Search results for: face lifting

Authors: Khaled Ben Oualid Medani, Samir Sayah

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The Optimal Reactive Power Dispatch (ORPD) problem has been solved and analysed usually in the normal conditions. However, network collapses appear in contingency conditions. In this paper, ORPD under several contingencies is presented using the proposed method WOA. To ensure viability of the power system in contingency conditions, several critical cases are simulated in order to prevent and prepare the power system to face such situations. The results obtained are carried out in IEEE 30 bus test system for the solution of ORPD problem in which control of bus voltages, tap position of transformers and reactive power sources are involved. Moreover, another method, namely, Particle Swarm Optimization with Time Varying Acceleration Coefficient (PSO-TVAC) has been compared with the proposed technique. Simulation results indicate that the proposed WOA gives remarkable solution in terms of effectiveness in case of outages.

Keywords: optimal reactive power dispatch, power system analysis, real power loss minimization, contingency condition, metaheuristic technique, whale optimization algorithm

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Authors: Motahareh Fadaei

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Wireless sensor networks that are used to monitor a special environment, are formed from a large number of sensor nodes. The role of these sensors is to sense special parameters from ambient and to make connection. In these networks, the most important challenge is the management of energy usage. Clustering is one of the methods that are broadly used to face this challenge. In this paper, a distributed clustering protocol based on learning automata is proposed for underwater wireless sensor networks. The proposed algorithm that is called LA-Clustering forms clusters in the same energy level, based on the energy level of nodes and the connection radius regardless of size and the structure of sensor network. The proposed approach is simulated and is compared with some other protocols with considering some metrics such as network lifetime, number of alive nodes, and number of transmitted data. The simulation results demonstrate the efficiency of the proposed approach.

Keywords: clustering, energy consumption‎, learning automata, underwater sensor networks

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Authors: Gül Çevik

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This paper summarizes the work conducted to assess the root cause of the failure of a medium commercial vehicle leaf spring failed in service. Macro- and micro-fractographic analyses by scanning electron microscope as well as material verification tests were conducted in order to understand the failure mechanisms and root cause of the failure. Findings from the fractographic analyses indicated that failure mechanism is fatigue. Crack initiation was identified to have occurred from a point on the top surface near to the front face and to the left side. Two other crack initiation points were also observed, however, these cracks did not propagate. The propagation mode of the fatigue crack revealed that the cyclic loads resulting in crack initiation and propagation were unidirectional bending. Fractographic analyses have also showed that the root cause of the fatigue crack initiation and propagation was loading the part above design stress. Material properties of the part were also verified by chemical composition analysis, microstructural analysis by optical microscopy and hardness tests.

Keywords: leaf spring, failure analysis, fatigue, fractography

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Authors: Mohammed Abdulridha Hamdan

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To face the water crisis, understanding the role of human activities on nutrient concentrations in aquatic ecosystems needs more investigations compare to extensively studies which have been carried out to understand these impacts on water quality of different aquatic ecosystems. We hypothesized human activates on the catchments of Tigris river may change nutrient concentrations in water along the river. The results showed that phosphate concentration differed significantly among the studied sites due to distributed human activities, while nitrate concentration did not. Phosphate and nitrate concentrations were not affected by water temperature. We concluded that human activities on the surrounding landscapes could be more essential sources for nutrients of aquatic ecosystems than role of ongoing climate warming. Despite the role of warming in driving nutrients availability in aquatic ecosystems, our findings suggest to take the different activities on the surrounding catchments into account in the studies caring about trophic status classification of aquatic ecosystems.

Keywords: phosphate, nitrate, anthropogenic, warming

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Authors: Mohammed Abdulridha Hamdan

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To face the water crisis, understanding the role of human activities on nutrient concentrations in aquatic ecosystems needs more investigations compare to extensively studies, which have been carried out to understand these impacts on water quality of different aquatic ecosystems. We hypothesized human activates on the catchments of Tigris river may change nutrient concentrations in water along the river. The results showed that phosphate concentration differed significantly among the studied sites due to distributed human activities, while nitrate concentration did not. Phosphate and nitrate concentrations were not affected by water temperature. We concluded that human activities on the surrounding landscapes could be more essential sources for nutrients of aquatic ecosystems than role of ongoing climate warming. Despite the role of warming in driving nutrients availability in aquatic ecosystems, our findings suggest to take the different activities on the surrounding catchments into account in the studies caring about trophic status classification of aquatic ecosystems.

