Search results for: supply demand model

Authors: Niyongabo Elyse

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Prefabricated building construction is a pioneering approach that combines design, production, and assembly to attain energy efficiency, environmental sustainability, and economic feasibility. Despite continuous development in the industry in China, the low technical maturity of standardized design, factory production, and construction assembly introduces uncertainties affecting prefabricated component production and on-site assembly processes. This research focuses on enhancing project management performance under uncertainty to help enterprises navigate these challenges and optimize project resources. The study introduces a perspective on how uncertain factors influence the implementation of prefabricated building construction projects. It proposes a theoretical model considering project process management ability, adaptability to uncertain environments, and collaboration ability of project participants. The impact of uncertain factors is demonstrated through case studies and quantitative analysis, revealing constraints on implementation time, cost, quality, and safety. To address uncertainties in prefabricated component production scheduling, a fuzzy model is presented, expressing processing times in interval values. The model utilizes a cooperative co-evolution evolution algorithm (CCEA) to optimize scheduling, demonstrated through a real case study showcasing reduced project duration and minimized effects of processing time disturbances. Additionally, the research addresses on-site assembly construction scheduling, considering the relationship between task processing times and assigned resources. A multi-objective model with fuzzy activity durations is proposed, employing a hybrid cooperative co-evolution evolution algorithm (HCCEA) to optimize project scheduling. Results from real case studies indicate improved project performance in terms of duration, cost, and resilience to processing time delays and resource changes. The study also introduces a multistage dynamic process control model, utilizing IoT technology for real-time monitoring during component production and construction assembly. This approach dynamically adjusts schedules when constraints arise, leading to enhanced project management performance, as demonstrated in a real prefabricated housing project. Key contributions include a fuzzy prefabricated components production scheduling model, a multi-objective multi-mode resource-constrained construction project scheduling model with fuzzy activity durations, a multi-stage dynamic process control model, and a cooperative co-evolution evolution algorithm. The integrated mathematical model addresses the complexity of prefabricated building construction project management, providing a theoretical foundation for practical decision-making in the field.

Keywords: prefabricated construction, project management performance, uncertainty, fuzzy scheduling

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Authors: Sai S. Hari, Shriram Ramanujam, Unnati Trivedi

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The advent of mass transit systems like rail, metro, maglev, and various other rail based transport has pacified the requirement of public transport for the masses to a great extent. However, the abatement of the demand does not necessarily mean it is managed efficiently, eloquently or in an encapsulating manner. The primary problem identified that the one this paper seeks to solve is the dipsomaniac like manner in which the compartments are occupied. This problem is solved by using a comparison of an empty train and an occupied one. The pixel data of an occupied train is compared to the pixel data of an empty train. This is done using canny edge detection technique. After the comparison it intimates the passengers at the consecutive stops which compartments are not occupied or have low occupancy. Thus, redirecting them and preventing overcrowding.

Keywords: canny edge detection, comparison, encapsulation, redirection

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Authors: M. Khairudin

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This paper investigates the system identification and design quantitative feedback theory (QFT) for the robust control of a lathe spindle. The dynamic of the lathe spindle is uncertain and time variation due to the deepness variation on cutting process. System identification was used to obtain the dynamics model of the lathe spindle. In this work, real time system identification is used to construct a linear model of the system from the nonlinear system. These linear models and its uncertainty bound can then be used for controller synthesis. The real time nonlinear system identification process to obtain a set of linear models of the lathe spindle that represents the operating ranges of the dynamic system. With a selected input signal, the data of output and response is acquired and nonlinear system identification is performed using Matlab to obtain a linear model of the system. Practical design steps are presented in which the QFT-based conditions are formulated to obtain a compensator and pre-filter to control the lathe spindle. The performances of the proposed controller are evaluated in terms of velocity responses of the the lathe machine spindle in corporating deepness on cutting process.

Keywords: lathe spindle, QFT, robust control, system identification

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Authors: Tiantian Feng

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There is a dearth of research on the literary circle as a teaching strategy in English as a Foreign Language (EFL) classes in Chinese colleges and universities and even fewer empirical studies on its impacts. In this one-quarter, design-based project, the researcher aims to increase students’ engagement, cooperation, and, on top of that, reading comprehension performance by utilizing a researcher-developed, adapted reading circle model in an EFL reading course at a Chinese college. The model also integrated team-based learning and portfolio assessment, with an emphasis on the specialization of individual responsibilities, contributions, and outcomes in reading projects, with the goal of addressing current issues in EFL classes at Chinese colleges, such as passive learning, test orientation, ineffective and uncooperative teamwork, and lack of dynamics. In this quasi-experimental research, two groups of students enrolled in the course were invited to participate in four in-class team projects, with the intervention class following the adapted literature circle model and team members rotating as Leader, Coordinator, Brain trust, and Reporter. The researcher/instructor used a sequential explanatory mixed-methods approach to quantitatively analyze the final grades for the pre-and post-tests, as well as individual scores for team projects and will code students' artifacts in the next step, with the results to be reported in a subsequent paper(s). Initial analysis showed that both groups saw an increase in final grades, but the intervention group enjoyed a more significant boost, suggesting that the adapted reading circle model is effective in improving students’ reading comprehension performance. This research not only closes the empirical research gap of literature circles in college EFL classes in China but also adds to the pool of effective ways to optimize reading comprehension performance and class performance in college EFL classes.

