Search results for: open information extraction

Authors: Chen-Jung Chen, Yi-Chang Chen

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While traditional virtual reality and augmented reality only allow for small movement learning and cannot provide a truly immersive teaching experience to give it the illusion of movement, the new technology of both content creation and immersive interactive simulation of the metaverse can just reach infinite close to the natural teaching situation. However, the mixed reality virtual classroom of metaverse has not yet explored its theory, and it is rarely implemented in the situational simulation teaching of nursing education. Therefore, in the first year, the study will intend to use grounded theory and case study methods and in-depth interviews with nursing education and information experts. Analyze the interview data to investigate the uniqueness of metaverse development. The proposed analysis will lead to alternative theories and methods for the development of nursing education. In the second year, it will plan to integrate the metaverse virtual situation simulation technology into the alternate teaching strategy in the pediatric nursing technology course and explore the nursing students' use of this teaching method as the construction of personal technology and experience. By leveraging the unique features of distinct teaching platforms and developing processes to deliver alternative teaching strategies in a nursing technology teaching environment. The aim is to increase learning achievements without compromising teaching quality and teacher-student relationships in the post-pandemic era. A descriptive and convergent mixed methods design will be employed. Sixty third-grade nursing students will be recruited to participate in the research and complete the pre-test. The students in the experimental group (N=30) agreed to participate in 4 real-time mixed virtual situation simulation courses in self-practice after class and conducted qualitative interviews after each 2 virtual situation courses; the control group (N=30) adopted traditional practice methods of self-learning after class. Both groups of students took a post-test after the course. Data analysis will adopt descriptive statistics, paired t-tests, one-way analysis of variance, and qualitative content analysis. This study addresses key issues in the virtual reality environment for teaching and learning within the metaverse, providing valuable lessons and insights for enhancing the quality of education. The findings of this study are expected to contribute useful information for the future development of digital teaching and learning in nursing and other practice-based disciplines.

Keywords: metaverse, post-pandemic era, online virtual classroom, immersive teaching

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Authors: Erine van Niekerk, Jason Holland

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In Māori culture water is considered to be the foundation of all life and has its own mana (spiritual power) and mauri (life force). Water classification for cultural values therefore includes categories like waitapu (sacred water), waimanawa-whenua (water from under the land), waipuna (freshwater springs), the relationship between water quantity and quality and the relationship between surface and groundwater. Particular rivers and lakes have special significance to iwi and hapu for their rohe (tribal areas). The Mararoa River, including its freshwater springs and wetlands, is an example of such an area. There is currently little information available about the sources, characteristics and behavior of these important water resources and this study on the water quality of the Mararoa River and adjacent freshwater springs will provide valuable information to be used in informed decisions about water management. The regional council of Southland, Environment Southland, is required to make changes under their water quality policy in order to comply with the requirements for the New National Standards for Freshwater to consult with Maori to determine strategies for decision making. This requires an approach that includes traditional knowledge combined with scientific knowledge in the decision-making process. This study provided the scientific data that can be used in future for decision making on fresh water springs combined with traditional values for this particular area. Several parameters have been tested in situ as well as in a laboratory. Parameters such as temperature, salinity, electrical conductivity, Total Dissolved Solids, Total Kjeldahl Nitrogen, Total Phosphorus, Total Suspended Solids, and Escherichia coli among others show that recorded values of all test parameters fall within recommended ANZECC guidelines and Environment Southland standards and do not raise any concerns for the water quality of the springs and the river at the moment. However, the destruction of natural areas, particularly due to changes in farming practices, and the changes to water quality by the introduction of Didymosphenia geminate (Didymo) means Māori have already lost many of their traditional mahinga kai (food sources). There is a major change from land use such as sheep farming to dairying in Southland which puts freshwater resources under pressure. It is, therefore, important to draw on traditional knowledge and spirituality alongside scientific knowledge to protect the waters of the Mararoa River and waipuna. This study hopes to contribute to scientific knowledge to preserve the cultural values of these significant waters.

Keywords: cultural values, freshwater springs, Maori, water quality

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Authors: Atucungwiire Rwebiita

