Search results for: secure data aggregation

Authors: Renata Konadu

Abstract:

In Ghana, electricity has become the main form of energy which all sectors of the economy rely on for their businesses. Therefore, as the economy grows, the demand and consumption of electricity also grow alongside due to the heavy dependence on it. However, since the supply of electricity has not increased to match the demand, there has been frequent power outages and load shedding affecting business performances. To solve this problem and advance policies to secure electricity in Ghana, it is imperative that those factors that cause consumption to increase be analysed by considering the three classes of consumers; residential, industrial and non-residential. The main argument, however, is that, export of electricity to other neighbouring countries should be included in the electricity consumption model and considered as one of the significant factors which can decrease or increase consumption. The author made use of multivariate time series data from 1980-2010 and econometric models such as Ordinary Least Squares (OLS) and Vector Error Correction Model. Findings show that GDP growth, urban population growth, electricity exports and industry value added to GDP were cointegrated. The results also showed that there is unidirectional causality from electricity export and GDP growth and Industry value added to GDP to electricity consumption in the long run. However, in the short run, there was found to be a directional causality among all the variables and electricity consumption. The results have useful implication for energy policy makers especially with regards to electricity consumption, demand, and supply.

Keywords: electricity consumption, energy policy, GDP growth, vector error correction model

Procedia PDF Downloads 437

Authors: Neelum Maqsood

Abstract:

This paper is a study of how institutional structures shape the policy-making activities of female legislators. The literature on this area indicates that if there is an institution created by men to secure elite interests, women will face constraints in legislative activities. This paper will analyze the institutional setting in Pakistan and document the conditions women face that both restrict or enable them from representing the general interests of other women. The main experimental design depends on the variation of international scrutiny that Pakistan faces in two different time periods that will be classified as high international scrutiny and low international scrutiny. A high international scrutiny period is one where Pakistan comes under the international lens because of a domestic event that has international ramifications, for example, in terms of gender equality. The argument is that women parliamentarians receive different treatment in periods of high international scrutiny. As Pakistan comes under scrutiny, women will be more active in their legislative activities than in low international scrutiny, as male parliamentarians will be less likely to influence or restrain women’s activities. Using this variation, the trends in memberships and support functions given to women in these two time periods will be studied. The second variation will comprise the analysis of male and female assignments, training, and funding on general seats across time, which will require data collection over this time of 12-15 years, including the years during the war when Pakistan was under high international scrutiny.

Keywords: female representation, gender equality, democratic institutions, quota seats

Procedia PDF Downloads 85

Authors: Ciolomic Ioana Andreea, Farcas Teodora, Tiron-Tudor Adriana

Abstract:

Investments in research and innovation are widely acknowledged as being crucial drivers for economic growth, for job-creation and to secure social and economic welfare. The aim of this article is to disseminate the results of a Leonardo da Vinci Innovation Transfer project, AdapTykes Adaptation of trainings based up on the Finnish Workplace Development Programme. This project aims to analyses the adaptability of the Finnish model to the economic and political environment of the two emergent countries Romania and Hungary, in order to develop workplace innovation. The focus of this paper is to present the adaptability of the Finnish model to the Romanian context.

Keywords: innovation, human resources, education, tools

Procedia PDF Downloads 530

Authors: Vahid Bairami Rad

Abstract:

Extracting knowledge from spatial data like GIS data is important to reduce the data and extract information. Therefore, the development of new techniques and tools that support the human in transforming data into useful knowledge has been the focus of the relatively new and interdisciplinary research area ‘knowledge discovery in databases’. Thus, we introduce a set of database primitives or basic operations for spatial data mining which are sufficient to express most of the spatial data mining algorithms from the literature. This approach has several advantages. Similar to the relational standard language SQL, the use of standard primitives will speed-up the development of new data mining algorithms and will also make them more portable. We introduced a database-oriented framework for spatial data mining which is based on the concepts of neighborhood graphs and paths. A small set of basic operations on these graphs and paths were defined as database primitives for spatial data mining. Furthermore, techniques to efficiently support the database primitives by a commercial DBMS were presented.

Keywords: spatial data base, knowledge discovery database, data mining, spatial relationship, predictive data mining

Procedia PDF Downloads 462

Authors: B. Suraj Aravind, M. H. M. Krishna Prasad

Abstract:

There exist emerging applications of data streams that require association rule mining, such as network traffic monitoring, web click streams analysis, sensor data, data from satellites etc. Data streams typically arrive continuously in high speed with huge amount and changing data distribution. This raises new issues that need to be considered when developing association rule mining techniques for stream data. This paper proposes to introduce an improved data stream association rule mining algorithm by eliminating the limitation of resources. For this, the concept of cloud computing is used. Inclusion of this may lead to additional unknown problems which needs further research.

