Search results for: neighbor based key sharing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 28190

Search results for: neighbor based key sharing

27800 The Relations between Language Diversity and Similarity and Adults' Collaborative Creative Problem Solving

Authors: Z. M. T. Lim, W. Q. Yow

Abstract:

Diversity in individual problem-solving approaches, culture and nationality have been shown to have positive effects on collaborative creative processes in organizational and scholastic settings. For example, diverse graduate and organizational teams consisting of members with both structured and unstructured problem-solving styles were found to have more creative ideas on a collaborative idea generation task than teams that comprised solely of members with either structured or unstructured problem-solving styles. However, being different may not always provide benefits to the collaborative creative process. In particular, speaking different languages may hinder mutual engagement through impaired communication and thus collaboration. Instead, sharing similar languages may have facilitative effects on mutual engagement in collaborative tasks. However, no studies have explored the relations between language diversity and adults’ collaborative creative problem solving. Sixty-four Singaporean English-speaking bilingual undergraduates were paired up into similar or dissimilar language pairs based on the second language they spoke (e.g., for similar language pairs, both participants spoke English-Mandarin; for dissimilar language pairs, one participant spoke English-Mandarin and the other spoke English-Korean). Each participant completed the Ravens Progressive Matrices Task individually. Next, they worked in pairs to complete a collaborative divergent thinking task where they used mind-mapping techniques to brainstorm ideas on a given problem together (e.g., how to keep insects out of the house). Lastly, the pairs worked on a collaborative insight problem-solving task (Triangle of Coins puzzle) where they needed to flip a triangle of ten coins around by moving only three coins. Pairs who had prior knowledge of the Triangle of Coins puzzle were asked to complete an equivalent Matchstick task instead, where they needed to make seven squares by moving only two matchsticks based on a given array of matchsticks. Results showed that, after controlling for intelligence, similar language pairs completed the collaborative insight problem-solving task faster than dissimilar language pairs. Intelligence also moderated these relations. Among adults of lower intelligence, similar language pairs solved the insight problem-solving task faster than dissimilar language pairs. These differences in speed were not found in adults with higher intelligence. No differences were found in the number of ideas generated in the collaborative divergent thinking task between similar language and dissimilar language pairs. In conclusion, sharing similar languages seem to enrich collaborative creative processes. These effects were especially pertinent to pairs with lower intelligence. This provides guidelines for the formation of groups based on shared languages in collaborative creative processes. However, the positive effects of shared languages appear to be limited to the insight problem-solving task and not the divergent thinking task. This could be due to the facilitative effects of other factors of diversity as found in previous literature. Background diversity, for example, may have a larger facilitative effect on the divergent thinking task as compared to the insight problem-solving task due to the varied experiences individuals bring to the task. In conclusion, this study contributes to the understanding of the effects of language diversity in collaborative creative processes and challenges the general positive effects that diversity has on these processes.

Keywords: bilingualism, diversity, creativity, collaboration

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27799 Distributive Justice through Constitution

Authors: Rohtash

Abstract:

Academically, the concept of Justice in the literature is vast, and theories are voluminous and definitions are numerous but it is very difficult to define. Through the ages, justice has been evolving and developing reasoning that how individuals and communities do the right thing that is just and fair to all in that society. Justice is a relative and dynamic concept, not absolute one. It is different in different societies based on their morality and ethics. The idea of justice cannot arise from a single morality but interaction of competing moralities and contending perspectives. Justice is the conditional and circumstantial term. Therefore, justice takes different meanings in different contexts. Justice is the application of the Laws. It is a values-based concept in order to protect the rights and liberties of the people. It is a socially created concept that has no physical reality. It exists in society on the basis of the spirit of sharing by the communities and members of society. The conception of justice in society or among communities and individuals is based on their social coordination. It can be effective only when people’s judgments are based on collective reasoning. Their behavior is shaped by social values, norms and laws. People must accept, share and respect the set of principles for delivering justice. Thus justice can be a reasonable solution to conflicts and to coordinate behavior in society. The subject matter of distributive justice is the Public Good and societal resources that should be evenly distributed among the different sections of society on the principles developed and established by the State through legislation, public policy and Executive orders. The Socioeconomic transformation of the society is adopted by the constitution within the limit of its morality and gives a new dimension to transformative justice. Therefore, both Procedural and Transformative justice is part of Distributive justice. Distributive justice is purely an economic phenomenon. It concerns the allocation of resources among the communities and individuals. The subject matter of distributive justice is the distribution of rights, responsibilities, burdens and benefits in society on the basis of the capacity and capability of individuals.

Keywords: distributive justice, constitutionalism, institutionalism, constitutional morality

Procedia PDF Downloads 56
27798 Nucleotide Diversity and Bacterial Endosymbionts of the Black Cherry Aphid Myzus cerasi (Fabricus, 1775) (Hemiptera: Aphididae) from Turkey

Authors: Burcu Inal, Irfan Kandemir

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Sequences of mitochondrial cytochrome oxidase I (COI) gene of twenty-five Turkish and one Greek Myzus cerasi (Fabricus) (Hemiptera: Aphididae) in populations were collected from Prunus avium and Prunus cerasus. The partial coding region of COI studied is 605 bp for all the populations, from which 565 nucleotides were conserved, 40 were variable, 37 were singleton, and 3 sites were parsimony-informative. Four haplotypes were identified based on nucleotide substitutions, and the mean of intraspecific divergence was calculated to be 0.3%. Phylogenetic trees were constructed using Maximum Likelihood, Minimum Evolution, Neighbor-joining, and Unweighed Pair Group Method of Arithmetic Averages (UPGMA) and Myzus persicae (Sulzer) and Myzus borealis Ossiannilson were included as outgroups. The population of M. cerasi from Isparta diverged from the rest of the groups and formed a clade (Haplotype B) with Myzus borealis. The rest of the haplotype diversity includes Haplotype A and Haplotype C with individuals characterized as Myzus cerasi pruniavium and Haplotype D with Myzus cerasi cerasi. M. cerasi diverge into two subspecies and it must be reevaluated whether this pest is monophagous or oligophagous in terms of plant type dependence. The obligated endosymbiont Buchnera aphidicola was also found during this research, but no facultative symbionts could be found. It is expected further studies will be required for a complete barcoding and diversity of bacterial endosymbionts present.

