Search results for: diagnostic obesity notation model assessment index

Authors: K. Nirmala Devi, V. Murali Bhaskaran

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Traditional document representation for classification follows Bag of Words (BoW) approach to represent the term weights. The conventional method uses the Vector Space Model (VSM) to exploit the statistical information of terms in the documents and they fail to address the semantic information as well as order of the terms present in the documents. Although, the phrase based approach follows the order of the terms present in the documents rather than semantics behind the word. Therefore, a semantic concept based approach is used in this paper for enhancing the semantics by incorporating the ontology information. In this paper a novel method is proposed to forecast the intraday stock market price directional movement based on the sentiments from Twitter and money control news articles. The stock market forecasting is a very difficult and highly complicated task because it is affected by many factors such as economic conditions, political events and investor’s sentiment etc. The stock market series are generally dynamic, nonparametric, noisy and chaotic by nature. The sentiment analysis along with wisdom of crowds can automatically compute the collective intelligence of future performance in many areas like stock market, box office sales and election outcomes. The proposed method utilizes collective sentiments for stock market to predict the stock price directional movements. The collective sentiments in the above social media have powerful prediction on the stock price directional movements as up/down by using Granger Causality test.

Keywords: Bag of Words, Collective Sentiments, Ontology, Semantic relations, Sentiments, Social media, Stock Prediction, Twitter, Vector Space Model and wisdom of crowds.

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Authors: Ákos Wolf, Richard P. Ray

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Due to the introduction of Eurocode 8, the structural design for seismic and dynamic effects has become more significant in Hungary. This has emphasized the need for more effort to describe the behavior of structures under these conditions. Soil conditions have a significant effect on the response of structures by modifying the stiffness and damping of the soil-structural system and by modifying the seismic action as it reaches the ground surface. Shear modulus (G) and shear wave velocity (v_s), which are often measured in the field, are the fundamental dynamic soil properties for foundation vibration problems, liquefaction potential and earthquake site response analysis. There are several laboratory and in-situ measurement techniques to evaluate dynamic soil properties, but unfortunately, they are often too expensive for general design practice. However, a significant number of correlations have been proposed to determine shear wave velocity or shear modulus from Cone Penetration Tests (CPT), which are used more and more in geotechnical design practice in Hungary. This allows the designer to analyze and compare CPT and seismic test result in order to select the best correlation equations for Hungarian soils and to improve the recommendations for the Hungarian geologic conditions. Based on a literature review, as well as research experience in Hungary, the influence of various parameters on the accuracy of results will be shown. This study can serve as a basis for selecting and modifying correlation equations for Hungarian soils. Test data are taken from seven locations in Hungary with similar geologic conditions. The shear wave velocity values were measured by seismic CPT. Several factors are analyzed including soil type, behavior index, measurement depth, geologic age etc. for their effect on the accuracy of predictions. The final results show an improved prediction method for Hungarian soils

Keywords: CPT correlation, dynamic soil properties, seismic CPT, shear wave velocity.

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Authors: Mihai Caramihai, Irina Severin

Abstract:

Bioprocesses are appreciated as difficult to control because their dynamic behavior is highly nonlinear and time varying, in particular, when they are operating in fed batch mode. The research objective of this study was to develop an appropriate control method for a complex bioprocess and to implement it on a laboratory plant. Hence, an intelligent control structure has been designed in order to produce biomass and to maximize the specific growth rate.

Keywords: Fed batch bioprocess, mass-balance model, fuzzy control

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Authors: Walenty Oniszczuk

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The use of buffer thresholds, blocking and adequate service strategies are well-known techniques for computer networks traffic congestion control. This motivates the study of series queues with blocking, feedback (service under Head of Line (HoL) priority discipline) and finite capacity buffers with thresholds. In this paper, the external traffic is modelled using the Poisson process and the service times have been modelled using the exponential distribution. We consider a three-station network with two finite buffers, for which a set of thresholds (tm1 and tm2) is defined. This computer network behaves as follows. A task, which finishes its service at station B, gets sent back to station A for re-processing with probability o. When the number of tasks in the second buffer exceeds a threshold tm2 and the number of task in the first buffer is less than tm1, the fed back task is served under HoL priority discipline. In opposite case, for fed backed tasks, “no two priority services in succession" procedure (preventing a possible overflow in the first buffer) is applied. Using an open Markovian queuing schema with blocking, priority feedback service and thresholds, a closed form cost-effective analytical solution is obtained. The model of servers linked in series is very accurate. It is derived directly from a twodimensional state graph and a set of steady-state equations, followed by calculations of main measures of effectiveness. Consequently, efficient expressions of the low computational cost are determined. Based on numerical experiments and collected results we conclude that the proposed model with blocking, feedback and thresholds can provide accurate performance estimates of linked in series networks.

