Search results for: enabling

Authors: Shimaa Nagro, Russell Campion

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Mobile devices are becoming ever more widely available, with growing functionality, and they are increasingly used as enabling technology to give students access to educational material anytime and anywhere. However, the design of educational material's user interfaces for mobile devices is beset by many unresolved research problems such as those arising from constraints associated with mobile devices or from issues linked to effective learning. The proposed research aims to produce: (i) a method framework for the design and evaluation of educational material’s interfaces to be delivered on mobile devices, in multimedia form based on Human Computer Interaction strategies; and (ii) a software tool implemented as a fast-track alternative to use the method framework in full. The investigation will combine qualitative and quantitative methods, including interviews and questionnaires for data collection and three case studies for validating the method framework. The method framework is a framework to enable an educational designer to effectively and efficiently create educational multimedia interfaces to be used on mobile devices by following a particular methodology that contains practical and usable tools and techniques. It is a method framework that accepts any educational material in its final lesson plan and deals with this plan as a static element, it will not suggest any changes in any information given in the lesson plan but it will help the instructor to design his final lesson plan in a multimedia format to be presented in mobile devices.

Keywords: mobile learning, M-Learn, HCI, educational multimedia, interface design

Procedia PDF Downloads 346

Authors: Rana Praween Kumar

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Preterm-low birth weight delivery is a major cause of infant morbidity and mortality in developing countries and has been linked to poor periodontal health during pregnancy. Gingivitis and chronic periodontitis are highly prevalent chronic inflammatory oral diseases. The detection and diagnosis of these common diseases is a fundamentally important component of oral health care. This study is intended to investigate predisposing and enabling factors as determinants of oral health indicators in pregnancy as well as the association between periodontal problems during pregnancy with age and socio economic status of the individual. A community –based prospective cohort study will be conducted in Jamshedpur, Jharkhand, India among pregnant women using completed interviews and a full mouth oral clinical examination using the CPITN (Community Periodontal Index of Treatment Need) and OHI-S (Simplified Oral Hygiene) indices with adequate sample size and informed consent to the patient following proper inclusion and exclusion criteria. Multiple logistic regression analyses will be used to identify independent determinants of periodontal problems and use of dental services during pregnancy. Analysis of covariance (ANCOVA) will be used to investigate the relationship between periodontal problems with the age and socioeconomic status. The result will help in proper monitoring of periodontal health during pregnancy encouraging the delivery of healthy child and the maintenance of proper health of the mother.

Keywords: infant, periodontal problems, pregnancy, pre-term-low birth weight delivery

Procedia PDF Downloads 128

Authors: Jutamas Wisansing, Thanakarn Vongvisitsin, Udom Hongchatikul

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Food could be used to open up a dialogue about local heritage. Contributing to the world sustainable consumption mission, this research aims to explore the linkages between agriculture, senses of place and performing arts. Thailand and its destination marketing ‘Discover Thainess’ was selected as a working principle, enabling a case example of how the three elements could be conceptualized. The model offered an integrated institutional arrangement where diverse entities could be formed to design how Thainess (local heritage) could be interpreted and embedded into an art of food. Using case study research approach, three areas (Chiangmai, Samutsongkram and Ban Rai Gong King) representing 3 different scales of tourism development were selected. Based on a theoretical analysis, a working model was formulated. An action research was then designed to experiment how the model could be materialized. Brainstorming elicitation and in-depth interview were employed to reflect on how each element could be integrated. The result of this study offered an innovation on how food tourism could be profoundly interpreted and how tourism development could enhance value creation for agricultural based community. The outcomes of the research present co-creative multi-stakeholder model and the value creation method through the whole supply chain of Thai gastronomy. The findings have been eventually incorporated into ‘gastro-diplomacy’ strategy for Thai tourism.

Keywords: community-based tourism, gastro-diplomacy, gastronomy tourism, sustainable tourism development

Procedia PDF Downloads 280

Authors: Ahmed Fradi

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Nowadays, recent technological advances in the acquisition, modeling, and processing of three-dimensional (3D) objects data lead to the creation of models stored in huge databases, which are used in various domains such as computer vision, augmented reality, game industry, medicine, CAD (Computer-aided design), 3D printing etc. On the other hand, the industry is currently benefiting from powerful modeling tools enabling designers to easily and quickly produce 3D models. The great ease of acquisition and modeling of 3D objects make possible to create large 3D models databases, then, it becomes difficult to navigate them. Therefore, the indexing of 3D objects appears as a necessary and promising solution to manage this type of data, to extract model information, retrieve an existing model or calculate similarity between 3D objects. The objective of the proposed research is to develop a framework allowing easy and fast access to 3D objects in a CAD models database with specific indexing algorithm to find objects similar to a reference model. Our main objectives are to study existing methods of similarity calculation of 3D objects (essentially shape-based methods) by specifying the characteristics of each method as well as the difference between them, and then we will propose a new approach for indexing and comparing 3D models, which is suitable for our case study and which is based on some previously studied methods. Our proposed approach is finally illustrated by an implementation, and evaluated in a professional context.

