Search results for: supply chain delivery models

Authors: Yuzhi Cai

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In this paper, we discuss a Bayesian approach to quantile autoregressive (QAR) time series model estimation and forecasting. Together with a combining forecasts technique, we then predict USD to GBP currency exchange rates. Combined forecasts contain all the information captured by the fitted QAR models at different quantile levels and are therefore better than those obtained from individual models. Our results show that an unequally weighted combining method performs better than other forecasting methodology. We found that a median AR model can perform well in point forecasting when the predictive density functions are symmetric. However, in practice, using the median AR model alone may involve the loss of information about the data captured by other QAR models. We recommend that combined forecasts should be used whenever possible.

Keywords: combining forecasts, MCMC, predictive density functions, quantile forecasting, quantile modelling

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Authors: Gabi N. Nehme

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Below-knee amputees commonly experience asymmetrical gait patterns. It is generally believed that ischemia is related to the formation of pressure sores due to uneven distribution of forces. Micro-vascular responses can reveal local malnutrition. Changes in local skin blood supply under various external loading conditions have been studied for a number of years. Radionuclide clearance, photo-plethysmography, trans-cutaneous oxygen tension along with other studies showed that the blood supply would be influenced by the epidermal forces, and the rate and the amount of blood supply would decrease with increased epidermal loads being shear forces or normal forces. Several cases of socket designs were investigated using Finite Element Model (FEM) and Design of Experiment (DOE) to increase flexibility and minimize the pressure at the limb/socket interface using ultra high molecular weight polyethylene (UHMWPE) and polyamide 6 (PA6) or Duraform. The pressure reliefs at designated areas where reducing thickness is involved are seen to be critical in determination of amputees’ comfort and are very important to clinical applications. Implementing a hole between the Patellar Tendon (PT) and Distal Tibia (DT) would decrease stiffness and increase prosthesis range of motion where flexibility is needed. In addition, displacement and prosthetic energy storage increased without compromising mechanical efficiency and prosthetic design integrity.

Keywords: patellar tendon, distal tibia, prosthetic socket relief areas, hole implementation

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Authors: Marcelo T. Okano, Oduvaldo Vendrametto, Osmildo S. Santos, Marcelo E. Fernandes, Heide Landi

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The literature on the interorganizational relationship between companies and organizations has increased in recent years, but there are still doubts about the various settings. The interorganizational networks are important in economic life, the fact facilitate the complex interdependence between transactional and cooperative organizations. A need identified in the literature is the lack of indicators to measure and identify the types of existing networks. The objective of this research is to examine the interorganizational relationships of two milk chains through indicators proposed by the theories of the four authors, characterizing them as network or not and what the benefits obtained by the chain organization. To achieve the objective of this work was carried out a survey of milk producers in two regions of the state of São Paulo. To collect the information needed for the analysis, exploratory research, qualitative nature was used. The research instrument of this work consists of a roadmap of semistructured interviews with open questions. Some of the answers were directed by the interviewer in the form of performance notes aimed at detecting the degree of importance, according to the perception of intensity to that regard. The results showed that interorganizational relationships are small and largely limited to the sale of milk or dairy cooperatives. These relationships relate only to trade relations between the owner and purchaser of milk. But when the producers are organized in associations or networks, interorganizational relationships and increase benefits for all participants in the network. The various visits and interviews in several dairy farms in the regions of São Pau-lo (indicated that the inter-relationships are small and largely limited to the sale of milk to cooperatives or dairy. These relationships refer only to trade relations between the owner and the purchaser of milk. But when the producers are organized in associations or networks, interorganizational relationships increase and bring benefits to all participants in the network.

Keywords: interorganizational networks, dairy chain, interorganizational system, São Pau-lo

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Authors: Rajneekant Bachan, Dhanush Vijay

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The visualization of operating systems has refined the Turing machine, and current trends suggest that the emulation of 32 bit architectures will soon emerge. After years of technical research into Web services, we demonstrate the synthesis of gigabit switches, which embodies the robust principles of theory. Loam, our new algorithm for forward-error correction, is the solution to all of these challenges.

Keywords: software engineering, architectures, introspective models, operating systems

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Authors: Nuwan Kuruwitaarachchi, M. K. M. Peiris, C. N. Madawala, K. M. A. R. Perera, V. U. N Perera

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Dealing with businesses with the foreign market always took a special place in a country’s economy. Political and social factors came into play making currency rate changes fluctuate rapidly. Currency rate prediction has become an important factor for larger international businesses since large amounts of money exchanged between countries. This research focuses on comparing the accuracy of mainly three models; Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Networks(ANN) and Support Vector Machines(SVM). series of data import, export, USD currency exchange rate respect to LKR has been selected for training using above mentioned algorithms. After training the data set and comparing each algorithm, it was able to see that prediction in SVM performed better than other models. It was improved more by combining SVM and SVR models together.

