Search results for: structured gravity model

Authors: Hammad Khan, Wookeun Bae

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The objective of this study was to optimize, achieve and control the highly loaded and efficient nitrite production having suitability for autotrophic and heterotrophic denitritation. A lab scale CSTR for partial and full nitritation was operated to treat the livestock manure digester liquor having an ammonium concentration of ~600 mg-NH4+-N/L and biodegradable contents of ~0.35 g-COD/L. The experiments were performed at 30°C, pH: 8.0, DO: 1.5 mg/L and SRT ranging from 7-20 days. After 125 days operation, >95% nitrite buildup having the ammonium loading rate of ~3.2 kg-NH4+-N/m3-day was seen with almost complete ammonium conversion. On increasing the loading rate further (i-e, from 3.2-6.2 kg-NH4+-N/m3-day), stability of the system remained unaffected. On decreasing the pH from 8 to7.5 and further 7.2, removal rate can be easily controlled as 95%, 75%, and even 50%. Results demonstrated that nitritation stability and desired removal rates are controlled by a balance of simultaneous inhibition by FA & FNA, pH affect and DO limitation. These parameters proved to be effective even to produce an appropriate influent for anammox. In addition, a mathematical model, identified through the occurring biological reactions, is proposed to optimize the full and partial nitritation process. The proposed model present relationship between pH, ammonium and produced nitrite for full and partial nitritation under the varying concentrations of DO, and simultaneous inhibition by FA and FNA.

Keywords: stable nitritation, high loading, autrophic denitritation, CSTR

Procedia PDF Downloads 243

Authors: Min Jin Kwon, Seung Won Kim, Eui Yeon Kim, Haeyoung Lee

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Numerous anonymous chat apps that help people to connect with random strangers have been released in South Korea. However, they become a serious problem for young people since young people often use them for channels of prostitution or sexual violence. Although ISPs in South Korea are responsible for making inappropriate content inaccessible on their networks, they do not block traffic of random chat apps since 1) the use of random chat apps is entirely legal. 2) it is reported that they use HTTP proxy blocking so that non-HTTP traffic cannot be blocked. In this paper, we propose a service model that can block random chat apps at home routers. A service provider manages a blacklist that contains blocked apps’ information. Home routers that subscribe the service filter the traffic of the apps out using deep packet inspection. We have implemented a prototype of the proposed model, including a centralized server providing the blacklist, a Raspberry Pi-based home router that can filter traffic of the apps out, and an Android app used by the router’s administrator to locally customize the blacklist.

Keywords: deep packet inspection, internet filtering, juvenile protection, technical blocking

Procedia PDF Downloads 352

Authors: Abebe Mulugojam Negash, Yongbin Yu, Ekong Favour, Bekalu Nigus Dawit, Molla Woretaw Teshome, Aynalem Birtukan Yirga

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Breast cancer remains a significant health concern, necessitating advancements in diagnostic methodologies. Addressing this, our paper confronts the notable challenges in breast cancer classification, particularly the imbalance in datasets and the constraints in the accuracy and interpretability of prevailing deep learning approaches. We proposed an attention-based residual neural network (ResNet), which effectively combines the robust features of ResNet with an advanced attention mechanism. Enhanced through strategic data augmentation and positive weight adjustments, this approach specifically targets the issue of data imbalance. The proposed model is tested on the BreakHis dataset and achieved accuracies of 99.00%, 99.04%, 98.67%, and 98.08% in different magnifications (40X, 100X, 200X, and 400X), respectively. We evaluated the performance by using different evaluation metrics such as precision, recall, and F1-Score and made comparisons with other state-of-the-art methods. Our experiments demonstrate that the proposed model outperforms existing approaches, achieving higher accuracy in breast cancer classification.

Keywords: residual neural network, attention mechanism, positive weight, data augmentation

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Authors: Aleksandra Majchrzak, Katarzyna Baruch, Monika Sobolewska, Bartlomiej Chojnacki, Adam Pilch

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Scaled modeling is very common in the areas of science such as aerodynamics or fluid mechanics, since defining characteristic numbers enables to determine relations between objects under test and their models. In acoustics, scaled modeling is aimed mainly at investigation of room acoustics, sound insulation and sound absorption phenomena. Despite such a range of application, there is no method developed that would enable scaling acoustical perforated panels freely, maintaining their sound absorption coefficient in a desired frequency range. However, conducted theoretical and numerical analyses have proven that it is not physically possible to obtain given sound absorption coefficient in a desired frequency range by directly scaling only all of the physical dimensions of a perforated panel, according to a defined characteristic number. This paper is a continuation of the research mentioned above and presents practical evaluation of theoretical and numerical analyses. The measurements of sound absorption coefficient of perforated panels were performed in order to verify previous analyses and as a result find the relations between full-scale perforated panels and their models which will enable to scale them properly. The measurements were conducted in a one-to-eight model of a reverberation chamber of Technical Acoustics Laboratory, AGH. Obtained results verify theses proposed after theoretical and numerical analyses. Finding the relations between full-scale and modeled perforated panels will allow to produce measurement samples equivalent to the original ones. As a consequence, it will make the process of designing acoustical perforated panels easier and will also lower the costs of prototypes production. Having this knowledge, it will be possible to emulate in a constructed model panels used, or to be used, in a full-scale room more precisely and as a result imitate or predict the acoustics of a modeled space more accurately.

