Search results for: service based environment.

Authors: M. Chaichanyut, S. Tungjitkusolmun

Abstract:

This paper is concerned with microwave (MW) ablation for a liver cancer tissue by using helix antenna. The antenna structure supports the propagation of microwave energy at 2.45 GHz. A 1½ turn spiral catheter-based microwave antenna applicator has been developed. We utilize the three-dimensional finite element method (3D FEM) simulation to analyze where the tissue heat flux, lesion pattern and volume destruction during MW ablation. The configurations of helix antenna where Helix air-core antenna and Helix Dielectric-core antenna. The 3D FEMs solutions were based on Maxwell and bio-heat equations. The simulation protocol was power control (10 W, 300s). Our simulation result, both helix antennas have heat flux occurred around the helix antenna and that can be induced the temperature distribution similar (teardrop). The region where the temperature exceeds 50°C the microwave ablation was successful (i.e. complete destruction). The Helix air-core antenna and Helix Dielectric-core antenna, ablation zone or axial ratios (Widest/length) were respectively 0.82 and 0.85; the complete destructions were respectively 4.18 cm³ and 5.64 cm³

Keywords: Liver cancer, Helix antenna, Finite element, Microwave ablation.

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Authors: Nada Azhar

Abstract:

This paper is drawn from a wider study of the management of gender, age and disability diversity in the banking sector in the Kingdom of Saudi Arabia (KSA), which aims to develop a framework for diversity management (DM) in this sector. The paper focuses on the management of disability diversity. The purpose of the paper is to assist in understanding disability DM in the banking sector in KSA and to make suggestions for its enhancement. Hence, it contributes to filling a research gap, as there is a dearth of literature on disability DM, in KSA in general, and in the banking sector specifically. Discrimination against people with disabilities is a social issue that has not been entirely overcome in any society. However, in KSA, Islam informs almost every aspect of daily life including work, and Islam is against discrimination. Hence, in KSA, there are regulations to accommodate people with disabilities; however, employers are still free not to hire job applicants with disabilities specifically because of their condition. Indeed, disabled people are almost entirely absent from the labour market. There are 12 Saudi-owned or part-Saudi-owned banks in KSA and two managers from each of these were interviewed, making a total of 24. The interviews aimed to investigate empirically the understanding of managers in the banking sector in KSA of diversity management, including disability DM, in the banking sector. The interview data were analysed using thematic analysis. Two interviewees stated that banks used the employment of people with disabilities to enhance their corporate image, while five expressed the opinion that disabled employees could contribute to the bank provided they did not have to deal with customers face-to-face. Nine of the interviewees perceived that disabled employees could be of value to the bank for their own sake, not only in ‘behind the scenes’ roles. Another two interviewees mentioned that employing disabled people could be part of the bank’s community service programme and one thought it would be part of the bank’s Saudisation efforts. The remaining five interviewees did not know how disabled people could contribute to the bank. The findings show that disability DM in the banking sector in KSA is a relatively new concept, and is not yet well understood. In the light of the findings, in order to achieve the purpose of the paper, the following suggestions were made for the enhancement of disability DM in the banking sector in KSA. A change in attitudes towards disabled people is necessary. Such a change in the workplace can only be achieved if a top-down approach is taken to the integration of disabled people. Hence, it is suggested that management and employees follow a course in disability awareness. Further, a diversity officer in the HR department could enhance the integration of disabled people into the banking workforce. It is also suggested that greater government support is required through closely monitored and enforced anti-discrimination legislation. Moreover, flexible working arrangements such as part-time work would facilitate the employment of disabled people and benefit other groups of employees.

Keywords: Banking, disability, diversity management, Kingdom of Saudi Arabia.

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Authors: Ling Ai Wong, Hussain Shareef, Azah Mohamed, Ahmad Asrul Ibrahim

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The installation of photovoltaic based distributed generation (PVDG) in active distribution system can lead to voltage fluctuation due to the intermittent and unpredictable PVDG output power. This paper presented a method in mitigating the voltage rise by optimally locating and sizing the battery energy storage system (BESS) in PVDG integrated distribution network. The improved firefly algorithm is used to perform optimal placement and sizing. Three objective functions are presented considering the voltage deviation and BESS off-time with state of charge as the constraint. The performance of the proposed method is compared with another optimization method such as the original firefly algorithm and gravitational search algorithm. Simulation results show that the proposed optimum BESS location and size improve the voltage stability.

