Search results for: opposition based learning

Authors: Shahid Nishat, Keith Thomas

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E-government initiatives attract substantial public investments around the world. These investments are based on the premise of digital transformation of the public services, improved efficiency and transparency, and citizen participation in the social democratic processes. However, many e-Government projects, especially in developing countries, fail to achieve their intended outcomes, and a strong disparity exists between the investments made and outcomes achieved, often referred to as e-Government paradox. Further, there is lack of research on evaluating the impacts of e-Government in terms of public value it creates, which ultimately drives usage. This study aims to address these gaps by identifying key enablers of e-Government success and by proposing a public value based framework to examine impact of e-Government services. The study will extend Delone and McLean Information System (IS) Success model by integrating Technology Readiness (TR) characteristics to develop an integrated success model. Level of analysis will be mobile government applications, and the framework will be empirically tested using quantitative methods. The research will add to the literature on e-Government success and will be beneficial for governments, especially in developing countries aspiring to improve public services through the use of Information Communication Technologies (ICT).

Keywords: e-Government, IS success model, public value, technology adoption, technology readiness

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Authors: Kristina Pflug, Markus Busch

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Being able to predict polymer properties and processing behavior based on the applied operating reaction conditions in one of the key challenges in modern polymer reaction engineering. Especially, for cost-intensive processes such as the high-pressure polymerization of low-density polyethylene (LDPE) with high safety-requirements, the need for simulation-based process optimization and product design is high. A multi-scale modelling approach was set-up and validated via a series of high-pressure mini-plant autoclave reactor experiments. The approach starts with the numerical modelling of the complex reaction network of the LDPE polymerization taking into consideration the actual reaction conditions. While this gives average product properties, the complex polymeric microstructure including random short- and long-chain branching is calculated via a hybrid Monte Carlo-approach. Finally, the processing behavior of LDPE -its melt flow behavior- is determined in dependence of the previously determined polymeric microstructure using the branch on branch algorithm for randomly branched polymer systems. All three steps of the multi-scale modelling approach can be independently validated against analytical data. A triple-detector GPC containing an IR, viscosimetry and multi-angle light scattering detector is applied. It serves to determine molecular weight distributions as well as chain-length dependent short- and long-chain branching frequencies. 13C-NMR measurements give average branching frequencies, and rheological measurements in shear and extension serve to characterize the polymeric flow behavior. The accordance of experimental and modelled results was found to be extraordinary, especially taking into consideration that the applied multi-scale modelling approach does not contain parameter fitting of the data. This validates the suggested approach and proves its universality at the same time. In the next step, the modelling approach can be applied to other reactor types, such as tubular reactors or industrial scale. Moreover, sensitivity analysis for systematically varying process conditions is easily feasible. The developed multi-scale modelling approach finally gives the opportunity to predict and design LDPE processing behavior simply based on process conditions such as feed streams and inlet temperatures and pressures.

Keywords: low-density polyethylene, multi-scale modelling, polymer properties, reaction engineering, rheology

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Authors: Yau-Luen Ng, Nathan Banka, Santosh Devasia

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In this paper, a method based on soft artificial cilia is introduced to separate particles based on size and mass. In nature, cilia are used for fluid propulsion in the mammalian circulatory system, as well as for swimming and size-selective particle entrainment for feeding in microorganisms. Inspired by biological cilia, an array of artificial cilia was fabricated using Polydimethylsiloxane (PDMS) to simulate the actual motion. A row of four individually-controlled magnetic artificial cilia in a semi-circular channel are actuated by the magnetic fields from four permanent magnets. Each cilium is a slender rectangular cantilever approximately 13mm long made from a composite of PDMS and carbonyl iron particles. A time-varying magnetic force is achieved by periodically varying the out-of-plane distance from the permanent magnets to the cilia, resulting in large-amplitude deflections of the cilia that can be used to drive fluid motion. Previous results have shown that this system of individually-controlled magnetic cilia can generate effective mixing flows; the purpose of the present work is to apply the individual cilia control to a particle separation task. Based on the observed beating patterns of cilia arrays in nature, the experimental beating patterns were selected as a metachronal wave, in which a fixed phase lead or lag is imposed between adjacent cilia. Additionally, the beating frequency was varied. For each set of experimental parameters, the channel was filled with water and polyethylene microspheres introduced at the center of the cilia array. Two types of particles were used: large red microspheres with density 0.9971 g/cm³ and 850-1000 μm avg. diameter, and small blue microspheres with density 1.06 g/cm³ and diameter 30 μm. At low beating frequencies, all particles were propelled in the mean flow direction. However, the large particles were observed to reverse directions above about 4.8 Hz, whereas reversal of the small particle transport direction did not occur until 6 Hz. Between these two transition frequencies, the large and small particles can be separated as they move in opposite directions. The experimental results show that selecting an appropriate cilia beating pattern can lead to selective transport of neutrally-buoyant particles based on their size. Importantly, the separation threshold can be chosen dynamically by adjusting the actuation frequency. However, further study is required to determine the range of particle sizes that can be effectively separated for a given system geometry.