Keywords: bacterial endosymbionts, barcoding, black cherry aphid, nucleotide diversity

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27797 Using Scale Invariant Feature Transform Features to Recognize Characters in Natural Scene Images

Authors: Belaynesh Chekol, Numan Çelebi

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The main purpose of this work is to recognize individual characters extracted from natural scene images using scale invariant feature transform (SIFT) features as an input to K-nearest neighbor (KNN); a classification learner algorithm. For this task, 1,068 and 78 images of English alphabet characters taken from Chars74k data set is used to train and test the classifier respectively. For each character image, We have generated describing features by using SIFT algorithm. This set of features is fed to the learner so that it can recognize and label new images of English characters. Two types of KNN (fine KNN and weighted KNN) were trained and the resulted classification accuracy is 56.9% and 56.5% respectively. The training time taken was the same for both fine and weighted KNN.

Keywords: character recognition, KNN, natural scene image, SIFT

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27796 Application of Blockchain Technology in Geological Field

Authors: Mengdi Zhang, Zhenji Gao, Ning Kang, Rongmei Liu

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Management and application of geological big data is an important part of China's national big data strategy. With the implementation of a national big data strategy, geological big data management becomes more and more critical. At present, there are still a lot of technology barriers as well as cognition chaos in many aspects of geological big data management and application, such as data sharing, intellectual property protection, and application technology. Therefore, it’s a key task to make better use of new technologies for deeper delving and wider application of geological big data. In this paper, we briefly introduce the basic principle of blockchain technology at the beginning and then make an analysis of the application dilemma of geological data. Based on the current analysis, we bring forward some feasible patterns and scenarios for the blockchain application in geological big data and put forward serval suggestions for future work in geological big data management.

Keywords: blockchain, intellectual property protection, geological data, big data management

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27795 Assessing Student Collaboration in Music Ensemble Class: From the Formulation of Grading Rubrics to Their Effective Implementation

Authors: Jason Sah

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Music ensemble class is a non-traditional classroom in the sense that it is always a group effort during rehearsal. When measuring student performance ability in class, it is imperative that the grading rubric includes a collaborative skill component. Assessments that stop short of testing students' ability to make music with others undermine the group mentality by elevating individual prowess. Applying empirical and evidence-based methodology, this research develops a grading rubric that defines the criteria for assessing collaborative skill, and then explores different strategies for implementing this rubric in a timely and effective manner. Findings show that when collaborative skill is regularly tested, students gradually shift their attention from playing their own part well to sharing their part with others.

Keywords: assessment, ensemble class, grading rubric, student collaboration

Procedia PDF Downloads 114
27794 Volunteered Geographic Information Coupled with Wildfire Fire Progression Maps: A Spatial and Temporal Tool for Incident Storytelling

Authors: Cassandra Hansen, Paul Doherty, Chris Ferner, German Whitley, Holly Torpey

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Wildfire is a natural and inevitable occurrence, yet changing climatic conditions have increased the severity, frequency, and risk to human populations in the wildland/urban interface (WUI) of the Western United States. Rapid dissemination of accurate wildfire information is critical to both the Incident Management Team (IMT) and the affected community. With the advent of increasingly sophisticated information systems, GIS can now be used as a web platform for sharing geographic information in new and innovative ways, such as virtual story map applications. Crowdsourced information can be extraordinarily useful when coupled with authoritative information. Information abounds in the form of social media, emergency alerts, radio, and news outlets, yet many of these resources lack a spatial component when first distributed. In this study, we describe how twenty-eight volunteer GIS professionals across nine Geographic Area Coordination Centers (GACC) sourced, curated, and distributed Volunteered Geographic Information (VGI) from authoritative social media accounts focused on disseminating information about wildfires and public safety. The combination of fire progression maps with VGI incident information helps answer three critical questions about an incident, such as: where the first started. How and why the fire behaved in an extreme manner and how we can learn from the fire incident's story to respond and prepare for future fires in this area. By adding a spatial component to that shared information, this team has been able to visualize shared information about wildfire starts in an interactive map that answers three critical questions in a more intuitive way. Additionally, long-term social and technical impacts on communities are examined in relation to situational awareness of the disaster through map layers and agency links, the number of views in a particular region of a disaster, community involvement and sharing of this critical resource. Combined with a GIS platform and disaster VGI applications, this workflow and information become invaluable to communities within the WUI and bring spatial awareness for disaster preparedness, response, mitigation, and recovery. This study highlights progression maps as the ultimate storytelling mechanism through incident case studies and demonstrates the impact of VGI and sophisticated applied cartographic methodology make this an indispensable resource for authoritative information sharing.

