Search results for: adaptive radio resource allocation

Authors: Komeil Jahanifar, Zahra Abedi, Yaghob Zeraatkish

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This research was conducted for the first time at the southeastern coasts of the Caspian Sea in order to evaluate the performance of osteichthyes cooperatives through production (catch) function. Using one of the indirect valuation methods in this research, contributory factors in catch were identified and were inserted into the function as independent variables. In order to carry out this research, the performance of 25 Osteichthyes catching cooperatives in the utilization year of 2009 which were involved in fishing in Miankale wildlife refuge region. The contributory factors in catch were divided into groups of economic, ecological and biological factors. In the mentioned function, catch rate of the cooperative were inserted into as the dependant variable and fourteen partial variables in terms of nine general variables as independent variables. Finally, after function estimation, seven variables were rendered significant at 99 percent reliably level. The results of the function estimation indicated that human resource (fisherman quantity) had the greatest positive effect on catch rate with an influence coefficient of 1.7 while weather conditions had the greatest negative effect on the catch rate of cooperatives with an influence coefficient of -2.07. Moreover, factors like member's share, experience and fisherman training and fishing effort played the main roles in the catch rate of cooperative with influence coefficients of 0.81, 0.5 and 0.21, respectively.

Keywords: Production Function, Coefficient, Variable, Osteichthyes, Caspian Sea

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Authors: Hamed Zolfaghari, Mojtaba Kord

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Project planners and controllers are frequently faced with the challenge of inadequate software for the preparation of automatic project progress reports based on actual project information updates. They usually make dashboards in Microsoft Excel, which is local and not applicable online. Another shortcoming is that Microsoft project does not store the data in database, so the data cannot automatically be imported from Microsoft Project into Microsoft Excel. This study aimed to propose a model for the preparation of reports on automatic online project progress based on actual project information updates by the integration of Primavera P6, SQL database, and Power BI (Business Intelligence) for a construction project. The designed model could be applicable to project planners and controller agents by enabling them to prepare project reports automatically and immediately after updating the project schedule using actual information. To develop the model, the data were entered into P6, and the information was stored on the SQL database. The proposed model could prepare a wide range of reports, such as earned value management, Human Resource (HR) reports, and financial, physical, and risk reports automatically on the Power BI application. Furthermore, the reports could be published and shared online.

Keywords: Primavera P6, SQL, Power BI, Earned Value Management, Integration Management.

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Authors: Andrea Tundis, Carlos García Cordero, Rolf Egert, Alfredo Garro, Max Mühlhäuser

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Resilience is an important system property that relies on the ability of a system to automatically recover from a degraded state so as to continue providing its services. Resilient systems have the means of detecting faults and failures with the added capability of automatically restoring their normal operations. Mastering resilience in the domain of Cyber-Physical Systems is challenging due to the interdependence of hybrid hardware and software components, along with physical limitations, laws, regulations and standards, among others. In order to overcome these challenges, this paper presents a modeling approach, based on the concept of Dynamic Cells, tailored to the management of Smart Grids. Additionally, a heuristic algorithm that works on top of the proposed modeling approach, to find resilient configurations, has been defined and implemented. More specifically, the model supports a flexible representation of Smart Grids and the algorithm is able to manage, at different abstraction levels, the resource consumption of individual grid elements on the presence of failures and faults. Finally, the proposal is evaluated in a test scenario where the effectiveness of such approach, when dealing with complex scenarios where adequate solutions are difficult to find, is shown.

Keywords: Cyber-physical systems, energy management, optimization, smart grids, self-healing, resilience, security.

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Authors: Javed Parvez, Mushtaq Ahmad Peer

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Mobile Ad hoc networks (MANETs) are collections of wireless mobile nodes dynamically reconfiguring and collectively forming a temporary network. These types of networks assume existence of no fixed infrastructure and are often useful in battle-field tactical operations or emergency search-and-rescue type of operations where fixed infrastructure is neither feasible nor practical. They also find use in ad hoc conferences, campus networks and commercial recreational applications carrying multimedia traffic. All of the above applications of MANETs require guaranteed levels of performance as experienced by the end-user. This paper focuses on key challenges in provisioning predetermined levels of such Quality of Service (QoS). It also identifies functional areas where QoS models are currently defined and used. Evolving functional areas where performance and QoS provisioning may be applied are also identified and some suggestions are provided for further research in this area. Although each of the above functional areas have been discussed separately in recent research studies, since these QoS functional areas are highly correlated and interdependent, a comprehensive and comparative analysis of these areas and their interrelationships is desired. In this paper we have attempted to provide such an overview.

Keywords: Bandwidth Reservation, Congestion, DynamicNetwork Topology, End-to-End Delay, Flexible QoS Model forMANET(FQMM), Hidden Terminal, Mobile AdhocNetwork(MANET), Packet Jitter, Queuing, Quality-of-Service(QoS), Relative Bandwidth Service Differentiation(RBSD), Resource ReSerVation Protocol (RSVP).