Keywords: CAD, 3D object retrieval, shape based retrieval, similarity calculation

Procedia PDF Downloads 237

Authors: Jing Hu, Dong Yang

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With the increasingly difficult development and operating environment of exploration, there are many new challenges and difficulties in developing and exploiting oil and gas resources. These include the ability to dynamically monitor wells and provide data and assurance for the completion and production of high-cost and complex wells. A key technology in providing these assurances and maximizing oilfield profitability is real-time permanent reservoir monitoring. The emergence of optical fiber sensing systems has gradually begun to replace traditional electronic systems. Traditional temperature sensors can only achieve single-point temperature monitoring, but fiber optic sensing systems based on the Bragg grating principle have a high level of reliability, accuracy, stability, and resolution, enabling cost-effective monitoring, which can be done in real-time, anytime, and without well intervention. Continuous data acquisition is performed along the entire wellbore. The integrated package with the downhole pressure gauge, packer, and surface system can also realize real-time dynamic monitoring of the pressure in some sections of the downhole, avoiding oil well intervention and eliminating the production delay and operational risks of conventional surveys. Real-time information obtained through permanent optical fibers can also provide critical reservoir monitoring data for production and recovery optimization.

Keywords: PDHM, optical fiber, coiled tubing, photoelectric composite cable, digital-oilfield

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Authors: Maaly Jarrah

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In a study abroad context, students have the advantage of immersing themselves in the environment of the target language and being exposed to it. However, in and a stay home context, where English is not the mother tongue, students’ exposure to the second language is often times restricted to the classroom. Although language teachers are keen to develop inside class room activities and practices that increase the suitability of students to acquire a second language (Cook & Singleton, 2014), many would agree that class time is too limited to enhance students’ oral fluency skills. Consequently, creating opportunities outside the classroom for students to speak English is an effective strategy in compensating for students’ limited use of the L2. In an argument by Ortega (2012) external classroom activities have equal significance in enabling students learn English as a second language. The author further asserts that the activities provide a non-educational environment from which a student may feel free and comfortable to acquire new language skills. This study investigates the significance of outside classroom activities in promoting students’ oral proficiency. In addition, it reports on students’ perceptions of such activities. 15 participants from the American University of Kuwait took part in this study. Open-ended interviews were done to find out what the participants thought of these activities, and what they gained from them. Interview results show that students found outside classroom activities very effective in improving not only their oral fluency skills, but their confidence and critical thinking skills as well. The implications of this research study are for language practitioners and language programs in the EFL context to be aware of the benefits of incorporating outside classroom activities in language teaching.

Keywords: language teaching, oral fluency, outside classroom activities

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Authors: Aya Belal, Ahmed Maher Eltair, Maggie Ahmed Mashaly

Abstract:

Geopolymer concrete is gaining recognition as a sustainable alternative to conventional Portland Cement concrete due to its environmentally friendly nature, which is a key goal for Smart City initiatives. It has demonstrated its potential as a reliable material for the design of structural elements. However, the production of Geopolymer concrete is hindered by batch-to-batch variations, which presents a significant challenge to the widespread adoption of Geopolymer concrete. To date, Machine learning has had a profound impact on various fields by enabling models to learn from large datasets and predict outputs accurately. This paper proposes an integration between the current drift to Artificial Intelligence and the composition of Geopolymer mixtures to predict their mechanical properties. This study employs Python software to develop machine learning model in specific Decision Trees. The research uses the percentage oxides and the chemical composition of the Alkali Solution along with the curing conditions as the input independent parameters, irrespective of the waste products used in the mixture yielding the compressive strength of the mix as the output parameter. The results showed 90 % agreement of the predicted values to the actual values having the ratio of the Sodium Silicate to the Sodium Hydroxide solution being the dominant parameter in the mixture.

Keywords: decision trees, geopolymer concrete, machine learning, smart cities, sustainability

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Authors: Meenu Mehta, Munish Garg

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The use of oral anticancer drugs from AYUSH system of medicine is widely increased among the society due to their low cost, enhanced efficacy, increased patient preference, lack of inconveniences related to infusion and they provide an opportunity to develop chronic treatment regimens. However, oral delivery of these drugs usually laid down by the limited bioavailability of the drug, which is associated with a wide variation. As most of the cytotoxic agents have a narrow therapeutic window and are dosed at or near the maximum tolerated dose, a wide variability in the bioavailability can negatively affect treatment result. It is estimated that 40% of active substances are poorly soluble in water. The improvement of bio-availability of drugs with such properties presents one of the greatest challenges in drug formulations. There are several techniques reported in literature. Among all these Self Emulsifying Drug Delivery System (SEDDS) has gained more attention due to enhanced oral bio-availability enabling a reduction in dose. Thus, SEDDS anticancer drugs will have the increased bioavailability and efficacy. These dosage form will provide societal benefit in a cost-effective manner as compared to other oral dosage forms. Present study reflects on the formulation strategies as SEDDS for oral anticancer agents of AYUSH system for enhanced bioavailability with proven efficacy by cancer cell lines.