Keywords: Blocking, Congestion control, Feedback, Markov chains, Performance evaluation, Threshold-base networks.

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Authors: Chhaya Gangwal, R. N. Bhaumik, Shishir Kumar

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Some properties of Intuitionistic Fuzzy (IF) rough relational algebraic operators under an IF rough relational data model are investigated and illustrated using diabetes and heart disease databases. These properties are important and desirable for processing queries in an effective and efficient manner.

 

Keywords: IF Set, Rough Set, IF Rough Relational Database, IF rough Relational Operators.

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Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki

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Transport infrastructure assets are key components of the national asset portfolio. The decision to invest in a new infrastructure in transports could take from a few years to some decades. This is mainly because of the need to reserve and spent many capitals, the long payback period, the number of the stakeholders involved in decision process and –many times- the investment and business risks are high. Therefore, the decision assessment framework is an essential challenge linked with the key decision factors meet the stakeholder expectations highlighting project trade-offs, financial risks, business uncertainties and market limitations. This paper examines the decision process for new transport infrastructure projects in cross border regions, where a wide range of stakeholders with different expectation is involved. According to a consequences analysis systemic approach, the relationship of transport infrastructure development, economic system development and stakeholder expectation is analyzed. Adopting the on system of system methodological approach, the decision making framework, variables, inputs and outputs are defined, highlighting the key shareholder’s role and expectations. The application provides the methodology outputs presenting the proposed decision framework for a strategic railway project in north Greece deals with the upgrade of the existing railway corridor connecting Greece, Turkey and Bulgaria.

Keywords: System of system approach, decision making, cross-border, infrastructure project.

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Authors: D. Ščeulovs, E. Gaile-Sarkane

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Latvia is the fourth in the world by means of broadband internet speed. The total number of internet users in Latvia exceeds 70% of its population. The number of active mailboxes of the local internet e-mail service Inbox.lv accounts for 68% of the population and 97.6% of the total number of internet users. The Latvian portal Draugiem.lv is a phenomenon of social media, because 58.4 % of the population and 83.5% of internet users use it. A majority of Latvian company profiles are available on social networks, the most popular being Twitter.com. These and other parameters prove the fact consumers and companies are actively using the Internet. 

However, after the authors in a number of studies analyzed how enterprises are employing the e-environment, namely, e-environment tools, they arrived to the conclusions that are not as flattering as the aforementioned statistics. There is an obvious contradiction between the statistical data and the actual studies. As a result, the authors have posed a question: Why are entrepreneurs resistant to e-tools? In order to answer this question, the authors have addressed the Technology Acceptance Model (TAM). The authors analyzed each phase and determined several factors affecting the use of e-environment, reaching the main conclusion that entrepreneurs do not have a sufficient level of e-literacy (digital literacy). 

The authors employ well-established quantitative and qualitative methods of research: grouping, analysis, statistic method, factor analysis in SPSS 20  environment etc. 

The theoretical and methodological background of the research is formed by, scientific researches and publications, that from the mass media and professional literature, statistical information from legal institutions as well as information collected by the author during the survey.

Keywords: E-environment, e-environment tools, technology acceptance model, factors.

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Authors: D. Zare, H. Naderi, A. A. Jafari

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Drying characteristics of rough rice (variety of lenjan) with an initial moisture content of 25% dry basis (db) was studied in a hot air dryer assisted by infrared heating. Three arrival air temperatures (30, 40 and 500C) and four infrared radiation intensities (0, 0.2 , 0.4 and 0.6 W/cm2) and three arrival air speeds (0.1, 0.15 and 0.2 m.s-1) were studied. Bending strength of brown rice kernel, percentage of cracked kernels and time of drying were measured and evaluated. The results showed that increasing the drying arrival air temperature and radiation intensity of infrared resulted decrease in drying time. High bending strength and low percentage of cracked kernel was obtained when paddy was dried by hot air assisted infrared dryer. Between this factors and their interactive effect were a significant difference (p<0.01). An intensity level of 0.2 W/cm2 was found to be optimum for radiation drying. Furthermore, in the present study, the application of Artificial Neural Network (ANN) for predicting the moisture content during drying (output parameter for ANN modeling) was investigated. Infrared Radiation intensity, drying air temperature, arrival air speed and drying time were considered as input parameters for the model. An ANN model with two hidden layers with 8 and 14 neurons were selected for studying the influence of transfer functions and training algorithms. The results revealed that a network with the Tansig (hyperbolic tangent sigmoid) transfer function and trainlm (Levenberg-Marquardt) back propagation algorithm made the most accurate predictions for the paddy drying system. Mean square error (MSE) was calculated and found that the random errors were within and acceptable range of ±5% with coefficient of determination (R2) of 99%.