Keywords: phosphate, nitrate, Anthropogenic, warming

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Authors: Ashik Sarder

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Bangladesh is a disaster-prone and one of the most vulnerable countries to climate change. The country has a long coastal area which is frequently being affected by several types of natural disasters due to climate change. The disasters have impacts on the life and livelihood of different natural resources depending on communities living in the coastal areas. The Malo is a Hindu religious traditional fishing community living at Sarafpur Union of Dumuria Upazila of Khulna district of south-west coastal Bangladesh. Fishing is the only means of their livelihood and the community has been engaged in fishing practices inherently in rivers, estuaries, and sea for more than 300 years. and they are totally dependent on this traditional occupation. But, in recent year’s climate change has negative impacts on their only livelihood option. The study aims to examine the impacts of climate change on the livelihood of Malo fishing community in south-west coastal Bangladesh, identify the adaptation strategies undertaken and practiced by Malo fishing community to cope with climate change and sustain their livelihood and explore the changing adaptation strategies undertaken by Malo fishing community and others. The study has been conducted from both qualitative and quantitative perspectives. Data has been collected from both primary and secondary sources. The primary data has been collected in the participatory observation approach following both qualitative and quantitative method. The primary source of data includes village census, face-to-face interview and in-depth case studies using structured questionnaire. The secondary source of the literature includes different national and international documents, policy papers, books and articles; related websites and peer-viewed documents on climate change, vulnerability, adaptation, livelihood, and fisheries. The study has identified different practices of adaption to climate change by Malo fishing community and others in the selected area. Three types of adaption practices have been identified. Firstly, the indigenous adaptation practices by Malo fishing community to cope with climate change have been identified. These identified adaptation practices by Malo fishing community include; ensuring drinking water and sanitation facilities, planting trees to tackle impacts of cyclone, excavating dumps to preserve the valuable assets, growing vegetables and rearing domestic livestock to earn surplus money, taking loans for ensuring continuation of present livelihood and migrating to near city or towns for better livelihood options. Secondly, adaptation initiatives undertaken by the government have provided limited facility to this vulnerable fishing community and made them benefited. And thirdly, some adaptation initiatives commenced by few non-government and community-based organizations have also made the Malo fishing community as beneficiaries. The study has suggested recommendations for Malo fishing community to overcome the challenges and impacts of climate change for retaining their traditional fishing livelihood. The accumulated recommendations would be very useful for the researchers, academicians, policy-makers of Government and non-government organizations to conduct more researches and take initiatives for Malo fishing community to make them more capable to sustain their fishing livelihood.

Keywords: climate change, livelihood, adaptation, anthropology, vulnerability

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Authors: Sajjad Sedaghat

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In this work, facile and green biosynthesis and characterization of silver–montmorillonite (MMT) nanocomposite is reported at room temperature. Silver nanoparticles (Ag–NPs) were synthesized into the interlamellar space of (MMT) by using water extract of Satureja hortensis L as reducing agent. The MMT was suspended in the aqueous AgNO₃ solution, and after the absorption of silver ions, Ag⁺ was reduced using water extract of Satureja hortensis L to Ag°. Evaluation of the antibacterial properties are also reported. The nanocomposite was characterized by ultraviolet-visible spectroscopy (UV–Vis), powder X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM). TEM study showed the formation of nanocomposite using water extract of Satureja hortensis L in the 4.88 – 26.70 nm range and average particles size were 15.79 nm also the XRD study showed that the particles have a face-centered cubic (fcc) structure. The nanocomposite showed the antibacterial properties against Gram-positive and Gram-negative bacteria.

Keywords: antibacterial effects, montmorillonite, Satureja hortensis l, transmission electron microscopy, nanocomposite

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Authors: Azhar Equbal, Anoop Kumar Sood, M. Asif Equbal, M. Israr Equbal

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In the present work response surface methodology (RSM) based central composite design (CCD) is used for analyzing the electrical discharge machining (EDM) process. For experimentation, mild steel is selected as work piece and copper is used as electrode. Three machining parameters namely current (I), spark on time (T_on) and spark off time (T_off) are selected as the input variables. The output or response chosen is material removal rate (MRR) which is to be maximized. To reduce the number of runs face centered central composite design (FCCCD) was used. ANOVA was used to determine the significance of parameter and interactions. The suitability of model is tested using Anderson darling (AD) plot. The results conclude that different parameters considered i.e. current, pulse on and pulse off time; all have dominant effect on the MRR. At last, the optimized parameter setting for maximizing MRR is found through main effect plot analysis.