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Authors: U. Schmidt, D. Dannehl, I. Schuch, J. Suhl, T. Rocksch, R. Salazar-Moreno, E. Fitz-Rodrigues, A. Rojano Aquilar, I. Lopez Cruz, G. Navas Gomez, R. A. Abraham, L. C. Irineo, N. G. Gilberto

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The integration of agricultural production systems into urban areas is a challenge for the coming decades. Because of increasing greenhouse gas emission and rising resource consumption as well as costs in animal husbandry, the dietary habits of people in the 21st century have to focus on herbal foods. Intensive plant cultivation systems in large cities and megacities require a smart coupling of information, material and energy flow with the urban infrastructure in terms of Horticulture 4.0. In recent years, many puzzle pieces have been developed for these closed processes at the Humboldt University. To compile these for an urban plant production, it has to be optimized and networked with urban infrastructure systems. In the field of heat energy production, it was shown that with closed greenhouse technology and patented heat exchange and storage technology energy can be provided for heating and domestic hot water supply in the city. Closed water circuits can be drastically reducing the water requirements of plant production in urban areas. Ion sensitive sensors and new disinfection methods can help keep circulating nutrient solutions in the system for a longer time in urban plant production greenhouses.

Keywords: Semi closed, greenhouses, urban farming, solar heat collector, closed water cycles, aquaponics.

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Authors: Hanaa T. El-Madany, Faten H. Fahmy, Ninet M. A. El-Rahman, Hassen T. Dorrah

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Designing and implementing intelligent systems has become a crucial factor for the innovation and development of better products of space technologies. A neural network is a parallel system, capable of resolving paradigms that linear computing cannot. Field programmable gate array (FPGA) is a digital device that owns reprogrammable properties and robust flexibility. For the neural network based instrument prototype in real time application, conventional specific VLSI neural chip design suffers the limitation in time and cost. With low precision artificial neural network design, FPGAs have higher speed and smaller size for real time application than the VLSI and DSP chips. So, many researchers have made great efforts on the realization of neural network (NN) using FPGA technique. In this paper, an introduction of ANN and FPGA technique are briefly shown. Also, Hardware Description Language (VHDL) code has been proposed to implement ANNs as well as to present simulation results with floating point arithmetic. Synthesis results for ANN controller are developed using Precision RTL. Proposed VHDL implementation creates a flexible, fast method and high degree of parallelism for implementing ANN. The implementation of multi-layer NN using lookup table LUT reduces the resource utilization for implementation and time for execution.

Keywords: Spacecraft, neural network, FPGA, VHDL.

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Authors: Mohammad Hossein Hojjati , Fardin Boustani

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

Keywords: Fars province , ground water overdraft , water table

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Authors: Naghmeh Moradpoor Sheykhkanloo

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Thousands of organisations store important and confidential information related to them, their customers, and their business partners in databases all across the world. The stored data ranges from less sensitive (e.g. first name, last name, date of birth) to more sensitive data (e.g. password, pin code, and credit card information). Losing data, disclosing confidential information or even changing the value of data are the severe damages that Structured Query Language injection (SQLi) attack can cause on a given database. It is a code injection technique where malicious SQL statements are inserted into a given SQL database by simply using a web browser. In this paper, we propose an effective pattern recognition neural network model for detection and classification of SQLi attacks. The proposed model is built from three main elements of: a Uniform Resource Locator (URL) generator in order to generate thousands of malicious and benign URLs, a URL classifier in order to: 1) classify each generated URL to either a benign URL or a malicious URL and 2) classify the malicious URLs into different SQLi attack categories, and a NN model in order to: 1) detect either a given URL is a malicious URL or a benign URL and 2) identify the type of SQLi attack for each malicious URL. The model is first trained and then evaluated by employing thousands of benign and malicious URLs. The results of the experiments are presented in order to demonstrate the effectiveness of the proposed approach.

Keywords: Neural Networks, pattern recognition, SQL injection attacks, SQL injection attack classification, SQL injection attack detection.

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Authors: Mohammed Erritali

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The growth in the volume of text data such as books and articles in libraries for centuries has imposed to establish effective mechanisms to locate them. Early techniques such as abstraction, indexing and the use of classification categories have marked the birth of a new field of research called "Information Retrieval". Information Retrieval (IR) can be defined as the task of defining models and systems whose purpose is to facilitate access to a set of documents in electronic form (corpus) to allow a user to find the relevant ones for him, that is to say, the contents which matches with the information needs of the user. Most of the models of information retrieval use a specific data structure to index a corpus which is called "inverted file" or "reverse index". This inverted file collects information on all terms over the corpus documents specifying the identifiers of documents that contain the term in question, the frequency of each term in the documents of the corpus, the positions of the occurrences of the word... In this paper we use an oriented object database (db4o) instead of the inverted file, that is to say, instead to search a term in the inverted file, we will search it in the db4o database. The purpose of this work is to make a comparative study to see if the oriented object databases may be competing for the inverse index in terms of access speed and resource consumption using a large volume of data.