Keywords: literature circle, EFL teaching, college english reading, reading comprehension

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Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

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Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing

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Authors: Amin Ardali, Mohammadreza Khalili, Mohammadreza Rezai

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In this paper, dynamic response of thin smart composite panel subjected to low-velocity transverse impact is investigated. Shape memory wires are used to reinforced curved composite panel in a smart way. One-dimensional thermodynamic constitutive model by Liang and Rogers is used for estimating the structural recovery stress. The two degrees-of-freedom mass-spring model is used for evaluation of the contact force between the curved composite panel and the impactor. This work is benefited from the Hertzian linear contact model which is linearized for the impact analysis of curved composite panel. The governing equations of curved panel are provided by first-order shear theory and solved by Fourier series related to simply supported boundary condition. For this purpose, the equation of doubly curved panel motion included the uniform in-plane forces is obtained. By the present analysis, the curved panel behavior under low-velocity impact, and also the effect of the impact parameters, the shape memory wire and the curved panel dimensions are studied.

Keywords: doubly curved shell, SMA wire, impact response, smart material, shape memory alloy

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Authors: Jian-Heng Wu, Bor-Shen Lin

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The temperature-salinity relationship is one of the most important characteristics used for identifying water masses in marine research. Temperature-salinity characteristics, however, may change dynamically with respect to the geographic location and is quite sensitive to the depth at the same location. When depth is taken into consideration, however, it is not easy to compare the characteristics of different water masses efficiently for a wide range of areas of the ocean. In this paper, the Gaussian mixture model was proposed to analyze the temperature-salinity-depth characteristics of water masses, based on which comparison between water masses may be conducted. Gaussian mixture model could model the distribution of a random vector and is formulated as the weighting sum for a set of multivariate normal distributions. The temperature-salinity-depth data for different locations are first used to train a set of Gaussian mixture models individually. The distance between two Gaussian mixture models can then be defined as the weighting sum of pairwise Bhattacharyya distances among the Gaussian distributions. Consequently, the distance between two water masses may be measured fast, which allows the automatic and efficient comparison of the water masses for a wide range area. The proposed approach not only can approximate the distribution of temperature, salinity, and depth directly without the prior knowledge for assuming the regression family, but may restrict the complexity by controlling the number of mixtures when the amounts of samples are unevenly distributed. In addition, it is critical for knowledge discovery in marine research to represent, manage and share the temperature-salinity-depth characteristics flexibly and responsively. The proposed approach has been applied to a real-time visualization system of ocean data, which may facilitate the comparison of water masses by aggregating the data without degrading the discriminating capabilities. This system provides an interface for querying geographic locations with similar temperature-salinity-depth characteristics interactively and for tracking specific patterns of water masses, such as the Kuroshio near Taiwan or those in the South China Sea.

Keywords: water mass, Gaussian mixture model, data visualization, system framework

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Authors: U. Yavas, M. Gokasan

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Control of diesel engine’s air path has drawn a lot of attention due to its multi input-multi output, closed coupled, non-linear relation. Today, precise control of amount of air to be combusted is a must in order to meet with tight emission limits and performance targets. In this study, passenger car size diesel engine is modeled by AVL Boost RT, and then simulated with standard, industry level PID controllers. Finally, linear model predictive control is designed and simulated. This study shows the importance of modeling and control of diesel engines with flexible algorithm development in computer based systems.