Keywords: data stream, association rule mining, cloud computing, frequent itemsets

Procedia PDF Downloads 503

Authors: Sina Mahdavi, Mahdi Asghari Ozma

Abstract:

Multiple sclerosis (MS) is the most common inflammatory autoimmune disease of the CNS that affects the myelination process in the central nervous system (CNS). Complex interactions of various "environmental or infectious" factors may act as triggers in autoimmunity and disease progression. The association between viral infections, especially human Varicella-zoster virus (VZV) and MS is one potential cause that is not well understood. This study aims to summarize the available data on VZV retrovirus infection in MS disease progression. For this study, the keywords "Multiple sclerosis", " Human Varicella-zoster virus ", and "central nervous system" in the databases PubMed, Google Scholar, Sid, and MagIran between 2016 and 2022 were searched and 14 articles were chosen, studied, and analyzed. Analysis of the amino acid sequences of HNRNPA1 with VZV proteins has shown a 62% amino acid sequence similarity between VZV gE and the PrLD/M9 epitope region (TNPO1 binding domain) of mutant HNRNPA1. A heterogeneous nuclear ribonucleoprotein (hnRNP), which is produced by HNRNPA1, is involved in the processing and transfer of mRNA and pre-mRNA. Mutant HNRNPA1 mimics gE of VZV as an antigen that leads to autoantibody production. Mutant HnRNPA1 translocates to the cytoplasm, after aggregation is presented by MHC class I, followed by CD8 + cells. Of these, antibodies and immune cells against the gE epitopes of VZV remain due to the memory immune response, causing neurodegeneration and the development of MS in genetically predisposed individuals. VZV expression during the course of MS is present in genetically predisposed individuals with HNRNPA1 mutation, suggesting a link between VZV and MS, and that this virus may play a role in the development of MS by inducing an inflammatory state. Therefore, measures to modulate VZV expression may be effective in reducing inflammatory processes in demyelinated areas of MS patients in genetically predisposed individuals.

Keywords: multiple sclerosis, varicella-zoster virus, central nervous system, autoimmunity

Procedia PDF Downloads 76

Authors: Suresh Lokiah

Abstract:

The emerging trend of integrating robots into elderly care, particularly for assisting patients with dementia, holds the potential to greatly transform the sector. Assisted living facilities, which house a significant number of elderly individuals and dementia patients, constantly strive to engage their residents in stimulating activities. However, due to staffing shortages, they often rely on volunteers to introduce new activities. Despite the availability of social interaction, these residents, frequently overlooked in society, are in desperate need of additional support. Robots designed for elder care are categorized based on their design and functionality. These categories include companion robots, telepresence robots, health monitoring robots, and rehab robots. However, the integration of such robots raises significant ethical concerns, notably regarding privacy, autonomy, and the risk of dehumanization. Privacy issues arise as these robots may need to continually monitor patient activities. There is also a risk of patients becoming overly dependent on these robots, potentially undermining their autonomy. Furthermore, the replacement of human touch with robotic interaction may lead to the dehumanization of care. This paper delves into the ethical considerations of incorporating robotic assistance in eldercare. It proposes a series of guidelines and strategies to ensure the ethical deployment of these robots. These guidelines suggest involving patients in the design and development process of the robots and emphasize the critical need for human oversight to respect the dignity and rights of the elderly and dementia patients. The paper also recommends implementing robust privacy measures, including secure data transmission and data anonymization. In conclusion, this paper offers a thorough examination of the ethical implications of using robotic assistance in elder care. It provides a strategic roadmap to ensure this technology is utilized ethically, thereby maximizing its potential benefits and minimizing any potential harm.

Keywords: human-robot interaction, robots for eldercare, ethics, health, dementia

Procedia PDF Downloads 99

Authors: Renate Gericke, Carol Long

Abstract:

