Search results for: deep neural models

Authors: I. M. L. Nadeesha Jayaweera, Adao Alex Trindade

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In choosing a candidate model in likelihood-based modeling via an information criterion, the practitioner is often faced with the difficult task of deciding just how far up the ranked list to look. Motivated by this pragmatic necessity, we construct an uncertainty band for a generalized (model selection) information criterion (GIC), defined as a criterion for which the limit in probability is identical to that of the normalized log-likelihood. This includes common special cases such as AIC & BIC. The method starts from the asymptotic normality of the GIC for the joint distribution of the candidate models in an independent and identically distributed (IID) data framework and proceeds by deriving the (asymptotically) exact distribution of the minimum. The calculation of an upper quantile for its distribution then involves the computation of multivariate Gaussian integrals, which is amenable to efficient implementation via the R package "mvtnorm". The performance of the methodology is tested on simulated data by checking the coverage probability of nominal upper quantiles and compared to the bootstrap. Both methods give coverages close to nominal for large samples, but the bootstrap is two orders of magnitude slower. The methodology is subsequently extended to two other commonly used model structures: regression and time series. In the regression case, we derive the corresponding asymptotically exact distribution of the minimum GIC invoking Lindeberg-Feller type conditions for triangular arrays and are thus able to similarly calculate upper quantiles for its distribution via multivariate Gaussian integration. The bootstrap once again provides a default competing procedure, and we find that similar comparison performance metrics hold as for the IID case. The time series case is complicated by far more intricate asymptotic regime for the joint distribution of the model GIC statistics. Under a Gaussian likelihood, the default in most packages, one needs to derive the limiting distribution of a normalized quadratic form for a realization from a stationary series. Under conditions on the process satisfied by ARMA models, a multivariate normal limit is once again achieved. The bootstrap can, however, be employed for its computation, whence we are once again in the multivariate Gaussian integration paradigm for upper quantile evaluation. Comparisons of this bootstrap-aided semi-exact method with the full-blown bootstrap once again reveal a similar performance but faster computation speeds. One of the most difficult problems in contemporary statistical methodological research is to be able to account for the extra variability introduced by model selection uncertainty, the so-called post-model selection inference (PMSI). We explore ways in which the GIC uncertainty band can be inverted to make inferences on the parameters. This is being attempted in the IID case by pivoting the CDF of the asymptotically exact distribution of the minimum GIC. For inference one parameter at a time and a small number of candidate models, this works well, whence the attained PMSI confidence intervals are wider than the MLE-based Wald, as expected.

Keywords: model selection inference, generalized information criteria, post model selection, Asymptotic Theory

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Authors: Victor Chinecherem Ejeke, Raphael Eze Nnam

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The main objective of this research is to produce biodiesel from waste vegetable oil using activated eggshell waste as solid catalysts. A transesterification reaction was performed for the conversion to biodiesel. Waste eggshells were calcined at 700°C, 800°C and 900°C for a time period of 3hrs for the preparation of the renewable catalyst. The calcined waste eggshell catalyst was characterized using X-Ray Florescence (XRF) Spectroscopy, which revealed CaO as the major constituent (90.86%); this was further confirmed by X-Ray Diffraction (XRD) and Fourier Transform Infrared (FTIR) analyses. The prepared catalyst was used for transesterification reaction and the effects of calcination temperature (700 to 900°C), Deep Eutectic Solvent DES loading (3 to 18 wt. %), Waste Egg Shell (WES) catalyst loading (6 to 14 wt. %) on the conversion to biodiesel were studied. The yield of biodiesel using a waste eggshell catalyst (91%) is comparable to conventional catalyst like sodium hydroxide with a yield of 80-90%. The maximum biodiesel production yield was obtained at a specific oil-to methanol molar ratio of 1:10, a temperature of 65°C and a catalyst loading of 14g-wt%. The biodiesel produced was characterized as being composed of methyl Tetradecanoate (C₁₄H₂₈O₂) 30.92% using the Gas Chromatographic (GC-MS) analysis. The fuel properties of the biodiesel (Flashpoint 138ᵒC) were comparable to commercial diesel, and hence it can be used in compression-ignition engines. The results indicated that the catalysts derived from waste eggshell had high potential to be used as biodiesel production catalysts in transesterification of waste vegetable oil with the advantage of reusability and also not requiring water washing steps.