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Introduction: In Uganda, provision of adolescent sexual reproductive health and rights (SRHR) services for key population is still hindered by negative attitudes, stigma and discrimination (S&D) at both the community and facility levels. To address this barrier, Integrated Community Based Initiatives (ICOBI) with support from SIDA is currently implementing a quality improvement (QI) innovative approach for strengthening the capacity of key population (KP) peer leaders and health workers to deliver friendly SRHR services without S&D. Methods: Our innovative approach involves continuous mentorship and coaching of 8 QI teams at 8 health facilities and their catchment areas. Each of the 8 teams (comprised of 5 health workers and 5 KP peer leaders) are facilitated twice a month by two QI Mentors in a 2-hour mentorship session over a period of 4 months. The QI mentors were provided a 2-weeks training on QI approaches for reducing S&D against young key populations in the delivery of SRHR Services. The mentorship sessions are guided by a manual where teams base to analyse root causes of S&D and develop key performance indicators (KPIs) in the 1st and 2nd second sessions respectively. The teams then develop action plans in the 3rd session and review implementation progress on KPIs at the end of subsequent sessions. The KPIs capture information on the attitude of health workers and peer leaders and the general service delivery setting as well as clients’ experience. A dashboard is developed to routinely track the KPIs for S&D across all the supported health facilities and catchment areas. After 4 months, QI teams share documented QI best practices and tested change packages on S&D in a learning and exchange session involving all the teams. Findings: The implementation of this approach is showing positive results. So far, QI teams have already identified the root causes of S&D against key populations including: poor information among health workers, fear of a perceived risk of infection, perceived links between HIV and disreputable behaviour. Others are perceptions that HIV & STIs are divine punishment, sex work and homosexuality are against religion and cultural values. They have also noted the perception that MSM are mentally sick and a danger to everyone. Eight QI teams have developed action plans to address the root causes of S&D. Conclusion: This approach is promising, offers a novel and scalable means to implement stigma-reduction interventions in facility and community settings.

Keywords: key populations, sexual reproductive health and rights, stigma and discrimination , quality improvement approach

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Authors: Helen Potkin

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This paper presents a practice-based case study of a project in which the student group designed and planned the curriculum content, classroom activities and assessment briefs in collaboration with the tutor. It focuses on the co-creation of the curriculum within a history and theory module, Researching the Contemporary, which runs for BA (Hons) Fine Art and Art History and for BA (Hons) Art Design History Practice at Kingston University, London. The paper analyses the potential of collaborative approaches to engender students’ investment in their own learning and to encourage reflective and self-conscious understandings of themselves as learners. It also addresses some of the challenges of working in this way, attending to the risks involved and feelings of uncertainty produced in experimental, fluid and open situations of learning. Alongside this, it acknowledges the tensions inherent in adopting such practices within the framework of the institution and within the wider of context of the commodification of higher education in the United Kingdom. The concept underpinning the initiative was to test out co-creation as a creative process and to explore the possibilities of altering the traditional hierarchical relationship between teacher and student in a more active, participatory environment. In other words, the project asked about: what kind of learning could be imagined if we were all in it together? It considered co-creation as producing different ways of being, or becoming, as learners, involving us reconfiguring multiple relationships: to learning, to each other, to research, to the institution and to our emotions. The project provided the opportunity for students to bring their own research and wider interests into the classroom, take ownership of sessions, collaborate with each other and to define the criteria against which they would be assessed. Drawing on students’ reflections on their experience of co-creation alongside theoretical considerations engaging with the processual nature of learning, concepts of equality and the generative qualities of the interrelationships in the classroom, the paper suggests that the dynamic nature of collaborative and participatory modes of engagement have the potential to foster relevant and significant learning experiences. The findings as a result of the project could be quantified in terms of the high level of student engagement in the project, specifically investment in the assessment, alongside the ambition and high quality of the student work produced. However, reflection on the outcomes of the experiment prompts a further set of questions about the nature of positionality in connection to learning, the ways our identities as learners are formed in and through our relationships in the classroom and the potential and productive nature of creative practice in education. Overall, the paper interrogates questions of what it means to work with students to invent and assemble the curriculum and it assesses the benefits and challenges of co-creation. Underpinning it is the argument that, particularly in the current climate of higher education, it is increasingly important to ask what it means to teach and to envisage what kinds of learning can be possible.

Keywords: co-creation, collaboration, learning, participation, risk

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Authors: Esteban Maioli

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Generational studies have an important research tradition in social and human sciences. On the one hand, the speed of social change in the context of globalization imposes the need to research the transformations are identified both the subjectivity of the agents involved and its inclusion in the institutional matrix, specifically employment. Generation Z, (generally considered as the population group whose birth occurs after 1995) have unique psycho-social characteristics. Gen Z is characterized by a different set of values, beliefs, attitudes and ambitions that impact in their concrete action in organizational structures. On the other hand, managers often have to deal with generational differences in the workplace. Organizations have members who belong to different generations; they had never before faced the challenge of having such a diverse group of members. The members of each historical generation are characterized by a different set of values, beliefs, attitudes and ambitions that are manifest in their concrete action in organizational structures. Gen Z it’s the only one who can fully be considered "global," while its members were born in the consolidated context of globalization. Some salient features of the Generation Z can be summarized as follows. They’re the first fully born into a digital world. Social networks and technology are integrated into their lives. They are concerned about the challenges of the modern world (poverty, inequality, climate change, among others). They are self-expressive, more liberal and open to change. They often bore easily, with short attention spans. They do not like routine tasks. They want to achieve a good life-work balance, and they are interested in a flexible work environment, as opposed to traditional work schedule. They are critical thinkers, who come with innovative and creative ideas to help. Research design considered methodological triangulation. Data was collected with two techniques: a self-administered survey with multiple choice questions and attitudinal scales applied over a non-probabilistic sample by reasoned decision. According to the multi-method strategy, also it was conducted in-depth interviews. Organizations constantly face new challenges. One of the biggest ones is to learn to manage a multi-generational scope of work. While Gen Z has not yet been fully incorporated (expected to do so in five years or so), many organizations have already begun to implement a series of changes in its recruitment and development. The main obstacle to retaining young talent is the gap between the expectations of iGen applicants and what companies offer. Members of the iGen expect not only a good salary and job stability but also a clear career plan. Generation Z needs to have immediate feedback on their tasks. However, many organizations have yet to improve both motivation and monitoring practices. It is essential for companies to take a review of organizational practices anchored in the culture of the organization.