Keywords: storytelling, wildfire progression maps, volunteered geographic information, spatial and temporal

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27793 Knowledge Transfer among Cross-Functional Teams as a Continual Improvement Process

Authors: Sergio Mauricio Pérez López, Luis Rodrigo Valencia Pérez, Juan Manuel Peña Aguilar, Adelina Morita Alexander

Abstract:

The culture of continuous improvement in organizations is very important as it represents a source of competitive advantage. This article discusses the transfer of knowledge between companies which formed cross-functional teams and used a dynamic model for knowledge creation as a framework. In addition, the article discusses the structure of cognitive assets in companies and the concept of "stickiness" (which is defined as an obstacle to the transfer of knowledge). The purpose of this analysis is to show that an improvement in the attitude of individual members of an organization creates opportunities, and that an exchange of information and knowledge leads to generating continuous improvements in the company as a whole. This article also discusses the importance of creating the proper conditions for sharing tacit knowledge. By narrowing gaps between people, mutual trust can be created and thus contribute to an increase in sharing. The concept of adapting knowledge to new environments will be highlighted, as it is essential for companies to translate and modify information so that such information can fit the context of receiving organizations. Adaptation will ensure that the transfer process is carried out smoothly by preventing "stickiness". When developing the transfer process on cross-functional teams (as opposed to working groups), the team acquires the flexibility and responsiveness necessary to meet objectives. These types of cross-functional teams also generate synergy due to the array of different work backgrounds of their individuals. When synergy is established, a culture of continuous improvement is created.

Keywords: knowledge transfer, continuous improvement, teamwork, cognitive assets

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27792 An Integrated Approach of Islamic Social Financing for Achieving Sustainable Development Goals (SDGS) Through Crowdfunding: A Model for Sharing Economy for Community Development in Bangladesh

Authors: Md. Abu Yousuf

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Islamic social financing (ISF) refers to the fair distribution of wealth and financial dealings and prevents economic exploitation at all levels. ISF instruments include Islamic institutions Zakat (obligatory charity), Sadaqah (voluntary charity) and Waqf (endowment) based on philanthropy such and Qard-al Hasan (beautiful loan), micro takaful (insurance) and social investments through Sukuk (bonds) based on cooperation. ISF contributes to socio-economic development, end poverty, protects environmental sustainability, promotes education, equality, social justice and above all, establishes social well-being since the birth of Islam. ISF tools are instrumental towards achieving sustainable development goals (SDGs) set by United Nations (UN). The present study will explore the scope of ISF for community development in Bangladesh and examine the challenges in implementing ISF tools and will provide the most practical model of ISF. The study will adopt a mixed-method (MM) design in the process of data collection and analysis. The researcher will consider all issues related to ethics, reliability, validity and feasibility while conducting the study.

Keywords: Islamic social financing, sustainable development goals, poverty eradication, zakat, waqf, sadaqah, Islamic microfinance

Procedia PDF Downloads 159
27791 Low Overhead Dynamic Channel Selection with Cluster-Based Spatial-Temporal Station Reporting in Wireless Networks

Authors: Zeyad Abdelmageid, Xianbin Wang

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Choosing the operational channel for a WLAN access point (AP) in WLAN networks has been a static channel assignment process initiated by the user during the deployment process of the AP, which fails to cope with the dynamic conditions of the assigned channel at the station side afterward. However, the dramatically growing number of Wi-Fi APs and stations operating in the unlicensed band has led to dynamic, distributed, and often severe interference. This highlights the urgent need for the AP to dynamically select the best overall channel of operation for the basic service set (BSS) by considering the distributed and changing channel conditions at all stations. Consequently, dynamic channel selection algorithms which consider feedback from the station side have been developed. Despite the significant performance improvement, existing channel selection algorithms suffer from very high feedback overhead. Feedback latency from the STAs, due to the high overhead, can cause the eventually selected channel to no longer be optimal for operation due to the dynamic sharing nature of the unlicensed band. This has inspired us to develop our own dynamic channel selection algorithm with reduced overhead through the proposed low-overhead, cluster-based station reporting mechanism. The main idea behind the cluster-based station reporting is the observation that STAs which are very close to each other tend to have very similar channel conditions. Instead of requesting each STA to report on every candidate channel while causing high overhead, the AP divides STAs into clusters then assigns each STA in each cluster one channel to report feedback on. With the proper design of the cluster based reporting, the AP does not lose any information about the channel conditions at the station side while reducing feedback overhead. The simulation results show equal performance and, at times, better performance with a fraction of the overhead. We believe that this algorithm has great potential in designing future dynamic channel selection algorithms with low overhead.

Keywords: channel assignment, Wi-Fi networks, clustering, DBSCAN, overhead

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27790 Balancing Biodiversity and Agriculture: A Broad-Scale Analysis of the Land Sparing/Land Sharing Trade-Off for South African Birds

Authors: Chevonne Reynolds, Res Altwegg, Andrew Balmford, Claire N. Spottiswoode

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Modern agriculture has revolutionised the planet’s capacity to support humans, yet has simultaneously had a greater negative impact on biodiversity than any other human activity. Balancing the demand for food with the conservation of biodiversity is one of the most pressing issues of our time. Biodiversity-friendly farming (‘land sharing’), or alternatively, separation of conservation and production activities (‘land sparing’), are proposed as two strategies for mediating the trade-off between agriculture and biodiversity. However, there is much debate regarding the efficacy of each strategy, as this trade-off has typically been addressed by short term studies at fine spatial scales. These studies ignore processes that are relevant to biodiversity at larger scales, such as meta-population dynamics and landscape connectivity. Therefore, to better understand species response to agricultural land-use and provide evidence to underpin the planning of better production landscapes, we need to determine the merits of each strategy at larger scales. In South Africa, a remarkable citizen science project - the South African Bird Atlas Project 2 (SABAP2) – collates an extensive dataset describing the occurrence of birds at a 5-min by 5-min grid cell resolution. We use these data, along with fine-resolution data on agricultural land-use, to determine which strategy optimises the agriculture-biodiversity trade-off in a southern African context, and at a spatial scale never considered before. To empirically test this trade-off, we model bird species population density, derived for each 5-min grid cell by Royle-Nicols single-species occupancy modelling, against both the amount and configuration of different types of agricultural production in the same 5-min grid cell. In using both production amount and configuration, we can show not only how species population densities react to changes in yield, but also describe the production landscape patterns most conducive to conservation. Furthermore, the extent of both the SABAP2 and land-cover datasets allows us to test this trade-off across multiple regions to determine if bird populations respond in a consistent way and whether results can be extrapolated to other landscapes. We tested the land sparing/sharing trade-off for 281 bird species across three different biomes in South Africa. Overall, a higher proportion of species are classified as losers, and would benefit from land sparing. However, this proportion of loser-sparers is not consistent and varies across biomes and the different types of agricultural production. This is most likely because of differences in the intensity of agricultural land-use and the interactions between the differing types of natural vegetation and agriculture. Interestingly, we observe a higher number of species that benefit from agriculture than anticipated, suggesting that agriculture is a legitimate resource for certain bird species. Our results support those seen at smaller scales and across vastly different agricultural systems, that land sparing benefits the most species. However, our analysis suggests that land sparing needs to be implemented at spatial scales much larger than previously considered. Species persistence in agricultural landscapes will require the conservation of large tracts of land, and is an important consideration in developing countries, which are undergoing rapid agricultural development.

