Search results for: emerging data sources

Authors: Shu Yin, Zhiyang Ding, Jianzhong Huang, Xiaojun Ruan, Xiaomin Zhu, Xiao Qin

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Since large-scale and data-intensive applications have been widely deployed, there is a growing demand for high-performance storage systems to support data-intensive applications. Compared with traditional storage systems, next-generation systems will embrace dedicated processor to reduce computational load of host machines and will have hybrid combinations of different storage devices. The advent of flash- memory-based solid state disk has become a critical role in revolutionizing the storage world. However, instead of simply replacing the traditional magnetic hard disk with the solid state disk, it is believed that finding a complementary approach to corporate both of them is more challenging and attractive. This paper explores an idea of active storage, an emerging new storage configuration, in terms of the architecture and design, the parallel processing capability, the cooperation of other machines in cluster computing environment, and a disk configuration, the hybrid combination of different types of disk drives. Experimental results indicate that the proposed HcDD achieves better I/O performance and longer storage system lifespan.

Keywords: arallel storage system, hybrid storage system, data inten- sive, solid state disks, reliability

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Authors: Akshita Bhardwaj

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Keratinase is an enzyme obtained from extracellular sources that is involved in biodegradation of keratin. It is a member of a group of proteases that can break down keratin into amino acids. Keratinases are produced only in the presence of substrate that contain keratin. It attacked the disulfide bond of substrate and involve in keratin degradation. Human hair, feathers, animal hard tissues, horns, claws, and hooves all contain keratin.. It exists in two form alpha keratin (found in soft tissues) and beta keratin (found in hard tissue). By taking part in the degradation of keratin, keratinases derived from microbial sources, often referred to as microbial keratinases, are important in the process of turning wastes containing keratin into products with added value. Chicken feathers contain high level of keratin protein content than other sources and became a suitable protein source. Keratinase production occurs at near alkaline pH and thermophilic temperatures. The bioprocessing of keratinous waste benefits greatly from the use of keratinases. Additionally, it lessens the issue caused by poultry excrement. The use of feather meal, along with keratinase, improves the digestion of proteins and amino acids.

Keywords: mili litre (ml), micro litre (Ul), TCA - trichloroacetic acid, OD - optical density

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Authors: Kofi Kyei, Kenchi Matsui

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Loss of vegetable products has been a major constraint in the post-harvest chain. Sources of post-harvest loss in the vegetable industry start from the time of harvesting to its handling and at the various market centers. Identifying vegetable farmers’ perceptions about post-harvest loss sources is one way of addressing this issue. In this paper, we assessed farmers’ perceptions about sources of post-harvest losses in the Ashanti Region of Ghana. We also identified the factors that influence their perceptions. To clearly understand farmers’ perceptions, we selected Sekyere-Kumawu District in the Ashanti Region. Sekyere-Kumawu District is one of the major producers of vegetables in the Region. Based on a questionnaire survey, 100 vegetable farmers growing tomato, pepper, okra, cabbage, and garden egg were purposely selected from five communities in Sekyere-Kumawu District. For farmers’ perceptions, the five points Likert scale was employed. On a scale from 1 (no loss) to 5 (extremely high loss), we processed the scores for each vegetable harvest. To clarify factors influencing farmers’ perceptions, the Pearson Correlation analysis was used. Our findings revealed that farmers perceive post-harvest loss by pest infestation as the most extreme loss. However, vegetable farmers did not perceive loss during transportation as a serious source of post-harvest loss. The Pearson Correlation analysis results further revealed that farmers’ age, gender, level of education, and years of experience had an influence on their perceptions. This paper then discusses some recommendations to minimize the post-harvest loss in the region.

Keywords: Ashanti Region, pest infestation, post-harvest loss, vegetable farmers

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Authors: Ella Sèdé Maforikan

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Accurate land cover mapping is essential for effective environmental monitoring and natural resources management. This study focuses on assessing the classification performance of two satellite datasets and evaluating the impact of different input feature combinations on classification accuracy in the Beterou catchment, situated in the northern part of Benin. Landsat-8 and Sentinel-2 images from June 1, 2020, to March 31, 2021, were utilized. Employing the Random Forest (RF) algorithm on Google Earth Engine (GEE), a supervised classification categorized the land into five classes: forest, savannas, cropland, settlement, and water bodies. GEE was chosen due to its high-performance computing capabilities, mitigating computational burdens associated with traditional land cover classification methods. By eliminating the need for individual satellite image downloads and providing access to an extensive archive of remote sensing data, GEE facilitated efficient model training on remote sensing data. The study achieved commendable overall accuracy (OA), ranging from 84% to 85%, even without incorporating spectral indices and terrain metrics into the model. Notably, the inclusion of additional input sources, specifically terrain features like slope and elevation, enhanced classification accuracy. The highest accuracy was achieved with Sentinel-2 (OA = 91%, Kappa = 0.88), slightly surpassing Landsat-8 (OA = 90%, Kappa = 0.87). This underscores the significance of combining diverse input sources for optimal accuracy in land cover mapping. The methodology presented herein not only enables the creation of precise, expeditious land cover maps but also demonstrates the prowess of cloud computing through GEE for large-scale land cover mapping with remarkable accuracy. The study emphasizes the synergy of different input sources to achieve superior accuracy. As a future recommendation, the application of Light Detection and Ranging (LiDAR) technology is proposed to enhance vegetation type differentiation in the Beterou catchment. Additionally, a cross-comparison between Sentinel-2 and Landsat-8 for assessing long-term land cover changes is suggested.