Keywords: waste vegetable oil, catalyst , biodiesel , waste egg shell

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Authors: Panas Gerasimos, Kotidou Varvara, Halkiopoulos Constantinos, Gkintoni Evgenia

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As a result of growing technology and briefing by the internet, users resort to the internet and subsequently to the opinion of an expert. In many cases, they take control of their health in their hand and make a decision without the contribution of a doctor. According to that, this essay intends to analyze the confidence of searching health issues on the internet. For the fulfillment of this study, there has been a survey among doctors in order to find out the reasons a patient uses the internet about their health problems and the consequences that health information could lead by searching on the internet, as well. Specifically, the results regarding the research of the users demonstrate: a) the majority of users make use of the internet about health issues once or twice a month, b) individuals that possess chronic disease make health search on the internet more frequently, c) the most important topics that the majority of users usually search are pathological, dietary issues and the search of issues that are associated with doctors and hospitals. However, it observed that topic search varies depending on the users’ age, d) the most common sources of information concern the direct contact with doctors, as there is a huge preference from the majority of users over the use of the electronic form for their briefing and e) it has been observed that there is large lack of knowledge about e-health services. From the doctor's point of view, the following conclusions occur: a) almost all doctors use the internet as their main source of information, b) the internet has great influence over doctors’ relationship with the patients, c) in many cases a patient first makes a visit to the internet and then to the doctor, d) the internet significantly has a psychological impact on patients in order to for them to reach a decision, e) the most important reason users choose the internet instead of the health professional is economic, f) the negative consequence that emerges is inaccurate information, g) and the positive consequences are about the possibility of online contact with the doctor and contributes to the easy comprehension of the doctor, as well. Generally, it’s observed from both sides that the use of the internet in health issues is intense, which declares that the new means the doctors have at their disposal, produce the conditions for radical changes in the way of providing services and in the doctor-patient relationship.

Keywords: cognitive models, health marketing, e-health, psychological factors, digital marketing, e-health services

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Authors: Jingsi Li, Neil S. Ferguson

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Time pressure could have an influence on the productivity, quality of decision making, and the efficiency of problem-solving. This has been mostly stemmed from cognitive research or psychological literature. However, a salient scarce discussion has been held for transport adjacent fields. It is conceivable that in many activity-travel contexts, time pressure is a potentially important factor since an excessive amount of decision time may incur the risk of late arrival to the next activity. The activity-travel rescheduling behavior is commonly explained by costs and benefits of factors such as activity engagements, personal intentions, social requirements, etc. This paper hypothesizes that an additional factor of perceived time pressure could affect travelers’ rescheduling behavior, thus leading to an impact on travel demand management. Time pressure may arise from different ways and is assumed here to be essentially incurred due to travelers planning their schedules without an expectation of unforeseen elements, e.g., transport disruption. In addition to a linear-additive utility-maximization model, the less computationally compensatory heuristic models are considered as an alternative to simulate travelers’ responses. The paper will contribute to travel behavior modeling research by investigating the following questions: how to measure the time pressure properly in an activity-travel day plan context? How do travelers reschedule their plans to cope with the time pressure? How would the importance of the activity affect travelers’ rescheduling behavior? What will the behavioral model be identified to describe the process of making activity-travel rescheduling decisions? How do these identified coping strategies affect the transport network? In this paper, a Mixed Heuristic Model (MHM) is employed to identify the presence of different choice heuristics through a latent class approach. The data about travelers’ activity-travel rescheduling behavior is collected via a web-based interactive survey where a fictitious scenario is created comprising multiple uncertain events on the activity or travel. The experiments are conducted in order to gain a real picture of activity-travel reschedule, considering the factor of time pressure. The identified behavioral models are then integrated into a multi-agent transport simulation model to investigate the effect of the rescheduling strategy on the transport network. The results show that an increased proportion of travelers use simpler, non-compensatory choice strategies instead of compensatory methods to cope with time pressure. Specifically, satisfying - one of the heuristic decision-making strategies - is adopted commonly since travelers tend to abandon the less important activities and keep the important ones. Furthermore, the importance of the activity is found to increase the weight of negative information when making trip-related decisions, especially route choices. When incorporating the identified non-compensatory decision-making heuristic models into the agent-based transport model, the simulation results imply that neglecting the effect of perceived time pressure may result in an inaccurate forecast of choice probability and overestimate the affectability to the policy changes.

Keywords: activity-travel rescheduling, decision making under uncertainty, mixed heuristic model, perceived time pressure, travel demand management

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Authors: Suneet Jagdev, Siddharth Singhal, Dhrubajyoti Bordoloi, Peesari Vamshidhar Reddy