Keywords: agriculture, birds, land sharing, land sparing

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27789 Methods and Algorithms of Ensuring Data Privacy in AI-Based Healthcare Systems and Technologies

Authors: Omar Farshad Jeelani, Makaire Njie, Viktoriia M. Korzhuk

Abstract:

Recently, the application of AI-powered algorithms in healthcare continues to flourish. Particularly, access to healthcare information, including patient health history, diagnostic data, and PII (Personally Identifiable Information) is paramount in the delivery of efficient patient outcomes. However, as the exchange of healthcare information between patients and healthcare providers through AI-powered solutions increases, protecting a person’s information and their privacy has become even more important. Arguably, the increased adoption of healthcare AI has resulted in a significant concentration on the security risks and protection measures to the security and privacy of healthcare data, leading to escalated analyses and enforcement. Since these challenges are brought by the use of AI-based healthcare solutions to manage healthcare data, AI-based data protection measures are used to resolve the underlying problems. Consequently, this project proposes AI-powered safeguards and policies/laws to protect the privacy of healthcare data. The project presents the best-in-school techniques used to preserve the data privacy of AI-powered healthcare applications. Popular privacy-protecting methods like Federated learning, cryptographic techniques, differential privacy methods, and hybrid methods are discussed together with potential cyber threats, data security concerns, and prospects. Also, the project discusses some of the relevant data security acts/laws that govern the collection, storage, and processing of healthcare data to guarantee owners’ privacy is preserved. This inquiry discusses various gaps and uncertainties associated with healthcare AI data collection procedures and identifies potential correction/mitigation measures.

Keywords: data privacy, artificial intelligence (AI), healthcare AI, data sharing, healthcare organizations (HCOs)

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27788 Artificial Bee Colony Optimization for SNR Maximization through Relay Selection in Underlay Cognitive Radio Networks

Authors: Babar Sultan, Kiran Sultan, Waseem Khan, Ijaz Mansoor Qureshi

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In this paper, a novel idea for the performance enhancement of secondary network is proposed for Underlay Cognitive Radio Networks (CRNs). In Underlay CRNs, primary users (PUs) impose strict interference constraints on the secondary users (SUs). The proposed scheme is based on Artificial Bee Colony (ABC) optimization for relay selection and power allocation to handle the highlighted primary challenge of Underlay CRNs. ABC is a simple, population-based optimization algorithm which attains global optimum solution by combining local search methods (Employed and Onlooker Bees) and global search methods (Scout Bees). The proposed two-phase relay selection and power allocation algorithm aims to maximize the signal-to-noise ratio (SNR) at the destination while operating in an underlying mode. The proposed algorithm has less computational complexity and its performance is verified through simulation results for a different number of potential relays, different interference threshold levels and different transmit power thresholds for the selected relays.

Keywords: artificial bee colony, underlay spectrum sharing, cognitive radio networks, amplify-and-forward

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27787 Development of the Academic Model to Predict Student Success at VUT-FSASEC Using Decision Trees

Authors: Langa Hendrick Musawenkosi, Twala Bhekisipho

Abstract:

The success or failure of students is a concern for every academic institution, college, university, governments and students themselves. Several approaches have been researched to address this concern. In this paper, a view is held that when a student enters a university or college or an academic institution, he or she enters an academic environment. The academic environment is unique concept used to develop the solution for making predictions effectively. This paper presents a model to determine the propensity of a student to succeed or fail in the French South African Schneider Electric Education Center (FSASEC) at the Vaal University of Technology (VUT). The Decision Tree algorithm is used to implement the model at FSASEC.

Keywords: FSASEC, academic environment model, decision trees, k-nearest neighbor, machine learning, popularity index, support vector machine

Procedia PDF Downloads 183
27786 The Adoption and Use of Social Media as a Source of Information by Egyptian Government Journalists

Authors: Essam Mansour

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This study purposes to explore the adoption and use of social media as a source of information by Egyptian government journalists. It applied a survey with a total of 386 journalists representing the three official newspapers of Egypt. Findings showed that 27.2% of journalists were found to not use social media, mainly males (69.7%), older than 40 years (77.7%) and mostly with a BA degree (80.4%). On the other hand, 72.8% of them were found to use these platforms who were also males (59.1%), younger than 40 years (65.9%) and mostly with a BA degree (93.2%). More than two-thirds (69.9%) were somewhat old users whose experience ranged from seven to ten years, and more than two-thirds (73.5%) have been heavily using these platforms (four to more than six hours a day. Such results confirm that a large number (95.7%) of users were found to be at least advanced users. Social media users’ home and work were the most significant places to access these platforms, which were found to be easy and useful to use. Most types of social media used were social news, media sharing and micro blogging, blogs comments and forums, social networking sites and bookmarking sites to perform tasks, such as finding information, making communication, keeping up to date, checking materials, sharing information and making discussions. A large number of users tend to accept these media platforms to be a source of information since they are accessible, linked references updated sources, accurate, promote current work, convenient, secured, credible, reliable, stabled, easily identified, copyrighted, build confident and contain filtered information. However, lack of know-how to cite sources, followed by lack of credibility of the source of news, lack of quality of information sources and lack of time were at least significant to journalists when using social media platforms.