Keywords: characteristic numbers, dimensional analysis, model study, scaled modeling, sound absorption coefficient

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Authors: Abolfazl Hosseinkhani, Sepehr Sanaye

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Different approaches have been used to predict the performance of the vertical axis wind turbines (VAWT), such as experimental, computational fluid dynamics (CFD), and analytical methods. Analytical methods, such as momentum models that use streamtubes, have low computational cost and sufficient accuracy. The double multiple streamtube (DMST) is one of the most commonly used of momentum models, which divide the rotor plane of VAWT into upwind and downwind. In fact, results from the DMST method have shown some discrepancy compared with experiment results; that is because the Darrieus turbine is a complex and aerodynamically unsteady configuration. In this study, analytical-experimental-based corrections, including dynamic stall, streamtube expansion, and finite blade length correction are used to improve the DMST method. Results indicated that using these corrections for a SANDIA 17-m VAWT will lead to improving the results of DMST.

Keywords: vertical axis wind turbine, analytical, double multiple streamtube, streamtube expansion model, dynamic stall model, finite blade length correction

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Authors: Lucky Malise, Hilary Rutto, Tumisang Seodigeng

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Heavy metal contamination in waste water is a very serious issue affecting a lot of industrialized countries due to the health and environmental impact of these heavy metals on human life and the ecosystem. Adsorption using activated carbon is the most promising method for the removal of heavy metals from waste water but commercial activated carbon is expensive which gives rise to the need for alternatively activated carbon derived from cheap precursors, agricultural wastes, or byproducts from other processes. In this study activated bio-carbon derived from the carbonaceous material obtained from the pyrolysis of Marula nut shells was chemically activated and used as an adsorbent for the removal of lead (II) and copper (II) ions from aqueous solution. The surface morphology and chemistry of the adsorbent before and after chemical activation with zinc chloride impregnation were studied using SEM and FTIR analysis respectively and the results obtained indicate that chemical activation with zinc chloride improves the surface morphology of the adsorbent and enhances the intensity of the surface oxygen complexes on the surface of the adsorbent. The effect of process parameters such as adsorbent dosage, pH value of the solution, initial metal concentration, contact time, and temperature on the adsorption of lead (II) and copper (II) ions onto Marula nut activated carbon were investigated, and their optimum operating conditions were also determined. The experimental data was fitted to both the Langmuir and Freundlich isotherm models, and the data fitted best on the Freundlich isotherm model for both metal ions. The adsorption kinetics were also evaluated, and the experimental data fitted the pseudo-first order kinetic model better than the pseudo second-order kinetic model. The adsorption thermodynamics were also studied and the results indicate that the adsorption of lead and copper ions is spontaneous and exothermic in nature, feasible, and also involves a dissociative mechanism in the temperature range of 25-45 °C.

Keywords: adsorption, isotherms, kinetics, marula nut shells activated carbon, thermodynamics

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Authors: Daniel Angwenyi

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Relationships between protected area managers and adjacent communities, as well as communities' attitudes, views and perceptions of these areas, are critical for the success of conservation efforts. It is, therefore, of utmost importance for protected area managers and administrators understand how local communities view these areas and their management, so that they can build sustainable working relationships. This paper is based on a survey of 375 semi-structured questionnaires administered to household heads, living at distances ranging from the edge of the reserves to 50 km away from the reserve boundary across Great Fish River, Mkambati, Hluleka, and Tsolwana in the Eastern Cape Province, South Africa. The paper provides a longitudinal assessment of households’ knowledge on the role of reserves and how the reserves. In addition to households’ knowledge, the paper also provides an assessment of their attitudes towards the location and management, as well as views on the best way to manage the reserves. For 79% of community members reserves are important as they were seen to conserve biodiversity and valuable ecological systems necessary for sustaining life. Most (75%) respondents indicated that closely located reserves gave them opportunities to learn about nature conservation and to subsidize their incomes through tourism ventures. However, 58% had a problem with reserves’ staff, due to restrictions on resource use, which negatively impacted their livelihoods. Over half (51%) of the households were of the view that sustainable conservation can only be achieved through an integrated approach, where local communities’ and conservation needs are given equal weighting. Thus, it is concluded that reserve management should look at communities as active partners in the running of protected areas if sustainable conservation objectives are to be realised.