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There is no universally accepted definition of what constitutes a Smart City. It means different things to different people. The definition varies from place to place depending on the level of development and the willingness of people to change and reform. It tries to improve the quality of resource management and service provisions for the people living in the cities. Smart city is an urban development vision to integrate multiple information and communication technology (ICT) solutions in a secure fashion to manage the assets of a city. But most of these projects are misinterpreted as being technology projects only. Due to urbanization, a lot of informal as well government funded settlements have come up during the last few decades, thus increasing the consumption of the limited resources available. The people of each city have their own definition of Smart City. In the imagination of any city dweller in India is the picture of a Smart City which contains a wish list of infrastructure and services that describe his or her level of aspiration. The research involved a comparative study of the Smart City models in India and in China. Behavioral changes experienced by the people living in the pilot/first ever smart cities have been identified and compared. This paper discussed what is the target of the quality of life for the people in India and in China and how well could that be realized with the facilities being included in these Smart City projects. Logical and comparative analyses of important data have been done, collected from government sources, government papers and research papers by various experts on the topic. Existing cities with historically grown infrastructure and administration systems will require a more moderate step-by-step approach to modernization. The models were compared using many different motivators and the data is collected from past journals, interacting with the people involved, videos and past submissions. In conclusion, we have identified how these projects could be combined with the ongoing small scale initiatives by the local people/ small group of individuals and what might be the outcome if these existing practices were implemented on a bigger scale.

Keywords: behavior change, mission monitoring, pilot smart cities, social capital

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Authors: Abdelhak Bouchakour, Mustafa Brahami, Layachi Zaghba

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The use of photovoltaic energy offers an inexhaustible supply of energy but also a clean and non-polluting energy, which is a definite advantage. The geographical location of Algeria promotes the development of the use of this energy. Indeed, given the importance of the intensity of the radiation received and the duration of sunshine. For this reason, the objective of our work is to develop a data-processing tool (software) of calculation and optimization of dimensioning of the photovoltaic installations. Our approach of optimization is basing on mathematical models, which amongst other things describe the operation of each part of the installation, the energy production, the storage and the consumption of energy.

Keywords: solar panel, solar radiation, inverter, optimization

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Authors: Alexandra K. Diem, Giles Richardson, Roxana O. Carare, Neil W. Bressloff

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Alzheimer's disease (AD) is the most common form of dementia and although it has been researched for over 100 years, there is still no cure or preventive medication. Its onset and progression is closely related to the accumulation of the neuronal metabolite Aβ. This raises the question of how metabolites and waste products are eliminated from the brain as the brain does not have a traditional lymphatic system. In recent years the rapid uptake of Aβ into cerebral artery walls and its clearance along those arteries towards the lymph nodes in the neck has been suggested and confirmed in mice studies, which has led to the hypothesis that interstitial fluid (ISF), in the basement membranes in the walls of cerebral arteries, provides the pathways for the lymphatic drainage of Aβ. This mechanism, however, requires a net reverse flow of ISF inside the blood vessel wall compared to the blood flow and the driving forces for such a mechanism remain unknown. While possible driving mechanisms have been studied using mathematical models in the past, a mechanism for net reverse flow has not been discovered yet. Here, we aim to address the question of the driving force of this reverse lymphatic drainage of Aβ (also called perivascular drainage) by using multi-scale numerical and analytical modelling. The numerical simulation software COMSOL Multiphysics 4.4 is used to develop a fluid-structure interaction model of a cerebral artery, which models blood flow and displacements in the artery wall due to blood pressure changes. An analytical model of a layer of basement membrane inside the wall governs the flow of ISF and, therefore, solute drainage based on the pressure changes and wall displacements obtained from the cerebral artery model. The findings suggest that an active role in facilitating a reverse flow is played by the components of the basement membrane and that stiffening of the artery wall during age is a major risk factor for the impairment of brain lymphatics. Additionally, our model supports the hypothesis of a close association between cerebrovascular diseases and the failure of perivascular drainage.

Keywords: Alzheimer's disease, artery wall mechanics, cerebral blood flow, cerebral lymphatics

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Authors: Riccardo Cacciotti, Jiri Frankl, Benjamin Wolf, Michael Machacek

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Moisture fluctuations govern the occurrence of fungi-related problems in buildings, which may impose significant health risks for users and even lead to structural failures. Several numerical engineering models attempt to capture the complexity of mold growth on building materials. From real life observations, in cases with suppressed daily variations of boundary conditions, e.g. in crawlspaces, mold growth model predictions well correspond with the observed mold growth. On the other hand, in cases with substantial diurnal variations of boundary conditions, e.g. in the ventilated cavity of a cold flat roof, mold growth predicted by the models is significantly overestimated. This study, founded by the Grant Agency of the Czech Republic (GAČR 20-12941S), aims at gaining a better understanding of mold growth behavior on solid wood, under varying boundary conditions. In particular, the experimental investigation focuses on the response of mold to changing conditions in the boundary layer and its influence on heat and moisture transfer across the surface. The main results include the design and construction at the facilities of ITAM (Prague, Czech Republic) of an innovative device allowing for the simulation of changing environmental conditions in buildings. It consists of a square section closed circuit with rough dimensions 200 × 180 cm and cross section roughly 30 × 30 cm. The circuit is thermally insulated and equipped with an electric fan to control air flow inside the tunnel, a heat and humidity exchange unit to control the internal RH and variations in temperature. Several measuring points, including an anemometer, temperature and humidity sensor, a loading cell in the test section for recording mass changes, are provided to monitor the variations of parameters during the experiments. The research is ongoing and it is expected to provide the final results of the experimental investigation at the end of 2022.

