Search results for: ecological binary data

Authors: P. Srinivasa Rao, K. Venkatesh Sharma, G. Sadhya Devi, V. Nagesh

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Privacy Preserving Data Publication is the main concern in present days because the data being published through the internet has been increasing day by day. This huge amount of data was named as Big Data by its size. This project deals the privacy preservation in the context of Big Data using a data warehousing solution called hive. We implemented Nearest Similarity Based Clustering (NSB) with Bottom-up generalization to achieve (v,l)-anonymity. (v,l)-Anonymity deals with the sensitivity vulnerabilities and ensures the individual privacy. We also calculate the sensitivity levels by simple comparison method using the index values, by classifying the different levels of sensitivity. The experiments were carried out on the hive environment to verify the efficiency of algorithms with Big Data. This framework also supports the execution of existing algorithms without any changes. The model in the paper outperforms than existing models.

Keywords: sensitivity, sensitive level, clustering, Privacy Preserving Data Publication (PPDP), bottom-up generalization, Big Data

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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: M. Illias Kanchan

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The death of a woman during pregnancy and childbirth is not only a health issue, but also a matter of social injustice. This study makes an attempt to explore the association between maternal death and associated factors in West Bengal using the approaches of facility-based and community-based maternal death review. Bivariate and binary logistic regression analysis have been performed to understand the causes and circumstances of maternal deaths in West Bengal. Delay in seeking care was the major contributor in maternal deaths, near about one-third women died due to this factor. The most common cause of maternal death is found to be hypertensive disorders of pregnancy or eclampsia. We believe that these deaths can be averted by reducing hypertensive disorders of pregnancy or eclampsia.

Keywords: maternal death, facility-based, community-based, review, west Bengal, eclampsia

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Authors: Bedilu Tafesse

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The diversity and ecological analysis of vascular epiphytes was studied in Gera Forest in southwestern Ethiopia at altitudes between 1600 and 2400 m.a.s.l. A total area of 4.5 ha was surveyed in coffee and non-coffee forest vegetation. Fifty sampling plots, each 30 m x 30 m (900 m2), were used for the purpose of data collection. A total of 59 species of vascular epiphytes were recorded, of which 34 (59%) were holo epiphytes, two (4%) were hemi epiphytes and 22 (37%) species were accidental vascular epiphytes. To study the altitudinal distribution of vascular epiphytes, altitudes were classified into higher >2000, middle 1800-2000 and lower 1600-1800 m.a.s.l. According to Shannon-Wiener Index (H/= 3.411) of alpha diversity the epiphyte community in the study area is medium. There was a statistically significant difference between host bark type and epiphyte richness as determined by one-way ANOVA p = 0.001 < 0.05. The post-hoc test shows that there is significant difference of vascular epiphytes richness between smooth bark with rough, flack and corky bark (P =0.001< 0.05), as well as rough and cork bark (p =0.43 <0.05). However, between rough and flack bark (p = 0.753 > 0.05) and between flack and corky bark (p = 0.854 > 0.05) no significant difference of epiphyte abundance was observed. Rough bark had 38%, corky 26%, flack 25%, and only 11% vascular epiphytes abundance occurred on smooth bark. The regression correlation test, (R2 = 0.773, p = 0.0001 < 0.05), showed that the number of species of vascular epiphytes and host DBH size are positively correlated. The regression correlation test (R2 = 0.28, p = 0.0001 < 0.05), showed that the number of species and host tree height positively correlated. The host tree preference of vascular epiphytes was recorded for only Vittaria volkensii species hosted on Syzygium guineense trees. The result of similarity analysis indicated that Gera Forest showed the highest vascular epiphytic similarity (0.35) with Yayu Forest and shared the least vascular epiphytic similarity (0.295) with Harenna Forest. It was concluded that horizontal stems and branches, large and rough, flack and corky bark type trees are more suitable for vascular epiphytes seedling attachments and growth. Conservation and protection of these phorophytes are important for the survival of vascular epiphytes and increase their ecological importance.

Keywords: accidental epiphytes, hemiepiphyte, holoepiphyte, phorophyte

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Authors: Nirmala Gopal, Sheetal Bhoola, Audecious Mugwagwa

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This paper discusses the continued infringement and exploitation of data by non-state actors for destructive purposes, emphasizing radical terrorist organizations. It will discuss how terrorist organizations access and use data to foster their nefarious agendas. It further examines how cybersecurity, designed as a tool to curb data exploitation, is ineffective in raising global citizens' concerns about how their data can be kept safe and used for its acquired purpose. The study interrogates several policies and data protection instruments, such as the Data Protection Act, Cyber Security Policies, Protection of Personal Information(PPI) and General Data Protection Regulations (GDPR), to understand data use and storage in democratic states. The study outcomes point to the fact that international cybersecurity and cybercrime legislation, policies, and conventions have not curbed violations of data access and use by radical terrorist groups. The study recommends ways to enhance cybersecurity and reduce cyber risks using democratic principles.