Keywords: nature conservation, conservation knowledge, local communities, views, protected areas

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Authors: Kedar Hardikar, Joe Varghese

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Conductive adhesives have found wide-ranging applications in electronics industry ranging from fixing a defective conductor on printed circuit board (PCB) attaching an electronic component in an assembly to protecting electronics components by the formation of “Faraday Cage.” The reliability requirements for the conductive adhesive vary widely depending on the application and expected product lifetime. While the conductive adhesive is required to maintain the structural integrity, the electrical performance of the associated sub-assembly can be affected by the degradation of conductive adhesive. The degradation of the adhesive is dependent upon the highly varied use case. The conventional approach to assess the reliability of the sub-assembly involves subjecting it to the standard environmental test conditions such as high-temperature high humidity, thermal cycling, high-temperature exposure to name a few. In order to enable projection of test data and observed failures to predict field performance, systematic development of an acceleration factor between the test conditions and field conditions is crucial. Common acceleration factor models such as Arrhenius model are based on rate kinetics and typically rely on an assumption of linear degradation in time for a given condition and test duration. The application of interest in this work involves conductive adhesive used in an electronic circuit of a capacitive sensor. The degradation of conductive adhesive in high temperature and humidity environment is quantified by the capacitance values. Under such conditions, the use of established models such as Hallberg-Peck model or Eyring Model to predict time to failure in the field typically relies on linear degradation rate. In this particular case, it is seen that the degradation is nonlinear in time and exhibits a square root t dependence. It is also shown that for the mechanism of interest, the presence of moisture is essential, and the dominant mechanism driving the degradation is the diffusion of moisture. In this work, a framework is developed to incorporate nonlinear degradation of the conductive adhesive for the development of an acceleration factor. This method can be extended to applications where nonlinearity in degradation rate can be adequately characterized in tests. It is shown that depending on the expected product lifetime, the use of conventional linear degradation approach can overestimate or underestimate the field performance. This work provides guidelines for suitability of linear degradation approximation for such varied applications

Keywords: conductive adhesives, nonlinear degradation, physics of failure, acceleration factor model.

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Authors: Amir Hedjripour

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The required dewatering configuration for a contaminated sediment dam is discussed to meet no-spill criteria for a defined Average Recurrence Interval (ARI). There is an option for the sediment dam to pump the contaminated water to another storage facility before its capacity is exceeded. The system is subjected to a range of storm durations belonging to the design ARI with concurrent dewatering to the other storage facility. The model is set up in 1-minute time intervals and temporal patterns of storm events are used to de-segregate the total storm depth into partial durations. By running the model for selected storm durations, the maximum water volume in the dam is recorded as the critical volume, which indicates the required storage capacity for that storm duration. Runoff from upstream catchment and the direct rainfall over the dam open area are calculated by taking into account the time of concentration for the catchment. Total 99 different storm durations from 5 minutes to 72 hours were modelled together with five dewatering scenarios from 50 l/s to 500 l/s. The optimised dam/pump configuration is selected by plotting critical points for all cases and storage-dewatering envelopes. A simple economic analysis is also presented in the paper using Present-Value (PV) analysis to assist with the financial evaluation of each configuration and selection of the best alternative.

Keywords: contaminated water, optimisation, pump, sediment dam

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Authors: N. R. P Withana, E. Auch

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The purpose of this study was to investigate perceptions of climate change risk to forest ecosystems and forest-based communities as well as perceived effectiveness of adaptation strategies for climate change as well as challenges for adaptation. Data was gathered using a pre-tested semi-structured questionnaire. Simple random selection technique was applied. For the majority of issues, the responses were obtained on multi-point Likert scales, and the scores provided were, in turn, used to estimate the means and other useful estimates. A composite knowledge index developed using correct responses to a set of self-rated statements were used to evaluate the issues. The mean of the knowledge index was 0.64. Also all respondents recorded values of the knowledge index above 0.25. Increase forest fire was perceived by respondents as the greatest risk to forest eco-system. Decrease access to water supplies was perceived as the greatest risk to livelihoods of forest based communities. The most effective adaptation strategy relevant to climate change risks to forest eco-systems and forest based communities livelihoods in Kathmandu valley in Nepal as perceived by the respondents was reforestation and afforestation. As well, lack of public awareness was perceived as the major limitation for climate change adaptation. However, perceived risks as well as effective adaptation strategies showed an inconsistent association with knowledge indicators and social-cultural variables. The results provide useful information to any party who involve with climate change issues in Nepal, since such attempts would be more effective once the people’s perceptions on these aspects are taken into account.

Keywords: climate change, risk perceptions, forest ecosystems, forest-based communities

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Authors: A. Ashok, K.Satapathy, B. Prerana Nashine

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The objective of this research work is to investigate for one dimensional transient radiative transfer equations with conduction using finite volume method. Within the infrastructure of finite-volume, we obtain the conservative discretization of the terms in order to preserve the overall conservative property of finitevolume schemes. Coupling of conductive and radiative equation resulting in fluxes is governed by the magnitude of emissivity, extinction coefficient, and temperature of the medium as well as geometry of the problem. The problem under consideration has been solved, for a slab dominating radiation coupled with transient conduction based on finite volume method. The boundary conditions are also chosen so as to give a good model of the discretized form of radiation transfer equation. The important feature of the present method is flexibility in specifying the control angles in the FVM, while keeping the simplicity in the solution procedure. Effects of various model parameters are examined on the distributions of temperature, radiative and conductive heat fluxes and incident radiation energy etc. The finite volume method is considered to effectively evaluate the propagation of radiation intensity through a participating medium.