Keywords: ARIMA, ANN, FFNN, RMSE, SVM, SVR

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Authors: Tarannom Parhizkar, Halle Bakhteeyar

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This paper presents a feasibility assessment of an expansion system applied to the natural gas transportation process in Iran. Power can be generated from the pressure energy of natural gas along its supply chain at various pressure reduction points by using turboexpanders. This technology is being applied in different countries around the world. The system consists of a turboexpander reducing the natural gas pressure and providing mechanical energy to drive electric generator. Moreover, gas pre-heating, required to prevent hydrate formation, is performed upstream of expansion stage using burner. The city gate station (CGS) has a nominal flow rate in range of 45000 to 270000 cubic meters per hour and a pressure reduction from maximum 62 bar at the upstream to 6 bar. Due to variable feed pressure and temperature in this station sensitivity analysis of generated electricity and required heat is performed. Results show that plant gain is more sensible to pressure variation than temperature changes. Furthermore, using turboexpander to reduce the pressure result in an electrical generation of 2757 to 17574 kW with the value of approximately 4 million US$ per year. Moreover, the required heat range to prevent a hydrate formation is almost 2189 to 14157 kW. To provide this heat, a burner is used with a maximum annual cost of 268,640 $ burner fuel. Therefore, the actual annual benefit of proposed plant modification is approximately over 6,5 million US$.

Keywords: feasibility study, simulation, turboexpander, feed characteristic

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Authors: Lung-Lung Hu

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Ronald Dworkin offered a legal theory of ‘chain enterprise’ that all the judges in legal history altogether create a ‘law’ aiming a specific purpose. Those judges are like co-writers of a chain-story who not only create freely but also are constrained by the story made by the judges before them. The law created by Chinese traditional judges is another case, they, compared with the judges mentioned by Ronald Dworkin, have relatively narrower space of making a legal sentence according to their own discretions because the statutes in Chinese traditional law at the very beginning have been designed as panel code that leaves small room to judge’s discretion. Furthermore, because law is a representative of the authority of the government, i.e. the emperor, any misjudges and misuses deviated from the law will be considered as a challenge to the supreme power. However, different from judges as the defenders of law, Chinese litigation masters who want to win legal cases have to be offenders challenging the verdict that does not favor his or his client’s interest. Besides, litigation master as an illegal or non-authorized profession does not belong to any legal system, therefore, they are relatively freer to ‘create’ the law. According to Stanley Fish’s articles that question Ronald Dworkin and Owen Fiss’ ideas about law, he construes that, since law is made of language, law is open to interpretations that cannot be constrained by any rules or any particular legal purposes. Stanley Fish’s idea can also be applied on the analysis about the stories of Chinese litigation masters in traditional Chinese literature. These Chinese litigation masters’ legal opinions in the so-called chain enterprise are like an unexpected episode that tries to revise the fixed story told by law. Although they are not welcome to the officials and also to the society, their existence is still a phenomenon representing another version of justice different from the official’s and can be seen as a de-structural power to the government. Hence, in this present paper the language and strategy applied by Chinese litigation masters in Chinese legal stories will be analysed to see how they refute made legal judgments and challenge the official standard of justice.

Keywords: Chinese legal stories, interdisciplinary, litigation master, post-structuralism

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Authors: Thipayasothorn Pastraporn, Phonpakdee Rachadakorn, Ponpo Sopar

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Forage production area development in Bangkok Metropolitan Region with an Agriculture in the city concept. Food chain of city man reduced distance of the food, so the food chain was a good attempt to connect the city’s product with the changes in each area of city. This paper purposed (I) to study the problems of using forage production area development in Bangkok Metropolitan Region, (II) to propose guidelines of forage production area development in Bangkok Metropolitan Region. We collected the data by questionnaire which we got from the agriculture, marketing and city plan sector in Bangkok Metropolitan Region. We analyzed the questionnaire in the way of relationship and guidelines of forage production area development in Bangkok Metropolitan Region. Results from the analyses are that the role of forage area productive plan in Bangkok Metropolitan Region is important to the cities for adapting in changing way of the food transmission. It also enhanced benefits using from cities fringe. Moreover, it managed watercourse and reduced energy consumption in order to sustainable distribute the food into the cities. .