Keywords: Rough rice, Infrared-hot air, Artificial Neural Network

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Authors: Mahesh Kumar Farejiya, Anil Kumar Dikshit

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The toxic metal contamination and their biomagnification in marine fishes is a serious public health concern specially, in the coastal areas and the small islands. In the present study, concentration of toxic heavy metals like zinc (Zn), cadmium (Cd), lead (Pb), nickel (Ni), cobalt (Co), chromium (Cr) and mercury (Hg) were determined in the tissues of tunas (T. albacores) caught from the area near to Lakshdweep Islands. The heavy metals are one of the indicators for the marine water pollution. Geochemical weathering, industrialization, agriculture run off, fishing, shipping and oil spills are the major pollutants. The presence of heavy toxic metals in the near coastal water fishes at both western coast and eastern coast of India has been well established. The present study was conducted assuming that the distant island will not have the metals presence in a way it is at the near main land coast. However, our study shows that there is a significant amount of the toxic metals present in the tissues of tuna samples. The gill, lever and flash samples were collected in waters around Lakshdweep Islands. They were analyzed using ICP–AES for the toxic metals after microwave digestion. The concentrations of the toxic metals were found in all fish samples and the general trend of presence was in decreasing order as Zn > Al > Cd > Pb > Cr > Ni > Hg. The amount of metals was found to higher in fish having more weight.

Keywords: Biomagnifications, marine environment, toxic heavy metals, Tuna fish.

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Authors: Omid F. Valilai, Mahmoud Houshmand

Abstract:

Nowadays companies strive to survive in a competitive global environment. To speed up product development/modifications, it is suggested to adopt a collaborative product development approach. However, despite the advantages of new IT improvements still many CAx systems work separately and locally. Collaborative design and manufacture requires a product information model that supports related CAx product data models. To solve this problem many solutions are proposed, which the most successful one is adopting the STEP standard as a product data model to develop a collaborative CAx platform. However, the improvement of the STEP-s Application Protocols (APs) over the time, huge number of STEP AP-s and cc-s, the high costs of implementation, costly process for conversion of older CAx software files to the STEP neutral file format; and lack of STEP knowledge, that usually slows down the implementation of the STEP standard in collaborative data exchange, management and integration should be considered. In this paper the requirements for a successful collaborative CAx system is discussed. The STEP standard capability for product data integration and its shortcomings as well as the dominant platforms for supporting CAx collaboration management and product data integration are reviewed. Finally a platform named LAYMOD to fulfil the requirements of CAx collaborative environment and integrating the product data is proposed. The platform is a layered platform to enable global collaboration among different CAx software packages/developers. It also adopts the STEP modular architecture and the XML data structures to enable collaboration between CAx software packages as well as overcoming the STEP standard limitations. The architecture and procedures of LAYMOD platform to manage collaboration and avoid contradicts in product data integration are introduced.

Keywords: CAx, Collaboration management, STEP applicationmodules, STEP standard, XML data structures

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Authors: G. S. Ayyappan, M. Raja Raghavan, R. Poonthalir, Kota Srinivas, B. Ramesh Babu

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Electrical energy demand in the World and particularly in India, is increasing drastically more than its production over a period of time. In order to reduce the demand-supply gap, conserving energy becomes mandatory. Induction motors are the main driving force in the industries and contributes to about half of the total plant energy consumption. By effective monitoring and control of induction motors, huge electricity can be saved. This paper deals about the design and development of such a system, which employs iLON Smart Server and motor performance monitoring nodes. These nodes will monitor the performance of induction motors on-line, on-site and in-situ in the industries. The node monitors the performance of motors by simply measuring the electrical power input and motor shaft speed; coupled to genetic algorithm to estimate motor efficiency. The nodes are connected to the iLON Server through RS485 network. The web server collects the motor performance data from nodes, displays online, logs periodically, analyzes, alerts, and generates reports. The system could be effectively used to operate the motor around its Best Operating Point (BOP) as well as to perform the Life Cycle Assessment of Induction motors used in the industries in continuous operation.

Keywords: Best operating point, iLON smart server, motor asset management, LONWORKS, Modbus RTU, motor performance.

