land, diverse culture and pleasant climatic conditions have degraded and decreased to a large extent. Narrow roads and old buildings are unable to bear the load of the changing requirements, fast improving technology and growing population. The built environment has hence been rendered unsustainable and unadaptable through fastidious changes of present era. Some of the common hazards that can be easily spotted in the built environment are half-finished built forms, pedestrians and vehicles moving on the same part of the road. Unpaved areas on street edges. Over-sized, bright and randomly placed hoardings. Negligible trees or green spaces. The old buildings have been poorly maintained and the new ones are being constructed over them. Roads are too narrow to cater to the increasing traffic, both pedestrian and vehicular. The streets have a large variety of activities taking place on them, but haphazardly. Trees are being cut down for road widening and new constructions. There is no space for greenery in the commercial as well as old residential areas. The old infrastructure is deteriorating because of poor maintenance and the economic limitations. Pseudo understanding of functionality as well as aesthetics drive the new infrastructure. It is hence necessary to evaluate the extent of sustainability of existing built environment of the city and create or regenerate the existing built environment into a more sustainable and adaptable one. For this purpose, research titled “Sustainability of the Built Environment of Ranchi District” has been carried out. In this research the condition of the built environment of Ranchi are explored so as to figure out the problems and shortcomings existing in the city and provide for design strategies that can make the existing built-environment sustainable. The built environment of Ranchi that include its outdoor spaces like streets, parks, other open areas, its built forms as well as its users, has been analyzed in terms of various urban design parameters. Based on which strategies have been suggested to make the city environmentally, socially, culturally and economically sustainable.

Keywords: adaptable, built-environment, sustainability, urban

Procedia PDF Downloads 223

Authors: Azzeddine Atibi, Lamalif latifa, Khadija El Kababi, Salim Ahmed, Mohamed Radid

Abstract:

This study analyzes the integration of Information and Communication Technologies (ICT) in modern education, where these tools have become essential. Due to the rapid emergence of new technologies and their increasing adoption in education, it is important to understand how teachers use and perceive these tools. The study pursues three objectives : examining current teacher practices regarding ICT, evaluating their impact on student skills and engagement, and making recommendations for better integration of ICT in education. The study's methodology is based on a quantitative approach, using a questionnaire administered to a sample of 104 teachers. This questionnaire, rigorously validated to ensure its reliability, gathers representative data on perceptions and challenges related to the use of ICT. The results show widespread adoption of ICT by teachers, with the majority reporting an improvement in student skills due to these technologies. However, opinions diverge on their impact on student engagement : some teachers note an increase in engagement, while others remain skeptical. Persistent challenges include insufficient technological infrastructure and the need for ongoing training. The recommendations highlight the importance of improving infrastructures and supporting the professional development of teachers to optimize the integration of ICT.

Keywords: ICT, education, teaching practices, teacher perceptions, continuing education

Procedia PDF Downloads 11