Search results for: data harvesting

Authors: Bolin Hua

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In city governance, various data are involved, including city component data, demographic data, housing data and all kinds of business data. These data reflects different aspects of people, events and activities. Data generated from various systems are different in form and data source are different because they may come from different sectors. In order to reflect one or several facets of an event or rule, data from multiple sources need fusion together. Data from different sources using different ways of collection raised several issues which need to be resolved. Problem of data fusion include data update and synchronization, data exchange and sharing, file parsing and entry, duplicate data and its comparison, resource catalogue construction. Governments adopt statistical analysis, time series analysis, extrapolation, monitoring analysis, value mining, scenario prediction in order to achieve pattern discovery, law verification, root cause analysis and public opinion monitoring. The result of Multi-source data fusion is to form a uniform central database, which includes people data, location data, object data, and institution data, business data and space data. We need to use meta data to be referred to and read when application needs to access, manipulate and display the data. A uniform meta data management ensures effectiveness and consistency of data in the process of data exchange, data modeling, data cleansing, data loading, data storing, data analysis, data search and data delivery.

Keywords: multi-source data fusion, urban comprehensive management, information fusion, government data

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Authors: Samira B. R. Prado, Paulo R. Melfi, Beatriz T. Minguzzi, João P. Fabi

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Fruit softening is the main change that occurs during papaya (Carica papaya L.) ripening. It is characterized by the depolymerization of cell wall polysaccharides, especially the pectic fractions, which causes cell wall disassembling. However, it is uncertain how the modification of the two main pectin polysaccharides fractions (water-soluble – WSF, and oxalate-soluble fractions - OSF) accounts for fruit softening. The aim of this work was to correlate molecular weight changes of WSF and OSF with the gene expression of pectin-solubilizing enzymes (pectinases) during papaya ripening. Papaya fruits obtained from a producer were harvest and storage under specific conditions. The fruits were divided in five groups according to days after harvesting. Cell walls from all groups of papaya pulp were isolated and fractionated (WSF and OSF). Expression profiles of pectinase genes were achieved according to the MIQE guidelines (Minimum Information for publication of Quantitative real-time PCR Experiments). The results showed an increased yield and a decreased molecular weight throughout ripening for WSF and OSF. Gene expression data support that papaya softening is achieved by polygalacturonases (PGs) up-regulation, in which their actions might have been facilitated by the constant action of pectinesterases (PMEs). Moreover, BGAL1 gene was up-regulated during ripening with a simultaneous galactose release, suggesting that galactosidases (GALs) could also account for pulp softening. The data suggest that a solubilization of galacturonans and a depolymerization of cell wall components were caused mainly by the action of PGs and GALs.

Keywords: carica papaya, fruit ripening, galactosidases, plant cell wall, polygalacturonases

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Authors: Mohammadali Abedini Sanigy, Jiangang Fei

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In this paper, a mathematical optimization model was developed to maximize the profit in a vegetable production planning problem. It serves as a decision support system that assists farmers in land allocation to crops and harvest scheduling decisions. The developed model can handle different rotation rules in two consecutive cycles of production, which is a common practice in organic production system. Moreover, different production methods of the same crop were considered in the model formulation. The main strength of the model is that it is not restricted to predetermined production periods, which makes the planning more flexible. The model is classified as a mixed integer programming (MIP) model and formulated in PYOMO -a Python package to formulate optimization models- and solved via Gurobi and CPLEX optimizer packages. The model was tested with secondary data from 'Australian vegetable growing farms', and the results were obtained and discussed with the computational test runs. The results show that the model can successfully provide reliable solutions for real size problems.

Keywords: crop rotation, harvesting, mathematical model formulation, vegetable production

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Authors: Sajjad Baghernezhad, Saeideh Baghernezhad

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Nowadays considering human involved in increasing data development some methods such as data mining to extract science are unavoidable. One of the discussions of data mining is inherent distribution of the data usually the bases creating or receiving such data belong to corporate or non-corporate persons and do not give their information freely to others. Yet there is no guarantee to enable someone to mine special data without entering in the owner’s privacy. Sending data and then gathering them by each vertical or horizontal software depends on the type of their preserving type and also executed to improve data privacy. In this study it was attempted to compare comprehensively preserving data methods; also general methods such as random data, coding and strong and weak points of each one are examined.