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Authors: Steve Fish, Chris Lambert

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Cumbria is a geo-political county in Northwest England within which the Lake District National Park, a UNESCO World Heritage site is located. Whilst the area has a formidable reputation for natural beauty and historic assets, the innovation ecosystem is described as ‘patchy’ for a number of reasons. The county is one of the largest in England by area and is sparsely populated. This paper describes the needs, development and delivery of an SME business-support programme funded by the European Regional Development Fund, Lancaster University and the University of Cumbria. The Cumbria Innovations Platform (CUSP) Project has been designed to respond to the nuanced needs of SMEs in this locale, whilst promoting the adoption of research and innovation. CUSP utilizes a funnel method to support rural businesses with access to university innovation intervention. CUSP has been built on a three-tier model: Communicate, Collaborate and Create. The paper describes this project in detail and presents results in terms of output indicators achieved, a beneficiary telephone survey and wider economic forecasts. From a pragmatic point-of-view, the paper provides experiences and reflections of those people who are delivering and evaluating knowledge exchange. The authors discuss some of the benefits, challenges and implications for both policy makers and practitioners. Finally, the paper aims to serve as an invitation to others who may consider adopting a similar method of university-industry collaboration in their own region.

Keywords: Regional business support, rural business support, university-industry collaboration, collaborative R&D, SMEs, knowledge exchange.

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Authors: Khaireyah Kh. Al-Hamad, V. Nassehi, A. R. Khan

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Air pollution is a major environmental health problem, affecting developed and developing countries around the world. Increasing amounts of potentially harmful gases and particulate matter are being emitted into the atmosphere on a global scale, resulting in damage to human health and the environment. Petroleum-related air pollutants can have a wide variety of adverse environmental impacts. In the crude oil production sectors, there is a strong need for a thorough knowledge of gaseous emissions resulting from the flaring of associated gas of known composition on daily basis through combustion activities under several operating conditions. This can help in the control of gaseous emission from flares and thus in the protection of their immediate and distant surrounding against environmental degradation. The impacts of methane and non-methane hydrocarbons emissions from flaring activities at oil production facilities at Kuwait Oilfields have been assessed through a screening study using records of flaring operations taken at the gas and oil production sites, and by analyzing available meteorological and air quality data measured at stations located near anthropogenic sources. In the present study the Industrial Source Complex (ISCST3) Dispersion Model is used to calculate the ground level concentrations of methane and nonmethane hydrocarbons emitted due to flaring in all over Kuwait Oilfields. The simulation of real hourly air quality in and around oil production facilities in the State of Kuwait for the year 2006, inserting the respective source emission data into the ISCST3 software indicates that the levels of non-methane hydrocarbons from the flaring activities exceed the allowable ambient air standard set by Kuwait EPA. So, there is a strong need to address this acute problem to minimize the impact of methane and non-methane hydrocarbons released from flaring activities over the urban area of Kuwait.

Keywords: Kuwait Oilfields, ISCST3 model, flaring, Airpollution, Methane and Non-methane.

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Authors: Pavan K. Emani, Shashank Kothari, V. S. Phanikanth

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The ultimate load analysis of RC pile groups has assumed a lot of significance under liquefying soil conditions, especially due to post-earthquake studies of 1964 Niigata, 1995 Kobe and 2001 Bhuj earthquakes. The present study reports the results of numerical simulations on pile groups subjected to monotonically increasing lateral loads under design amounts of pile axial loading. The soil liquefaction has been considered through the non-linear p-y relationship of the soil springs, which can vary along the depth/length of the pile. This variation again is related to the liquefaction potential of the site and the magnitude of the seismic shaking. As the piles in the group can reach their extreme deflections and rotations during increased amounts of lateral loading, a precise modeling of the inelastic behavior of the pile cross-section is done, considering the complete stress-strain behavior of concrete, with and without confinement, and reinforcing steel, including the strain-hardening portion. The possibility of the inelastic buckling of the individual piles is considered in the overall collapse modes. The model is analysed using Riks analysis in finite element software to check the post buckling behavior and plastic collapse of piles. The results confirm the kinds of failure modes predicted by centrifuge test results reported by researchers on pile group, although the pile material used is significantly different from that of the simulation model. The extension of the present work promises an important contribution to the design codes for pile groups in liquefying soils.

Keywords: Collapse load analysis, inelastic buckling, liquefaction, pile group.

