Search results for: spatial temporal data mining

Authors: Ritesh Verma, Manisha Rathi, Chand Singh Dhull, Sumit Sachdeva, Jitender Phogat

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Temporal trabeculectomy with the Ologen implant was done in a 66-year-old lady with uveitic glaucoma. Serial IOP measurement was done to assess the efficacy of ologen implant in uveitic glaucoma. The patient had an IOP of 4mmhg day 1 postoperatively and Ologen implant was in place with a well-formed bleb. On follow up patient had an IOP of 14mmhg and unaided visual acuity of 6/12 on day 10 postoperatively. After 12 weeks of Trabeculectomy with Ologen implant, the IOP of the patient was 14 mmHg, the vision was 6/6 with -1.25 DS and -1.25 DC at 90 degrees. Trabeculectomy performed in patients with uveitic glaucoma has a higher chance of failure due to increased inflammation and fibrosis. Trabeculectomy with ologen implant done in a patient of uveitic glaucoma provides excellent postoperative results and the patient has a well-controlled IOP even after 56 weeks of surgery and a best corrected visual acuity of 6/6. Trabeculectomy with the ologen implant is superior to other surgeries in cases of secondary glaucoma with increased inflammation.

Keywords: glaucoma surgery, ologen implant, temporal trabeculectomy, uveitic glaucoma

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Authors: Jaqueline Maria Ribeiro Vieira

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Different strategies and tools are available at the oil and gas industry for detecting and analyzing tension and possible fractures in borehole walls. Most of these techniques are based on manual observation of the captured borehole images. While this strategy may be possible and convenient with small images and few data, it may become difficult and suitable to errors when big databases of images must be treated. While the patterns may differ among the image area, depending on many characteristics (drilling strategy, rock components, rock strength, etc.). Previously we developed and proposed a novel strategy capable of detecting patterns at borehole images that may point to regions that have tension and breakout characteristics, based on segmented images. In this work we propose the inclusion of data-mining classification strategies in order to create a knowledge database of the segmented curves. These classifiers allow that, after some time using and manually pointing parts of borehole images that correspond to tension regions and breakout areas, the system will indicate and suggest automatically new candidate regions, with higher accuracy. We suggest the use of different classifiers methods, in order to achieve different knowledge data set configurations.

Keywords: image segmentation, oil well visualization, classifiers, data-mining, visual computer

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Authors: Vinayaka Gude Divya Sampath

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The research introduces an integrated prediction model to assess the susceptibility of roads in a future flooding event. The model consists of deep learning algorithm for forecasting gauge height data and Flood Inundation Mapper (FIM) for spatial flooding. An optimal architecture for Long short-term memory network (LSTM) was identified for the gauge located on Tangipahoa River at Robert, LA. Dropout was applied to the model to evaluate the uncertainty associated with the predictions. The estimates are then used along with FIM to identify the spatial flooding. Further geoprocessing in ArcGIS provides the susceptibility values for different roads. The model was validated based on the devastating flood of August 2016. The paper discusses the challenges for generalization the methodology for other locations and also for various types of flooding. The developed model can be used by the transportation department and other emergency response organizations for effective disaster management.

Keywords: deep learning, disaster management, flood prediction, urban flooding

Procedia PDF Downloads 138

Authors: Ahmad Shahin, Walid Moudani, Ali Bekraki

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This research aims at presenting a predictive data mining model to handle an accurate diagnosis of acute appendicitis with patients for the purpose of maximizing the health service quality, minimizing morbidity/mortality, and reducing cost. However, acute appendicitis is the most common disease which requires timely accurate diagnosis and needs surgical intervention. Although the treatment of acute appendicitis is simple and straightforward, its diagnosis is still difficult because no single sign, symptom, laboratory or image examination accurately confirms the diagnosis of acute appendicitis in all cases. This contributes in increasing morbidity and negative appendectomy. In this study, the authors propose to generate an accurate model in prediction of patients with acute appendicitis which is based, firstly, on the segmentation technique associated to ABC algorithm to segment the patients; secondly, on applying fuzzy logic to process the massive volume of heterogeneous and noisy data (age, sex, fever, white blood cell, neutrophilia, CRP, urine, ultrasound, CT, appendectomy, etc.) in order to express knowledge and analyze the relationships among data in a comprehensive manner; and thirdly, on applying dynamic programming technique to reduce the number of data attributes. The proposed model is evaluated based on a set of benchmark techniques and even on a set of benchmark classification problems of osteoporosis, diabetes and heart obtained from the UCI data and other data sources.