Keywords: cybersecurity, data exploitation, terrorist organizations, data democracy

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Authors: Eugenia Jilinguirian

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In the healthcare industry, data mining is essential since it transforms the field by collecting useful data from large datasets. Data mining is the process of applying advanced analytical methods to large patient records and medical histories in order to identify patterns, correlations, and trends. Healthcare professionals can improve diagnosis accuracy, uncover hidden linkages, and predict disease outcomes by carefully examining these statistics. Additionally, data mining supports personalized medicine by personalizing treatment according to the unique attributes of each patient. This proactive strategy helps allocate resources more efficiently, enhances patient care, and streamlines operations. However, to effectively apply data mining, however, and ensure the use of private healthcare information, issues like data privacy and security must be carefully considered. Data mining continues to be vital for searching for more effective, efficient, and individualized healthcare solutions as technology evolves.

Keywords: data mining, healthcare, big data, individualised healthcare, healthcare solutions, database

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Authors: Yunus Doğan, Ahmet Durap

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Coastal regions are the one of the most commonly used places by the natural balance and the growing population. In coastal engineering, the most valuable data is wave behaviors. The amount of this data becomes very big because of observations that take place for periods of hours, days and months. In this study, some statistical methods such as the wave spectrum analysis methods and the standard statistical methods have been used. The goal of this study is the discovery profiles of the different coast areas by using these statistical methods, and thus, obtaining an instance based data set from the big data to analysis by using data mining algorithms. In the experimental studies, the six sample data sets about the wave behaviors obtained by 20 minutes of observations from Mersin Bay in Turkey and converted to an instance based form, while different clustering techniques in data mining algorithms were used to discover similar coastal places. Moreover, this study discusses that this summarization approach can be used in other branches collecting big data such as medicine.

Keywords: clustering algorithms, coastal engineering, data mining, data summarization, statistical methods

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Authors: Vasti Oelofse, Niekie van der Merwe, Dorita du Toit

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This study addresses the need for a unified best practice model for Physical Education across BRICS nations, as current research primarily offers individual country recommendations. Drawing on relevant literature within the framework of Bronfenbrenner’s Ecological Systems Theory, as well as data from open-ended questionnaires completed by Physical Education experts from the BRICS countries, , the study develops a best practice model based on identified challenges and effective practices in Physical Education. A model is proposed that incorporates flexible and resource-efficient strategies tailored to address PE challenges specific to these countries, enhancing outcomes for learners, empowering teachers, and fostering systemic collaboration among BRICS members. The proposed model comprises six key areas: “Curriculum and policy requirements”, “General approach”, “Theoretical basis”, “Strategies for presenting content”, “Teacher training”, and “Evaluation”. The “Strategies for presenting program content” area addresses both well-resourced and poorly resourced schools, adapting curriculum, teaching strategies, materials, and learner activities for varied socio-economic contexts. The model emphasizes a holistic approach to learner development, engaging environments, and continuous teacher training. A collaborative approach among BRICS countries, focusing on shared best practices and continuous improvement, is vital for the model's successful implementation, enhancing Physical Education programs and outcomes across these nations.

Keywords: BRICS countries, physical education, best practice model, ecological systems theory

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Authors: Tagore Sai Priya Nunna, Ankhi Banerjee

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The rapid growth of the tourism industry in India in the last few years after the economic crisis in 2009 has been one of the significant causes that led to the Land Use Land Cover change (LULC) of most tourism destinations. The tourist regions are subjected to significant increase in built-up due to increased construction activities for developing accommodation facilities further boosting tourism demand. This research attempts to analyse the changing LULC and the growth pattern of the built-up area within tourist destinations. Four popular tourist destinations, which promises various types of tourism activity and which are significantly dependent on tourism for economic growth, are selected for the study. The study uses remotely sensed data for analysis of land use change through supervised segmentation into five broad classes. Further, the landuse map is reclassified into binary classes to extract the built-up area. The growth patterns of the built-up are analysed in terms of size, shape, direction and form of growth, through a set of spatial metrics. Additionally, a detailed analysis of the existing development pattern corresponding to planned development zones was performed to identify unplanned growth spots in the study regions. The findings of the study provide insights into how tourism has contributed to significant changes in LULC around tourist sites. Also, the study highlights the growth pattern of built-up areas with respect to the type of tourism activity and geographical characteristics. The research attempts to address the need of integrating spatial metrics for the development of sustainable tourism plans as part of the goals of sustainable development.