Keywords: magnetic cilia, particle separation, tunable separation, soft actutors

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Authors: Toufik Bensana, Slimane Mekhilef, Kamel Tadjine

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The use of vibration analysis has been established as the most common and reliable method of analysis in the field of condition monitoring and diagnostics of rotating machinery. Rolling bearings cover a broad range of rotary machines and plays a crucial role in the modern manufacturing industry. Unfortunately, the vibration signals collected from a faulty bearing are generally non-stationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA) and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that, the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. the results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, local mean decomposition, rolling element bearing, vibration analysis

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Authors: Siti Hasnah Kamarudin, Luqman Chuah Abdullah, Min Min Aung, Chantara Thevy Ratnam

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The primary objective of this work was to develop fully nanocomposite material based on poly(lactic acid), epoxidized jatropha oil (EJO) and nanocrystalline cellulose. EJO was investigated as a sustainable alternative to petrochemical-based plasticizers to reinforce the ductility and toughness of plastics, in this case, nanocellulose/poly(lactic acid) (PLA). The EJO was melt blended into nanocellulose/PLA at concentrations from 1 wt% to 5 wt%. The blends were then hot-pressed into sheets to characterize their mechanical and physical properties. Microcrystalline cellulose had been converted to nanocrystalline cellulose by acid mercerisation technique and the effects thereof on the composites’ tensile, flexural, and impact properties, as well as their water absorption and density, were studied. The impact strengths of the nanocomposites were improved with the addition of NCC up to 0.5 wt%, with a maximum over 10 times that of the neat PLA. The flexural strength and modulus increased 4% and 50%, respectively, for NCC/PLA plasticized with EJO. This increase demonstrated the nanocrystalline cellulose addition gave notable improvements to the composites’ properties. Furthermore, analysis by scanning electron microscopy (SEM) of the nanocomposites’ tensile fracture surfaces indicated better interaction adhesion of the NCC/PLA plasticized with EJO compared with the PLA/EJO composites.

Keywords: nanocrystalline cellulose, nanocomposite, poly (lactic acid), epoxidised jatropha oil

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Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman

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Feature selection has been used in many fields such as classification, data mining and object recognition and proven to be effective for removing irrelevant and redundant features from the original data set. In this paper, a new design of distributed intrusion detection system using a combination feature selection model based on bees and decision tree. Bees algorithm is used as the search strategy to find the optimal subset of features, whereas decision tree is used as a judgment for the selected features. Both the produced features and the generated rules are used by Decision Making Mobile Agent to decide whether there is an attack or not in the networks. Decision Making Mobile Agent will migrate through the networks, moving from node to another, if it found that there is an attack on one of the nodes, it then alerts the user through User Interface Agent or takes some action through Action Mobile Agent. The KDD Cup 99 data set is used to test the effectiveness of the proposed system. The results show that even if only four features are used, the proposed system gives a better performance when it is compared with the obtained results using all 41 features.

Keywords: distributed intrusion detection system, mobile agent, feature selection, bees algorithm, decision tree

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Authors: James Jr. Mashiyane, Risuna Nkolele, Stephanie J. Müller, Gciniwe S. Dlamini, Rebone L. Meraba, Darlington S. Mapiye

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When performing language tasks in natural language processing (NLP), the dimensionality of word embeddings is chosen either ad-hoc or is calculated by optimizing the Pairwise Inner Product (PIP) loss. The PIP loss is a metric that measures the dissimilarity between word embeddings, and it is obtained through matrix perturbation theory by utilizing the unitary invariance of word embeddings. Unlike in natural language, in genomics, especially in genome sequence processing, unlike in natural language processing, there is no notion of a “word,” but rather, there are sequence substrings of length k called k-mers. K-mers sizes matter, and they vary depending on the goal of the task at hand. The dimensionality of word embeddings in NLP has been studied using the matrix perturbation theory and the PIP loss. In this paper, the sufficiency and reliability of applying word-embedding algorithms to various genomic sequence datasets are investigated to understand the relationship between the k-mer size and their embedding dimension. This is completed by studying the scaling capability of three embedding algorithms, namely Latent Semantic analysis (LSA), Word2Vec, and Global Vectors (GloVe), with respect to the k-mer size. Utilising the PIP loss as a metric to train embeddings on different datasets, we also show that Word2Vec outperforms LSA and GloVe in accurate computing embeddings as both the k-mer size and vocabulary increase. Finally, the shortcomings of natural language processing embedding algorithms in performing genomic tasks are discussed.