Keywords: land cover mapping, Google Earth Engine, random forest, Beterou catchment

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Authors: Malith Premarathne, Shehan Bandara, Kaushalya G. Batawala, Thilini U. Ariyadasa

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The rapid depletion of fossil fuel supplies and the emission of carbon dioxide by their continued combustion have paved the way for increased production of carbon-neutral biodiesel from naturally occurring oil sources. The high biomass growth rate and lipid production of microalgae make it a viable source for biodiesel production compared to conventional feedstock. In Sri Lanka, the production of biodiesel by employing indigenous microalgae species is at its emerging stage. This work was an attempt to compare the various pre-treatment methods before extracting lipids such as autoclaving, microwaving and sonication. A mixed culture of microalgae predominantly consisting of Chlorella sp. was obtained from Beire Lake which is an algae rich, organically polluted water body located in Colombo, Sri Lanka. After each pre-treatment method, a standard solvent extraction using Bligh and Dyer’s method was used to compare the total lipid content in percentage dry weight (% dwt). The fatty acid profiles of the oils extracted with each pretreatment method were analyzed using gas chromatography-mass spectrometry (GC-MS). The properties of the biodiesels were predicted by Biodiesel Analyzer© Version 1.1, in order to compare with ASTM 6751-08 biodiesel standard.

Keywords: biodiesel, lipid extraction, microalgae, pre-treatment

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Authors: Rubisha Adhikari, Rajani Shah

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Introduction: Aging is a natural, global and inevitable phenomenon every single person has to go through, and nobody can escape the process. One of the emerging challenges to public health is to improve the quality of later years of life as life expectancy continues to increase. Quality of life (QoL) has grown to be a key goal for many public health initiatives. Population aging has become a global phenomenon as they are growing more quickly in emerging nations than they are in industrialized nations, leaving minimal opportunities to regulate the consequences of the demographic shift. Methods: A community-based descriptive analytical approach was used to examine the quality of life and associated factors among elderly people. A mixed method was chosen for the study. For the quantitative data collection, a household survey was conducted using the WHOQOL-OLD tool. In-depth interviews were conducted among twenty participants for qualitative data collection. Data generated through in-depth interviews were transcribed verbatim. In-depth interviews lasted about an hour and were audio recorded. The in-depth interview guide had been developed by the research team and pilot-tested before actual interviews. Results: This study result showed the association between quality of life and socio-demographic variables. Among all the variables under socio-demographic variable of this study, age (ꭓ2=14.445, p=0.001), gender (ꭓ2=14.323, p=<0.001), marital status (ꭓ2=10.816, p=0.001), education status (ꭓ2=23.948, p=<0.001), household income (ꭓ2=13.493, p=0.001), personal income (ꭓ2=14.129, p=0.001), source of personal income (ꭓ2=28.332,p=<0.001), social security allowance (ꭓ2=18.005,p=<0.001), alcohol consumption (ꭓ2=9.397,p=0.002) are significantly associated with quality of life of elderly. In addition, affordability (ꭓ2=12.088, p=0.001), physical activity (ꭓ2=9.314, p=0.002), emotional support (ꭓ2=9.122, p=0.003), and economic support (ꭓ2=8.104, p=0.004) are associated with quality of life of elderly people. Conclusion: In conclusion, this mixed method study provides insight into the attributes of the quality of life of elderly people in Nepal and similar settings. As the geriatric population is growing in full swing, maintaining a high quality of life has become a major challenge. This study showed that determinants such as age, gender, marital status, education status, household income, personal income, source of personal income, social security allowance and alcohol consumption, economic support, emotional support, affordability and physical activity have an association with quality of life of the elderly.

Keywords: ageing, chitwan, elderly, health status, quality of life

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Authors: Paiboon Jeamponk, Tasanee Ponglaa, Patchapon Srisanguan

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The aim of this research paper was based on an examination of sources of water supply and water quality for local consumption, conducted at eco-tourism villages of Suan Luang Sub- District Municipality of Amphawa District, Samut Songkram Province. The study incorporated both questionnaire and field work of water testing as the research tool and method. The sample size of 288 households was based on the population of the district, whereas the selected sample water sources were from 60 households: 30 samples were ground water and another 30 were surface water. Degree of heavy metal contamination in the water including copper, iron, manganese, zinc, cadmium and lead was investigated utilizing the Atomic Absorption- Direct Aspiration method. The findings unveiled that 96.0 percent of household water consumption was based on water supply, while the rest on canal, river and rain water. The household behaviour of consumption revealed that 47.2 percent of people routinely consumed water without boiling or filtering prior to consumption. The investigation of water supply quality found that the degree of heavy metal contamination including metal, lead, iron, copper, manganese and cadmium met the standards of the Department of Health.