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Authors: R. Unnikrishnan, K. Shankar

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In the case of high-speed fighter aircrafts, seat ejection is designed mainly for the safety of the pilot in case of an emergency. Strong windblast due to the high velocity of flight is one main difficulty in clearing the tail of the aircraft. Excessive G-forces generated, immobilizes the pilot from escape. In most of the cases, seats are ejected out of the aircrafts by explosives or by rocket motors attached to the bottom of the seat. Ejection forces are primarily in the vertical direction with the objective of attaining the maximum possible velocity in a specified period of time. The safe ejection parameters are studied to estimate the critical time of ejection for various geometries and velocities of flight. An equivalent analytical 2-dimensional biomechanical model of the human spine has been modelled consisting of vertebrae and intervertebral discs with a lumped mass approach. The 24 vertebrae, which consists of the cervical, thoracic and lumbar regions, in addition to the head mass and the pelvis has been designed as 26 rigid structures and the intervertebral discs are assumed as 25 flexible joint structures. The rigid structures are modelled as mass elements and the flexible joints as spring and damper elements. Here, the motions are restricted only in the mid-sagittal plane to form a 26 degree of freedom system. The equations of motions are derived for translational movement of the spinal column. An ejection force with a linearly increasing acceleration profile is applied as vertical base excitation on to the pelvis. The dynamic vibrational response of each vertebra in time-domain is estimated.

Keywords: Biomechanical model, lumped mass, seat ejection, vibrational response.

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Authors: Mohamed K. Shahin, Ahmed M. Badawi, Mohamed E. M. Rasmy

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Prior research evidenced that unimodal biometric systems have several tradeoffs like noisy data, intra-class variations, restricted degrees of freedom, non-universality, spoof attacks, and unacceptable error rates. In order for the biometric system to be more secure and to provide high performance accuracy, more than one form of biometrics are required. Hence, the need arise for multimodal biometrics using combinations of different biometric modalities. This paper introduces a multimodal biometric system (MMBS) based on fusion of whole dorsal hand geometry and fingerprints that acquires right and left (Rt/Lt) near-infra-red (NIR) dorsal hand geometry (HG) shape and (Rt/Lt) index and ring fingerprints (FP). Database of 100 volunteers were acquired using the designed prototype. The acquired images were found to have good quality for all features and patterns extraction to all modalities. HG features based on the hand shape anatomical landmarks were extracted. Robust and fast algorithms for FP minutia points feature extraction and matching were used. Feature vectors that belong to similar biometric traits were fused using feature fusion methodologies. Scores obtained from different biometric trait matchers were fused using the Min-Max transformation-based score fusion technique. Final normalized scores were merged using the sum of scores method to obtain a single decision about the personal identity based on multiple independent sources. High individuality of the fused traits and user acceptability of the designed system along with its experimental high performance biometric measures showed that this MMBS can be considered for med-high security levels biometric identification purposes.

Keywords: Unimodal, Multi-Modal, Biometric System, NIR Imaging, Dorsal Hand Geometry, Fingerprint, Whole Hands, Feature Extraction, Feature Fusion, Score Fusion

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Authors: Aurela Saliaj, Majlinda Zahaj, Bruna Pura

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Background: Breast milk may impact early brain development, with potentially important biological, medical and social implications. There is an important discussion on which is the adequate breastfeeding extension to the development consolidation and how the children breastfeeding affects their psychomotor development, in the first year of life, and in following periods as well. Some special fats (LC PUFA) contained in breast milk play a key role in the brain’s maturation and cognitive development or social skills. These capacities created during breastfeeding time would be unfolded throughout all lifespan. Aim of the study: In our research, we have studied the effect of breastfeeding in preschooler's psychomotor assessment. Method: This study was conducted in a sample of 158 preschool children in Vlorë, Albania. We have measured the psychometric parameters of preschoolers with ASQ-3 (Age&Stage Questionnaires- 3). The studied sample was divided in three groups according to their breastfeeding duration (3, 6 and 12 months). Results: Children breastfed for only 3 months have definitely lower psychometric scores compared to the ones with 6 or more months of breastfeeding (respectively 217 to 239 ASQ-3 scores). Six and twelvemonth breastfed children have progressively more odds to have high levels of psychomotor development comparing to those with only 3 months of breastfeeding. The most affected psychometric domains by shortness of breastfeeding are Communication and Global motor. Conclusion: This leads to conclusion that to ensure high psychomotor parameters during childhood is necessary breastfeeding for at least 6 months.

Keywords: Breastfeeding, preschoolers, psycho-motor development, psycho-motor domains.