Keywords: BESS, PVDG, firefly algorithm, voltage fluctuation.

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Authors: Mohamed Abdallah, Mostafa Warith, Roberto Narbaitz, Emil Petriu, Kevin Kennedy

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Heterogeneity of solid waste characteristics as well as the complex processes taking place within the landfill ecosystem motivated the implementation of soft computing methodologies such as artificial neural networks (ANN), fuzzy logic (FL), and their combination. The present work uses a hybrid ANN-FL model that employs knowledge-based FL to describe the process qualitatively and implements the learning algorithm of ANN to optimize model parameters. The model was developed to simulate and predict the landfill gas production at a given time based on operational parameters. The experimental data used were compiled from lab-scale experiment that involved various operating scenarios. The developed model was validated and statistically analyzed using F-test, linear regression between actual and predicted data, and mean squared error measures. Overall, the simulated landfill gas production rates demonstrated reasonable agreement with actual data. The discussion focused on the effect of the size of training datasets and number of training epochs.

Keywords: Adaptive neural fuzzy inference system (ANFIS), gas production, landfill

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Authors: Ime R. Udotong, Justina I. R. Udotong, Ofonime U. M. John

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Ibeno, Nigeria hosts the operational base of Mobil Producing Nigeria Unlimited (MPNU), a subsidiary of ExxonMobil and the current highest oil & condensate producer in Nigeria. Besides MPNU, other oil companies operate onshore, on the continental shelf and deep offshore of the Atlantic Ocean in Ibeno, Nigeria. This study was designed to delineate oil polluted sites in Ibeno, Nigeria using geophysical methods of electrical resistivity (ER) and ground penetrating radar (GPR). Results obtained revealed that there have been hydrocarbon contaminations of this environment by past crude oil spills as observed from high resistivity values and GPR profiles which clearly show the distribution, thickness and lateral extent of hydrocarbon contamination as represented on the radargram reflector tones. Contaminations were of varying degrees, ranging from slight to high, indicating levels of substantial attenuation of crude oil contamination over time. Moreover, the display of relatively lower resistivities of locations outside the impacted areas compared to resistivity values within the impacted areas and the 3-D Cartesian images of oil contaminant plume depicted by red, light brown and magenta for high, low and very low oil impacted areas, respectively confirmed significant recent pollution of the study area with crude oil.

Keywords: Electrical resistivity, geophysical investigations, ground penetrating radar, oil-polluted sites.

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Authors: Karim Sobh, Khaled El-Ayat, Fady Morcos, Amr El-Kadi

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Distributed applications deployed on LEO satellites and ground stations require substantial communication between different members in a constellation to overcome the earth coverage barriers imposed by GEOs. Applications running on LEO constellations suffer the earth line-of-sight blockage effect. They need adequate lab testing before launching to space. We propose a scalable cloud-based network simulation framework to simulate problems created by the earth line-of-sight blockage. The framework utilized cloud IaaS virtual machines to simulate LEO satellites and ground stations distributed software. A factorial ANOVA statistical analysis is conducted to measure simulator overhead on overall communication performance. The results showed a very low simulator communication overhead. Consequently, the simulation framework is proposed as a candidate for testing LEO constellations with distributed software in the lab before space launch.

Keywords: LEO, Cloud Computing, Constellation, Satellite, Network Simulation, Netfilter.

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Authors: Majid Yazdandoust

Abstract:

This study, tries to suggest a design method based on displacement using finite difference numerical modeling in reinforcing soil retaining wall with steel strip. In this case, dynamic loading characteristics such as duration, frequency, peak ground acceleration, geometrical characteristics of reinforced soil structure and type of the site are considered to correct the pseudo static method and finally introduce the pseudo static coefficient as a function of seismic performance level and peak ground acceleration. For this purpose, the influence of dynamic loading characteristics, reinforcement length, height of reinforced system and type of the site are investigated on seismic behavior of reinforcing soil retaining wall with steel strip. Numerical results illustrate that the seismic response of this type of wall is highly dependent to cumulative absolute velocity, maximum acceleration, and height and reinforcement length so that the reinforcement length can be introduced as the main factor in shape of failure. Considering the loading parameters, geometric parameters of the wall and type of the site showed that the used method in this study leads to efficient designs in comparison with other methods, which are usually based on limit-equilibrium concept. The outputs show the over-estimation of equilibrium design methods in comparison with proposed displacement based methods here.