Keywords: built-up, growth, patterns, tourism, sustainable

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Authors: Anny Retnowati, Elisabeth Sundari

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This research aims to elaborate the meaning of personal data protection principles on patient access to health data in medical records in Indonesia and its implications. The method uses normative legal research by examining health law in Indonesia regarding the patient's right to access their health data in medical records. The data will be analysed qualitatively using the interpretation method to elaborate on the limitation of the meaning of personal data protection principles on patients' access to their data in medical records. The results show that patients only have the right to obtain copies of their health data in medical records. There is no right to inspect directly at any time. Indonesian health law limits the principle of patients' right to broad access to their health data in medical records. This restriction has implications for the reduction of personal data protection as part of human rights. This research contribute to show that a limitaion of personal data protection may abuse the human rights.

Keywords: access, health data, medical records, personal data, protection

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Authors: Martin Böhmer, Agatha Dabrowski, Boris Otto

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The trend of digitization significantly changes the role of data for enterprises. Data turn from an enabler to an intangible organizational asset that requires management and qualifies as a tradeable good. The idea of a networked economy has gained momentum in the data domain as collaborative approaches for data management emerge. Traditional organizational knowledge consequently needs to be extended by comprehensive knowledge about data. The knowledge about data is vital for organizations to ensure that data quality requirements are met and data can be effectively utilized and sovereignly governed. As this specific knowledge has been paid little attention to so far by academics, the aim of the research presented in this paper is to conceptualize it by proposing a “data knowledge model”. Relevant model entities have been identified based on a design science research (DSR) approach that iteratively integrates insights of various industry case studies and literature research.

Keywords: data management, digitization, industry 4.0, knowledge engineering, metamodel

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Authors: Oral S. Saulters, Shanon D. Goldberg, Wendy A. Staples, Ellena I. Martinez, Lorie M. Sanchez, Diego E. Archuleta, Deborah L. Williams, Scot D. Johnson

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To address an important set of unverified field conditions, the Los Alamos National Laboratory Waste Compliance and Tracking System (WCATS) Wall-to-Wall Team performed an unprecedented and advanced inventory. This reconciliation involved confirmation analysis for approximately 5850 hazardous, low-level, mixed low-level, and transuranic waste containers located in more than 200 staging and storage areas across 33 technical areas. The interdisciplinary team scoped, planned, and developed the multidimensional assessments. Through coordination with cross-functional site hosts, they were able to verify and validate data while resolving discrepancies identified in WCATS. The results were extraordinary with an updated inventory, tailored outreach, more cohesive communications, and timely closed-loop feedback.

Keywords: circular economy, environmental performance data, social-ecological-technological systems, waste management

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Authors: M. Unaldi, R. Kus

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Brake pads are important parts of the braking system and they are made of different materials. Use of asbestos fibre can cause health risks. The goal of this study is to determine the effect of ecological brake pad samples which are produced under different compaction pressure values and mixture ratios by using miscanthus as reinforcement component on the density, hardness, wear rate and compression strength properties, and friction coefficients changes of ecological brake pad samples. Miscanthus powder, cashew powder, alumina powder, phenolic resin powder, and calcite powder mixtures were used to produce ecological brake pad samples. The physical properties of the brake pad samples produced under different mixture ratios and compaction pressures values were determined to assign their effects on them by using Taguchi experimental design. Mixture ratios and compaction pressures values were chosen as the factors with three-levels. Experiments are conducted to L₉(3⁴) Taguchi orthogonal array design. The results showed that hardness value is very much affected both compaction pressure values and mixture ratios than the other physical properties. When reinforcing component ratio within the mixture and compaction pressure value is increased, hardness and compression strength values of the all samples are also increased. All test results taking into account, the ideal compaction value for used components and mixture ratios were determined as 200 MPa.