Despite the robust empirical support of attachment, advancement in the description and conceptualization of attachment has been slow and has not significantly advanced beyond the identification of attachment security or type (namely, secure, avoidant, ambivalent and disorganized). This has continued despite papers arguing for theoretical refinement in the classification of attachment presentations. For thinking and practice to advance, it is critically important that these categories and their assessment be interrogated in different contexts and across developmental age. To achieve this, a quantitative design was used with descriptive and inferential statistics, and general linear models were employed to analyze the data. The Attachment Story Completion Test (ASCT) was administered to 105 children between the ages of eight and twelve from socio-economically deprived contexts with high exposure to trauma. A staggering 93% of the children had insecure attachments (specifically, avoidant 37%, disorganized 34% and ambivalent 22%) and attachment was more complex than currently conceptualized in the attachment literature. Primary attachment did not only present as one of four discreet categories, but 70% of the sample had a complex attachment with more than one type of maternal attachment style. Attachment intensity also varied along a continuum (between 1 and 5). The findings have implications for a) research that has not considered the potential complexity of attachment or attachment intensity, b) policy to more actively support mother-infant dyads, particularly in high-risk contexts and c) question the applicability of a western conceptualization of a primary maternal attachment figure in non-western collectivist societies.

Keywords: attachment, children at risk, middle childhood, non-western context

Procedia PDF Downloads 194

Authors: Ejaz Ashraf, Raheel Babar, Muhammad Yaseen, Hafiz Khurram Shurjeel, Nosheen Fatima

Abstract:

Main purpose of this study was to assess adoption level of farmers for quinoa cultivation after they had been taught through training and visit extension approach. At this time of the 21^st century, population structure, climate change, food requirements and eating habits of people are changing rapidly. In this scenario, farmers must play their key role in sustainable crop development and production through adoption of new crops that may also be helpful to overcome the issue of food insecurity as well as reducing poverty in rural areas. Its cultivation in Pakistan is at the early stages and there is a need to raise awareness among farmers to grow quinoa crops. In the middle of the 2015, a training and visit extension approach was used to raise awareness and convince farmers to grow quinoa in the area. During training and visit extension program, 80 farmers were randomly selected for the training of quinoa cultivation. Later on, these farmers trained 60 more farmers living into their neighborhood. After six months, a survey was conducted with all 140 farmers to assess the impact of the training and visit program on adoption level of respondents for the quinoa crop. The survey instrument was developed with the help of literature review and other experts of the crop. Validity and reliability of the instrument were checked before complete data collection. The data were analyzed by using SPSS. Multiple regression analysis was used for interpretation of the results from the survey, which indicated that factors like information/ training, change in agronomic and plant protection practices play a key role in the adoption of quinoa cultivation by respondents. In addition, the model explains more than 50% of variation in the adoption level of respondents. It is concluded that farmers need timely information for improved knowledge of agronomic and plant protection practices to adopt cultivation of the quinoa crop in the area.

Keywords: farmers, quinoa, adoption, contact, training and visit

Procedia PDF Downloads 359

Authors: Sidra Islam, Moin Uddin, Mir A. Rouf

Abstract:

A wide variety of pathological disorders owing to hyperglycemic conditions involves structural rearrangements and condensations of proteins. The implication of methylglyoxal (MG) modified immunoglobulin G (IgG) in the onset and progression of diabetes type 2 (T2DM) is studied in the present study. Using biophysical and biochemical approaches MG was found to perturb the structure of IgG, effect its microenvironment and leads to aggregate formation. Furthermore, MG-IgG was found to be highly immunogenic inducing high titre antibodies in female rabbits. Clinical studies revealed the presence of circulating anti-MG-IgG antibodies as analyzed by direct binding ELISA. The circulating auto antibodies were highly specific for MG-IgG as revealed by inhibition ELISA. Thus it can be concluded that MG is a powerful agent with a high damaging potential. To IgG. It is highly capable of generating immune response that contributes to the immunopathology associated with diabetes. Dicarbonyl adducts may emerge as potential biomarkers for T2DM.

Keywords: immunogenicity, Immunoglobulin G, methylglyoxal, Type 2 Diabetes Mellitus

Procedia PDF Downloads 271

Authors: Tosin Ige

Abstract:

Ethics must be a condition of the world, like logic. (Ludwig Wittgenstein, 1889-1951). As important as data mining is, it possess a significant threat to ethics, privacy, and legality, since data mining makes it difficult for an individual or consumer (in the case of a company) to control the accessibility and usage of his data. This research focuses on Current issues and the latest research and development on Privacy preserving data mining methods as at year 2022. It also discusses some advances in those techniques while at the same time highlighting and providing a new technique as a solution to an existing technique of privacy preserving data mining methods. This paper also bridges the wide gap between Data mining and the Web Application Programing Interface (web API), where research is urgently needed for an added layer of security in data mining while at the same time introducing a seamless and more efficient way of data mining.