Keywords: Pseudo static coefficient, seismic performance design, numerical modeling, steel strip reinforcement, retaining walls, cumulative absolute velocity, failure shape.

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Authors: P.-W. Tsai, C.-Y. Chen, C.-W. Chen

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In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking performance inequality for the control system. The tracking problem is characterized to solve an eigenvalue problem (EVP). Next, an adaptive fuzzy sliding model controller (AFSMC) is proposed to stabilize the system so as to achieve good control performance. Lyapunov’s direct method can be used to ensure the stability of the nonlinear system. It is shown that the stability analysis can reduce nonlinear systems into a linear matrix inequality (LMI) problem. Finally, a numerical simulation is provided to demonstrate the control methodology.

Keywords: Adaptive fuzzy sliding mode control, Lyapunov direct method, swarm intelligence, evolved bat algorithm.

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Authors: D. Maneetham, L. Sivhour

Abstract:

Robotic arm manipulators are widely used to accomplish many kinds of tasks. SCORBOT-ER 4u is a 5-degree of freedom (DOF) vertical articulated educational robotic arm, and all joints are revolute. It is specifically designed to perform pick and place task with its gripper. The pick and place task consists of consideration of the end effector coordinate of the robotic arm and the desired position coordinate in its workspace. This paper describes about forward kinematics modeling and analysis of the robotic end effector motion through joint space. The kinematics problems are defined by the transformation from the Cartesian space to the joint space. Denavit-Hartenberg (D-H) model is used in order to model the robotic links and joints with 4x4 homogeneous matrix. The forward kinematics model is also developed and simulated in MATLAB. The mathematical model is validated by using robotic toolbox in MATLAB. By using this method, it may be applicable to get the end effector coordinate of this robotic arm and other similar types to this arm. The software development of SCORBOT-ER 4u is also described here. PC-and EtherCAT based control technology from BECKHOFF is used to control the arm to express the pick and place task.

Keywords: Forward kinematics, D-H model, robotic toolbox, PC-and EtherCAT based control.

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Authors: D. Plikynas, S. Masteika, A. Budrionis

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This interdisciplinary research aims to distinguish universal scale-free and field-like fundamental principles of selforganization observable across many disciplines like computer science, neuroscience, microbiology, social science, etc. Based on these universal principles we provide basic premises and postulates for designing holistic social simulation models. We also introduce pervasive information field (PIF) concept, which serves as a simulation media for contextual information storage, dynamic distribution and organization in social complex networks. PIF concept specifically is targeted for field-like uncoupled and indirect interactions among social agents capable of affecting and perceiving broadcasted contextual information. Proposed approach is expressive enough to represent contextual broadcasted information in a form locally accessible and immediately usable by network agents. This paper gives some prospective vision how system-s resources (tangible and intangible) could be simulated as oscillating processes immersed in the all pervasive information field.

Keywords: field-based coordination, multi-agent systems, information-rich social networks, pervasive information field

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Authors: Ramin Mirzada, Takuya Maruyama

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Kabul is the heart of political, commercial, cultural, educational and social life in Afghanistan and the fifth fastest growing city in the world. Minimum income inclined most of Kabul residents to use public transport, especially buses, although there is no proper bus system, beside that there is no proper fare exist in Kabul city Due to wars. From 1992 to 2001 during civil wars, Kabul suffered damage and destruction of its transportation facilities including pavements, sidewalks, traffic circles, drainage systems, traffic signs and signals, trolleybuses and almost all of the public transport system (e.g. Millie bus). This research is mainly focused on Kabul city’s transportation system. In this research, the data used have been gathered by Japan International Cooperation Agency (JICA) in 2008 and this data will be used to find demand and fare structure, additionally a survey was done in 2016 to find satisfaction level of Kabul residents for fare structure. Aim of this research is to observe the demand for Large Buses, compare to the actual supply from the government, analyze the current fare structure and compare it with the proposed fare (distance based fare) structure which has already been analyzed. Outcome of this research shows that the demand of Kabul city residents for the public transport (Large Buses) exceeds from the current supply, so that current public transportation (Large Buses) is not sufficient to serve public transport in Kabul city, worth to be mentioned, that in order to overcome this problem, there is no need to build new roads or exclusive way for buses. This research proposes government to change the fare from fixed fare to distance based fare, invest on public transportation and increase the number of large buses so that the current demand for public transport is met.