Keywords: word embeddings, k-mer embedding, dimensionality reduction

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Authors: Dan Wang

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Sandplay therapy is a Jungian psychological therapy developed by Dora Kalff in 1956. In sandplay therapy, the client first makes a sandtray with various miniatures and then has a communication with the therapist based on the sandtray. The special method makes sandplay therapy has great assessment potential. With regarding that the core treatment hypothesis of sandplay therapy - the self-healing power, is very similar to resilience. This study tries to use sandplay to evaluate psychological resilience. Participants are 107 undergraduates recruited from three public universities in China who were required to make an initial sandtray and to complete the Ego-Resiliency Scale (ER89) respectively. First, a 28- category General Sandtray Coding Manual (GSCM) was developed based on literature on sandplay therapy. Next, using GSCM to code the 107 initial sandtrays and conducted correlation analysis and regression analysis between all GSCM categories and ER89. Results show three categories (i.e., vitality, water types, and relationships) of sandplay account for 36.6% of the variance of ego-resilience and form the four-point Likert-type Sandtray Projective Test of Resilience (SPTR). Finally, it is found that SPTR dimensions and total score all have good inter-rater reliability, ranging from 0.89 to 0.93. This study provides an alternative approach to measure psychological resilience and can help to guide clinical social work.

Keywords: sandplay therapy, psychological resilience, measurement, college students

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Authors: Yating Yang, Xue Zhang, Chengli Zhao

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Technology capability refers to the comprehensive ability that influences all factors of technological development. Among them, researchers’ resources serve as the foundation and driving force for technology capability, representing a significant manifestation of a country/region's technological capability. Therefore, the cross-border transfer behavior of researchers to some extent reflects changes in technological capability between countries/regions, providing a unique research perspective for technological capability assessment. This paper proposes a technological capability assessment model based on personnel transfer networks, which consists of a researchers' transfer network model and a country/region role evolution model. It evaluates the changes in a country/region's technological capability roles from the perspective of researcher transfers and conducts an analysis using artificial intelligence as a case study based on literature data. The study reveals that the United States, China, and the European Union are core nodes, and identifies the role evolution characteristics of several major countries/regions.

Keywords: transfer network, technological capability assessment, central-peripheral structure, role evolution

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Authors: Bashir Abdu Muzakkari, Mohamad Afendee Mohamad, Mohd Fadzil Abdul Kadir

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Wireless Sensor Networks (WSNs) is an aggregation of several tiny, low-cost sensor nodes, spatially distributed to monitor physical or environmental status. WSN is constantly changing because of the rapid technological advancements in sensor elements such as radio, battery and operating systems. The Medium Access Control (MAC) protocols remain very vital in the WSN because of its role in coordinating communication amongst the sensors. Other than battery consumption, packet collision, network lifetime and latency are factors that largely depend on WSN MAC protocol and these factors have been widely treated in recent days. In this paper, we survey some latest proposed WSN Contention-based, Scheduling-based and Hybrid MAC protocols while presenting an examination, correlation of advantages and limitations of each protocol. Concentration is directed towards investigating the treatment of Quality of Service (QoS) performance metrics within these particular protocols. The result shows that majority of the protocols leaned towards energy conservation. We, therefore, believe that other performance metrics of guaranteed QoS such as latency, throughput, packet loss, network and bandwidth availability may play a critical role in the design of future MAC protocols for WSNs.

Keywords: WSN, QoS, energy consumption, MAC protocol

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Authors: Michael W. Markowitz, Jeffrey Gingerich

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The landscape of higher education in the United States has undergone significant changes in the last 25 years. What was once a domain of competition among prospective students for a limited number of college and university seats has become a marketplace in which institutions vie for the enrollment of educational consumers. A central figure in this paradigm shift has been the Chief Academic Officer (CAO), whose institutional role has also evolved beyond academics to include such disparate responsibilities as strategic planning, fiscal oversight, student recruitment, fundraising and personnel management. This paper explores the scope and impact of this transition by, first, explaining its context: the intersection of key social, economic and political factors in neo-conservative, late 20th Century America that redefined the value and accountability of institutions of higher learning. This context, in turn, is shown to have redefined the role and function of the CAO from a traditional academic leader to one centered on the successful application of corporate principles of organizational and fiscal management. Information gathered from a number of sitting Provosts, Vice-Presidents of Academic Affairs and Deans of Faculty is presented to illustrate the parameters of this change, as well as the extent to which today’s academic officers feel prepared and equipped to fulfill this broader institutional role. The paper concludes with a discussion of the impact of this transition on the American academy and whether it serves as a portend of change to come in higher education systems around the globe.