Keywords: Information Retrieval, indexation, oriented object database (db4o), inverted file.

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Authors: Silvina Caíno-Lores, Jesús Carretero

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Large scale computing infrastructures have been widely developed with the core objective of providing a suitable platform for high-performance and high-throughput computing. These systems are designed to support resource-intensive and complex applications, which can be found in many scientific and industrial areas. Currently, large scale data-intensive applications are hindered by the high latencies that result from the access to vastly distributed data. Recent works have suggested that improving data locality is key to move towards exascale infrastructures efficiently, as solutions to this problem aim to reduce the bandwidth consumed in data transfers, and the overheads that arise from them. There are several techniques that attempt to move computations closer to the data. In this survey we analyse the different mechanisms that have been proposed to provide data locality for large scale high-performance and high-throughput systems. This survey intends to assist scientific computing community in understanding the various technical aspects and strategies that have been reported in recent literature regarding data locality. As a result, we present an overview of locality-oriented techniques, which are grouped in four main categories: application development, task scheduling, in-memory computing and storage platforms. Finally, the authors include a discussion on future research lines and synergies among the former techniques.

Keywords: Co-scheduling, data-centric, data-intensive, data locality, in-memory storage, large scale.

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Authors: M. Rezvani, F. Zaefarian, M. Aghaalikhani, H. Rahimian Mashhadi, E. Zand

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The spatial variation in plant species associated with intercropping is intended to reduce resource competition between species and increase yield potential. A field experiment was carried out on corn (Zea mays L.) and soybean (Glycine max L.) intercropping in a replacement series experiment with weed contamination consist of: weed free, infestation of redroot pigweed, infestation of jimsonweed and simultaneous infestation of redroot pigweed and jimsonweed in Karaj, Iran during 2007 growing season. The experimental design was a randomized complete block in factorial experiment with replicated thrice. Significant (P≤0.05) differences were observed in yield in intercropping. Corn yield was higher in intercropping, but soybean yield was significantly reduced by corn when intercropped. However, total productivity and land use efficiency were high under the intercropping system even in contamination of either species of weeds. Aggressivity of corn relative to soybean revealed the greater competitive ability of corn than soybean. Land equivalent ratio (LER) more than 1 in all treatments attributed to intercropping advantages and was highest in 50: 50 (corn/soybean) in weed free. These findings suggest that intercropping corn and soybean increase total productivity per unit area and improve land use efficiency. Considering the experimental findings, corn-soybean intercropping (50:50) may be recommended for yield advantage, more efficient utilization of resources, and weed suppression as a biological control.

Keywords: Corn, soybean, intercropping, redroot pigweed, jimsonweed.

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Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

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Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: Lithium-Ion batteries, genetic algorithm optimization, battery aging test, and parameter identification.

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Authors: Muqdad Al-Juboori, Bithin Datta

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Hydraulic structures such as gravity dams are classified as essential structures, and have the vital role in providing strong and safe water resource management. Three major aspects must be considered to achieve an effective design of such a structure: 1) The building cost, 2) safety, and 3) accurate analysis of seepage characteristics. Due to the complexity and non-linearity relationships of the seepage process, many approximation theories have been developed; however, the application of these theories results in noticeable errors. The analytical solution, which includes the difficult conformal mapping procedure, could be applied for a simple and symmetrical problem only. Therefore, the objectives of this paper are to: 1) develop a surrogate model based on numerical simulated data using SEEPW software to approximately simulate seepage process related to a hydraulic structure, 2) develop and solve a linked simulation-optimization model based on the developed surrogate model to describe the seepage occurring under a concrete gravity dam, in order to obtain optimum and safe design at minimum cost. The result shows that the linked simulation-optimization model provides an efficient and optimum design of concrete gravity dams.

Keywords: Artificial neural network, concrete gravity dam, genetic algorithm, seepage analysis.

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Authors: S. Anastasiou, C. Nathanailides

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The purpose of this study is to examine the possible link between employee and customer satisfaction. The service provided by employees, help to build a good relationship with customers and can help at increasing their loyalty. Published data for job satisfaction and indicators of customer services of banks were gathered from relevant published works which included data from five different countries. The scores of customers and employees satisfaction of the different published works were transformed and normalized to the scale of 1 to 100. The data were analyzed and a regression analysis of the two parameters was used to describe the link between employee’s satisfaction and customer’s satisfaction. Assuming that employee satisfaction has a significant influence on customer’s service and the resulting customer satisfaction, the reviewed data indicate that employee’s satisfaction contributes significantly on the level of customer satisfaction in the Banking sector. There was a significant correlation between the two parameters (Pearson correlation R2=0.52 P<0.05). The reviewed data indicate that published data support the hypothesis that practical evidence link these two parameters. During the recent global economic crisis, the financial services sector was affected severely and job security, remuneration and recruitment of personnel of banks was in many countries, including Greece, significantly reduced. Nevertheless, modern organizations should always consider their personnel as a capital, which is the driving force for success in the future. Appropriate human resource management policies can increase the level of job satisfaction of the personnel with positive consequences for the level of customer’s satisfaction.