Keywords: anticancer agents, AYUSH system, bioavailability, SEDDS

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Authors: Kwaku Damoah

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This paper presents a methodology and software application (App) designed to empower users in accessing, retrieving, and comparatively exploring data within the hierarchical network framework of the Government Finance Statistics (GFS) system. It explores the ease of navigating the GFS system and identifies the gaps filled by the new methodology and App. The GFS, embodies a complex Hierarchical Network Classification (HNC) structure, encapsulating institutional units, revenues, expenses, assets, liabilities, and economic activities. Navigating this structure demands specialized knowledge, experience, and skill, posing a significant challenge for effective analytics and fiscal policy decision-making. Many professionals encounter difficulties deciphering these classifications, hindering confident utilization of the system. This accessibility barrier obstructs a vast number of professionals, students, policymakers, and the public from leveraging the abundant data and information within the GFS. Leveraging R programming language, Data Science Analytics and Machine Learning, an efficient methodology enabling users to access, navigate, and conduct exploratory comparisons was developed. The machine learning Fiscal Analytics App (FLOWZZ) democratizes access to advanced analytics through its user-friendly interface, breaking down expertise barriers.

Keywords: data science, data wrangling, drilldown analytics, government finance statistics, hierarchical network classification, machine learning, web application.

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Authors: Jonas Colin

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Standing at the vanguard of AI development, Alpha represents an unprecedented synthesis of logical rigor and human abstraction, meticulously crafted to mirror the user's unique persona and personality, a feat previously unattainable in AI development. Alpha, an avant-garde artefact in the realm of artificial intelligence, epitomizes a paradigmatic shift in personalized digital interaction, amalgamating user-specific dialogic patterns with the sophisticated algorithmic prowess of OpenAI's GPT-3.5 to engender a platform for enhanced metacognitive engagement and individualized user experience. Underpinned by a sophisticated algorithmic framework, Alpha integrates vast datasets through a complex interplay of neural network models and symbolic AI, facilitating a dynamic, adaptive learning process. This integration enables the system to construct a detailed user profile, encompassing linguistic preferences, emotional tendencies, and cognitive styles, tailoring interactions to align with individual characteristics and conversational contexts. Furthermore, Alpha incorporates advanced metacognitive elements, enabling real-time reflection and adaptation in communication strategies. This self-reflective capability ensures continuous refinement of its interaction model, positioning Alpha not just as a technological marvel but as a harbinger of a new era in human-computer interaction, where machines engage with us on a deeply personal and cognitive level, transforming our interaction with the digital world.

Keywords: chatbot, GPT 3.5, metacognition, symbiose

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Authors: Lina Vyas, Stuti Rawat

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The COVID-19 outbreak has forced many employees to extensively adopt remote work or, widely known as work from home (WFH) arrangements. During the last two years, both employers and employees have had the opportunity to be increasingly aware of the benefits and drawbacks of WFH. Likewise, it gained the attention of academics from various schools of thought who have been interested in the future of work practices and work-life balance. Additionally, employees might also have various demands regarding their work practices after the pandemic. This study explores the potential of hybrid ways of working in the post-pandemic period by comparing first-timers who (sometimes or always) worked from home during the pandemic with those who did not, in terms of the aspects of work-life balance, work-life interference, job performance and willingness to work from home after the pandemic. The quantitative research approach was adopted. Data were collected via an online questionnaire from employees working from home in Hong Kong during the pandemic. There were one thousand three hundred and twenty-eight responses, but only 1,235 respondents experienced working from home during the pandemic. The findings reveal that 72.2% never had or hardly experienced work from home prior to the pandemic. There were statistically significant differences between first-timers and non-first-timers in work-life balance and work-life interference. The study also found that first-timers who were always working from home during the pandemic would prefer having longer WFH after the pandemic than those who were sometimes working from home. These results would serve as a basis for policy development, enabling policymakers to design appropriate HR policies and amend them to meet the current context of actual employee needs.

Keywords: hybrid working mode, remote working, work from home, work-life balance, workplace

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Authors: Md Yeasin, Ranjit Kumar Paul

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In recent years, recommendation systems have become indispensable tools for agricultural system. The accurate and timely recommendations can significantly impact crop yield and overall productivity. Causal inference modeling aims to establish cause-and-effect relationships by identifying the impact of variables or factors on outcomes, enabling more accurate and reliable recommendations. New advancements in causal inference models have been found in the literature. With the advent of the modern era, deep learning and machine learning models have emerged as efficient tools for modeling. This study proposed an innovative approach to enhance recommendation systems-based machine learning based casual inference model. By considering the causal effect and opportunity cost of covariates, the proposed system can provide more reliable and actionable recommendations for cereal farmers. To validate the effectiveness of the proposed approach, experiments are conducted using cereal cultivation data of eastern India. Comparative evaluations are performed against existing correlation-based recommendation systems, demonstrating the superiority of the advanced causal inference modeling approach in terms of recommendation accuracy and impact on crop yield. Overall, it empowers farmers with personalized recommendations tailored to their specific circumstances, leading to optimized decision-making and increased crop productivity.