Keywords: brake pad, eco-friendly materials, hardness, Miscanthus, Taguchi method

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Authors: Manaranjan Pradhan, Shailaja Grover, U. Dinesh Kumar

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Farming community in India, as well as other parts of the world, is one of the highly stressed communities due to reasons such as increasing input costs (cost of seeds, fertilizers, pesticide), droughts, reduced revenue leading to farmer suicides. Lack of integrated farm advisory system in India adds to the farmers problems. Farmers need right information during the early stages of crop’s lifecycle to prevent damage and loss in revenue. In this paper, we use deep learning techniques to develop an early warning system for detection of crop diseases using images taken by farmers using their smart phone. The research work leads to building a smart assistant using analytics and big data which could help the farmers with early diagnosis of the crop diseases and corrective actions. The classical approach for crop disease management has been to identify diseases at crop level. Recently, ImageNet Classification using the convolutional neural network (CNN) has been successfully used to identify diseases at individual plant level. Our model uses convolution filters, max pooling, dense layers and dropouts (to avoid overfitting). The models are built for binary classification (healthy or not healthy) and multi class classification (identifying which disease). Transfer learning is used to modify the weights of parameters learnt through ImageNet dataset and apply them on crop diseases, which reduces number of epochs to learn. One shot learning is used to learn from very few images, while data augmentation techniques are used to improve accuracy with images taken from farms by using techniques such as rotation, zoom, shift and blurred images. Models built using combination of these techniques are more robust for deploying in the real world. Our model is validated using tomato crop. In India, tomato is affected by 10 different diseases. Our model achieves an accuracy of more than 95% in correctly classifying the diseases. The main contribution of our research is to create a personal assistant for farmers for managing plant disease, although the model was validated using tomato crop, it can be easily extended to other crops. The advancement of technology in computing and availability of large data has made possible the success of deep learning applications in computer vision, natural language processing, image recognition, etc. With these robust models and huge smartphone penetration, feasibility of implementation of these models is high resulting in timely advise to the farmers and thus increasing the farmers' income and reducing the input costs.

Keywords: analytics in agriculture, CNN, crop disease detection, data augmentation, image recognition, one shot learning, transfer learning

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Authors: J-C. Leneveu, A. Chereau, L. Mansart, T. Mesbah, M. Wyka

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Extracting and interpreting information from Big Data represent a stake for years to come in several sectors such as finance. Currently, numerous methods are used (such as Technical Analysis) to try to understand and to anticipate market behavior, with mixed results because it still seems impossible to exactly predict a financial trend. The increase of available data on Internet and their diversity represent a great opportunity for the financial world. Indeed, it is possible, along with these standard financial data, to focus on exogenous data to take into account more macroeconomic factors. Coupling the interpretation of these data with standard methods could allow obtaining more precise trend predictions. In this paper, in order to observe the influence of exogenous data price independent of other usual effects occurring in classical markets, behaviors of Bitcoin users are introduced in a model reconstituting Bitcoin value, which is elaborated and tested for prediction purposes.

Keywords: big data, bitcoin, data mining, social network, financial trends, exogenous data, global economy, behavioral finance

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Authors: Mingbao Chen

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The blue economy is a new comprehensive marine economy integrated with resources, industries, and regions, and is an upgraded version of the marine economy. The blue economy attaches great importance to the coordinated development of the ecological environment and the economy, which is an emerging economic form advocated by all countries in the world. This paper constructs the model including four variables：natural capital, economic capital, intellectual capital, cultural capital. Theoretically, this paper deduces the function mechanism of variables on economic growth, and empirically calculates the driving force and influence of the blue economy on the national economy by using data of China's 2006-2015 year. The results show that natural capital and economic capital remain the main factors of blue growth in the blue economy. And with the development of economic society and technological progress, the role of intellectual capital and cultural capital is bigger and bigger. Therefore, promoting the development of marine science and technology and culture is the focus of the future blue economic development.

Keywords: blue growth, natural capital, intellectual capital, cultural capital

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Authors: Jong-Ho Moon, Dong-Ho Lee, Hyunuk Kim, Young Cheol Park, Jong-Seop Lee, Jae-deok Jeon, Hyung-Keun Lee

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A novel membrane reactor process for DMC synthesis from carbon dioxide has been developing in Korea Institute of Energy Research. The scheme of direct synthesis of DMC from CO₂ and Methanol is 'CO₂ + 2MeOH ↔ DMC + H₂O'. Among them, reactants are CO₂ and MeOH, product is DMC, and byproduct is H₂O (water). According to Le Chatelier’s principle, removing byproduct (water) can shift the reaction equilibrium to the right (DMC production). The main purpose of this process is removing water during the reaction. For efficient in situ water removal (dehydration) and DMC separation, zeolite 4A membranes with very small pore diameter and hydrophilicity were introduced. In this study, pervaporation performances of binary and ternary DMC / methanol / water mixtures were evaluated.