Keywords: data mining, distributed data mining, privacy protection, privacy preserving

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Authors: Morteza Aien, Masoud Rashidinejad, Mahmud Fotuhi-Firuzabad

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As energetic and environmental issues are getting more and more attention all around the world, the penetration of distributed energy resources (DERs) mainly those harvesting renewable energies (REs) ascends with an unprecedented rate. This matter causes more uncertainties to appear in the power system context; ergo, the uncertainty analysis of the system performance is an obligation. The uncertainties of any system can be represented probabilistically or possibilistically. Since sufficient historical data about all the system variables is not available, therefore, they do not have a probability density function (PDF) and must be represented possibilistiacally. When some of system uncertain variables are probabilistic and some are possibilistic, neither the conventional pure probabilistic nor pure possibilistic methods can be implemented. Hence, a combined solution is appealed. The first of this two-paper series formulates a new possibilistic-probabilistic tool for the load flow uncertainty assessment. The proposed methodology is based on the evidence theory and joint propagation of possibilistic and probabilistic uncertainties. This possibilistic- probabilistic formulation is solved in the second companion paper in an uncertain load flow (ULF) study problem.

Keywords: probabilistic uncertainty modeling, possibilistic uncertainty modeling, uncertain load flow, wind turbine generator

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Authors: Roman Bieda

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The General Data Protection Regulation (GDPR) will come into force on 25 May 2018 which will create a new legal framework for the protection of personal data in the European Union. Article 20 of GDPR introduces a right to data portability. This right allows for data subjects to receive the personal data which they have provided to a data controller, in a structured, commonly used and machine-readable format, and to transmit this data to another data controller. The right to data portability, by facilitating transferring personal data between IT environments (e.g.: applications), will also facilitate changing the provider of services (e.g. changing a bank or a cloud computing service provider). Therefore, it will contribute to the development of competition and the digital market. The aim of this paper is to discuss the right to data portability and its influence on the development of new digital services.

Keywords: data portability, digital market, GDPR, personal data

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Authors: Fahad Hanash Alzahrani

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This paper describes some recent advances in a quickly developing area of data storing and processing based on Data Warehouses and Data Mining techniques, which are associated with software, hardware, data mining algorithms and visualisation techniques having common features for any specific problems and tasks of their implementation.

Keywords: data warehouse, data mining, knowledge discovery in databases, on-line analytical processing

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Authors: Mehmet Akif Aslan, Mehmet Simsek, Eyup Sensoy

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Big Data stands for today’s cutting-edge technology. As the technology becomes widespread, so does Data. Utilizing massive data sets enable companies to get competitive advantages over their adversaries. Out of many area of Big Data usage, logistics has significance role in both commercial sector and military. This paper lays out what big data is and how it is used in both military and commercial logistics.

Keywords: big data, logistics, operational efficiency, risk management

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Authors: Carly Madge, Melanie Zurba, Ryan Bullock

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The Boreal Forest has experienced some of the most drastic climate change-induced temperature rises in Canada, with average winter temperatures increasing by 3°C since 1948. One of the main concerns of the province of Saskatchewan, and particularly wildfire managers, is the increased risk of wildfires due to climate change. With these concerns in mind Sakaw Askiy Management Inc., a forestry corporation located in Prince Albert, Saskatchewan with operations in the Boreal Forest biome, is developing wildfire risk reduction strategies that are supported by the shareholders of the corporation as well as the stakeholders of the Prince Albert Forest Management Area (which includes citizens, hunters, trappers, cottage owners, and outfitters). In the past, wildfire management strategies implemented through harvesting have been received with skepticism by some community members of Prince Albert. Engagement of the stakeholders of the Prince Albert Management Area through the development of the wildfire risk reduction strategies aims to reduce this skepticism and rebuild some of the trust that has been lost between industry and community. This research project works with the framework of social learning, which is defined as the learning that occurs when individuals come together to form a group with the purpose of understanding environmental challenges and determining appropriate responses to them. The project evaluates the social learning processes that occur through the development of the risk reduction strategies and how the learning has allowed Sakaw to work towards implementing the strategies into their forest harvesting plans. The incorporation of wildfire risk reduction strategies works to increase the adaptive capacity of Sakaw, which in this case refers to the ability to adjust to climate change, moderate potential damages, take advantage of opportunities, and cope with consequences. Using semi-structured interviews and wildfire workshop meetings shareholders and stakeholders shared their knowledge of wildfire, their main wildfire concerns, and changes they would like to see made in the Prince Albert Forest Management Area. Interviews and topics discussed in the workshops were inductively coded for themes related to learning, adaptive capacity, areas of concern, and preferred methods of wildfire risk reduction strategies. Analysis determined that some of the learning that has occurred has resulted through social interactions and the development of networks oriented towards wildfire and wildfire risk reduction strategies. Participants have learned new knowledge and skills regarding wildfire risk reduction. The formation of wildfire networks increases access to information on wildfire and the social capital (trust and strengthened relations) of wildfire personnel. Both factors can be attributed to increases in adaptive capacity. Interview results were shared with the General Manager of Sakaw, where the areas of concern and preferred strategies of wildfire risk reduction will be considered and accounted for in the implementation of new harvesting plans. This research also augments the growing conceptual and empirical evidence of the important role of learning and networks in regional wildfire risk management efforts.