Keywords: sources of water supply, water quality, water supply, Thailand

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Authors: Bassey Odiong Akan

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In recent decades potentially significant changes have taken place in the world of work and these have led to the emergence of new challenges in occupational safety and health. The working environment is now not only wroth with concerns about physical, biological and chemical risks but also emerging risks which are completely new risks that have never been seen before or previously known risks that are evolving in unexpected ways with unanticipated consequences. Psychosocial risk factors and its attendant hazards happen to be one of them and can impact health directly or indirectly, mediated by work-related stress. These risks are related to the way work is designed, organised and managed, as well as the economic and social contexts of work. It has become necessary to identify, explore and anticipate the dynamics of these risks factors and hazards with regards to how it affects women. This presentation is a review of information gathered from books of distinguished authors, research work and scientific/professional journals on the psychosocial work environment intended as a guide to stimulate discussion, raise awareness and encourage research and action at different levels.

Keywords: emerging risks, psychosocial hazards, psychosocial risk factors, work related stress

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Authors: Oluwole A. Solanke

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This article explores internal generation of revenues in higher education institutions. The research focuses on how polytechnic institutions in Nigeria generate other sources of revenues to augment government subventions and tuition fees. The study provides a qualitative case study and triangulation data on three polytechnics representing tertiary institution structure of federal, state and private ownership in Nigeria. The article argues that dependence on government subventions by the public polytechnics and tuition fees by private polytechnic would not provide funding adequacy for the activities of the institutions under study. Findings revealed that there are basically seven themes; guest houses; poly consult; part-time courses; tuition fees; capitation fees; ownership contribution; and printing and business centre by which the polytechnics generate additional sources of revenues in the management of the institutions. The research concludes that for the polytechnics to gain financial adequacy, entrepreneurial activities must be embarked upon vigorously by stakeholders of the polytechnics as this is the only way by which financial self-reliance can be achieved.

Keywords: entrepreneurial, government subventions, internal generation, polytechnics, revenues

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Authors: Feng Yang

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Machine learning (ML), especially deep learning (DL), has been extensively applied to many applications in recently years and gained great success in solving different problems, including scientific problems. However, conventional ML/DL methodologies are purely data-driven which have the limitations, such as need of ample amount of labelled training data, lack of consistency to physical principles, and lack of generalizability to new problems/domains. Recently, there is a growing consensus that ML models need to further take advantage of prior knowledge to deal with these limitations. Physics-informed machine learning, aiming at integration of physics/domain knowledge into ML, has been recognized as an emerging area of research, especially in the recent 2 to 3 years. In this work, physics-informed ML, specifically physics-informed neural network (NN), is employed and implemented to estimate the displacements at x, y, z directions in a solid mechanics problem that is controlled by equilibrium equations with boundary conditions. By incorporating the physics (i.e. the equilibrium equations) into the learning process of NN, it is showed that the NN can be trained very efficiently with a small set of labelled training data. Experiments with different settings of the NN model and the amount of labelled training data were conducted, and the results show that very high accuracy can be achieved in fulfilling the equilibrium equations as well as in predicting the displacements, e.g. in setting the overall displacement of 0.1, a root mean square error (RMSE) of 2.09 × 10−4 was achieved.

Keywords: deep learning, neural network, physics-informed machine learning, solid mechanics

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Authors: Sandeep Sharma, Sarabjit Singh

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As per the user demand and growth trends of large free data the storage solutions are now becoming more challenge-able to protect, store and to retrieve data. The days are not so far when the storage companies and organizations are start saying 'no' to store our valuable data or they will start charging a huge amount for its storage and protection. On the other hand as per the environmental conditions it becomes challenge-able to maintain and establish new data warehouses and data centers to protect global warming threats. A challenge of small data is over now, the challenges are big that how to manage the exponential growth of data. In this paper we have analyzed the growth trend of big data and its future implications. We have also focused on the impact of the unstructured data on various concerns and we have also suggested some possible remedies to streamline big data.