Keywords: dimehtyl carbonate, methanol, water, zeolite membrane, pervaporation

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Authors: A. Elsariti, T. Evans

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An understanding of the interaction between acoustic waves and cancellous bone is needed in order to realize the full clinical potential of ultrasonic bone measurements. Scattering is likely to be of central importance but has received little attention to date. Few theoretical approaches have been described to explain scattering of ultrasound from bone. In this study, a scattering model based on velocity and density fluctuations in a binary mixture (marrow fat and cortical matrix) was used to estimate the ultrasonic attenuation in cancellous bone as a function of volume fraction. Predicted attenuation and backscatter coefficient were obtained for a range of porosities and scatterer size. At 600 kHZ and for different scatterer size the effect of velocity and density fluctuations in the predicted attenuation was approximately 60% higher than velocity fluctuations.

Keywords: ultrasound scattering, sound speed, density fluctuations, attenuation coefficient

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Authors: Tabugbo B. Ifeyinwa, Josephat O. Ogbuagu, Okeke A. Princewill, Victor C. Eze

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The increasing amount of plastic pollution in maritime settings poses a substantial risk to the functioning of ecosystems and the preservation of biodiversity. This comprehensive analysis combines the most recent data on the environmental effects of pollution from macroplastics, microplastics, and nanoplastics within marine ecosystems. Our goal is to provide a comprehensive understanding of the cumulative impacts that plastic waste accumulates on marine life by outlining the origins, processes, and ecological repercussions connected with each size category of plastic debris. Microplastics and nanoplastics have more sneaky effects that are controlled by chemicals. These effects can get through biological barriers and affect the health of cells and the whole body. Compared to macroplastics, which primarily contribute to physical harm through entanglement and ingestion by marine fauna, microplastics, and nanoplastics are associated with non-physical effects. The review underlines a vital need for research that crosses disciplinary boundaries to untangle the intricate interactions that the various sizes of plastic pollution have with marine animals, evaluate the long-term ecological repercussions, and identify effective measures for mitigating the effects of plastic pollution. Additionally, we urge governmental interventions and worldwide cooperation to solve this pervasive environmental concern. Specifically, we identify significant knowledge gaps in the detection and effect assessment of nanoplastics. To protect marine biodiversity and preserve ecosystem services, this review highlights how urgent it is to address the broad spectrum of plastic pollution.

Keywords: macroplastic pollution, marine ecosystem, microplastic pollution, nanoplastic pollution

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Authors: Ejiobih Hyginus Chidozie

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Geographic Information System (GIS) is a configuration of computer hardware and software specifically designed to effectively capture, store, update, manipulate, analyse and display and display all forms of spatially referenced information. GIS database is referred to as the heart of GIS. It has location data, attribute data and spatial relationship between the objects and their attributes. Sewage and wastewater management have assumed increased importance lately as a result of general concern expressed worldwide about the problems of pollution of the environment contamination of the atmosphere, rivers, lakes, oceans and ground water. In this research GIS database was created to study the impacts of domestic wastewater disposal methods on Bida town, Niger State as a model for investigating similar impacts on other cities in Nigeria. Results from GIS database are very useful to decision makers and researchers. Bida Town was subdivided into four regions, eight zones, and 24 sectors based on the prevailing natural morphology of the town. GIS receiver and structured questionnaire were used to collect information and attribute data from 240 households of the study area. Domestic wastewater samples were collected from twenty four sectors of the study area for laboratory analysis. ArcView 3.2a GIS software, was used to create the GIS databases for ecological, health and socioeconomic impacts of domestic wastewater disposal methods in Bida town.

Keywords: environment, GIS, pollution, software, wastewater

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Authors: Amirmohsen Behjat, Aleck Ostry, Christina Miewald, Bernie Pauly

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Farmers’ Markets have become one of the important healthy food suppliers in both rural communities and urban settings. Farmers’ markets are evolving and their number has rapidly increased in the past decade. Despite this drastic increase, the distribution of the farmers’ markets is not even across different areas. The main goal of this study is to explore the socioeconomic, geographic, and demographic variables which affect the establishment of farmers’ market in rural communities in British Columbia (BC). Thus, the data on available farmers’ markets in rural areas were collected from BC Association of Farmers’ Markets and spatially joined to BC map at Dissemination Area (DA) level using ArcGIS software to link the farmers’ market to the respective communities that they serve. Then, in order to investigate this issue and understand which rural communities farmer’ markets tend to operate, a binary logistic regression analysis was performed with the availability of farmer’ markets at DA-level as dependent variable and Deprivation Index (DI), Metro Influence Zone (MIZ) and population as independent variables. The results indicated that DI and MIZ variables are not statistically significant whereas the population is the only which had a significant contribution in predicting the availability of farmers’ markets in rural BC. Moreover, this study found that farmers’ markets usually do not operate in rural food deserts where other healthy food providers such as supermarkets and grocery stores are non-existent. In conclusion, the presence of farmers markets is not associated with socioeconomic and geographic characteristics of rural communities in BC, but farmers’ markets tend to operate in more populated rural communities in BC.