Keywords: adaptive capacity, community-engagement, social learning, wildfire risk reduction

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Authors: Siyanda S. Biyela, Willie A. Cronje

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This paper presents a desktop study of comparing two different wave energy to electricity technologies (WECs) using a techno-economic approach. This techno-economic approach forms basis of a framework for rapid comparison of current and future technologies. The approach also seeks to assist in investment and strategic decision making expediting future deployment of wave energy harvesting in South Africa.

Keywords: cost of energy (COE) tool, sea state, wave energy converter (WEC), WEC-Sim

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Authors: Darius Phiri, Moses Chibesa, Donald Zulu, Robby Kasubika

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In Zambia, wildlife is co-managed by Zambia Wildlife Authority (ZAWA) and the local communities by sharing management responsibilities and benefits derived from harvesting wildlife resources under a benefit sharing mechanism. Although the benefit sharing mechanism has been formulated under good principles, it is still facing numerous challenges. In response to these challenges, a study on the sustainability of ZAWA benefit sharing mechanism was carried out in order to assess its potential and continuity in line with community empowerment and wildlife resources management. Systematic sampling was used with a sampling intensity of 4% to administer three types of questionnaires to community members in Mumbwa Game Management Area (GMA), ZAWA officers, and to the Ministry of Tourism, Environment and Natural Resources (MTENR) staffs. The collected data was then analysed using SPSS version 16.5. The findings indicated that many people in the GMA do not participate fully because of lacking satisfactory benefits. However, the mechanism contribute to the community well-being and can still remain sustainable especially if measures to address the current challenges are put in place.

Keywords: benefit sharing, concessions, licenses, poaching, local communities, sustainability

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Authors: Jihyun Song, Kyeongjoo Kim, Minsoo Lee

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Due to the development of information technology and wireless Internet technology, various data are being generated in various fields. These data are advantageous in that they provide real-time information to the users themselves. However, when the data are accumulated and analyzed, more various information can be extracted. In addition, development and dissemination of boards such as Arduino and Raspberry Pie have made it possible to easily test various sensors, and it is possible to collect sensor data directly by using database application tools such as MySQL. These directly collected data can be used for various research and can be useful as data for data mining. However, there are many difficulties in using the board to collect data, and there are many difficulties in using it when the user is not a computer programmer, or when using it for the first time. Even if data are collected, lack of expert knowledge or experience may cause difficulties in data analysis and visualization. In this paper, we aim to construct a library for sensor data collection and analysis to overcome these problems.

Keywords: clustering, data mining, DBSCAN, k-means, k-medoids, sensor data

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Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

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Organizations, including governments, generate (big) data that are high in volume, velocity, veracity, and come from a variety of sources. Public Administrations are using (big) data, implementing base registries, and enforcing data sharing within the entire government to deliver (big) data related integrated services, provision of insights to users, and for good governance. Government (Big) data ecosystem actors represent distinct entities that provide data, consume data, manipulate data to offer paid services, and extend data services like data storage, hosting services to other actors. In this research work, we perform a systematic literature review. The key objectives of this paper are to propose a robust definition of government (big) data ecosystem and a classification of government (big) data ecosystem actors and their roles. We showcase a graphical view of actors, roles, and their relationship in the government (big) data ecosystem. We also discuss our research findings. We did not find too much published research articles about the government (big) data ecosystem, including its definition and classification of actors and their roles. Therefore, we lent ideas for the government (big) data ecosystem from numerous areas that include scientific research data, humanitarian data, open government data, industry data, in the literature.