Keywords: healthcare management, acute appendicitis, data mining, classification, decision tree

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Authors: Khries Sawsan

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the phenomenon of urbanization is considered as one of the most important tourism resources that differ from one country to another and from one region to another in the same country. Our concern in tourism accommodation is explained by the fact that their location is directly related to the movement to tourist sites .Besides, these constructions comport security considered as the most important motivation for tourists in their choice of any destination. Hotels are the most representative expression of tourism. This is due to their physical prominence in the landscape and being the sole urban component totally unique to tourism. This study sheds light on the impact of tourism development on the spatial pattern in Jordan. It describes the linkages between existing tourism development policies and the spatial development patterns that have occurred as a result throughout Jordan, particularly looking at the impact that tourism has had on the physical environment of major tourism destinations. It puts an illustrative plan of the impact of the augmentation of tourism accommodations in Jordan in the past 40 years ago. The findings of this study help us to understand better the operation of Jordan’ dynamic changes in the location An intensive analysis is then applied on a representative case study in three regions: Amman, Petra and Aqaba. The study proceeds from an historical perspective to, show the evolution of the current development patterns an increase of tourism’s impact on spatial, in the presence of factors as political and economic stability, is expected.

Keywords: spatial patterns, urbanisation, spatial transformations, tourism planning, Jordan

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Authors: Yin-Yee Leong, Jack C. Yue, Hsin-Chung Wang

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Human longevity has been experiencing its largest increase since the end of World War II, and modeling the mortality rates is therefore often the focus of many studies. Among all mortality models, the Lee–Carter model is the most popular approach since it is fairly easy to use and has good accuracy in predicting mortality rates (e.g., for Japan and the USA). However, empirical studies from several countries have shown that the age parameters of the Lee–Carter model are not constant in time. Many modifications of the Lee–Carter model have been proposed to deal with this problem, including adding an extra cohort effect and adding another period effect. In this study, we propose a spatial modification and use clusters to explain why the age parameters of the Lee–Carter model are not constant. In spatial analysis, clusters are areas with unusually high or low mortality rates than their neighbors, where the “location” of mortality rates is measured by age and time, that is, a 2-dimensional coordinate. We use a popular cluster detection method—Spatial scan statistics, a local statistical test based on the likelihood ratio test to evaluate where there are locations with mortality rates that cannot be described well by the Lee–Carter model. We first use computer simulation to demonstrate that the cluster effect is a possible source causing the problem of the age parameters not being constant. Next, we show that adding the cluster effect can solve the non-constant problem. We also apply the proposed approach to mortality data from Japan, France, the USA, and Taiwan. The empirical results show that our approach has better-fitting results and smaller mean absolute percentage errors than the Lee–Carter model.

Keywords: mortality improvement, Lee–Carter model, spatial statistics, cluster detection

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Authors: Triano Nurhikmat

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Along with the progress of science and technology, the development of the industrialized world in Indonesia took place very rapidly. This leads to a process of industrialization of society Indonesia faster with the establishment of the company and the workplace are diverse. Development of the industry relates to the activity of the worker. Where in these work activities do not cover the possibility of an impending crash on either the workers or on a construction project. The cause of the occurrence of industrial accidents was the fault of electrical damage, work procedures, and error technique. The method of an association rule is one of the main techniques in data mining and is the most common form used in finding the patterns of data collection. In this research would like to know how relations of the association between the incidence of any industrial accidents. Therefore, by using methods of analysis association rule patterns associated with combination obtained two iterations item set (2 large item set) when every factor of industrial accidents with a West Jakarta so industrial accidents caused by the occurrence of an electrical value damage = 0.2 support and confidence value = 1, and the reverse pattern with value = 0.2 support and confidence = 0.75.