Keywords: participating media, finite volume method, radiation coupled with conduction, transient radiative heat transfer

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Authors: Qaiser Munir, Hamid Hussain

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Oil prices are believed to have a major impact on several economic indicators, leading to several instances where a comparison between oil prices and a trade deficit of oil-importing countries have been carried out. Building upon the narrative, this paper sheds light on the ongoing debate by inquiring upon the possibility of asymmetric linkages between oil prices, industrial production, exchange rate, whole price index, and trade deficit. The analytical tool used to further understand the complexities of a recent approach called nonlinear auto-regressive distributed lag model (NARDL) is utilised. Our results suggest that there are significant asymmetric effects among the main variables of interest. Further, our findings indicate that any variation in oil prices, industrial production, exchange rate, and whole price index on trade deficit tend to fluctuate in the long run. Moreover, the long-run picture denotes that increased oil price leads to a negative impact on the trade deficit, which, in its true essence, is a disproportionate impact. In addition to this, the Wald test simultaneously conducted concludes the absence of any significant evidence of the asymmetry in the oil prices impact on the trade balance in the short-run.

Keywords: trade deficit, oil prices, developing economy, NARDL

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Authors: Zelalem Markos Borko

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The quality of life of people with blindness is significantly influenced by the level of resilience they possess. A qualitative approach of the descriptive phenomenological design was employed to address basic study objectives. The researcher purposely selected three blind graduate students from Sidist Kilo Campus and conducted a semi-structured interview to gather data. Data were analyzed by using thematic coding techniques. The present study found that personal characteristics such as commitment, living hope, motivation, positive self-esteem, self-confidence, and communication have shaped resiliency for successful university students with visual disabilities. The finding showed that the school environment is the place in which blind students had developed/experienced social, psychological, and economical competency and hope for their academic and entire life success. Furthermore, the finding showed that blind students had experienced individual, family, school, and community-related risks in the success track. Therefore, governmental and non-governmental organizations should provide training for students with visual impairments that focus on the individual traits that shape resilience for academic success, such as commitment, living hope, motivation, positive self-esteem, self-confidence, and communication and also community-oriented training should be to break the social stigma and discriminations for the individuals with the visual impairment.

Keywords: blind students, risk and protective factors, lived experience, success

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Authors: Martins Onyekwelu Onuorah, Jnr Dahiru Usman

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Introduction: In the realm of public health, the threat posed by Monkeypox continues to elicit concern, prompting rigorous studies to understand its dynamics and devise effective containment strategies. Particularly significant is its recurrence in variable populations, such as the observed outbreak in Nigeria in 2022. In light of this, our study undertakes a meticulous analysis, employing a data-driven approach to explore, validate, and propose optimized intervention strategies tailored to the distinct dynamics of Monkeypox within varying demographic structures. Utilizing a deterministic mathematical model, we delved into the intricate dynamics of Monkeypox, with a particular focus on a variable population context. Our qualitative analysis provided insights into the disease-free equilibrium, revealing its stability when R0 is less than one and discounting the possibility of backward bifurcation, as substantiated by the presence of a single stable endemic equilibrium. The model was rigorously validated using real-time data from the Nigerian 2022 recorded cases for Epi weeks 1 – 52. Transitioning from qualitative to quantitative, we augmented our deterministic model with optimal control, introducing three time-dependent interventions to scrutinize their efficacy and influence on the epidemic's trajectory. Numerical simulations unveiled a pronounced impact of the interventions, offering a data-supported blueprint for informed decision-making in containing the disease. A comprehensive cost-effectiveness analysis employing the Infection Averted Ratio (IAR), Average Cost-Effectiveness Ratio (ACER), and Incremental Cost-Effectiveness Ratio (ICER) facilitated a balanced evaluation of the interventions’ economic and health impacts. In essence, our study epitomizes a holistic approach to understanding and mitigating Monkeypox, intertwining rigorous mathematical modeling, empirical validation, and economic evaluation. The insights derived not only bolster our comprehension of Monkeypox's intricate dynamics but also unveil optimized, cost-effective interventions. This integration of methodologies and findings underscores a pivotal stride towards aligning public health imperatives with economic sustainability, marking a significant contribution to global efforts in combating infectious diseases.

Keywords: monkeypox, equilibrium states, stability, bifurcation, optimal control, cost-effectiveness

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Authors: Radhe Tado, Ashish B. Deoghare, K. M. Pandey

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The aim of this study is to estimate the effect of blood flow through the coronary artery in human heart so as to assess the coronary artery disease.Velocity, wall shear stress (WSS), strain rate and wall pressure distribution are some of the important hemodynamic parameters that are non-invasively assessed with computational fluid dynamics (CFD). These parameters are used to identify the mechanical factors responsible for the plaque progression and/or rupture in left coronary arteries (LCA) in coronary arteries.The initial step for CFD simulations was the construction of a geometrical model of the LCA. Patient specific artery model is constructed using computed tomography (CT) scan data with the help of MIMICS Research 19.0. For CFD analysis ANSYS FLUENT-14.5 is used.Hemodynamic parameters were quantified and flow patterns were visualized both in the absence and presence of coronary plaques. The wall pressure continuously decreased towards distal segments and showed pressure drops in stenotic segments. Areas of high WSS and high flow velocities were found adjacent to plaques deposition.