Keywords: big data, big data ecosystem, classification of big data actors, big data actors roles, definition of government (big) data ecosystem, data-driven government, eGovernment, gaps in data ecosystems, government (big) data, public administration, systematic literature review

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Authors: D. Serero, L. Couton, J. D. Parisse, R. Leroy

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In urban planning, an increasing number of cities require wind analysis to verify comfort of public spaces and around buildings. These studies are made using computer fluid dynamic simulation (CFD). However, this technique is often based on wind information taken from meteorological stations located at several kilometers of the spot of analysis. The approximated input data on project surroundings produces unprecise results for this type of analysis. They can only be used to get general behavior of wind in a zone but not to evaluate precise wind speed. This paper presents another approach to this problem, based on collecting wind data and generating an urban wind cartography using connected ultrasound anemometers. They are wireless devices that send immediate data on wind to a remote server. Assembled in array, these devices generate geo-localized data on wind such as speed, temperature, pressure and allow us to compare wind behavior on a specific site or building. These Netatmo-type anemometers communicate by wifi with central equipment, which shares data acquired by a wide variety of devices such as wind speed, indoor and outdoor temperature, rainfall, and sunshine. Beside its precision, this method extracts geo-localized data on any type of site that can be feedback looped in the architectural design of a building or a public place. Furthermore, this method allows a precise calibration of a virtual wind tunnel using numerical aeraulic simulations (like STAR CCM + software) and then to develop the complete volumetric model of wind behavior over a roof area or an entire city block. The paper showcases connected ultrasonic anemometers, which were implanted for an 18 months survey on four study sites in the Grand Paris region. This case study focuses on Paris as an urban environment with multiple historical layers whose diversity of typology and buildings allows considering different ways of capturing wind energy. The objective of this approach is to categorize the different types of wind in urban areas. This, particularly the identification of the minimum and maximum wind spectrum, helps define the choice and performance of wind energy capturing devices that could be implanted there. The localization on the roof of a building, the type of wind, the altimetry of the device in relation to the levels of the roofs, the potential nuisances generated. The method allows identifying the characteristics of wind turbines in order to maximize their performance in an urban site with turbulent wind.

Keywords: computer fluid dynamic simulation in urban environment, wind energy harvesting devices, net-zero energy building, urban wind behavior simulation, advanced building skin design methodology

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Authors: J. Naalamle Amissah, Dorcas Osei‐Safo, C. M. Asare, Benjamin Missah‐Assihene, Eric. Y. Danquah, Ivan Addae‐Mensah

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Medicinal plants serve as a reservoir of active ingredients for the treatment of common ailments such as cancer, malaria and diabetes. With the recent wave of health consciousness and reliance on plant based medicines, the demand for medicinal plants has increased considerably. This surge in medicinal plant use has raised great concern amongst key players (herbalist, collectors, conservationist and researchers) along the value chain about the sustainability of the raw material. The over reliance on wild crafting as a means to obtain the raw material spells doom for several of Africa’s native medicinal plant species. In this study domestication protocols for the cultivation of Cryptolepis sanguinolenta (CS), a medicinal plant used in the treatment of malaria were developed. Initial surveys were conducted, using questionnaires comprising of open and close ended questions, to gather information that would inform the domestication and cultivation of the species. A field study was then conducted to determine the plant’s cropping cycle and the effect of staking and plant age on the active ingredient (cryptolepine) concentration in its roots. Results of the survey confirmed the demand for the raw material and threw more light on the harvesting methods and intensity of CS collection from the wild. Cryptolepine concentration was found to be highest (~1.84 mg/100 mg of root material) at 289 days after planting (DAP) which coincided with the peak of root dry weight (52.8 g), signifying the best time for root harvest. Staking was found to be important for seed production. The first 105 DAP were characterized by low yields of root dry weight (13.5 g), followed by a period of rapid growth in which the root dry weight increased almost linearly until 289 DAP. Although dry matter partitioned to the vines increased towards the end of the experimental period (60%), dry matter partitioned to the roots remained fairly constant (30%) throughout the experimental period. Cryptolepine was found to increase as the plant aged and the practice of staking CS promoted pod formation. A suitable cropping cycle for the cultivation of CS was also developed.

Keywords: domestication, staking, conservation, wild harvesting

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Authors: Thanunthon Bowornsakulwong, Charukorn Charukarn, Franck Courtes, Panit Kitsubun, Lalintip Horcharoen

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Vero cell is a continuous cell line that is widely used for the production of viral vaccines. However, due to its adherent characteristic, scaling up strategy in large-scale production remains complicated and thus limited. Consequently, suspension-like Vero cell culture processes based on microcarriers have been introduced and employed while also providing increased surface area per volume unit. However, harvesting Vero cells from microcarriers is a huge challenge due to difficulties in cells detaching, lower recovery yield, time-consuming and dissociation agent carry-over. To overcome these problems, we developed a dissociation-association platform technology for detaching and re-attaching cells during subculturing from microcarriers to microcarriers, which will be conveniently applied to seed trains strategies in large scale bioreactors. Herein, Hillex-2 was used to culture Vero cells in serum-containing media using spinner flasks as a scale-down model. The overall confluency of cells on microcarriers was observed using inverted microscope, and the sample cells were daily detached in order to obtain the kinetics data. The metabolites consumption and by-products formation were determined by Nova Biomedical BioprofileFlex.