Keywords: city plan, forage production area, urban development, Bangkok Metropolitan Region

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Authors: Jefri Draup, Antoine Ambard, Chi-Toan Nguyen

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Zirconium alloys exhibit solid-state phase transformations under thermal loading. These can lead to a significant evolution of the microstructure and associated mechanical properties of materials used in nuclear fuel cladding structures. Therefore, the ability to capture effects of phase transformation on the material constitutive behavior is of interest during conditions of severe transient thermal loading. Whilst typical Avrami, or Johnson-Mehl-Avrami-Kolmogorov (JMAK), type models for phase transformations have been shown to have a good correlation with the behavior of Zircaloy-4 under constant heating rates, the effects of variable and fast heating rates are not fully explored. The present study utilises the results of in-situ high energy synchrotron X-ray diffraction (SXRD) measurements in order to validate the phase transformation models for Zircaloy-4 under fast variable heating rates. These models are used to assess the performance of fuel cladding structures under loss of coolant accident (LOCA) scenarios. The results indicate that simple Avrami type models can provide a reasonable indication of the phase distribution in experimental test specimens under variable fast thermal loading. However, the accuracy of these models deteriorates under the faster heating regimes, i.e., 100Cs⁻¹. The studies highlight areas for improvement of simple Avrami type models, such as the inclusion of temperature rate dependence of the JMAK n-exponent.

Keywords: accident, fuel, modelling, zirconium

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Authors: Choupani Andisheh, Temucin Elif Sevval, Bediz Bekir

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Due to their various advantages compared to many other drug delivery systems such as hypodermic injections and oral medications, microneedle arrays (MNAs) are a promising drug delivery system. To achieve enhanced performance of the MN, it is crucial to develop numerical models, optimization methods, and simulations. Accordingly, in this work, the optimized design of dissolvable MNAs, as well as their manufacturing, is investigated. For this purpose, a mechanical model of a single MN, having the geometry of an obelisk, is developed using commercial finite element software. The model considers the condition in which the MN is under pressure at the tip caused by the reaction force when penetrating the skin. Then, a multi-objective optimization based on non-dominated sorting genetic algorithm II (NSGA-II) is performed to obtain geometrical properties such as needle width, tip (apex) angle, and base fillet radius. The objective of the optimization study is to reach a painless and effortless penetration into the skin along with minimizing its mechanical failures caused by the maximum stress occurring throughout the structure. Based on the obtained optimal design parameters, master (male) molds are then fabricated from PMMA using a mechanical micromachining process. This fabrication method is selected mainly due to the geometry capability, production speed, production cost, and the variety of materials that can be used. Then to remove any chip residues, the master molds are cleaned using ultrasonic cleaning. These fabricated master molds can then be used repeatedly to fabricate Polydimethylsiloxane (PDMS) production (female) molds through a micro-molding approach. Finally, Polyvinylpyrrolidone (PVP) as a dissolvable polymer is cast into the production molds under vacuum to produce the dissolvable MNAs. This fabrication methodology can also be used to fabricate MNAs that include bioactive cargo. To characterize and demonstrate the performance of the fabricated needles, (i) scanning electron microscope images are taken to show the accuracy of the fabricated geometries, and (ii) in-vitro piercing tests are performed on artificial skin. It is shown that optimized MN geometries can be precisely fabricated using the presented fabrication methodology and the fabricated MNAs effectively pierce the skin without failure.

Keywords: microneedle, microneedle array fabrication, micro-manufacturing structural optimization, finite element analysis

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Authors: Yong Bum Shin

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This case focuses on Weighted additive difference, Conjunctive, Disjunctive, and Elimination by aspects methodologies in consumer decision-making models and the Simple additive weighting (SAW) approach in the multi-criteria decision-making (MCDM) area. Most decision-making models illustrate that the rank reversal phenomenon is unpreventable. This paper presents that rank reversal occurs in popular managerial methods such as Weighted Additive Difference (WAD), Conjunctive Method, Disjunctive Method, Elimination by Aspects (EBA) and MCDM methods as well as such as the Simple Additive Weighting (SAW) and finally Unified Commensurate Multiple (UCM) models which successfully addresses these rank reversal problems in most popular MCDM methods in decision-making area.

Keywords: multiple criteria decision making, rank inconsistency, unified commensurate multiple, analytic hierarchy process

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Authors: Maryam Maleki, Esther Mead, Mohammad Arani, Nitin Agarwal

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This study is conducted to examine how opposing viewpoints related to COVID-19 were diffused on Twitter. To accomplish this, six datasets using two epidemiological models, SIR (Susceptible, Infected, Recovered) and SEIZ (Susceptible, Exposed, Infected, Skeptics), were analyzed. The six datasets were chosen because they represent opposing viewpoints on the COVID-19 pandemic. Three of the datasets contain anti-subject hashtags, while the other three contain pro-subject hashtags. The time frame for all datasets is three years, starting from January 2020 to December 2022. The findings revealed that while both models were effective in evaluating the propagation trends of these polarizing viewpoints, the SEIZ model was more accurate with a relatively lower error rate (6.7%) compared to the SIR model (17.3%). Additionally, the relative error for both models was lower for anti-subject hashtags compared to pro-subject hashtags. By leveraging epidemiological models, insights into the propagation trends of polarizing viewpoints on Twitter were gained. This study paves the way for the development of methods to prevent the spread of ideas that lack scientific evidence while promoting the dissemination of scientifically backed ideas.