Keywords: social media, social networking sites, newspapers, journalists, Egypt

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27785 The Gender Dialectic in Mothers and Daughters’ Relationships

Authors: Ronit Even Zahav

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Objectives: Mother-daughter relationships are often portrayed as one of the most constitutive ties that shape women's identities throughout their lives. Yet, to the best of author’s knowledge, only few studies examine mother-daughter relationships in adulthood in the context of cross-cultural transition. Most of them focus on the mother-daughter relationship among one origin group. Hence, the existing knowledge about these relationships in adulthood, in the context of intercultural transition and encounters between different cultures, remain limited. Based on a critical feminist approach critical and cultural perspectives the current study focuses on a cross-cultural comparison of adult mother-daughter relationships among three groups of origin: Ethiopia, Russia, and Israel. The study aimed to: Explore the voices of women participating in a mother-daughter discourse in the context of gender and ethnicity; examine the differences in the mother-daughter relationship through number of factors (e.g. expectations of similarity and difference, perceptions of gender roles, gender identity, emotional closeness, sharing and stress) and finally, to develop a gender informed tool for understanding the gender dialectic in mother-daughter relationship in the context of cross cultural transitions. Method: 37 dyads of mothers and adult daughters participated in a qualitative study. A semi-structured interview was conducted that included questions about socio-demographic characteristics, language proficiency, social distance, closeness, emotional stress, and expectations of similarity and difference in mother-daughter relationships. Results: Analysis of the findings yielded three relationship patterns of gender dialectic and expectations of similarity and difference that characterize the groups of origin. Ethiopian mothers reported more sharing their daughters, fewer expectations of similarity, and felt more stress in the relationship compered to women from the two other origin groups. Conclusions: The study highlighted the impact of intercultural transition and social exclusion on mother-daughter relationships in adulthood in the context of the gender dialectic and women’s status in society. The presentation will explore the findings that were brought up by participants. The discussion will focus on the practices related to gender dialectic and intersecting inequalities regarding diverse groups and discuss gender development reducing inequalities and promoting empowerment to transform oppressive conditions.

Keywords: gender informed perspectives, gender dialectic, mother-daughter relationships, multiculturalism

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27784 The Utilization of Big Data in Knowledge Management Creation

Authors: Daniel Brian Thompson, Subarmaniam Kannan

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The huge weightage of knowledge in this world and within the repository of organizations has already reached immense capacity and is constantly increasing as time goes by. To accommodate these constraints, Big Data implementation and algorithms are utilized to obtain new or enhanced knowledge for decision-making. With the transition from data to knowledge provides the transformational changes which will provide tangible benefits to the individual implementing these practices. Today, various organization would derive knowledge from observations and intuitions where this information or data will be translated into best practices for knowledge acquisition, generation and sharing. Through the widespread usage of Big Data, the main intention is to provide information that has been cleaned and analyzed to nurture tangible insights for an organization to apply to their knowledge-creation practices based on facts and figures. The translation of data into knowledge will generate value for an organization to make decisive decisions to proceed with the transition of best practices. Without a strong foundation of knowledge and Big Data, businesses are not able to grow and be enhanced within the competitive environment.

Keywords: big data, knowledge management, data driven, knowledge creation

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27783 Intrusion Detection in Cloud Computing Using Machine Learning

Authors: Faiza Babur Khan, Sohail Asghar

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With an emergence of distributed environment, cloud computing is proving to be the most stimulating computing paradigm shift in computer technology, resulting in spectacular expansion in IT industry. Many companies have augmented their technical infrastructure by adopting cloud resource sharing architecture. Cloud computing has opened doors to unlimited opportunities from application to platform availability, expandable storage and provision of computing environment. However, from a security viewpoint, an added risk level is introduced from clouds, weakening the protection mechanisms, and hardening the availability of privacy, data security and on demand service. Issues of trust, confidentiality, and integrity are elevated due to multitenant resource sharing architecture of cloud. Trust or reliability of cloud refers to its capability of providing the needed services precisely and unfailingly. Confidentiality is the ability of the architecture to ensure authorization of the relevant party to access its private data. It also guarantees integrity to protect the data from being fabricated by an unauthorized user. So in order to assure provision of secured cloud, a roadmap or model is obligatory to analyze a security problem, design mitigation strategies, and evaluate solutions. The aim of the paper is twofold; first to enlighten the factors which make cloud security critical along with alleviation strategies and secondly to propose an intrusion detection model that identifies the attackers in a preventive way using machine learning Random Forest classifier with an accuracy of 99.8%. This model uses less number of features. A comparison with other classifiers is also presented.