Keywords: association rule, data mining, industrial accidents, rules

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Authors: Salma El Hajjami, Jamal Malki, Alain Bouju, Mohammed Berrada

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With the expansion of machine learning and data mining in the context of Big Data analytics, the common problem that affects data is class imbalance. It refers to an imbalanced distribution of instances belonging to each class. This problem is present in many real world applications such as fraud detection, network intrusion detection, medical diagnostics, etc. In these cases, data instances labeled negatively are significantly more numerous than the instances labeled positively. When this difference is too large, the learning system may face difficulty when tackling this problem, since it is initially designed to work in relatively balanced class distribution scenarios. Another important problem, which usually accompanies these imbalanced data, is the overlapping instances between the two classes. It is commonly referred to as noise or overlapping data. In this article, we propose an approach called: One Side Behavioral Noise Reduction (OSBNR). This approach presents a way to deal with the problem of class imbalance in the presence of a high noise level. OSBNR is based on two steps. Firstly, a cluster analysis is applied to groups similar instances from the minority class into several behavior clusters. Secondly, we select and eliminate the instances of the majority class, considered as behavioral noise, which overlap with behavior clusters of the minority class. The results of experiments carried out on a representative public dataset confirm that the proposed approach is efficient for the treatment of class imbalances in the presence of noise.

Keywords: machine learning, imbalanced data, data mining, big data

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Authors: Livhuwani Muthelo, Tebogo Maria Mothiba, Rambelani Nancy Malema

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Background: Despite occupational legislation/standards being in place in the industry, there are many reported health and safety incidents, including both occupational injuries and illnesses in the South African mining industry. Purpose: This systematic literature review aimed to describe and identify the existing gaps in health and safety compliance within the South African mining industry and propose future research areas. Methodology: A systematic literature review was conducted using the key concepts of health and safety, compliance, standards, and mining. A total of 102 papers issued from 1994 to April 2020 were extracted from an online database search, which included a combination of South African and international government OHS legislation documents, policies, standards, reports from the mineral departments and international labour office, qualitative and quantitative journal articles, dissertations, seminars and conference proceedings. Results: The literature review revealed that, though there are laws, regulations, standards to guide the industry on health and safety issues in South Africa, the main challenge is with the compliance with the existing health and safety systems, wherein systems are not being implemented. Conclusion: Gaps between research, policy, and implementation in occupational health practice in the South African mining industry were also identified.

Keywords: circumstances, non-compliance, health and safety, standards, mining industry

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Authors: Sujata Upgupta, Prasoon Kumar Singh

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The expansion of large scale coal mining into forest areas is a potential hazard for the local biodiversity and wildlife. The objective of this study is to provide a picture of the threat that coal mining poses to the forests of the East Bokaro landscape. The vulnerable forest areas at risk have been assessed and the priority areas for conservation have been presented. The forested areas at risk in the current scenario have been assessed and compared with the past conditions using classification and buffer based overlay approach. Forest vulnerability has been assessed using an analytical framework based on systematic indicators and composite vulnerability index values. The results indicate that more than 4 km² of forests have been lost from 1973 to 2016. Large patches of forests have been diverted for coal mining projects. Forests in the northern part of the coal field within 1-3 km radius around the coal mines are at immediate risk. The original contiguous forests have been converted into fragmented and degraded forest patches. Most of the collieries are located within or very close to the forests thus threatening the biodiversity and hydrology of the surrounding regions. Based on the vulnerability values estimated, it was concluded that more than 90% of the forested grids in East Bokaro are highly vulnerable to mining. The forests in the sub-districts of Bermo and Chandrapura have been identified as the most vulnerable to coal mining activities. This case study would add to the capacity of the forest managers and mine managers to address the risk and vulnerability of forests at a small landscape level in order to achieve sustainable development.

Keywords: forest, coal mining, indicators, vulnerability

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Authors: Ashneel Ajay Singh, Anish Maharaj, Havish Naidu, Michelle Kumar

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Mangrove patches are the foundation species located in the estuarine land areas. These patches provide a nursery, food source and protection for numerous aquatic, intertidal and well as land-based organisms. Mangroves also help in coastal protection, maintain water clarity and are one of the biggest sinks for blue carbon sequestration. In the Pacific Island countries, numerous coastal communities have a heavy socioeconomic dependence on coastal resources and mangroves play a key ecological and economical role in structuring the availability of these resources. Fiji has a large mangrove patch located in the Votua area of the Ba province. Globally, mangrove population continues to decline with the changes in climatic conditions and anthropogenic activities. Baseline information through wetland maps and time series change are essential references for development of effective mangrove management plans. These maps reveal the status of the resource and the effects arising from anthropogenic activities and climate change. In this study, we used remote sensing and GIS tools for mapping and temporal change detection over a period of >20 years in Votua, Fiji using Landsat imagery. Landsat program started in 1972 initially as Earth Resources Technology Satellite. Since then it has acquired millions of images of Earth. This archive allows mapping of temporal changes in mangrove forests. Mangrove plants consisted of the species Rhizophora stylosa, Rhizophora samoensis, Bruguiera gymnorrhiza, Lumnitzera littorea, Heritiera littoralis, Excoecaria agallocha and Xylocarpus granatum. Change detection analysis revealed significant reduction in the mangrove patch over the years. This information serves as a baseline for the development and implementation of effective management plans for one of Fiji’s biggest mangrove patches.

