Search results for: data life cycle

Authors: Jayesh M. Patel, Bharat P. Modi

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The availability of on mobile devices that can invoke the demonstrated that the total data demand from users is far higher than previously articulated by measurements based solely on a cellular-centric view of smart-phone usage. The ratio of Wi-Fi to cellular traffic varies significantly between countries, This paper is shown the compression between the cellular data usage and Wi-Fi data usage by the user. This strategy helps operators to understand the growing importance and application of yield management strategies designed to squeeze maximum returns from their investments into the networks and devices that enable the mobile data ecosystem. The transition from unlimited data plans towards tiered pricing and, in the future, towards more value-centric pricing offers significant revenue upside potential for mobile operators, but, without a complete insight into all aspects of smartphone customer behavior, operators will unlikely be able to capture the maximum return from this billion-dollar market opportunity.

Keywords: cellular, Wi-Fi, mobile, smart phone

Procedia PDF Downloads 370

Authors: Nigatu Tadesse, Li Juan, Liuhong Ming

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Gastric cancer (GC) is the fifth most common and fourth deadly cancer in the world with limited treatment options at late advanced stage in which surgical therapy is not recommended with chemotherapy remain as the mainstay of treatment. However, the occurrence of chemoresistance as well as intera-tumoral and inter-tumoral heterogeneity of response to targeted and immunotherapy underlined a clear unmet treatment need in gastroenterology. Several molecular and cellular alterations ascribed for chemo resistance in GC including cancer stem cells (CSC) and tumor microenvironment (TME) remodeling. Cancer cells including CSC bears higher metabolic demand and major changes in TME involves alterations of gut microbiota interacting with nutrients metabolism. Metabolic upregulation in lipids, carbohydrates, amino acids, fatty acids biosynthesis pathways identified as a common hall mark in GC. Metabolic addiction to methionine metabolism occurs in many cancer cells to promote the biosynthesis of S-Adenosylmethionine (SAM), a universal methyl donor molecule for high rate of transmethylation in GC and promote cell proliferation. Targeting methionine metabolism found to promotes chemo-sensitivity with treatment non-heterogeneity. Methionine restriction (MR) promoted the arrest of cell cycle at S/G2 phase and enhanced downregulation of GC cells resistance to apoptosis (including ferroptosis), which suggests the potential of synergy with chemotherapies acting at S-phase of the cell cycle as well as inducing cell apoptosis. Accumulated evidences showed both the biogenesis as well as intracellular metabolism of exogenous methionine could be safe and effective target for therapy either alone or in combination with chemotherapies. This review article provides an over view of the upregulation in methionine biosynthesis pathway and the molecular signaling through the PI3K/Akt/mTOR-c-MYC axis to promote metabolic reprograming through activating the expression of L-type aminoacid-1 (LAT1) transporter and overexpression of Methionine adenosyltransferase 2A(MAT2A) for intercellular metabolic conversion of exogenous methionine to SAM in GC, and the potential of targeting with novel therapeutic agents such as methioninase (METase), Methionine adenosyltransferase 2A (MAT2A), c-MYC, methyl like transferase 16 (METTL16) inhibitors that are currently under clinical trial development stages and future perspectives.

Keywords: gastric cancer, methionine metabolism, pi3k/akt/mtorc1-c-myc axis, gut microbiota, MAT2A, c-MYC, METTL16, methioninase

Procedia PDF Downloads 56

Authors: Funda Kul, İsmail Gür

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Pension scheme providers have to price mortality risk by accurate mortality forecasting method. There are many mortality-forecasting methods constructed and used in literature. The Lee-Carter model is the first model to consider stochastic improvement trends in life expectancy. It is still precisely used. Mortality forecasting is done by mortality index in the Lee-Carter model. It is assumed that mortality index fits ARIMA time series model. In this paper, we propose and use dynamic normal inverse gaussian distribution to modeling mortality indes in the Lee-Carter model. Using population mortality data for Italy, France, and Turkey, the model is forecasting capability is investigated, and a comparative analysis with other models is ensured by some well-known benchmarking criterions.

Keywords: mortality, forecasting, lee-carter model, normal inverse gaussian distribution

Procedia PDF Downloads 364

Authors: Debbarma Asis, Guha Chandan

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Tumor Protein-53 (P53) is one of the tumor suppressor proteins. P53 regulates the cell cycle that conserves stability by preventing genome mutation. It is named so as it runs as 53-kilodalton (kDa) protein on Polyacrylamide gel electrophoresis although the actual mass is 43.7 kDa. Experimental evidence has indicated that P53 cancer mutants loses tumor suppression activity and subsequently gain oncogenic activities to promote tumourigenesis. Tumor-specific DNA has recently been detected in the plasma of breast cancer patients. Detection of tumor-specific genetic materials in cancer patients may provide a unique and valuable tumor marker for diagnosis and prognosis. Commercially available MDA-468 breast cancer cell line was used for the proposed study.