Keywords: academic administration, higher education, leadership, organizational management

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Authors: Sunny Deo, Eve Barnes, Peter Arnold-Smith

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Introduction: Healthcare technology is a rapidly expanding field in healthcare, with enthusiasts suggesting a revolution in the quality and efficiency of healthcare delivery based on the utilisation of better e-healthcare, including the move to paperless healthcare. The role and use of computers and programmes for healthcare have been increasing over the past 50 years. Despite this, there is no standardised method of assessing the quality of hardware and software utilised by frontline healthcare workers. Methods and subjects: Based on standard Patient Related Outcome Measures, a questionnaire was devised with the aim of providing quantitative and qualitative data on clinicians’ perspectives of their hospital’s Information Technology (IT). The survey was distributed via the Institution’s Intranet to all contracted doctors, and the survey's qualitative results were analysed. Qualitative opinions were grouped as positive, neutral, or negative and further sub-grouped into speed/usability, software/hardware, integration, IT staffing, clinical risk, and wellbeing. Analysis was undertaken on the basis of doctor seniority and by specialty. Results: There were 196 responses, with 51% from senior doctors (consultant grades) and the rest from junior grades, with the largest group of respondents 52% coming from medicine specialties. Differences in the proportion of principle and sub-groups were noted by seniority and specialty. Negative themes were by far the commonest stated opinion type, occurring in almost 2/3’s of responses (63%), while positive comments occurred less than 1 in 10 (8%). Conclusions: This survey confirms strongly negative attitudes to the current state of electronic documentation and IT in a large single-centre cohort of hospital-based frontline physicians after two decades of so-called progress to a paperless healthcare system. Greater use would provide further insights and potentially optimise the focus of development and delivery to improve the quality and effectiveness of IT for clinicians and their patients.

Keywords: information technology, electronic patient records, digitisation, paperless healthcare

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Authors: Leonard D. Agana, Wendell Ace Dela Cruz, Arjan C. Lingaya, Bonifacio T. Doma Jr.

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The purpose of this paper is to study the predict the fuel performance parameters, which include drivability index (DI), vapor lock index (VLI), and vapor lock potential using distillation curve and Reid vapor pressure (RVP) of dual alcohol-gasoline fuel blends. Distillation curve and Reid vapor pressure were predicted using artificial neural networks (ANN) with macroscopic properties such as boiling points, RVP, and molecular weights as the input layers. The ANN consists of 5 hidden layers and was trained using Bayesian regularization. The training mean square error (MSE) and R-value for the ANN of RVP are 91.4113 and 0.9151, respectively, while the training MSE and R-value for the distillation curve are 33.4867 and 0.9927. Fuel performance analysis of the dual alcohol–gasoline blends indicated that highly volatile gasoline blended with dual alcohols results in non-compliant fuel blends with D4814 standard. Mixtures of low-volatile gasoline and 10% methanol or 10% ethanol can still be blended with up to 10% C3 and C4 alcohols. Intermediate volatile gasoline containing 10% methanol or 10% ethanol can still be blended with C3 and C4 alcohols that have low RVPs, such as 1-propanol, 1-butanol, 2-butanol, and i-butanol. Biography: Graduate School of Chemical, Biological, and Materials Engineering and Sciences, Mapua University, Muralla St., Intramuros, Manila, 1002, Philippines

Keywords: dual alcohol-gasoline blends, distillation curve, machine learning, reid vapor pressure

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Authors: Ahmad Badawi Saluy

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This study aims to develop strategies for the prevention or elimination of environmental pollution as well as changes in external variables of the environment in order to implement the environmental management system ISO 14001:2004 by integrating analysis of environmental issues data, RKL-RPL transactional data and regulation as part of ERP on the management dashboard. This research uses a quantitative descriptive approach with analysis method comparing with air quality standard (PP 42/1999, LH 21/2008), water quality standard (permenkes RI 416/1990, KepmenLH 51/2004, kepmenLH 55/2013 ), and biodiversity indicators. Based on the research, the parameters of RPL monitoring have been identified, among others, the quality of emission air (SO₂, NO₂, dust, particulate) due to the influence of fuel quality, combustion performance in a combustor and the effect of development change around the generating area. While in water quality (TSS, TDS) there was an increase due to the flow of water in the cooling intake carrying sedimentation from the flow of Banjir Kanal Timur. Including compliance with the ISO 14001:2004 clause on application design significantly contributes to the improvement of the quality of power plant management.

