Search results for: mathematical framework

Authors: Rong Zhou, Shun’ich Kaneko, Fumio Tanaka, Miyuki Kayamori, Motoshige Shimizu

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In this paper, we propose a robust disease detection method, called adaptive orientation code matching (Adaptive OCM), which is developed from a robust image registration algorithm: orientation code matching (OCM), to achieve continuous and site-specific detection of changes in plant disease. We use two-stage framework for realizing our research purpose; in the first stage, adaptive OCM was employed which could not only realize the continuous and site-specific observation of disease development, but also shows its excellent robustness for non-rigid plant object searching in scene illumination, translation, small rotation and occlusion changes and then in the second stage, a machine learning method of support vector machine (SVM) based on a feature of two dimensional (2D) xy-color histogram is further utilized for pixel-wise disease classification and quantification. The indoor experiment results demonstrate the feasibility and potential of our proposed algorithm, which could be implemented in real field situation for better observation of plant disease development.

Keywords: Cercospora Leaf Spot (CLS), Disease detection, Image processing, Orientation Code Matching (OCM), Support Vector Machine (SVM).

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Authors: Ashly Joseph, Jithu Paulose

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The increased usage of cloud computing has revolutionized the IT landscape, but it has also raised new security concerns. DevSecOps emerged as a way for tackling these difficulties by integrating security into the software development process. However, the rising complexity and sophistication of cyber threats need more advanced solutions. This paper looks into the usage of artificial intelligence (AI) techniques in the DevSecOps framework to increase cloud security. This study uses quantitative and qualitative techniques to assess the usefulness of AI approaches such as machine learning, natural language processing, and deep learning in reducing security issues. This paper thoroughly examines the symbiotic relationship between AI and DevSecOps, concentrating on how AI may be seamlessly integrated into the continuous integration and continuous delivery (CI/CD) pipeline, automated security testing, and real-time monitoring methods. The findings emphasize AI's huge potential to improve threat detection, risk assessment, and incident response skills. Furthermore, the paper examines the implications and challenges of using AI in DevSecOps workflows, considering factors like as scalability, interpretability, and adaptability. This paper adds to a better understanding of AI's revolutionary role in cloud security and provides valuable insights for practitioners and scholars in the field.

Keywords: Cloud Security, DevSecOps, Artificial Intelligence, AI, Machine Learning, Natural Language Processing, NLP, cybersecurity, AI-driven Security.

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Authors: M. Gooroochurn, D. Kerr, K. Bouazza-Marouf, M. Vloeberghs

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This paper presents the automated methods employed for extracting craniofacial landmarks in white light images as part of a registration framework designed to support three neurosurgical procedures. The intraoperative space is characterised by white light stereo imaging while the preoperative plan is performed on CT scans. The registration aims at aligning these two modalities to provide a calibrated environment to enable image-guided solutions. The neurosurgical procedures can then be carried out by mapping the entry and target points from CT space onto the patient-s space. The registration basis adopted consists of natural landmarks (eye corner and ear tragus). A 5mm accuracy is deemed sufficient for these three procedures and the validity of the selected registration basis in achieving this accuracy has been assessed by simulation studies. The registration protocol is briefly described, followed by a presentation of the automated techniques developed for the extraction of the craniofacial features and results obtained from tests on the AR and FERET databases. Since the three targeted neurosurgical procedures are routinely used for head injury management, the effect of bruised/swollen faces on the automated algorithms is assessed. A user-interactive method is proposed to deal with such unpredictable circumstances.

Keywords: Face Processing, Craniofacial Feature Extraction, Preoperative to Intraoperative Registration, Registration Basis.

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Authors: V.S.Kale, S.R.Bhide, P.P.Bedekar, G.V.K.Mohan

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The protection of parallel transmission lines has been a challenging task due to mutual coupling between the adjacent circuits of the line. This paper presents a novel scheme for detection and classification of faults on parallel transmission lines. The proposed approach uses combination of wavelet transform and neural network, to solve the problem. While wavelet transform is a powerful mathematical tool which can be employed as a fast and very effective means of analyzing power system transient signals, artificial neural network has a ability to classify non-linear relationship between measured signals by identifying different patterns of the associated signals. The proposed algorithm consists of time-frequency analysis of fault generated transients using wavelet transform, followed by pattern recognition using artificial neural network to identify the type of the fault. MATLAB/Simulink is used to generate fault signals and verify the correctness of the algorithm. The adaptive discrimination scheme is tested by simulating different types of fault and varying fault resistance, fault location and fault inception time, on a given power system model. The simulation results show that the proposed scheme for fault diagnosis is able to classify all the faults on the parallel transmission line rapidly and correctly.