Keywords: cloud security, threats, machine learning, random forest, classification

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27782 The Cloud Systems Used in Education: Properties and Overview

Authors: Agah Tuğrul Korucu, Handan Atun

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Diversity and usefulness of information that used in education are have increased due to development of technology. Web technologies have made enormous contributions to the distance learning system especially. Mobile systems, one of the most widely used technology in distance education, made much easier to access web technologies. Not bounding by space and time, individuals have had the opportunity to access the information on web. In addition to this, the storage of educational information and resources and accessing these information and resources is crucial for both students and teachers. Because of this importance, development and dissemination of web technologies supply ease of access to information and resources are provided by web technologies. Dynamic web technologies introduced as new technologies that enable sharing and reuse of information, resource or applications via the Internet and bring websites into expandable platforms are commonly known as Web 2.0 technologies. Cloud systems are one of the dynamic web technologies that defined as a model provides approaching the demanded information independent from time and space in appropriate circumstances and developed by NIST. One of the most important advantages of cloud systems is meeting the requirements of users directly on the web regardless of hardware, software, and dealing with install. Hence, this study aims at using cloud services in education and investigating the services provided by the cloud computing. Survey method has been used as research method. In the findings of this research the fact that cloud systems are used such studies as resource sharing, collaborative work, assignment submission and feedback, developing project in the field of education, and also, it is revealed that cloud systems have plenty of significant advantages in terms of facilitating teaching activities and the interaction between teacher, student and environment.

Keywords: cloud systems, cloud systems in education, online learning environment, integration of information technologies, e-learning, distance learning

Procedia PDF Downloads 325
27781 Knowledge Management Barriers: A Statistical Study of Hardware Development Engineering Teams within Restricted Environments

Authors: Nicholas S. Norbert Jr., John E. Bischoff, Christopher J. Willy

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Knowledge Management (KM) is globally recognized as a crucial element in securing competitive advantage through building and maintaining organizational memory, codifying and protecting intellectual capital and business intelligence, and providing mechanisms for collaboration and innovation. KM frameworks and approaches have been developed and defined identifying critical success factors for conducting KM within numerous industries ranging from scientific to business, and for ranges of organization scales from small groups to large enterprises. However, engineering and technical teams operating within restricted environments are subject to unique barriers and KM challenges which cannot be directly treated using the approaches and tools prescribed for other industries. This research identifies barriers in conducting KM within Hardware Development Engineering (HDE) teams and statistically compares significance to barriers upholding the four KM pillars of organization, technology, leadership, and learning for HDE teams. HDE teams suffer from restrictions in knowledge sharing (KS) due to classification of information (national security risks), customer proprietary restrictions (non-disclosure agreement execution for designs), types of knowledge, complexity of knowledge to be shared, and knowledge seeker expertise. As KM evolved leveraging information technology (IT) and web-based tools and approaches from Web 1.0 to Enterprise 2.0, KM may also seek to leverage emergent tools and analytics including expert locators and hybrid recommender systems to enable KS across barriers of the technical teams. The research will test hypothesis statistically evaluating if KM barriers for HDE teams affect the general set of expected benefits of a KM System identified through previous research. If correlations may be identified, then generalizations of success factors and approaches may also be garnered for HDE teams. Expert elicitation will be conducted using a questionnaire hosted on the internet and delivered to a panel of experts including engineering managers, principal and lead engineers, senior systems engineers, and knowledge management experts. The feedback to the questionnaire will be processed using analysis of variance (ANOVA) to identify and rank statistically significant barriers of HDE teams within the four KM pillars. Subsequently, KM approaches will be recommended for upholding the KM pillars within restricted environments of HDE teams.

Keywords: engineering management, knowledge barriers, knowledge management, knowledge sharing

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27780 The Trend of Competitive Balance in Turkish Football Super League

Authors: Tugbay Inan

Abstract:

Competitive balance is known to have an important effect in determining the result of football matches. The degree of competitiveness is referred as competitive balance in football. Sports economics are the extent to which overall league attendances will be raised by measures, such as media effect, home advantage, revenue sharing, which aim to improve competitive balance. The purpose of present study was to measure the competitive balance in the football league of Turkey. In this study, by using long term competitive balance analysis, some facing problems and precautions were discussed through the seasons (1987-2014) in Turkish Football Super League (TSL). Within the practice of this study, The way that competitive balance level followed was determined in the history of super league (27 years). Based on this purpose, C5 Competitive Balance Index (C5CBI) and a Herfindahl index of competitive balance (HICB) were used. Finally, it is seen that in Super League, competitive balance factor took place time to time, however in total, a view apart from competitive balance is obviously seen.

Keywords: competitive balance, turkish football, c5 competitive balance index, Herfindahl-Hirschman Index

Procedia PDF Downloads 537
27779 An Early Detection Type 2 Diabetes Using K - Nearest Neighbor Algorithm

Authors: Ng Liang Shen, Ngahzaifa Abdul Ghani

Abstract:

This research aimed at developing an early warning system for pre-diabetic and diabetics by analyzing simple and easily determinable signs and symptoms of diabetes among the people living in Malaysia using Particle Swarm Optimized Artificial. With the skyrocketing prevalence of Type 2 diabetes in Malaysia, the system can be used to encourage affected people to seek further medical attention to prevent the onset of diabetes or start managing it early enough to avoid the associated complications. The study sought to find out the best predictive variables of Type 2 Diabetes Mellitus, developed a system to diagnose diabetes from the variables using Artificial Neural Networks and tested the system on accuracy to find out the patent generated from diabetes diagnosis result in machine learning algorithms even at primary or advanced stages.

Keywords: diabetes diagnosis, Artificial Neural Networks, artificial intelligence, soft computing, medical diagnosis

Procedia PDF Downloads 310
27778 Podcasting as an Instructional Method: Case Study of a School Psychology Class

Authors: Jeff A. Tysinger, Dawn P. Tysinger

Abstract:

There has been considerable growth in online learning. Researchers continue to explore the impact various methods of delivery. Podcasting is a popular method for sharing information. The purpose of this study was to examine the impact of student motivation and the perception of the acquisition of knowledge in an online environment of a skill-based class. 25 students in a school psychology graduate class completed a pretest and posttest examining podcast use and familiarity. In addition, at the completion of the course they were administered a modified version of the Instructional Materials Motivation Survey. The four subscales were examined (attention, relevance, confidence, and satisfaction). Results indicated that students are motivated, they perceive podcasts as positive instructional tools, and students are successful in acquiring the needed information. Additional benefits of using podcasts and recommendations in school psychology training are discussed.