Keywords: employment, expectations, generation Z, organizational culture, organizations, psycho-social characteristics

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Authors: Lin Tang, Xiaoxia Guo, Lingling Zhang

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Recent vaccine scandals overshadowed China’s accomplishment of public health, triggering discussions on the causes of vaccine incidents. Through legal interpretation of selected vaccine incidents and analysis of systemic vulnerabilities in vaccine circulation and lot release, a panoramic review of legislative progresses in the vaccine administration sheds the light on this debate. In essence, it is the combination of the lagging legal system and the absence of information technology infrastructure in the process of vaccine administration reform that has led to the recurrence of vaccine incidents. These findings have significant implications for further improvement of vaccine administration and China’s participation in global healthcare.

Keywords: legislation, lot release, public health, reform, vaccine administration, vaccine circulation

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Authors: Weitao Lin

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To quickly extract adequate information from large-scale unstructured text data, this paper studies the representation of events in Chinese scenarios and performs the regularized abstraction. It proposes a Chinese event detection technique based on dependency parsing and rule matching. The method first performs dependency parsing on the original utterance, then performs pattern matching at the word or phrase granularity based on the results of dependent syntactic analysis, filters out the utterances with prominent non-event characteristics, and obtains the final results. The experimental results show the effectiveness of the method.

Keywords: natural language processing, Chinese event detection, rules matching, dependency parsing

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Authors: Nasser Alsadoun

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Today's companies in Saudi Arabian capital market must comply with strict criteria and adhere to rigid corporate governance rules and continuous disclosure requirements. Unlike other regulators in the region, decision makers of the Capital Market Authority (hereafter CMA) of Saudi Arabia believes that the announcements of economic sanctions and penalties for non-compliance firms will foster more effective regulatory compliance and hence improve the quality of financial reporting. An implied argument put forward by the opponents, however, states that such penalties are unnecessary and stated to be onerous for non-compliance firms. Over that last years, the CMA has publicly announced several economic fines levied on some listed companies for their failing to comply with corporate governance and continuous disclosure regulation clauses, with the amount of fine levied ranges between 50,000 SR to 100,000 SR for each failing. Economic theory suggests that rational investors make decisions based on a cost-benefit principal. The regulatory intervention made by CMA on the announcement of economic sanctions has been costly to the society (economy) hoping that it improves the transparency of financial statements. It is argued, therefore, that threat of regulators and economic sanctions will provide incentives for firms’ managers to report more relevant and reliable accounting information, and the benefit of such announcements is likely to be reflected in the context of the quality of the financial reports. Yet, the economic consequences of the revealed fines announcement for non-compliance firms in Saudi Arabian market have not been examined. Thus, this study attempts to empirically examine whether market participants are pricing the supposed benefits of rigid governance and disclosure rules in the Saudi market. The study employs an event study methodology to assess the impact of CMA economic sanctions announcements on the market price of non-compliance firms. The study also estimates and examines bid–ask spread behavior of violated firms around the CMA announcements. The findings indicate that the CMA fines announcements for failing to comply with governance and disclosure rules do not appear to play any significant role in securities pricing. In addition, tests of bid-ask behavior does not indicate any significant increases in information asymmetry surrounding these announcements. While the CMA has developed many goals to increase the awareness of listed companies with the best governance and disclosure practices, it seems they have to develop more goals to improve market efficiency and increase investors and public awareness.

Keywords: governance and disclosure violations, financial reporting quality, regulatory intervention, market efficiency

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Authors: Maroonisha Maharajh

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Based on the Black Swan and Disruptive Innovation Theories, this study proposes an educational game based learning model within the context of the traditional classroom learning environment. In the proposed model, the perceived e-learning component is decomposed into accessibility, perceived quality and perceived usability within the traditional rural classroom environment. A sample of 92 respondents took part in this study. The results suggest that users’ continuance intention is determined by both economic and grassroots internet accessibility, which in turn is jointly determined by perceived usefulness, information quality, service quality, system quality, perceived ease of use and cognitive absorption of learning.