Keywords: mathematical modeling, epidemiological model, seiz model, sir model, covid-19, twitter, social network analysis, social contagion

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Authors: Ramona Zharfpeykan, Paul Rouse

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Organizational sustainability is important to both organizations themselves and their stakeholders. Despite its increasing popularity and increasing numbers of organizations reporting sustainability, research on evaluating and comparing the sustainability performance of companies is limited. The aim of this study was to develop models to measure sustainability performance for both cross-sectional and longitudinal comparisons across companies in the same or different industries. A secondary aim was to see if sustainability reports can be used to evaluate sustainability performance. The study used both a content analysis of Australian sustainability reports in mining and metals and financial services for 2011-2014 and a survey of Australian and New Zealand organizations. Two methods ranging from a composite index using uniform weights to data envelopment analysis (DEA) were employed to analyze the data and develop the models. The results show strong statistically significant relationships between the developed models, which suggests that each model provides a consistent, systematic and reasonably robust analysis. The results of the models show that for both industries, companies that had sustainability scores above or below the industry average stayed almost the same during the study period. These indices and models can be used by companies to evaluate their sustainability performance and compare it with previous years, or with other companies in the same or different industries. These methods can also be used by various stakeholders and sustainability ranking companies such as the Global Reporting Initiative (GRI).

Keywords: data envelopment analysis, sustainability, sustainability performance measurement system, sustainability performance index, global reporting initiative

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Authors: Y. Baba, A. Archibong-Eso, H. Yeung

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Experimental study of high viscosity oil-gas flows in horizontal pipelines published in literature has indicated that hydrodynamic slug flow is the dominant flow pattern observed. Investigations have shown that hydrodynamic slugging brings about high instabilities in pressure that can damage production facilities thereby making it inherent to study high viscous slug flow regime so as to improve the understanding of its flow dynamics. Most slug flow models used in the petroleum industry for the design of pipelines together with their closure relationships were formulated based on observations of low viscosity liquid-gas flows. New experimental investigations and data are therefore required to validate these models. In cases where these models underperform, improving upon or building new predictive models and correlations will also depend on the new experimental dataset and further understanding of the flow dynamics in high viscous oil-gas flows. In this study conducted at the Flow laboratory, Oil and Gas Engineering Centre of Cranfield University, slug flow variables such as pressure gradient, mean liquid holdup, frequency and slug length for oil viscosity ranging from 1..0 – 5.5 Pa.s are experimentally investigated and analysed. The study was carried out in a 0.076m ID pipe, two fast sampling gamma densitometer and pressure transducers (differential and point) were used to obtain experimental measurements. Comparison of the measured slug flow parameters to the existing slug flow prediction models available in the literature showed disagreement with high viscosity experimental data thus highlighting the importance of building new predictive models and correlations.

Keywords: gamma densitometer, mean liquid holdup, pressure gradient, slug frequency and slug length

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Authors: Myungjin Lee, Daegun Han, Jongsung Kim, Soojun Kim, Hung Soo Kim

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Recently, the localized heavy rainfall and typhoons are frequently occurred due to the climate change and the damage is becoming bigger. Therefore, we may need a more accurate prediction of the rainfall and runoff. However, the gauge rainfall has the limited accuracy in space. Radar rainfall is better than gauge rainfall for the explanation of the spatial variability of rainfall but it is mostly underestimated with the uncertainty involved. Therefore, the ensemble of radar rainfall was simulated using error structure to overcome the uncertainty and gauge rainfall. The simulated ensemble was used as the input data of the rainfall-runoff models for obtaining the ensemble of runoff hydrographs. The previous studies discussed about the accuracy of the rainfall-runoff model. Even if the same input data such as rainfall is used for the runoff analysis using the models in the same basin, the models can have different results because of the uncertainty involved in the models. Therefore, we used two models of the SSARR model which is the lumped model, and the Vflo model which is a distributed model and tried to simulate the optimum runoff considering the uncertainty of each rainfall-runoff model. The study basin is located in Han river basin and we obtained one integrated runoff hydrograph which is an optimum runoff hydrograph using the blending methods such as Multi-Model Super Ensemble (MMSE), Simple Model Average (SMA), Mean Square Error (MSE). From this study, we could confirm the accuracy of rainfall and rainfall-runoff model using ensemble scenario and various rainfall-runoff model and we can use this result to study flood control measure due to climate change. Acknowledgements: This work is supported by the Korea Agency for Infrastructure Technology Advancement(KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 18AWMP-B083066-05).