Keywords: predictive control, engine control, engine modeling, PID control, feedforward compensation

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Authors: Yusha'u Shu'aibu Baraya, Kah Keng Wong, Nik Soriani Yaacob

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Strobilanthes crispus (S. crispus), is a Malaysian herb locally known as ‘Pecah kaca’ or ‘Jin batu’ which have demonstrated potent anticancer effects in both in vitro and in vivo models. In particular, S. crispus subfraction (SCS) significantly reduced tumor growth in N-methyl-N-Nitrosourea-induced breast cancer rat model. However, there is paucity of information on the effects of SCS in breast cancer metastasis. Thus, in this study, the antimetastatic effects of SCS (100 mg/kg) was investigated following 30 days of treatment in 4T1-induced mammary tumor (n = 5) model. The response to treatment was assessed based on the outcome of the tumour growth, body weight and hematological parameters. The results demonstrated that tumor bearing mice treated with SCS (TM-S) had significant (p<0.05) reduction in the mean tumor number and tumor volume as well as tumor weight compared to the tumor bearing mice (TM), i.e. tumor untreated group. Also, there was no secondary tumor formation or tumor-associated lesions in the major organs of TM-S compared to the TM group. Similarly, comparable body weights were observed among the TM-S, normal (uninduced) mice treated with SCS and normal (untreated/control) mice (NM) groups compared to the TM group (p<0.05). Furthermore, SCS administration does not cause significant changes in the hematological parameters as compared to the NM group, which indicates no sign of anemia and toxicity related effects. In conclusion, SCS significantly inhibited the overall tumor growth and metastasis in 4T1-induced breast cancer mouse model suggesting its promising potentials as therapeutic agent for breast cancer treatment.

Keywords: 4T1-cells, breast cancer, metastasis, Strobilanthes crispus

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Authors: Tingyu Zhang

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The horizontal ecological compensation (HEC) mechanism is the key to stimulating the active participation of the whole basin in ecological protection. In this paper, we construct an evolutionary model for HEC in the Yangtze River Economic Belt (YREB) basin with the introduction of the central government constraint and incentive mechanism (CGCIM) and explore the conditions for the realization of a (Protection and compensation) strategy that meets the social expectations. Further, the water quality-water quantity model is utilized to measure the HEC amount with the characteristic factual data of the YREB in 2020-2022. The results show that the stability of the evolutionary game model of upstream and downstream governments in the YREB is closely related to the CGCIM. If (Protection Compensation) is to be realized as the only evolutionary stable strategy of the evolutionary game system composed of upstream and downstream governments, it is necessary for the CGCIM to satisfy that the sum of the incentives for the protection side and its unilateral or bilateral constraints is greater than twice the input cost of the active strategy, and the sum of the incentives for the compensation side and its unilateral or bilateral constraints is greater than the amount of ecological compensation that needs to be paid by it when it adopts the active strategy. At this point, the total amount of HEC that the downstream government should give to the upstream government of the YREB is 2856.7 million yuan in 2020, 5782.1 million yuan in 2021, and 23166.7 million yuan in 2022. The results of the study can provide a reference for promoting the improvement and refinement of the HEC mechanism in the YREB.

Keywords: horizontal ecological compensation, Yangtze river economic belt, evolutionary game analysis, water quality and quantity model research on territorial ecological restoration in Mianzhu city, Sichuan, under the dual evaluation framework

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Authors: A. Omeiri, A. Djellad, P. O. Logerais, O. Riou, J. F. Durastanti

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With the growing of electrical energy demand, wind power capacity has experienced tremendous growth in the past decade, thanks to wind power’s environmental benefits. Direct driven permanent magnet synchronous generator (PMSG) with a full size back-to-back converter set is one of the promising technologies employed with wind power generation. Wind grid integration brings the problems of voltage fluctuation and harmonic pollution. In the present study, the filter is placed between the wind system and the network to reduce the total harmonic distortion (THD) and enhance power quality during disturbances. The models of wind turbine, PMSG, power electronic converters and the filter are implemented in MATLAB/SIMULINK environment.

Keywords: wind energy conversion system, PMSG, PWM, THD, power quality, passive filter

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Authors: Huihui Zhang, Zhongzhi Zhang

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Coagulation/flocculation is regarded a simple and effective wastewater treatment technology. Chlorine-containing coagulants may release chloride ions into the wastewater, causing corrosion. A green chlorine-free coagulant of polyaluminum ferric silicate (PSAF) was prepared by the copolymerization method to treat oily refractory wastewaters. Results showed that the highest removal efficiency of turbidity and chemical oxygen demand (COD) achieved 97.4% and 93.0% at a dosage of 700 mg/L, respectively. After PSAF coagulation, the chloride ion concentration was also almost the same as that in the raw wastewater. Thus, the chlorine-free coagulant is highly efficient and does not introduce additional chloride ions into the wastewater, avoiding corrosion.