Keywords: Job satisfaction, job performance, customer service, banks, human resources management.

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Authors: Joshua N. Edokpayi, John O. Odiyo, Patience P. Shikwambana

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Water is a very rare natural resource in South Africa. Ga-Selati River is used for both domestic and industrial purposes. This study was carried out in order to assess the quality of Ga-Selati River in a mining area of Limpopo Province-Phalaborwa. The pH, Electrical Conductivity (EC) and Total Dissolved Solids (TDS) were determined using a Crinson multimeter while turbidity was measured using a Labcon Turbidimeter. The concentrations of Al, Ca, Cd, Cr, Fe, K, Mg, Mn, Na and Pb were analysed in triplicate using a Varian 520 flame atomic absorption spectrometer (AAS) supplied by PerkinElmer, after acid digestion with nitric acid in a fume cupboard. The average pH of the river from eight different sampling sites was 8.00 and 9.38 in wet and dry season respectively. Higher EC values were determined in the dry season (138.7 mS/m) than in the wet season (96.93 mS/m). Similarly, TDS values were higher in dry (929.29 mg/L) than in the wet season (640.72 mg/L) season. These values exceeded the recommended guideline of South Africa Department of Water Affairs and Forestry (DWAF) for domestic water use (70 mS/m) and that of the World Health Organization (WHO) (600 mS/m), respectively. Turbidity varied between 1.78-5.20 and 0.95-2.37 NTU in both wet and dry seasons. Total hardness of 312.50 mg/L and 297.75 mg/L as the concentration of CaCO₃ was computed for the river in both the wet and the dry seasons and the river water was categorised as very hard. Mean concentration of the metals studied in both the wet and the dry seasons are: Na (94.06 mg/L and 196.3 mg/L), K (11.79 mg/L and 13.62 mg/L), Ca (45.60 mg/L and 41.30 mg/L), Mg (48.41 mg/L and 44.71 mg/L), Al (0.31 mg/L and 0.38 mg/L), Cd (0.01 mg/L and 0.01 mg/L), Cr (0.02 mg/L and 0.09 mg/L), Pb (0.05 mg/L and 0.06 mg/L), Mn (0.31 mg/L and 0.11 mg/L) and Fe (0.76 mg/L and 0.69 mg/L). Results from this study reveal that most of the metals were present in concentrations higher than the recommended guidelines of DWAF and WHO for domestic use and the protection of aquatic life.

Keywords: Contamination, mining activities, surface water, trace metals.

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Authors: Anita, Sari Septiani Tangke, Rusdina Bte Ladju, Nasrum Massi

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New diagnostic tools are urgently needed to interrupt the transmission of tuberculosis and multidrug-resistant tuberculosis. The microscopic-observation drug-susceptibility (MODS) assay is a rapid, accurate and simple liquid culture method to detect multidrug-resistant tuberculosis (MDR-TB). MODS were evaluated to determine a lower and same concentration of isoniazid and rifampin for detection of MDR-TB. Direct drug-susceptibility testing was performed with the use of the MODS assay. Drug-sensitive control strains were tested daily. The drug concentrations that used for both isoniazid and rifampin were at the same concentration: 0.16, 0.08 and 0.04μg per milliliter. We tested 56 M. tuberculosis clinical isolates and the control strains M. tuberculosis H37RV. All concentration showed same result. Of 53 M. tuberculosis clinical isolates, 14 were MDR-TB, 38 were susceptible with isoniazid and rifampin, 1 was resistant with isoniazid only. Drug-susceptibility testing was performed with the use of the proportion method using Mycobacteria Growth Indicator Tube (MGIT) system as reference. The result of MODS assay using lower concentration was significance (P<0.001) compare with the reference methods.

A lower and same concentration of isoniazid and rifampin can be used to detect MDR-TB. Operational cost and application can be more efficient and easier in resource-limited environments. However, additional studies evaluating the MODS using lower and same concentration of isoniazid and rifampin must be conducted with a larger number of clinical isolates.

Keywords: Isoniazid, MODS assay, MDR-TB, Rifampin.

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Authors: J. Gu, W.B. Lee, C.F. Cheung, E. Tsui, W.M. Wang

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Knowledge of an organization does not merely reside in structured form of information and data; it is also embedded in unstructured form. The discovery of such knowledge is particularly difficult as the characteristic is dynamic, scattered, massive and multiplying at high speed. Conventional methods of managing unstructured information are considered too resource demanding and time consuming to cope with the rapid information growth. In this paper, a Multi-faceted and Automatic Knowledge Elicitation System (MAKES) is introduced for the purpose of discovery and capture of organizational knowledge. A trial implementation has been conducted in a public organization to achieve the objective of decision capture and navigation from a number of meeting minutes which are autonomously organized, classified and presented in a multi-faceted taxonomy map in both document and content level. Key concepts such as critical decision made, key knowledge workers, knowledge flow and the relationship among them are elicited and displayed in predefined knowledge model and maps. Hence, the structured knowledge can be retained, shared and reused. Conducting Knowledge Management with MAKES reduces work in searching and retrieving the target decision, saves a great deal of time and manpower, and also enables an organization to keep pace with the knowledge life cycle. This is particularly important when the amount of unstructured information and data grows extremely quickly. This system approach of knowledge management can accelerate value extraction and creation cycles of organizations.