Keywords: EDM, electrode, MRR, RSM, ANOVA

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Authors: Malik Assi

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This research presents a strengthening technique for enhancing the punching shear resistance of concrete flat slabs. Internal square patches of CFRP were centrally installed inside 450*450mm concrete panels during casting at a chosen distance from the tension face to produce six simply supported samples. The dimensions of those patches ranged from 50*50mm to 360*360mm. All the examined slabs contained the same amount of tensile reinforcement, had identical dimensions, were designed according to the American Concrete Institute code (ACI) and tested to failure. Compared to the control unstrengthened spacemen, all the strengthened slabs have shown an enhancement in punching capacity and stiffness. This enhancement has been found to be proportional to the area of the installed CFRP patches. In addition to the reasonably enhanced stiffness and punching shear, this strengthening technique can change the slab failure mode from shear to flexural.

Keywords: CFRP patches, Flat slabs, Flexural, Stiffness, Punching shear

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Authors: Jennifer Kehinde, Claire O'donnell, Annmarie Grealish

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Introduction: Breastfeeding has been shown to provide numerous health benefits for both infants and mothers. The decision to breastfeed is influenced by physiological, psychological, and emotional factors. However, the importance of equipping mothers with the necessary knowledge for successful breastfeeding practice cannot be ruled out. The decline in global breastfeeding rate can be linked to lack of adequate breastfeeding education during prenatal stage.This systematic review examined the effectiveness of prenatal breastfeeding education on breastfeeding uptake postpartum. Method: This review was undertaken and reported in conformity with the Preferred Reporting Items for Systemic Reviews and Meta-Analysis statement (PRISMA) and was registered on the international prospective register for systematic reviews (PROSPERO: CRD42020213853). A PICO analysis (population, intervention, comparison, outcome) was undertaken to inform the choice of keywords in the search strategy to formulate the review question which was aimed at determining the effectiveness of prenatal breastfeeding educational programs at improving breastfeeding uptake following birth. A systematic search of five databases (Cumulative Index to Nursing and Allied Health Literature, Medline, Psych INFO, and Applied Social Sciences Index and Abstracts) were searched between January 2014 until July 2021 to identify eligible studies. Quality assessment and narrative synthesis were subsequently undertaken. Results: Fourteen studies were included. All 14 studies used different types of breastfeeding programs; eight used a combination of curriculum based breastfeeding education program, group prenatal breastfeeding counselling and one-to-one breastfeeding educational programs which were all delivered in person; four studies used web-based learning platforms to deliver breastfeeding education prenatally which were both delivered online and face to face over a period of 3 weeks to 2 months with follow-up periods ranging from 3 weeks to 6 months; one study delivered breastfeeding educational intervention using mother-to-mother breastfeeding support groups in promoting exclusive breastfeeding and one study disseminated breastfeeding education to participants based on the theory of planned behaviour. The most effective interventions were those that included both theory and hands-on demonstrations. Results showed an increase in breastfeeding uptake, breastfeeding knowledge, increase in positive attitude to breastfeeding and an increase in maternal breastfeeding self-efficacy among mothers who participated in breastfeeding educational programs during prenatal care. Conclusion: Prenatal breastfeeding education increases women’s knowledge of breastfeeding. Mothers who are knowledgeable about breastfeeding and hold a positive approach towards breastfeeding have the tendency to initiate breastfeeding and continue for a lengthened period. Findings demonstrates a general correlation between prenatal breastfeeding education and increased breastfeeding uptake postpartum. The high level of positive breastfeeding outcome inherent in all the studies can be attributed to prenatal breastfeeding education. This review provides rigorous contemporary evidence that healthcare professionals and policymakers can apply when developing effective strategies to improve breastfeeding rates and ultimately improve the health outcomes of mothers and infants.

Keywords: breastfeeding, breastfeeding programs, breastfeeding self-efficacy, prenatal breastfeedng education

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Authors: John Gaber, Youssef Ahmed, Hossam A.Gabbar, Jing Ren

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Nuclear Power Plant (NPP) operators have a large responsibility on their shoulders. They must allow the plant to generate a high amount of energy while inspecting and maintaining the safety of the plant. This type of occupation comes with high amounts of mental fatigue, and a small mistake can have grave consequences. Electroencephalography (EEG) is a method of gathering the electromagnetic waves emitted by a human brain. We propose a safety system by monitoring brainwaves for signs of mental fatigue. This requires an analysis of the tasks and mental models of the NPP operator, as well as risk factors on mental fatigue and attention that NPP operators face when performing their tasks. The brain waves generated from experiencing mental fatigue can then be monitored for. These factors are analyzed, developing an EEG-based monitoring system, which aims to alert NPP operators when levels of mental fatigue and attention start affecting their performance in task completion.