Keywords: big data, unstructured data, volume, variety, velocity

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Authors: Mohan Li

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Nowadays, intelligent research technology is more and more important than traditional research methods in urban research work, and this proportion will greatly increase in the next few decades. Frequently such analyzing work cannot be carried without some software engineering knowledge. And here, domain models of urban research will be necessary when applying software engineering knowledge to urban work. In many urban plan practice projects, making rational models, feeding reliable data, and providing enough computation all make indispensable assistance in producing good urban planning. During the whole work process, domain models can optimize workflow design. At present, human beings have entered the era of big data. The amount of digital data generated by cities every day will increase at an exponential rate, and new data forms are constantly emerging. How to select a suitable data set from the massive amount of data, manage and process it has become an ability that more and more planners and urban researchers need to possess. This paper summarizes and makes predictions of the emergence of technologies and technological iterations that may affect urban research in the future, discover urban problems, and implement targeted sustainable urban strategies. They are summarized into seven major domain models. They are urban and rural regional domain model, urban ecological domain model, urban industry domain model, development dynamic domain model, urban social and cultural domain model, urban traffic domain model, and urban space domain model. These seven domain models can be used to guide the construction of systematic urban research topics and help researchers organize a series of intelligent analytical tools, such as Python, R, GIS, etc. These seven models make full use of quantitative spatial analysis, machine learning, and other technologies to achieve higher efficiency and accuracy in urban research, assisting people in making reasonable decisions.

Keywords: big data, domain model, urban planning, urban quantitative analysis, machine learning, workflow design

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Authors: Hamid Yazdani, Raheleh Akbar

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Infrared thermography is a modern non-destructive measuring method for the examination of redeveloped and non-renovated buildings. Infrared cameras provide a means for temperature measurement in building constructions from the inside, as well as from the outside. Thus, heat bridges can be detected. It has been shown that infrared thermography is applicable for insulation inspection, identifying air leakage and heat losses sources, finding the exact position of heating tubes or for discovering the reasons why mold, moisture is growing in a particular area, and it is also used in conservation field to detect hidden characteristics, degradations of building structures. The paper gives a brief description of the theoretical background of infrared thermography.

Keywords: infrared thermography, examination of buildings, emissivity, heat losses sources

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Authors: Talip Turkmen

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From the moment the first beats, the first step into the world mankind finds him in a struggle to survive. Most important case to win this fight is power. Power is one of the most common concepts which we encounter in our life. Mainly power is ability to reach desired results on someone else or ability to penetrate into the behavior of others. Throughout history merging technology and changing political trade-offs caused the change of concept of power. Receiving a state of multipolar new world order in the 21st century and increasing impacts of media have narrowed the limits of military power. With increasing globalization and peaceful diplomacy this gap, left by military power, has filled by soft power which has ability to persuade and attract. As concepts of power soft power also has not compromised yet. For that reason it is important to specify, sources of soft power, soft power strategies and limits of soft power. The purpose of this study was to analyze concept of soft power and importance of soft power in foreign relations. This project focuses on power, hard power and soft power relations, sources of soft power and strategies to gain soft power. Datas in this project was acquired from other studies on soft power and foreign relations. This paper was prepared in terms of concept and research techniques. As a result of data gained in this study the one of important topics in international relations is balance between soft power.

Keywords: soft power, foreign policy, national power, hard power

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Authors: Maroua Sbiti, Karim Beddiar, Djaoued Beladjine, Romuald Perrault

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Productivity is decreasing in construction compared to the manufacturing industry. It seems that the sector is suffering from organizational problems and have low maturity regarding technological advances. High international competition due to the growing context of globalization, complex projects, and shorter deadlines increases these challenges. Field employees are more exposed to coordination problems than design officers. Execution collaboration is then a major issue that can threaten the cost, time, and quality completion of a project. Initially, this paper will try to identify field professional requirements as to address building management process weaknesses such as the unreliability of scheduling, the fickleness of monitoring and inspection processes, the inaccuracy of project’s indicators, inconsistency of building documents and the random logistic management. Subsequently, we will focus our attention on providing solutions to improve scheduling, inspection, and hours tracking processes using emerging lean tools and field mobility applications that bring new perspectives in terms of cooperation. They have shown a great ability to connect various field teams and make informations visual and accessible to planify accurately and eliminate at the source the potential defects. In addition to software as a service use, the adoption of the human resource module of the Enterprise Resource Planning system can allow a meticulous time accounting and thus make the faster decision making. The next step is to integrate external data sources received from or destined to design engineers, logisticians, and suppliers in a holistic system. Creating a monolithic system that consolidates planning, quality, procurement, and resources management modules should be our ultimate target to build the construction industry supply chain.

Keywords: lean, last planner system, field mobility applications, construction productivity

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Authors: Justin D. Olmanson, Fitsum Abebe, Valerie Jones, Eric Kyle, Xianquan Liu, Katherine Robbins, Guieswende Rouamba

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The history of education technology--and designing, adapting, and adopting technologies for use in educational spaces--is nuanced, complex, and dynamic. Yet, despite a range of continually emerging technologies, the design and development process often yields results that appear quite similar in terms of affordances and interactions. Through this study we (1) verify the extent to which designs have been constrained, (2) consider what might account for it, and (3) offer a way forward in terms of how we might identify and strategically sidestep these influences--thereby increasing the diversity of our designs with a given technology or within a particular learning domain. We begin our inquiry from the perspective that a host of co-influencing elements, fields, and meta narratives converge on the education technology design process to exert a tangible, often homogenizing effect on the resultant designs. We identify several elements that influence design in often implicit or unquestioned ways (e.g. curriculum, learning theory, economics, learning context, pedagogy), we describe our methodology for identifying the elemental positionality embedded in a design, we direct our analysis to a particular subset of technologies in the field of literacy, and unpack our findings. Our early analysis suggests that the majority of education technologies designed for use/used in US public schools are heavily influenced by a handful of mainstream theories and meta narratives. These findings have implications for how we approach the education technology design process--which we use to suggest alternative methods for designing/ developing with emerging technologies. Our analytical process and re conceptualized design process hold the potential to diversify the ways emerging and established technologies get incorporated into our designs.