Keywords: moisture, mold growth, testing, wood

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Authors: Christian Uchechukwu Gilbert

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Generativism in language design investigates the framework on which varying sentence structures are built in the English language. Propounded by Noam Chomsky in 1965, the theory transforms sentences from an active structure to a passive one by the application of established rules of the theory. Resident in the body of syntax, the rules include movement, insertion, substitution, and deletion rules. Using the movement rule, the analysis is armed with the qualitative research method, on which the works of scholars were duly consulted for more insight and in line with the academic practice in research activities. The investigation showed that the rules of competent grammar explain the formulation of sentences in a language and how transformation takes place among sentences from a deep structure to a surface structure with accurate results. The structural differences that could be got through dative movement and the deletion of the preposition; passivisation got from an active sentence by the insertion of the preposition “by” a “be verb” and the aspect tense marker “–en”, held as the creative aspect of language vocabulary and the subject-auxiliary inversion that exchanges the auxiliary of a sentence with the subject of the same sentence thereby transforming a kennel sentence to a polar question, viewed as an external argument under θ-theory. Generativism in language design, therefore, changes available types of sentences and relates one form of linguistic category with others in language design.

Keywords: language, generate, transformation, structure, design

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Authors: Anis Eloud, Mohamed Ben Amor

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Tunisia is a semi-arid country on ¾ of its territory. It is characterized by the scarcity of water resources and accentuated by climate variability. The potential water resources are estimated at 4.6 million m3 / year, of which 2.7 million m3 / year represent surface water and 1.9 million m3 / year feed all the layers that make up the renewable groundwater resources. Water available in Tunisia easily exceed health or agricultural salinity standards. Barely 50% of water resources are less than 1.5 g / l divided at 72% of surface water salinity, 20% of deep groundwater and only 8% in groundwater levels. Southern Tunisia has the largest web "of water in the country, these waters are characterized by a relatively high salinity may exceed 4 gl-1. This is the "root of many problems encountered during their operation. In the region of Djérid, Albian wells are numerous. These wells debit a geothermal water with an average flow of 390 L / s. This water is characterized by a relatively high salinity and temperature of which is around 65 ° C at the source. Which promotes the formation of limescale deposits within the water supply pipe and the cooling loss thereby increasing the load in direct relation with enormous expense and circuits to replace these lines when completely plugged. The present work is a study of geothermal water quality of the region Djérid from physico-chemical analyzes.

Keywords: water quality, salinity, geothermal, supply pipe

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Authors: Lawrence Williams

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As the mechanism which converts domains to internet protocol (IP) addresses, Domain Name System (DNS) is an essential part of internet usage. It was not designed securely and can be subject to attacks. DNS attacks have become more frequent and sophisticated and the need for detecting and preventing them becomes more important for the modern network. DNS tunnelling attacks are one type of attack that are primarily used for distributed denial-of-service (DDoS) attacks and data exfiltration. Discussion of different techniques to detect and prevent DNS tunneling attacks is done. The methods, models, experiments, and data for each technique are discussed. A proposal about feasibility is made. Future research on these topics is proposed.

Keywords: DNS, tunneling, exfiltration, botnet

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Authors: Dimitrios Dimitriou, Maria Sartzetaki

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In the early days of the of civil aviation, airports are totally state-owned companies under the control of national authorities or regional governmental bodies. From that time the picture has totally changed and airports privatisation and airport business commercialisation are key success factors to stimulate air transport demand, generate revenues and attract investors, linked to reliable and resilience of air transport system. Nowadays, airport's corporate strategy deals with policies and actions, affecting essential the business plans, the financial targets and the economic footprint in a regional economy they serving. Therefore, exploring airport corporate strategy is essential to support the decision in business planning, management efficiency, sustainable development and investment attractiveness on one hand; and define policies towards traffic development, revenues generation, capacity expansion, cost efficiency and corporate social responsibility. This paper explores key outputs in airport corporate strategy for different ownership schemes. The airport corporations are grouped in three major schemes: (a) Public, in which the public airport operator acts as part of the government administration or as a corporised public operator; (b) Mixed scheme, in which the majority of the shares and the corporate strategy is driven by the private or the public sector; and (c) Private, in which the airport strategy is driven by the key aspects of globalisation and liberalisation of the aviation sector. By a systemic approach, the key drivers in corporate strategy for modern airport business structures are defined. Key objectives are to define the key strategic opportunities and challenges and assess the corporate goals and risks towards sustainable business development for each scheme. The analysis based on an extensive cross-sectional dataset for a sample of busy European airports providing results on corporate strategy key priorities, risks and business models. The conventional wisdom is to highlight key messages to authorities, institutes and professionals on airport corporate strategy trends and directions.