Keywords: EEG, power plant operator, psychology, task analysis

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Authors: Alireza Taghdiri, Sara Ghanbarzade Ghomi

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Nowadays, steel structures are used for not only common buildings but also high-rise construction and wide span covering. The advanced methods of construction as well as the advanced structural connections have a great effect on architecture. However a better use of steel structural systems will be achieved with the deep understanding of steel structures specifications and their substantial advantages. On the other hand, the steel structures face to the different environmental factors such as air flow which cause erosion and corrosion. With the time passing, the amount of these steel mass damages and also the imposed stress will be increased. In other words, the position of erosion in steel structures related to existing stresses indicates that effective environmental conditions will gradually decrease the structural resistance of steel components and result in decreasing the durability of steel components. In this paper, the durability of different steel structural components is evaluated and on the basis of these stress, architectural strategies for designing the system and the components of steel structures is recognized in order to achieve an optimum life cycle.

Keywords: durability, bending stress, erosion in steel structure, life cycle

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Authors: Andrei Bogdan Stanescu, Laura Diaconescu

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With the increasing concerns about data breaches and privacy violations, organizations seek robust security measures to protect sensitive information. This research paper highlights the importance of implementing the Zero-Trust Security methodology using Passwordless Authentication Gateways that leverage Keycloak, an open-source Identity and Access Management (IAM) software, as a solution to address the security challenges these organizations face. The paper presents the successful implementation and deployment of such a solution in a mid-size, privacy-oriented organization. The implementation resulted in significant security improvements, reducing the risk of unauthorized access and potential data breaches. Moreover, user feedback indicated enhanced convenience and streamlined authentication experiences. The results of this study bring solid contributions in the field of cybersecurity and provide practical insights for organizations aiming to strengthen their security practices.

Keywords: identity and access management, passwordless authentication, privacy, zero-trust security

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Authors: M. A. T. AlSudairi, T. G. K. Vasista

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The concept of social media is becoming the top of the agenda for many business executives and public sector executives today. Decision makers as well as consultants, try to identify ways in which firms and enterprises can make profitable use of social media and network related applications such as Wikipedia, Face book, YouTube, Google+, Twitter. While it is fun and useful to participating in this media and network for achieving the communication effectively and efficiently, semantic and sentiment analysis and interpretation becomes a crucial issue. So, the objective of this paper is to provide literature review on social media, network and related technology related to semantics and sentiment or opinion analysis covering business and governance perspectives. In this regard, a case study on the use and adoption of Social media in Saudi Arabia has been discussed. It is concluded that semantic web technology play a significant role in analyzing the social networks and social media content for extracting the interpretational knowledge towards strategic decision support.

Keywords: CRASP methodology, formative assessment, literature review, semantic web services, social media, social networks

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Authors: Gaurav Kumar, Shilpa

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Digital libraries have been established all over the world to create, maintain and to preserve the digital materials. This paper focuses on operational digital preservation systems specifically in educational organizations in India. It considers the broad range of digital objects including e-journals, technical reports, e-records, project documents, scientific data, etc. This paper describes the main objectives, process and technological issues involved in preservation of digital materials. Digital preservation refers to the various methods of keeping digital materials alive for the future. It includes everything from electronic publications on CD-ROM to Online database and collections of experimental data in digital format maintains the ability to display, retrieve and use digital collections in the face of rapidly changing technological and organizational infrastructures elements. This paper exhibits the importance and objectives of digital preservation. The necessities of preservation are hardware and software technology to interpret the digital documents and discuss various aspects of digital preservation.

Keywords: preservation, digital preservation, digital dark age, conservation, archive, repository, document, information technology, hardware, software, organization, machine readable format

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Authors: Inuusah Mahama

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The study focused on the importance of diversity and the use of evidence-based practices and strategies in teaching learners with ASD. The study employed a mixed-methods design, including surveys, interviews, and observations. A total of 500 K-12 practitioners participated in the study, including teachers, administrators, and support staff. The study sought to investigate the current understanding and knowledge level of K-12 practitioners regarding diversity, evidence-based practices, and strategies for teaching learners with ASD. The study also examined the challenges that K-12 practitioners face in preparing learners with ASD and the resources they require to improve their practice. The results indicated that K-12 practitioners in Ghana have limited knowledge and skills in teaching learners with ASD, particularly in using evidence-based practices and strategies. Therefore, there is a need for providing training and professional development opportunities for K-12 practitioners, developing and implementing evidence-based practices and strategies, and increasing awareness of ASD and the need for effective teaching strategies. This would go a long way to improve the quality of education for learners with ASD in Ghana and ultimately lead to better outcomes for these students.