Keywords: Transportation, planning, public transport, large buses, fixed fare, distance based fare, Kabul, Afghanistan.

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Authors: M. D. Haneef, R. B. Randall, Z. Peng

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Journal bearings used in IC engines are prone to premature failures and are likely to fail earlier than the rated life due to highly impulsive and unstable operating conditions and frequent starts/stops. Vibration signature extraction and wear debris analysis techniques are prevalent in industry for condition monitoring of rotary machinery. However, both techniques involve a great deal of technical expertise, time, and cost. Limited literature is available on the application of these techniques for fault detection in reciprocating machinery, due to the complex nature of impact forces that confounds the extraction of fault signals for vibration-based analysis and wear prediction. In present study, a simulation model was developed to investigate the bearing wear behaviour, resulting because of different operating conditions, to complement the vibration analysis. In current simulation, the dynamics of the engine was established first, based on which the hydrodynamic journal bearing forces were evaluated by numerical solution of the Reynold’s equation. In addition, the essential outputs of interest in this study, critical to determine wear rates are the tangential velocity and oil film thickness between the journals and bearing sleeve, which if not maintained appropriately, have a detrimental effect on the bearing performance. Archard’s wear prediction model was used in the simulation to calculate the wear rate of bearings with specific location information as all determinative parameters were obtained with reference to crank rotation. Oil film thickness obtained from the model was used as a criterion to determine if the lubrication is sufficient to prevent contact between the journal and bearing thus causing accelerated wear. A limiting value of 1 μm was used as the minimum oil film thickness needed to prevent contact. The increased wear rate with growing severity of operating conditions is analogous and comparable to the rise in amplitude of the squared envelope of the referenced vibration signals. Thus on one hand, the developed model demonstrated its capability to explain wear behaviour and on the other hand it also helps to establish a co-relation between wear based and vibration based analysis. Therefore, the model provides a cost effective and quick approach to predict the impending wear in IC engine bearings under various operating conditions.

Keywords: Condition monitoring, IC engine, journal bearings, vibration analysis, wear prediction.

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Authors: Edward Guillén, Jeisson Sánchez, Carlos Omar Ramos

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In recent years, a wide variety of applications are developed with Support Vector Machines -SVM- methods and Artificial Neural Networks -ANN-. In general, these methods depend on intrusion knowledge databases such as KDD99, ISCX, and CAIDA among others. New classes of detectors are generated by machine learning techniques, trained and tested over network databases. Thereafter, detectors are employed to detect anomalies in network communication scenarios according to user’s connections behavior. The first detector based on training dataset is deployed in different real-world networks with mobile and non-mobile devices to analyze the performance and accuracy over static detection. The vulnerabilities are based on previous work in telemedicine apps that were developed on the research group. This paper presents the differences on detections results between some network scenarios by applying traditional detectors deployed with artificial neural networks and support vector machines.

Keywords: Anomaly detection, back-propagation neural networks, network intrusion detection systems, support vector machines.

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Authors: G. Rajesh, B. Vinayaga Sundaram, C. Aarthi

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In wireless sensor network, sensor node transmits the sensed data to the sink node in multi-hop communication periodically. This high traffic induces congestion at the node which is present one-hop distance to the sink node. The packet transmission and reception rate of these nodes should be very high, when compared to other sensor nodes in the network. Therefore, the energy consumption of that node is very high and this effect is known as the “funneling effect”. The tree based-data aggregation technique (TBDA) is used to reduce the energy consumption of the node. The throughput of the overall performance shows a considerable decrease in the number of packet transmissions to the sink node. The proposed scheme, TBDA, avoids the funneling effect and extends the lifetime of the wireless sensor network. The average case time complexity for inserting the node in the tree is O(n log n) and for the worst case time complexity is O(n2).