Keywords: airport corporate strategy, airport ownership, airports business models, corporate risks

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Authors: Wojciech Górecki, Anna Sowiżdżał, Grzegorz Machowski, Tomasz Maćkowski, Bartosz Papiernik, Michał Stefaniuk

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The article shows results of the project which aims at evaluating possibilities of effective development and exploitation of natural gas from argillaceous series of the Autochthonous Miocene in the Carpathian Foredeep. To achieve the objective, the research team develop a world-trend based but unique methodology of processing and interpretation, adjusted to data, local variations and petroleum characteristics of the area. In order to determine the zones in which maximum volumes of hydrocarbons might have been generated and preserved as shale gas reservoirs, as well as to identify the most preferable well sites where largest gas accumulations are anticipated a number of task were accomplished. Evaluation of petrophysical properties and hydrocarbon saturation of the Miocene complex is based on laboratory measurements as well as interpretation of well-logs and archival data. The studies apply mercury porosimetry (MICP), micro CT and nuclear magnetic resonance imaging (using the Rock Core Analyzer). For prospective location (e.g. central part of Carpathian Foredeep – Brzesko-Wojnicz area) reprocessing and reinterpretation of detailed seismic survey data with the use of integrated geophysical investigations has been made. Construction of quantitative, structural and parametric models for selected areas of the Carpathian Foredeep is performed on the basis of integrated, detailed 3D computer models. Modeling are carried on with the Schlumberger’s Petrel software. Finally, prospective zones are spatially contoured in a form of regional 3D grid, which will be framework for generation modelling and comprehensive parametric mapping, allowing for spatial identification of the most prospective zones of unconventional gas accumulation in the Carpathian Foredeep. Preliminary results of research works indicate a potentially prospective area for occurrence of unconventional gas accumulations in the Polish part of Carpathian Foredeep.

Keywords: autochthonous Miocene, Carpathian foredeep, Poland, shale gas

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Authors: Randa Alharbi, Vladislav Vyshemirsky

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Systems biology is an important field in science which focuses on studying behaviour of biological systems. Modelling is required to produce detailed description of the elements of a biological system, their function, and their interactions. A well-designed model requires selecting a suitable mechanism which can capture the main features of the system, define the essential components of the system and represent an appropriate law that can define the interactions between its components. Complex biological systems exhibit stochastic behaviour. Thus, using probabilistic models are suitable to describe and analyse biological systems. Continuous-Time Markov Chain (CTMC) is one of the probabilistic models that describe the system as a set of discrete states with continuous time transitions between them. The system is then characterised by a set of probability distributions that describe the transition from one state to another at a given time. The evolution of these probabilities through time can be obtained by chemical master equation which is analytically intractable but it can be simulated. Uncertain parameters of such a model can be inferred using methods of Bayesian inference. Yet, inference in such a complex system is challenging as it requires the evaluation of the likelihood which is intractable in most cases. There are different statistical methods that allow simulating from the model despite intractability of the likelihood. Approximate Bayesian computation is a common approach for tackling inference which relies on simulation of the model to approximate the intractable likelihood. Particle Markov chain Monte Carlo (PMCMC) is another approach which is based on using sequential Monte Carlo to estimate intractable likelihood. However, both methods are computationally expensive. In this paper we discuss the efficiency and possible practical issues for each method, taking into account the computational time for these methods. We demonstrate likelihood-free inference by performing analysing a model of the Repressilator using both methods. Detailed investigation is performed to quantify the difference between these methods in terms of efficiency and computational cost.

Keywords: Approximate Bayesian computation(ABC), Continuous-Time Markov Chains, Sequential Monte Carlo, Particle Markov chain Monte Carlo (PMCMC)

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Authors: Amitesh Goswami, Vishal Gulati, Annu Yadav

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In this paper, WEDM has been used to investigate the machining characteristics of Inconel-625 alloy. The machining characteristics namely material removal rate (MRR) and surface roughness (SR) have been investigated along with surface microstructure analysis using SEM and EDS of the machined surface. Taguchi’s L27 Orthogonal array design has been used by considering six varying input parameters viz. Pulse-on time (Ton), Pulse-off time (Toff), Spark Gap Set Voltage (SV), Peak Current (IP), Wire Feed (WF) and Wire Tension (WT) for the responses of interest. It has been found out that Pulse-on time (Ton) and Spark Gap Set Voltage (SV) are the most significant parameters affecting material removal rate (MRR) and surface roughness (SR) are. Microstructure analysis of workpiece was also done using Scanning Electron Microscope (SEM). It was observed that, variations in pulse-on time and pulse-off time causes varying discharge energy and as a result of which deep craters / micro cracks and large/ small number of debris were formed. These results were helpful in studying the effects of pulse-on time and pulse-off time on MRR and SR. Energy Dispersive Spectrometry (EDS) was also done to check the compositional analysis of the material and it was observed that Copper and Zinc which were initially not present in the Inconel 625, later migrated on the material surface from the brass wire electrode during machining