Keywords: autism, practitioners, diversity, evidence-based practises

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Authors: Mohamed Laamim, Abdelilah Rochd, Aboubakr Benazzouz, Abderrahim El Fadili

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Smart grids have recently sparked a lot of interest in the energy sector as they allow for the modernization and digitization of the existing power infrastructure. Smart grids have several advantages in terms of reducing the environmental impact of generating power from fossil fuels due to their capacity to integrate large amounts of distributed energy resources. On the other hand, smart grid technologies necessitate many field investigations and requirements. This paper focuses on the major difficulties that governments face around the world and compares them to the situation in Morocco. Also presented in this study are the current works and projects being developed to improve the penetration of smart grid technologies into the electrical system. Furthermore, the findings of this study will be useful to promote the smart grid revolution in Morocco, as well as to construct a strong foundation and develop future needs for better penetration of technologies that aid in the integration of smart grid features.

Keywords: smart grids, microgrids, virtual power plants, digital twin, distributed energy resources, vehicle-to-grid, advanced metering infrastructure.

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Authors: Jo Mitchell, Daniel Johnson

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MindMax is a digital community and learning platform built to maximise the wellbeing and resilience of AFL Players and Australian men. The MindMax application engages men, via their existing connection with sport and video games, in a range of wellbeing ideas, stories and actions, because we believe fit minds, kick goals. MindMax is an AFL Players Association led project, supported by a Movember Foundation grant, to improve the mental health of Australian males aged between 16-35 years. The key engagement and delivery strategy for the project was digital technology, sport (AFL) and video games, underpinned by evidenced based wellbeing science. The project commenced April 2015, and the expected completion date is March 2017. This paper describes the conceptual model underpinning product development, including progress, key learnings and challenges, as well as the research agenda. Evaluation of the MindMax project is a multi-pronged approach of qualitative and quantitative methods, including participatory design workshops, online reference groups, longitudinal survey methods, a naturalistic efficacy trial and evaluation of the social and economic return on investment. MindMax is focused on the wellness pathway and maximising our mind's capacity for fitness by sharing and promoting evidence-based actions that support this. A range of these ideas (from ACT, mindfulness and positive psychology) are already being implemented in AFL programs and services, mostly in face-to-face formats, with strong engagement by players. Player's experience features strongly as part of the product content. Wellbeing science is a discipline of psychology that explores what helps individuals and communities to flourish in life. Rather than ask questions about illness and poor functioning, wellbeing scientists and practitioners ask questions about wellness and optimal functioning. While illness and wellness are related, they operate as separate constructs and as such can be influenced through different pathways. The essential idea was to take the evidence-based wellbeing science around building psychological fitness to the places and spaces that men already frequent, namely sport and video games. There are 800 current senior AFL players, 5000+ past players, and 11 million boys and men that are interested in the lives of AFL Players; what they think and do to be their best both on and off field. AFL Players are also keen video gamers – using games as one way to de-stress, connect and build wellbeing. There are 9.5 million active gamers in Australia with 93% of households having a device for playing games. Video games in MindMax will be used as an engagement and learning tool. Gamers (including AFL players) can also share their personal experience of how games help build their mental fitness. Currently available games (i.e., we are not in the game creation business) will also be used to motivate and connect MindMax participants. The MindMax model is built with replication by other sport codes (e.g., Cricket) in mind. It is intended to not only support our current crop of athletes but also the community that surrounds them, so they can maximise their capacity for health and wellbeing.

Keywords: Australian football league, digital application, positive psychology, wellbeing

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Authors: Clemens Pizzinini, Philipp Rosner, David Ziegler, Markus Lienkamp

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Transportation is a constitutional part of most supply and value chains in modern economies. Smallholder farmers in rural Ethiopia face severe challenges along their supply and value chains. In particular, suitable, affordable, and available transport services are in high demand. To develop a context-specific technical solutions, a problem-to-solution methodology based on the interaction with technology is developed. With this approach, we fill the gap between proven transportation assessment frameworks and general user-centered techniques. Central to our approach is an electric test vehicle that is implemented in rural supply and value chains for research, development, and testing. Based on our objective and the derived methodological requirements, a set of existing methods is selected. Local partners are integrated into an organizational framework that executes major parts of this research endeavour in the Arsi Zone, Oromia Region, Ethiopia.