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Authors: Nanjiang Chen

Abstract:

In the backdrop of expanding urban landscapes, accurately assessing spatial openness is critical. Traditional visibility analysis methods grapple with discretization errors and inefficiencies, creating a gap in truly capturing the human experience of space. Addressing these gaps, this paper presents a continuous visibility algorithm, providing a potentially valuable approach to measuring urban spaces from a human - centric perspective. This study presents a methodological breakthrough by applying this algorithm to urban visibility analysis. Unlike conventional approaches, this technique allows for a continuous range of visibility assessment, closely mirroring human visual perception. By eliminating the need for predefined subdivisions in ray casting, it offers a more accurate and efficient tool for urban planners and architects. The proposed algorithm not only reduces computational errors but also demonstrates faster processing capabilities, validated through a case study in Beijing's urban setting. Its key distinction lies in its potential to benefit a broad spectrum of stakeholders, ranging from urban developers to public policymakers, aiding in the creation of urban spaces that prioritize visual openness and quality of life. This advancement in urban analysis methods could lead to more inclusive, comfortable, and well-integrated urban environments, enhancing the spatial experience for communities worldwide.

Keywords: Visual openness, spatial continuity, ray-tracing algorithms, urban computation.

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Authors: Vipin Saxena, Deepa Raj

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Unified Modeling language (UML) is one of the important modeling languages used for the visual representation of the research problem. In the present paper, UML model is designed for the Instruction pipeline which is used for the evaluation of the instructions of software programs. The class and sequence diagrams are designed & performance is evaluated for instructions of a sample program through a case study.

Keywords: UML, Instruction Pipeline, Class Diagram &Sequence Diagram.

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Authors: Yasin Tadayonrad, Alassane Ballé Ndiaye

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Most of the supply chain networks have many nodes starting from the suppliers’ side up to the customers’ side that each node sends/receives the raw materials/products from/to the other nodes. One of the major concerns in this kind of supply chain network is finding the best schedule for loading/unloading the shipments through the whole network by which all the constraints in the source and destination nodes are met and all the shipments are delivered on time. One of the main constraints in this problem is the loading/unloading capacity in each source/destination node at each time slot (e.g., per week/day/hour). Because of the different characteristics of different products/groups of products, the capacity of each node might differ based on each group of products. In most supply chain networks (especially in the Fast-moving consumer goods (FMCG) industry), there are different planners/planning teams working separately in different nodes to determine the loading/unloading timeslots in source/destination nodes to send/receive the shipments. In this paper, a mathematical problem has been proposed to find the best timeslots for loading/unloading the shipments minimizing the overall delays subject to respecting the capacity of loading/unloading of each node, the required delivery date of each shipment (considering the lead-times), and working-days of each node. This model was implemented on Python and solved using Python-MIP on a sample data set. Finally, the idea of a heuristic algorithm has been proposed as a way of improving the solution method that helps to implement the model on larger data sets in real business cases, including more nodes and shipments.

Keywords: Supply chain management, transportation, multiple-multiple network, timeslots management, mathematical modeling, mixed integer programming.

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Authors: Sareh Rajabi, Salwa Bheiry

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In general, Covid-19 created many financial and non-financial damages to the economy and community. Level and severity of covid-19 as pandemic case varies over the region and due to different types of the projects. Covid-19 virus emerged as one of the most imperative risk management factors word-wide recently. Therefore, as part of portfolio management assessment, it is essential to evaluate severity of such risk on the project and program in portfolio management level to avoid any risky portfolio. Covid-19 appeared very effectively in South America, part of Europe and Middle East. Such pandemic infection affected the whole universe, due to lock down, interruption in supply chain management, health and safety requirements, transportations and commercial impacts. Therefore, this research proposes Analytical Hierarchy Process (AHP) to analyze and assess such pandemic case like Covid-19 and its impacts on the construction projects. The AHP technique uses four sub-criteria: Health and safety, commercial risk, completion risk and contractual risk to evaluate the project and program. The result will provide the decision makers with information which project has higher or lower risk in case of Covid-19 and pandemic scenario. Therefore, the decision makers can have most feasible solution based on effective weighted criteria for project selection within their portfolio to match with the organization’s strategies.

Keywords: Portfolio management, risk management, COVID-19, analytical hierarchy process technique.

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Authors: Rodolfo Lorbieski, Silvia Modesto Nassar

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Many supervised machine learning tasks require decision making across numerous different classes. Multi-class classification has several applications, such as face recognition, text recognition and medical diagnostics. The objective of this article is to analyze an adapted method of Stacking in multi-class problems, which combines ensembles within the ensemble itself. For this purpose, a training similar to Stacking was used, but with three levels, where the final decision-maker (level 2) performs its training by combining outputs from the tree-based pair of meta-classifiers (level 1) from Bayesian families. These are in turn trained by pairs of base classifiers (level 0) of the same family. This strategy seeks to promote diversity among the ensembles forming the meta-classifier level 2. Three performance measures were used: (1) accuracy, (2) area under the ROC curve, and (3) time for three factors: (a) datasets, (b) experiments and (c) levels. To compare the factors, ANOVA three-way test was executed for each performance measure, considering 5 datasets by 25 experiments by 3 levels. A triple interaction between factors was observed only in time. The accuracy and area under the ROC curve presented similar results, showing a double interaction between level and experiment, as well as for the dataset factor. It was concluded that level 2 had an average performance above the other levels and that the proposed method is especially efficient for multi-class problems when compared to binary problems.