Keywords: coagulation, chloride-free coagulant, oily refractory wastewater, coagulation performance

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Authors: Emílie Kučerová, Tereza Veverková, Marina Morozovová, Eva Kudová, Jitka Viktorová

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The blood-brain barrier (BBB) is a key element regulating the transport of substances between the blood and the central nervous system (CNS). The BBB protects the CNS from potentially harmful substances and maintains a suitable environment for nervous activity in the CNS, but at the same time, it represents a significant obstacle to the entry of drugs into the CNS. Pharmacoresistant epilepsy is a form of epilepsy that cannot be suppressed using two (or more) appropriately chosen antiepileptic drugs. In many cases, pharmacoresistant epilepsy is characterized by an increased concentration of efflux pumps on the luminal sides of the endothelial cells that form the BBB and an increased number of drug-metabolizing enzymes in the BBB cells, thereby preventing the effective transport of antiepileptic drugs into the CNS. Currently, a number of scientific groups are focusing on the preparation and improvement of BBB models in vitro in order to study cell interactions or transport mechanisms. However, in pathological conditions such as pharmacoresistant epilepsy, there are changes in BBB structure, and current BBB models are insufficient for related research. Our goal is to develop a suitable BBB model for pharmacoresistant epilepsy in vitro and use it to test the transfer of potential antiepileptic drugs. This model is created by co-culturing immortalized human cerebral microvascular endothelial cells, human vascular pericytes and immortalized human astrocytes. The BBB in vitro is cultivated in the form of a 2D transwell model and the integrity of the barrier is verified by measuring transendothelial electrical resistance (TEER). From the current results, a contact cell arrangement with the cultivation of endothelial cells on the upper side of the insert and the co-cultivation of astrocytes and pericytes on the lower side of the insert is selected as the most promising for BBB model cultivation. The pharmacoresistance of the BBB model is achieved by long-term cultivation of endothelial cells in an increasing concentration of selected antiepileptic drugs, which should lead to increased production of efflux pumps and drug-metabolizing enzymes. The pharmacoresistant BBB model in vitro will be further used for the screening of substances that could act both as antiepileptics and at the same time as inhibitors of efflux pumps in endothelial cells. This project was supported by the Technology Agency of the Czech Republic (TACR), Personalized Medicine: Translational research towards biomedical applications, No. TN02000109 and by the Academy of Sciences of the Czech Republic (AS CR) – grant RVO 61388963.

Keywords: antiepileptic drugs, blood-brain barrier, efflux transporters, pharmacoresistance

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Authors: Kimberly Winnie Achieng Otieno

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The Nairobi Hospital plays a pivotal role in healthcare provision in East and Central Africa, yet it faces challenges in providing accessible dialysis care. This paper explores strategic interventions to enhance dialysis care, improve access and streamline health information management, with an aim of fostering an integrated and patient-centered healthcare system in our region. Challenges at The Nairobi Hospital The Nairobi Hospital currently grapples with insufficient dialysis machines which results in extended turn around times. This issue stems from both staffing bottle necks and infrastructural limitations given our growing demand for renal care services. Our Paper-based record keeping system and fragmented flow of information downstream hinders the hospital’s ability to manage health data effectively. There is also a need for investment in expanding The Nairobi Hospital dialysis facilities to far reaching communities. Setting up satellite clinics that are closer to people who live in areas far from the main hospital will ensure better access to underserved areas. Community Outreach and Education Implementing education programs on kidney health within local communities is vital for early detection and prevention. Collaborating with local leaders and organizations can establish a proactive approach to renal health hence reducing the demand for acute dialysis interventions. We can amplify this effort by expanding The Nairobi Hospital’s corporate social responsibility outreach program with weekend engagement activities such as walks, awareness classes and fund drives. Enhancing Efficiency in Dialysis Care Demand for dialysis services continues to rise due to an aging Kenyan population and the increasing prevalence of chronic kidney disease (CKD). Present at this years International Nursing Conference are a diverse group of caregivers from around the world who can share with us their process optimization strategies, patient engagement techniques and resource utilization efficiencies to catapult The Nairobi Hospital to the 21st century and beyond. Plans are underway to offer ongoing education opportunities to keep staff updated on best practices and emerging technologies in addition to utilizing a patient feedback mechanisms to identify areas for improvement and enhance satisfaction. Staff empowerment and suggestion boxes address The Nairobi Hospital’s organizational challenges. Current financial constraints may limit a leapfrog in technology integration such as the acquisition of new dialysis machines and an investment in predictive analytics to forecast patient needs and optimize resource allocation. Streamlining Health Information Management Fully embracing a shift to 100% Electronic Health Records (EHRs) is a transformative step toward efficient health information management. Shared information promotes a holistic understanding of patients’ medical history, minimizing redundancies and enhancing overall care quality. To manage the transition to community-based care and EHRs effectively, a phased implementation approach is recommended. Conclusion By strategically enhancing dialysis care access and streamlining health information management, The Nairobi Hospital can strengthen its position as a leading healthcare institution in both East and Central Africa. This comprehensive approach aligns with the hospital’s commitment to providing high-quality, accessible, and patient-centered care in an evolving landscape of healthcare delivery.