Keywords: blended learning, flipped classroom, e-learning, gaming

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Authors: Spanova Yerkezhan, Amantay Ayan, Alimzhanova Laura

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This article discusses the concept of rebranding and its relationship to cybersecurity. Rebranding is the process of changing the appearance and image of a company or organization in order to appeal to new customers or change the perception of a company. It can be a powerful tool for businesses looking to renew their reputation or expand into new markets. In today's digital age, companies increasingly rely on technology and the internet to conduct business; rebranding can also present significant cybersecurity risks. This is because a rebranding effort can create new vulnerabilities for companies, particularly in terms of their online presence. This article explores the potential hazards associated with rebranding and provides recommendations for mitigating those risks. It also highlights the importance of considering cybersecurity in the rebranding process and how it can be integrated into the overall strategy for a successful and secure rebranding.

Keywords: rebranding, cybersecurity, cyberattack, logo, vulnerability

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Authors: Mindaye Teshome, Evaldo Muñoz Braz, Carlos M. M. Eleto Torres, Patricia Mattos

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Sustainable forest management planning requires up-to-date information on the structure, standing volume, biomass, and growth rate of trees from a given forest. This kind of information is lacking in many forests in Ethiopia. The objective of this study was to quantify the population structure, diameter growth rate, and standing volume of wood from Juniperus procera trees in the Chilimo forest. A total of 163 sample plots were set up in the forest to collect the relevant vegetation data. Growth ring measurements were conducted on stem disc samples collected from 12 J. procera trees. Diameter and height measurements were recorded from a total of 1399 individual trees with dbh ≥ 2 cm. The growth rate, maximum current and mean annual increments, minimum logging diameter, and cutting cycle were estimated, and alternative cutting cycles were established. Using these data, the harvestable volume of wood was projected by alternating four minimum logging diameters and five cutting cycles following the stand table projection method. The results show that J. procera trees have an average density of 183 stems ha⁻¹, a total basal area of 12.1 m² ha⁻¹, and a standing volume of 98.9 m³ ha⁻¹. The mean annual diameter growth ranges between 0.50 and 0.65 cm year⁻¹ with an overall mean of 0.59 cm year⁻¹. The population of J. procera tree followed a reverse J-shape diameter distribution pattern. The maximum current annual increment in volume (CAI) occurred at around 49 years when trees reached 30 cm in diameter. Trees showed the maximum mean annual increment in volume (MAI) around 91 years, with a diameter size of 50 cm. The simulation analysis revealed that 40 cm MLD and a 15-year cutting cycle are the best minimum logging diameter and cutting cycle. This combination showed the largest harvestable volume of wood potential, volume increments, and a 35% recovery of the initially harvested volume. It is concluded that the forest is well stocked and has a large amount of harvestable volume of wood from J. procera trees. This will enable the country to partly meet the national wood demand through domestic wood production. The use of the current population structure and diameter growth data from tree ring analysis enables the exact prediction of the harvestable volume of wood. The developed model supplied an idea about the productivity of the J. procera tree population and enables policymakers to develop specific management criteria for wood harvesting.

Keywords: logging, growth model, cutting cycle, minimum logging diameter

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Authors: S. Suman, G. N. Singh

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The present manuscript addresses the estimation procedure of population parameter using Poisson probability distribution when characteristic under study possesses a rare sensitive attribute. The generalized form of unrelated randomized response model is suggested in order to acquire the truthful responses from respondents. The resultant estimators have been proposed for two situations when the information on an unrelated rare non-sensitive characteristic is known as well as unknown. The properties of the proposed estimators are derived, and the measure of confidentiality of respondent is also suggested for respondents. Empirical studies are carried out in the support of discussed theory.

Keywords: Poisson distribution, randomized response model, rare sensitive attribute, non-sensitive attribute

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Authors: Olga I. Moskalenko, Vladislav A. Khanadeev, Anastasya D. Koloskova, Alexey A. Koronovskii, Anatoly A. Pivovarov

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Generalized synchronization is one of the most intricate phenomena in nonlinear science. It can be observed both in systems with a unidirectional and mutual type of coupling including the complex networks. Such a phenomenon has a number of practical applications, for example, for the secure information transmission through the communication channel with a high level of noise. Known methods for the secure information transmission needs in the increase of the privacy of data transmission that arises a question about the observation of such phenomenon in systems with a complex topology of chaotic attractor possessing two or more positive Lyapunov exponents. The present report is devoted to the study of such phenomenon in two unidirectionally and mutually coupled dynamical systems being in chaotic (with one positive Lyapunov exponent) and hyperchaotic (with two or more positive Lyapunov exponents) regimes, respectively. As the systems under study, we have used two mutually coupled modified Lorenz oscillators and two unidirectionally coupled time-delayed generators. We have shown that in both cases the generalized synchronization regime can be detected by means of the calculation of Lyapunov exponents and phase tube approach whereas due to the complex topology of attractor the nearest neighbor method is misleading. Moreover, the auxiliary system approaches being the standard method for the synchronous regime observation, for the mutual type of coupling results in incorrect results. To calculate the Lyapunov exponents in time-delayed systems we have proposed an approach based on the modification of Gram-Schmidt orthogonalization procedure in the context of the time-delayed system. We have studied in detail the mechanisms resulting in the generalized synchronization regime onset paying a great attention to the field where one positive Lyapunov exponent has already been become negative whereas the second one is a positive yet. We have found the intermittency here and studied its characteristics. To detect the laminar phase lengths the method based on a calculation of local Lyapunov exponents has been proposed. The efficiency of the method has been verified using the example of two unidirectionally coupled Rössler systems being in the band chaos regime. We have revealed the main characteristics of intermittency, i.e. the distribution of the laminar phase lengths and dependence of the mean length of the laminar phases on the criticality parameter, for all systems studied in the report. This work has been supported by the Russian President's Council grant for the state support of young Russian scientists (project MK-531.2018.2).