Keywords: climate change, GIS, Landsat, mangrove, temporal change

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Authors: Fofie Kokea Ariane Darolle, Gouet Daniel Hervé, Koumetio Fidèle, Yemele David

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The electrical resistivity method is successfully used in this paper in order to have a clearer picture of the subsurface of the North-East ofFiguil in northern Cameroon. It is worth noting that this method is most often used when the objective of the study is to image the shallow subsoils by considering them as a set of stratified ground layers. The problem to be solved is very often environmental, and in this case, it is necessary to perform an inversion of the data in order to have a complete and accurate picture of the parameters of the said layers. In the case of this work, thirty-three (33) Schlumberger VES have been carried out on an irregular grid to investigate the subsurface of the study area. The 1D inversion applied as a preliminary modeling tool and in correlation with the mechanical drillings results indicates a complex subsurface lithology distribution mainly consisting of marbles and schists. Moreover, the quasi-3D inversion with lateral constraint shows that the misfit between the observed field data and the model response is quite good and acceptable with a value low than 10%. The method also reveals existence of two water bearing in the considered area. The first is the schist or weathering aquifer (unsuitable), and the other is the marble or the fracturing aquifer (suitable). The final quasi 3D inversion results and geological models indicate proper sites for groundwaters prospecting and for mining exploitation, thus allowing the economic development of the study area.

Keywords: electrical resistivity method, 1D inversion, quasi 3D inversion, groundwaters, mining

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Authors: Hung-Chu Chen, Han Qi, Bauke de Vries

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Energy consumption in the urban environment has attracted numerous researches in recent decades. However, it is comparatively rare to find literary works which investigated 3D spatial analysis of urban energy demand modelling. In order to analyze the spatial correlation between urban morphology and energy demand comprehensively, this paper investigates their relation by using the spatial regression tool. In addition, the spatial regression tool which is applied in this paper is ordinary least squares regression (OLS) and geographically weighted regression (GWR) model. Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), and building volume are explainers of urban morphology, which act as independent variables of Energy-land use (E-L) model. NDBI and NDVI are used as the index to describe five types of land use: urban area (U), open space (O), artificial green area (G), natural green area (V), and water body (W). Accordingly, annual electricity, gas demand and energy demand are dependent variables of the E-L model. Based on the analytical result of E-L model relation, it revealed that energy demand and urban morphology are closely connected and the possible causes and practical use are discussed. Besides, the spatial analysis methods of OLS and GWR are compared.

Keywords: energy demand model, geographically weighted regression, normalized difference built-up index, normalized difference vegetation index, spatial statistics

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Authors: Khaled A. Abdel-Sater

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There are four areas of the temporal lobe. Primary auditory area (areas 41 and 42); it is for the perception of auditory impulse, auditory association area (area 22, 21, and 20): Areas 21 and 20 are for understanding and interpretation of auditory sensation, recognition of language, and long-term memories. Area 22, also called Wernicke’s area, and a sensory speech centre. It is for interpretation of auditory and visual information, formation of thoughts in the mind, and choice of words to be used. Ideas and thoughts originate in it. The limbic system is a part of cortical and subcortical structure forming a ring around the brainstem. Cortical structures are the orbitofrontal area, subcallosal gyrus, cingulate gyrus, parahippocampal gyrus, and uncus. Subcortical structures are the hypothalamus, hippocampus, amygdala, septum, paraolfactory area, anterior nucleus of the thalamus portions of the basal ganglia. There are several physiological functions of the limbic system, including regulation of behavior, motivation, and emotion.

Keywords: limbic system, motivation, emotions, temporal lobe

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Authors: Behnam Tavakkol

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Uncertain data mining algorithms use different ways to consider uncertainty in data such as by representing a data object as a sample of points or a probability distribution. Fuzzy methods have long been used for clustering traditional (certain) data objects. They are used to produce non-crisp cluster labels. For uncertain data, however, besides some uncertain fuzzy k-medoids algorithms, not many other fuzzy clustering methods have been developed. In this work, we develop a fuzzy kernel k-medoids algorithm for clustering uncertain data objects. The developed fuzzy kernel k-medoids algorithm is superior to existing fuzzy k-medoids algorithms in clustering data sets with non-linearly separable clusters.