Keywords: agriculture, casual inference, machine learning, recommendation system

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Authors: Nadiya Didyk

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This thesis deals with the unique history of the emergence of the Ukrainian feminist movement. Ukrainian feminism is still in its making, so the field is under-investigated in general. Nevertheless, the perspective of political economy and the enabling and constraining effects of capitalist dynamics are almost absent from the research on the emergence and the development of the feminist movement in Ukraine. This research was inspired by Hetland and Goodwin’s approach and an attempt to test their approach on the case of the Ukrainian feminist movement. Hetland and Goodwin claim that many scholars tend to neglect political economy from analysis of feminism as a new social movements, namely because such movement are not about class or materialist concerns, and thus have no discernible connection to capitalism. Both scholars, however, point out that there at least four ways in which capitalism has been of high importance for any social movement. Accordingly, the following issues are analysed in this paper: capitalism as the facilitator of the emergence and development of Ukrainian feminism; the influence of class balance in society on the formation of the Ukrainian feminist movement, and the ways in which class divisions within the movement shape its goals and strategies. This paper also focuses on the role of capitalist institutions and free wage labour expansion in shaping collective feminist identities and solidarities. Specific attention is paid to the representativeness of women in the highest echelons in business and politics under the capitalist systems. This study shows that there is a significant hole in the literature regarding the feminist movement in Ukraine and aims to motivate further detailed research.

Keywords: feminism, hetland, goodwin, new soical movements, political economy

Procedia PDF Downloads 291

Authors: Ali Almadan, Anoop Krishnan, Ajita Rattani

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Facial recognition is a widely adopted technology in surveillance, border control, healthcare, banking services, and lately, in mobile user authentication with Apple introducing “Face ID” moniker with iPhone X. A lot of research has been conducted in the area of face recognition on datasets captured by surveillance cameras, DSLR, and mobile devices. Recently, face recognition technology has also been deployed on body-worn cameras to keep officers safe, enabling situational awareness and providing evidence for trial. However, limited academic research has been conducted on this topic so far, without the availability of any publicly available datasets with a sufficient sample size. This paper aims to advance research in the area of face recognition using body-worn cameras. To this aim, the contribution of this work is two-fold: (1) collection of a dataset consisting of a total of 136,939 facial images of 102 subjects captured using body-worn cameras in in-door and daylight conditions and (2) evaluation of various deep-learning architectures for face identification on the collected dataset. Experimental results suggest a maximum True Positive Rate(TPR) of 99.86% at False Positive Rate(FPR) of 0.000 obtained by SphereFace based deep learning architecture in daylight condition. The collected dataset and the baseline algorithms will promote further research and development. A downloadable link of the dataset and the algorithms is available by contacting the authors.

Keywords: face recognition, body-worn cameras, deep learning, person identification

Procedia PDF Downloads 141

Authors: Thomas Yeboah

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In contemporary times, the incessant movement of northern children especially girls to southern Ghana at the detriment of their education is worrisome. Due to the misplaced mindset of the migrants concerning southern Ghana, majority of them move without an idea of where to stay and what to do exposing them to hash conditions of living. Majority find menial work in cocoa farms, illegal mining and head porterage business. This study was conducted in the Kumasi Metropolis to ascertain the major causes of child migration from the northern part of Ghana to the south and their living conditions. Both qualitative and quantitative tools of data collection and analysis were employed. The purposive sampling technique was used to select 90 migrants below 18 years. Specifically, interviews, focus group discussions and questionnaires were used to elicit responses from the units of analysis. The study revealed that the major cause of child migration from northern Ghana to the south is poverty. It was evident that respondents were vulnerable to the new environment in which they lived. They are exposed to harsh environmental conditions; sexual, verbal and physical assault; and harassment from arm robbers. The paper recommends that policy decisions should be able to create an enabling environment for the labour force in the north to ameliorate the compelling effects poverty has on child migration. Efforts should also be made to create a proper psychological climate in the minds of the children regarding their destination areas through sensitization and education.