Keywords: environmental management systems, power plant management, regulatory compliance , enterprises resource planning

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Authors: V. Lukášová, P. Peukert, V. Votrubec

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Thermal conductivity in the x, y and z-directions was measured on a pultruded profile that was manufactured by the technology of pulling from glass fibers and a polyester matrix. The results of measurements of thermal conductivity showed considerable variability in different directions. The caused variability in thermal conductivity was expected due fraction variations. The cross-section of the pultruded profile was scanned. An image analysis illustrated an uneven distribution of the fibers and the matrix in the cross-section. The distribution of these inequalities was processed into a Voronoi diagram in the observed area of the pultruded profile cross-section. In order to verify whether the variation of the fiber volume fraction in the pultruded profile can affect its thermal conductivity, the numerical simulations in the ANSYS Fluent were performed. The simulation was based on the geometry reconstructed from image analysis. The aim is to quantify thermal conductivity numerically. Above all, images with different volume fractions were chosen. The results of the measured thermal conductivity were compared with the calculated thermal conductivity. The evaluated data proved a strong correlation between volume fraction and thermal conductivity of the pultruded profile. Based on presented results, a modification of production technology may be proposed.

Keywords: pultrusion profile, volume fraction, thermal conductivity, numerical simulation

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Authors: M. S. Mousavi-Daramoroudi, H. Yousefnia, S. Zolghadri, F. Abbasi-Davani

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Dosimetry is an indispensable and precious factor in patient treatment planning; to minimize the absorbed dose in vital tissues. In this study, In accordance with the proper characteristics of DOTATOC and ¹⁷⁷Lu, after preparing ¹⁷⁷Lu-DOTATOC at the optimal conditions for the first time in Iran, radionuclidic and radiochemical purity of the solution was investigated using an HPGe spectrometer and ITLC method, respectively. The biodistribution of the compound was assayed for treatment of adenocarcinoma breast cancer in bearing BALB/c mice. The results have demonstrated that ¹⁷⁷Lu-DOTATOC is a profitable selection for therapy of the tumors. Because of the vital role of internal dosimetry before and during therapy, the effort to improve the accuracy and rapidity of dosimetric calculations is necessary. For this reason, a new method was accomplished to calculate the absorbed dose through mixing between compartmental model, animal dosimetry and extrapolated data from animal to human and using MIRD method. Despite utilization of compartmental model based on the experimental data, it seems this approach may increase the accuracy of dosimetric data, confidently.

Keywords: ¹⁷⁷Lu-DOTATOC, biodistribution modeling, compartmental model, internal dosimetry

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Authors: Mehdi Fuladipanah

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Sensitivity analysis as a technique is applied to determine influential input factors on model output. Variance-based sensitivity analysis method has more application compared to other methods because of including linear and non-linear models. In this paper, van Rijn’s movable bed roughness formula was selected to evaluate because of its reasonable results in sandy rivers. This equation contains four variables as: flow depth, sediment size,bBed form height and bed form length. These variable’s importance was determined using the first order of Fourier Amplitude Sensitivity Test. Sensitivity index was applied to evaluate importance of factors. The first order FAST based sensitivity indices test, explain 90% of the total variance that is indicating acceptance criteria of FAST application. More value of this index is indicating more important variable. Results show that bed form height, bed form length, sediment size and flow depth are more influential factors with sensitivity index: 32%, 24%, 19% and 15% respectively.

Keywords: sdensitivity analysis, variance, movable bed roughness formula, Sandy River

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Authors: Janette Porter, Kay Standing

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The paper presents our experiences of working in both mainstream and Special Education Needs and Disabilities (SEND) schools in England from 2012-2019, using creative methodologies to deliver and evaluate healthy relationship education. It aims to explore to explore how young people's perceptions of relationships and their "perfect partner" are mediated by factors such as gender, body image, and social media. It will be an interactive session, inviting participants to reflect on their own experiences of relationship education, and to take part in an example of a classroom activity of 'a perfect partner'. Young people aged 16-25 are most at risk of relationship abuse and intimate partner violence. This can be enacted both on the body, through physical and sexual violence, but also emotional and psychological abuse. In England and Wales relationship education became compulsory in schools in September 2020. There is increasing recognition for the need for whole school approaches to prevent gender-based violence, in particular domestic abuse, from happening in the first place and for equipping schools to feel more confident supporting young people affected by gender-based violence. The project used creative methods, including arts, drama, music, poetry, song, and creative writing, to engage participants in sensitive topics related to relationship education. Interactive workshops with pupils aged 11-19 enabled young people to express themselves freely, pupils then used drama to share their knowledge with their peer group. We co-produced material with young people, including an accessible resource pack for use in SEND schools, particularly for children with visual and sensory impairments. The project was evaluated by questionnaires and interviews with pupils. The paper also reflects on the ethical issues involved in the research. After the project, young people had a better understanding of healthy and unhealthy relationships, improved knowledge of the early warning signs of abuse and knew where to go to for help and advice. It found that creative methods are an effective way to engage young people in relationship education and sensitive topics. We argue that age and ability appropriate relationship education should be compulsory across the curriculum and that implementing creative and art-based approaches to address sensitive topics can enhance the effectiveness of relationship education programs in promoting healthy relationships and preventing abuse. The paper provides academic and practitioner perspectives, providing a reflection on our research, looking at practical, methodological, and ethical issues involved in research on Gender Based Violence with young people in a school setting.