Keywords: dissociation-reassociation, microcarrier, scale up, Vero cell

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Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

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Data that is high in volume, velocity, veracity and comes from a variety of sources is usually generated in all sectors including the government sector. Globally public administrations are pursuing (big) data as new technology and trying to adopt a data-centric architecture for hosting and sharing data. Properly executed, big data and data analytics in the government (big) data ecosystem can be led to data-driven government and have a direct impact on the way policymakers work and citizens interact with governments. In this research paper, we conduct a systematic literature review. The main aims of this paper are to highlight essential aspects of the government (big) data ecosystem and to explore the most critical socio-technical factors that contribute to the successful implementation of government (big) data ecosystem. The essential aspects of government (big) data ecosystem include definition, data types, data lifecycle models, and actors and their roles. We also discuss the potential impact of (big) data in public administration and gaps in the government data ecosystems literature. As this is a new topic, we did not find specific articles on government (big) data ecosystem and therefore focused our research on various relevant areas like humanitarian data, open government data, scientific research data, industry data, etc.

Keywords: applications of big data, big data, big data types. big data ecosystem, critical success factors, data-driven government, egovernment, gaps in data ecosystems, government (big) data, literature review, public administration, systematic review

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Authors: Anli Du Preez, James Bekker

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Data is currently one of the most critical and influential emerging technologies. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data are ever actually analyzed for value creation. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen’s framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application.

Keywords: Data analytics, Industrial engineering, Machine learning, Value creation

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Authors: Azhan Azhar, Mohammed Sakib, Zaurez Ahmad

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The energy we receive from the sun is known as solar energy, and it is a reliable, long-lasting, eco-friendly and the most widely used energy source in the 21st century. It is. There are several techniques for harnessing solar energy, and we are all seeing large utility-scale projects to collect maximum amperes from the sun using current technologies. Solar PV is now on the rise as a means of harvesting energy from the sun. Moving a step further, our project is focused on designing an All-in-one portable Solar Energy based solution. We considered the minimum load conditions and evaluated the requirements of various devices utilized in this study to resolve the power requirements of small stores, hawkers, or travelers.

Keywords: DOD-depth of discharge, pulse width modulation charge controller, renewable energy, solar PV- solar photovoltaic

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Authors: Annapureddy Srikant Reddy, Atthanti Mahendra, Samala Chinni Krishna, N. Neelima

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In our present world, we are generating a lot of data and we, need a specific device to store all these data. Generally, we store data in pen drives, hard drives, etc. Sometimes we may loss the data due to the corruption of devices. To overcome all these issues, we implemented a cloud space for storing the data, and it provides more security to the data. We can access the data with just using the internet from anywhere in the world. We implemented all these with the java using Net beans IDE. Once user uploads the data, he does not have any rights to change the data. Users uploaded files are stored in the cloud with the file name as system time and the directory will be created with some random words. Cloud accepts the data only if the size of the file is less than 2MB.

Keywords: cloud space, AES, FTP, NetBeans IDE

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Authors: Vano Tsertsvadze, Marina Chavchanidze, Lali Khurtsia

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Problem of drug use is often seen as a combination of psychological and social problems, but this problem can be considered as economically rational decision in the process of buying pleasure (looking after children, reading, harvesting fruits in the fall, sex, eating, etc.). Before the adoption of the decisions people face to a trade-off - when someone chooses a delicious meal, she takes a completely rational decision, that the pleasure of eating has a lot more value than the pleasure which she will experience after two months diet on the summer beach showing off her beautiful body. This argument is also true for alcohol, drugs and cigarettes. Smoking has a negative effect on health, but smokers are not afraid of the threat of a lung cancer after 40 years, more valuable moment is a pleasure from smoking. Our hypothesis - unsatisfied pleasure and frustration, probably determines the risk of dependence on drug abuse. The purpose of research: 1- to determine the relative measure unit of pleasure, which will be used to measure and assess the intensity of various human pleasures. 2- to compare the intensity of the pleasure from different kinds of activity, with pleasures received from drug use. 3- Based on the analysis of data, to identify factors affecting the rational decision making. Research method: Respondents will be asked to recall the greatest pleasure of their life, which will be used as a measure of the other pleasures. The study will use focus groups and structured interviews.