Keywords: farmers’ markets, socioeconomic and demographic variables, metro influence zone, logistic regression, ArcGIS

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Authors: Sandra Cecilia Bautista-Rodríguez, Vladimir Melgarejo

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Climate change, loss of ecosystems, increasing poverty, increasing marginalization of rural communities and declining food security are global issues that require urgent attention. In this regard, a great deal of research has focused on how agroecosystems respond to these challenges as they provide ecosystem services (ES) that lead to higher levels of resilience, adaptation, productivity and self-sufficiency. Hence, the valuing of ecosystem services plays an important role in the decision-making process for the design and management of agroecosystems. This paper aims to define the link between ecosystem service valuation methods and ES value dimensions in agroecosystems from ecological economics and agroecology. The method used to identify valuation methodologies was a literature review in the fields of Agroecology and Ecological Economics, based on a strategy of information search and classification. The conceptual framework of the work is based on the multidimensionality of value, considering the social, ecological, political, technological and economic dimensions. Likewise, the valuation process requires consideration of the ecosystem function associated with ES, such as regulation, habitat, production and information functions. In this way, valuation methods for ES in agroecosystems can integrate more than one value dimension and at least one ecosystem function. The results allow correlating the ecosystem functions with the ecosystem services valued, and the specific tools or models used, the dimensions and valuation methods. The main methodologies identified are multi-criteria valuation (1), deliberative - consultative valuation (2), valuation based on system dynamics modeling (3), valuation through energy or biophysical balances (4), valuation through fuzzy logic modeling (5), valuation based on agent-based modeling (6). Amongst the main conclusions, it is highlighted that the system dynamics modeling approach has a high potential for development in valuation processes, due to its ability to integrate other methods, especially multi-criteria valuation and energy and biophysical balances, to describe through causal cycles the interrelationships between ecosystem services, the dimensions of value in agroecosystems, thus showing the relationships between the value of ecosystem services and the welfare of communities. As for methodological challenges, it is relevant to achieve the integration of tools and models provided by different methods, to incorporate the characteristics of a complex system such as the agroecosystem, which allows reducing the limitations in the processes of valuation of ES.

Keywords: ecological economics, agroecosystems, ecosystem services, valuation of ecosystem services

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Authors: Tannaz Alizadeh Ashrafi

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Seasonal variability in biological and ecological factors together with relevant socio-economic determinants affect the choice of fishing gear, frequency of its usage and decision about gear conversion under multi-species situation. In order to deal with the complex dynamics of fisheries, fishers, constantly, have to make decisions about how long to fish, when to go fishing, what species to target, and which gear to deploy. In this regard, the purpose of this study is to examine the dynamics of gear/ species combination in Norwegian fishery. A comprehensive vessel-level set of data for the main economically important species including: cod, haddock, saithe, shrimp and mixed catch have been obtained from the Norwegian Directorate of Fisheries covering the daily data in 2010. The present study further analyzes the level of flexibility and rationality of the fishers operating in the trawl fishery. The results show the disproportion between intention of the trawl fishers to maximize profitability of each fishing trip and their harvesting behavior in reality. Discussion is based on so-called maximizing behavior.

Keywords: trawl fishery, gear substitution, rationality, profit maximizing behavior

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Authors: Jeroen S. de Bruin, Karin Schindler, Christian Schuh

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With increasingly more mobile health applications appearing due to the popularity of smartphones, the possibility arises that these data can be used to improve the medical diagnostic process, as well as the overall quality of healthcare, while at the same time lowering costs. However, as of yet there have been no reports of a successful combination of patient-generated data from smartphones with data from clinical routine. In this paper, we describe how these two types of data can be combined in a secure way without modification to hospital information systems, and how they can together be used in a medical expert system for automatic nutritional classification and triage.