Keywords: angiography, computational fluid dynamics (CFD), time-average wall shear stress (TAWSS), wall pressure, wall shear stress (WSS)

Procedia PDF Downloads 191

Authors: Ayoade Adeyemi, Leo Nherera, Paul Trueman, Antje Emmermann

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Background and objectives: Radiofrequency (RF) generated plasma chondroplasty is considered a promising treatment alternative to mechanical debridement (MD) with a shaver. The aim of the study was to perform a cost-effectiveness analysis comparing costs and outcomes following COBLATION chondroplasty versus mechanical debridement in patients with knee pain associated with a medial meniscus tear and idiopathic ICRS grade III focal lesion of the medial femoral condyle from a payer perspective. Methods: A decision-analytic model was developed comparing economic and clinical outcomes between the two treatment options in German patients following knee chondroplasty. Revision rates based on the frequency of repeat arthroscopy, osteotomy and conversion to total knee replacement, reimbursement costs and outcomes data over a 4-year time horizon were extracted from published literature. One-way sensitivity analyses were conducted to assess uncertainties around model parameters. Threshold analysis determined the revision rate at which model results change. All costs were reported in 2016 euros, future costs were discounted at a 3% annual rate. Results: Over a 4 year period, COBLATION chondroplasty resulted in an overall net saving cost of €461 due to a lower revision rate of 14% compared to 48% with MD. Threshold analysis showed that both options were associated with comparable costs if COBLATION revision rate was assumed to increase up to 23%. The initial procedure costs for COBLATION were higher compared to MD and outcome scores were significantly improved at 1 and 4 years post-operation versus MD. Conclusion: The analysis shows that COBLATION chondroplasty is a cost-effective option compared to mechanical debridement in the treatment of patients with a medial meniscus tear and idiopathic ICRS grade III defect of the medial femoral condyle.

Keywords: COBLATION, cost-effectiveness, knee chondroplasty, mechanical debridement

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Authors: Khalil Ur Rehman, M. Y. Malik, Usman Ali

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In this paper, the problem proposed by Von Karman is treated in the attendance of additional flow field effects when the liquid is spaced above the rotating rigid disk. To be more specific, a purely viscous fluid flow yield by rotating rigid disk with Navier’s condition is considered in both magnetohydrodynamic and hydrodynamic frames. The rotating flow regime is manifested with heat source/sink and chemically reactive species. Moreover, the features of thermophoresis and Brownian motion are reported by considering nanofluid model. The flow field formulation is obtained mathematically in terms of high order differential equations. The reduced system of equations is solved numerically through self-coded computational algorithm. The pertinent outcomes are discussed systematically and provided through graphical and tabular practices. A simultaneous way of study makes this attempt attractive in this sense that the article contains dual framework and validation of results with existing work confirms the execution of self-coded algorithm for fluid flow regime over a rotating rigid disk.

Keywords: Navier’s condition, Newtonian fluid model, chemical reaction, heat source/sink

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Authors: Maria Lita Sudo

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The debate is an effective tool in cultivating critical thinking skills in English classes. It involves writing evidence-based arguments about a resolution in a form of constructive speech and oral discussion using constructive speech, which will then be attacked and defended. In the process of writing, EFL learners may experience anxiety, an emotional problem that affects writing achievement and cognitive processing. Thus, this study explored the sources and effect of English writing anxiety in the context of debate writing with a view to providing EFL teachers pedagogical suggestions in alleviating English writing anxiety in debate writing. The participants of this study are 95 Japanese senior high school EFL learners and 3 Japanese senior high school English teachers. In selecting the participants, opportunity sampling was employed and consent from Japanese English teachers was sought. Data were collected thru (1) observation (2) open-ended questionnaire and (3) semi-structured interview. This study revealed that not all teachers of English in the context of this study recognize the existence of English writing anxiety among their students and that the very nature of the debate, in general, may also be a source of English writing anxiety in the context of debate writing. The interview revealed that English writing anxiety affects students’ ability to retrieve L2 vocabulary. Further, this study revealed different sources of writing anxiety in debate writing, which can be categorized into four main categories: (1) L2 linguistic ability-related factors (2) instructional –related factors, (3) interpersonal-related factors, and (4) debate- related factors. Based on the findings, recommendations for EFL teachers and EFL learners in managing writing anxiety in debate writing are provided.