Keywords: drug, drug-user, measurement, satisfaction

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Authors: Chayma Bahar, Chokri Baccouch, Hedi Sakli, Nizar Sakli

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Harvesting and transport of optical and radiofrequency signals are a topical subject with multiple challenges. In this paper, we present a Optical RECTENNA system. We propose here a hybrid system solar cell antenna for 5G mobile communications networks. Thus, we propose rectifying circuit. A parametric study is done to follow the influence of load resistance and input power on Optical RECTENNA system performance. Thus, we propose a solar cell antenna structure in the frequency band of future 5G standard in 2.45 GHz bands.

Keywords: antenna, IoT, optical rectenna, solar cell

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Authors: Siran Offman, Hermes Pacule, Teofilo Nhamuhuco

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Marine invertebrates are very important for the livelihood of coastal communities, particularly in Pemba City. The study was conducted From June 2011 to March 2012. The aim of this study is to determine the socioeconomic impact of collecting marine invertebrates in communities and Chuiba Maringanha. Data were collected biweekly during the spring tide ebb in the intertidal zone, and through structured surveys, the confrontation of data was done through direct observation in the neighborhoods. In total 40 collectors was surveyed and it was found that activity of collecting marine invertebrates is practiced by women 57.2% and men 42.5%. Their ages ranged from 9 to 45 years, and the range was 25-32 dominant with 30.5% and collection practice 5-7 times per week they spend about 4-6 hours a day. The collection methods are direct harvesting by hand aided by knives, sharp irons, and transport use pots, buckets, basins, shawls. Were identified in total 8 marketable species namely: Octopus vulgaris 8.6 Kg, Cyprea Tigers 7 units, Cypraea annulus 48 kg, 40 kg holuturias, Cyprea bully, Atrina vexilium 10 kg, Modiulus philiphinarum and lambis lambis. The species with the greatest economic value are sea cucumber (3 Usd/ kg) and Octopus vulgaris ( 2.5 Usd/ kg) more commercialized. The socio-economic impacts on communities of collectors the average income of collectors varies from 0.5 to 5 Usd/ day and the money are intended to purchase food and agricultural instruments. The other socioeconomics impacts are illiteracy with 36% dropout, and 28% have never studied 87% of unemployed collectors, a high number of family members, weak economic power, poor housing made the basis of local materials and relies on community wells to access water, and most do not have electric power.

Keywords: socio-economic, impacts, collecting marine invertebrates, communities

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Authors: Medha Iyer, Anshul Paul, Aunnesha Bhowmick, Anahita Banerjee, Sana Prasad, Anoushka Singal, Lauren Sinopoli, Pooja Bapat, Shivi Jain

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In Himachal Pradesh, India, a majority of the population lives in rural villages spread throughout its hilly regions; many of these households rely on subsistence farming as their main source of livelihood. The student-run non-profit organization affiliated with this study, Project RISHI (Rural India Social and Health Improvement), works to promote sustainable development practices in Bharog Baneri, a gram panchayat, or union, of villages in Himachal Pradesh. In 2017, an established rainwater harvesting (RWH) project group within Project RISHI had surveyed many families, finding that the most common issue regarding food and water access was a lack of accessible water sources for agricultural use in the dry season. After a prototype build in 2018, the group built 6 systems for eligible residents that demonstrated need in 2019. Subsequently, the project went through an evaluation period, including self-evaluation of project goals and post-impact surveying of system recipients. The group used the social impact assessment model to optimize the implementation of domestic RWH systems in Bharog Baneri. Assessing implementation after in-person builds produced three pillars of focus — system design, equitable recipient selection, and community involvement. After two years of remote involvement during COVID-19, the group prepared to visit Bharog Baneri to build 10 new systems in the Summer 2022. First, the group created a more durable and cost-effective design that could withstand debris and heavy rains to prevent gutter failure. The domestic system design is a rooftop RWH catchment system with two tanks attached, an overflow pipe, debris filtration, and a spigot for accessibility. The group also developed a needs-based eligibility methodology with assistance from village leaders and surveying in Bharog Baneri and set up the groundwork for a future community board. COVID-19 has strengthened remote work, telecommunications, and other organizational support systems. As sustainable development evolves to encompass these practices in a post-pandemic world, the potential for new RWH system design and implementation processes has emerged as well. This raises the question: how can a social impact assessment of rural RWH projects inform an integrated approach to post-pandemic RWH system practices? The objective of this exploratory study is to investigate and evaluate a novel remote build infrastructure that brings access to reliable and sustainable sources of water for agricultural use. To construct the remote build approach, the group identified and assigned a point of contact who was experienced with previous RWH system builds. The recipients were selected based on demonstrated need and ease of building. The contact visited each of the houses and coordinated supplier relations and transportation of the materials in accordance with the participatory approach to sustainable development. Over the course of two months, the group completed four system builds with the resulting infrastructure. The infrastructure adhered to the social impact assessment model by centering supplier relations, material transportation, and construction logistics within the community. The conclusion of this exploration is that post-pandemic rural RWH practices should be rooted in strengthening villager communication and utilizing local assets. Through this, non-profit organizations can incorporate remote build strategies into their long-term goals.