Keywords: tumor protein (P53), cancer mutants, MDA-468, tumor suppressor gene

Procedia PDF Downloads 484

Authors: Pedram Saadati, Zahra Nazari

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Anticipating and identifying future opportunities and challenges facing industry activists for the emergence and entry of new knowledge and technologies of personal financial planning, and providing practical solutions is one of the goals of this research. For this purpose, a future research tool based on receiving opinions from the main players of the insurance industry has been used. The research method in this study was in 4 stages; including 1- a survey of the specialist salesforce of life insurance in order to identify the variables 2- the ranking of the variables by experts selected by a researcher-made questionnaire 3- holding a panel of experts with the aim of understanding the mutual effects of the variables and 4- statistical analyzes of the mutual effects matrix in Mick Mac software is done. The integrated analysis of influencing variables in the future has been done with the method of Structural Analysis, which is one of the efficient and innovative methods of future research. A list of opportunities and challenges was identified through a survey of best-selling life insurance representatives who were selected by snowball sampling. In order to prioritize and identify the most important issues, all the issues raised were sent to selected experts who were selected theoretically through a researcher-made questionnaire. The respondents determined the importance of 36 variables through scoring, so that the prioritization of opportunity and challenge variables can be determined. 8 of the variables identified in the first stage were removed by selected experts, and finally, the number of variables that could be examined in the third stage became 28 variables, which, in order to facilitate the examination, were divided into 6 categories, respectively, 11 variables of organization and management. Marketing and sales 7 cases, social and cultural 6 cases, technological 2 cases, rebranding 1 case and insurance 1 case were divided. The reliability of the researcher-made questionnaire was confirmed with the Cronbach's alpha test value of 0.96. In the third stage, by forming a panel consisting of 5 insurance industry experts, the consensus of their opinions about the influence of factors on each other and the ranking of variables was entered into the matrix. The matrix included the interrelationships of 28 variables, which were investigated using the structural analysis method. By analyzing the data obtained from the matrix by Mic Mac software, the findings of the research indicate that the categories of "correct training in the use of the software, the weakness of the technology of insurance companies in personalizing products, using the approach of equipping the customer, and honesty in declaring no need Customer to Insurance", the most important challenges of the influencer and the categories of "salesforce equipping approach, product personalization based on customer needs assessment, customer's pleasant experience of being consulted with consulting robots, business improvement of the insurance company due to the use of these tools, increasing the efficiency of the issuance process and optimal customer purchase" were identified as the most important opportunities for influence.

Keywords: personal financial planning, wealth management, advisor robots, life insurance, digital transformation

Procedia PDF Downloads 52

Authors: U. Paniveni

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A few parameters of supergranular cells are studied using intensity patterns from the Kodaikanal Solar Observatory and Dopplergrams from SOHO. The turbulent aspect of the solar supergranulation is established by examining the interrelationships amongst the parameters characterizing a supergranular cell, namely size, lifetime, area, perimeter, fractal dimension, and horizontal flow velocity. The complexity of supergranular cells depicted by their fractal dimension is indicative of their non-laminar characteristics. The findings corroborate Kolmogorov’s theory of turbulence. Some parameters of supergranular cells also show a latitudinal dependence. Supergranulation is a synonym of convective phenomenon and hence can shed light on the physical conditions in the convection zone of the Sun. It plays a major role in the transport and dispersal of magnetic fields that may have a relation to the phases of the solar cycle.

Keywords: sun, granulation, convection, turbulence

Procedia PDF Downloads 46

Authors: Feras Hanandeh, Izzat Alsmadi, Muhammad M. Kwafha

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Prefix trees or tries are data structures that are used to store data or index of data. The goal is to be able to store and retrieve data by executing queries in quick and reliable manners. In principle, the structure of the trie depends on having letters in nodes at the different levels to point to the actual words in the leafs. However, the exact structure of the trie may vary based on several aspects. In this paper, we evaluated different structures for building tries. Using datasets of words of different sizes, we evaluated the different forms of trie structures. Results showed that some characteristics may impact significantly, positively or negatively, the size and the performance of the trie. We investigated different forms and structures for the trie. Results showed that using an array of pointers in each level to represent the different alphabet letters is the best choice.

Keywords: data structures, indexing, tree structure, trie, information retrieval

Procedia PDF Downloads 455

Authors: Elizaveta Petelina, Anton Sizo

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Environmental remediation projects deal with a wide spectrum of data, including data collected during site assessment, execution of remediation activities, and environmental monitoring. Therefore, an appropriate data management is required as a key factor for well-grounded decision making. The Environmental Data Management System (EDMS) was developed to address all necessary data management aspects, including efficient data handling and data interoperability, access to historical and current data, spatial and temporal analysis, 2D and 3D data visualization, mapping, and data sharing. The system focuses on support of well-grounded decision making in relation to required mitigation measures and assessment of remediation success. The EDMS is a combination of enterprise and desktop level data management and Geographic Information System (GIS) tools assembled to assist to environmental remediation, project planning, and evaluation, and environmental monitoring of mine sites. EDMS consists of seven main components: a Geodatabase that contains spatial database to store and query spatially distributed data; a GIS and Web GIS component that combines desktop and server-based GIS solutions; a Field Data Collection component that contains tools for field work; a Quality Assurance (QA)/Quality Control (QC) component that combines operational procedures for QA and measures for QC; Data Import and Export component that includes tools and templates to support project data flow; a Lab Data component that provides connection between EDMS and laboratory information management systems; and a Reporting component that includes server-based services for real-time report generation. The EDMS has been successfully implemented for the Project CLEANS (Clean-up of Abandoned Northern Mines). Project CLEANS is a multi-year, multimillion-dollar project aimed at assessing and reclaiming 37 uranium mine sites in northern Saskatchewan, Canada. The EDMS has effectively facilitated integrated decision-making for CLEANS project managers and transparency amongst stakeholders.