Keywords: debate, EFL learners, English writing anxiety, sources

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Authors: Rungrot Trongsakul

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This paper was aimed to study the strategic cooperation development of Thailand in accordance with the door open policy of Myanmar, by use of DIMES Model: Diplomacy, Information, Military and Economics, Socio-Culture. This research employed qualitative method, aiming to study, analyze and synthesize the content of laws, policies, relevant research papers and documents, and relevant theories, and to study external environment and national power based on DIMES Model. The five steps of strategic development utilized in this study included (1) conceptual framework and definition; (2) environmental scanning; (3) assessing; (4) determining; and (5) drafting strategic plan. The suggested strategies were based on the concept of 'Soft Power'. Therefore, the determination of measures, action plans or projects as strategic means of public and private organizations should be based on sincere participation among people and communities living on the borders shared by both countries. Adoption of education, learning and sharing process is a key to building sustainability of the countries’ strategic cooperation, while an application of 'Soft Power' in all dimensions of the cooperation between the two countries was suggested.

Keywords: education, strategic cooperation, Thailand-Myanmar borders, sustainability

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Authors: K. D. R. Jagath-Kumara, D. D. Dias

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The sea waves carry thousands of GWs of power globally. Although there are a number of different approaches to harness offshore energy, they are likely to be expensive, practically challenging and vulnerable to storms. Therefore, this paper considers using the near shore waves for generating mechanical and electrical power. It introduces two new approaches, the wave manipulation and using a variable duct turbine, for intercepting very wide wave fronts and coping with the fluctuations of the wave height and the sea level, respectively. The first approach effectively allows capturing much more energy yet with a much narrower turbine rotor. The second approach allows using a rotor with a smaller radius but captures energy of higher wave fronts at higher sea levels yet preventing it from totally submerging. To illustrate the effectiveness of the approach, the paper contains a description and the simulation results of a scale model of a wave manipulator. Then, it includes the results of testing a physical model of the manipulator and a single duct, axial flow turbine, in a wave flume in the laboratory. The paper also includes comparisons of theoretical predictions, simulation results and wave flume tests with respect to the incident energy, loss in wave manipulation, minimal loss, brake torque and the angular velocity.

Keywords: near-shore sea waves, renewable energy, wave energy conversion, wave manipulation

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Authors: Yaolin Tian, Shanxiong Chen, Fujia Zhao, Xiaoyu Lin, Hailing Xiong

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Ancient books are significant culture inheritors and their background textures convey the potential history information. However, multi-style texture recovery of ancient books has received little attention. Restricted by insufficient ancient textures and complex handling process, the generation of ancient textures confronts with new challenges. For instance, training without sufficient data usually brings about overfitting or mode collapse, so some of the outputs are prone to be fake. Recently, image generation and style transfer based on deep learning are widely applied in computer vision. Breakthroughs within the field make it possible to conduct research upon multi-style texture recovery of ancient books. Under the circumstances, we proposed a network of layout analysis and image fusion system. Firstly, we trained models by using Deep Convolution Generative against Networks (DCGAN) to synthesize multi-style ancient textures; then, we analyzed layouts based on the Position Rearrangement (PR) algorithm that we proposed to adjust the layout structure of foreground content; at last, we realized our goal by fusing rearranged foreground texts and generated background. In experiments, diversified samples such as ancient Yi, Jurchen, Seal were selected as our training sets. Then, the performances of different fine-turning models were gradually improved by adjusting DCGAN model in parameters as well as structures. In order to evaluate the results scientifically, cross entropy loss function and Fréchet Inception Distance (FID) are selected to be our assessment criteria. Eventually, we got model M8 with lowest FID score. Compared with DCGAN model proposed by Radford at el., the FID score of M8 improved by 19.26%, enhancing the quality of the synthetic images profoundly.

Keywords: deep learning, image fusion, image generation, layout analysis

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Authors: Yonathan Audhitya Suthihono, Ratih Dyah Kusumastuti

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The radiology department in a tertiary referral hospital faces service operation challenges such as huge and various patient arrival, which can increase the probability of patient queuing. During the COVID-19 pandemic, it is mandatory to apply social distancing protocol in the radiology department. A strategy to prevent the accumulation of patients at one spot would be required. The aim of this study is to identify an alternative solution which can reduce the patient’s waiting time in radiology department. Discrete event simulation (DES) is used for this study by constructing several improvement scenarios with Arena simulation software. Statistical analysis is used to test the validity of the base case scenario model and to investigate the performance of the improvement scenarios. The result of this study shows that the selected scenario is able to reduce patient waiting time significantly, which leads to more efficient services in a radiology department, be able to serve patients more effectively, and thus increase patient satisfaction. The result of the simulation can be used by the hospital management to improve the operational performance of the radiology department.

Keywords: discrete event simulation, hospital management patient queuing model, radiology department services

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Authors: Humayun Murshed, Shibly Abdullah

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The research conducted in early seventies apparently assumed the existence of a universal decision model for union negotiators and furthermore tended to regard financial information as a ‘neutral’ input into a rational decision-making process. However, research in the eighties began to question the neutrality of financial information as an input in collective bargaining rather viewing it as a potentially effective means for controlling the labour force. Furthermore, this later research also started challenging the simplistic assumptions relating particularly to union objectives which have underpinned the earlier search for universal union decision models. Despite the above developments there seems to be a dearth of studies in developing countries concerning the use of financial information in collective bargaining. This paper seeks to begin to remedy this deficiency. Utilising a case study approach based on two enterprises, one in the public sector and the other a multinational, the universal decision model is rejected and it is argued that the decision whether or not to use financial information is a contingent one and such a contingency is largely defined by the context and environment in which both union and management negotiators work. An attempt is also made to identify the factors constraining as well as promoting the use of financial information in collective bargaining, these being regarded as unique to the organizations within which the case studies are conducted.