Keywords: child migration, vulnerability, social exclusion, child labour, Ghana

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Authors: Eleni Giouli

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Distance learning provides a flexible approach to education, enabling busy learners to complete their coursework at their own pace, on their own schedule, and from a convenient location. This flexibility combined with a series of other issues; make the benefits of lifelong distance learning numerous. The purpose of the paper is to investigate whether distance education can contribute to the improvement of adult skills in Greece, highlighting in this way the necessity of the lifelong distance learning. To investigate this goal, a questionnaire is constructed and analyzed based on responses from 3,016 attendees of lifelong distance learning programs in the e-learning of the National and Kapodistrian University of Athens in Greece. In order to do so, a series of relationships is examined including the effects of a) the gender, b) the previous educational level, c) the current employment status, and d) the method used in the distance learning program, on the development of new general, technical, administrative, social, cultural, entrepreneurial and green skills. The basic conclusions that emerge after using a binary logistic framework are that the following factors are critical in order to develop new skills: the gender, the education level and the educational method used in the lifelong distance learning program. The skills more significantly affected by those factors are the acquiring new skills in general, as well as acquiring general, language and cultural, entrepreneurial and green skills, while for technical and social skills only gender and educational method play a crucial role. Moreover, routine skills and social skills are not affected by the four factors included in the analysis.

Keywords: adult skills, distance learning, education, lifelong learning

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Authors: P. S. Jagadeesh Kumar, S. Meenakshi Sundaram

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With the increase of prevailing non-traditional rivalry, mobile banking experiences an ever changing commercial backdrop. Substantial customer demands have established to be more intricate as customers request more expediency and superintend over their banking services. To enterprise advance and modernization in mobile banking applications, it is gradually obligatory to deeply leapfrog the scuffle using business model transformation. The dramaturgical vicissitudes taking place in mobile banking entail advanced traditions to exploit security. By reforming and transforming older back office into integrated mobile banking applications, banks can engender a supple and nimble banking environment that can rapidly respond to new business requirements over cloud computing. Cloud computing is transfiguring ecosystems in numerous industries, and mobile banking is no exemption providing services innovation, greater flexibility to respond to improved security and enhanced business intelligence with less cost. Cloud technology offer secure deployment possibilities that can provision banks in developing new customer experiences, empower operative relationship and advance speed to efficient banking transaction. Cloud adoption is escalating quickly since it can be made secured for commercial mobile banking transaction through backend as a service in scrutinizing the security strategies of the cloud service provider along with the antiquity of transaction details and their security related practices.

Keywords: cloud adoption, backend as a service, business intelligence, secured mobile banking

Procedia PDF Downloads 232

Authors: Kamakshaiah Kolli, R. Seshadri

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Water is a key resource in all economic activities ranging from agriculture to industry. Only a tiny fraction of the planet's abundant water is available to us as fresh water. Assessment of water quality has always been paramount in the field of environmental quality management. It is the foundation for health, hygiene, progress and prosperity. With ever increasing pressure of human population, there is severe stress on water resources. Therefore efficient water management is essential to civil society for betterment of quality of life. The present study emphasizes on the groundwater quality, sources of ground water contamination, variation of groundwater quality and its spatial distribution. The bases for groundwater quality assessment are groundwater bodies and representative monitoring network enabling determination of chemical status of groundwater body. For this study, water samples were collected from various areas of the entire corporation area of Guntur. Water is required for all living organisms of which 1.7% is available as ground water. Water has no calories or any nutrients, but essential for various metabolic activities in our body. Chemical and physical parameters can be tested for identifying the portability of ground water. Electrical conductivity, pH, alkalinity, Total Alkalinity, TDS, Calcium, Magnesium, Sodium, Potassium, Chloride, and Sulphate of the ground water from Guntur district: Different areas of the District were analyzed. Our aim is to check, if the ground water from the above areas are potable or not. As multivariate are present, Data mining technique using JRIP rules was employed for classifying the ground water.

Keywords: groundwater, water quality standards, potability, data mining, JRIP, PCA, classification

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Authors: Maulana Ayoub Ali

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“Both Socialist as well as the capitalist in the economic systems have proven their failure to ensure economic justice that serves to benefit all in the society, both the rich and the poor. In particular, capitalism is currently causing a terrifying scenario by making the rich richer and the poor poorer” . In this paper, the author looks at the level of exploitation which is taking place to small and middle entrepreneurs (SME’s), government and private employees as well as large investors in East African countries who depends on interest-based loans which undermines their lives every day due to heavy monthly returns. Numbers of families have been evicted from their family premises and SME’s properties have been attached in the courts due to failure to return their loans timely. In fact, there are a lot of issues which have taken place on the ground which badly affected number of families socially and most importantly economically due to engagement in interest-based loans offered by commercial banks in East Africa. This paper looks on the alternative ways of eliminating interest-based loans to better lives of devastated Africans who are almost “dying” of heavy debts generated through higher interest loans. Reaching to that particular root the author has visited various literatures in a bid to deeply investigate and find out the best alternative mode of enabling African SME’s, businessmen and employees to benefit from the interest-free loans. The question is whether interest-free loans can be a long term solution towards poverty alleviation in East Africa generally and Tanzania in particular.