Keywords: curriculum, design, innovation, meta narratives

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Authors: Miriam Itzkowitz, Katie Olson

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Through an interdisciplinary and trauma-responsive lens, this article reviews the legal and social history of mandated reporting laws and family separation, examines the ethical conundrum of mandated reporting as it relates to evidence-based practice, and discusses alternatives to mandated reporting as a primary prevention strategy. Using existing and emerging data, the authors argue that mandated reporting as a universal strategy contributes to racial disproportionality in the child welfare system and that anti-racist practices should begin with an examination of our reliance on mandated reporting.

Keywords: child welfare, education, mandated reporting, racial disproportionality, trauma

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Authors: Morteza Ghanbarpour, Rahmatollah Khodabandeh

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In this study, second law of thermodynamic is employed to evaluate heat pipe thermal performance. In fact, nanofluids potential to decrease the entropy generation of cylindrical heat pipes are studied and the results are compared with experimental data. Some cylindrical copper heat pipes of 200 mm length and 6.35 mm outer diameter were fabricated and tested with distilled water and water based Al2O3 nanofluids with volume concentrations of 1-5% as working fluids. Nanofluids are nanotechnology-based colloidal suspensions fabricated by suspending nanoparticles in a base liquid. These fluids have shown potential to enhance heat transfer properties of the base liquids used in heat transfer application. When the working fluid undergoes between different states in heat pipe cycle the entropy is generated. Different sources of irreversibility in heat pipe thermodynamic cycle are investigated and nanofluid effect on each of these sources is studied. Both experimental and theoretical studies reveal that nanofluid is a good choice to minimize the entropy generation in heat pipe thermodynamic cycle which results in higher thermal performance and efficiency of the system.

Keywords: heat pipe, nanofluid, thermodynamics, entropy generation, thermal resistance

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Authors: Omogboyega Abe

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This paper examines the relationships between socio-economic inequalities of power, race, wealth engendered by corporate structure, and domination in postcolonial Africa. The paper further considers how land as an epitome of property and power for the locals paved the way for capitalist accumulation and control in the hands of transnational corporations. European colonization of Africa was contingent on settler colonialism, where properties, including land, were re-modified as extractive resources for primitive accumulation. In developing Africa's extractive resources, transnational corporations (TNCs) usurped states' structures and domination over native land. The usurpation/corporate capture that exists to date has led to remonstrations and arguably a counter-productive approach to development projects. In some communities, the mention of extractive companies triggers resentment. The paradigm of state capture and state autonomy is simply inadequate to either describe or resolve the play of forces or actors responsible for severe corporate-induced human rights violations in emerging markets. Moreover, even if the deadly working conditions are conceived as some regulatory failure, it is tough to tell whose failure. The analysis in this paper is that the complexity and ambiguity evidenced by the multiple regimes and political and economic forces shaping production, consumption, and distribution of socio-economic variables are not exceptional in emerging markets. Instead, the varied experience in developing countries provides a window for seeing what we face in understanding and theorizing the structure and operation of the global economic and regulatory order in general.

Keywords: colonial, emerging markets, business, human rights, corporation

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Authors: Dawit Abay Tesfamariam

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Ethiopia’s Climate- Resilient Green Economy strategy focuses mainly on generating and utilization of Renewable Energy (RE). The data collected in 2016 by Ethiopian Electric Power (EEP) indicates that the intermittent RE sources on the grid from solar and wind energy were only 8 % of the total energy produced. On the other hand, the EEP electricity generation plan in 2030 indicates that 36 % of the energy generation share will be covered by solar and wind sources. Thus, a case study was initiated to model and compute the balance and consumption of electricity in three different scenarios: 2016, 2025, and 2030 using the Energy PLAN Model (EPM). Initially, the model was validated using the 2016 annual power-generated data to conduct the EPM analysis for two predictive scenarios. The EPM simulation analysis using EPM for 2016 showed that there was no significant excess power generated. Hence, the model’s results are in line with the actual 2016 output. Thus, the EPM was applied to analyze the role of energy storage in RE in Ethiopian grid systems. The results of the EPM simulation analysis showed there will be excess production of 402 /7963 MW average and maximum, respectively, in 2025. The excess power was dominant in all months except in the three rainy months of the year (June, July, and August). Consequently, based on the validated outcomes of EPM indicates, there is a good reason to think about other alternatives for the utilization of excess energy and storage of RE. Thus, from the scenarios and model results obtained, it is realistic to infer that; if the excess power is utilized with a storage mechanism that can stabilize the grid system; as a result, the extra RE generated can be exported to support the economy. Therefore, researchers must continue to upgrade the current and upcoming energy storage system to synchronize with RE potentials that can be generated from RE.