Keywords: relationship education, healthy relationships, creative methods, young people

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Authors: T. Häfele, J. Kaspar, M. Vielhaber, W. Calles, J. Griebsch

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The demand for an increasing diversification of the product spectrum associated with the current huge customization desire and subsequently the decreasing unit quantities of each production lot is gaining more and more importance within a great variety of industrial branches, e.g. automotive industry. Nevertheless, traditional product development and production processes (molding, extrusion) are already reaching their limits or fail to address these trends of a flexible and digitized production in view of a product variability up to lot size one. Thus, upcoming innovative production concepts like the additive manufacturing technology basically create new opportunities with regard to extensive potentials in product development (constructive optimization) and manufacturing (economic individualization), but mostly suffer from insufficient strength regarding structural components. Therefore, this contribution presents an innovative technological and procedural conception of a hybrid additive manufacturing process (fiber-reinforced sandwich structures based on selective laser sintering technology) to overcome these current structural weaknesses, and consequently support the design of complex lightweight components.

Keywords: additive manufacturing, fiber-reinforced plastics (FRP), hybrid design, lightweight design

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Authors: Rihab Belguith, Fathi Abid

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The paper develops a system-based approach to investigate the dynamic adjustment of debt structure and investment policies of the Dow-Jones index. This approach enables the assessment of relations among sales, debt, and investment opportunities by considering the simultaneous effect of the market environmental change and future growth opportunities. We integrate the firm-specific sales variance to capture the industries' conditions in the model. Empirical results were obtained through a panel data set of firms with different sectors. The analysis support that environmental change does not affect equally the different industry since operating leverage differs among industries and so the sensitivity to sales variance. Including adjusted-specific variance, we find that there is no monotonic relation between leverage, sales, and investment. The firm may choose a low debt level in response to high sales variance but high leverage to attenuate the negative relation between sales variance and the current level of investment. We further find that while the overall effect of debt maturity on leverage is unaffected by the level of growth opportunities, the shorter the maturity of debt is, the smaller the direct effect of sales variance on investment.

Keywords: dynamic panel, investment, leverage decision, sales uncertainty

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Authors: Chidozie C. Nwobi-Okoye, Basil Q. Ochieze, Stanley Okiy

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This research reports on the modeling of age hardening process using adaptive neuro-fuzzy inference system (ANFIS). The age hardening output (Hardness) was predicted using ANFIS. The input parameters were ageing time, temperature and percentage composition of cow horn particles (CHp%). The results show the correlation coefficient (R) of the predicted hardness values versus the measured values was of 0.9985. Subsequently, values outside the experimental data points were predicted. When the temperature was kept constant, and other input parameters were varied, the average relative error of the predicted values was 0.0931%. When the temperature was varied, and other input parameters kept constant, the average relative error of the hardness values predictions was 80%. The results show that ANFIS with coarse experimental data points for learning is not very effective in predicting process outputs in the age hardening operation of A356 alloy/CHp particulate composite. The fine experimental data requirements by ANFIS make it more expensive in modeling and optimization of age hardening operations of A356 alloy/CHp particulate composite.

Keywords: adaptive neuro-fuzzy inference system (ANFIS), age hardening, aluminum alloy, metal matrix composite

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Authors: Paul Kenneth D. Luzon, Maria Antonia N. Tanchuling

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The Quezon City Controlled Dumping facility also known as Payatas produces leachate which can contaminate soil and water environment in the area. The goal of this study is to quantify the leachate produced by the QCCDF using the Hydrologic Evaluation of Landfill Performance (HELP) model. Results could be used as input for groundwater contaminant transport studies. The HELP model is based on a simple water budget and is an essential “model requirement” used by the US Environmental Protection Agency (EPA). Annual waste profile of the QCCDF was calculated. Based on topographical maps and estimation of settlement due to overburden pressure and degradation, a total of 10M m^3 of waste is contained in the landfill. The input necessary for the HELP model are weather data, soil properties, and landfill design. Results showed that from 1988 to 2011, an average of 50% of the total precipitation percolates through the bottom layer. Validation of the results is still needed due to the assumptions made in the study. The decrease in porosity of the top soil cover showed the best mitigation for minimizing percolation rate. This study concludes that there is a need for better leachate management system in the QCCDF.