Keywords: capturing run-off from rooftops, domestic rainwater harvesting, Implementation approaches and strategies, rainwater harvesting and management in rural sectors

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Authors: Rokhmatul Insani, Hira Laksmiwati Soemitro

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Business Intelligence is a methodology that exploits the data to produce information and knowledge systematically, business intelligence can support the decision-making process. Some methods in business intelligence are data warehouse and data mining. A data warehouse can store historical data from transactional data. For data modelling in data warehouse, we apply dimensional modelling by Kimball. While data mining is used to extracting patterns from the data and get insight from the data. Data mining has many techniques, one of which is segmentation. For profiling of telecommunication customer, we use customer segmentation according to customer’s usage of services, customer invoice and customer payment. Customers can be grouped according to their characteristics and can be identified the profitable customers. We apply K-Means Clustering Algorithm for segmentation. The input variable for that algorithm we use RFM (Recency, Frequency and Monetary) model. All process in data mining, we use tools IBM SPSS modeller.

Keywords: business intelligence, customer segmentation, data warehouse, data mining

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Authors: Messay Mulugeta, Degefa Tolossa

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The purpose of this paper is to scrutinize trends of climate risks in eastern and southeastern parts of Ethiopia. This part of the country appears severely affected by recurrent droughts, erratic rainfall, and increasing temperature condition. Particularly, erratic rains and moisture stresses have been forcibly threatening and shoving the people over many decades coupled with unproductive policy frameworks and weak institutional setups. These menaces have been more severe in dry lowlands where rainfall is more erratic and scarce. Long-term climate data of nine weather stations in eastern and southeastern parts of Ethiopia were obtained from National Meteorological Agency of Ethiopia (NMA). As issues related to climate risks are very intricate, different techniques and indices were applied to deal with the objectives of the study. It is concluded that erratic rainfall, moisture scarcity, and increasing temperature conditions have been the main challenges in eastern and southeastern Ethiopia. In fact, these risks can be eased by putting in place efficient and integrated rural development strategies, environmental rehabilitation plans of action in overworked areas, proper irrigation and water harvesting practices and well thought-out and genuine resettlement schemes.

Keywords: rainfall variability, erratic rains, precipitation concentration index (PCI), climatic pattern, Ethiopia

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Authors: Younies Saeed Hassan Mahmoud, Mai Mabrouk, Elsayed Sallam

Abstract:

Analysing DNA microarray data sets is a great challenge, which faces the bioinformaticians due to the complication of using statistical and machine learning techniques. The challenge will be doubled if the microarray data sets contain missing data, which happens regularly because these techniques cannot deal with missing data. One of the most important data analysis process on the microarray data set is feature selection. This process finds the most important genes that affect certain disease. In this paper, we introduce a technique for imputing the missing data in microarray data sets while performing feature selection.

Keywords: DNA microarray, feature selection, missing data, bioinformatics

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Authors: Lutful Karim, Mohammed S. Al-kahtani

Abstract:

Sensors are being used in various applications such as agriculture, health monitoring, air and water pollution monitoring, traffic monitoring and control and hence, play the vital role in the growth of big data. However, sensors collect redundant data. Thus, aggregating and filtering sensors data are significantly important to design an efficient big data framework. Current researches do not focus on aggregating and filtering data at multiple layers of sensor-based big data framework. Thus, this paper introduces (i) three layers data aggregation and framework for big data and (ii) a priority-based, dynamic data aggregation scheme (PDDA) for the lowest layer at sensors. Simulation results show that the PDDA outperforms existing tree and cluster-based data aggregation scheme in terms of overall network energy consumptions and end-to-end data transmission delay.