Keywords: radar rainfall ensemble, rainfall-runoff models, blending method, optimum runoff hydrograph

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Authors: Viriyavudh Sim, WooYoung Jung

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Damage due to high wind is not limited to load resistance components such as beam and column. The majority of damage is due to breach in the building envelope such as broken roof, window, and door. In this paper, wind fragility of window glass in residential apartment was determined to compare the difference between two window configuration models. Monte Carlo Simulation method had been used to derive damage data and analytical fragilities were constructed. Fragility of window system showed that window located in leeward wall had higher probability of failure, especially those close to the edge of structure. Between the two window models, Model 2 had higher probability of failure, this was due to the number of panel in this configuration.

Keywords: wind fragility, glass window, high rise building, wind disaster

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Authors: Flora Babongo, Valerie Chavez

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Inferring causality from observational data is one of the fundamental subjects, especially in quantitative finance. So far most of the papers analyze additive noise models with either linearity, nonlinearity or Gaussian noise. We fill in the gap by providing a nonlinear and non-gaussian causal multiplicative noise model that aims to distinguish the cause from the effect using a two steps method based on Bayesian additive models for location, scale and shape (BAMLSS) and on causal additive models (CAM). We have tested our method on simulated and real data and we reached an accuracy of 0.86 on average. As real data, we considered the causality between financial indices such as S&P 500, Nasdaq, CAC 40 and Nikkei, and companies' log-returns. Our results can be useful in inferring causality when the data is heteroskedastic or non-injective.

Keywords: causal inference, DAGs, BAMLSS, financial index

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Authors: Jamil Ahmed

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Access control models aim to decide whether a user should be denied or granted access to the user‟s requested activity. Various access control models have been established and proposed. The most prominent of these models include role-based, attribute-based, policy based access control models as well as role-centric attribute based access control model. In this paper, a novel access control model is presented called “Role centric Attribute based Policy Driven Access Control (RAPDAC) model”. RAPDAC incorporates the concept of “policy” in the “role centric attribute based access control model”. It leverages the concept of "policy‟ by precisely combining the evaluation of conditions, attributes, permissions and roles in order to allow authorization access. This approach allows capturing the "access control policy‟ of a real time application in a well defined manner. RAPDAC model allows making access decision at much finer granularity as illustrated by the case study of a real time library information system.

Keywords: authorization, access control model, role based access control, attribute based access control

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Authors: Nadarajah I. Ramesh

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Much of the research on stochastic point process models for rainfall has focused on Poisson cluster models constructed from either the Neyman-Scott or Bartlett-Lewis processes. The doubly stochastic Poisson process provides a rich class of point process models, especially for fine-scale rainfall modelling. This paper provides an account of recent development on this topic and presents the results based on some of the fine-scale rainfall models constructed from this class of stochastic point processes. Amongst the literature on stochastic models for rainfall, greater emphasis has been placed on modelling rainfall data recorded at hourly or daily aggregation levels. Stochastic models for sub-hourly rainfall are equally important, as there is a need to reproduce rainfall time series at fine temporal resolutions in some hydrological applications. For example, the study of climate change impacts on hydrology and water management initiatives requires the availability of data at fine temporal resolutions. One approach to generating such rainfall data relies on the combination of an hourly stochastic rainfall simulator, together with a disaggregator making use of downscaling techniques. Recent work on this topic adopted a different approach by developing specialist stochastic point process models for fine-scale rainfall aimed at generating synthetic precipitation time series directly from the proposed stochastic model. One strand of this approach focused on developing a class of doubly stochastic Poisson process (DSPP) models for fine-scale rainfall to analyse data collected in the form of rainfall bucket tip time series. In this context, the arrival pattern of rain gauge bucket tip times N(t) is viewed as a DSPP whose rate of occurrence varies according to an unobserved finite state irreducible Markov process X(t). Since the likelihood function of this process can be obtained, by conditioning on the underlying Markov process X(t), the models were fitted with maximum likelihood methods. The proposed models were applied directly to the raw data collected by tipping-bucket rain gauges, thus avoiding the need to convert tip-times to rainfall depths prior to fitting the models. One advantage of this approach was that the use of maximum likelihood methods enables a more straightforward estimation of parameter uncertainty and comparison of sub-models of interest. Another strand of this approach employed the DSPP model for the arrivals of rain cells and attached a pulse or a cluster of pulses to each rain cell. Different mechanisms for the pattern of the pulse process were used to construct variants of this model. We present the results of these models when they were fitted to hourly and sub-hourly rainfall data. The results of our analysis suggest that the proposed class of stochastic models is capable of reproducing the fine-scale structure of the rainfall process, and hence provides a useful tool in hydrological modelling.