Keywords: data management, environmental remediation, geographic information system, GIS, decision making

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Authors: Bharat Singh Om Prakash Vyas

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Now a day’s applications deal with High Dimensional Data have tremendously used in the popular areas. To tackle with such kind of data various approached has been developed by researchers in the last few decades. To tackle with such kind of data various approached has been developed by researchers in the last few decades. One of the problems with the NMF approaches, its randomized valued could not provide absolute optimization in limited iteration, but having local optimization. Due to this, we have proposed a new approach that considers the initial values of the decomposition to tackle the issues of computationally expensive. We have devised an algorithm for initializing the values of the decomposed matrix based on the PSO (Particle Swarm Optimization). Through the experimental result, we will show the proposed method converse very fast in comparison to other row rank approximation like simple NMF multiplicative, and ACLS techniques.

Keywords: ALS, NMF, high dimensional data, RMSE

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Authors: Debasmita Misra, Arthur Nash

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Energy security and sufficiency enables the economic development and welfare of a nation or a society. Currently, the global energy system is dominated by fossil fuels, which is a non-renewable energy resource, which renders vulnerability to energy security. Hence, many nations have begun augmenting their energy system with renewable energy resources, such as solar, wind, biomass and hydro. However, with climate change, how sustainable are some of the renewable energy resources in the future is a matter of concern. Geothermal energy resources have been underexplored or underexploited in global renewable energy production and security, although it is gaining attractiveness as a renewable energy resource. The question is, whether geothermal energy resources are more sustainable than other renewable energy resources. High-temperature reservoirs (> 220 °F) can produce electricity from flash/dry steam plants as well as binary cycle production facilities. Most of the world’s high enthalpy geothermal resources are within the seismo-tectonic belt. However, exploration for geothermal energy is of great importance in conventional geothermal systems in order to improve its economic viability. In recent years, there has been an increase in the use and development of several exploration methods for geo-thermal resources, such as seismic or electromagnetic methods. The thermal infrared band of the Landsat can reflect land surface temperature difference, so the ETM+ data with specific grey stretch enhancement has been used to explore underground heat water. Another way of exploring for potential power is utilizing fairway play analysis for sites without surface expression and in rift zones. Utilizing this type of analysis can improve the success rate of project development by reducing exploration costs. Identifying the basin distribution of geologic factors that control the geothermal environment would help in identifying the control of resource concentration aside from the heat flow, thus improving the probability of success. The first step is compiling existing geophysical data. This leads to constructing conceptual models of potential geothermal concentrations which can then be utilized in creating a geodatabase to analyze risk maps. Geospatial analysis and other GIS tools can be used in such efforts to produce spatial distribution maps. The goal of this paper is to discuss how climate change may impact renewable energy resources and how could a synthesized analysis be developed for geothermal resources to ensure sustainable and cost effective exploitation of the resource.

Keywords: exploration, geothermal, renewable energy, sustainable

Procedia PDF Downloads 155

Authors: Enkelejda Koka, Denard Veshi

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Since 2011, in the name of ‘humanitarianism’ and deaths in the Mediterranean Sea, the legal and political justification delivered by Greece to manage the refugee crisis is pre-emptive interception. Although part of the EU, Greece adopted its own strategy. These practices have also created high risks for migrants generally resulting in non-rescue episodes and push-back practices having lethal consequences to the life of the irregular migrant. Thus, this article provides an analysis of the Greek ‘compassionate border work’ policy, a practice known as push-back. It is argued that these push-back practices violate international obligations, notably the ‘right to life’, the ‘duty to search and rescue’, the prohibition of inhuman or degrading treatment or punishment and the principle of non-refoulement.

Keywords: Greece, migrants, push-back policy, violation of international law

Procedia PDF Downloads 142

Authors: Xudong Guan, Ainong Li, Gaohuan Liu, Chong Huang, Wei Zhao

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Due to the low spatial resolution of MODIS data, the accuracy of small-area plaque extraction with a high degree of landscape fragmentation is greatly limited. To this end, the study combines Landsat data with higher spatial resolution and MODIS data with higher temporal resolution for decision-level fusion. Considering the importance of the land heterogeneity factor in the fusion process, it is superimposed with the weighting factor, which is to linearly weight the Landsat classification result and the MOIDS classification result. Three levels were used to complete the process of data fusion, that is the pixel of MODIS data, the pixel of Landsat data, and objects level that connect between these two levels. The multilevel decision fusion scheme was tested in two sites of the lower Mekong basin. We put forth a comparison test, and it was proved that the classification accuracy was improved compared with the single data source classification results in terms of the overall accuracy. The method was also compared with the two-level combination results and a weighted sum decision rule-based approach. The decision fusion scheme is extensible to other multi-resolution data decision fusion applications.