Keywords: data, privacy, data mining, association rule, privacy preserving, mining technique

Procedia PDF Downloads 173

Authors: A. Alexandru, C. A. Alexandru, D. Coardos, E. Tudora

Abstract:

Big Data (BD) is associated with a new generation of technologies and architectures which can harness the value of extremely large volumes of very varied data through real time processing and analysis. It involves changes in (1) data types, (2) accumulation speed, and (3) data volume. This paper presents the main concepts related to the BD paradigm, and introduces architectures and technologies for BD and BD sets. The integration of BD with the Hadoop Framework is also underlined. BD has attracted a lot of attention in the public sector due to the newly emerging technologies that allow the availability of network access. The volume of different types of data has exponentially increased. Some applications of BD in the public sector in Romania are briefly presented.

Keywords: big data, big data analytics, Hadoop, cloud

Procedia PDF Downloads 312

Authors: A. Matiushkina, A. Bazhenova, I. Litvinov, E. Kornilova, A. Dubavik, A. Orlova

Abstract:

Magnetic-luminescent complexes based on superparamagnetic iron oxide nanoparticles (SPIONs) and semiconductor quantum dots (QDs) have been recognized as a new class of materials that have high potential in modern medicine. These materials can serve for theranostics of oncological diseases, and also as a target agent for drug delivery. They combine the qualities characteristic of magnetic nanoparticles, that is, magneto-controllability and the ability to local heating under the influence of an external magnetic field, as well as phosphors, due to luminescence of which, for example, early tumor imaging is possible. The complexity of creating complexes is the energy transfer between particles, which quenches the luminescence of QDs in complexes with SPIONs. In this regard, a relatively new type of alloyed (CdₓZn₁₋ₓSeᵧS₁₋ᵧ)-ZnS QDs is used in our work. The presence of a sufficiently thick gradient semiconductor shell in alloyed QDs makes it possible to reduce the probability of energy transfer from QDs to SPIONs in complexes. At the same time, Forster Resonance Energy Transfer (FRET) is a perfect instrument to confirm the formation of complexes based on QDs and different-type energy acceptors. The formation of complexes in the aprotic bipolar solvent dimethyl sulfoxide is ensured by the coordination of the carboxyl group of the stabilizing QD molecule (L-cysteine) on the surface iron atoms of the SPIONs. An analysis of the photoluminescence (PL) spectra has shown that a sequential increase in the SPIONs concentration in the samples is accompanied by effective quenching of the luminescence of QDs. However, it has not confirmed the formation of complexes yet, because of a decrease in the PL intensity of QDs due to reabsorption of light by SPIONs. Therefore, a study of the PL kinetics of QDs at different SPIONs concentrations was made, which demonstrates that an increase in the SPIONs concentration is accompanied by a symbatic reduction in all characteristic PL decay times. It confirms the FRET from QDs to SPIONs, which indicates the QDs/SPIONs complex formation, rather than a spontaneous aggregation of QDs, which is usually accompanied by a sharp increase in the percentage of the QD fraction with the shortest characteristic PL decay time. The complexes have been studied by the magnetic circular dichroism (MCD) spectroscopy that allows one to estimate the response of magnetic material to the applied magnetic field and also can be useful to check SPIONs aggregation. An analysis of the MCD spectra has shown that the complexes have zero residual magnetization, which is an important factor for using in biomedical applications, and don't contain SPIONs aggregates. Cell penetration, biocompatibility, and stability of QDs/SPIONs complexes in cancer cells have been studied using HeLa cell line. We have found that the complexes penetrate in HeLa cell and don't demonstrate cytotoxic effect up to 25 nM concentration. Our results clearly demonstrate that alloyed (CdₓZn₁₋ₓSeᵧS₁₋ᵧ)-ZnS QDs can be successfully used in complexes with SPIONs reached new hybrid nanostructures, which combine bright luminescence for tumor imaging and magnetic properties for targeted drug delivery and magnetic hyperthermia of tumors. Acknowledgements: This work was supported by the Ministry of Science and Higher Education of Russian Federation, goszadanie no. 2019-1080 and was financially supported by Government of Russian Federation, Grant 08-08.

Keywords: alloyed quantum dots, magnetic circular dichroism, magneto-luminescent complexes, superparamagnetic iron oxide nanoparticles

Procedia PDF Downloads 118

Authors: Ma Lei-Lei, Zhou You

Abstract:

Aiming at the problems of low detection accuracy of deep learning algorithm in traffic sign detection, this paper proposes improved EfficientDet based traffic sign detection algorithm. Multi-head self-attention is introduced in the minimum resolution layer of the backbone of EfficientDet to achieve effective aggregation of local and global depth information, and this study proposes an improved feature fusion pyramid with increased vertical cross-layer connections, which improves the performance of the model while introducing a small amount of complexity, the Balanced L1 Loss is introduced to replace the original regression loss function Smooth L1 Loss, which solves the problem of balance in the loss function. Experimental results show, the algorithm proposed in this study is suitable for the task of traffic sign detection. Compared with other models, the improved EfficientDet has the best detection accuracy. Although the test speed is not completely dominant, it still meets the real-time requirement.