Keywords: renewable energy, storage, wind, energyplan

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Authors: Anuradha Chug, Sunali Gandhi

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Regression Testing is a very expensive and time-consuming process carried out to ensure the validity of modified software. Due to the availability of insufficient resources to re-execute all the test cases in time constrained environment, efforts are going on to generate test data automatically without human efforts. Many search based techniques have been proposed to generate efficient, effective as well as optimized test data, so that the overall cost of the software testing can be minimized. The generated test data should be able to uncover all potential lapses that exist in the software or product. Inspired from the natural behavior of bat for searching her food sources, current study employed a meta-heuristic, search-based bat algorithm for optimizing the test data on the basis certain parameters without compromising their effectiveness. Mathematical functions are also applied that can effectively filter out the redundant test data. As many as 50 Java programs are used to check the effectiveness of proposed test data generation and it has been found that 86% saving in testing efforts can be achieved using bat algorithm while covering 100% of the software code for testing. Bat algorithm was found to be more efficient in terms of simplicity and flexibility when the results were compared with another nature inspired algorithms such as Firefly Algorithm (FA), Hill Climbing Algorithm (HC) and Ant Colony Optimization (ACO). The output of this study would be useful to testers as they can achieve 100% path coverage for testing with minimum number of test cases.

Keywords: regression testing, test case selection, test case prioritization, genetic algorithm, bat algorithm

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Authors: Nidhi Prabha

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Transportation as a sector is one of the most significant infrastructural elements of the ‘urban.' The distinctness of an urban life in a city is marked by the dynamic movements that it enables within the city-space. Therefore it is important to study the public-transport systems that enable and foster mobility which characterizes the urban. It is also crucial to underscore the way one is examining the urban transport systems - either as an infrastructural unit in a strict physical-structural sense or as a structural unit which acts as a prism refracting multiple experiences depending on the location of the ‘commuter.' In the proposed paper, the attempt is to uncover and investigate the assumption of the neuter-commuter by looking at urban transportation in the secondary sense i.e. as a structural unit which is experienced differently by different kinds of commuters, thus making transportation deeply distributed with various social structures and locations like class or gender which map onto the transport systems. To this end, the public-transit systems operating in Urban Delhi i.e. the Delhi Metros and the Delhi Transport Corporation run public-buses are looked at as case studies. The study is premised on the knowledge and data gained from both primary and secondary sources. Primary sources include data and knowledge collected from fieldwork, the methodology for which has ranged from adopting ‘mixed-methods’ which is ‘Qualitative-then-Quantitative’ as well as borrowing ethnographic techniques. Apart from fieldwork, other primary sources looked at including Annual Reports and policy documents of the Delhi Metro Rail Corporation (DMRC) and the Delhi Transport Corporation (DTC), Union and Delhi budgets, Economic Survey of Delhi, press releases, etc. Secondary sources include the vast array of literature available on the critical nodes that inform the research like gender, transport geographies, urban-space, etc. The study indicates a deeply-distributed urban transport system wherein the various social-structural locations or different kinds of commuters map onto the way these different commuters experience mobility or movement within the city space. Mobility or movement, therefore, becomes gendered or has class-based ramifications. The neuter-commuter assumption is thus challenged. Such an understanding enables us to challenge the anonymity which the ‘urban’ otherwise claims it provides over the rural. The rural is opposed to the urban wherein urban ushers a modern way of life, breaking ties of traditional social identities. A careful study of the transport systems through the traveling patterns and choices of the commuters, however, indicate that this does not hold true as even the same ‘public-space’ of the transport systems allocates different places to different kinds of commuters. The central argument made though the research done is therefore that infrastructure like urban-transport-systems has to be studied and examined as seen beyond just a physical structure. The various experiences of daily mobility of different kinds of commuters have to be taken into account in order to design and plan more inclusive transport systems.

Keywords: gender, infrastructure, mobility, urban-transport-systems

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Authors: Nemat Sokhandan Bashir