Keywords: Artificial neural network, fault detection and classification, parallel transmission lines, wavelet transform.

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Authors: Gert Van Schalkwyk, Chris Cloete

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South Africa is experiencing a massive housing backlog in urban low-cost housing. A backlog in the transfer of low-cost housing units is exacerbated by various impediments and delays that exist in the current legal framework. Structured interviews were conducted with 45 practicing conveyancers and 15 deeds office examiners at the Deeds Office in Pretoria, South Africa. One of the largest, the Deeds Office in Pretoria implements a uniform registration process and can be regarded as representative of other deeds offices in South Africa. It was established that a low percentage of low-cost properties are freely transferable. The main economic impediments are the absence of financing and the affordability or payment of rates and taxes to local government. Encroachment of buildings on neighbouring stands caused by enlargement of existing small units on small stands also cause long-term unresolved legal disputes. In addition, as transfer of properties is dependent on the proper functioning of administrative functions of various government departments, the adverse service delivery of government departments hampers transfer. Addressing the identified problems will contribute to a more sustainable process for the transfer of low-cost housing units in South Africa.

Keywords: Conveyancing, low-cost housing, South Africa, tenure, transfer, titling.

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Authors: Deniz T. Sodiri, Venkat V S S Sastry

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The paper presents an on-line recognition machine (RM) for continuous/isolated, dynamic and static gestures that arise in Flight Deck Officer (FDO) training. RM is based on generic pattern recognition framework. Gestures are represented as templates using summary statistics. The proposed recognition algorithm exploits temporal and spatial characteristics of gestures via dynamic programming and Markovian process. The algorithm predicts corresponding index of incremental input data in the templates in an on-line mode. Accumulated consistency in the sequence of prediction provides a similarity measurement (Score) between input data and the templates. The algorithm provides an intuitive mechanism for automatic detection of start/end frames of continuous gestures. In the present paper, we consider isolated gestures. The performance of RM is evaluated using four datasets - artificial (W TTest), hand motion (Yang) and FDO (tracker, vision-based ). RM achieves comparable results which are in agreement with other on-line and off-line algorithms such as hidden Markov model (HMM) and dynamic time warping (DTW). The proposed algorithm has the additional advantage of providing timely feedback for training purposes.

Keywords: On-line Recognition Algorithm, IsolatedDynamic/Static Gesture Recognition, On-line Markovian/DynamicProgramming, Training in Virtual Environments.

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Authors: P. Chatrabhuti, S. Visessri, T. Charinpanitkul

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Precision irrigation (PI) technology has emerged as a solution to optimize water usage in agriculture, aiming to maximize crop yields while minimizing water waste. Developing a PI for commercialization requires developers to research, synthesize, evaluate, and select appropriate technologies and make use of such information to produce innovative products. The objective of this review is to facilitate innovators by providing them with a summary of existing knowledge and the identification of gaps in research linking to the innovative development of PI. This paper reviews and synthesizes technologies and components relevant to precision irrigation, highlighting its potential benefits and challenges. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) framework is used for the review. As a result of this review, the different technologies have limitations and may only be suitable for specific orchards or spatial settings. The current technologies are readily available in a range of options, from affordable controllers to high-performance systems that are both reliable and precise. Furthermore, the future prospects for incorporating artificial intelligence and machine learning techniques hold promise for advancing autonomous irrigation systems.

Keywords: Innovation synthesis, technology assessment, precision irrigation technologies, precision irrigation components, new product development.