Keywords: Data Aggregation, Funneling Effect, Traffic Congestion, Wireless Sensor Network.

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Authors: Arash Esmaeili, Zhibang Liu, Yang Xiang, Jimmy Yun, Lei Shao

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A high pressure carbon dioxide (CO₂) absorption from a specific gas in a conventional column has been evaluated by the Aspen HYSYS simulator using a wide range of single absorbents and blended solutions to estimate the outlet CO₂ concentration, absorption efficiency and CO₂ loading to choose the most proper solution in terms of CO₂ capture for environmental concerns. The property package (Acid Gas-Chemical Solvent) which is compatible with all applied solutions for the simulation in this study, estimates the properties based on an electrolyte non-random two-liquid (E-NRTL) model for electrolyte thermodynamics and Peng-Robinson equation of state for the vapor and liquid hydrocarbon phases. Among all the investigated single amines as well as blended solutions, piperazine (PZ) and the mixture of piperazine and monoethanolamine (MEA) have been found as the most effective absorbents respectively for CO₂ absorption with high reactivity based on the simulated operational conditions.

Keywords: Absorption, amine solutions, Aspen HYSYS, carbon dioxide, simulation.

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Authors: Ali Asadian, Behzad Moshiri, Ali Khaki Sedigh, Caro Lucas

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Most integrated inertial navigation systems (INS) and global positioning systems (GPS) have been implemented using the Kalman filtering technique with its drawbacks related to the need for predefined INS error model and observability of at least four satellites. Most recently, a method using a hybrid-adaptive network based fuzzy inference system (ANFIS) has been proposed which is trained during the availability of GPS signal to map the error between the GPS and the INS. Then it will be used to predict the error of the INS position components during GPS signal blockage. This paper introduces a genetic optimization algorithm that is used to update the ANFIS parameters with respect to the INS/GPS error function used as the objective function to be minimized. The results demonstrate the advantages of the genetically optimized ANFIS for INS/GPS integration in comparison with conventional ANFIS specially in the cases of satellites- outages. Coping with this problem plays an important role in assessment of the fusion approach in land navigation.

Keywords: Adaptive Network based Fuzzy Inference System (ANFIS), Genetic optimization, Global Positioning System (GPS), Inertial Navigation System (INS).

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Authors: M. Geetha Priya, D. Krishnaveni

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Snow depth estimation and monitoring studies have been carried out for decades using empirical relationship or extrapolation of point measurements carried out in field. With the development of advanced satellite based remote sensing techniques, a modified approach is proposed in the present study to estimate the winter accumulated snow depth at basin scale. Assessment of snow depth by differencing Digital Elevation Model (DEM) generated at the beginning and end of winter season can be experimented for the region of interest (Himalayan and polar regions) accounting for winter accumulation (solid precipitation). The proposed approach is based on existing geodetic method that is being used for glacier mass balance estimation. Considering the satellite datasets purely acquired during beginning and end of winter season, it is possible to estimate the change in depth or thickness for the snow that is accumulated during the winter as it takes one year for the snow to get transformed into firn (snow that has survived one summer or one-year old snow).

Keywords: Digital elevation model, snow depth, geodetic method, snow cover.

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Authors: Kai-Ying A. Chan, Leon A.G. Oerlemans, Marthinus W. Pretorius

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Science parks are often established to drive regional economic growth, especially in countries with emerging economies. However, mixed findings regarding the performances of science park firms are found in the literature. This study tries to explain these mixed findings by taking a relational approach and exploring (un)intended knowledge transfers between new technology-based firms (NTBFs) in the emerging South African economy. Moreover, the innovation outcomes of these NTBFs are examined by using a multi-dimensional construct. Results show that science park location plays a significant role in explaining innovative sales, but is insignificant when a different indicator of innovation outcomes is used. Furthermore, only for innovations that are new to the firms, both science park location and intended knowledge transfer via informal business relationships have a positive impact; whereas social relationships have a negative impact.