Keywords: convolutional neural network, transformer, feature pyramid networks, loss function

Procedia PDF Downloads 99

Authors: Aïcha Ben Salem, Faouzi Boufares, Sebastiao Correia

Abstract:

The subject covered in this paper aims at assisting the user in its quality approach. The goal is to better extract, mix, interpret and reuse data. It deals with the semantic schema recognition of a data source. This enables the extraction of data semantics from all the available information, inculding the data and the metadata. Firstly, it consists of categorizing the data by assigning it to a category and possibly a sub-category, and secondly, of establishing relations between columns and possibly discovering the semantics of the manipulated data source. These links detected between columns offer a better understanding of the source and the alternatives for correcting data. This approach allows automatic detection of a large number of syntactic and semantic anomalies.

Keywords: schema recognition, semantic data profiling, meta-categorisation, semantic dependencies inter columns

Procedia PDF Downloads 418

Authors: Bikis Muhammed, Sehra Sedigh Sarvestani, Ali R. Hurson, Lasanthi Gamage

Abstract:

Vehicular traffic events have overly complex spatial correlations and temporal interdependencies and are also influenced by environmental events such as weather conditions. To capture these spatial and temporal interdependencies and make more realistic vehicular traffic predictions, graph neural networks (GNN) based traffic prediction models have been extensively utilized due to their capability of capturing non-Euclidean spatial correlation very effectively. However, most of the already existing GNN-based traffic prediction models have some limitations during learning complex and dynamic spatial and temporal patterns due to the following missing factors. First, most GNN-based traffic prediction models have used static distance or sometimes haversine distance mechanisms between spatially separated traffic observations to estimate spatial correlation. Secondly, most GNN-based traffic prediction models have not incorporated environmental events that have a major impact on the normal traffic states. Finally, most of the GNN-based models did not use an attention mechanism to focus on only important traffic observations. The objective of this paper is to study and make real-time vehicular traffic predictions while incorporating the effect of weather conditions. To fill the previously mentioned gaps, our prediction model uses a real-time driving distance between sensors to build a distance matrix or spatial adjacency matrix and capture spatial correlation. In addition, our prediction model considers the effect of six types of weather conditions and has an attention mechanism in both spatial and temporal data aggregation. Our prediction model efficiently captures the spatial and temporal correlation between traffic events, and it relies on the graph attention network (GAT) and Bidirectional bidirectional long short-term memory (Bi-LSTM) plus attention layers and is called GAT-BILSTMA.

Keywords: deep learning, real time prediction, GAT, Bi-LSTM, attention

Procedia PDF Downloads 73

Authors: D. R. Rama Brahma Reddy, A. Vijaya Sarada Reddy

Abstract:

Nanoparticles represent a promising drug delivery system of controlled and targeted drug release. They are specially designed to release the drug in the vicinity of target tissue. The aim of this study was to prepare and evaluate polymethacrylic acid nanoparticles containing Zidovudine in different drug to polymer ratio by nanoprecipitation method. SEM indicated that nanoparticles have a discrete spherical structure without aggregation. The average particle size was found to be 120 ± 0.02 - 420 ± 0.05 nm. The particle size of the nanoparticles was gradually increased with increase in the proportion of polymethacrylic acid polymer. The drug content of the nanoparticles was increasing on increasing polymer concentration up to a particular concentration. No appreciable difference was observed in the extent of degradation of product during 60 days in which, nanoparticles were stored at various temperatures. FT-IR studies indicated that there was no chemical interaction between drug and polymer and stability of drug. The in-vitro release behavior from all the drug loaded batches was found to be zero order and provided sustained release over a period of 24 h. The developed formulation overcome and alleviates the drawbacks and limitations of Zidovudine sustained release formulations and could possibility be advantageous in terms of increased bio availability of Zidovudine.