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Authors: N. Basanta Singh, Sanjoy Deb, G. P Mishra, Subir Kumar Sarkar

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Carrier mobility has become the most important characteristic of high speed low dimensional devices. Due to development of very fast switching semiconductor devices, speed of computer and communication equipment has been increasing day by day and will continue to do so in future. As the response of any device depends on the carrier motion within the devices, extensive studies of carrier mobility in the devices has been established essential for the growth in the field of low dimensional devices. Small-signal ac transport of degenerate two-dimensional hot electrons in GaAs quantum wells is studied here incorporating deformation potential acoustic, polar optic and ionized impurity scattering in the framework of heated drifted Fermi-Dirac carrier distribution. Delta doping is considered in the calculations to investigate the effects of double delta doping on millimeter and submillimeter wave response of two dimensional hot electrons in GaAs nanostructures. The inclusion of delta doping is found to enhance considerably the two dimensional electron density which in turn improves the carrier mobility (both ac and dc) values in the GaAs quantum wells thereby providing scope of getting higher speed devices in future.

Keywords: Carrier mobility, Delta doping, Hot carriers, Quantum wells.

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Authors: Debabrata Das, Pankaj Dutta

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Along with forward supply chain organization needs to consider the impact of reverse logistics due to its economic advantage, social awareness and strict legislations. In this paper, we develop a system dynamics framework for a closed-loop supply chain with fuzzy demand and fuzzy collection rate by incorporating product exchange policy in forward channel and various recovery options in reverse channel. The uncertainty issues associated with acquisition and collection of used product have been quantified using possibility measures. In the simulation study, we analyze order variation at both retailer and distributor level and compare bullwhip effects of different logistics participants over time between the traditional forward supply chain and the closed-loop supply chain. Our results suggest that the integration of reverse logistics can reduce order variation and bullwhip effect of a closed-loop system. Finally, sensitivity analysis is performed to examine the impact of various parameters on recovery process and bullwhip effect.

Keywords: Bullwhip Effect, Fuzzy Possibility Measures, Reverse Supply Chain, System Dynamics.

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Authors: Marco Morini, Nicolandrea Calabrese, Dario Chello

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Despite the international commitment of Algeria towards the development of energy efficiency and renewable energy in the country, the internal energy demand has been continuously growing during the last decade due to the substantial increase of population and of living conditions, which in turn has led to an unprecedented expansion of the residential building sector. The RTB (Thermal Building Regulation) is the technical document that establishes the calculation framework for the thermal performance of buildings in Algeria, setting up minimum obligatory targets for the thermal performance of new buildings. An update of this regulation is due in the coming years and this paper discusses some proposals in this regard, with the aim to improve the energy efficiency of the building sector, particularly with regard to social housing. In particular, it proposes a methodology for drafting an energy performance label of new Algerian residential buildings, moving from the results of the thermal compliance verification and sizing of technical systems as defined in the RTB. Such an energy performance label – whose calculation method is briefly described in the paper – aims to raise citizens' awareness of the benefits of energy efficiency. It can represent the first step in a process of integrating technical installations into the calculation of the energy performance of buildings in Algeria.

Keywords: building, energy certification, energy efficiency, social housing, international cooperation, Mediterranean Region

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Authors: Vikas Tewari, Shivendra Tewari, K. R. Pardasani

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Calcium is a vital second messenger used in signal transduction. Calcium controls secretion, cell movement, muscular contraction, cell differentiation, ciliary beating and so on. Two theories have been used to simplify the system of reaction-diffusion equations of calcium into a single equation. One is excess buffer approximation (EBA) which assumes that mobile buffer is present in excess and cannot be saturated. The other is rapid buffer approximation (RBA), which assumes that calcium binding to buffer is rapid compared to calcium diffusion rate. In the present work, attempt has been made to develop a model for calcium diffusion under excess buffer approximation in neuron cells. This model incorporates the effect of [Na+] influx on [Ca2+] diffusion,variable calcium and sodium sources, sodium-calcium exchange protein, Sarcolemmal Calcium ATPase pump, sodium and calcium channels. The proposed mathematical model leads to a system of partial differential equations which have been solved numerically using Forward Time Centered Space (FTCS) approach. The numerical results have been used to study the relationships among different types of parameters such as buffer concentration, association rate, calcium permeability.

Keywords: Excess buffer approximation, Na+ influx, sodium calcium exchange protein, sarcolemmal calcium atpase pump, forward time centred space.