Keywords: interest-free loans, SME’s, financial institutions, poverty, east Africa

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Authors: Kirsty Liddiard

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In this paper, we detail the politics and practicalities of co-produced disability research with disabled young people with life-limiting and life-threatening impairments in our ESRC funded project, Life, Death, Disability and the Human: Living Life to the Fullest. We centre our Co-Researcher Collective of disabled young people who, through virtual research methods and social technologies, are co-leading this innovative project exploring the lives, hopes, desires and ambitions of young disabled people living short(er) lives. Co-production is an established approach; however, our co-researchers have led us to develop inclusive and transformative research practices that engage with online social research methods in innovative ways. Through this discussion, we demarcate the Academy and ‘research process’ as potentially deeply ableist spaces that propogate the normative researcher as non-disabled; someone integrated into the Academy and insecure employment; and who enacts normative modes of leadership. We use our experiences of co-production in Living Life to the Fullest, then, to show that research – as a discipline, a set of politics, and scholarly practice – must be transformed in order to enable new inclusive research futures that support meaningful co-production with marginalised young people. In conclusion, as we detail our experiences, we aim to encourage disability studies researchers and others to adopt virtual environments and social technologies when researching with and for the lives of disabled people.

Keywords: co-production, illness, youth, technology

Procedia PDF Downloads 127

Authors: Nadya Patel, Jawn Lim

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Foresight 3.0 is a synergistic methodology that encompasses systems analysis, future studies, capacity building, and forward planning. These components are interconnected, fostering a collective anticipatory intelligence that promotes societal resilience (Ravetz, 2020). However, traditional applications of these strands can often fall short, leading to missed opportunities and narrow perspectives. Therefore, Foresight 3.0 champions a holistic approach to tackling complex issues, focusing on systemic transformations and power dynamics. Businesses are pivotal in preparing the workforce for an increasingly uncertain and complex world. This necessitates the adoption of innovative tools and methodologies, such as Foresight 3.0, that can better equip young employees to anticipate and navigate future challenges. Firstly, the incorporation of its methodology into workplace training can foster a holistic perspective among employees. This approach encourages employees to think beyond the present and consider wider social, economic, and environmental contexts, thereby enhancing their problem-solving skills and resilience. This paper discusses our research on integrating Foresight 3.0's transformative principles with a newly developed Critical Design Futures (CDF) framework to equip organisations with the ability to innovate for the world's most complex social problems. This approach is grounded in 'collective forward intelligence,' enabling mutual learning, co-innovation, and co-production among a diverse stakeholder community, where business transformation and innovation are achieved.

Keywords: business transformation, innovation, foresight, critical design

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Authors: Ifeanyi Charles Otuokere, Victoria Nneoma Nnochiri

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Entrepreneurship generally and specifically within the rural communities in Nigeria is a fast means of bringing development within the communities. This is made possible by utmost maximization and management of available local resources to develop rural areas through good management of these local resources. This study anchors on the rural development paradigm and the integrated rural development theories to understudy the knowledge of rural entrepreneurs on rural economic development. The research study made use of surveys and descriptive analysis. The assessable population for the study, which was randomly selected, is 100 rural entrepreneurs from ten rural communities within the Ikwuano Local Government Area of Abia State. The study made use of both primary and secondary as a source of data collection with much emphasis on a primary source, although secondary data such as journals, textbooks electronic sources were also utilised. A carefully structured questionnaire drafted to extract raw data was administered to selected entrepreneurs. The findings of the study showed that developments within rural communities can only be achieved through rural entrepreneurship. This is evidenced in increased output, job creation, and most importantly, reduction of rural to urban migration, among other things. Recommendations were also made based on these findings; the researchers recommended that infrastructural developments should be made available in the rural communities and government policies should create enabling environments along with other assistance to help these rural entrepreneurs achieve their sole aim.

Keywords: economic developments, rural communities, rural development, rural entrepreneurship

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Authors: Joel Y. Y. Loh, Geoffrey A. Ozin, Charles A. Mims, Nazir P. Kherani

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A major goal in the emerging field of solar fuels is to realize an ‘artificial leaf’ – a material that converts light energy in the form of solar photons into chemical energy – using CO2 as a feedstock to generate useful chemical species. Enabling this technology will allow the greenhouse gas, CO2, emitted from energy and manufacturing production exhaust streams to be converted into valuable solar fuels or chemical products. Indium Oxide (In2O3) with surface hydroxyl (OH) groups have been shown to reduce CO2 in the presence of H2 to CO with a reaction rate of 15 μmol gcat−1 h−1. The likely mechanism is via a Frustrated Lewis Pair sites heterolytically splitting H2 to be absorbed and form protonic and hydric sites that can dissociate CO2. In this study, we investigate the dependence of oxygen composition of In2O3 on the CO2 reduction rate. In2O3-x films on quartz fiber paper were DC sputtered with an Indium target and varying O2/Ar plasma mixture. OH surface groups were then introduced by immersing the In2O3-x samples in KOH. We show that hydroxylated In2O3-x reduces more CO2 than non-hydroxylated groups and that a hydroxylated and higher O2/Ar ratio sputtered In2O3-x has a higher reaction rate of 45 μmol gcat-1 h-1. We show by electrical resistivity-temperature curves that H2 is adsorbed onto the surface of In2O3 whereas CO2 itself does not affect the indium oxide surface. We also present activation and ionization energy levels of the hydroxylated In2O3-x under vacuum, CO2 and H2 atmosphere conditions.