Keywords: fine-scale rainfall, maximum likelihood, point process, stochastic model

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Authors: John Oupa Hlatshwayo

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Background: There seem to be preferred digital business models with varying impacts within hospitality, tourism and catering sub-sectors explored through online commerce, as all are ingrained in the business economics domain. Aim: A study aims to establish if such phenomena (Digital Business Models) exist and to what extent if any, within the hospitality, tourism and catering industries, respectively. Setting: This is a qualitative study conducted by exploring several (Four) institutions globally through Case Studies. Method: This research explored explanatory case studies to answer questions about ‘how’ or ’why’ with little control by a researcher over the occurrence of events. It is qualitative research, deductive, and inductive methods. Hence, a comprehensive approach to analyzing qualitative data was attainable through immersion by reading to understand the information. Findings: The results corroborated the notion that digital business models are applicable, by and large, in business economics. Thus, three sectors wherein enterprises operate in the business economics sphere have been narrowed down i.e. hospitality, tourism and catering, are also referred to as triangular polygons due to the atypical nature of being ‘stand-alone’, yet ‘sub-sectors’, but there are confounding factors to consider. Conclusion: The significance of digital business models and digital transformation shows an inevitable merger between business and technology within Hospitality, Tourism, and Catering. Contribution: Such symbiotic relationship of business and technology, persistent evolution of clients’ interface with end-products, forever changing market, current adaptation as well as adjustment to ‘new world order’ by enterprises must be embraced constantly without fail by Business Practitioners, Academics, Business Students, Organizations and Governments.

Keywords: digital business models, hospitality, tourism, catering, business economics

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Authors: Osayande Pascal Omondiagbe, Sherlock a Licorish

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Stack Overflow is a popular community question and answer portal which is used by practitioners to solve technology-related challenges during software development. Previous studies have shown that this forum is becoming a substitute for official software programming languages documentation. While tools have looked to aid developers by presenting interfaces to explore Stack Overflow, developers often face challenges searching through many possible answers to their questions, and this extends the development time. To this end, researchers have provided ways of predicting acceptable Stack Overflow answers by using various modeling techniques. However, less interest is dedicated to examining the performance and quality of typically used modeling methods, and especially in relation to models’ and features’ complexity. Such insights could be of practical significance to the many practitioners that use Stack Overflow. This study examines the performance and quality of various modeling methods that are used for predicting acceptable answers on Stack Overflow, drawn from 2014, 2015 and 2016. Our findings reveal significant differences in models’ performance and quality given the type of features and complexity of models used. Researchers examining classifiers’ performance and quality and features’ complexity may leverage these findings in selecting suitable techniques when developing prediction models.

Keywords: feature selection, modeling and prediction, neural network, random forest, stack overflow

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Authors: Mehrnaz Mostafavi

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Nanoliposomes, minute lipid-based vesicles at the nano-scale, show promise in the realm of photothermal therapy (PTT). This study presents an extensive overview of nanoliposomes in PTT, exploring their distinct attributes and the significant progress in this therapeutic methodology. The research delves into the fundamental traits of nanoliposomes, emphasizing their adaptability, compatibility with biological systems, and their capacity to encapsulate diverse therapeutic substances. Specifically, it examines the integration of light-absorbing materials, like gold nanoparticles or organic dyes, into nanoliposomal formulations, enabling their efficacy as proficient agents for photothermal treatment Additionally, this paper elucidates the mechanisms involved in nanoliposome-mediated PTT, highlighting their capability to convert light energy into localized heat, facilitating the precise targeting of diseased cells or tissues. This precise regulation of light absorption and heat generation by nanoliposomes presents a non-invasive and precisely focused therapeutic approach, particularly in conditions like cancer. The study explores advancements in nanoliposomal formulations aimed at optimizing PTT outcomes. These advancements include strategies for improved stability, enhanced drug loading, and the targeted delivery of therapeutic agents to specific cells or tissues. Furthermore, the paper discusses multifunctional nanoliposomal systems, integrating imaging components or targeting elements for real-time monitoring and improved accuracy in PTT. Moreover, the review highlights recent preclinical and clinical trials showcasing the effectiveness and safety of nanoliposome-based PTT across various disease models. It also addresses challenges in clinical implementation, such as scalability, regulatory considerations, and long-term safety assessments. In conclusion, this paper underscores the substantial potential of nanoliposomes in advancing PTT as a promising therapeutic approach. Their distinctive characteristics, combined with their precise ability to convert light into heat, offer a tailored and efficient method for treating targeted diseases. The encouraging outcomes from preclinical studies pave the way for further exploration and potential clinical applications of nanoliposome-based PTT.