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Authors: Ahmed Kiani

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The United Arab Emirates is clearly facing a multitude of challenges in curbing its greenhouse gas emissions to meet its pre-allotted framework of Kyoto protocol and COP21 targets due to its hunger for modernization, industrialization, infrastructure growth, soaring population and oil and gas activity. In this work, we focus on the bonafide zero emission electric vehicles market penetration in the country’s transport industry for emission reduction. We study the global electric vehicle market trends, the complementary battery technologies and the trends by manufacturers, emission standards across borders and prioritized advancements which will ultimately dictate the terms of future conditions for the United Arab Emirate transport industry. Based on our findings and analysis at every stage of current viability and state-of-transport-affairs, we postulate policy recommendations to local governmental entities from a supply and demand perspective covering aspects of technology, infrastructure requirements, change in power dynamics, end user incentives program, market regulators behavior and communications amongst key stakeholders. 

Keywords: Electric vehicles, greenhouse gas emission reductions, market analysis, policy recommendations.

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Authors: Mansour N. Jadid

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This paper describes the implementation of a GIS to provide decision support for successfully monitoring the movements and storage of materials, hence ensuring that finished products travel from the point of origin to the destination construction site through the supply-chain management (SCM) system. This system ensures the efficient operation of suppliers, manufacturers, and distributors by determining the shortest path from the point of origin to the final destination to reduce construction costs, minimize time, and enhance productivity. These systems are essential to the construction industry because they reduce costs and save time, thereby improve productivity and effectiveness. This study describes a typical supply-chain model and a geographical information system (GIS)-based SCM that focuses on implementing an electronic document management system, which maps the application framework to integrate geodetic support with the supply-chain system. This process provides guidance for locating the nearest suppliers to fill the information needs of project members in different locations. Moreover, this study illustrates the use of a GIS-based SCM as a collaborative tool in innovative methods for implementing Web mapping services, as well as aspects of their integration by generating an interactive GIS for the construction industry platform.

Keywords: Construction, coordinate, engineering, GIS, management, map.

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Authors: Motlhale Judicial Sebatana, Washington Takawira Dudu

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This study investigated how one beginner Physical Sciences teacher implemented Problem-Based Learning (PBL) strategy in the teaching and learning of Particulate Nature of Matter (PNM) in the Grade 10 classroom. PBL was implemented to explore how it can promote a 21st-century skill of creativity and enhance understanding of PNM. This study was guided by theoretical framework of Social Interdependence Theory (SIT). This exploratory qualitative case study was conveniently conducted in the North West province, South Africa, where one Physical Sciences teacher was purposefully sampled. A self-developed open-ended questionnaire, portfolio and individual semi-structured interview were used as the methods of generating data for this study. The results show that the participant of this study had no prior knowledge of utilising PBL in the teaching and learning of PNM before the Teacher Professional Development (TPD) programme, no knowledge of creativity as a 21st-century skill, and a successful PBL implementation post TPD to promote creativity.

Keywords: Beginner teachers, physical sciences teachers, problem-based learning, 21st-century skills, creativity skill, particulate nature of matter.

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Authors: Chang-Guk Sun, Jin-Soo Shin

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In this study, an inland metropolitan area, Gwangju, in Korea was selected to assess the amplification potential of earthquake motion and provide the information for regional seismic countermeasure. A geographic information system-based expert system was implemented for reliably predicting the spatial geotechnical layers in the entire region of interesting by building a geo-knowledge database. Particularly, the database consists of the existing boring data gathered from the prior geotechnical projects and the surface geo-knowledge data acquired from the site visit. For practical application of the geo-knowledge database to estimate the earthquake hazard potential related to site amplification effects at the study area, seismic zoning maps on geotechnical parameters, such as the bedrock depth and the site period, were created within GIS framework. In addition, seismic zonation of site classification was also performed to determine the site amplification coefficients for seismic design at any site in the study area. KeywordsEarthquake hazard, geo-knowledge, geographic information system, seismic zonation, site period.

Keywords: Earthquake hazard, geo-knowledge, geographic information system, seismic zonation, site period.