Keywords: solar fuels, photocatalysis, indium oxide nanoparticles, carbon dioxide

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Authors: Keaghan Brown

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The prioritization of drug resistance mutations impacting protein folding or protein-drug and protein-DNA interactions within macromolecular systems is critical to the success of treatment regimens. With a continual increase in computational tools to assess these impacts, the need for scalability and reproducibility became an essential component of computational analysis and experimental research. Here it introduce a bioinformatics pipeline that combines several structural analysis tools in a simplified workflow, by optimizing the present computational hardware and software to automatically ease the flow of data transformations. Utilizing preestablished software tools, it was possible to develop a pipeline with a set of pre-defined functions that will automate mutation introduction into the HIV-1 Integrase protein structure, calculate the gain and loss of polar interactions and calculate the change in energy of protein fold. Additionally, an automated molecular dynamics analysis was implemented which reduces the constant need for user input and output management. The resulting pipeline, Automated Mutation Introduction and Analysis (AMIA) is an open source set of scripts designed to introduce and analyse the effects of mutations on the static protein structure as well as the results of the multi-conformational states from molecular dynamic simulations. The workflow allows the user to visualize all outputs in a user friendly manner thereby successfully enabling the prioritization of variant systems for experimental validation.

Keywords: automated workflow, variant prioritization, drug resistance, HIV Integrase

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Authors: Sandeep Kaur, Jenny Vuong, Marcel Julliard, Sean O'Donoghue

Abstract:

Time-series data are useful for modelling as they can enable model-evaluation. However, when reconstructing models from phosphoproteomic data, often non-exact methods are utilised, as the knowledge regarding the network structure, such as, which kinases and phosphatases lead to the observed phosphorylation state, is incomplete. Thus, such reactions are often hypothesised, which gives rise to uncertainty. Here, we propose a framework, implemented via a web-based tool (as an extension to Minardo), which given time-series phosphoproteomic datasets, can generate κ models. The incompleteness and uncertainty in the generated model and reactions are clearly presented to the user via the visual method. Furthermore, we demonstrate, via a toy EGF signalling model, the use of algorithmic verification to verify κ models. Manually formulated requirements were evaluated with regards to the model, leading to the highlighting of the nodes causing unsatisfiability (i.e. error causing nodes). We aim to integrate such methods into our web-based tool and demonstrate how the identified erroneous nodes can be presented to the user via the visual method. Thus, in this research we present a framework, to enable a user to explore phosphorylation proteomic time-series data in the context of models. The observer can visualise which reactions in the model are highly uncertain, and which nodes cause incorrect simulation outputs. A tool such as this enables an end-user to determine the empirical analysis to perform, to reduce uncertainty in the presented model - thus enabling a better understanding of the underlying system.

Keywords: κ-models, model verification, time-series phosphoproteomic datasets, uncertainty and error visualisation

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Authors: Mohsen Akhlaghi, Tahereh Ebrahimi

Abstract:

Pricing strategy is a vital component in achieving the balance between customer value and business profitability. The aim of this study is to provide insights into the factors, techniques, and approaches involved in pricing decisions. The study utilizes a descriptive approach to discuss various aspects of pricing strategy in marketing, drawing on concepts from market research, consumer psychology, competitive analysis, and adaptability. This approach presents a comprehensive view of pricing decisions. The result of this exploration is a framework that highlights key factors influencing pricing decisions. The study examines how factors such as market positioning, product differentiation, and brand image shape pricing strategies. Additionally, it emphasizes the role of consumer psychology in understanding price elasticity, perceived value, and price-quality associations that influence consumer behavior. Various pricing techniques, including charm pricing, prestige pricing, and bundle pricing, are mentioned as methods to enhance sales by influencing consumer perceptions. The study also underscores the importance of adaptability in responding to market dynamics through regular price monitoring, dynamic pricing, and promotional strategies. It recognizes the role of digital platforms in enabling personalized pricing and dynamic pricing models. In conclusion, the study emphasizes that effective pricing strategies strike a balance between customer value and business profitability, ultimately driving sales, enhancing brand perception, and fostering lasting customer relationships.

Keywords: business, customer benefits, marketing, pricing

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Authors: Kang Huang, Wanting Zhou, Shiwei Yuan, Lei Li

Abstract:

Since information technology develops rapidly, the security issue has become an increasingly critical for computer system. In particular, as cloud computing and the Internet of Things (IoT) continue to gain widespread adoption, computer systems need to new security threats and attacks. The Root of Trust (RoT) is the foundation for providing basic trusted computing, which is used to verify the security and trustworthiness of other components. Design a reliable Root of Trust and guarantee its own security are essential for improving the overall security and credibility of computer systems. In this paper, we discuss the implementation of self-security technology based on the RISC-V Root of Trust at the hardware level. To effectively safeguard the security of the Root of Trust, researches on security safeguard technology on the Root of Trust have been studied. At first, a lightweight and secure boot framework is proposed as a secure mechanism. Secondly, two kinds of memory protection mechanism are built to against memory attacks. Moreover, hardware implementation of proposed method has been also investigated. A series of experiments and tests have been carried on to verify to effectiveness of the proposed method. The experimental results demonstrated that the proposed approach is effective in verifying the integrity of the Root of Trust’s own boot rom, user instructions, and data, ensuring authenticity and enabling the secure boot of the Root of Trust’s own system. Additionally, our approach provides memory protection against certain types of memory attacks, such as cache leaks and tampering, and ensures the security of root-of-trust sensitive information, including keys.