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Threats from viruses to agricultural crops could be even larger than the losses caused by the other pathogens because, in many cases, the viral infection is latent but crucial from an epidemic point of view. Wild vegetation can be a source of many viruses that eventually find their destiny in crop plants. Although often asymptomatic in wild plants due to adaptation, they can potentially cause serious losses in crops. Therefore, exploring viruses in wild vegetation is very important. Recently, omics have been quite useful for exploring plant viruses from various plant sources, especially wild vegetation. For instance, we have discovered viruses such as Ambrossia asymptomatic virus I (AAV-1) through the application of metagenomics from Oklahoma Prairie Reserve. Accordingly, extracts from randomly-sampled plants are subjected to high speed and ultracentrifugation to separated virus-like particles (VLP), then nucleic acids in the form of DNA or RNA are extracted from such VLPs by treatment with phenol—chloroform and subsequent precipitation by ethanol. The nucleic acid preparations are separately treated with RNAse or DNAse in order to determine the genome component of VLPs. In the case of RNAs, the complementary cDNAs are synthesized before submitting to DNA sequencing. However, for VLPs with DNA contents, the procedure would be relatively straightforward without making cDNA. Because the length of the nucleic acid content of VPLs can be different, various strategies are employed to achieve sequencing. Techniques similar to so-called "chromosome walking" may be used to achieve sequences of long segments. When the nucleotide sequence data were obtained, they were subjected to BLAST analysis to determine the most related previously reported virus sequences. In one case, we determined that the novel virus was AAV-l because the sequence comparison and analysis revealed that the reads were the closest to the Indian citrus ringspot virus (ICRSV). AAV—l had an RNA genome with 7408 nucleotides in length and contained six open reading frames (ORFs). Based on phylogenies inferred from the replicase and coat protein ORFs of the virus, it was placed in the genus Mandarivirus.

Keywords: wild, plant, novel, metagenomics

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Authors: Veronica S. Moertini, Vinsensius Kevin, Gede Karya

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Customer reviews have been collected by many kinds of e-commerce websites selling products, services, hotel rooms, tickets and so on. Each website collects its own customer reviews. The reviews can be crawled, collected from those websites and stored as big data. Text analysis techniques can be used to analyze that data to produce summarized information, such as customer opinions. Then, these opinions can be published by independent service provider websites and used to help customers in choosing the most suitable products or services. As the opinions are analyzed from big data of reviews originated from many websites, it is expected that the results are more trusted and accurate. Indonesian customers write reviews in Indonesian language, which comes with its own structures and uniqueness. We found that most of the reviews are expressed with “daily language”, which is informal, do not follow the correct grammar, have many abbreviations and slangs or non-formal words. Hadoop is an emerging platform aimed for storing and analyzing big data in distributed systems. A Hadoop cluster consists of master and slave nodes/computers operated in a network. Hadoop comes with distributed file system (HDFS) and MapReduce framework for supporting parallel computation. However, MapReduce has weakness (i.e. inefficient) for iterative computations, specifically, the cost of reading/writing data (I/O cost) is high. Given this fact, we conclude that MapReduce function is best adapted for “one-pass” computation. In this research, we develop an efficient technique for extracting or mining opinions from big data of Indonesian reviews, which is based on MapReduce with one-pass computation. In designing the algorithm, we avoid iterative computation and instead adopt a “look up table” technique. The stages of the proposed technique are: (1) Crawling the data reviews from websites; (2) cleaning and finding root words from the raw reviews; (3) computing the frequency of the meaningful opinion words; (4) analyzing customers sentiments towards defined objects. The experiments for evaluating the performance of the technique were conducted on a Hadoop cluster with 14 slave nodes. The results show that the proposed technique (stage 2 to 4) discovers useful opinions, is capable of processing big data efficiently and scalable.

Keywords: big data analysis, Hadoop MapReduce, analyzing text data, mining Indonesian reviews

Procedia PDF Downloads 188

Authors: A. Alem, Y. Dahmani, A. Hadjali, A. Boualem

Abstract:

Managing the problem of the conflict, either by using the Dempster-Shafer theory, or by the application of the fusion process to push researchers in recent years to find ways to get to make best decisions especially; for information systems, vision, robotic and wireless sensor networks. In this paper we are interested to take account of the conflict in the combination step that took the conflict into account and tries to manage such a way that it does not influence the decision step, the conflict what from reliable sources. According to [1], the conflict lead to erroneous decisions in cases where was with strong degrees between sources of information, if the conflict is more than the maximum of the functions of belief mass K > max1...n (mi (A)), then the decision becomes impossible. We will demonstrate in this paper that the multiplication of mass functions by coefficients of reliability is a decreasing function; it leads to the reduction of conflict and a good decision. The definition of reliability coefficients accurately and multiply them by the mass functions of each information source to resolve the conflict and allow deciding whether the degree of conflict. The evaluation of this technique is done by a use case; a comparison of the combination of springs with a maximum conflict without, and with reliability coefficients.

Keywords: Dempster-Shafer theory, fusion process, conflict managing, reliability factors, decision

Procedia PDF Downloads 409

Authors: Mubashir Hussain, Mu Lv, Xiaohan Dong, Zhiyang Li, Bin Liu, Nongyue He

Abstract:

Detection and classification of microbes have a vast range of applications in biomedical engineering especially in detection, characterization, and quantification of bacterial contaminants. For identification of pathogens, different techniques are emerging in the field of biomedical engineering. Latest technology uses light scattering, capable of identifying different pathogens without any need for biochemical processing. Bacterial Pathogens Identification System (BPIS) which uses a laser beam, passes through the sample and light scatters off. An assembly of photodetectors surrounded by the sample at different angles to detect the scattering of light. The algorithm of the system consists of two parts: (a) Library files, and (b) Comparator. Library files contain data of known species of bacterial microbes in the form of binned plots, while comparator compares data of unknown sample with library files. Using collected data of unknown bacterial species, highest voltage values stored in the form of peaks and arranged in 3D histograms to find the frequency of occurrence. Resulting data compared with library files of known bacterial species. If sample data matching with any library file of known bacterial species, sample identified as a matched microbe. An experiment performed to identify three different bacteria particles: Enterococcus faecalis, Pseudomonas aeruginosa, and Escherichia coli. By applying algorithm using library files of given samples, results were compromising. This system is potentially applicable to several biomedical areas, especially those related to cell morphology.