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Authors: Worachat Wannawong, Chaiwat Ekkawatpanit, Sanit Wongsa

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Both prognostic and diagnostic modes of a 3D baroclinic model in hydrodynamic and sediment transport models of the Princeton Ocean Model (POM) were conducted to separate prognose and diagnose effects of different hydrodynamic factors on transport of suspended sediment discharged from the rivers to the Gulf of Thailand (GoT). Both transport modes of suspended sediment distribution in the GoT were numerically simulated. It could be concluded that the suspended sediment discharged from the rivers around the GoT. Most of sediments in estuaries and coastal areas are deposited outside the GoT under the condition of wind-driven current, and very small amount of the sediments of them are transported faraway. On the basis of wind forcing, sediments from the lower GoT to the upper GoT are mainly transported south-northwestward and also continuously moved north-southwestward. An obvious 3D characteristic of suspended sediment transport is produced in the wind-driven current residual circulation condition. In this study, the transport patterns at the third layer are generally consistent with the typhoon-induced strong currents in two case studies of Typhoon Linda 1997. The case studies presented the prognostic and diagnostic modes during 00UTC28OCT1997 to 12UTC06NOV1997 in a short period with the current condition for pre-operation of the suspended sediment transport model in estuaries and coastal areas.

Keywords: prognostic, diagnostic, baroclinic, sediment transport, estuaries.

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Authors: S. Bouharati, I. Bouharati, C. Benzidane, F. Alleg, M. Belmahdi

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Sensors possess several properties of physical measures. Whether devices that convert a sensed signal into an electrical signal, chemical sensors and biosensors, thus all these sensors can be considered as an interface between the physical and electrical equipment. The problem is the analysis of the multitudes of saved settings as input variables. However, they do not all have the same level of influence on the outputs. In order to identify the most sensitive parameters, those that can guide users in gathering information on the ground and in the process of model calibration and sensitivity analysis for the effect of each change made. Mathematical models used for processing become very complex. In this paper a fuzzy rule-based system is proposed as a solution for this problem. The system collects the available signals information from sensors. Moreover, the system allows the study of the influence of the various factors that take part in the decision system. Since its inception fuzzy set theory has been regarded as a formalism suitable to deal with the imprecision intrinsic to many problems. At the same time, fuzzy sets allow to use symbolic models. In this study an example was applied for resolving variety of physiological parameters that define human health state. The application system was done for medical diagnosis help. The inputs are the signals expressed the cardiovascular system parameters, blood pressure, Respiratory system paramsystem was done, it will be able to predict the state of patient according any input values.

Keywords: Sensors, Sensivity, fuzzy logic, analysis, physiological parameters, medical diagnosis.

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Authors: Fiasal Assiri, Joanna Wincenciak, David Morrison-Love

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With the rapid spread of the COVID-19 pandemic, the Saudi government suspended students from going to school to combat the outbreak. As e-learning was not applied at all in schools, online teaching and learning have been revived in Saudi Arabia by providing a new platform called ‘Madrasati’. The Decomposed Theory of Planned Behaviour (DTPB) is used to examine individuals’ intention behaviour in many fields. Nevertheless, the factors that affect teachers’ continuance intention of the Madrasati platform have not yet been investigated. The purpose of this paper is to present a conceptual model in light with DTPB. To enhance the predictability of the model, the study incorporates other variables including learning content quality and interactivity as sub-factors under the perceived usefulness, students and government influences under the subjective norms, and technical support and prior e-learning experience under the perceived behavioural control. The model will be further validated using a mixed methods approach. Such findings would help administrators and stakeholders to understand teachers’ needs and develop new methods that might encourage teachers to continue using Madrasati effectively in their teaching.

Keywords: Madrasati, Decomposed Theory of Planned Behaviour, continuance intention, attitude, subjective norms, perceived behavioural control.

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Authors: Shahadat Uddin, Md Ekramul Hossain, Arif Khan

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The collaboration among physicians during episodes of care for a hospitalised patient has a significant contribution towards effective health outcome. This research aims at improving this health outcome by analysing the attributes of patient-sharing physician collaboration network (PCN) on hospital data. To accomplish this goal, we present a research framework that explores the impact of several types of attributes (such as clique and clan) of PCN on hospitalisation cost and hospital length of stay. We use electronic health insurance claim dataset to construct and explore PCNs. Each PCN is categorised as ‘low’ and ‘high’ in terms of hospitalisation cost and length of stay. The results from the proposed model show that the clique and clan of PCNs affect the hospitalisation cost and length of stay. The clique and clan of PCNs show the difference between ‘low’ and ‘high’ PCNs in terms of hospitalisation cost and length of stay. The findings and insights from this research can potentially help the healthcare stakeholders to better formulate the policy in order to improve quality of care while reducing cost.