Keywords: root of trust, secure boot, memory protection, hardware security

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Authors: Paweł Żur, Alicja Żur, Andrzej Baier

Abstract:

Modal analysis is a crucial tool in the field of engineering for understanding the dynamic behavior of structures. In this study, numerical modal analysis was conducted on a multi-material 3D-printed composite bushing, which comprised a polylactic acid (PLA) outer shell and a thermoplastic polyurethane (TPU) flexible filling. The objective was to investigate the modal characteristics of the bushing and assess its potential for practical applications. The analysis involved the development of a finite element model of the bushing, which was subsequently subjected to modal analysis techniques. Natural frequencies, mode shapes, and damping ratios were determined to identify the dominant vibration modes and their corresponding responses. The numerical modal analysis provided valuable insights into the dynamic behavior of the bushing, enabling a comprehensive understanding of its structural integrity and performance. Furthermore, the study expanded its scope by investigating the entire shaft mounting of a small electric car, incorporating the 3D-printed composite bushing. The shaft mounting system was subjected to numerical modal analysis to evaluate its dynamic characteristics and potential vibrational issues. The results of the modal analysis highlighted the effectiveness of the 3D-printed composite bushing in minimizing vibrations and optimizing the performance of the shaft mounting system. The findings contribute to the broader field of composite material applications in automotive engineering and provide valuable insights for the design and optimization of similar components.

Keywords: 3D printing, composite bushing, modal analysis, multi-material

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Authors: M. Javahar, H. B. Dong

Abstract:

Single crystal components manufactured using Ni-base Superalloys are routinely used in the hot sections of aero engines and industrial gas turbines due to their outstanding high temperature strength, toughness and resistance to degradation in corrosive and oxidative environments. To control the quality of the single crystal turbine blades, particular attention has been paid to grain selection, which is used to obtain the single crystal morphology from a plethora of columnar grains. For this purpose, different designs of grain selectors are employed and the most common type is the spiral grain selector. A typical spiral grain selector includes a starter block and a spiral (helix) located above. It has been found that the grains with orientation well aligned to the thermal gradient survive in the starter block by competitive grain growth while the selection of the single crystal grain occurs in the spiral part. In the present study, 2D spiral selectors with different geometries were designed and produced using a state-of-the-art Bridgeman Directional Solidification casting furnace to investigate the competitive growth during grain selection in 2d grain selectors. The principal advantage of using a 2-D selector is to facilitate the wax injection process in investment casting by enabling significant degree of automation. The automation within the process can be derived by producing 2D grain selector wax patterns parts using a split die (metal mold model) coupled with wax injection stage. This will not only produce the part with high accuracy but also at an acceptable production rate.

Keywords: grain selector, single crystal, directional solidification, CMSX-4 superalloys, investment casting

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Authors: Pradeep Jawale, Sharad Supare, Sachin Kumar Jain, Nagesh Walke

Abstract:

One can witness the constant development and redevelopment of cities throughout the world. Construction equipment vehicles (CEVs) are commonly used on the construction site. However, noise pollution from construction sites due to the use of CEV has become a major problem for many cities. The construction equipment employed, which includes excavators and bulldozers, is one of the main causes of these elevated noise levels. The construction workers possibly will face a potential risk to their auditory health and well-being due to the noise levels they are exposed to. Different countries have imposed exterior and operator noise limits for construction equipment vehicles, enabling them to control noise pollution from CEVs. In this study, the operator ear level noise of the identified vehicle is higher than the benchmark vehicle by 8 dB(A). It was a tough time for the NVH engineer to beat the interior noise level of the benchmark vehicle. Initially, the noise source identification technique was used to identify the dominant sources for increasing the interior noise of the test vehicle. It was observed that the transfer of structure-borne and air-borne noise to the cabin was the major issue with the vehicle. It was foremost required to address the issue without compromising the overall performance of the vehicle. Surprisingly, the steering pump and radiator fan were identified as the major dominant sources than typical conventional sources like powertrain, intake, and exhaust. Individual sources of noise were analyzed in detail, and optimizations were made to minimize the noise at the source. As a result, the significant noise reduction achieved inside the vehicle and the overall in-cab noise level for the vehicle became a new benchmark in the market.

Keywords: interior noise, noise reduction, CEV, noise source identification

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