Keywords: clustering algorithm, fuzzy methods, kernel k-medoids, uncertain data

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Authors: Mohammad Reza Boromand, Masoud Moradi, Amin Eskandari

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The present study attempts to determine ranking of managerial parameters impacting upon performance of football referees in Iran. The population consisted of all referees in Leagues 1, 2 and 3 as well as super league of Iran (N=273), of which we selected 160 referees and assistant referees in 2013-2014. A research-designed questionnaire was used for data collection which was divided into two sections: (1) Demographic details (age range, Marital status, employment, refereeing experience, education level, refereeing level and proficiency) and (2) items related to parameters impacting upon performance of referees (structural parameters, operational parameters, environmental parameters, temporal parameters, economic parameters, facilities and tools, personal performance and performance evaluation). Internal consistency was calculated by Cronbach's alpha (r=0.85). For data analysis, we performed Freedman's Test and used SPSS software (α>0.05), along with descriptive statistics. The findings showed the following ranking for the above-mentioned managerial parameters: Facilities and tools, personal performance, economic parameters, structural parameters, operational parameters, environmental parameters, temporal parameters, and performance evaluation.

Keywords: Iran, football referees, managerial parameters, performance

Procedia PDF Downloads 563

Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial Neural network, Competitive dynamics, Logistic Regression, Text classification, Text mining

Procedia PDF Downloads 118

Authors: Congping Lin

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Intracellular transport in fungi has a number of important roles in, e.g., filamentous fungal growth and cellular metabolism. Two basic mechanisms for intracellular transport are motor-driven trafficking along microtubules (MTs) and diffusion. Mathematical modelling has been actively developed to understand such intracellular transport and provide unique insight into cellular complexity. Based on live-cell imaging data in Ustilago hyphal cells, probabilistic models have been developed to study mechanism underlying spatial organization of molecular motors and organelles. In particular, anther mechanism - stochastic motility of dynein motors along MTs has been found to contribute to half of its accumulation at hyphal tip in order to support early endosome (EE) recycling. The EE trafficking not only facilitates the directed motion of peroxisomes but also enhances their diffusive motion. Considering the importance of spatial organization of early endosomes in supporting peroxisome movement, computational and experimental approaches have been combined to a whole-cell level. Results from this interdisciplinary study promise insights into requirements for other membrane trafficking systems (e.g., in neurons), but also may inform future 'synthetic biology' studies.

Keywords: intracellular transport, stochastic process, molecular motors, spatial organization

Procedia PDF Downloads 127

Authors: Rubab Z. Kahlon, Ibtisam Butt, Isma Younis, Aamer G. Mufti

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Worldwide lung cancer 1.61 million cases were seen in both genders. Lung carcinoma is the major cause of both morbidity and mortality in the world. Purpose of the present study was to describe the spatio- temporal trends of lung cancer in both genders. A retrospective study was conducted. Total 1498 patients of lung carcinoma were examined. Only lung cancer patients from all over the Punjab were included in the present study. MS Excel 2010 was used for data tabulation and calculation while the Arc GIS version 9.3 was used for geographical representation of the data. 1498 cases of Lung cancer were found from 2008-2012. The number of male patients was 1236 and female was 262. Majority of the patients were from Lahore districts with 807 patients. Lung cancer was more prevalent in male as compared to female in our region. Increase in the prevalence of lung cancer was prominently seen in the most populated and industrial areas of the Punjab province. Time trend of five years showed fluctuation in the lung cancer incidence during the study period.