Keywords: motivation, online learning, pedagogy, podcast

Procedia PDF Downloads 113
27777 Legacy of Smart Cities on Urban Future: Discussing the Future of Smart City by Sharing Its Experiences

Authors: Arsalan Makinian

Abstract:

Our future cities will constantly evolve the necessary technologies for tomorrow’s needs. Technologies which enable a better kind of prosperity and security. This paper reports on the precedent of a smart city from its beginning to prevalence among urbanism academic literature and reports of tech companies. The article aims to direct urban foresight studies and to build a pathway for the future of smart city concept by gathering theoretical and empirical experiences related to smart cities with both top-down and bottom-up approaches. It hopes to deliver results of different studies, pilot projects, and development strategies of some of the smart cities in order to allow a shareable knowledge to take shape and develop in terms of qualitative aspects of a smart city. Now the definition of the smart city goes beyond removing physical boundaries, changing the concept of mobility and providing electronic service for citizens, it now constitutes fields such as energy efficiency, economic competitiveness, protecting the environment and finally, it takes advantage of technology and data science to improve the quality of life. In the smart city, the role of citizens is considered as both final purpose and contributor. Emerging issues which are almost implications of advanced technologies -as the most important trends of the future- and their reflection on the society need to be foresighted. Educating and fostering knowledge of smartness is one of the targets of the smart city concept. In this regard, some of these smart cites have established research and development units to share their projects and smart city initiatives. Due to this fact, gaining experience and sharing the results of this subject is necessary for technology management and moving toward a smart urban future.

Keywords: age of urban tech, bottom-up approach, role of citizens, smart city

Procedia PDF Downloads 120
27776 The Image of Victim and Criminal in Love Crimes on Social Media in Egypt: Facebook Discourse Analysis

Authors: Sherehan Hamdalla

Abstract:

Egypt has experienced a series of terrifying love crimes in the last few months. This ‘trend’ of love crimes started with a young man caught on video slaughtering his ex-girlfriend in the street in the city of El Mansoura. The crime shocked all Egyptian citizens at all levels; unfortunately, not less than three similar crimes took place in other different Egyptian cities with the same killing trigger. The characteristics and easy access and reach of social media consider the reason why it is one of the most crucial online communication channels; users utilize social media platforms for sharing and exchanging ideas, news, and many other activities; they can freely share posts that reflect their mindset or personal views regarding any issues, these posts are going viral in all social media account by reposting or numbers of shares for these posts to support the content included, or even to attack. The repetition of sharing certain posts could mobilize other supporters with the same point of view, especially when that crowd’s online participation is confronting a public opinion case’s consequences. The death of that young woman was followed by similar crimes in other cities, such as El Sharkia and Port Said. These love crimes provoked a massive wave of contention among all social classes in Egypt. Strangely, some were supporting the criminal and defending his side for several reasons, which the study will uncover. Facebook, the most popular social media platform for Egyptians, reflects the debate between supporters of the victim and supporters of the criminal. Facebook pages were created specifically to disseminate certain viewpoints online, for example, asking for the maximum penalty to be given to criminals. These pages aimed to mobilize the maximum number of supporters and to affect the outcome of the trials.

Keywords: love crimes, victim, criminal, social media

Procedia PDF Downloads 53
27775 Systematics of Water Lilies (Genus Nymphaea L.) Using 18S rDNA Sequences

Authors: M. Nakkuntod, S. Srinarang, K.W. Hilu

Abstract:

Water lily (Nymphaea L.) is the largest genus of Nymphaeaceae. This family is composed of six genera (Nuphar, Ondinea, Euryale, Victoria, Barclaya, Nymphaea). Its members are nearly worldwide in tropical and temperate regions. The classification of some species in Nymphaea is ambiguous due to high variation in leaf and flower parts such as leaf margin, stamen appendage. Therefore, the phylogenetic relationships based on 18S rDNA were constructed to delimit this genus. DNAs of 52 specimens belonging to water lily family were extracted using modified conventional method containing cetyltrimethyl ammonium bromide (CTAB). The results showed that the amplified fragment is about 1600 base pairs in size. After analysis, the aligned sequences presented 9.36% for variable characters comprising 2.66% of parsimonious informative sites and 6.70% of singleton sites. Moreover, there are 6 regions of 1-2 base(s) for insertion/deletion. The phylogenetic trees based on maximum parsimony and maximum likelihood with high bootstrap support indicated that genus Nymphaea was a paraphyletic group because of Ondinea, Victoria and Euryale disruption. Within genus Nymphaea, subgenus Nymphaea is a basal lineage group which cooperated with Euryale and Victoria. The other four subgenera, namely Lotos, Hydrocallis, Brachyceras and Anecphya were included the same large clade which Ondinea was placed within Anecphya clade due to geographical sharing.