Keywords: Knowledge-Based System, Knowledge Elicitation, Knowledge Management, Taxonomy, Unstructured Information Management

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Authors: Pavel Shcherban, Viktoria Ivanova, Alexander Neprokin, Vladislav Golovanov

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Currently, LLC «Lukoil-Kaliningradmorneft» is implementing a comprehensive program for the development of offshore fields of the Kaliningrad region. This is largely associated with the depletion of the resource base of land in the region, as well as the positive results of geological investigation surrounding the Baltic Sea area and the data on the volume of hydrocarbon recovery from a single offshore field are working on the Kaliningrad region – D-6 «Kravtsovskoye».The article analyzes the main stages of the LLC «Lukoil-Kaliningradmorneft»’s development program for the development of the hydrocarbon resources of the region's shelf and suggests an optimization algorithm that allows managing a multi-criteria process of development of shelf deposits. The algorithm is formed on the basis of the problem of sequential decision making, which is a section of dynamic programming. Application of the algorithm during the consolidation of the initial data, the elaboration of project documentation, the further exploration and development of offshore fields will allow to optimize the complex of technical and technological solutions and increase the economic efficiency of the field development project implemented by LLC «Lukoil-Kaliningradmorneft».

Keywords: Offshore fields of hydrocarbons of the Baltic Sea, Development of offshore oil and gas fields, Optimization of the field development scheme, Solution of multi-criteria tasks in the oil and gas complex, Quality management of technical and technological processes.

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Authors: Konstantinos C. Giotopoulos, Christos E. Alexakos, Grigorios N. Beligiannis, Spiridon D.Likothanassis

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In this contribution an innovative platform is being presented that integrates intelligent agents and evolutionary computation techniques in legacy e-learning environments. It introduces the design and development of a scalable and interoperable integration platform supporting: I) various assessment agents for e-learning environments, II) a specific resource retrieval agent for the provision of additional information from Internet sources matching the needs and profile of the specific user and III) a genetic algorithm designed to extract efficient information (classifying rules) based on the students- answering input data. The agents are implemented in order to provide intelligent assessment services based on computational intelligence techniques such as Bayesian Networks and Genetic Algorithms. The proposed Genetic Algorithm (GA) is used in order to extract efficient information (classifying rules) based on the students- answering input data. The idea of using a GA in order to fulfil this difficult task came from the fact that GAs have been widely used in applications including classification of unknown data. The utilization of new and emerging technologies like web services allows integrating the provided services to any web based legacy e-learning environment.

Keywords: Bayesian Networks, Computational Intelligencetechniques, E-learning legacy systems, Service Oriented Integration, Intelligent Agents, Genetic Algorithms.

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Authors: Abeer Samy, Oliver C. Saavedra Valeriano, Abdelazim Negm

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The Blue Nile Basin is the most important tributary of the Nile River. Egypt and Sudan are almost dependent on water originated from the Blue Nile. This multi-dependency creates conflicts among the three countries Egypt, Sudan, and Ethiopia making the management of these conflicts as an international issue. Good assessment of the water resources of the Blue Nile is an important to help in managing such conflicts. Hydrological models are good tool for such assessment. This paper presents a critical review of the nature and variability of the climate and hydrology of the Blue Nile Basin as a first step of using hydrological modeling to assess the water resources of the Blue Nile. Many several attempts are done to develop basin-scale hydrological modeling on the Blue Nile. Lumped and semi distributed models used averages of meteorological inputs and watershed characteristics in hydrological simulation, to analyze runoff for flood control and water resource management. Distributed models include the temporal and spatial variability of catchment conditions and meteorological inputs to allow better representation of the hydrological process. The main challenge of all used models was to assess the water resources of the basin is the shortage of the data needed for models calibration and validation. It is recommended to use distributed model for their higher accuracy to cope with the great variability and complexity of the Blue Nile basin and to collect sufficient data to have more sophisticated and accurate hydrological modeling.

Keywords: Blue Nile Basin, Climate Change, Hydrological Modeling, Watershed.