Keywords: MRR, SEM, SR, taguchi, Wire Electric Discharge Machining

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Authors: Hugo Rodríguez

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Migrations of researchers, scientists, and inventors are a widespread phenomenon in modern times. In some cases, migrants stay linked to research groups in their countries of origin, either out of their own conviction or because of government policies. We examine different linear models of technological development (using the Ordinary Least Squares (OLS) technique) in eight selected countries and find that the collaborations between resident and nonresident patent applicants correlate with different levels of performance of the technological policies in three different scenarios. Therefore, the reinforcement of that link must be considered a powerful tool for technological development.

Keywords: development, collaboration, patents, technology

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Authors: Lindani Mbatha, Suvendi Rimer, Mpho Gololo

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Image segmentation is the process of dividing an image into several sections, such as the object's background and the foreground. It is a critical technique in both image-processing tasks and computer vision. Most of the image segmentation algorithms have been developed for gray-scale images and little research and algorithms have been developed for the color images. Most image segmentation algorithms or techniques vary based on the input data and the application. Nearly all of the techniques are not suitable for noisy environments. Most of the work that has been done uses the Markov Random Field (MRF), which involves the computations and is said to be robust to noise. In the past recent years' image segmentation has been brought to tackle problems such as easy processing of an image, interpretation of the contents of an image, and easy analysing of an image. This article reviews and summarizes some of the image segmentation techniques and algorithms that have been developed in the past years. The techniques include neural networks (CNN), edge-based techniques, region growing, clustering, and thresholding techniques and so on. The advantages and disadvantages of medical ultrasound image segmentation techniques are also discussed. The article also addresses the applications and potential future developments that can be done around image segmentation. This review article concludes with the fact that no technique is perfectly suitable for the segmentation of all different types of images, but the use of hybrid techniques yields more accurate and efficient results.

Keywords: clustering-based, convolution-network, edge-based, region-growing

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Authors: Pingshan Chen, Zhiliang Dong

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In order to estimate the post-construction settlement more objectively, the power-polynomial model is proposed, which can reflect the trend of settlement development based on the observed settlement data. It was demonstrated by an actual case history of an embankment, and during the prediction. Compared with the other three prediction models, the power-polynomial model can estimate the post-construction settlement more accurately with more simple calculation.

Keywords: prediction, model, post-construction settlement, soft ground

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Authors: Ana María Rojas Chaparro, Cristian Camilo Sarmiento Chaves

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Given the growing importance of logistics as a discipline for efficient management of materials flow and information, the adoption of tools that permit to create facilities in making decisions based on a global perspective of the system studied has been essential. The article shows how from a concepts-based model is possible to organize and represent in appropriate way the reality, showing accurate and timely information, features that make this kind of models an ideal component to support an information system, recognizing that information as relevant to establish particularities that allow get a better performance about the evaluated sector.

Keywords: system, information, conceptual model, logistics

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Authors: Aakansha Gupta, Neha Vadnere, Tapasvi Soni, M. Anbarsi

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Protein secondary structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Some aspects of protein functions and genome analysis can be predicted by secondary structure prediction. This is used to help annotate sequences, classify proteins, identify domains, and recognize functional motifs. In this paper, we represent protein secondary structure as a mathematical model. To extract and predict the protein secondary structure from the primary structure, we require a set of parameters. Any constants appearing in the model are specified by these parameters, which also provide a mechanism for efficient and accurate use of data. To estimate these model parameters there are many algorithms out of which the most popular one is the EM algorithm or called the Expectation Maximization Algorithm. These model parameters are estimated with the use of protein datasets like RS126 by using the Bayesian Probabilistic method (data set being categorical). This paper can then be extended into comparing the efficiency of EM algorithm to the other algorithms for estimating the model parameters, which will in turn lead to an efficient component for the Protein Secondary Structure Prediction. Further this paper provides a scope to use these parameters for predicting secondary structure of proteins using machine learning techniques like neural networks and fuzzy logic. The ultimate objective will be to obtain greater accuracy better than the previously achieved.