Keywords: Africa, urology, diaylsis, healthcare

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Authors: Touhami Tahenni

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Excessively wide cracks are harmful to the serviceability of reinforced concrete (RC) beams and may lead to durability problems in the longer term. They also reduce the rigidity of RC sections, rendering the tensile concrete ineffective structurally. To reduce the negative effects of cracks, steel fibers are added to concrete mixes in the same manner as aggregates. In the present work, steel fibers reinforced concrete (SFRC) beams, made of normal strength and high strength concretes, were tested in a four-point bending test using a digital image correlation technique. The beams had different volume fractions of fibres and different aspect ratios (fiber length/fiber diameter). The evaluation of flexural cracking widths was determined using Gom-Aramis software. The experimental crack widths were compared with theoretical values predicted by the technical document of Rilem TC 162-TDF. The model proposed in this document seems to be the only one that considers the efficiency of steel fibres in restraining the crack widths. However, the model of Rilem takes into account only the aspect ratio of steel fibres to predict the crack width of SFRC beams. It has been reported in several pieces of research that the contribution of steel fibres to the limitation of flexural cracking widths is based on three essential parameters namely, the volume fraction, the orientation and the aspect ratio of fibres. Referring to the literature on the flexural cracking behavior of SFRC beams and the experimental observations of the present work, a correction of the Rilem model by the introduction of these parameters in the formula is proposed. The crack widths predicted by the new empirical model were compared with the experimental results and assessed against other test data on SFRC beams taken from the literature. The modified Rilem model gives better results and is found more satisfactory in predicting the crack widths of fibres concrete.

Keywords: stee fibres, reinforced concrete, flexural cracking, tensile strength, crack width

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Authors: Tirtha Raj Dhakal, Brian Davidson, Bob Farquharson

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Institutional design is important if water resources are to be managed efficiently. In Nepal, the supply of water in both farmer- and agency-managed irrigation systems is inefficient because of the weak institutional frameworks. This type of inefficiency is linked with collective problems such as non-excludability of irrigation water, inadequate recognition of property rights and externalities. Irrigation scheme surveys from Nepal as well as existing literature revealed that the Nepalese irrigation sector is facing many issues such as low cost recovery, inadequate maintenance of the schemes and inefficient allocation and utilization of irrigation water. The institutional practices currently in place also fail to create/force any incentives for farmers to use water efficiently and to pay for its use. This, thus, compels the need of refined institutional framework that can address the collective problems and improve irrigation efficiency.

Keywords: agency-managed, cost recovery, farmer-managed, institutional design

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Authors: Sefiu Adebowale Adewumi

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Continuous improvement programme (CIP) adopts an approach to improve organizational performance with small incremental steps over time. In this approach, it is not the size of each step that is important, but the likelihood that the improvements will be ongoing. Many companies in developing nations are now complementing continuous improvement with innovation, which is the successful exploitation of new ideas. Focus area of CIP in the organization was in relation to the size of the organizations and also in relation to the generic classification of these organizations. Product quality was prevalent in the manufacturing industry while manpower training and retraining and marketing strategy were emphasized for improvement to be made in the service, transport and supply industries. However, focus on innovation in raw materials, process and methods are needed because these are the critical factors that influence product quality in the manufacturing industries.

Keywords: continuous improvement programme, developing countries, generic classfications, technological innovation

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Authors: F. Boudet, V. Galano, D. Gmira, L. Munoz, A. Reina

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Commodities pricing needs a specific approach as they are often linked to each other and so are expectedly doing their prices. They are called co-integrated when at least one stationary linear combination exists between them. Though widespread in economic literature, and even if many equilibrium relations and co-movements exist in the economy, this principle of co-movement is not developed in derivatives field. The present study focuses on the following problem: How can the price of a forward agreement on a commodity be simulated, when it is co-integrated with other ones? Theoretical analysis is developed from Gibson-Schwartz model and an analytical solution is given for short maturities contracts and under risk-neutral conditions. The application has been made to crude oil and heating oil energy commodities and result confirms the applicability of proposed method.

Keywords: co-integration, commodities, forward pricing, Gibson-Schwartz

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Authors: K. Boumediene, S. E. Belhenniche

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This article presents a numerical analysis of a turbulent flow past DTMB 4119 marine propeller by the means of RANS approach; the propeller designed at David Taylor Model Basin in USA. The purpose of this study is to predict the hydrodynamic performance of the marine propeller, it aims also to compare the results obtained with the experiment carried out in open water tests; a periodical computational domain was created to reduce the unstructured mesh size generated. The standard kw turbulence model for the simulation is selected; the results were in a good agreement. Therefore, the errors were estimated respectively to 1.3% and 5.9% for KT and KQ.

