A Review on Applications of Evolutionary Algorithms to Reservoir Operation for Hydropower Production

Evolutionary Algorithms (EAs) have been used widely through evolution theory to discover acceptable solutions that corresponds to challenges such as natural resources management. EAs are also used to solve varied problems in the real world. EAs have been rapidly identified for its ease in handling multiple objective problems. Reservoir operations is a vital and researchable area which has been studied in the last few decades due to the limited nature of water resources that is found mostly in the semi-arid regions of the world. The state of some developing economy that depends on electricity for overall development through hydropower production, a renewable form of energy, is appalling due to water scarcity. This paper presents a review of the applications of evolutionary algorithms to reservoir operation for hydropower production. This review includes the discussion on areas such as genetic algorithm, differential evolution, and reservoir operation. It also identified the research gaps discovered in these areas. The results of this study will be an eye opener for researchers and decision makers to think deeply of the adverse effect of water scarcity and drought towards economic development of a nation. Hence, it becomes imperative to identify evolutionary algorithms that can address this issue which can hamper effective hydropower generation.

Evaluation of Chromium Fortified Parboiled Rice Coated with Herbal Extracts: Cooking Quality and Sensory Properties

Parboiled rice was developed to produce rice, which has a low glycemic index for diabetics. However, diabetics also have a chromium (Cr) deficiency. Thus, it is important to fortify rice with Cr to increase the Cr content. Moreover, parboiled rice becomes rancid easily and has a musty odor, rendering the rice unfavorable. Natural herbs such as pandan leaves (Pandanus amaryllifolius Roxb.), bay leaves (Syzygium polyanthum [Wigh] Walp) and cinnamon bark powder (Cinnamomon cassia) are commonly added to food as aroma enhancers. Previous research has shown that these herbs could improve insulin sensitivity. The purpose of this study was to evaluate the effect of herbal extract coatings on the cooking quality and the preference level of chromium fortified - parboiled rice (CFPR). The rice grain variety used for this experiment was Ciherang and the fortificant was CrCl3. The three herbal extracts used for coating the CFPR were cinnamon, pandan and bay leaf, with concentration variations of 3%, 6%, and 9% (w/w) for each of the extracts. The samples were analyzed for their alkali spreading value, cooking time, elongation, water uptake ratio, solid loss, colour and lightness; and their sensory properties were determined by means of an organoleptic test. The research showed that coating the CFPR with pandan and cinnamon extracts at a concentration of 3% each produced a preferred CFPR. When coated with those herbal extracts the CFPR had the following cooking quality properties: alkali spreading value 5 (intermediate gelatinization temperature), cooking time, 26-27 min, color value, 14.95-15.00, lightness, 42.30 – 44.06, elongation, 1.53 – 1.54, water uptake ratio , 4.05-4.06, and solid loss, 0.09/100 g – 0.13 g/100 g.

Automating Test Activities: Test Cases Creation, Test Execution, and Test Reporting with Multiple Test Automation Tools

Software testing has become a mandatory process in assuring the software product quality. Hence, test management is needed in order to manage the test activities conducted in the software test life cycle. This paper discusses on the challenges faced in the software test life cycle, and how the test processes and test activities, mainly on test cases creation, test execution, and test reporting is being managed and automated using several test automation tools, i.e. Jira, Robot Framework, and Jenkins.

Spatio-Temporal Data Mining with Association Rules for Lake Van

People, throughout the history, have made estimates and inferences about the future by using their past experiences. Developing information technologies and the improvements in the database management systems make it possible to extract useful information from knowledge in hand for the strategic decisions. Therefore, different methods have been developed. Data mining by association rules learning is one of such methods. Apriori algorithm, one of the well-known association rules learning algorithms, is not commonly used in spatio-temporal data sets. However, it is possible to embed time and space features into the data sets and make Apriori algorithm a suitable data mining technique for learning spatiotemporal association rules. Lake Van, the largest lake of Turkey, is a closed basin. This feature causes the volume of the lake to increase or decrease as a result of change in water amount it holds. In this study, evaporation, humidity, lake altitude, amount of rainfall and temperature parameters recorded in Lake Van region throughout the years are used by the Apriori algorithm and a spatio-temporal data mining application is developed to identify overflows and newlyformed soil regions (underflows) occurring in the coastal parts of Lake Van. Identifying possible reasons of overflows and underflows may be used to alert the experts to take precautions and make the necessary investments.