Keywords: Clique, clan, electronic health records, physician collaboration.

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Authors: Saeed Safari Dolatabad, Rajab Choukan

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Selection of maize (Zea mays) hybrids with wide adaptability across diverse farming environments is important, prior to recommending them to achieve a high rate of hybrid adoption. Grain yield of 14 maize hybrids, tested in a randomized completeblock design with four replicates across 22 environments in Iran, was analyzed using site regression (SREG) stability model. The biplot technique facilitates a visual evaluation of superior genotypes, which is useful for cultivar recommendation and mega-environment identification. The objectives of this study were (i) identification of suitable hybrids with both high mean performance and high stability (ii) to determine mega-environments for maize production in Iran. Biplot analysis identifies two mega-environments in this study. The first mega-environments included KRM, KSH, MGN, DZF A, KRJ, DRB, DZF B, SHZ B, and KHM, where G10 hybrid was the best performing hybrid. The second mega-environment included ESF B, ESF A, and SHZ A, where G4 hybrid was the best hybrid. According to the ideal-hybrid biplot, G10 hybrid was better than all other hybrids, followed by the G1 and G3 hybrids. These hybrids were identified as best hybrids that have high grain yield and high yield stability. GGE biplot analysis provided a framework for identifying the target testing locations that discriminates genotypes that are high yielding and stable.

Keywords: Zea mays L, GGE biplot, Multi-environment trials, Yield stability.

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Authors: Chiung-Hui Chen

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The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.

Keywords: Behavior, big data, hierarchical Hidden Markov Model, intelligent object.

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Authors: FH. Sarieddeen, R. El Berbari, S. Imad, J. Abdel Baki, M. Hamad, R. Blanc, A. Nakib, Y.Chenoune

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Brain ArterioVenous Malformation (BAVM) is an abnormal tangle of brain blood vessels where arteries shunt directly into veins with no intervening capillary bed which causes high pressure and hemorrhage risk. The success of treatment by embolization in interventional neuroradiology is highly dependent on the accuracy of the vessels visualization. In this paper the performance of clustering techniques on vessel segmentation from 3- D rotational angiography (3DRA) images is investigated and a new technique of segmentation is proposed. This method consists in: preprocessing step of image enhancement, then K-Means (KM), Fuzzy C-Means (FCM) and Expectation Maximization (EM) clustering are used to separate vessel pixels from background and artery pixels from vein pixels when possible. A post processing step of removing false-alarm components is applied before constructing a three-dimensional volume of the vessels. The proposed method was tested on six datasets along with a medical assessment of an expert. Obtained results showed encouraging segmentations.

Keywords: Brain arteriovenous malformation (BAVM), 3-D rotational angiography (3DRA), K-Means (KM) clustering, Fuzzy CMeans (FCM) clustering, Expectation Maximization (EM) clustering, volume rendering.

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Authors: Efthymios Chondrogiannis, Vassiliki Andronikou, Efstathios Karanastasis, Theodora Varvarigou

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A large amount of data is typically stored in relational databases (DB). The latter can efficiently handle user queries which intend to elicit the appropriate information from data sources. However, direct access and use of this data requires the end users to have an adequate technical background, while they should also cope with the internal data structure and values presented. Consequently the information retrieval is a quite difficult process even for IT or DB experts, taking into account the limited contributions of relational databases from the conceptual point of view. Ontologies enable users to formally describe a domain of knowledge in terms of concepts and relations among them and hence they can be used for unambiguously specifying the information captured by the relational database. However, accessing information residing in a database using ontologies is feasible, provided that the users are keen on using semantic web technologies. For enabling users form different disciplines to retrieve the appropriate data, the design of a Graphical User Interface is necessary. In this work, we will present an interactive, ontology-based, semantically enable web tool that can be used for information retrieval purposes. The tool is totally based on the ontological representation of underlying database schema while it provides a user friendly environment through which the users can graphically form and execute their queries.