Keywords: image classification, decision fusion, multi-temporal, remote sensing

Procedia PDF Downloads 127

Authors: Wang Lin, Li Zhiqiang

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The purpose of this paper is to analyze the cooperative learning behavior pattern based on the data of students' movement. The study firstly reviewed the cooperative learning theory and its research status, and briefly introduced the k-means clustering algorithm. Then, it used clustering algorithm and mathematical statistics theory to analyze the activity rhythm of individual student and groups in different functional areas, according to the movement data provided by 10 first-year graduate students. It also focused on the analysis of students' behavior in the learning area and explored the law of cooperative learning behavior. The research result showed that the cooperative learning behavior analysis method based on movement data proposed in this paper is feasible. From the results of data analysis, the characteristics of behavior of students and their cooperative learning behavior patterns could be found.

Keywords: behavior pattern, cooperative learning, data analyze, k-means clustering algorithm

Procedia PDF Downloads 191

Authors: Nirav Vaghela, Sanket Parekh

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Objective: Musculoskeletal disorders (MSD) represent one of the most common and important occupational health problems in working populations, being responsible for a substantial impact on quality of life and incurring a major economic burden in compensation cost and lost wages. School teachers represent an occupational group among which there appears to be a high prevalence of MSD. Design: Three hundred and fourteen teachers were enrolled in this study. Teachers were interview with the Modified Nordic Questionnaire. Result: In current study total 314 participants have been recruited in that minimum age of participants is 22 and maximum age is 59 with mean 40.5± 9.88. Total prevalence of the MSD is 71.95% among the teachers. In that Female were more affected with 72% than the males with 28%. Conclusion: The teachers here in reported a high prevalence of musculoskeletal pain in the shoulder, knee and back.

Keywords: repetitive stress injury, pain, occupational hazards, disability, abneetism, physical health, quality of life

Procedia PDF Downloads 294

Authors: C.Ardil

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Open Science translates the understanding and application of various theories and practices in open science philosophy, systems, paradigms and epistemology. Open Science originates with the premise that universal scientific knowledge is a product of a collective scholarly and social collaboration involving all stakeholders and knowledge belongs to the global society. Scientific outputs generated by public research are a public good that should be available to all at no cost and without barriers or restrictions. Open Science has the potential to increase the quality, impact and benefits of science and to accelerate advancement of knowledge by making it more reliable, more efficient and accurate, better understandable by society and responsive to societal challenges, and has the potential to enable growth and innovation through reuse of scientific results by all stakeholders at all levels of society, and ultimately contribute to growth and competitiveness of global society. Open Science is a global movement to improve accessibility to and reusability of research practices and outputs. In its broadest definition, it encompasses open access to publications, open research data and methods, open source, open educational resources, open evaluation, and citizen science. The implementation of open science provides an excellent opportunity to renegotiate the social roles and responsibilities of publicly funded research and to rethink the science system as a whole. Open Science is the practice of science in such a way that others can collaborate and contribute, where research data, lab notes and other research processes are freely available, under terms that enable reuse, redistribution and reproduction of the research and its underlying data and methods. Open Science represents a novel systematic approach to the scientific process, shifting from the standard practices of publishing research results in scientific publications towards sharing and using all available knowledge at an earlier stage in the research process, based on cooperative work and diffusing scholarly knowledge with no barriers and restrictions. Open Science refers to efforts to make the primary outputs of publicly funded research results (publications and the research data) publicly accessible in digital format with no limitations. Open Science is about extending the principles of openness to the whole research cycle, fostering, sharing and collaboration as early as possible, thus entailing a systemic change to the way science and research is done. Open Science is the ongoing transition in how open research is carried out, disseminated, deployed, and transformed to make scholarly research more open, global, collaborative, creative and closer to society. Open Science involves various movements aiming to remove the barriers for sharing any kind of output, resources, methods or tools, at any stage of the research process. Open Science embraces open access to publications, research data, source software, collaboration, peer review, notebooks, educational resources, monographs, citizen science, or research crowdfunding. The recognition and adoption of open science practices, including open science policies that increase open access to scientific literature and encourage data and code sharing, is increasing in the open science philosophy. Revolutionary open science policies are motivated by ethical, moral or utilitarian arguments, such as the right to access digital research literature for open source research or science data accumulation, research indicators, transparency in the field of academic practice, and reproducibility. Open science philosophy is adopted primarily to demonstrate the benefits of open science practices. Researchers use open science applications for their own advantage in order to get more offers, increase citations, attract media attention, potential collaborators, career opportunities, donations and funding opportunities. In open science philosophy, open data findings are evidence that open science practices provide significant benefits to researchers in scientific research creation, collaboration, communication, and evaluation according to more traditional closed science practices. Open science considers concerns such as the rigor of peer review, common research facts such as financing and career development, and the sacrifice of author rights. Therefore, researchers are recommended to implement open science research within the framework of existing academic evaluation and incentives. As a result, open science research issues are addressed in the areas of publishing, financing, collaboration, resource management and sharing, career development, discussion of open science questions and conclusions.