Keywords: propeller flow, CFD simulation, RANS, hydrodynamic performance

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Authors: Anand Malik

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The Himalayas with high tectonic activities poses a great threat to human life and property. Climate change is another reason which triggering extreme events multiple fold effect on high mountain glacial environment, rock falls, landslides, debris flows, flash flood and snow avalanches. One such extreme event of cloud burst along with breach of moraine dammed Chorabri Lake occurred from June 14 to June 17, 2013, triggered flooding of Saraswati and Mandakini rivers in the Kedarnath Valley of Rudraprayag district of Uttrakhand state of India. As a result, huge volume of water with its high velocity created a catastrophe of the century, which resulted into loss of large number of human/animals, pilgrimage, tourism, agriculture and property. Thus a comprehensive assessment of debris flow hazards requires GIS-based modeling using numerical methods. The aim of present study is to focus on analysis and mapping of debris flow movements using geospatial data with flow-r (developed by team at IGAR, University of Lausanne). The model is based on combined probabilistic and energetic algorithms for the assessment of spreading of flow with maximum run out distances. Aster Digital Elevation Model (DEM) with 30m x 30m cell size (resolution) is used as main geospatial data for preparing the run out assessment, while Landsat data is used to analyze land use land cover change in the study area. The results of the study area show that model can be applied with great accuracy as the model is very useful in determining debris flow areas. The results are compared with existing available landslides/debris flow maps. ArcGIS software is used in preparing run out susceptibility maps which can be used in debris flow mitigation and future land use planning.

Keywords: debris flow, geospatial data, GIS based modeling, flow-R

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Authors: Hanee Ryu

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The supporting policies for renewable energy have been designed to deploy renewable energy technology targeting domestic market. The government encourages market creation through obligations such as FIT or RPS on an energy supplier. With these policy measures, the securing vast market needs to induce technology development. Furthermore, it is crucial that ensuring developing market can make the environment nurture the renewable energy industry. Overseas expansion to countries being in demand is essential under immature domestic market. Extending its business abroad can make the domestic company get the knowledge through learning-by-doing. Besides, operation in the countries to be rich in renewable resources such as weather conditions helps to develop proven track record required for verifying technologies. This paper figures out the factor to hamper the global market entry and build up the strategies to overcome difficulties. Survey conducted renewable energy company having overseas experiences at least once. Based on the survey we check the obstacle against exporting home goods and services. As a result, securing funds is salient fact to proceed to business. It is difficult that only private bank or investment agencies participate in the project under uncertainty which renewable energy development project bears inherently. These uncertainties need public fund such as ODA to encourage private sectors to start a business. Furthermore, international organizations such as IRENA or multilateral development banks as WBG play a role to guarantee the investment including risk insurance against uncertainty. It can also manage excavation business cooperating with developing countries and supplement inadequate government funding involved. With survey results strategies to obtain the order, the international organization places are categorized according to the type of getting a contract. This paper suggests 3 types approaching to the international organization project (going through international competitive bidding, using ODA and project financing) and specifies the role of government to support the domestic firms with running out of funds. Under renewable energy industry environment where hard to being created as a spontaneous market, government policy approach needs to motivate the actors to get into the business. It is one of the good strategies that countries with the low demand of renewable energies participate in the project international agencies order in the developing countries having abundant resources. This provides crucial guidance for the formulation of renewable energy development policy and planning with consideration of business opportunities and funding.

Keywords: exporting strategies, multilateral development banks, promoting in developing countries, renewable energy technologies

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Authors: G. Hubert, S. Aubry