Keywords: complex topology of attractor, generalized synchronization, hyperchaos, Lyapunov exponents

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Authors: Laleh Taheri, Noraini C. Pa, Rusli Abdullah, Salfarina Abdullah

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Knowledge plays an important role to the success of any organization. Software development organizations are highly knowledge-intensive organizations especially in their Requirement Elicitation Process (REP). There are several problems regarding communicating and using the knowledge in REP such as misunderstanding, being out of scope, conflicting information and changes of requirements. All of these problems occurred in transmitting the requirements knowledge during REP. Several researches have been done in REP in order to solve the problem towards requirements. Knowledge Audit (KA) approaches were proposed in order to solve managing knowledge in human resources, financial, and manufacturing. There is lack of study applying the KA in requirements elicitation process. Therefore, this paper proposes a KA model for REP in supporting to acquire good requirements.

Keywords: knowledge audit, requirement elicitation process, KA model, knowledge in requirement elicitation

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Authors: A. Azizi, M. Toubane, L. Chetibi

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Differential scanning calorimetry (DSC) is a widely used technique for the study of phase transformations, particularly in the study of precipitation. The kinetic of the precipitation and dissolution is always related to the concept of activation energy Ea. The determination of the activation energy gives important information about the kinetic of the precipitation reaction. In this work, we were interested in the study of the isothermal and non-isothermal treatments on the decomposition of the supersaturated solid solution in the alloy AZ91 (Mg-9 Al-Zn 1-0.2 Mn. mass fraction %), using Differential Calorimetric method. Through this method, the samples were heat treated up to 425° C, using different rates. To calculate the apparent activation energies associated with the formation of precipitated phases, we used different isoconversional methods. This study was supported by other analysis: X-ray diffraction and microhardness measurements.

Keywords: calorimetric, activation energy, AZ91 alloys, microstructural evolution

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Authors: Akkouche Karim, Nekmouche Aghiles, Bouzid Leyla

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This study focuses on the development of a multifunctional Expert System (ES) called post-seismic damage inspection tool (PSDIT), a powerful tool which allows the evaluation, the processing and the archiving of the collected data stock after earthquakes. PSDIT can be operated by two user types; an ordinary user (engineer, expert or architect) for the damage visual inspection and an administrative user for updating the knowledge and / or for adding or removing the ordinary user. The knowledge acquisition is driven by a hierarchical knowledge model, the Information from investigation reports and those acquired through feedback from expert / engineer questionnaires are part.

Keywords: buildings, earthquake, seismic damage, damage assessment, expert system

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Authors: Maysam Shahsavari, Seyed Jamalaldin Haddadi

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There are several methods to localize a mobile robot such as relative, absolute and probabilistic. In this paper, particle filter due to its simple implementation and the fact that it does not need to know to the starting position will be used. This method estimates the position of the mobile robot using a probabilistic distribution, relying on a known map of the environment instead of predicting it. Afterwards, it updates this estimation by reading input sensors and control commands. To receive information from the surrounding world, distance to obstacles, for example, a Kinect is used which is much cheaper than a laser range finder. Finally, after explaining the Adaptive Particle Filter method and its implementation in detail, we will compare this method with the dead reckoning method and show that this method is much more suitable for situations in which we have a map of the environment.

Keywords: particle filter, localization, methods, odometry, kinect

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Authors: Yuli Widiana

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The study of implicature which is one of the discussions of pragmatics is an interesting and challenging topic to discuss. Implicature is a meaning which is implied in an utterance which is not the same as its literal meaning. The rapid development of information technology results in social networks as media to broadcast messages. The broadcast messages may be in the form of jokes which contain implicature. The research applies the pragmatic equivalent method to analyze the topics of jokes based on the implicatures contained in them. Furthermore, the method is also applied to reveal the purpose of creating implicature in jokes. The findings include the kinds of implicature found in jokes which are classified into conventional implicature and conversational implicature. Then, in detailed analysis, implicature in jokes is divided into implicature related to gender, culture, and social phenomena. Furthermore, implicature in jokes may not only be used to give entertainment but also to soften criticisms or satire so that it does not sound rude and harsh.