Keywords: knowledge flows, innovative performances, science parks, new technology-based firms

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Authors: W. Walke, J. Przondziono, K. Nowińska

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The study comprises evaluation of suitability of passive layer created on the surface of AISI 316L stainless steel for products that are intended to have contact with blood. For that purpose, prior to and after chemical passivation, samples were subject to 7 day exposure in artificial plasma at the temperature of T=37°C. Next, tests of metallic ions infiltration from the surface to the solution were performed. The tests were performed with application of spectrometer JY 2000, by Yobin – Yvon, employing Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES). In order to characterize physical and chemical features of electrochemical processes taking place during exposure of samples to artificial plasma, tests with application of electrochemical impedance spectroscopy were suggested. The tests were performed with application of measuring unit equipped with potentiostat PGSTAT 302n with an attachment for impedance tests FRA2. Measurements were made in the environment simulating human blood at the temperature of T=37°C. Performed tests proved that application of chemical passivation process for AISI 316L stainless steel used for production of goods intended to have contact with blood is well-grounded and useful in order to improve safety of their usage.

Keywords: AISI 316L stainless steel, chemical passivation, artificial plasma, ions infiltration, EIS.

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Authors: Arnab Majumdar, Srimani Sen

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In this paper, a vivid simulated study has been made on 35 GHz Ka-band window frequency in order to judge and compare the DC and high frequency properties of cubic ZnB-GaN with the existing hexagonal 4H-SiC. A flat profile p⁺pnn⁺ DDR structure of impatt is chosen and is optimized at a particular bias current density with respect to efficiency and output power taking into consideration the effect of mobile space charge also. The simulated results obtained reveals the strong potentiality of impatts based on both cubic ZnB-GaN and hexagonal 4H-SiC. The DC-to-millimeter wave conversion efficiency for cubic ZnB-GaN impatt obtained is 50% with an estimated output power of 2.83 W at an optimized bias current density of 2.5×10⁸ A/m². The conversion efficiency and estimated output power in case of hexagonal 4H-SiC impatt obtained is 22.34% and 40 W respectively at an optimum bias current density of 0.06×10⁸ A/m².

Keywords: Cubic ZnB-GaN, hexagonal 4H-SiC, Double drift impatt diode, millimeter wave, optimized bias current density, wide band gap semiconductor.

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Authors: A. J. Otjen

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Native American communities are struggling with unemployment and depressed economies. A major cause is a lack of business knowledge, education, and cultural desire. And yet, in the history of the American West, Native Americans were considered the best traders and negotiators for everything from furs to weapons to buffalo. To improve these economies, there has been an effort to reintroduce that heritage to todays and tomorrows generation of tribal members, such Crow, Cheyenne, and Blackfeet. Professors at the College of Business Montana State University-Billings (MSUB) teach tribal students in Montana to create business plans. These plans have won national small business plan competitions. The teaching and advising method used at MSUB is uniquely successful as theses business students are now five time national champions. This article reviews the environment and the method of learning to achieve a winning small business plan with Native American students. It discusses the five plans that became national champions. And it discusses the problems and solutions discovered in the process of achieving results. Students who participated in this endeavor have graduated and become CPAs, MBAs, and gainfully employed in their chosen professions. They have also worked to improve the economies of their native lands and homes. By educating members of these communities with business strategy and plan development, they are better able to impact their own economies.

Keywords: Entrepreneurship, Native Americans economies, small businesses.

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Authors: Ball J., Capanni N., Watt S.

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This paper argues that fostering mutual understanding in landscape planning is as much about the planners educating stakeholder groups as the stakeholders educating the planners. In other words it is an epistemological agreement as to the meaning and nature of place, especially where an effort is made to go beyond the quantitative aspects, which can be achieved by the phenomenological experience of the Virtual Reality (VR) environment. This education needs to be a bi-directional process in which distance can be both temporal as well as spatial separation of participants, that there needs to be a common framework of understanding in which neither 'side' is disadvantaged during the process of information exchange and it follows that a medium such as VR offers an effective way of overcoming some of the shortcomings of traditional media by taking advantage of continuing technological advances in Information, Technology and Communications (ITC). In this paper we make particular reference to this as an extension to Geographical Information Systems (GIS). VR as a two-way communication tool offers considerable potential particularly in the area of Public Participation GIS (PPGIS). Information rich virtual environments that can operate over broadband networks are now possible and thus allow for the representation of large amounts of qualitative and quantitative information 'side-by-side'. Therefore, with broadband access becoming standard for households and enterprises alike, distributed virtual reality environments have great potential to contribute to enabling stakeholder participation and mutual learning within the planning context.