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The earth is constantly bombarded by cosmic rays that can be of either galactic or solar origin. Thus, humans are exposed to high levels of galactic radiation due to altitude aircraft. The typical total ambient dose equivalent for a transatlantic flight is about 50 μSv during quiet solar activity. On the contrary, estimations differ by one order of magnitude for the contribution induced by certain solar particle events. Indeed, during Ground Level Enhancements (GLE) event, the Sun can emit particles of sufficient energy and intensity to raise radiation levels on Earth's surface. Analyses of GLE characteristics occurring since 1942 showed that for the worst of them, the dose level is of the order of 1 mSv and more. The largest of these events was observed on February 1956 for which the ambient dose equivalent rate is in the orders of 10 mSv/hr. The extra dose at aircraft altitudes for a flight during this event might have been about 20 mSv, i.e. comparable with the annual limit for aircrew. The most recent GLE, occurred on September 2017 resulting from an X-class solar flare, and it was measured on the surface of both the Earth and Mars using the Radiation Assessment Detector on the Mars Science Laboratory's Curiosity Rover. Recently, Hubert et al. proposed a GLE model included in a particle transport platform (named ATMORAD) describing the extensive air shower characteristics and allowing to assess the ambient dose equivalent. In this approach, the GCR is based on the Force-Field approximation model. The physical description of the Solar Cosmic Ray (i.e. SCR) considers the primary differential rigidity spectrum and the distribution of primary particles at the top of the atmosphere. ATMORAD allows to determine the spectral fluence rate of secondary particles induced by extensive showers, considering altitude range from ground to 45 km. Ambient dose equivalent can be determined using fluence-to-ambient dose equivalent conversion coefficients. The objective of this paper is to analyze the GCR and SCR impacts on ambient dose equivalent considering a high number statistic of world-flight paths. Flight trajectories are based on the Eurocontrol Demand Data Repository (DDR) and consider realistic flight plan with and without regulations or updated with Radar Data from CFMU (Central Flow Management Unit). The final paper will present exhaustive analyses implying solar impacts on ambient dose equivalent level and will propose detailed analyses considering route and airplane characteristics (departure, arrival, continent, airplane type etc.), and the phasing of the solar event. Preliminary results show an important impact of the flight path, particularly the latitude which drives the cutoff rigidity variations. Moreover, dose values vary drastically during GLE events, on the one hand with the route path (latitude, longitude altitude), on the other hand with the phasing of the solar event. Considering the GLE occurred on 23 February 1956, the average ambient dose equivalent evaluated for a flight Paris - New York is around 1.6 mSv, which is relevant to previous works This point highlights the importance of monitoring these solar events and of developing semi-empirical and particle transport method to obtain a reliable calculation of dose levels.

Keywords: cosmic ray, human dose, solar flare, aviation

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Authors: Etienne Alain Feukeu, L. W. Snyman

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Water scarcity is becoming a real issue nowadays. Most countries in the world are facing it in their own way based on their own geographical coordinate and condition. Many countries are facing a challenge of a growing water demand as a result of not only an increased population, economic growth, but also as a pressure of the population dynamic and urbanization. In view to mitigate some of this related problem, an accurate method of water estimation and future prediction, forecast is essential to guarantee not only the sufficient quantity, but also a good water distribution and management system. Beside the fact that several works have been undertaken to address this concern, there is still a considerable disparity between different methods and standard used for water prediction and estimation. Hence this work contrast and compare two well-defined and established methods from two countries (USA and South Africa) to demonstrate the inconsistency when different method and standards are used interchangeably.

Keywords: water scarcity, water estimation, water prediction, water forecast.

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Authors: Noha A. Alowedi

Abstract:

This paper proposes a Translator Career Path (TCP) which is based on the Dreyfus Model of Skills Acquisition as the conceptual framework. In this qualitative study, the methodology to collect and analyze the data takes an inductive approach that draws upon the literature to form the criteria for the different steps in the TCP. This path is based on descriptors of expert translator performance and best employees’ practice documented in the literature. Each translator skill will be graded as novice, advanced beginner, competent, proficient, and expert. Consequently, five levels of translator performance are identified in the TCP as five ranks. The first rank is the intern translator, which is equivalent to the novice level; the second rank is the assistant translator, which is equivalent to the advanced beginner level; the third rank is the associate translator, which is equivalent to the competent level; the fourth rank is the translator, which is equivalent to the proficient level; finally, the fifth rank is the expert translator, which is equivalent to the expert level. The main function of this career path is to guide the processes of translator development in translation organizations. Although it is designed primarily for the need of in-house translators’ supervisors, the TCP can be used in academic settings for translation trainers and teachers.

Keywords: Dreyfus model, translation organization, translator career path, translator development, translator evaluation, translator promotion

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Authors: Sungjun Hong, Yanghon Chung, Nyunbae Park, Sangyong Park

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South Korea, as the 7th largest greenhouse gas emitting country in 2011, announced that the national reduction target of greenhouse gas emissions was 30% based on BAU (Business As Usual) by 2020. And the reduction rate of the transport sector is 34.3% which is the highest figure among all sectors. This paper attempts to analyze the environmental effect on deploying the green cars in Korean road transport sector. In order to calculate the greenhouse gas emissions, the LEAP model is applied in this study.

Keywords: green car, greenhouse gas, LEAP model, road transport sector

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Authors: Ritesh Kumar, Rajendra Pamula

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In this paper, we present our contribution for book recommendation. In our experiment, we combine the results of Sequential Dependence Model (SDM) and exploitation of book information such as reviews, tags and ratings. This social information is assigned by users. For this, we used CLEF-2016 Social Book Search Track Suggestion task. Finally, our proposed method extensively evaluated on CLEF -2015 Social Book Search datasets, and has better performance (nDCG@10) compared to other state-of-the-art systems. Recently we got the good performance in CLEF-2016.