Keywords: implicature, broadcast messages, conventional implicature, conversational implicature

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Authors: Lawrence Ngalim

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The paucity of entrepreneurial finance in Sub-Saharan Africa (SSA) can plausibly be tied to her comparatively less-developed capital markets, which potentially hurts entrepreneurial activities. The high rate of informality in SSA worsens information asymmetry, which restricts the supply of funds in a heavily bank-led environment. In this paper, we ask whether the adoption of recent technological improvements in delivering financial services, such as crowdfunding, assists the financially excluded within Africa. Secondly, we investigate the individual determinants of crowdfunding, such as income, level of education, demographics, culture/trust, and the effects of crowdfunding on households’ usage of formal financial services. The paper discusses the long-term policy implications of this particular type of fintech in achieving financial inclusion within the regional bloc and its advantage for Africa-Agenda-2063.

Keywords: fintech, banks, entrepreneurship, regional integration

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Authors: Taissir Fekih Romdhane

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This paper proposes a mobile web application named Pharmacy-Station that sells medicines and permits user to search for medications based on their symptoms, making it is easy to locate a specific drug online without the need to visit a pharmacy where it may be out of stock. This application is developed using the jQuery Mobile framework, which uses many web technologies and languages such as HTML5, PHP, JavaScript and CSS3. To test the proposed application, we used data from popular pharmacies in Saudi Arabia that included important information such as location, contact, and medicines in stock, etc. This document describes the different steps followed to create the Pharmacy-Station application along with screenshots. Finally, based on the results, the paper concludes with recommendations and further works planned to improve the Pharmacy-Station mobile application.

Keywords: pharmacy, mobile application, jquery mobile framework, search, medicine

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Authors: Salma A. Mahmoud

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Epigenetic, or alteration in gene expression influenced by extragenetic factors, has emerged as one of the most promising areas that will address some of the gaps in our current knowledge in understanding patterns of human variation. In the last decade, the research investigating epigenetic mechanisms in many fields has flourished and witnessed significant progress. It paved the way for a new era of integrated research especially between anthropology/archeology and life sciences. Skeletal remains are considered the most significant source of information for studying human variations across history, and by utilizing these valuable remains, we can interpret the past events, cultures and populations. In addition to archeological, historical and anthropological importance, studying bones has great implications in other fields such as medicine and science. Bones also can hold within them the secrets of the future as they can act as predictive tools for health, society characteristics and dietary requirements. Bones in their basic forms are composed of cells (osteocytes) that are affected by both genetic and environmental factors, which can only explain a small part of their variability. The primary objective of this project is to examine the epigenetic landscape/signature within bones of archeological remains as a novel marker that could reveal new ways to conceptualize chronological events, gender differences, social status and ecological variations. We attempted here to address discrepancies in common variants such as methylome as well as novel epigenetic regulators such as chromatin remodelers, which to our best knowledge have not yet been investigated by anthropologists/ paleoepigenetists using plethora of techniques (biological, computational, and statistical). Moreover, extracting epigenetic information from bones will highlight the importance of osseous material as a vector to study human beings in several contexts (social, cultural and environmental), and strengthen their essential role as model systems that can be used to investigate and construct various cultural, political and economic events. We also address all steps required to plan and conduct an epigenetic analysis from bone materials (modern and ancient) as well as discussing the key challenges facing researchers aiming to investigate this field. In conclusion, this project will serve as a primer for bioarcheologists/anthropologists and human biologists interested in incorporating epigenetic data into their research programs. Understanding the roles of epigenetic mechanisms in bone structure and function will be very helpful for a better comprehension of their biology and highlighting their essentiality as interdisciplinary vectors and a key material in archeological research.

Keywords: epigenetics, archeology, bones, chromatin, methylome

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Authors: Hanan Alshaher, Jinsheng Xu

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Large amounts of data on the web can provide valuable information. For example, product reviews help business owners measure customer satisfaction. Sentiment analysis classifies texts into two polarities: positive and negative. This paper examines movie reviews and tweets using a new term weighting scheme, called one-over-sigma (1/sigma), on benchmark datasets for sentiment classification. The proposed method aims to improve the performance of sentiment classification. The results show that 1/sigma is more accurate than the popular term weighting schemes. In order to verify if the entropy reflects the discriminating power of terms, we report a comparison of entropy values for different term weighting schemes.

Keywords: 1/sigma, natural language processing, sentiment analysis, term weighting scheme, text classification

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Authors: Refik Uyanöz, Sadife Güngör, Sevilay Konya

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The aim of this study is to show the employing ability of vocational students. And also, the employment problems of these students are emphasized in this study.The rapid development in technology and information and increased qualified labor is widely affects labor market. On the other hand, labor market will look for educated, qualified, talented and young people. Because of this reason, qualified staff should be educated at vocational high schools. Vocational high schools are one of the best institutions to educate qualified staff. In this research, the conditions of vocational high schools are studied. The difference between the employment policies and current employment problems are researched.