Keywords: nrDNA, phylogeny, taxonomy, waterlily

Procedia PDF Downloads 122
27774 Buffer Allocation and Traffic Shaping Policies Implemented in Routers Based on a New Adaptive Intelligent Multi Agent Approach

Authors: M. Taheri Tehrani, H. Ajorloo

Abstract:

In this paper, an intelligent multi-agent framework is developed for each router in which agents have two vital functionalities, traffic shaping and buffer allocation and are positioned in the ports of the routers. With traffic shaping functionality agents shape the traffic forward by dynamic and real time allocation of the rate of generation of tokens in a Token Bucket algorithm and with buffer allocation functionality agents share their buffer capacity between each other based on their need and the conditions of the network. This dynamic and intelligent framework gives this opportunity to some ports to work better under burst and more busy conditions. These agents work intelligently based on Reinforcement Learning (RL) algorithm and will consider effective parameters in their decision process. As RL have limitation considering much parameter in its decision process due to the volume of calculations, we utilize our novel method which invokes Principle Component Analysis (PCA) on the RL and gives a high dimensional ability to this algorithm to consider as much as needed parameters in its decision process. This implementation when is compared to our previous work where traffic shaping was done without any sharing and dynamic allocation of buffer size for each port, the lower packet drop in the whole network specifically in the source routers can be seen. These methods are implemented in our previous proposed intelligent simulation environment to be able to compare better the performance metrics. The results obtained from this simulation environment show an efficient and dynamic utilization of resources in terms of bandwidth and buffer capacities pre allocated to each port.

Keywords: principal component analysis, reinforcement learning, buffer allocation, multi- agent systems

Procedia PDF Downloads 489
27773 Investigation and Estimation of State of Health of Battery Pack in Battery Electric Vehicles-Online Battery Characterization

Authors: Ali Mashayekh, Mahdiye Khorasani, Thomas Weyh

Abstract:

The tendency to use the Battery-Electric vehicle (BEV) for the low and medium driving range or even high driving range has been growing more and more. As a result, higher safety, reliability, and durability of the battery pack as a component of electric vehicles, which has a great share of cost and weight of the final product, are the topics to be considered and investigated. Battery aging can be considered as the predominant factor regarding the reliability and durability of BEV. To better understand the aging process, offline battery characterization has been widely used, which is time-consuming and needs very expensive infrastructures. This paper presents the substitute method for the conventional battery characterization methods, which is based on battery Modular Multilevel Management (BM3). According to this Topology, the battery cells can be drained and charged concerning their capacity, which allows varying battery pack structures. Due to the integration of the power electronics, the output voltage of the battery pack is no longer fixed but can be dynamically adjusted in small steps. In other words, each cell can have three different states, namely series, parallel, and bypass in connection with the neighbor cells. With the help of MATLAB/Simulink and by using the BM3 modules, the battery string model is created. This model allows us to switch two cells with the different SoC as parallel, which results in the internal balancing of the cells. But if the parallel switching lasts just for a couple of ms, we can have a perturbation pulse which can stimulate the cells out of the relaxation phase. With the help of modeling the voltage response pulse of the battery, it would be possible to characterize the cell. The Online EIS method, which is discussed in this paper, can be a robust substitute for the conventional battery characterization methods.

Keywords: battery characterization, SoH estimation, RLS, BEV

Procedia PDF Downloads 132
27772 Investigating the Energy Gap and Wavelength of (AlₓGa₁₋ₓAs)ₘ/(GaAs)ₙ Superlattices in Terms of Material Thickness and Al Mole Fraction Using Empirical Tight-Binding Method

Authors: Matineh Sadat Hosseini Gheidari, Vahid Reza Yazdanpanah

Abstract:

In this paper, we used the empirical tight-binding method (ETBM) with sp3s* approximation and considering the first nearest neighbor with spin-orbit interactions in order to model superlattice structure (SLS) of (AlₓGa₁₋ₓAs)ₘ/(GaAs)ₙ grown on GaAs (100) substrate at 300K. In the next step, we investigated the behavior of the energy gap and wavelength of this superlattice in terms of different thicknesses of core materials and Al mole fractions. As a result of this survey, we found out that as the Al composition increases, the energy gap of this superlattice has an upward trend and ranges from 1.42-1.63 eV. Also, according to the wavelength range that we gained from this superlattice in different Al mole fractions and various thicknesses, we can find a suitable semiconductor for a special light-emitting diode (LED) application.

Keywords: energy gap, empirical tight-binding method, light-emitting diode, superlattice, wavelength

Procedia PDF Downloads 174
27771 The Use of Simulation-Based Training to Improve Team Dynamics during Code in Critical Care Units

Authors: Akram Rasheed

Abstract:

Background: Simulation in the health care field has been increasingly used over the last years in the training of resuscitation and life support practices. It has shown the advantage of improving the decision-making and technical skills through deliberate practice and return demonstration. Local Problem: This article reports on the integration of simulation-based training (SBT) in the training program about proper team dynamics and leadership skills during cardiopulmonary resuscitation (CPR) in the intensive care unit (ICU). Method and Intervention: Training of 180 critical care nurses was conducted using SBT between 1st January and 30th 2020. We had conducted 15 workshops, with the integration of SBT using high fidelity manikins and using demonstration and return-demonstration approach to train the nursing staff about proper team dynamics and leadership skills during CPR. Results: After completing the SBT session, all 180 nurses completed the evaluation form. The majority of evaluation items were rated over 95% for the effectiveness of the education; four items were less than 95% (88–94%). Lower rated items considered training and practice time, improved competency, and commitment to apply to learn. The team dynamics SBT was evaluated as an effective means to improve team dynamics and leadership skills during CPR in the intensive care unit (ICU). Conclusion: The use of simulation-based training to improve team dynamics and leadership skills is an effective method for better patient management during CPR. Besides skills competency, closed-loop communication, clear messages, clear roles, and assignments, knowing one’s limitations, knowledge sharing, constructive interventions, re-evaluating and summarizing, and mutual respect are all important concepts that should be considered during team dynamics training. However, participants reported the need for a repeated practice opportunity to build competency.

Keywords: cardiopulmonary resuscitation, high fidelity manikins, simulation-based training, team dynamics

Procedia PDF Downloads 122