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Authors: Seshi Reddy Kasu, Florian Misoc

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The use of hydroelectric pump-storage system at large scale, MW-size systems, is already widespread around the world. Designed for large scale applications, pump-storage station can be scaled-down for small, remote residential applications. Given the cost and complexity associated with installing a substation further than 100 miles from the main transmission lines, a remote, independent and self-sufficient system is by far the most feasible solution. This article is aiming at the design of wind and solar power generating system, by means of pumped-storage to replace the wind and /or solar power systems with a battery bank energy storage. Wind and solar pumped-storage power generating system can reduce the cost of power generation system, according to the user's electricity load and resource condition and also can ensure system reliability of power supply. Wind and solar pumped-storage power generation system is well suited for remote residential applications with intermittent wind and/or solar energy. This type of power systems, installed in these locations, could be a very good alternative, with economic benefits and positive social effects. The advantage of pumped storage power system, where wind power regulation is calculated, shows that a significant smoothing of the produced power is obtained, resulting in a power-on-demand system’s capability, concomitant to extra economic benefits.

Keywords: Battery bank, photo-voltaic, pump-storage, wind energy.

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Authors: Abimbola Motunrayo Folami, Ibironke Titilayo Enitan, Feroz Mohomed Swalaha

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Water is a vital resource that is important in ensuring the growth and development of any country. To sustain the basic human needs and the demands for agriculture, industry, conservational and ecosystem, enough quality and quantity water is needed. Contamination of water resources is now a global and public health concern. Hence, this study assessed the water quality of Ndawuse River by measuring the physicochemical parameters and heavy metals concentrations of the river using standard methods. In total, 16 surface water samples were obtained from five locations along the river, from upstream to downstream as well as samples from the dumpsite. The results obtained were compared with the standard limits set by both the World Health Organization and the Federal Environmental Protection Agency for domestic purposes. The results of the measured parameters indicated that biological oxygen demand (85.88 mg/L), turbidity (44.51 NTU), Iron (0.014 - 3.511 mg /L) and chromium (0.078 - 0.14 mg /L) were all above the standard limits. The results further showed that the quality of surface water is being significantly affected by human activities around the Ndawuse River which could pose an adverse health risk to several communities that rely on this river as their primary source of water. Therefore, there is a need for strict enforcement of environmental laws to protect the aquatic ecosystem and to avoid long term cumulative exposure risk that heavy metals may pose on human health.

Keywords: Abuja, contaminants, heavy metals, Ndawuse River, Nigeria, surface water.

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Authors: V. Charaia

Abstract:

From the strategic point of view, not all Foreign Direct Investments (FDIs) are always positively benefiting the host economy, i.e. not all Multinational Enterprises (MNEs) are promoting local/host economies. FDI could have different impact on different sectors of the economy, based not only on annual investment amount, but MNE motivations and peculiarities of the host economy in particular. FDI analysis based only on its amount can lead to incorrect decisions, it is much more important to understand the essence of investment. Consequently, our research is oriented on MNE’s motivations, answering which sectors are most popular among international investors and why, what motivated them to invest into one or another business. Georgian economy for the last period of time is attracting more and more efficiency seeking investments, which could be translated as - concentrating production in a limited number of locations to supply various markets, while benefiting local economy with: new technologies, employment, exports diversification, increased income for the local economy and so on. Foreign investors and MNEs in particular are no longer and not so much interested in the resource seeking investments, which was the case for Georgia in the last decade of XX century. Despite the fact of huge progress for the Georgian economy, still there is a room for foreign investors to make a local market oriented investments. The local market is still rich in imported products, which should be replaced by local ones. And the last but not the least important issue is that approximately 30% of all FDIs in Georgia according to this research are “efficiency seeking” investments, which is an enormous progress and a hope for future Georgian success.

Keywords: Investments, MNE, FDI motivations, Georgian economy.

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Authors: Talal Alsulaiman, Khaldoun Khashanah

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In this paper, we provided a literature survey on the artificial stock problem (ASM). The paper began by exploring the complexity of the stock market and the needs for ASM. ASM aims to investigate the link between individual behaviors (micro level) and financial market dynamics (macro level). The variety of patterns at the macro level is a function of the AFM complexity. The financial market system is a complex system where the relationship between the micro and macro level cannot be captured analytically. Computational approaches, such as simulation, are expected to comprehend this connection. Agent-based simulation is a simulation technique commonly used to build AFMs. The paper proceeds by discussing the components of the ASM. We consider the roles of behavioral finance (BF) alongside the traditionally risk-averse assumption in the construction of agent’s attributes. Also, the influence of social networks in the developing of agents interactions is addressed. Network topologies such as a small world, distance-based, and scale-free networks may be utilized to outline economic collaborations. In addition, the primary methods for developing agents learning and adaptive abilities have been summarized. These incorporated approach such as Genetic Algorithm, Genetic Programming, Artificial neural network and Reinforcement Learning. In addition, the most common statistical properties (the stylized facts) of stock that are used for calibration and validation of ASM are discussed. Besides, we have reviewed the major related previous studies and categorize the utilized approaches as a part of these studies. Finally, research directions and potential research questions are argued. The research directions of ASM may focus on the macro level by analyzing the market dynamic or on the micro level by investigating the wealth distributions of the agents.