Keywords: big data, clustering, tree topology, data aggregation, sensor networks

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Authors: Kritiyaporn Kunsook

Abstract:

Machine learning algorithms (MLAs) such us artificial neural networks (ANNs), decision tree, support vector machines (SVMs), Naïve Bayes, and ensemble classifier by voting are powerful data driven methods that are relatively less widely used in the mapping of technique of system, and thus have not been comparatively evaluated together thoroughly in this field. The performances of a series of MLAs, ANNs, decision tree, SVMs, Naïve Bayes, and ensemble classifier by voting in technique of hydroponic systems prospectively modeling are compared based on the accuracy of each model. Classification of hydroponic systems only covers the test samples from vegetables grown with Nutrient film technique (NFT) and Deep flow technique (DFT). The feature, which are the characteristics of vegetables compose harvesting height width, temperature, require light and color. The results indicate that the classification performance of the ANNs is 98%, decision tree is 98%, SVMs is 97.33%, Naïve Bayes is 96.67%, and ensemble classifier by voting is 98.96% algorithm respectively.

Keywords: artificial neural networks, decision tree, support vector machines, naïve Bayes, ensemble classifier by voting

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Authors: Antonella Di Sotto, Cinzia Ingallina, Caterina Fraschetti, Simone Circi, Marcello Locatelli, Simone Carradori, Gabriela Mazzanti, Luisa Mannina, Silvia Di Giacomo

Abstract:

Cannabis sativa L. is one of the oldest cultivated plant species known not only for its voluptuous use but also for the wide application in food, textile, and therapeutic industries. Recently, the progress of biotechnologies applied to medicinal plants has allowed to produce different hemp varieties with low content of psychotropic phytoconstituents (tetrahydrocannabinol < 0.2% w/v), thus leading to a renewed industrial and therapeutic interest for this plant. In this context, in order to discover new potential remedies of pharmaceutical and/or nutraceutical interest, the chemopreventive properties of different organic and hydroalcoholic extracts, obtained from the inflorescences of C. sativa L. var. USO31, collected in June and September harvesting, were assessed. Particularly, the antimutagenic activity towards the oxidative DNA-damage induced by tert-butyl hydroperoxide (t-BOOH) was evaluated, and the DPPH (2,2-diphenyl-1-picrylhydrazyl) and ABTS (2,2'-azino-bis-3-ethylbenzthiazoline-6-sulphonic acid) radical scavenging power of the samples were assessed as possible mechanisms of antimutagenicity. Furthermore, the ability of the extracts to inhibit the glucose-6-phosphate dehydrogenase (G6PD), whose overexpression has been found to play a critical role in neoplastic transformation and tumor progression, has been studied as a possible chemopreventive strategy. A careful phytochemical characterization of the extracts for phenolic and terpenoid composition has been obtained by high performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS) methods. Under our experimental condition, all the extracts were found able to interfere with the tBOOH-induced mutagenicity in WP2uvrAR strain, although with different potency and effectiveness. The organic extracts from both the harvesting periods were found to be the main effective antimutagenic samples, reaching about a 55% inhibition of the tBOOH-mutagenicity at the highest concentration tested (250 μg/ml). All the extracts exhibited radical scavenger activity against DPPH and ABTS radicals, with a higher potency of the hydroalcoholic samples. The organic extracts were also able to inhibit the G6PD enzyme, being the samples from September harvesting the highly potent (about 50% inhibition respect to the vehicle). At the phytochemical analysis, all the extracts resulted to contain both polar and apolar phenolic compounds. The HPLC analysis revealed the presence of catechin and rutin as the major constituents of the hydroalcoholic extracts, with lower levels of quercetin and ferulic acid. The monoterpene carvacrol was found to be an ubiquitarian constituent. At GC-MS analysis, different terpenoids, among which caryophyllene sesquiterpenes, were identified. This evidence suggests a possible role of both polyphenols and terpenoids in the chemopreventive properties of the extracts from the inflorescences of C. sativa var. USO31. According to the literature, carvacrol and caryophyllene sesquiterpenes can contribute to the strong antimutagenicity although the role of all the hemp phytocomplex cannot be excluded. In conclusion, present results highlight a possible interest for the inflorescences of C. sativa var. USO31 as source of bioactive molecules and stimulate further studies in order to characterize its possible application for nutraceutical and pharmaceutical purposes.

Keywords: antimutagenicity, glucose-6-phosphate dehydrogenase, hemp inflorescences, nutraceuticals, sesquiterpenes

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