Keywords: districts, gender, lung cancer trends, Punjab province of Pakistan

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Authors: Irna Malganova

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The paper assessed the effectiveness of the use of urban functional zoning using the method of M.A. Kramer by the example of Kazan city (Republic of Tatarstan, Russian Federation) using geoinformation technologies. On the basis of the data obtained, the calculations were carried out to obtain data on population density, overcoming geographic determinism, as well as the effectiveness of the formation of urban frameworks. The authors proposed recommendations for the effectiveness of municipal frameworks in the period from 2018 to 2021: economic, social, environmental and social. The study of effective territorial planning in a given period allows to display of the dynamics of planning changes, as well as assessment of changes in the formation of urban frameworks. Based on the incoming data obtained from the master plan of the municipal formation of Kazan, in the period from 2018 to 2021, there was an increase in population by 13841 people or 1.1% of the values of 2018. In addition, the area of Kazan increased by 2419.6 hectares. In the structure of the distribution of areas of functional zones, there was an increase in such zones of the municipality as zones of residential and public purpose. Changes in functional zoning, as well as territories requiring reorganization, are presented using geoinformation technologies in open-source software Quantum Geographic Information System (QGIS 3.32). According to the calculations based on the method of functional zoning efficiency by M.A. Kreimer, the territorial-planning structure of Kazan City is quite effective. However, in the development of spatial planning concepts, it is possible to emphasize the weakened interest of the population in the development of territorial planning documents. Thus, the approach to spatial planning of Kazan differs from foreign methods and approaches based on the joint development of planning directions and development of territories of municipalities between the developers of the planning structure, business representatives and the population. The population plays the role of the target audience on which territorial planning is oriented. It follows that there is a need to satisfy the opinions and demands of the population.

Keywords: spatial development, metamorphosis, Kazan city, spatial planning, efficiency, geographic determinism., GIS, QGIS

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Authors: Lauren C. Porter, Andrew Curtis, Eric Jefferis, Susanne Mitchell

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A wealth of research has been generated examining the variation in crime across neighborhoods. However, there is also a striking degree of crime concentration within neighborhoods. A number of studies show that a small percentage of street segments, intersections, or addresses account for a large portion of crime. Not surprisingly, a focus on these crime hot spots can be an effective strategy for reducing community level crime and related ills, such as health problems. However, research is also limited in an important respect. Studies tend to use official data to identify hot spots, such as 911 calls or calls for service. While the use of call data may be more representative of the actual level and distribution of crime than some other official measures (e.g. arrest data), call data still suffer from the 'dark figure of crime.' That is, there is most certainly a degree of error between crimes that occur versus crimes that are reported to the police. In this study, we present an alternative method of identifying crime hot spots, that does not rely on official data. In doing so, we highlight the potential utility of neighborhood-insiders to identify and understand crime dynamics within geographic spaces. Specifically, we use spatial video and geo-narratives to record the crime insights of 36 police, ex-offenders, and residents of a high crime neighborhood in northeast Ohio. Spatial mentions of crime are mapped to identify participant-identified hot spots, and these are juxtaposed with calls for service (CFS) data. While there are bound to be differences between these two sources of data, we find that one location, in particular, a corner store, emerges as a hot spot for all three groups of participants. Yet it does not emerge when we examine CFS data. A closer examination of the space around this corner store and a qualitative analysis of narrative data reveal important clues as to why this store may indeed be a hot spot, but not generate disproportionate calls to the police. In short, our results suggest that researchers who rely solely on official data to study crime hot spots may risk missing some of the most dangerous places.

Keywords: crime, narrative, video, neighborhood

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Authors: Javad Someehneshin, Weizhou Quan, Abdelsalam Abugharara, Stephen Butt

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Narrow vein mining (NVM) is exploiting very thin but valuable ore bodies that are uneconomical to extract by conventional mining methods. NVM applies the technique of Sustainable Mining by Drilling (SMD). The SMD method is used to mine stranded, steeply dipping ore veins, which are too small or isolated to mine economically using conventional methods since the dilution is minimized. This novel mining technique uses drilling rigs to extract the ore through directional drilling surgically. This paper is focusing on utilizing the run of the mine tailings and Portland cement as backfill material to support the hanging wall for providing safe mine operation. Cemented paste backfill (CPB) is designed by mixing waste tailings, water, and cement of the precise percentage for optimal outcomes. It is a non-homogenous material that contains 70-85% solids. Usually, a hydraulic binder is added to the mixture to increase the strength of the CPB. The binder fraction mostly accounts for 2–10% of the total weight. In the mining industry, CPB has been improved and expanded gradually because it provides safety and support for the mines. Furthermore, CPB helps manage the waste tailings in an economical method and plays a significant role in environmental protection.