Keywords: help model, landfill, payatas trash slide, quezon city controlled dumping facility

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Authors: Emma Groenewald

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In 1994, numerous policies of a democratic dispensation envisage social justice and the transformation of the South Africa society. The drive for transformation and social justice resulted in an increasing number of university students from diverse backgrounds, which in turn, lead to the establishment of Sol Plaatje University (SPU) in 2014. A re-curriculated B. Ed. programme at SPU aims to equip students with knowledge and skills to realise the aim of social justice and to enhance the transformation of the South African society. The aim of this study is to explore the experiences and perceptions of students at a diverse university campus on a curriculum that aims to promote social justice. Four education modules, with the assumption that it reflects social justice content, were selected. Four students, representative of different ethnic and language groupings found at the SPU, were chosen as participants. Data were generated by the participants through four reflective exercises on each of the modules, spread over a period of four years. The module aims, linked with the narratives of the participants' perceptions and experiences of each module, provided an overview of the enacted curriculum. A qualitative research design with an interpretivist approach informed by Vygotsky's theory of learning was used. The participants' experiences of the four modules were analysed, and their views were interpreted. The students' narratives shed light on the strengths and weaknesses of how the B.Ed. Curriculum works towards social justice and revealed student's perceptions of otherness. From the narratives it became apparent that module did promote a social justice orientation in prospective teachers trained at a university.

Keywords: student diversity, social justice, transformation, teacher education

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Authors: M. S. Gadala, Khaled Ahmed, Elasadig Mahdi

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In this paper, we introduced a gradient-based inverse solver to obtain the missing boundary conditions based on the readings of internal thermocouples. The results show that the method is very sensitive to measurement errors, and becomes unstable when small time steps are used. The artificial neural networks are shown to be capable of capturing the whole thermal history on the run-out table, but are not very effective in restoring the detailed behavior of the boundary conditions. Also, they behave poorly in nonlinear cases and where the boundary condition profile is different. GA and PSO are more effective in finding a detailed representation of the time-varying boundary conditions, as well as in nonlinear cases. However, their convergence takes longer. A variation of the basic PSO, called CRPSO, showed the best performance among the three versions. Also, PSO proved to be effective in handling noisy data, especially when its performance parameters were tuned. An increase in the self-confidence parameter was also found to be effective, as it increased the global search capabilities of the algorithm. RPSO was the most effective variation in dealing with noise, closely followed by CRPSO. The latter variation is recommended for inverse heat conduction problems, as it combines the efficiency and effectiveness required by these problems.

Keywords: inverse analysis, function specification, neural net works, particle swarm, run-out table

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Authors: Mehdi Radmehr, Amir Hamed Mashhadzadeh, Mehdi Jafari

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Traditional HVDC systems are tough to DC short circuits as they are current regulated with a large reactance connected in series with cables. Multi-terminal DC wind farm topologies are attracting increasing research attempt. With AC/DC converters on the generator side, this topology can be developed into a multi-terminal DC network for wind power collection, which is especially suitable for large-scale offshore wind farms. For wind farms, the topology uses high-voltage direct-current transmission based on voltage-source converters (VSC-HVDC). Therefore, they do not suffer from over currents due to DC cable faults and there is no over current to react to. In this study, the multi-terminal DC wind farm topology is introduced. Then, possible internal DC faults are analyzed according to type and characteristic. Fault over current expressions are given in detail. Under this characteristic analysis, fault detection and detailed protection methods are proposed. Theoretical analysis and PSCAD/EMTDC simulations are provided.

Keywords: DC short circuits, multi-terminal DC wind farm topologies, HVDC transmission based on VSC, fault analysis

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Authors: Gabriel Sunday Ayayia

Abstract:

The paper argues that Ubuntu, as a philosophy that emphasizes the interconnectedness of all living things and importance of community and mutual support, can be used as a social framework to address the problems of climate change and promote environmental sustainability. The research demonstrate that Ubuntu is an ideological concept that encourages collective action on climate change, with the emphasis on individual and collective commitment to taking concrete action to address the problems of climate change. The paper shows that Ubuntu can be employed as a social tool that would enhance the cultivation of shared identity and promote the sense of shared response responsibility to develop the resilience to cope with climate change. Using qualitative and quantitative methodologies, the study establishes the imperativeness of mutual support and cooperation through the lens of Ubuntu as a human-centered scalable response to the debacle of climate change. It recommends that we can build a society that values the environment and promotes sustainable practices by encouraging community involvement in sustainable initiatives by integrating Ubuntu-based principles to our decision-making processes, collaboration, leadership, human agency and governance.