Keywords: nanoparticles, zidovudine, biodegradable, polymethacrylic acid

Procedia PDF Downloads 627

Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

Abstract:

Port authorities have many challenges in congested ports to allocate their resources to provide a safe and secure loading/ unloading procedure for cargo vessels. Selecting a destination port is the decision of a vessel master based on many factors such as weather, wavelength and changes of priorities. Having access to a tool which leverages AIS messages to monitor vessel’s movements and accurately predict their next destination port promotes an effective resource allocation process for port authorities. In this research, we propose a method, namely, Reference Route of Trajectory (RRoT) to assist port authorities in predicting inflow and outflow traffic in their local environment by monitoring Automatic Identification System (AIS) messages. Our RRoT method creates a reference route based on historical AIS messages. It utilizes some of the best trajectory similarity measure to identify the destination of a vessel using their recent movement. We evaluated five different similarity measures such as Discrete Fr´echet Distance (DFD), Dynamic Time Warping (DTW), Partial Curve Mapping (PCM), Area between two curves (Area) and Curve length (CL). Our experiments show that our method identifies the destination port with an accuracy of 98.97% and an fmeasure of 99.08% using Dynamic Time Warping (DTW) similarity measure.

Keywords: spatial temporal data mining, trajectory mining, trajectory similarity, resource optimization

Procedia PDF Downloads 122

Authors: Carolinda Douglass

Abstract:

Institutional Effectiveness (IE) is the purposeful integration of functions that foster student success and support institutional performance. IE is growing rapidly within higher education as it is increasingly viewed by higher education administrators as a beneficial approach for promoting data-informed decision-making in campus-wide strategic planning and execution of strategic initiatives. Specific IE tools, including, but not limited to, project management; impactful collaboration and communication; commitment to continuous quality improvement; and accountability through rigorous evaluation; are gaining momentum under the auspices of IE. This research utilizes a case study approach to examine the use of these IE tools, highlight successes of this use, and identify areas for improvement in the implementation of IE tools within higher education. The research includes three case studies: (1) improving upon academic program review processes including the assessment of student learning outcomes as a core component of program quality; (2) revising an institutional vision, mission, and core values; and (3) successfully navigating an institution-wide re-accreditation process. Several methods of data collection are embedded within the case studies, including surveys, focus groups, interviews, and document analyses. Subjects of these methods include higher education administrators, faculty, and staff. Key findings from the research include areas of success and areas for improvement in the use of IE tools associated with specific case studies as well as aggregated results across case studies. For example, the use of case management proved useful in all of the case studies, while rigorous evaluation did not uniformly provide the value-added that was expected by higher education decision-makers. The use of multiple IE tools was shown to be consistently useful in decision-making when applied with appropriate awareness of and sensitivity to core institutional culture (for example, institutional mission, local environments and communities, disciplinary distinctions, and labor relations). As IE gains a stronger foothold in higher education, leaders in higher education can make judicious use of IE tools to promote better decision-making and secure improved outcomes of strategic planning and the execution of strategic initiatives.

Keywords: accreditation, data-informed decision-making, higher education management, institutional effectiveness tools, institutional mission, program review, strategic planning

Procedia PDF Downloads 118

Authors: Weena Siangphro, Orawon Chailapakul, Kriangsak Songsrirote

Abstract:

A simple, rapid, sensitive, and economical method based on colorimetry for the determination of paraquat, a widely used herbicide, was developed. Citrate-coated silver nanoparticles (AgNPs) were synthesized as colorimetric probe. The mechanism of the assay is related to aggregation of negatively charged AgNPs induced by positively-charged paraquat resulting from coulombic attraction which causes the color change from deep greenish yellow to pale yellow upon the concentrations of paraquat. Silica gel was exploited as paraquat adsorbent for purification and pre-concentration prior to the direct determination with negatively charged AgNPs without elution step required. The validity of the proposed approach was evaluated by spiking standard paraquat in water and plant samples. Recoveries of paraquat in water samples were 93.6-95.4%, while those in plant samples were 86.6-89.5% by using the optimized extraction procedure. The absorbance of AgNPs at 400 nm was linearly related to the concentration of paraquat over the range of 0.05-50 mg/L with detection limits of 0.05 ppm for water samples, and 0.10 ppm for plant samples.

Keywords: colorimetric assay, paraquat, silica gel, silver nanoparticles

Procedia PDF Downloads 239

Authors: Michael Gidey Gebru

Abstract:

Most of Data Envelopment Analysis models operate in a static environment with input and output parameters that are chosen by deterministic data. However, due to ambiguity brought on shifting market conditions, input and output data are not always precisely gathered in real-world scenarios. Fuzzy numbers can be used to address this kind of ambiguity in input and output data. Therefore, this work aims to expand crisp Data Envelopment Analysis into Data Envelopment Analysis with fuzzy environment. In this study, the input and output data are regarded as fuzzy triangular numbers. Then, the Data Envelopment Analysis model with fuzzy environment is solved using a multi-objective method to gauge the Decision Making Units' efficiency. Finally, the developed Data Envelopment Analysis model is illustrated with an application on real data 50 educational institutions.