Keywords: mobile health, data integration, expert systems, disease-related malnutrition

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Authors: Davendra Singh Malik

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India is one of the mega-biodiversity countries in the world and contributing about 11.72% of global fish diversity. The Yamuna river is the longest tributary of Ganga river ecosystem, providing a natural habitat for existing fish diversity of Himalayan region of Indian subcontinent. The several hydropower dams and barrages have been constructed on different locations of major rivers in Garhwal region. These dams have caused a major ecological threat to change existing fresh water ecosystems altering water flows, interrupting ecological connectivity, fragmenting habitats and native riverine fish species. Mahseer fishes (Indian carp) of the genus Tor, are large cyprinids endemic to continental Asia popularly known as ‘Game or sport fishes’ have continued to be decimated by fragmented natural habitats due to damming the water flow in riverine system and categorized as threatened fishes of India. The fresh water fish diversity as 24 fish species were recorded from Yamuna river. The present fish catch data has revealed that mahseer fishes (Tor tor and Tor putitora) were contributed about 32.5 %, 25.6 % and 18.2 % in upper, middle and lower riverine stretches of Yaumna river. The length range of mahseer (360-450mm) recorded as dominant size of catch composition. The CPUE (catch per unit effort) of mahseer fishes also indicated about a sharp decline of fish biomass, changing growth pattern, sex ratio and maturity stages of fishes. Only 12.5 – 14.8 % mahseer female brooders have showed only maturity phases in breeding months. The fecundity of mature mahseer female fish brooders ranged from 2500-4500 no. of ova during breeding months. The present status of mahseer fishery has attributed to the over exploitative nature in Yamuna river. The mahseer population is shrinking continuously in down streams of Yamuna river due to cumulative effects of various ecological stress. Mahseer conservation programme have implemented as 'in situ fish conservation' for enhancement of viable population size of mahseer species and restore the genetic loss of mahseer fish germplasm in Yamuna river of Garhwal Himalayan region.

Keywords: conservation practice, population dynamics, tor fish species, Yamuna River

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Authors: Davendra S. Malik

Abstract:

Bhimtal lake is located between 290 21’ N latitude and 790 24’ E longitude, at an elevation of 1332m above mean sea level in the Kumaun region of Uttarakhand of Indian subcontinent. The lake surface area is decreasing in water area, depth level in relation to ecological and biological characteristics due to climatic variations, invasive land use pattern, degraded forest zones and changed agriculture pattern in lake catchment basin. The present study is focused on long and short term effects of climate change on aquatic biodiversity and productivity of Bhimtal lake. The meteorological data of last fifteen years of Bhimtal lake catchment basin revealed that air temperature has been increased 1.5 to 2.1oC in summer, 0.2 to 0.8 C in winter, relative humidity increased 4 to 6% in summer and rainfall pattern changed erratically in rainy seasons. The surface water temperature of Bhimtal lake showed an increasing pattern as 0.8 to 2.6 C, pH value decreased 0.5 to 0.2 in winter and increased 0.4 to 0.6 in summer. Dissolved oxygen level in lake showed a decreasing trend as 0.7 to 0.4mg/l in winter months. The mesotrophic nature of Bhimtal lake is changing towards eutrophic conditions and contributed for decreasing biodiversity. The aquatic biodiversity of Bhimtal lake consisted mainly phytoplankton, zooplankton, benthos and fish species. In the present study, a total of 5 groups of phytoplankton, 3 groups of zooplankton, 11 groups of benthos and 15 fish species were recorded from Bhimtal lake. The comparative data of biodiversity of Bhimtal lake since January, 2000 indicated the changing pattern of phytoplankton biomass were decreasing as 1.99 and 1.08% of Chlorophyceae and Bacilleriophyceae families respectively. The biomass of Cynophyceae was increasing as 0.45% and contributing the algal blooms during summer season in lake. The biomass of zooplankton and benthos were found decreasing in winter season and increasing during summer season. The endemic fish species (18 no.) were found in year 2000-05, as while the fish species (15 no.) were recorded in present study. The relative fecundity of major fish species were observed decreasing trends during their breeding periods in lake. The natural and anthropogenic factors were identified as ecological threats for existing aquatic biodiversity of Bhimtal lake. The present research paper emphasized on the effect of changing pattern of different climatic variables on species composition, biomass of phytoplankton, zooplankton, benthos, and fishes in Bhimtal lake of Kumaun region. The present research data will be contributed significantly to assess the changing pattern of aquatic biodiversity and productivity of Bhimtal lake with different time scale.

Keywords: aquatic biodiversity, Bhimtal lake, climate change, lake ecology

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Authors: Sombol Mokhles

Abstract:

This paper tries to show the prospects of utilising (big)data for enabling just the transition of diverse cities. Our key purpose is to offer a framework of applications and implications of utlising (big) data in comparing sustainability transitions across different cities. Relying on the cosmopolitan comparison, this paper explains the potential application of (big) data but also its limitations. The paper calls for adopting a data-driven and just perspective in including different cities around the world. Having a just and inclusive approach at the front and centre ensures a just transition with synergistic effects that leave nobody behind.