Keywords: nanoliposomes, photothermal therapy, light absorption, heat conversion, therapeutic agents, targeted delivery, cancer therapy

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Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

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The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse

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Authors: Vijaya Chandra Tenneti

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The juvenile justice delivery system in India suffers from many lacunae at the operational level and ignores many dimensions of human rights guaranteed to the juvenile delinquents. The present study begins with the hypothesis that the existing justice delivery system seemingly ignores the basic tenets of the fair trial and systemic support to the delinquent juveniles in integrating them into the mainstream of society. As per the designed methodology, data has been collected from the unit of the present study, and other stakeholders, namely, Juvenile Justice Board, Observation Homes etc., of Warangal district of Telangana state, India. The study shows that there is the overemphasis on procedural laws. The juvenile integration programs are not effective. The administrators lack training. Juveniles lack formal education. The study indicates the incidents of juvenile crimes is on the rise and that the majority of the juvenile delinquents hold a low socio-economic profile. Another significant observation of the study is that the juvenile justice system lacks a holistic and human rights-centric approach.

Keywords: delinquency, human rights, juvenile justice, rehabilitation

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Authors: Sudipta Ghorai, Ossama Salem

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Pavement maintenance, repair, and rehabilitation (MRR) processes may have considerable environmental impacts due to traffic disruptions associated with work zones. The simulation models in use to predict the emission of work zones were mostly static emission factor models (SEFD). SEFD calculates emissions based on average operation conditions e.g. average speed and type of vehicles. Although these models produce accurate results for large-scale planning studies, they are not suitable for analyzing driving conditions at the micro level such as acceleration, deceleration, idling, cruising, and queuing in a work zone. The purpose of this study is to prepare a comprehensive work zone environmental assessment (WEA) framework to calculate the emissions caused due to disrupted traffic; by integrating traffic microsimulation tools with emission models. This will help highway officials to assess the benefits of accelerated construction and opt for the most suitable TMP not only economically but also from an environmental point of view.

Keywords: accelerated construction, pavement MRR, traffic microsimulation, congestion, emissions

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Authors: Min Kyung An

Abstract:

In Wireless Sensor Networks which consist of tiny wireless sensor nodes with limited battery power, one of the most fundamental applications is data aggregation which collects nearby environmental conditions and aggregates the data to a designated destination, called a sink node. Important issues concerning the data aggregation are time efficiency and energy consumption due to its limited energy, and therefore, the related problem, named Minimum Latency Aggregation Scheduling (MLAS), has been the focus of many researchers. Its objective is to compute the minimum latency schedule, that is, to compute a schedule with the minimum number of timeslots, such that the sink node can receive the aggregated data from all the other nodes without any collision or interference. For the problem, the two interference models, the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR), have been adopted with different power models, uniform-power and non-uniform power (with power control or without power control), and different antenna models, omni-directional antenna and directional antenna models. In this survey article, as the problem has proven to be NP-hard, we present and compare several state-of-the-art approximation algorithms in various models on the basis of latency as its performance measure.

Keywords: data aggregation, convergecast, gathering, approximation, interference, omni-directional, directional

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Authors: Aboli Gore, Aritra Das, Sunil Sonthalia, Tanmay Mahapatra, Sridhar Srikantiah, Hemant Shah

Abstract:

AMANAT is an initiative, taken in collaboration with the Government of Bihar, aimed at improving the Quality of Maternal and Neonatal care services at Bihar’s public health facilities – those offering either the Basic Emergency Obstetric and Neonatal care (BEmONC) or Comprehensive Emergency Obstetric and Neonatal care (CEmONC) services. The effectiveness of this program is evaluated by conducting cross-sectional assessments at the concerned facilities prior to (baseline) and following completion (endline) of intervention. Direct Observation of Delivery (DOD) methodology is employed for carrying out the baseline and endline assessments – through which key obstetric and neonatal care practices among the Health Care Providers (especially the nurses) are assessed quantitatively by specially trained nursing professionals. Assessment of vitals prior to delivery improved during all three phases of BEmONC and all four phases of CEmONC training with statistically significant improvement noted in: i) pulse measurement in BEmONC phase 2 (9% to 68%), 3 (4% to 57%) & 4 (14% to 59%) and CEmONC phase 2 (7% to 72%) and 3 (0% to 64%); ii) blood pressure measurement in BEmONC phase 2 (27% to 84%), 3 (21% to 76%) & 4 (36% to 71%) and CEmONC phase 2 (23% to 76%) and 3 (2% to 70%); iii) fetal heart rate measurement in BEmONC phase 2 (10% to 72%), 3 (11% to 77%) & 4 (13% to 64%) and CEmONC phase 1 (24% to 38%), 2 (14% to 82%) and 3 (1% to 73%); and iv) abdominal examination in BEmONC phase 2 (14% to 59%), 3 (3% to 59%) & 4 (6% to 56%) and CEmONC phase 1 (0% to 24%), 2 (7% to 62%) & 3 (0% to 62%). Regarding infection control, wearing of apron, mask and cap by the delivery conductors improved significantly in all BEmONC phases. Similarly, the practice of handwashing improved in all BEmONC and CEmONC phases. Even on disaggregation, the handwashing showed significant improvement in all phases but CEmONC phase-4. Not only the positive practices related to handwashing improved but also negative practices such as turning off the tap with bare hands declined significantly in the aforementioned phases. Significant decline was also noted in negative maternal care practices such as application of fundal pressure for hastening the delivery process and administration of oxytocin prior to delivery. One of the notable achievement of AMANAT is an improvement in active management of the third stage of labor (AMTSL). The overall AMTSL (including administration of oxytocin or other uterotonics uterotonic in proper dose, route and time along with controlled cord traction and uterine massage) improved in all phases of BEmONC and CEmONC mentoring. Another key area of improvement, across phases, was in proper cutting/clamping of the umbilical cord. AMANAT mentoring also led to improvement in important immediate newborn care practices such as initiation of skin-to-skin care and timely initiation of breastfeeding. The next phase of the mentoring program seeks to institutionalize mentoring across the state that could potentially perpetuate improvement with minimal external intervention.