Keywords: efficiency, Data Envelopment Analysis, fuzzy, higher education, input, output

Procedia PDF Downloads 62

Authors: Maciej Jedrzejczyk, Karolina Marzantowicz

Abstract:

Traditional utility value chain is being transformed during last few years into unbundled markets. Increased distributed generation of energy is one of considerable challenges faced by Smart Grid networks. New sources of energy introduce volatile demand response which has a considerable impact on traditional middlemen in E&U market. The purpose of this research is to search for ways to allow near-real-time electricity markets to transact with surplus energy based on accurate time synchronous measurements. A proposed framework evaluates the use of secure peer-2-peer (P2P) communication and distributed transaction ledgers to provide flat hierarchy, and allow real-time insights into present and forecasted grid operations, as well as state and health of the network. An objective is to achieve dynamic grid operations with more efficient resource usage, higher security of supply and longer grid infrastructure life cycle. Methods used for this study are based on comparative analysis of different distributed ledger technologies in terms of scalability, transaction performance, pluggability with external data sources, data transparency, privacy, end-to-end security and adaptability to various market topologies. An intended output of this research is a design of a framework for safer, more efficient and scalable Smart Grid network which is bridging a gap between traditional components of the energy network and individual energy producers. Results of this study are ready for detailed measurement testing, a likely follow-up in separate studies. New platforms for Smart Grid achieving measurable efficiencies will allow for development of new types of Grid KPI, multi-smart grid branches, markets, and businesses.

Keywords: autonomous agents, Distributed computing, distributed ledger technologies, large scale systems, micro grids, peer-to-peer networks, Self-organization, self-stabilization, smart grids

Procedia PDF Downloads 303

Authors: Ariel Barel, Rotem Manor, Alfred M. Bruckstein

Abstract:

We present a probabilistic gathering algorithm for agents that can only detect the presence of other agents in front of or behind them. The agents act in the plane and are identical and indistinguishable, oblivious, and lack any means of direct communication. They do not have a common frame of reference in the plane and choose their orientation (direction of possible motion) at random. The analysis of the gathering process assumes that the agents act synchronously in selecting random orientations that remain fixed during each unit time-interval. Two algorithms are discussed. The first one assumes discrete jumps based on the sensing results given the randomly selected motion direction, and in this case, extensive experimental results exhibit probabilistic clustering into a circular region with radius equal to the step-size in time proportional to the number of agents. The second algorithm assumes agents with continuous sensing and motion, and in this case, we can prove gathering into a very small circular region in finite expected time.

Keywords: control, decentralized, gathering, multi-agent, simple sensors

Procedia PDF Downloads 164

Authors: Ismail Haddad, Djamel Herbadji, Aissa Belmeguenai, Selma Boumerdassi

Abstract:

in this paper, we provide a novel approach for image encryption that employs the Fibonacci matrix and an enhanced fractional order chaotic map. The enhanced map overcomes the drawbacks of the classical map, especially the limited chaotic range and non-uniform distribution of chaotic sequences, resulting in a larger encryption key space. As a result, this strategy improves the encryption system's security. Our experimental results demonstrate that our proposed algorithm effectively encrypts grayscale images with exceptional efficiency. Furthermore, our technique is resistant to a wide range of potential attacks, including statistical and entropy attacks.

Keywords: image encryption, logistic map, fibonacci matrix, grayscale images

Procedia PDF Downloads 318

Authors: Aqeel Zeid, Hasna Anees, Mohamed Adheeb, Mohamed Rifan, Kalpani Manathunga

Abstract:

To achieve constructive alignment in a higher education program, a clear set of learning outcomes must be defined. Traditional learning outcome definition techniques such as Bloom’s taxonomy are not written to be utilized by the student. This might be disadvantageous for students in student-centric learning settings where the students are expected to formulate their own learning strategies. To solve the problem, we propose the learning outcome relation and aggregation (LORA) model. To achieve alignment, we developed learning outcome, assessment, and resource authoring tools which help teachers to tag learning outcomes during creation. A pilot study was conducted with an expert panel consisting of experienced professionals in the education domain to evaluate whether the LORA model and tools present an improvement over the traditional methods. The panel unanimously agreed that the model and tools are beneficial and effective. Moreover, it helped them model learning outcomes in a more student centric and descriptive way.