Keywords: 3D, communication, geographical information systems, planning, public participation, virtual reality, visualisation.

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Authors: Prakash Singh

Abstract:

The aim of this study was to investigate the extent of teachers’ experiences of tobephobia (TBP) in their heterogeneous classrooms and what impact this had on their emotions and job satisfaction. The expansive and continuously changing demands for quality and equal education for all students in educational organisations that have limited resources connotes that the negative effects of TBP cannot be simply ignored as being non-existent in the educational environment. As this quantitative study reveals, teachers disliking their job with low expectations, lack of motivation in their workplace and pessimism, result in their low self-esteem. When there is pessimism in the workplace, then the employees’ self-esteem will inevitably be low, as pointed out by 97.1% of the respondents in this study. Self-esteem is a reliable indicator of whether employees are happy or not in their jobs and the majority of the respondents in this study agreed that their experiences of TBP negatively impacted on their self-esteem. Hence, this exploratory study strongly indicates that productivity in the workplace is directly linked to the employees’ expectations, self-confidence and their self-esteem. It is therefore inconceivable for teachers to be productive in their regular classrooms if their genuine professional concerns, anxieties, and curriculum challenges are not adequately addressed. This empirical study contributes to our knowledge on TBP because it clearly outlines some of the teaching problems that we are grappling with and constantly experience in our schools in this century. Therefore, it is imperative that the tobephobic experiences of teachers are not merely documented, but appropriately addressed with relevant action by every stakeholder associated with education so that our teachers’ emotions and job satisfaction needs are fully taken care of.

Keywords: Demotivated teachers’ pessimism, low expectations of teachers’ job satisfaction, Self-esteem, Tobephobia.

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Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

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Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: Malaria, deep learning, DL, convolution neural network, CNN, thin blood smears.

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Authors: A. Preetha Priyadharshini, S. B. M. Priya

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In this paper, we consider the MU-MISO downlink scenario, under imperfect channel state information (CSI). The main issue in imperfect CSI is to keep the probability of each user achievable outage rate below the given threshold level. Such a rate outage constraints present significant and analytical challenges. There are many probabilistic methods are used to minimize the transmit optimization problem under imperfect CSI. Here, decomposition based large deviation inequality and Bernstein type inequality convex restriction methods are used to perform the optimization problem under imperfect CSI. These methods are used for achieving improved output quality and lower complexity. They provide a safe tractable approximation of the original rate outage constraints. Based on these method implementations, performance has been evaluated in the terms of feasible rate and average transmission power. The simulation results are shown that all the two methods offer significantly improved outage quality and lower computational complexity.

Keywords: Imperfect channel state information, outage probability, multiuser- multi input single output.

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Authors: Madhuri Bhavsar, Anupam K Singh, Shrikant Pradhan

Abstract:

Long term rainfall analysis and prediction is a challenging task especially in the modern world where the impact of global warming is creating complications in environmental issues. These factors which are data intensive require high performance computational modeling for accurate prediction. This research paper describes a prototype which is designed and developed on grid environment using a number of coupled software infrastructural building blocks. This grid enabled system provides the demanding computational power, efficiency, resources, user-friendly interface, secured job submission and high throughput. The results obtained using sequential execution and grid enabled execution shows that computational performance has enhanced among 36% to 75%, for decade of climate parameters. Large variation in performance can be attributed to varying degree of computational resources available for job execution. Grid Computing enables the dynamic runtime selection, sharing and aggregation of distributed and autonomous resources which plays an important role not only in business, but also in scientific implications and social surroundings. This research paper attempts to explore the grid enabled computing capabilities on weather indices from HOAPS data for climate impact modeling and change detection.