Keywords: sequential dependence model, social information, social book search, query expansion

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Authors: Rakesh Kumar, A. K. Ghosh

Abstract:

The paper presents the modeling of linear and nonlinear longitudinal aerodynamics using real flight data of Hansa-3 aircraft gathered at low and high angles of attack. The Neural-Gauss-Newton (NGN) method has been applied to model the linear and nonlinear longitudinal dynamics and estimate parameters from flight data. Unsteady aerodynamics due to flow separation at high angles of attack near stall has been included in the aerodynamic model using Kirchhoff’s quasi-steady stall model. NGN method is an algorithm that utilizes Feed Forward Neural Network (FFNN) and Gauss-Newton optimization to estimate the parameters and it does not require any a priori postulation of mathematical model or solving of equations of motion. NGN method was validated on real flight data generated at moderate angles of attack before application to the data at high angles of attack. The estimates obtained from compatible flight data using NGN method were validated by comparing with wind tunnel values and the maximum likelihood estimates. Validation was also carried out by comparing the response of measured motion variables with the response generated by using estimates a different control input. Next, NGN method was applied to real flight data generated by executing a well-designed quasi-steady stall maneuver. The results obtained in terms of stall characteristics and aerodynamic parameters were encouraging and reasonably accurate to establish NGN as a method for modeling nonlinear aerodynamics from real flight data at high angles of attack.

Keywords: parameter estimation, NGN method, linear and nonlinear, aerodynamic modeling

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Authors: Dorothea Voß, Tobias Esser, Michael Huber, Jakob Albert

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The growing world population and the associated increase in demand for energy and consumer goods, as well as increasing waste production, requires the development of sustainable processes. In addition, the increasing environmental awareness of our society is a driving force for the requirement that processes must be as resource and energy efficient as possible. In this context, the use of polyoxometalate catalysts (POMs) has emerged as a promising approach for the development of green processes. POMs are bifunctional polynuclear metal-oxo-anion cluster characterized by a strong Brønsted acidity, a high proton mobility combined with fast multi-electron transfer and tunable redox potential. In addition, POMs are soluble in many commonly known solvents and exhibit resistance to hydrolytic and oxidative degradation. Due to their structure and excellent physicochemical properties, POMs are efficient acid and oxidation catalysts that have attracted much attention in recent years. Oxidation processes with molecular oxygen are worth mentioning here. However, the fact that the POM catalysts are homogeneous poses a challenge for downstream processing of product solutions and recycling of the catalysts. In this regard, nanofiltration membranes have gained increasing interest in recent years, particularly due to their relative sustainability advantage over other technologies and their unique properties such as increased selectivity towards multivalent ions. In order to establish an efficient downstream process for the highly selective separation of homogeneous POM catalysts from aqueous solutions using nanofiltration membranes, a laboratory-scale membrane system was designed and constructed. By varying various process parameters, a sensitivity analysis was performed on a model system to develop an optimized method for the recovery of POM catalysts. From this, process-relevant key figures such as the rejection of various system components were derived. These results form the basis for further experiments on other systems to test the transferability to serval separation tasks with different POMs and products, as well as for recycling experiments of the catalysts in processes on laboratory scale.

Keywords: downstream processing, nanofiltration, polyoxometalates, homogeneous catalysis, green chemistry

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Authors: Eda Yakit Ak, Ergül Aslan

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The study was conducted using the quasi-experimental design to determine the influence of the nursing support program prepared according to the Health Belief Model on reproductive health behaviors of orthopedically disabled women in the physical therapy and rehabilitation clinic at a university hospital between August 2019-October, 2020. The research sample included 50 women (35 in the control group and 15 in the experimental group with orthopedic disability). A 3-week nursing support program was applied to the experimental group of women. To collect the data, Introductory Information Form and Scale for Determining the Protective Attitudes of Married Women towards Reproductive Health (SDPAMW) were applied. The evaluation was made with a follow-up form for four months. In the first evaluation, the total SDPAMW scores were 119.93±20.59 for the experimental group and 122.20±16.71 for the control group. In the final evaluation, the total SDPAMW scores were 144.27±11.95 for the experimental group and 118.00±16.43 for the control group. The difference between the groups regarding the first and final evaluations for the total SDPAMW scores was statistically significant (p<0.01). In the experimental group, between the first and final evaluations regarding the sub-dimensions of SDPAMW, an increase was found in the behavior of seeing the doctor on reproductive health issues, protection from reproductive organ and breast cancer, general health behaviors to protect reproductive health, and protection from genital tract infections (p<0.05). Consequently, the nursing support program based on the Health Belief Model applied to orthopedically disabled women positively affected reproductive health behaviors.

Keywords: orthopedically disabled, woman, reproductive health, nursing support program, health belief model

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Authors: Ravija Gunawardana, Banuka Athuraliya

Abstract:

Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

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