Keywords: learning design, constructive alignment, Bloom’s taxonomy, learning outcome modelling

Procedia PDF Downloads 188

Authors: Oded Hochman

Abstract:

We first show that current measures of welfare changes in the whole economy do not apply to an economy with cities. In addition, since such measures are defined over a partial equilibrium, they capture only partially the effect of a welfare change. We then define a unique and additive measure that we term the modified economic surplus (mES) which fully captures the welfare effects caused by a change in the price of a nationally traded good. We show that the price change causes, on the one hand a change of land rents in the economy and, on the other hand, an equal change of mES that can be estimated by measuring areas in the price-quantity national demand and supply plane. We construct for each city a cost function from which we derive a city’s and, after aggregation, an economy-wide demand and supply functions of nationwide prices and of either the unearned incomes (Marshalian functions) or the utility levels (compensated functions).

Keywords: city cost function, welfare measures, modified compensated variation, modified economic surplus, unearned income function, differential land rents, city size

Procedia PDF Downloads 323

Authors: Jeana Cadby, Kae Miyazawa

Abstract:

With rapidly expanding worldwide adoption of mobile technologies, Information and Communication Technology (ITC) is a major energy user and a contributor to global carbon emissions, due to infrastructure and operational energy consumption. The agricultural sector is also significantly responsible for contributing to global carbon emissions. However, ICT cloud computing using mobile technology can directly reduce environmental impacts in the agricultural sector through applications and mobile connectivity, such as precision fertilizer and pesticide applications, or access to weather data, for example. While direct impacts are easily calculated, indirect environmental impacts from ICT cloud computing usage have not been thoroughly investigated. For example, while women may be more poorly equipped for adaptation to environmentally sustainable agricultural practices due to resource constraints, this research concludes that indirect environmental benefits can be achieved by improving rural access to mobile technology for women. Women in advanced roles and secure land tenure are more likely to invest in long-term agricultural conservation strategies, which protect against environmental degradation. This study examines how ICT using mobile technology advances the role of women in rural agricultural systems and indirectly reduces environmental impacts from agricultural production, through literature examination from secondary sources. Increasing access for women to ICT mobile technology provides indirect environmental and social benefits in the rural agricultural sector.

Keywords: cloud computing, environmental benefits, mobile technology, women

Procedia PDF Downloads 171

Authors: Chieh-Fu Chang, Wan-Hsin Hsieh

Abstract:

We have proposed a novel scheme— iterative word-extension (IWE) to enhance the cliff effect of Reed-Solomon codes regarding the error performance at a specific Eb/N0. The scheme can be readily extended to block codes and the important properties of IWE are further investigated here. In order to select proper block codes specifying the desired cliff Eb/N0, the associated features of IWE are explored. These properties and features grant IWE ability to enhance security regarding the received Eb/N0 in physical layer so that IWE scheme can cooperate with the traditional presentation layer approach — cryptography, to meet the secure requirements in diverse applications. The features and feasibility of IWE scheme in satellite communication are finally discussed.

Keywords: security, IWE, cliff effect, space communications

Procedia PDF Downloads 427

Authors: Kacper Tomasz Kröber-Mulawa

Abstract:

This paper will address the topic of data ownership from an economic perspective, and examples of economic limitations of data property rights will be provided, which have been identified using methods and approaches of economic analysis of law. To properly build a background for the economic focus, in the beginning a short perspective of data and data ownership in the EU’s legal system will be provided. It will include a short introduction to its political and social importance and highlight relevant viewpoints. This will stress the importance of a Single Market for data but also far-reaching regulations of data governance and privacy (including the distinction of personal and non-personal data, data held by public bodies and private businesses). The main discussion of this paper will build upon the briefly referred to legal basis as well as methods and approaches of economic analysis of law.

Keywords: antitrust, data, data ownership, digital economy, property rights

Procedia PDF Downloads 83

Authors: Abdullah Alsaeed

Abstract:

Virtualized computing and cloud computing infrastructures are no longer fuzz or marketing term. They are a core reality in today’s corporate Information Technology (IT) organizations. Hence, developing an effective and efficient methodologies for data backup and data recovery is required more than any time. The purpose of data backup and recovery techniques are to assist the organizations to strategize the business continuity and disaster recovery approaches. In order to accomplish this strategic objective, a variety of mechanism were proposed in the recent years. This research paper will explore and examine the latest techniques and solutions to provide data backup and restoration for the cloud computing platforms.

Keywords: data backup, data recovery, cloud computing, business continuity, disaster recovery, cost-effective, data encryption.

Procedia PDF Downloads 89