Keywords: model parameters, expectation maximization algorithm, protein secondary structure prediction, bioinformatics

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Authors: Nihat Dipova, Bulent Cangir

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This article presents the results of probabilistic seismic hazard analysis (PSHA) for Antalya (SW Turkey). South west of Turkey is characterized by large earthquakes resulting from the continental collision between the African, Arabian and Eurasian plates and crustal faults. Earthquakes around the study area are grouped into two; crustal earthquakes (D=0-50 km) and subduction zone earthquakes (50-140 km). Maximum observed magnitude of subduction earthquakes is Mw=6.0. Maximum magnitude of crustal earthquakes is Mw=6.6. Sources for crustal earthquakes are faults which are related with Isparta Angle and Cyprus Arc tectonic structures. A new earthquake catalogue for Antalya, with unified moment magnitude scale has been prepared and seismicity of the area around Antalya city has been evaluated by defining ‘a’ and ‘b’ parameters of the Gutenberg-Richter recurrence relationship. The Standard Cornell-McGuire method has been used for hazard computation utilizing CRISIS2007 software. Attenuation relationships proposed by Chiou and Youngs (2008) has been used for 0-50 km earthquakes and Youngs et. al (1997) for deep subduction earthquakes. Finally, Seismic hazard map for peak horizontal acceleration on a uniform site condition of firm rock (average shear wave velocity of about 1130 m/s) at a hazard level of 10% probability of exceedance in 50 years has been prepared.

Keywords: Antalya, peak ground acceleration, seismic hazard assessment, subduction

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Authors: Lama Ajinah

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Luxury brands witnessed continuous growth which followed women’s desire towards individual distinctiveness and social glare. Bags are a woman’s best friend either for aesthetic or functional purposes when she leaves her home for leisure or work. One way of women constant aspiration for being distinguished while reflecting their wealth is through handbags. Subsequently, the demand and attraction by consumers towards the dazzle of luxurious brands for personal pleasure and social status have flourished. According to the literature review, a visual analysis on luxury brands has been explored yet a focus on bags was not discussed in details. Hence, a deep analysis will be dedicated on the two segments by showcasing examples of high-end bag advertising. The research is conducted to understand advertising strategies used in promoting for luxurious products. Furthermore, the paper explores the definition of the term luxury, the condition in which it is used in, and the visual language used along with the term. As luxury is an indicator of superior satisfaction, it is obtained on two levels: a personal and a social level. The examples of luxury brand ads are selected from the last five years to uncover the latest, most common strategies used to promote for luxurious brands. The methods employed in this paper consist of literature review, semiotic analysis, and content analysis. The researcher concludes with revealing the methods used in advertising while categorizing them into various themes.

Keywords: advertising, brands, fashion, graphic design, luxury, semiotic analysis, semiology, visual analysis, visual communication

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Authors: Nuri Caglayan, H. Kursat Celik

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There are many factors that influence the health and productivity of the animals in livestock production fields, including temperature, humidity, carbon dioxide (CO2), ammonia (NH3), hydrogen sulfide (H2S), physical activity and particulate matter. High NH3 concentrations reduce feed consumption and cause daily weight gain. At high concentrations, H2S causes respiratory problems and CO2 displace oxygen, which can cause suffocation or asphyxiation. Good air quality in livestock facilities can have an impact on the health and well-being of animals and humans. Air quality assessment basically depends on strictly given limits without taking into account specific local conditions between harmful gases and other meteorological factors. The stated limitations may be eliminated. using controlling systems based on neural networks and fuzzy logic. This paper describes a fuzzy logic based ventilation algorithm, which can calculate different fan speeds under pre-defined boundary conditions, for removing harmful gases from the production environment. In the paper, a fuzzy logic model has been developed based on a Mamedani’s fuzzy method. The model has been built on MATLAB software. As the result, optimum fan speeds under pre-defined boundary conditions have been presented.

Keywords: air quality, fuzzy logic model, livestock housing, fan speed

Procedia PDF Downloads 358

Authors: Somojit Saha, Rohit K. Chatterjee, Sarit K. Das, Avijit Kar

Abstract:

A new force field is designed for propagation of the parametric contour into deep narrow cortical fold in the application of knowledge based reconstruction of cerebral cortex from MR image of brain. Designing of this force field is highly inspired by the Generalized Gradient Vector Flow (GGVF) model and markedly differs in manipulation of image information in order to determine the direction of propagation of the contour. While GGVF uses edge map as its main driving force, the newly designed force field uses the map of distance between zero valued pixels and their nearest non-zero valued pixel as its main driving force. Hence, it is called Zero-Non-Zero Distance (ZNZD) force field. The objective of this force field is forceful propagation of the contour beyond spurious convergence due to partial volume effect (PVE) in to narrow sulcal fold. Being function of the corresponding non-zero pixel value, the force field has got an inherent property to determine spuriousness of the edge automatically. It is effectively applied along with some morphological processing in the application of cortical reconstruction to breach the hindrance of PVE in narrow sulci where conventional GGVF fails.