Keywords: agricultural value chain, participatory methods, agile methods, sub-Saharan Africa, Ethiopia, electric vehicle, transport service

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Authors: Gohar Rahman, Rabia Saad Ullah

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This research aims to examine the use of discourse markers within the dominion of political speeches, differentiating between genders. The analysis centers on twelve speakers, comprising six males and six females. Speeches selected include commencement, victory, state union addresses, campaigns, and presidential speeches. Halliday and Hasan's cohesion framework, specifically discourse markers, is utilized as a theoretical framework. Data is quantitatively analyzed using AntConc to identify marker frequency. The findings are presented through Excel's tables and graphs, suggesting differences in discourse marker preferences between genders. The findings suggest a divergence in the preferences for discourse markers between males and females. However, asserting that females utilize discourse markers more frequently due to the increased use of filler words, face threat mitigation, and polite speech would be an exaggeration. The disparity in frequency is not substantial, suggesting that males and females exhibit varying language inclinations to some degree.

Keywords: discourse markers, political discourse, gender, speeches, language

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Authors: Wala A. Bagunaid, Maram Meccawy, Arwa Allinjawi, Zilal Meccawy

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Continuous self-assessment becomes crucial in self-paced online learning environments. Students often depend on themselves to assess their progress; which is considered an essential requirement for any successful learning process. Today’s education institutions face major problems around student motivation and engagement. Thus, personalized e-learning systems aim to help and guide the students. Gamification provides an opportunity to help students for self-assessment and social comparison with other students through attempting to harness the motivational power of games and apply it to the learning environment. Furthermore, Open Social Student Modeling (OSSM) as considered as the latest user modeling technologies is believed to improve students’ self-assessment and to allow them to social comparison with other students. This research integrates OSSM approach and gamification concepts in order to provide self-assessment for English language learners at King Abdulaziz University (KAU). This is achieved through an interactive visual representation of their learning progress.

Keywords: e-learning system, gamification, motivation, social comparison, visualization

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Authors: María Victoria Alvarez Magañini, Lautaro Nahuel Rubbi

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According to different theories, the hegemonic war between the United States and the People's Republic of China seems to be imminent. However, nowadays, it is clear that China's conventional military capacity is inferior to that of the United States. Nevertheless, the conditions that in the past were considered to be an indicator of validity in asymmetrical warfare, at present, in a possible asymmetric war scenario, are no longer considered to be taken as such. The military capacity is not the only concept that represents the main indicator of victory. The organisation and the use of forces are also an essential part of it. The present paper aims to analyze the Chinese Defense Strategy in relation to the concept of asymmetric warfare in the face of a possible war with the United States. The starting point will be developed on the basis of application of the theory which corresponds to the concept aforementioned making focus on recent developments of the People’s Republic of China in the field of non-conventional defense. A comparative analysis of the conventional forces of both powers/countries will also be carried out.

Keywords: asymmetric warfare, China, United States, hegemonic warfare

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Authors: Ayoub Daoudi, Javad Eslami, Anne-Lise Beaucour, Martin Vigroux, Albert Noumowé

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As a fact, many cultural heritage masonry buildings have undergone violent fires during their history. In order to investigate the high temperature behaviour of stone masonry, six French limestones were heated to 600 °C at a rate of 9 °C/min. The main focus is the comparison between the high temperature behaviour of stones at the material and at the structural scale. In order to evaluate the risk of spalling, the tests have been carried out on the stone blocks (12x30x30 cm) instrumented with thermocouples and subjected to an unidirectional heating on one face. Thereafter, visual assessments and non-destructive measurements (dynamic elastic modulus) performed on blocks demonstrate a different behaviour from what was observed at the material scale. Finally, a series of thermo-mechanical computations, using finite element method, allowed us to highlight the difference between the behaviour of stones at material and block scales.

Keywords: limestones, hight temperature behaviour, damage, thermo-mechanical modeling, material and blocks scales, color change

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Authors: Yousef Abu Nahleh, Alhasan Hakami, Arun Kumar, Fugen Daver

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This study considers the problem of calculating safety stocks in disaster situations inventory systems that face demand uncertainties. Safety stocks are essential to make the supply chain, which is controlled by forecasts of customer needs, in response to demand uncertainties and to reach predefined goal service levels. To solve the problem of uncertainties due to the disaster situations affecting the industry sector, the concept of Emergency Safety Stock (ESS) was proposed. While there exists a huge body of literature on determining safety stock levels, this literature does not address the problem arising due to the disaster and dealing with the situations. In this paper, the problem of improving the Order Quantity Model to deal with uncertainty of demand due to disasters is managed by incorporating a new idea called ESS which is based on the probability of disaster occurrence and uses probability matrix calculated from the historical data.