Keywords: microbial identification, laser scattering, peak identification, binned plots classification

Procedia PDF Downloads 133

Authors: Benjamin Sonnenreich

Abstract:

Brittle fracture failure probability is best described using a stochastic approach which is based on the 'weakest link concept' and the connection between a microstructure and macroscopic fracture scale. A general theoretical and experimental framework is presented to predict the uniaxial strength distribution according to independent uniaxial test data. The framework takes as input the applied stresses, the geometry, the materials, the defect distributions and the relevant random variables from uniaxial test results and gives as output an overall failure probability that can be used to improve the reliability of practical designs. Additionally, the method facilitates comparisons of strength data from several sources, uniaxial tests, and sample geometries.

Keywords: brittle fracture, strength distribution, uniaxial, weakest link concept

Procedia PDF Downloads 308

Authors: Janusz Bobulski, Mariusz Kubanek

Abstract:

The main goal of the research is to develop a multimedia container structure containing three types of images: RGB, lidar and infrared, properly calibrated to each other. An additional goal is to develop program libraries for creating and saving this type of file and for restoring it. It will also be necessary to develop a method of data synchronization from lidar and RGB cameras as well as infrared. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. Autonomous cars are increasingly breaking into our consciousness. No one seems to have any doubts that self-driving cars are the future of motoring. Manufacturers promise that moving the first of them to showrooms is the prospect of the next few years. Many experts believe that creating a network of communicating autonomous cars will be able to completely eliminate accidents. However, to make this possible, it is necessary to develop effective methods of detection of objects around the moving vehicle. In bad weather conditions, this task is difficult on the basis of the RGB(red, green, blue) image. Therefore, in such situations, you should be supported by information from other sources, such as lidar or infrared cameras. The problem is the different data formats that individual types of devices return. In addition to these differences, there is a problem with the synchronization of these data and the formatting of this data. The goal of the project is to develop a file structure that could be containing a different type of data. This type of file is calling a multimedia container. A multimedia container is a container that contains many data streams, which allows you to store complete multimedia material in one file. Among the data streams located in such a container should be indicated streams of images, films, sounds, subtitles, as well as additional information, i.e., metadata. This type of file could be used in autonomous vehicles, which would certainly facilitate data processing by the intelligent autonomous vehicle management system. As shown by preliminary studies, the use of combining RGB and InfraRed images with Lidar data allows for easier data analysis. Thanks to this application, it will be possible to display the distance to the object in a color photo. Such information can be very useful for drivers and for systems in autonomous cars.

Keywords: an autonomous car, image processing, lidar, obstacle detection

Procedia PDF Downloads 207

Authors: Yang Bao, Shi Wei Deng, WangQun Lin

Abstract:

This paper introduces the concept and principle of data cleaning, analyzes the types and causes of dirty data, and proposes several key steps of typical cleaning process, puts forward a well scalability and versatility data cleaning framework, in view of data with attribute dependency relation, designs several of violation data discovery algorithms by formal formula, which can obtain inconsistent data to all target columns with condition attribute dependent no matter data is structured (SQL) or unstructured (NoSQL), and gives 6 data cleaning methods based on these algorithms.

Keywords: data cleaning, dependency rules, violation data discovery, data repair

Procedia PDF Downloads 546

Authors: Ercan Eker, Muhammer Karaman, Akif Aslan, Hakan Tanrikuluoglu

Abstract:

Deficiency of institutional memory and knowledge management can result in information security breaches, loss of prestige and trustworthiness and the worst the loss of know-how and institutional knowledge. Traditional learning management within organizations is generally handled by personal efforts. That kind of struggle mostly depends on personal desire, motivation and institutional belonging. Even if an organization has highly motivated employees at a certain time, the institutional knowledge and memory life cycle will generally remain limited to these employees’ spending time in this organization. Having a learning management system in an organization can sustain the institutional memory, knowledge and know-how in the organization. Learning management systems are much more needed especially in public organizations where the job rotation is frequently seen and managers are appointed periodically. However, a learning management system should not be seen as an organizations’ website. It is a more comprehensive, interactive and user-friendly knowledge management tool for organizations. In this study, the importance of using learning management systems in the process of emerging tacit knowledge is underlined.

Keywords: knowledge management, learning management systems, tacit knowledge, institutional memory

Procedia PDF Downloads 361