Keywords: collective bargaining, developing countries, disclosures, financial information

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Authors: Victor N. Anisimov, Igor E. Serov, Ksenia M. Kolkova, Natalia V. Galkina

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The problem of memorability of the advertising content is closely connected with the key issues of neuromarketing. The memorability of the advertising content contributes to the marketing effectiveness of the promoted product. Significant directions of studying the phenomenon of memorability are the memorability of the brand (detected through the memorability of the logo) and the memorability of the product offer (detected through the memorization of dynamic audiovisual advertising content - commercial). The aim of this work is to reveal the predictors of memorization of static and dynamic audiovisual stimuli (logos and commercials). An important direction of the research was revealing differences in psychophysiological correlates of memorability between static and dynamic audiovisual stimuli. We assumed that static and dynamic images are perceived in different ways and may have a difference in the memorization process. Objective methods of recording psychophysiological parameters while watching static and dynamic audiovisual materials are well suited to achieve the aim. The electroencephalography (EEG) method was performed with the aim of identifying correlates of the memorability of various stimuli in the electrical activity of the cerebral cortex. All stimuli (in the groups of statics and dynamics separately) were divided into 2 groups – remembered and not remembered based on the results of the questioning method. The questionnaires were filled out by survey participants after viewing the stimuli not immediately, but after a time interval (for detecting stimuli recorded through long-term memorization). Using statistical method, we developed the classifier (statistical model) that predicts which group (remembered or not remembered) stimuli gets, based on psychophysiological perception. The result of the statistical model was compared with the results of the questionnaire. Conclusions: Predictors of the memorability of static and dynamic stimuli have been identified, which allows prediction of which stimuli will have a higher probability of remembering. Further developments of this study will be the creation of stimulus memory model with the possibility of recognizing the stimulus as previously seen or new. Thus, in the process of remembering the stimulus, it is planned to take into account the stimulus recognition factor, which is one of the most important tasks for neuromarketing.

Keywords: memory, commercials, neuromarketing, EEG, branding

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Authors: Vikrant Gupta, Amrit Goswami

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The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

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Authors: Mohammad Abdallah

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Due to the constant increase in terrorist attacks, the research and engineering communities have given significant attention to building performance under explosions. This paper presents a methodology for studying and simulating the dynamic responses of steel structures during external detonations, particularly for accurately investigating the impact of incrementing charge weight on the members total behavior, resistance and failure. Prediction damage method was introduced to evaluate the damage level of the steel members based on five scenarios of explosions. Johnson–Cook strength and failure model have been used as well as ABAQUS finite element code to simulate the explicit dynamic analysis, and antecedent field tests were used to verify the acceptance and accuracy of the proposed material strength and failure model. Based on the structural response, evaluation criteria such as deflection, vertical displacement, drift index, and damage level; the obtained results show the vulnerability of steel columns and un-braced steel frames which are designed and optimized to carry dead and live load to resist and endure blast loading.

Keywords: steel structure, blast load, terrorist attacks, charge weight, damage level

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Authors: Marina E. Konstantinidi

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It is now well-established that the fight against climate change and its consequences, which are a threat to mankind and to life on the planet Earth, requires that global temperature rise be kept under 1,5°C. It is also well-established that this requires humanity to put an end to the use of fossil fuels in the next decades, at the latest. However, investors in the fossil energy sector have brought or threatened to bring investment arbitration claims against States which put an end to their activity for the purpose of reaching their climate change policies’ objectives. Examples of such claims are provided by the cases of WMH v. Canada, Lone Pine v. Canada, Uniper v. Netherlands and RWE v. Netherlands. Irrespective of the outcome of the arbitration proceedings, the risk of being ordered to pay very substantial damages may have a ‘chilling effect’ on States, meaning that they may hesitate to implement the energy transition measures needed to fight climate change and its consequences. Although mitigation action is a relatively recent phenomenon, knowledge about the negative impact of fossil fuels has existed for a long time ago. In this paper, it is argued that structured documentation of evidence of knowledge about climate change may influence the adjudication of investment treaty claims and, consequently, affect the content of energy transition regulations that will be implemented. For example, as concerns investors, evidence that change in the regulatory framework towards environmental protection could have been predicted would refute the argument concerning legitimate expectations for legislative stability. By reference to relevant case law, it attempted to explore how pre-existing knowledge about climate change can be used in the adjudication of investor-State disputes and resulting from green energy transition policies.