Keywords: Stacking, multi-layers, ensemble, multi-class.

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Authors: Chethana K., Guru Prasad A. S., Vikranth H. N., Varun H., Omkar S. N., Asokan S.

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This paper describes a novel application of Fiber Braggs Grating (FBG) sensors in the assessment of human postural stability and balance on an unstable platform. In this work, FBG sensor Stability Analyzing Device (FBGSAD) is developed for measurement of plantar strain to assess the postural stability of subjects on unstable platforms during different stances in eyes open and eyes closed conditions on a rocker board. The studies are validated by comparing the Centre of Gravity (CG) variations measured on the lumbar vertebra of subjects using a commercial accelerometer. The results obtained from the developed FBGSAD depict qualitative similarities with the data recorded by commercial accelerometer. The advantage of the FBGSAD is that it measures simultaneously plantar strain distribution and postural stability of the subject along with its inherent benefits like non-requirement of energizing voltage to the sensor, electromagnetic immunity and simple design which suits its applicability in biomechanical applications. The developed FBGSAD can serve as a tool/yardstick to mitigate space motion sickness, identify individuals who are susceptible to falls and to qualify subjects for balance and stability, which are important factors in the selection of certain unique professionals such as aircraft pilots, astronauts, cosmonauts etc.

Keywords: Biomechanics, Fiber Bragg Gratings, Plantar Strain Measurement, Postural Stability Analysis.

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Authors: Mihai Caramihai Ana A Chirvase, Irina Severin

Abstract:

Bioprocesses are appreciated as difficult to control because their dynamic behavior is highly nonlinear and time varying, in particular, when they are operating in fed batch mode. The research objective of this study was to develop an appropriate control method for a complex bioprocess and to implement it on a laboratory plant. Hence, an intelligent control structure has been designed in order to produce biomass and to maximize the specific growth rate.

Keywords: Fed batch bioprocess, mass-balance model, fuzzy control.

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Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L Duan

Abstract:

The conditional density characterizes the distribution of a response variable y given other predictor x, and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts a motivating starting point. In this work, we extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zP , zN]. The zP component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zN component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach, coined Augmented Posterior CDE (AP-CDE), only requires a simple modification on the common normalizing flow framework, while significantly improving the interpretation of the latent component, since zP represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of x-related variations due to factors such as lighting condition and subject id, from the other random variations. Further, the experiments show that an unconditional NF neural network, based on an unsupervised model of z, such as Gaussian mixture, fails to generate interpretable results.

Keywords: Conditional density estimation, image generation, normalizing flow, supervised dimension reduction.

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Authors: Mohammad Hossein Hojjati , Fardin Boustani

Abstract:

Groundwater is one of the most important water resources in Fars province. Based on this study, 95 percent of the total annual water consumption in Fars is used for agriculture, whereas the percentages for domestic and industrial uses are 4 and 1 percent, respectively. Population growth, urban and industrial growth, and agricultural development in Fars have created a condition of water stress. In this province, farmers and other users are pumping groundwater faster than its natural replenishment rate, causing a continuous drop in groundwater tables and depletion of this resource. In this research variation of groundwater level , their effects and ways to help control groundwater levels in some plains of Fars were evaluated .Excessive exploitation of groundwater in Darab, Jahrom, Estahban, Arsanjan, Khir and Niriz plains of Fars caused the groundwater levels fall too fast or to unacceptable levels. The average drawdown of the water table in Arsanjan, Khir. Estahban and Niriz plain plains were 12,8, 9 and 6 meters during 16,11,11 and 13 years ago respectively. This not only reduces available water resources and well yields but also can saline water intrusion, reductions in river flow and in wetland areas , drying springs, and ground subsidence, considerable increase in pumping costs and a significant decline in crop yields as a result of the increasing salinity. Finally based on situation and condition of the aquifer some suggestions are recommended.

Keywords: Fars province , ground water overdraft , water table

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Authors: John Hadden, Ashutosh Tiwari, Rajkumar Roy, Dymitr Ruta

Abstract:

The aim of this paper is to identify the most suitable model for churn prediction based on three different techniques. The paper identifies the variables that affect churn in reverence of customer complaints data and provides a comparative analysis of neural networks, regression trees and regression in their capabilities of predicting customer churn.