Keywords: Artificial stock markets, agent based simulation, bounded rationality, behavioral finance, artificial neural network, interaction, scale-free networks.

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Authors: Ahmed Elsayed, Andrew Shea, Nicolas Kelly, John Allison

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In northern European climates, domestic space heating and hot water represents a significant proportion of total primary total primary energy use and meeting these demands from a national electricity grid network supplied by renewable energy sources provides an opportunity for a significant reduction in EU CO₂ emissions. However, in order to adapt to the intermittent nature of renewable energy generation and to avoid co-incident peak electricity usage from consumers that may exceed current capacity, the demand for heat must be decoupled from its generation. Storage of heat within the fabric of dwellings for use some hours, or days, later provides a route to complete decoupling of demand from supply and facilitates the greatly increased use of renewable energy generation into a local or national electricity network. The integration of thermal energy storage into the building fabric for retrieval at a later time requires much evaluation of the many competing thermal, physical, and practical considerations such as the profile and magnitude of heat demand, the duration of storage, charging and discharging rate, storage media, space allocation, etc. In this paper, the authors report investigations of thermal storage in building fabric using concrete material and present an evaluation of several factors that impact upon performance including heating pipe layout, heating fluid flow velocity, storage geometry, thermo-physical material properties, and also present an investigation of alternative storage materials and alternative heat transfer fluids. Reducing the heating pipe spacing from 200 mm to 100 mm enhances the stored energy by 25% and high-performance Vacuum Insulation results in heat loss flux of less than 3 W/m², compared to 22 W/m² for the more conventional EPS insulation. Dense concrete achieved the greatest storage capacity, relative to medium and light-weight alternatives, although a material thickness of 100 mm required more than 5 hours to charge fully. Layers of 25 mm and 50 mm thickness can be charged in 2 hours, or less, facilitating a fast response that could, aggregated across multiple dwellings, provide significant and valuable reduction in demand from grid-generated electricity in expected periods of high demand and potentially eliminate the need for additional new generating capacity from conventional sources such as gas, coal, or nuclear.

Keywords: Fabric integrated thermal storage, FITS, demand side management, energy storage, load shifting, renewable energy integration.

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Authors: Bülent Dilmaç, Didem Aydoğan

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Problem Statement:Rapid technological developments of the 21st century have advanced our daily lives in various ways. Particularly in education, students frequently utilize technological resources to aid their homework and to access information. listen to radio or watch television (26.9 %) and e-mails (34.2 %) [26]. Not surprisingly, the increase in the use of technologies also resulted in an increase in the use of e-mail, instant messaging, chat rooms, mobile phones, mobile phone cameras and web sites by adolescents to bully peers. As cyber bullying occurs in the cyber space, lesser access to technologies would mean lesser cyber-harm. Therefore, the frequency of technology use is a significant predictor of cyber bullying and cyber victims. Cyber bullies try to harm the victim using various media. These tools include sending derogatory texts via mobile phones, sending threatening e-mails and forwarding confidential emails to everyone on the contacts list. Another way of cyber bullying is to set up a humiliating website and invite others to post comments. In other words, cyber bullies use e-mail, chat rooms, instant messaging, pagers, mobile texts and online voting tools to humiliate and frighten others and to create a sense of helplessness. No matter what type of bullying it is, it negatively affects its victims. Children who bully exhibit more emotional inhibition and attribute themselves more negative self-statements compared to non-bullies. Students whose families are not sympathetic and who receive lower emotional support are more prone to bully their peers. Bullies have authoritarian families and do not get along well with them. The family is the place where the children-s physical, social and psychological needs are satisfied and where their personalities develop. As the use of the internet became prevalent so did parents- restrictions on their children-s internet use. However, parents are unaware of the real harm. Studies that explain the relationship between parental attitudes and cyber bullying are scarce in literature. Thus, this study aims to investigate the relationship between cyber bullying and parental attitudes in the primary school. Purpose of Study: This study aimed to investigate the relationship between cyber bullying and parental attitudes. A second aim was to determine whether parental attitudes could predict cyber bullying and if so which variables could predict it significantly. Methods:The study had a cross-sectional and relational survey model. A demographics information form, questions about cyber bullying and a Parental Attitudes Inventory were conducted with a total of 346 students (189 females and 157 males) registered at various primary schools. Data was analysed by multiple regression analysis using the software package SPSS 16.

Keywords: Cyber bullying, cyber victim, parental attitudes, primary school students.