Keywords: capacity building, nurse-mentoring, quality of care, pregnancy, newborn care

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Authors: Hamed K. Esfahani, Bithin Datta

Abstract:

Transport of reactive chemical contaminant species in groundwater aquifers is a complex and highly non-linear physical and geochemical process especially for real life scenarios. Simulating this transport process involves solving complex nonlinear equations and generally requires huge computational time for a given aquifer study area. Development of optimal remediation strategies in aquifers may require repeated solution of such complex numerical simulation models. To overcome this computational limitation and improve the computational feasibility of large number of repeated simulations, Genetic Programming based trained surrogate models are developed to approximately simulate such complex transport processes. Transport process of acid mine drainage, a hazardous pollutant is first simulated using a numerical simulated model: HYDROGEOCHEM 5.0 for a contaminated aquifer in a historic mine site. Simulation model solution results for an illustrative contaminated aquifer site is then approximated by training and testing a Genetic Programming (GP) based surrogate model. Performance evaluation of the ensemble GP models as surrogate models for the reactive species transport in groundwater demonstrates the feasibility of its use and the associated computational advantages. The results show the efficiency and feasibility of using ensemble GP surrogate models as approximate simulators of complex hydrogeologic and geochemical processes in a contaminated groundwater aquifer incorporating uncertainties in historic mine site.

Keywords: geochemical transport simulation, acid mine drainage, surrogate models, ensemble genetic programming, contaminated aquifers, mine sites

Procedia PDF Downloads 274

Authors: Michalis Linardakis, Vasilis Grammatikopoulos, Athanasios Gregoriadis, Kalliopi Trouli

Abstract:

Discrete choice models belong to the family of Conjoint analysis that are applied on the preferences of the respondents towards a set of scenarios that describe alternative choices. The scenarios have been pre-designed to cover all the attributes of the alternatives that may affect the choices. In this study, we examine how preschool educators integrate physical activities into their everyday teaching practices through the use of discrete choice models. One of the advantages of discrete choice models compared to other more traditional data collection methods (e.g. questionnaires and interviews that use ratings) is that the respondent is called to select among competitive and realistic alternatives, rather than objectively rate each attribute that the alternatives may have. We present the effort to construct and choose representative attributes that would cover all possible choices of the respondents, and the scenarios that have arisen. For the purposes of the study, we used a sample of 50 preschool educators in Greece that responded to 4 scenarios (from the total of 16 scenarios that the orthogonal design resulted), with each scenario having three alternative teaching practices. Seven attributes of the alternatives were used in the scenarios. For the analysis of the data, we used multinomial logit model with random effects, multinomial probit model and generalized mixed logit model. The conclusions drawn from the estimated parameters of the models are discussed.

Keywords: conjoint analysis, discrete choice models, educational data, multivariate statistical analysis

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Authors: N. Sopipan

Abstract:

In this paper, we study of rainfall time series of weather stations in Nakhon Ratchasima province in Thailand using various statistical methods enabled to analyse the behaviour of rainfall in the study areas. Time-series analysis is an important tool in modelling and forecasting rainfall. ARIMA and Holt-Winter models based on exponential smoothing were built. All the models proved to be adequate. Therefore, could give information that can help decision makers establish strategies for proper planning of agriculture, drainage system and other water resource applications in Nakhon Ratchasima province. We found the best perform for forecasting is ARIMA(1,0,1)(1,0,1)12.

Keywords: ARIMA Models, exponential smoothing, Holt-Winter model

Procedia PDF Downloads 297