Keywords: Open Science, Open Science Philosophy, Open Science Research, Open Science Data

Procedia PDF Downloads 139

Authors: B. Sudarsan Baskar, S. Pooja Pragati, S. Raj Kumar

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The cost effectiveness in aircraft maintenance is of high privilege in the recent days. The cost effectiveness can be effectively made when line maintenance activities are incorporated at airports during Turn around time (TAT). The present work outcomes the shortcomings that affect the dispatching of the aircrafts, aiming at high fleet operability and low maintenance cost. The operational and cost constraints have been discussed and a suggestive alternative mechanism is proposed. The possible allocation of all deferred maintenance tasks to a set of all deferred maintenance tasks to a set of suitable airport resources have termed as alternative and is discussed in this paper from the data’s collected from the kingfisher airlines.

Keywords: decision support system, aircraft maintenance planning, maintenance-cost, RUL(remaining useful life), logistics, supply chain management

Procedia PDF Downloads 511

Authors: Behnaz Pahlousay, Farshad Kazemnejad, Elisa Palezzato, Michele Torielli

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In this paper, we study the notions of connected domination number and of outer-connected domination number for middle graphs. Indeed, we obtain tight bounds for these numbers in terms of the order of the middle graph M(G). We also compute the outer-connected domination number of some families of graphs such as star graphs, cycle graphs, wheel graphs, complete graphs, complete bipartite graphs and some operation on graphs, explicitly. Moreover, some Nordhaus-Gaddum-like relations are presented for the outer-connected domination number of middle graphs.

Keywords: connected domination number, outer-connected dom- ination number, domination number, middle graph, nordhaus- gaddum-like relation.

Procedia PDF Downloads 51

Authors: Jakia Rajoana

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The key aim of this research is to achieve Sustainable Rural Tourism (SRT) through women’s empowerment in the Sundarbans area of Bangladesh. Women in rural areas in developing countries depend on biomass for their survival and that of their family. Yet they have an unequal access to resources as well as decision making, thus making them more vulnerable to any changes in the environment. Women in the developing countries experience gender inequality which is culturally embedded resulting into women having less access to and control over financial and material resources, information, and also a lack of recognition of their contribution as compared to men. Their disadvantaged social position is augmented by their extreme poverty, little or no power they have over their own lives vis-à-vis the disproportionate burden they bear in reproduction and child-raising. Despite the significance of the need to pay attention to gender related issues in sustainable rural tourism (SRT), research remains rather scant. For instance, there is very little research that illustrates the role of women in tourism in the Sundarbans area. Thus empirically, this research seeks to fill a significant gap by focusing on rural areas and in particular focus on considerably under-researched area, namely the Sundarbans women’s role in tourism. In order to fully comprehend their experiences and life stories, this research will apply the empowerment theory and consider it along with the research on sustainable rural tourism. Since, women’s empowerment can act as a potential tool for SRT development and also examine the role tourism plays in the lives of Sundarbans’ women. Methodologically, this study will follow a qualitative research design using an ethnographic approach. Participant observation, semi- structured interviews, and documentation will be the primary data collection instruments in four communities – Shayamnagar, Koyra, Mongla and Sarankhola – in the Sundarbans area. It is hoped that by focusing on the life stories of these invisible women, research is better able to engage with nuances inherent in marginal and significantly under-researched communities.

Keywords: gender, sustainable rural tourism, women empowerment, Sundarbans

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Authors: Meng Su

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High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

Procedia PDF Downloads 114

Authors: Ming Lun Wang, Yan Wang, Ning Ruo Sun

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With the development of cloud computing, more and more users start to utilize the cloud storage service. However, there exist some issues: 1) cloud server steals the shared data, 2) sharers collude with the cloud server to steal the shared data, 3) cloud server tampers the shared data, 4) sharers and key generation center (KGC) conspire to steal the shared data. In this paper, we use advanced encryption standard (AES), hash algorithms, and accountable key-policy attribute-based encryption without key escrow (WOKE-AKP-ABE) to build a security cloud storage scheme. Moreover, the data are encrypted to protect the privacy. We use hash algorithms to prevent the cloud server from tampering the data uploaded to the cloud. Analysis results show that this scheme can resist conspired attacks.