Keywords: vocational high school, employment, employment problems, vocational students

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Authors: Hemant Upadhyay, Tarun Kumar Kundu

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It is utmost important for a blast furnace operator to understand the mechanisms governing the liquid flow, accumulation, drainage and heat transfer between various phases in blast furnace hearth for a stable and efficient blast furnace operation. Abnormal drainage behavior may lead to high liquid build up in the hearth. Operational problems such as pressurization, low wind intake, and lower material descent rates, normally be encountered if the liquid levels in the hearth exceed a critical limit when Hearth coke and Deadman start to float. Similarly, hot metal temperature is an important parameter to be controlled in the BF operation; it should be kept at an optimal level to obtain desired product quality and a stable BF performance. It is not possible to carry out any direct measurement of above due to the hostile conditions in the hearth with chemically aggressive hot liquids. The objective here is to develop a mathematical model to simulate the variation in hot metal / slag accumulation and temperature during the tapping of the blast furnace based on the computed drainage rate, production rate, mass balance, heat transfer between metal and slag, metal and solids, slag and solids as well as among the various zones of metal and slag itself. For modeling purpose, the BF hearth is considered as a pressurized vessel, filled with solid coke particles. Liquids trickle down in hearth from top and accumulate in voids between the coke particles which are assumed thermally saturated. A set of generic mass balance equations gives the amount of metal and slag intake in hearth. A small drainage (tap hole) is situated at the bottom of the hearth and flow rate of liquids from tap hole is computed taking in account the amount of both the phases accumulated their level in hearth, pressure from gases in the furnace and erosion behaviors of tap hole itself. Heat transfer equations provide the exchange of heat between various layers of liquid metal and slag, and heat loss to cooling system through refractories. Based on all that information a dynamic simulation is carried out which provides real time information of liquids accumulation in hearth before and during tapping, drainage rate and its variation, predicts critical event timings during tapping and expected tapping temperature of metal and slag on preset time intervals. The model is in use at JSPL, India BF-II and its output is regularly cross-checked with actual tapping data, which are in good agreement.

Keywords: blast furnace, hearth, deadman, hotmetal

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Authors: Stacey Pollard, Henry Baraket, Girish Ganesan, Natalie Kim

Abstract:

One year after U.S.-led coalition operations liberated ISIS-held territories in Iraq and Syria and killed ISIS core leader Abu Bakr al-Baghdadi, ISIS is resurging. Taking a page from its old playbook, the organization is capitalizing on social unrest and a rapidly deteriorating security environment—exacerbated by the COVID-19 pandemic—to reconstitute in permissive areas of Iraq and Syria. This Short examines ISIS’s pandemic-era ground and information operations through the lens of its state- and nation-making efforts to help analysts and decisionmakers better understand the imminence and scope of the threat. ISIS is rapidly overcoming U.S.-supported counterterrorism gains and, without direct pressure to reverse these advances, is poised for recovery.

Keywords: Terrorism, COVID-19, Islamic State, Instability, Iraq, Syria, Global, Resurgence

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Authors: D. Pérez, M. M. E. Alemany

Abstract:

In this work a Framework to model the Supply Chain (SC) Collaborative Planning (CP) Process is proposed, and particularly its Decisional view. The main Framework contributions with regards to previous related works are the following, 1) the consideration of not only the Decision view, the most important one due to the Process type, but other additional three views which are the Physical, Organisation and Information ones, closely related and complementing the Decision View, 2) the joint consideration of two interdependence types, the Temporal (among Decision Centres belonging to different Decision Levels) and Spatial (among Decision Centres belonging to the same Decision Level) to support the distributed Decision-Making process in SC where several decision Centres interact among them in a collaborative manner.

Keywords: collaborative planning, decision view, distributed decision-making, framework

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Authors: Stefan K. Behfar

Abstract:

The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: Mehriban Ahmadova

Abstract:

Country of origin has been found to be an important determinant of the level of corporate social disclosure. The purpose of this study is to investigate the differences of corporate social disclosure, including sharia non-compliant information, by Islamic banks. The study applies content analysis approach of annual reports of fully-fledged Islamic banks from 24 countries. International differences are found in terms of level, methods and location of disclosure.