Keywords: Ontologies, Relational Databases, SPARQL, Web Interface.

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Authors: Leila Vafajoo, Farhad Khorasheh, Mehrnoosh Hamzezadeh Nakhjavani, Moslem Fattahi

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In the present study, a procedure was developed to determine the optimum reaction rate constants in generalized Arrhenius form and optimized through the Nelder-Mead method. For this purpose, a comprehensive mathematical model of a fixed bed reactor for dehydrogenation of heavy paraffins over Pt–Sn/Al2O3 catalyst was developed. Utilizing appropriate kinetic rate expressions for the main dehydrogenation reaction as well as side reactions and catalyst deactivation, a detailed model for the radial flow reactor was obtained. The reactor model composed of a set of partial differential equations (PDE), ordinary differential equations (ODE) as well as algebraic equations all of which were solved numerically to determine variations in components- concentrations in term of mole percents as a function of time and reactor radius. It was demonstrated that most significant variations observed at the entrance of the bed and the initial olefin production obtained was rather high. The aforementioned method utilized a direct-search optimization algorithm along with the numerical solution of the governing differential equations. The usefulness and validity of the method was demonstrated by comparing the predicted values of the kinetic constants using the proposed method with a series of experimental values reported in the literature for different systems.

Keywords: Dehydrogenation, Pt-Sn/Al2O3 Catalyst, Modeling, Nelder-Mead, Optimization

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Authors: Kenneth M. Oba

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This study investigated factors affecting the price of cement in Nigeria, and developed a mathematical model that can predict future cement prices. Cement is key in the Nigerian construction industry. The changes in price caused by certain factors could affect economic and infrastructural development; hence there is need for proper proactive planning. Secondary data were collected from published information on cement between 2014 and 2019. In addition, questionnaires were sent to some domestic cement retailers in Port Harcourt in Nigeria, to obtain the actual prices of cement between the same periods. The study revealed that the most critical factors affecting the price of cement in Nigeria are inflation rate, population growth rate, and Gross Domestic Product (GDP) growth rate. With the use of data from United Nations, International Monetary Fund, and Central Bank of Nigeria databases, amongst others, a Multiple Linear Regression model was formulated. The model was used to predict the price of cement for 2020-2025. The model was then tested with 95% confidence level, using a two-tailed t-test and an F-test, resulting in an R² of 0.8428 and R² (adj.) of 0.6069. The results of the tests and the correlation factors confirm the model to be fit and adequate. This study will equip researchers and stakeholders in the construction industry with information for planning, monitoring, and management of present and future construction projects that involve the use of cement.

Keywords: Cement price, multiple linear regression model, Nigerian Construction Industry, price prediction.

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Authors: A. Doaa M. Atia, Faten H. Fahmy, Ninet M. Ahmed, Hassen T. Dorrah

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Temperature is one of the most principle factors affects aquaculture system. It can cause stress and mortality or superior environment for growth and reproduction. This paper presents the control of pond water temperature using artificial intelligence technique. The water temperature is very important parameter for shrimp growth. The required temperature for optimal growth is 34oC, if temperature increase up to 38oC it cause death of the shrimp, so it is important to control water temperature. Solar thermal water heating system is designed to supply an aquaculture pond with the required hot water in Mersa Matruh in Egypt. Neural networks are massively parallel processors that have the ability to learn patterns through a training experience. Because of this feature, they are often well suited for modeling complex and non-linear processes such as those commonly found in the heating system. Artificial neural network is proposed to control water temperature due to Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques. They have been used to solve complicated practical problems. Moreover this paper introduces a complete mathematical modeling and MATLAB SIMULINK model for the aquaculture system. The simulation results indicate that, the control unit success in keeping water temperature constant at the desired temperature by controlling the hot water flow rate.