Keywords: cloud storage security, sharing storage, attributes, Hash algorithm

Procedia PDF Downloads 392

Authors: Amela Ajanovic, Reinhard Haas

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Electric vehicles (EVs) are considered as an important means to cope with current environmental problems in transport. However, their high capital costs and limited driving ranges state major barriers to a broader market penetration. The core objective of this paper is to investigate the future market prospects of various types of EVs from an economic and ecological point of view. Our method of approach is based on the calculation of total cost of ownership of EVs in comparison to conventional cars and a life-cycle approach to assess the environmental benignity. The most crucial parameters in this context are km driven per year, depreciation time of the car and interest rate. The analysis of future prospects it is based on technological learning regarding investment costs of batteries. The major results are the major disadvantages of battery electric vehicles (BEVs) are the high capital costs, mainly due to the battery, and a low driving range in comparison to conventional vehicles. These problems could be reduced with plug-in hybrids (PHEV) and range extenders (REXs). However, these technologies have lower CO₂ emissions in the whole energy supply chain than conventional vehicles, but unlike BEV they are not zero-emission vehicles at the point of use. The number of km driven has a higher impact on total mobility costs than the learning rate. Hence, the use of EVs as taxis and in car-sharing leads to the best economic performance. The most popular EVs are currently full hybrid EVs. They have only slightly higher costs and similar operating ranges as conventional vehicles. But since they are dependent on fossil fuels, they can only be seen as energy efficiency measure. However, they can serve as a bridging technology, as long as BEVs and fuel cell vehicle do not gain high popularity, and together with PHEVs and REX contribute to faster technological learning and reduction in battery costs. Regarding the promotion of EVs, the best results could be reached with a combination of monetary and non-monetary incentives, as in Norway for example. The major conclusion is that to harvest the full environmental benefits of EVs a very important aspect is the introduction of CO₂-based fuel taxes. This should ensure that the electricity for EVs is generated from renewable energy sources; otherwise, total CO₂ emissions are likely higher than those of conventional cars.

Keywords: costs, mobility, policy, sustainability,

Procedia PDF Downloads 228

Authors: Mathew O. Ayoola, Foluke Aderemi, Tunde E. Lawal, Opeyemi Oladejo, Micheal A. Abiola

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Food animals reared for meat require transportation during their life cycle. The transportation procedures could initiate stressors capable of disrupting the physiological homeostasis. Such stressors associated with transportation may include; loading and unloading, crowding, environmental temperature, fear, vehicle motion/vibration, feed / water deprivation, and length of travel. This may cause oxidative stress and damage to excess free radicals or reactive oxygen species (ROS). In recent years, the application of natural products as a substitute for synthetic electrolytes and tranquilizers as anti-stress agents during the transportation is yet under investigation. Sweet orange, a predominant fruit in humid tropics, has been reported to have a good content of vitamin C (Ascorbic acid). Vitamin C, which is an active ingredient in orange juice, plays a major role in the biosynthesis of Corticosterone, a hormone that enhances energy supply during transportation and heat stress. Ninety-six, 15weeks, Isa brown pullets were allotted to four (4) oral treatments; sterile water (T1), synthetic vit C (T2), 30ml orange/liter of water (T3), 50ml orange/1 liter (T4). Physiological parameters; body temperature (BTC), rectal temperature (RTC), respiratory rate (RR), and panting rate (PR) were measured pre and post-transportation. The birds were transported with a specialized vehicle for a distance of 50km at a speed of 60 km/hr. The average environmental THI and within the vehicle was 81.8 and 74.6, respectively, and the average wind speed was 11km/hr. Treatments and periods had a significant (p>0.05) effect on all the physiological parameters investigated. Birds on T1 are significantly (p<0.05) different as compared to T2, T3, and T4. Values recorded post-transportation are significantly (p<0.05) higher as compared to pre-transportation for all parameters. In conclusion, this study showed that transportation as a stressor can affect the physiological homeostasis of pullets. Oral supplementation of electrolytes or tranquilizers is essential as an anti-stress during transportation. The application of the organic product in form of sweet orange could serve as a suitable alternative for the synthetic vitamin C.

Keywords: physiological, pullets, sweet orange, transportation stress, and vitamin C

Procedia PDF Downloads 123

Authors: Jamil Khalil Izraqi

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This paper investigates the transition of a 1970 Volkswagen Beetle from an internal combustion engine (ICE) to an EV using Matlab/Simulink modeling and simulation. The performance of the EV drivetrain system was simulated under various operating conditions, including standard and custom driving cycles in Turkey and Jordan (Amman), respectively. The results of this paper indicate that the transition is viable and that modeling and simulation can help in understanding the performance and efficiency of the electric drivetrain system, including battery pack, power electronics, and brushless direct current (BLDC) Motor.

Keywords: BLDC, buck-boost, inverter, SOC, drive-cycle

Procedia PDF Downloads 104

Authors: Abdelkadir Elhaouari

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The priciest thing in human life since his birth is his freedom, basing on this idea, the conflict exists till now, the fight against oppression, injustice, tyranny and slavery, searching for freedom and political resistances, and this makes the freedom is deeply related to the defense for its existence all over years. This project attempts using any way to preserve this freedom, and building and maintaining bases and rules to organize this life. Appeal is a one of the most important method that human uses to protect his freedom, and we will mention in this thesis our attempt to clarify this aspect to the individual. We can say that the law does not know just one color or one logic, and is not based on one rule to be taken by heart, but the law is neutrality, the diversity, abstraction and diligence diversity. The penal law is a valued law and it deserves to be studied and searched more… so that to attempt to master it. Our thesis is just a brief explanation of an important point in this law, where we attempt to clarify and simplify the image to the normal person, so that he can preserve his rights, and we hope that we had succeeded to choose the right topic for that.