Keywords: Content analysis, Corporate social disclosure, Islamic banks, Sharia non-compliant disclosure

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Authors: A. Basu, A. A. Purohit, M. M. Vaidya, M. D. Kudale

Abstract:

Mumbai, being traditionally the epicenter of India's trade and commerce, the existing major ports such as Mumbai and Jawaharlal Nehru Ports (JN) situated in Thane estuary are also developing its waterfront facilities. Various developments over the passage of decades in this region have changed the tidal flux entering/leaving the estuary. The intake at Pir-Pau is facing the problem of shortage of water in view of advancement of shoreline, while jetty near Ulwe faces the problem of ship scheduling due to existence of shallower depths between JN Port and Ulwe Bunder. In order to solve these problems, it is inevitable to have information about tide levels over a long duration by field measurements. However, field measurement is a tedious and costly affair; application of artificial intelligence was used to predict water levels by training the network for the measured tide data for one lunar tidal cycle. The application of two layered feed forward Artificial Neural Network (ANN) with back-propagation training algorithms such as Gradient Descent (GD) and Levenberg-Marquardt (LM) was used to predict the yearly tide levels at waterfront structures namely at Ulwe Bunder and Pir-Pau. The tide data collected at Apollo Bunder, Ulwe, and Vashi for a period of lunar tidal cycle (2013) was used to train, validate and test the neural networks. These trained networks having high co-relation coefficients (R= 0.998) were used to predict the tide at Ulwe, and Vashi for its verification with the measured tide for the year 2000 & 2013. The results indicate that the predicted tide levels by ANN give reasonably accurate estimation of tide. Hence, the trained network is used to predict the yearly tide data (2015) for Ulwe. Subsequently, the yearly tide data (2015) at Pir-Pau was predicted by using the neural network which was trained with the help of measured tide data (2000) of Apollo and Pir-Pau. The analysis of measured data and study reveals that: The measured tidal data at Pir-Pau, Vashi and Ulwe indicate that there is maximum amplification of tide by about 10-20 cm with a phase lag of 10-20 minutes with reference to the tide at Apollo Bunder (Mumbai). LM training algorithm is faster than GD and with increase in number of neurons in hidden layer and the performance of the network increases. The predicted tide levels by ANN at Pir-Pau and Ulwe provides valuable information about the occurrence of high and low water levels to plan the operation of pumping at Pir-Pau and improve ship schedule at Ulwe.

Keywords: artificial neural network, back-propagation, tide data, training algorithm

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Authors: Andrea Pietrelli, Vincenzo Ferrara, Bruno Allard, Francois Buret, Irene Bavasso, Nicola Lovecchio, Francesca Costantini, Firas Khaled

Abstract:

This paper aims to show some applications of microbial fuel cells (MFCs), an energy harvesting technique, as clean power source to supply low power device for application like wireless sensor network (WSN) for environmental monitoring. Furthermore, MFC can be used directly as biosensor to analyse parameters like pH and temperature or arranged in form of cluster devices in order to use as small power plant. An MFC is a bioreactor that converts energy stored in chemical bonds of organic matter into electrical energy, through a series of reactions catalysed by microorganisms. We have developed a lab-scale terrestrial microbial fuel cell (TMFC), based on soil that acts as source of bacteria and flow of nutrient and a lab-scale waste water microbial fuel cell (WWMFC), where waste water acts as flow of nutrient and bacteria. We performed large series of tests to exploit the capability as biosensor. The pH value has strong influence on the open circuit voltage (OCV) delivered from TMFCs. We analyzed three condition: test A and B were filled with same soil but changing pH from 6 to 6.63, test C was prepared using a different soil with a pH value of 6.3. Experimental results clearly show how with higher pH value a higher OCV was produced; indeed reactors are influenced by different values of pH which increases the voltage in case of a higher pH value until the best pH value of 7 is achieved. The influence of pH on OCV of lab-scales WWMFC was analyzed at pH value of 6.5, 7, 7.2, 7.5 and 8. WWMFCs are influenced from temperature more than TMFCs. We tested the power performance of WWMFCs considering four imposed values of ambient temperature. Results show how power performance increase proportionally with higher temperature values, doubling the output power from 20° to 40°. The best value of power produced from our lab-scale TMFC was equal to 310 μW using peaty soil, at 1KΩ, corresponding to a current of 0.5 mA. A TMFC can supply proper energy to low power devices of a WSN by means of the design of three stages scheme of an energy management system, which adapts voltage level of TMFC to those required by a WSN node, as 3.3V. Using a commercial DC/DC boost converter, that needs an input voltage of 700 mV, the current source of 0.5 mA, charges a capacitor of 6.8 mF until it will have accumulated an amount of charge equal to 700 mV in a time of 10 s. The output stage includes an output switch that close the circuit after a time of 10s + 1.5ms because the converter can boost the voltage from 0.7V to 3.3V in 1.5 ms. Furthermore, we tested in form of clusters connected in series up to 20 WWMFCs, we have obtained a high voltage value as output, around 10V, but low current value. MFC can be considered a suitable clean energy source to be used to supply low power devices as a WSN node or to be used directly as biosensor.

Keywords: energy harvesting, low power electronics, microbial fuel cell, terrestrial microbial fuel cell, waste-water microbial fuel cell, wireless sensor network

Procedia PDF Downloads 206