Keywords: Climate model, Computational Grid, GridApplication, Heterogeneous Grid

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Authors: Arturo Aquino, Manuel Emilio Gegundez, Jose Manuel Bravo, Diego Marin

Abstract:

Retinal vascularity assessment plays an important role in diagnosis of ophthalmic pathologies. The employment of digital images for this purpose makes possible a computerized approach and has motivated development of many methods for automated vascular tree segmentation. Metrics based on contingency tables for binary classification have been widely used for evaluating performance of these algorithms and, concretely, the accuracy has been mostly used as measure of global performance in this topic. However, this metric shows very poor matching with human perception as well as other notable deficiencies. Here, a new similarity function for measuring quality of retinal vessel segmentations is proposed. This similarity function is based on characterizing the vascular tree as a connected structure with a measurable area and length. Tests made indicate that this new approach shows better behaviour than the current one does. Generalizing, this concept of measuring descriptive properties may be used for designing functions for measuring more successfully segmentation quality of other complex structures.

Keywords: Retinal vessel segmentation, quality assessment, performanceevaluation, similarity function.

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Authors: Abraham Varghese, Kannan Balakrishnan, Reji R. Varghese, Joseph S. Paul

Abstract:

Magnetic Resonance Imaging play a vital role in the decision-diagnosis process of brain MR images. For an accurate diagnosis of brain related problems, the experts mostly compares both T1 and T2 weighted images as the information presented in these two images are complementary. In this paper, rotational and translational invariant form of Local binary Pattern (LBP) with additional gray scale information is used to retrieve similar slices of T1 weighted images from T2 weighted images or vice versa. The incorporation of additional gray scale information on LBP can extract more local texture information. The accuracy of retrieval can be improved by extracting moment features of LBP and reweighting the features based on users feedback. Here retrieval is done in a single subject scenario where similar images of a particular subject at a particular level are retrieved, and multiple subjects scenario where relevant images at a particular level across the subjects are retrieved.

Keywords: Local Binary pattern (LBP), Modified Local Binary pattern (MOD-LBP), T1 and T2 weighted images, Moment features.

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Authors: Daniel Stamate

Abstract:

One of the most used assumptions in logic programming and deductive databases is the so-called Closed World Assumption (CWA), according to which the atoms that cannot be inferred from the programs are considered to be false (i.e. a pessimistic assumption). One of the most successful semantics of conventional logic programs based on the CWA is the well-founded semantics. However, the CWA is not applicable in all circumstances when information is handled. That is, the well-founded semantics, if conventionally defined, would behave inadequately in different cases. The solution we adopt in this paper is to extend the well-founded semantics in order for it to be based also on other assumptions. The basis of (default) negative information in the well-founded semantics is given by the so-called unfounded sets. We extend this concept by considering optimistic, pessimistic, skeptical and paraconsistent assumptions, used to complete missing information from a program. Our semantics, called extended well-founded semantics, expresses also imperfect information considered to be missing/incomplete, uncertain and/or inconsistent, by using bilattices as multivalued logics. We provide a method of computing the extended well-founded semantics and show that Kripke-Kleene semantics is captured by considering a skeptical assumption. We show also that the complexity of the computation of our semantics is polynomial time.

Keywords: Logic programs, imperfect information, multivalued logics, bilattices, assumptions.

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Authors: A. Belayadi, A. Mougari, L. Ait-Gougam, F. Mekideche-Chafa

Abstract:

The artificial neural network is one of the interesting techniques that have been advantageously used to deal with modeling problems. In this study, the computing with artificial neural network (CANN) is proposed. The model is applied to modulate the information processing of one-dimensional task. We aim to integrate a new method which is based on a new coding approach of generating the input-output mapping. The latter is based on increasing the neuron unit in the last layer. Accordingly, to show the efficiency of the approach under study, a comparison is made between the proposed method of generating the input-output set and the conventional method. The results illustrated that the increasing of the neuron units, in the last layer, allows to find the optimal network’s parameters that fit with the mapping data. Moreover, it permits to decrease the training time, during the computation process, which avoids the use of computers with high memory usage.

Keywords: Neural network computing, information processing, input-output mapping, training time, computers with high memory.

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