Keywords: appeal, penalization, judgement, criminal

Procedia PDF Downloads 285

Authors: Dipanshu Sur, Ratnabali Chakravorty, Rimi Pal, Siddhartha Chatterjee, Joyshree Chaterjee, Amal Mallik

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Background: Polycystic ovary syndrome (PCOS) is a common endocrine disease in reproductive women with a complex hormonal disturbance that affects the menstrual cycle and leads to metabolic consequences in later life. Hyperandrogenaemia is noticeable features of PCOS and influence the process of folliculogenesis in women. The levels of Antimüllerian Hormone (AMH) reflect the number of pre-antral follicles and thus are a marker of oocyte pool – germinal reserve of the ovary for reproduction. Besides its utilization in IVF (In-vitro fertilization), determination of AMH may serve as an additional marker in the diagnostics of PCOS, where increased AMH levels reflect the severity of the disease. The positive correlation of serum AMH with the number of antral follicles was found also in patients with PCOS. Objective: The objective of this study was to investigate the relationship between AMH androgens and whether AMH contributes to altered folliculogenesis in non-obese women with PCOS. Methods: We designed a prospective study which included a total of 65 IVF individuals. It enrolled 26 cases of PCOS based on 2003 Rotterdam criteria and 39 ovulatory normal- non PCOS, healthy, age-matched controls. AMH levels and ovarian morphology were assessed. The relationships between AMH and androgenaemia in patients with and without PCOS were studied. Results: Mean age of PCOS patients were slightly higher than controls (32±4 and 28±3 years, respectively). AMH generally increased with antral follicle count (AFC) [P=0.001], testosterone, and luteinising hormone, and decreased with age, and serum sex hormone binding globulin (SHBG). No significant relationships were found between circulating AMH levels and BMI between PCOS and non-PCOS patients. The calculation of AMH production per antral follicle (AMH/AF) showed that there was a significant difference in median AMH/AF between PCOS and non-PCOS (P =0.001). Both PCOS and non-PCOS groups showed a very similar increase in AMH with increases in AFC, but the PCOS patients had consistently higher AMH across all AFC levels. Conclusions: These observations indicate that there is a connection between AMH and androgens levels between PCOS and non-PCOS East Indian women. Excessive granulosa cell activity may be implicated in the abnormal follicular dynamic of the syndrome. They are higher in women with PCOS and, on the other hand, very low in women with an ovarian failure.

Keywords: anti-Mullerian hormone, polycystic ovary syndrome, antral follicle count, androgens

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Authors: Fatemeh Asadi Farsad, Sima Modirkhameneh

Abstract:

The purpose of this study was to explore the pattern of Psychological Well-Being (PWB) of Iranian male and female EFL teachers during the pandemic. It was intended to see if such a drastic change in the context and mode of teaching affects teachers' PWB. Furthermore, the possible difference between the six elements of PWB of Iranian EFL male vs. female teachers during the pandemic was investigated. The other purpose was to find out the EFL teachers’ perceptions of any modifications, and factors leading to such modifications in their PWB during pandemic. For the purpose of this investigation, a total of 81 EFL teachers (59 female, 22 male) with an age range of 25 to 35 were conveniently sampled from different cities in Iran. Ryff’s PWB questionnaire was sent to participant teachers through online platforms to elicit data on their PWB. As for their perceptions on the possible modifications and the factors involved in PWB during pandemic, a set of semi-structured interviews were run among both sample groups. The findings revealed that male EFL teachers had the highest mean on personal growth, followed by purpose of life, and self-acceptance and the lowest mean on environmental mastery. With a slightly similar pattern, female EFL teachers had the highest mean on personal growth, followed by purpose in life, and positive relationship with others with the lowest mean on environmental mastery. However, no significant difference was observed between the male and female groups’ overall means on elements of PWB. Additionally, participants perceived that their anxiety level in online classes altered due to factors like (1) Computer literacy skills, (2) Lack of social communications and interactions with colleagues and students, (3) Online class management, (4) Overwhelming workloads, and (5) Time management. The study ends with further suggestions as regards effective online teaching preparation considering teachers PWB, especially at severe situations such as covid-19 pandemic. The findings offer to determine the reformations of educational policies concerning enhancing EFL teachers’ PWB through computer literacy courses and stress management courses. It is also suggested that to proactively support teachers’ mental health, it is necessary to provide them with advisors and psychologists if possible for free. Limitations: One limitation is the small number of participants (81), suggesting that future replications should include more participants for reliable findings. Another limitation is the gender imbalance, which future studies should address to yield better outcomes. Furthermore, Limited data gathering tools suggest using observations, diaries, and narratives for more insights in future studies. The study focused on one model of PWB, calling for further research on other models in the literature. Considering the wide effect of the COVID-19 pandemic, future studies should consider additional variables (e.g., teaching experience, age, income) to understand Iranian EFL teachers’ vulnerabilities and strengths better.