Keywords: artificial neural networks, aquaculture, forced circulation hot water system,

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Authors: Thuy Thi Nguyen, Nguyen Dang Binh, Horst Bischof

Abstract:

In this work, we present a novel active learning approach for learning a visual object detection system. Our system is composed of an active learning mechanism as wrapper around a sub-algorithm which implement an online boosting-based learning object detector. In the core is a combination of a bootstrap procedure and a semi automatic learning process based on the online boosting procedure. The idea is to exploit the availability of classifier during learning to automatically label training samples and increasingly improves the classifier. This addresses the issue of reducing labeling effort meanwhile obtain better performance. In addition, we propose a verification process for further improvement of the classifier. The idea is to allow re-update on seen data during learning for stabilizing the detector. The main contribution of this empirical study is a demonstration that active learning based on an online boosting approach trained in this manner can achieve results comparable or even outperform a framework trained in conventional manner using much more labeling effort. Empirical experiments on challenging data set for specific object deteciton problems show the effectiveness of our approach.

Keywords: Computer vision, object detection, online boosting, active learning, labeling complexity.

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Authors: Zeineb Deymi-Gheriani

Abstract:

In the last two decades, one can clearly observe a boom of interest for e-learning and web-supported programs. However, one can also notice that many of these programs focus on the accumulation and delivery of content generally as a business industry with no much concern for theoretical underpinnings. The existing research, at least in online English language teaching (ELT), has demonstrated a lack of an effective online teaching pedagogy anchored in a well-defined theoretical framework. Hence, this paper comes as an attempt to present constructivism as one of the theoretical bases for the design of an effective online language teaching pedagogy which is at the same time technologically intelligent and theoretically informed to help envision how education can best take advantage of the information and communication technology (ICT) tools. The present paper discusses the key principles underlying constructivism, its implications for online language teaching design, as well as its limitations that should be avoided in the e-learning instructional design. Although the paper is theoretical in nature, essentially based on an extensive literature survey on constructivism, it does have practical illustrations from an action research conducted by the author both as an e-tutor of English using Moodle online educational platform at the Virtual University of Tunis (VUT) from 2007 up to 2010 and as a face-to-face (F2F) English teaching practitioner in the Professional Certificate of English Language Teaching Training (PCELT) at AMIDEAST, Tunisia (April-May, 2013).

Keywords: Active learning, constructivism, experiential learning, Piaget, Vygotsky.

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Authors: Stefan Menzel

Abstract:

As a result of the daily workflow in the design development departments of companies, databases containing huge numbers of 3D geometric models are generated. According to the given problem engineers create CAD drawings based on their design ideas and evaluate the performance of the resulting design, e.g. by computational simulations. Usually, new geometries are built either by utilizing and modifying sets of existing components or by adding single newly designed parts to a more complex design. The present paper addresses the two facets of acquiring components from large design databases automatically and providing a reasonable overview of the parts to the engineer. A unified framework based on the topographic non-negative matrix factorization (TNMF) is proposed which solves both aspects simultaneously. First, on a given database meaningful components are extracted into a parts-based representation in an unsupervised manner. Second, the extracted components are organized and visualized on square-lattice 2D maps. It is shown on the example of turbine-like geometries that these maps efficiently provide a wellstructured overview on the database content and, at the same time, define a measure for spatial similarity allowing an easy access and reuse of components in the process of design development.

Keywords: Design decomposition, topographic non-negative matrix factorization, parts-based representation, self-organization, unsupervised feature extraction.

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Authors: Wu Defu, Kiefer Chiam, Yang Kin Seng

Abstract:

The planning of geological survey works is an iterative process which involves planner, geologist, civil engineer and other stakeholders, who perform different roles and have different points of view. Traditionally, the team used paper maps or CAD drawings to present the proposal which is not an efficient way to present and share idea on the site investigation proposal such as sitting of borehole location or seismic survey lines. This paper focuses on how a GIS approach can be utilised to develop a webbased system to support decision making process in the planning of geological survey works and also to plan site activities carried out by Singapore Geological Office (SGO). The authors design a framework of building an interactive web-based GIS system, and develop a prototype, which enables the users to obtain rapidly existing geological information and also to plan interactively borehole locations and seismic survey lines via a web browser. This prototype system is used daily by SGO and has shown to be effective in increasing efficiency and productivity as the time taken in the planning of geological survey works is shortened. The prototype system has been developed using the ESRI ArcGIS API 3.7 for Flex which is based on the ArcGIS 10.2.1 platform.

Keywords: Engineering geology, Flex, Geological survey planning, Geoscience, GIS, Site investigation, WebGIS.

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