Keywords: big data, just sustainable transition, cosmopolitan city comparison, cities

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Authors: Temenuzhka Spasova, Nadya Yanakieva

Abstract:

Snow modulates the hydrological cycle and influences the functioning of ecosystems and is a significant resource for many populations whose water is harvested from cold regions. Snow observations are important for validating climate models. The accumulation and rapid melt of snow are two of the most dynamical seasonal environmental changes on the Earth’s surface. The actuality of this research is related to the modern tendencies of the remote sensing application in the solution of problems of different nature in the ecological monitoring of the environment. The subject of the study is the dynamic during the different seasons on Livingstone Island, South Shetland Islands in Antarctica and on Svalbard in Arctic. The objects were analyzed and mapped according to the Еuropean Space Agency data (ESA), acquired by sensors Sentinel-1 SAR (Synthetic Aperture Radar), Sentinel 2 MSI and GIS. Results have been obtained for changes in snow coverage during the summer-winter transition and its dynamics in the two hemispheres. The data used is of high time-spatial resolution, which is an advantage when looking at the snow cover. The MSI images are with different spatial resolution at the Earth surface range. The changes of the environmental objects are shown with the SAR images and different processing approaches. The results clearly show that snow and snow melting can be best registered by using SAR data via hh- horizontal polarization. The effect of the researcher on aerospace data and technology enables us to obtain different digital models, structuring and analyzing results excluding the subjective factor. Because of the large extent of terrestrial snow coverage and the difficulties in obtaining ground measurements over cold regions, remote sensing and GIS represent an important tool for studying snow areas and properties from regional to global scales.

Keywords: climate changes, GIS, remote sensing, SAR images, snow coverage

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Authors: Modesta E. Ezema, Christopher C. Ezema, Christian C. Ugwu, Udoka F. Eze, Florence M. Babalola

Abstract:

Some employees knowingly or unknowingly contribute to loss of data and also expose data to threat in the process of getting their jobs done. Many organizations today are faced with the challenges of how to secure their data as cyber criminals constantly devise new ways of attacking the organization’s secret data. However, this paper enlists the latest strategies that must be put in place in order to protect these important data from being attacked in a collaborative work place. It also introduces us to Advanced Persistent Threats (APTs) and how it works. The empirical study was conducted to collect data from the employee in data centers on how data could be protected from malicious codes and cyber criminals and their responses are highly considered to help checkmate the activities of malicious code and cyber criminals in our work places.

Keywords: data, employee, malware, work place

Procedia PDF Downloads 382

Authors: Martial Amou

Abstract:

This study was carried out to assess the situation of households’ livelihood under a changing climate pattern in the Zio district of Togo, West Africa. The study examined three important aspects: (i) assessment of households’ livelihood situation under a changing climate pattern, (ii) farmers’ perception and understanding of local climate change, (iii) determinants of adaptation strategies undertaken in cropping pattern to climate change. To this end, secondary sources of data, and survey data collected from 235 farmers in four villages in the study area were used. Adapted conceptual framework from Sustainable Livelihood Framework of DFID, two steps Binary Logistic Regression Model and descriptive statistics were used in this study as methodological approaches. Based on Sustainable Livelihood Approach (SLA), various factors revolving around the livelihoods of the rural community were grouped into social, natural, physical, human, and financial capital. Thus, the study came up that households’ livelihood situation represented by the overall livelihood index in the study area (34%) is below the standard average households’ livelihood security index (50%). The natural capital was found as the poorest asset (13%) and this will severely affect the sustainability of livelihood in the long run. The result from descriptive statistics and the first step regression (selection model) indicated that most of the farmers in the study area have clear understanding of climate change even though they do not have any idea about greenhouse gases as the main cause behind the issue. From the second step regression (output model) result, education, farming experience, access to credit, access to extension services, cropland size, membership of a social group, distance to the nearest input market, were found to be the significant determinants of adaptation measures undertaken in cropping pattern by farmers in the study area. Based on the result of this study, recommendations are made to farmers, policy makers, institutions, and development service providers in order to better target interventions which build, promote or facilitate the adoption of adaptation measures with potential to build resilience to climate change and then improve rural livelihood.

Keywords: climate change, rural livelihood, cropping pattern, adaptation, Zio District

Procedia PDF Downloads 325