Keywords: deformable model, external force field, partial volume effect, cortical reconstruction, MR image of brain

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Authors: S. Kopylov, C. Z. Bo

Abstract:

This study is aimed at exploring the possibility of energy recovery through the suppression of vibrations. The article describes design of electromagnetic dynamic damper. The magnetic part of the device performs the function of a tuned mass damper, thereby providing both energy regeneration and damping properties to the protected mass. According to the theory of tuned mass damper, equations of mathematical models were obtained. Then, under given properties of current system, amplitude frequency response was investigated. Therefore, main ideas and methods for further research were defined.

Keywords: electromagnetic damper, oscillations with two degrees of freedom, regeneration systems, tuned mass damper

Procedia PDF Downloads 199

Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

Procedia PDF Downloads 152

Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

Abstract:

Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

Procedia PDF Downloads 139

Authors: Chanya Inprasit, Yi-Wen Lin

Abstract:

Motion sickness (MS) is an acute disorder that occurs in healthy persons without considering gender, age or ethnicity worldwide. All signs and symptoms of MS are the results of confliction and mismatch among neural signal inputs. It is known that no singular remedy works for everybody, and electroacupuncture (EA) is one of the popular alternative therapies used for MS. Our study utilized a mouse model in order to exclude any psychological factors of MS and EA. Mice lack an emetic reflex. Therefore pica behavior, which is a normal consumption of non-nutritive substances, was found to measure the response of MS in mice. In the laboratory, Kaolin was used as a non-nutrient food substance instead of natural substances lacking nutritional value such as wood, cloth, charcoal, soil or grass. It was hypothesized that EA treatment could reduce the symptoms of MS through the TRPV1 pathways. The results of pica behavior showed a significantly increased intake of kaolin in the MS group throughout the experiment period. Moreover, the Kaolin intake of the EA group decreased to the average baseline of the control group. There was no recorded difference in the food and water intake of each group. The results indicated an increase of the TRPV1, pERK, pJNK and pmTOR protein levels in the thalamus after MS stimulation, and a significant decrease in the EA group compared with that of the control group. These findings suggest that TRPV1 pathways are associated in MS mechanisms and can be reduced by EA.

Keywords: electroacupuncture, motion sickness, Thalamus, TRPV1

Procedia PDF Downloads 239

Authors: R. M. Kashim

Abstract:

The study investigates the conceptual and procedural knowledge of rational number in primary school teachers, specifically, the primary school teachers level of conceptual knowledge about rational number and the primary school teachers level of procedural knowledge about rational numbers. The study was carried out in Bauchi metropolis in Bauchi state of Nigeria. A Conceptual and Procedural Knowledge Test was used as the instrument for data collection, 54 mathematics teachers in Bauchi primary schools were involved in the study. The collections were analyzed using mean and standard deviation. The findings revealed that the primary school mathematics teachers in Bauchi metropolis posses a low level of conceptual knowledge of rational number and also possess a high level of Procedural knowledge of rational number. It is therefore recommended that to be effective, teachers teaching mathematics most posses a deep understanding of both conceptual and procedural knowledge. That way the most knowledgeable teachers in mathematics deliver highly effective rational number instructions. Teachers should not ignore the mathematical concept aspect of rational number teaching. This is because only the procedural aspect of Rational number is highlighted during instructions; this often leads to rote - learning of procedures without understanding the meanings. It is necessary for teachers to learn rational numbers teaching method that focus on both conceptual knowledge and procedural knowledge teaching.

Keywords: conceptual knowledge, primary school teachers, procedural knowledge, rational numbers

Procedia PDF Downloads 308

Authors: Wanlapa Kunsongkeit

Abstract:

When a person gets sick, he or she goes to hospital for the treatment. In the case of severe illness, there might be no hope for some patients to recover. In this state, the patients will face anxiety and fear. These feelings make the patients suffer in mind until the time of death or called bad death. These feeling also directly effect to family members who are loved ones and significant persons of the patients. They can help the dying patients to have good death. From literature reviews, many studies focused on good death in patients and nurses. Little is known about good death in family member. Therefore, the qualitative research based on Heideggerian phenomenology aimed to describe good death as perceived by the critically ill patients’ family members. Five informants who were the critically ill patients’ family members at hospital in Chonburi were purposively selected. Data were collected by in-depth interview, observation and critical reflection during January, 2014 to March, 2014 . Cohen, Kahn and Steeves’s (2000) steps guided data analysis. Trustworthiness was maintained throughout the study following Lincoln and Guba’s guidelines. Four themes were emerged, which were no suffering, acceptance of imminent death, preparing for death, and being with the family. This findings provide deep understanding of good death as perceived by the critically ill patients’ family members. It can be basic information for nurses to provide good death nursing care and further explore for development of knowledge regarding good death nursing care.

Keywords: good death, family member, critically ill patient, phenomenology

Procedia PDF Downloads 423