Space Telemetry Anomaly Detection Based on Statistical PCA Algorithm

The critical concern of satellite operations is to ensure the health and safety of satellites. The worst case in this perspective is probably the loss of a mission, but the more common interruption of satellite functionality can result in compromised mission objectives. All the data acquiring from the spacecraft are known as Telemetry (TM), which contains the wealth information related to the health of all its subsystems. Each single item of information is contained in a telemetry parameter, which represents a time-variant property (i.e. a status or a measurement) to be checked. As a consequence, there is a continuous improvement of TM monitoring systems to reduce the time required to respond to changes in a satellite's state of health. A fast conception of the current state of the satellite is thus very important to respond to occurring failures. Statistical multivariate latent techniques are one of the vital learning tools that are used to tackle the problem above coherently. Information extraction from such rich data sources using advanced statistical methodologies is a challenging task due to the massive volume of data. To solve this problem, in this paper, we present a proposed unsupervised learning algorithm based on Principle Component Analysis (PCA) technique. The algorithm is particularly applied on an actual remote sensing spacecraft. Data from the Attitude Determination and Control System (ADCS) was acquired under two operation conditions: normal and faulty states. The models were built and tested under these conditions, and the results show that the algorithm could successfully differentiate between these operations conditions. Furthermore, the algorithm provides competent information in prediction as well as adding more insight and physical interpretation to the ADCS operation.

Numerical Simulation of the Bond Behavior between Concrete and Steel Reinforcing Bars in Specialty Concrete

In this study, the commercial finite element software ABAQUS was used to develop a three-dimensional nonlinear finite element model capable of simulating the pull-out test of reinforcing bars from underwater concrete. The results of thirty-two pull-out tests that have different parameters were implemented in the software to study the effect of the concrete cover, the bar size, the use of stirrups, and the compressive strength of concrete. The interaction properties used in the model provided accurate results in comparison with the experimental bond-slip results, thus the model has successfully simulated the pull-out test. The results of the finite element model are used to better understand and visualize the distribution of stresses in each component of the model, and to study the effect of the various parameters used in this study including the role of the stirrups in preventing the stress from reaching to the sides of the specimens.

Bridging Consumer-Farmer Mobile Application Divide

Electronic mediums such as websites, feeds, blogs and social media sites are on a daily basis influencing our decision making, are improving our productivity and are shaping futures of many consumers and service/product providers. This research identifies that both customers and business providers heavily rely on smart phone applications. Based on this, mobile applications available on iTunes store were studied. It was identified that fruit and vegetable related applications used by consumers can broadly be categorized into purchase applications, diaries, tracking health applications, trip farm location and cooking applications. On the other hand, applications used by farmers can broadly be classified as: weather tracking, pests / fertilizer applications and general social media applications such as Facebook. To blur this farmer-consumer application divide, our research utilizes Context Specific eTransformation Framework and based on it identifies characteristic future consumer-farmer applications will need to have so that the current divide can be narrowed and consequently better farmerconsumer supply chain link established.

Chatter Suppression in Boring Process Using Passive Damper

During machining process, chatter is an unavoidable phenomenon. Boring bars possess the cantilever shape and due to this, it is subjected to chatter. The adverse effect of chatter includes the increase in temperature which will leads to excess tool wear. To overcome these problems, in this investigation, Cartridge brass (Cu – 70% and Zn – 30%) is passively fixed on the boring bar and also clearance is provided in order to reduce the displacement, tool wear and cutting temperature. A conventional all geared lathe is attached with vibrometer and pyrometer is used to measure the displacement and temperature. The influence of input parameters such as cutting speed, depth of cut and clearance on temperature, tool wear and displacement are investigated for various cutting conditions. From the result, the optimum conditions to obtain better damping in boring process for chatter reduction is identified.

Comparison of Noise Emissions in the Interior of Passenger Cars

The noise is one of the negative elements which affects the human health. This article presents the measurement of emitted noise by road vehicle and its parts during the operation. Measurement was done in the interior of common passenger cars with a digital sound meter. The results compare the noise value in different cars with different body shape, which influences the driver’s health. Transport has considerable ecological effects; many of them are detrimental to environmental sustainability. Roads and traffic exert a variety of direct and mostly detrimental effects on nature.

An Institutional Analysis of IFRS Adoption in Poor Jurisdictions

The last two decades witnessed a movement towards harmonization of international financial reporting standards (IFRS) throughout the global economy. This investigation seeks to identify the factors that could explain the adoption of IFRS by poor jurisdictions. While there has been a considerable amount of literature published on the effects and key drivers of IFRS adoption in both developed and developing countries, little attention has been paid to jurisdictions with less developed capital markets and low income levels exclusively. Drawing upon the Institutional Isomorphism theory and analyzing a sample of 45 poor jurisdictions between 2008 and 2013, the study empirically shows that poor jurisdictions are driven by legitimacy concerns rather than by economic reasoning to adopt an international accounting perspective. This in turn has implications for the IASB, as it should seek to influence institutional pressures within a particular jurisdiction in order to promote IFRS adoption.