Keywords: climate change, energy transition, international investment law, knowledge

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Authors: Dhiaadin Bahaadin Noory

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This research involves the effect of both sizes of reinforced zone and the amount of polypropylene fiber reinforcement on the structural behavior of model-reinforced sand loaded by square footing. The ratio of the side of the square reinforced zone to the footing width (W/B) and the ratio of the square reinforced zone depth to footing width (H/B) has been varied from one to six and from one to three, respectively. The tests were carried out on a small-scale laboratory model in which uniform-graded sand was used as a fill material. It was placed in a highly dense state by hitting a thin wooden board placed on the sand surface with a hammer. The sand was reinforced with randomly oriented discrete fibrillated polypropylene fibers. The test results indicated a significant increase in the bearing capacity and stiffness of the subgrade and a modification of load–the settlement behavior of sand with the size of the reinforced zone and amount of fiber reinforcement. On the basis of the present test results, the optimal side width and depth of the reinforced zone were 4B and 2B, respectively, while the optimal percentage of fibers was 0.4%.

Keywords: square footing, polypropylene fibers, bearing capacity, stiffness, load settlement behavior, relative density

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Authors: Roberta Martino, Viviana Ventre

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The Discounted Utility Model is the essential reference for calculating the utility of intertemporal prospects. According to this model, the value assigned to an outcome is the smaller the greater the distance between the moment in which the choice is made and the instant in which the outcome is perceived. This diminution determines the intertemporal preferences of the individual, the psychological significance of which is encapsulated in the discount rate. The classic model provides a discount rate of linear or exponential nature, necessary for temporally consistent preferences. Empirical evidence, however, has proven that individuals apply discount rates with a hyperbolic nature generating the phenomenon of intemporal inconsistency. What this means is that individuals have difficulty managing their money and future. Behavioral finance, which analyzes the investor's attitude through cognitive psychology, has made it possible to understand that beyond individual financial competence, there are factors that condition choices because they alter the decision-making process: behavioral bias. Since such cognitive biases are inevitable, to improve the quality of choices, research has focused on a personalized approach to strategies that combines behavioral finance with personality theory. From the considerations, it emerges the need to find a procedure to construct the personalized strategies that consider the personal characteristics of the client, such as age or gender, and his personality. The work is developed in three parts. The first part discusses and investigates the weight of the degree of impatience and impatience decrease in the anomalies of the discounted utility model. Specifically, the degree of decrease in impatience quantifies the impact that emotional factors generated by haste and financial market agitation have on decision making. The second part considers the relationship between decision making and personality theory. Specifically, four behavioral categories associated with four categories of behavioral investors are considered. This association allows us to interpret intertemporal choice as a combination of bias and temperament. The third part of the paper presents a method for constructing personalized strategies using Analytic Hierarchy Process. Briefly: the first level of the analytic hierarchy process considers the goal of the strategic plan; the second level considers the four temperaments; the third level compares the temperaments with the anomalies of the discounted utility model; and the fourth level contains the different possible alternatives to be selected. The weights of the hierarchy between level 2 and level 3 are constructed considering the degrees of decrease in impatience derived for each temperament with an experimental phase. The results obtained confirm the relationship between temperaments and anomalies through the degree of decrease in impatience and highlight that the actual impact of emotions in decision making. Moreover, it proposes an original and useful way to improve financial advice. Inclusion of additional levels in the Analytic Hierarchy Process can further improve strategic personalization.

Keywords: analytic hierarchy process, behavioral finance anomalies, intertemporal choice, personalized strategies

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Authors: Sisay Wondmagegn Molla, Mulugeta Admasu Delele, Tadelle Nigusu Mekonen

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It is common to observe quality deterioration and mechanical injury of horticulture products as a result of suboptimal design and handling of the packaging systems. Society uses the old and primitive way of handling horticulture products, which is produced through trial and error This method is known to have many limitations on quality, environmental pollution, labor and cost. Ethiopia stands first in bamboo resources in Africa, which is 67 % of the African and 7 % of the world's bamboo resources. The purpose of this project was to design and develop bamboo-based ventilated horticultural produce crates using validated computational fluid dynamics (CFD). The model was used to predict the airflow and temperature distribution inside the loaded crate. The study included: sizing, collection of the thermo-physical properties, and designing and developing a CFD model of the bamboo-based ventilated horticultural crate. The designed crate (40×30×25cm) had a capacity of about 18 kg, and cold air temperature (130C) was used for cooling the fruit. Airflow in the loaded crate is far from uniform. There is a relatively high-velocity flow at the top, near inlet and near outlet sections, and a relatively low airflow near the center of the loaded crate. The predicted velocity variation within the bulk of the produce was relatively large, it was in the range of 0.04-7m/s. The vented produce package contributed the highest cooling airflow resistance. Similar to the airflow, the cooling characteristics of the product were not uniform. There was a difference in the cooling rate of the produce in the airflow direction and from the top to the bottom section of the loaded crate. The products that were located near the inlet side and top of the bulk showed a faster cooling rate than the rest of the bulk. The result showed that the produced volume average temperature was 17.9°C after a cooling period of 3 hr. It was reduced by 12.05°C. The result showed the potential of the CFD modeling approach in developing the bamboo-based design of horticultural produce crates in terms of airflow and heat transfer characteristics.

Keywords: bamboo, modeling, cooling, horticultural, packaging

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