Keywords: Emergency Safety Stocks, safety stocks, Order Quantity Model, supply chain

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Authors: Damith Tennakoon, Mojgan Jadidi, Seyedreza Razavialavi

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With recent advancements of automation in robotics, from self-driving cars to autonomous 4-legged quadrupeds, one industry that has been stagnant is the construction industry. The methodologies used in a modern-day construction site consist of arduous physical labor and the use of heavy machinery, which has not changed over the past few decades. The dangers of a modern-day construction site affect the health and safety of the workers due to performing tasks such as lifting and moving heavy objects and having to maintain unhealthy posture to complete repetitive tasks such as painting, installing drywall, and laying bricks. Further, training for heavy machinery is costly and requires a lot of time due to their complex control inputs. The main focus of this research is using immersive wearable technology and robotic arms to perform the complex and intricate skills of modern-day construction workers while alleviating the physical labor requirements to perform their day-to-day tasks. The methodology consists of mounting a stereo vision camera, the ZED Mini by Stereolabs, onto the end effector of an industrial grade robotic arm, streaming the video feed into the Virtual Reality (VR) Meta Quest 2 (Quest 2) head-mounted display (HMD). Due to the nature of stereo vision, and the similar field-of-views between the stereo camera and the Quest 2, human-vision can be replicated on the HMD. The main advantage this type of camera provides over a traditional monocular camera is it gives the user wearing the HMD a sense of the depth of the camera scene, specifically, a first-person view of the robotic arm’s end effector. Utilizing the built-in cameras of the Quest 2 HMD, open-source hand-tracking libraries from OpenXR can be implemented to track the user’s hands in real-time. A mixed-reality (XR) Unity application can be developed to localize the operator's physical hand motions with the end-effector of the robotic arm. Implementing gesture controls will enable the user to move the robotic arm and control its end-effector by moving the operator’s arm and providing gesture inputs from a distant location. Given that the end effector of the robotic arm is a gripper tool, gripping and opening the operator’s hand will translate to the gripper of the robot arm grabbing or releasing an object. This human-robot interaction approach provides many benefits within the construction industry. First, the operator’s safety will be increased substantially as they can be away from the site-location while still being able perform complex tasks such as moving heavy objects from place to place or performing repetitive tasks such as painting walls and laying bricks. The immersive interface enables precision robotic arm control and requires minimal training and knowledge of robotic arm manipulation, which lowers the cost for operator training. This human-robot interface can be extended to many applications, such as handling nuclear accident/waste cleanup, underwater repairs, deep space missions, and manufacturing and fabrication within factories. Further, the robotic arm can be mounted onto existing mobile robots to provide access to hazardous environments, including power plants, burning buildings, and high-altitude repair sites.

Keywords: construction automation, human-robot interaction, hand-tracking, mixed reality

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Authors: A. Gonzalez Aguna, J. M. Santamaria Garcia, J. L. Gomez Gonzalez, R. Barchino Plata, M. Fernandez Batalla, S. Herrero Jaen

Abstract:

Background: Computer Science is a field that transcends other disciplines of knowledge because it allows to support all kinds of physical and mental tasks. Health centres have a greater number and complexity of technological devices and the population consume and demand services derived from technology. Also, nursing education plans have included competencies related to and, even, courses about new technologies are offered to health professionals. However, nurses still limit their performance to the use and evaluation of products previously built. Objective: Develop a teaching-learning methodology for acquiring skills on designing applications for care. Methodology: Blended learning teaching with a group of graduate nurses through official training within a Master's Degree. The study sample was selected by intentional sampling without exclusion criteria. The study covers from 2015 to 2017. The teaching sessions included a four-hour face-to-face class and between one and three tutorials. The assessment was carried out by written test consisting of the preparation of an IEEE 830 Standard Specification document where the subject chosen by the student had to be a problem in the area of care. Results: The sample is made up of 30 students: 10 men and 20 women. Nine students had a degree in nursing, 20 diploma in nursing and one had a degree in Computer Engineering. Two students had a degree in nursing specialty through residence and two in equivalent recognition by exceptional way. Except for the engineer, no subject had previously received training in this regard. All the sample enrolled in the course received the classroom teaching session, had access to the teaching material through a virtual area and maintained at least one tutoring. The maximum of tutorials were three with an hour in total. Among the material available for consultation was an example of a document drawn up based on the IEEE Standard with an issue not related to care. The test to measure competence was completed by the whole group and evaluated by a multidisciplinary teaching team of two computer engineers and two nurses. Engineers evaluated the correctness of the characteristics of the document and the degree of comprehension in the elaboration of the problem and solution elaborated nurses assessed the relevance of the chosen problem statement, the foundation, originality and correctness of the proposed solution and the validity of the application for clinical practice in care. The results were of an average grade of 8.1 over 10 points, a range between 6 and 10. The selected topic barely coincided among the students. Examples of care areas selected are care plans, family and community health, delivery care, administration and even robotics for care. Conclusion: The applied methodology of learning-teaching for the design of technologies demonstrates the success in the training of nursing professionals. The role of expert is essential to create applications that satisfy the needs of end users. Nursing has the possibility, the competence and the duty to participate in the process of construction of technological tools that are going to impact in care of people, family and community.