Keywords: online teaching, psychological well-being, female and male EFL teachers, pandemic

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Authors: Badli Shah Mohd Yusoff, Khairur Rijal Jamaludin, Rozetta Dollah

Abstract:

The emerging of reverse logistics and product recovery management is an important concept in reconciling economic and environmental objectives through recapturing values of the end of life product returns. End of life products contains valuable modules, parts, residues and materials that can create value if recovered efficiently. The main objective of this study is to explore and develop a model to recover as much of the economic value as reasonably possible to find the optimality of return acquisition and sorting to meet demand and maximize profits over time. In this study, the benefits that can be obtained for remanufacturer is to develop demand forecasting of used products in the future with uncertainty of returns and quality of products. Formulated based on a generic disassembly tree, the proposed model focused on three reverse logistics activity, namely refurbish, remanufacture and disposal incorporating all plausible means quality levels of the returns. While stricter sorting policy, constitute to the decrease amount of products to be refurbished or remanufactured and increases the level of discarded products. Numerical experiments carried out to investigate the characteristics and behaviour of the proposed model with mathematical programming model using Lingo 16.0 for medium-term planning of return acquisition, disassembly (refurbish or remanufacture) and disposal activities. Moreover, the model seeks an analysis a number of decisions relating to trade off management system to maximize revenue from the collection of use products reverse logistics services through refurbish and remanufacture recovery options. The results showed that full utilization in the sorting process leads the system to obtain less quantity from acquisition with minimal overall cost. Further, sensitivity analysis provides a range of possible scenarios to consider in optimizing the overall cost of refurbished and remanufactured products.

Keywords: core acquisition, end of life, reverse logistics, quality uncertainty

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Authors: S. Arpit, P. K. Das, S. K. Dash

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In this paper, a comparative study is done between two fuels, naphtha and natural gas (NG), for a gas turbine (GT) plant of 32.5 MW with the same thermodynamic configuration. From the energy analysis, it is confirmed that the turbine inlet temperature (TIT) of the gas turbine in the case of natural gas is higher as compared to naphtha, and hence the isentropic efficiency of the turbine is better. The result from the exergy analysis also confirms that due to high turbine inlet temperature in the case of natural gas, exergy destruction in combustion chamber is less. But comparing two fuels for overall analysis, naphtha has higher energy and exergetic efficiency as compared to natural gas.

Keywords: exergy analysis, gas turbine, naphtha, natural gas

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Authors: C. Xavier Mendieta, J. J McArthur

Abstract:

Governments are playing an increasingly active role in reducing carbon emissions, and a key strategy has been the introduction of mandatory energy disclosure policies. These policies have resulted in a significant amount of publicly available data, providing researchers with a unique opportunity to develop location-specific energy and carbon emission benchmarks from this data set, which can then be used to develop building archetypes and used to inform urban energy models. This study presents the development of such a benchmark using the public reporting data. The data from Ontario’s Ministry of Energy for Post-Secondary Educational Institutions are being used to develop a series of building archetype dynamic building loads and energy benchmarks to fill a gap in the currently available building database. This paper presents the development of a benchmark for college and university residences within ASHRAE climate zone 6 areas in Ontario using the mandatory disclosure energy and greenhouse gas emissions data. The methodology presented includes data cleaning, statistical analysis, and benchmark development, and lessons learned from this investigation are presented and discussed to inform the development of future energy benchmarks from this larger data set. The key findings from this initial benchmarking study are: (1) the importance of careful data screening and outlier identification to develop a valid dataset; (2) the key features used to develop a model of the data are building age, size, and occupancy schedules and these can be used to estimate energy consumption; and (3) policy changes affecting the primary energy generation significantly affected greenhouse gas emissions, and consideration of these factors was critical to evaluate the validity of the reported data.

Keywords: building archetypes, data analysis, energy benchmarks, GHG emissions

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Authors: R. Hellmuth

Abstract:

The method of factory planning has changed a lot, especially when it is about planning the factory building itself. Factory planning has the task of designing products, plants, processes, organization, areas, and the building of a factory. Regular restructuring is becoming more important in order to maintain the competitiveness of a factory. Restrictions in new areas, shorter life cycles of product and production technology as well as a VUCA world (Volatility, Uncertainty, Complexity and Ambiguity) lead to more frequent restructuring measures within a factory. A digital factory model is the planning basis for rebuilding measures and becomes an indispensable tool. Furthermore, digital building models are increasingly being used in factories to support facility management and manufacturing processes. The main research question of this paper is, therefore: What kind of digital factory model is suitable for the different areas of application during the operation of a factory? First, different types of digital factory models are investigated, and their properties and usabilities for use cases are analysed. Within the scope of investigation are point cloud models, building information models, photogrammetry models, and these enriched with sensor data are examined. It is investigated which digital models allow a simple integration of sensor data and where the differences are. Subsequently, possible application areas of digital factory models are determined by means of a survey and the respective digital factory models are assigned to the application areas. Finally, an application case from maintenance is selected and implemented with the help of the appropriate digital factory model. It is shown how a completely digitalized maintenance process can be supported by a digital factory model by providing information. Among other purposes, the digital factory model is used for indoor navigation, information provision, and display of sensor data. In summary, the paper shows a structuring of digital factory models that concentrates on the geometric representation of a factory building and its technical facilities. A practical application case is shown and implemented. Thus, the systematic selection of digital factory models with the corresponding application cases is evaluated.

Keywords: building information modeling, digital factory model, factory planning, maintenance

Procedia PDF Downloads 114