Keywords: Churn, Decision Trees, Neural Networks, Regression.

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Authors: Joel S. Mtebe, Aron Kondoro, Mussa M. Kissaka, Elia Kibga

Abstract:

Sub-Saharan Africa is described as the second fastest growing in mobile phone penetration in the world more than in the United States or the European Union. Mobile phones have been used to provide a lot of opportunities to improve people’s lives in the region such as in banking, marketing, entertainment, and paying for various bills such as water, TV, and electricity. However, the potential of mobile phones to enhance teaching and learning has not been explored. This study presents an experience of developing and delivering SMS based quiz questions used to assess mastery of subject content knowledge of science and mathematics secondary school teachers in Tanzania. The SMS quizzes were used as a follow up support mechanism to 500 teachers who participated in a project to upgrade subject content knowledge of teachers in science and mathematics subjects in Tanzania. Quizzes of 10-15 questions were sent to teachers each week for 8 weeks and the results were analyzed using SPSS. Results show that teachers who participated in chemistry and biology subjects have better performance compared to those who participated in mathematics and physics subjects. Teachers reported some challenges that led to poor performance, This research has several practical implications for those who are implementing or planning to use mobile phones in teaching and learning especially in rural secondary schools in sub-Saharan Africa.

Keywords: Mobile learning, e-learning, educational technologies, SMS, secondary education, assessment.

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Authors: Mohamed Ammar Abbassi, Kamel Guedri, Mohamed Naceur Borjini, Kamel Halouani, Belkacem Zeghmati

Abstract:

The radiative heat transfer problem is investigated numerically for 2D complex geometry biomass pyrolysis reactor composed of two pyrolysis chambers and a heat recuperator. The fumes are a mixture of carbon dioxide and water vapor charged with absorbing and scattering particles and soot. In order to increase gases residence time and heat transfer, the heat recuperator is provided with many inclined, vertical, horizontal, diffuse and grey baffles of finite thickness and has a complex geometry. The Finite Volume Method (FVM) is applied to study radiative heat transfer. The blocked-off region procedure is used to treat the geometrical irregularities. Eight cases are considered in order to demonstrate the effect of adding baffles on the walls of the heat recuperator and on the walls of the pyrolysis rooms then choose the best case giving the maximum heat flux transferred to the biomass in the pyrolysis chambers. Ray effect due to the presence of baffles is studied and demonstrated to have a crucial effect on radiative heat flux on the walls of the pyrolysis rooms. Shadow effect caused by the presence of the baffles is also studied. The non grey radiative heat transfer is studied for the real existent configuration. The Weighted Sum of The Grey Gases (WSGG) Model of Kim and Song is used as non grey model. The effect of soot volumetric fraction on the non grey radiative heat flux is investigated and discussed.

Keywords: Baffles, Blocked-off region procedure, FVM, Heat recuperation, Radiative heat transfer, Shadow effect.

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Authors: B. Karakas, S. Lakestani, C. Guler, B. Guciz Dogan, S. Acar Vaizoglu, A. Taner, B. Sekerel, R. Tıpırdamaz, G. Gullu

Abstract:

Particulate matter (PM) in ambient air is responsible for adverse health effects in adults and children. Relatively little is known about the concentrations, sources and health effects of PM in indoor air. A monitoring study was conducted in Ankara by three campaigns in order to measure PM levels in indoor and outdoor environments to identify and quantify associations between sources and concentrations. Approximately 82 homes (1st campaign for 42, 2nd campaign for 12, and 3rd campaign for 28), three rooms (living room, baby-s room and living room used as a baby-s room) and outdoor ambient at each home were sampled with Grimm Environmental Dust Monitoring (EDM) 107, during different seasonal periods of 2011 and 2012. In this study, the relationship between indoor and outdoor PM levels for particulate matter less than 10 micrometer (.m) (PM10), particulate matter less than 2.5.m (PM2.5) and particulate matter less than 1.0.m (PM1) were investigated. The mean concentration of PM10, PM2.5, and PM1.0 at living room used as baby-s room is higher than living and baby-s room (or bedroom) for three sampling campaigns. It is concluded that the household activities and environmental conditions are very important for PM concentrations in the indoor environments during the sampling periods. The amount of smokers, being near a main street and/or construction activities increased the PM concentration. This study is based on the assessment the relationship between indoor and outdoor PM levels and the household activities and environmental conditions

Keywords: Indoor air quality, particulate matter (PM), PM10, PM2.5, PM1.0.

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