Keywords: care, learning, nursing, technology

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Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani

Abstract:

Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.

Keywords: color space, neural network, random forest, skin detection, statistical feature

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Authors: Sahar S. Moursi

Abstract:

Due to the unique background of the Saudi female international students who study in western institutes, they face tough challenges as English as a second language (ESL) learners. This paper draws on a Ph.D. study that examines a wide range of challenges faced by Saudi female international students when they study the English language and other academic subjects in a new culture. This research project followed the phenomenological approach and, more specifically, used the in-depth interview to provide an opportunity to the seven female participants to make their voices heard through telling their stories. The data analysis indicated that the Saudi female international students who study in western institutes are faced with religious and cultural challenges that impact their academic performance. This study is significant for the authorities in Saudi Arabia and the hosting universities as it gives essential recommendations to both sides of the aisle. It also provides the Saudi female international students with vital recommendations to better cope with those challenges.

Keywords: English language learners, religious and cultural background, Saudi female students, tough challenges

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Authors: Mikhail Gritskevich, Sebastian Hohenstein

Abstract:

The paper presents the results of a detailed assessment of several modern Reynolds Averaged Navier-Stokes (RANS) turbulence models for prediction of C3X vane film cooling at various injection regimes. Three models are considered, namely the Shear Stress Transport (SST) model, the modification of the SST model accounting for the streamlines curvature (SST-CC), and the Explicit Algebraic Reynolds Stress Model (EARSM). It is shown that all the considered models face with a problem in prediction of the adiabatic effectiveness in the vicinity of the cooling holes; however, accounting for the Reynolds stress anisotropy within the EARSM model noticeably increases the solution accuracy. On the other hand, further downstream all the models provide a reasonable agreement with the experimental data for the adiabatic effectiveness and among the considered models the most accurate results are obtained with the use EARMS.

Keywords: discrete holes film cooling, Reynolds Averaged Navier-Stokes (RANS), Reynolds stress tensor anisotropy, turbulent heat transfer

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Authors: Armin Nabaei, M. Omair Ahmad, M. N. S. Swamy

Abstract:

Many facial expression and emotion recognition methods in the traditional approaches of using LDA, PCA, and EBGM have been proposed. In recent years deep learning models have provided a unique platform addressing by automatically extracting the features for the detection of facial expression and emotions. However, deep networks require large training datasets to extract automatic features effectively. In this work, we propose an efficient emotion detection algorithm using face images when only small datasets are available for training. We design a deep network whose feature extraction capability is enhanced by utilizing several parallel modules between the input and output of the network, each focusing on the extraction of different types of coarse features with fined grained details to break the symmetry of produced information. In fact, we leverage long range dependencies, which is one of the main drawback of CNNs. We develop this work by introducing a Dynamic Soft-Margin SoftMax.The conventional SoftMax suffers from reaching to gold labels very soon, which take the model to over-fitting. Because it’s not able to determine adequately discriminant feature vectors for some variant class labels. We reduced the risk of over-fitting by using a dynamic shape of input tensor instead of static in SoftMax layer with specifying a desired Soft- Margin. In fact, it acts as a controller to how hard the model should work to push dissimilar embedding vectors apart. For the proposed Categorical Loss, by the objective of compacting the same class labels and separating different class labels in the normalized log domain.We select penalty for those predictions with high divergence from ground-truth labels.So, we shorten correct feature vectors and enlarge false prediction tensors, it means we assign more weights for those classes with conjunction to each other (namely, “hard labels to learn”). By doing this work, we constrain the model to generate more discriminate feature vectors for variant class labels. Finally, for the proposed optimizer, our focus is on solving weak convergence of Adam optimizer for a non-convex problem. Our noteworthy optimizer is working by an alternative updating gradient procedure with an exponential weighted moving average function for faster convergence and exploiting a weight decay method to help drastically reducing the learning rate near optima to reach the dominant local minimum. We demonstrate the superiority of our proposed work by surpassing the first rank of three widely used Facial Expression Recognition datasets with 93.30% on FER-2013, and 16% improvement compare to the first rank after 10 years, reaching to 90.73% on RAF-DB, and 100% k-fold average accuracy for CK+ dataset, and shown to provide a top performance to that provided by other networks, which require much larger training datasets.

Keywords: computer vision, facial expression recognition, machine learning, algorithms, depp learning, neural networks

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