Keywords: ubuntu, climate change, humanity, collective actions, community-based

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Authors: Robert L. Williamson

Abstract:

A 'token economy' refers to a method of positive behaviour support whereby ‘tokens’ are delivered to students as a reward for exhibiting specific behaviours. Students later exchange tokens to ‘purchase’ items of interest. Unfortunately, implementation fidelity can be problematic as some find physical delivery of tokens while teaching difficult. This project developed and tested a prototype, iPad-based tool that enabled teachers to deliver and track tokens electronically. Using an alternating treatment design, any differences in on-task individual and/or group behaviours between the virtual versus physical token delivery systems were examined. Results indicated that while students and teachers preferred iPad-based implementation, no significant difference was found concerning on-task behaviours of students between the two methodologies. Perhaps more interesting was that the teacher found implementation of both methods problematic and suggested a second person was most effective in implementing a token economy method. This would represent a significant cost to the effective use of such a method. Further research should focus on the use of a lay volunteer regarding method implementation fidelity and associated outcomes of the method.

Keywords: positive behaviour support, inclusion, token economy, applied behaviour analysis

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Authors: Hafiza Javaria Ashraf, Asim Abbasi, Muhammad Hussnain Babar, Muhammad Sufyan

Abstract:

Brevicoryne brassicae (Aphid) is not only the major biotic constraint of rapeseed crop but also transmits 20 different viral pathogens that cause diseases in crucifers. Aphids cause major losses to rapeseed by stunting growth and yield, with real damage being contamination of harvested heads. The misuse of pesticides has led to tremendous economic losses and hazards to human health and environmental pollution. Thus, newer approaches for pest control are continuously being sought. The naturally occurring, biologically active plant-based products seem to have a prominent role in the development of future commercial pesticides not only for increased productivity but their eco-friendly nature. The present experiment was carried out in Research Area of Ayub Agriculture Research Institute, Faisalabad to check the efficacy of different botanicals against rapeseed aphid. The tested botanicals were, neem seed extract, neem leaf extract, dathora seed extract, kaner leaf extract and aak leaf extract. Insecticide, advantage 20 EC served as the positive control in the experiment. Data was recorded before and after 1, 3 and 7 days of treatment application. The results of the experiment revealed that neem seed extract exhibited maximum mortality (48.42%) followed by dathora (45.54%) and kaner leaf extract (40.29%) after 7 days of treatment application. However minimum mortality i.e. 26.64% was observed in case of aak leaf extract. Advantage encountered maximum mortality i.e. 86.14%. All treatments caused maximum mortality after 7 days of treatment application. In case of pollinators maximum population reduction was observed in case of insecticide (74.29%) while minimum reduction was observed in neem leaf extract (11.57%). Hence it was concluded that unlike insecticides, plant based products can be a better option for regulating pests and conserving beneficial insect fauna.

Keywords: Aphid, mortality, plant based, pollinators

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Authors: Khaled M. Alqahtani

Abstract:

Copy number alterations (CNA) are variations in the structure of the genome, where certain regions deviate from the typical two chromosomal copies. These alterations are pivotal in understanding tumor progression and are indicative of patients' survival outcomes. However, effectively modeling patients' survival based on their genomic CNA profiles while identifying relevant genomic regions remains a statistical challenge. Various methods, such as the Cox proportional hazard (PH) model with ridge, lasso, or elastic net penalties, have been proposed but often overlook the inherent dependencies between genomic regions, leading to results that are hard to interpret. In this study, we enhance the elastic net penalty by incorporating an additional penalty that accounts for these dependencies. This approach yields smooth parameter estimates and facilitates variable selection, resulting in a sparse solution. Our findings demonstrate that this method outperforms other models in predicting survival outcomes, as evidenced by our simulation study. Moreover, it allows for a more meaningful interpretation of genomic regions associated with patients' survival. We demonstrate the efficacy of our approach using both real data from a lung cancer cohort and simulated datasets.

Keywords: copy number alterations, cox proportional hazard, lung cancer, regression, sparse solution

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Authors: Pei Li, Chunyi Zhi

Abstract:

Conversion-type lithium-ion batteries show great potential as high-energy-density, low-cost and sustainable alternatives to current transition-metal-based intercalation cells. Li-Cl₂/Li⁻I₂ conversion batteries, based on anionic redox reactions of Cl⁻/Cl⁰ or I⁻/I⁰, are highly attractive due to their superior voltage and capacity. However, a redox-active and reversible chlorine cathode has not been developed in organic electrolytes. And thermodynamic instability and shuttling issues of iodine cathodes have plagued the active iodine loading, capacity retention and cyclability. By reversible chemical bonds, we develop reversible chlorine redox reactions in organic electrolytes with interhalogen bonds between I and Cl for Li-I₂ batteries and develop a highly thermally stable I/I₃--bonded organic salts with iodine content up to 80% as cathode materials for the rechargeable Li-I₂ batteries. The demonstration of reversible chemical bonds enabled rechargeable Li-halogen batteries opens a new avenue to develop halogen compound cathodes.

Keywords: conversion-type, chlorine, halogen cathode, high energy density, iodine, interhalogen bond, lithium-ion batteries

Procedia PDF Downloads 69