Keywords: backfilling, cement backfill, tailings, Portland cement

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Authors: T. Garba, Y. Y. Babanyara, M. Isah, A. K. Muktari, R. Y. Abdullahi

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The increased in demand of fuel wood for heating, cooking and sometimes bakery has continued to exert appreciable impact on natural vegetation. This study focus on the use of multi-temporal data from land sat TM of 1986, land sat EMT of 1999 and lands sat ETM of 2006 to investigate the changes of Natural Vegetation resulting from charcoal production activities. The three images were classified based on bare soil, built up areas, cultivated land, and natural vegetation, Rock out crop and water bodies. From the classified images Land sat TM of 1986 it shows natural vegetation of the study area to be 308,941.48 hectares equivalent to 50% of the area it then reduces to 278,061.21 which is 42.92% in 1999 it again depreciated to 199,647.81 in 2006 equivalent to 30.83% of the area. Consequently cultivated continue increasing from 259,346.80 hectares (42%) in 1986 to 312,966.27 hectares (48.3%) in 1999 and then to 341.719.92 hectares (52.78%). These show that within the span of 20 years (1986 to 2006) the natural vegetation is depreciated by 119,293.81 hectares. This implies that if the menace is not control the natural might likely be lost in another twenty years. This is because forest cleared for charcoal production is normally converted to farmland. The study therefore concluded that there is the need for alternatives source of domestic energy such as the use of biomass which can easily be accessible and affordable to people. In addition, the study recommended that there should be strong policies enforcement for the protection forest reserved.

Keywords: charcoal, classification, data, images, land use, natural vegetation

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Authors: Chunxiao Wu, Dongyun Jiang, Tao Jiang, Luxia Xu, Qian Xu, Meng Zhao, Qin Zhu, Zhigang Guo, Jinlan Pan, Suning Chen

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The stability and evolution of human genetics depends on chromosomes (and chromosome-chromosome interactions). We wish to understand the spatial location of chromosomes in dividing cells in order to understand the relationship between chromosome-chromosome interactions and to further investigate the role of chromosomes and their impact on cell biological behavior. In this study, we explored the relative spatial positional relationships of chromosomes [t (9;22) and t (15;17)] in B-ALL cells by using the three-dimensions DNA in situ fluorescent hybridization (3D-FISH) method. The results showed that chromosomes [t (9;22) and t (15;17)] showed relatively stable spatial relationships. The relative stability of the spatial location of chromosomes in dividing cells may be relevant to disease.

Keywords: chromosome, human genetics, chromosome territory, 3D-FISH

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Authors: Musyimi Mbathi

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Information regarding social, political, demographic, economic and other attributes of human settlement is important for decision makers at all levels of planning, as they have to grapple with dynamic environments often associated with settlements. At the local level, it is particularly important for both communities and urban managers to have accurate and reliable information regarding all planning attributes. Settlement mapping, in particular, informal settlements mapping in Kenya, has over the past few years been carried out using modern tools like Geographic information systems (GIS) and remote sensing for spatial data analysis and planning. GIS tools offer a platform for integration of spatial and non-spatial data as well as visualisation of the settlements. The capabilities offered by these tools have enabled communities to participate especially in the planning and management of new infrastructure as well as settlement upgrading. Land tenure based projects within informal settlements have also relied on GIS and related tools with considerable success. Additionally, the adoption of participatory approaches and use of geo-information tools helped to provide a basis for all inclusive planning thus promoting accountability, transparency, legitimacy, and other dimensions of governance within human settlement planning. The paper examines the context and application of geo-information tools for planning within low-income settlements of Kenya. A case study of Kiambiu settlement will be used to demonstrate how the tools have been applied for planning and decision-making purposes.

Keywords: informal settlements, GIS, governance, modern tools

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Authors: Iacopo Testi, Diego Pajarito, Nicoletta Roberto, Carmen Greco

Abstract:

Today, a consistent segment of the world’s population lives in urban areas, and this proportion will vastly increase in the next decades. Therefore, understanding the key trends in urbanization, likely to unfold over the coming years, is crucial to the implementation of sustainable urban strategies. In parallel, the daily amount of digital data produced will be expanding at an exponential rate during the following years. The analysis of various types of data sets and its derived applications have incredible potential across different crucial sectors such as healthcare, housing, transportation, energy, and education. Nevertheless, in city development, architects and urban planners appear to rely mostly on traditional and analogical techniques of data collection. This paper investigates the prospective of the data science field, appearing to be a formidable resource to assist city managers in identifying strategies to enhance the social, economic, and environmental sustainability of our urban areas. The collection of different new layers of information would definitely enhance planners' capabilities to comprehend more in-depth urban phenomena such as gentrification, land use definition, mobility, or critical infrastructural issues. Specifically, the research results correlate economic, commercial, demographic, and housing data with the purpose of defining the youth economic discomfort index. The statistical composite index provides insights regarding the economic disadvantage of citizens aged between 18 years and 29 years, and results clearly display that central urban zones and more disadvantaged than peripheral ones. The experimental set up selected the city of Rome as the testing ground of the whole investigation. The methodology aims at applying statistical and spatial analysis to construct a composite index supporting informed data-driven decisions for urban planning.