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Authors: Rehab Abdullah Shendi

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The use of customised soft-core processors in which instructions can be integrated into a system in application hardware is increasing in the Field Programmable Gate Array (FPGA) field. Specifically, the partial run-time reconfiguration of FPGAs in specialised processors for a particular domain can be very beneficial. In this report, the design and implementation for the customisation of a soft-core MIPS processor using an FPGA and partial reconfiguration (PR) of FPGA technology will be addressed to achieve efficient resource use. This can be achieved using a PR design flow that helps the design fit into a smaller device. Moreover, the impact of static power consumption could be reduced due to runtime reconfiguration. This will be done by configurable custom instructions implemented in the hardware as an extension on the MIPS CPU. The aim of this project is to investigate the PR of FPGAs for run-time adaptations of the instruction set of a soft-core CPU, including the integration of custom instructions and the exploration of the potential to use the MultiBoot feature available in Xilinx FPGAs to carry out the PR process. The system will be evaluated and tested on a Nexus 3 development board featuring a Xilinx Spartran-6 FPGA. The system will be able to load reconfigurable custom instructions dynamically into user programs with the help of the trap handler when the custom instruction is called by the MIPS CPU. The results of this experiment demonstrate that custom instructions in hardware can speed up a certain function and many instructions can be saved when compared to a software implementation of the same function. Implementing custom instructions in hardware is perfectly possible and worth exploring.

Keywords: Customisation, FPGA, MIPS, partial reconfiguration.

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Authors: D. Sathan, A. Meetoo, R. K. Subramaniam

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Context awareness is a capability whereby mobile computing devices can sense their physical environment and adapt their behavior accordingly. The term context-awareness, in ubiquitous computing, was introduced by Schilit in 1994 and has become one of the most exciting concepts in early 21st-century computing, fueled by recent developments in pervasive computing (i.e. mobile and ubiquitous computing). These include computing devices worn by users, embedded devices, smart appliances, sensors surrounding users and a variety of wireless networking technologies. Context-aware applications use context information to adapt interfaces, tailor the set of application-relevant data, increase the precision of information retrieval, discover services, make the user interaction implicit, or build smart environments. For example: A context aware mobile phone will know that the user is currently in a meeting room, and reject any unimportant calls. One of the major challenges in providing users with context-aware services lies in continuously monitoring their contexts based on numerous sensors connected to the context aware system through wireless communication. A number of context aware frameworks based on sensors have been proposed, but many of them have neglected the fact that monitoring with sensors imposes heavy workloads on ubiquitous devices with limited computing power and battery. In this paper, we present CALEEF, a lightweight and energy efficient context aware framework for resource limited ubiquitous devices.

Keywords: Context-Aware, Energy-Efficient, Lightweight, Ubiquitous Devices.

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Authors: Mohd Hasmadi Ismail, Kamaruzaman Jusoff

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In order to develop forest management strategies in tropical forest in Malaysia, surveying the forest resources and monitoring the forest area affected by logging activities is essential. There are tremendous effort has been done in classification of land cover related to forest resource management in this country as it is a priority in all aspects of forest mapping using remote sensing and related technology such as GIS. In fact classification process is a compulsory step in any remote sensing research. Therefore, the main objective of this paper is to assess classification accuracy of classified forest map on Landsat TM data from difference number of reference data (200 and 388 reference data). This comparison was made through observation (200 reference data), and interpretation and observation approaches (388 reference data). Five land cover classes namely primary forest, logged over forest, water bodies, bare land and agricultural crop/mixed horticultural can be identified by the differences in spectral wavelength. Result showed that an overall accuracy from 200 reference data was 83.5 % (kappa value 0.7502459; kappa variance 0.002871), which was considered acceptable or good for optical data. However, when 200 reference data was increased to 388 in the confusion matrix, the accuracy slightly improved from 83.5% to 89.17%, with Kappa statistic increased from 0.7502459 to 0.8026135, respectively. The accuracy in this classification suggested that this strategy for the selection of training area, interpretation approaches and number of reference data used were importance to perform better classification result.

Keywords: Image Classification, Reference Data, Accuracy Assessment, Kappa Statistic, Forest Land Cover

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Authors: Daniel Micallef, Damien Bounaudet, Robert N. Farrugia, Simon P. Borg, Vincent Buhagiar, Tonio Sant

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The physical effects of upstream flow obstructions such as vegetation on cross-ventilation phenomena of a building are important for issues such as indoor thermal comfort. Modelling such effects in Computational Fluid Dynamics simulations may also be challenging. The aim of this work is to establish the cross-ventilation jet behaviour in such complex terrain conditions as well as to provide guidelines on the implementation of CFD numerical simulations in order to model complex terrain features such as vegetation in an efficient manner. The methodology consists of onsite measurements on a test cell coupled with numerical simulations. It was found that the cross-ventilation flow is highly turbulent despite the very low velocities encountered internally within the test cells. While no direct measurement of the jet direction was made, the measurements indicate that flow tends to be reversed from the leeward to the windward side. Modelling such a phenomenon proves challenging and is strongly influenced by how vegetation is modelled. A solid vegetation tends to predict better the direction and magnitude of the flow than a porous vegetation approach. A simplified terrain model was also shown to provide good comparisons with observation. The findings have important implications on the study of cross-ventilation in complex terrain conditions since the flow direction does not remain trivial, as with the traditional isolated building case.

Keywords: Complex terrain, cross-ventilation, wind driven ventilation, Computational Fluid Dynamics (CFD), wind resource.

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