Keywords: data science, spatial analysis, composite index, Rome, urban planning, youth economic discomfort index

Procedia PDF Downloads 127

Authors: Jamal R. Elbergali

Abstract:

Multiple Input Multiple Output (MIMO) systems are wireless systems with multiple antenna elements at both ends of the link. Wireless communication systems demand high data rate and spectral efficiency with increased reliability. MIMO systems have been popular techniques to achieve these goals because increased data rate is possible through spatial multiplexing scheme and diversity. Spatial Multiplexing (SM) is used to achieve higher possible throughput than diversity. In this paper, we propose a Zero-Forcing (ZF) detection using a combination of Ordered Successive Interference Cancellation (OSIC) and Zero Forcing using Interference Cancellation (ZF-IC). The proposed method used an OSIC based on Signal to Noise Ratio (SNR) ordering to get the estimation of last symbol (x ̃_(N_T )), then the estimated last symbol is considered to be an input to the ZF-IC. We analyze the Bit Error Rate (BER) performance of the proposed MIMO system over Rayleigh Fading Channel, using Binary Phase Shift Keying (BPSK) modulation scheme. The results show better performance than the previous methods.

Keywords: SNR, BER, BPSK, MIMO, modulation, zero forcing (ZF), OSIC, ZF-IC, spatial multiplexing (SM)

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Authors: Geng-Gui Wang, Chia-Hao Chang, Jee-Cheng Wu

Abstract:

A shoreline is a line where a body of water and the shore meet. It provides economic and social security to coastal habitations. However, shorelines face multiple threats due to both natural processes and man-made effects because of disasters, rapid urbanization, industrialization, and sand deposition and erosion, etc. In this study, we analyzed multi-temporal satellite images of the Yilan coast, Taiwan from 1978 to 2016, using the United States Geological Survey (USGS) Digital Shoreline Analysis System (DSAS), weather information (as rainfall records and typhoon routes), and man-made construction project data to explore the causes of shoreline changes. The results showed that the shoreline at Yilan coast is greatly influenced by typhoons and anthropogenic interventions.

Keywords: shoreline change, multi-temporal satellite, digital shoreline analysis system, DSAS, Yi-Lan coast

Procedia PDF Downloads 157

Authors: Ziwei Huang

Abstract:

The standard unit of Shenzhen land spatial planning has the characteristics of vertical conduction, horizontal evaluation, internal balance and supervision of implementation. It mainly assumes the role of geospatial unit, assists in promoting the complex development of the business in Shenzhen and undertakes the management and transmission of upper and lower levels of planning as well as the Urban management functions such as gap analysis of public facilities, planning evaluation and dynamic monitoring of planning information. Combining with the application examples of the analysis of gaps in public facilities in Longgang District, it can be found that the standard unit of land spatial planning in Shenzhen as a small-scale geographic basic unit, has a stronger urban spatial coupling effect. However, the universality of the application of the system is still lacking and it is necessary to propose more scientific and powerful standard unit delineation standards and planning function evaluation indicators to guide the implementation of the system's popularization and application.

Keywords: Shenzhen city, land spatial planning, standard unit system, urban delicacy management

Procedia PDF Downloads 118

Authors: Liu Mingxin

Abstract:

Streets act as the organizers of each image element on the urban spatial route, and the spatial continuity of urban streets is the basis for people to perceive the overall image of the city. This paper takes the walking space of Zhengzhou city as the research object, conducts investigation and analysis through questionnaire interviews, and selects typical walking space for in-depth study. Through the analysis of questionnaire data, the investigation and analysis of the current situation of walking space, and the analysis of pedestrian psychological behavior activities, the paper summarizes the construction suggestions of urban walking space continuity from the three aspects of the composition of walking street, the bottom interface and side interface, and the service facilities of walking space. The walking space is not only the traffic space but also the comfortable experience and the continuity of the space.

Keywords: walking space, spatial continuity, walking psychology, space reconstruction

Procedia PDF Downloads 32