Sorption of Charged Organic Dyes from Anionic Hydrogels

Hydrogels are three-dimensional, hydrophilic, polymeric networks composed of homopolymers or copolymers and are insoluble in water due to the presence of chemical or physical cross-links. When hydrogels come in contact with aqueous solutions, they can effectively sorb and retain the dissolved substances, depending on the nature of the monomeric units comprising the hydrogel. For this reason, hydrogels have been proposed in several studies as water purification agents. At the present work anionic hydrogels bearing negatively charged –COO- groups were prepared and investigated. These gels are based on sodium acrylate (ANa), either homopolymerized (poly(sodiumacrylate), PANa) or copolymerized (P(DMAM-co-ANa)) with N,N Dimethylacrylamide (DMAM). The hydrogels were used to extract some model organic dyes from water. It is found that cationic dyes are strongly sorbed and retained by the hydrogels, while sorption of anionic dyes was negligible. In all cases it was found that both maximum sorption capacity and equilibrium binding constant varied from one dye to the other depending on the chemical structure of the dye, the presence of functional chemical groups and the hydrophobic-hydrophilic balance. Finally, the nonionic hydrogel of the homopolymer poly(N,Ndimethylacrylamide), PDMAM, was also used for reasons of comparison.

MFCA: An Environmental Management Accounting Technique for Optimal Resource Efficiency in Production Processes

Revenue leakages are one of the major challenges manufacturers face in production processes, as most of the input materials that should emanate as products from the lines are lost as waste. Rather than generating income from material input which is meant to end-up as products, losses are further incurred as costs in order to manage waste generated. In addition, due to the lack of a clear view of the flow of resources on the lines from input to output stage, acquiring information on the true cost of waste generated have become a challenge. This has therefore given birth to the conceptualization and implementation of waste minimization strategies by several manufacturing industries. This paper reviews the principles and applications of three environmental management accounting tools namely Activity-based Costing (ABC), Life-Cycle Assessment (LCA) and Material Flow Cost Accounting (MFCA) in the manufacturing industry and their effectiveness in curbing revenue leakages. The paper unveils the strengths and limitations of each of the tools; beaming a searchlight on the tool that could allow for optimal resource utilization, transparency in production process as well as improved cost efficiency. Findings from this review reveal that MFCA may offer superior advantages with regards to the provision of more detailed information (both in physical and monetary terms) on the flow of material inputs throughout the production process compared to the other environmental accounting tools. This paper therefore makes a case for the adoption of MFCA as a viable technique for the identification and reduction of waste in production processes, and also for effective decision making by production managers, financial advisors and other relevant stakeholders.

Smart Grids Cyber Security Issues and Challenges

The energy need is growing rapidly due to the population growth and the large new usage of power. Several works put considerable efforts to make the electricity grid more intelligent to reduce essentially energy consumption and provide efficiency and reliability of power systems. The Smart Grid is a complex architecture that covers critical devices and systems vulnerable to significant attacks. Hence, security is a crucial factor for the success and the wide deployment of Smart Grids. In this paper, we present security issues of the Smart Grid architecture and we highlight open issues that will make the Smart Grid security a challenging research area in the future.

Coefficients of Some Double Trigonometric Cosine and Sine Series

In this paper, the results of Kano from one dimensional cosine and sine series are extended to two dimensional cosine and sine series. To extend these results, some classes of coefficient sequences such as class of semi convexity and class R are extended from one dimension to two dimensions. Further, the function f(x, y) is two dimensional Fourier Cosine and Sine series or equivalently it represents an integrable function or not, has been studied. Moreover, some results are obtained which are generalization of Moricz’s results.

Model Predictive Control of Three Phase Inverter for PV Systems

This paper presents a model predictive control (MPC) of a utility interactive three phase inverter (TPI) for a photovoltaic (PV) system at commercial level. The proposed model uses phase locked loop (PLL) to synchronize the TPI with the power electric grid (PEG) and performs MPC control in a dq reference frame. TPI model consists of a boost converter (BC), maximum power point tracking (MPPT) control, and a three-leg voltage source inverter (VSI). The operational model of VSI is used to synthesize the sinusoidal current and track the reference. The model is validated using a 35.7 kW PV system in Matlab/Simulink. Implementation results show simplicity and accuracy, as well as reliability of the model.

Enhanced Imperialist Competitive Algorithm for the Cell Formation Problem Using Sequence Data

Imperialist Competitive Algorithm (ICA) is a recent meta-heuristic method that is inspired by the social evolutions for solving NP-Hard problems. The ICA is a population-based algorithm which has achieved a great performance in comparison to other metaheuristics. This study is about developing enhanced ICA approach to solve the Cell Formation Problem (CFP) using sequence data. In addition to the conventional ICA, an enhanced version of ICA, namely EICA, applies local search techniques to add more intensification aptitude and embed the features of exploration and intensification more successfully. Suitable performance measures are used to compare the proposed algorithms with some other powerful solution approaches in the literature. In the same way, for checking the proficiency of algorithms, forty test problems are presented. Five benchmark problems have sequence data, and other ones are based on 0-1 matrices modified to sequence based problems. Computational results elucidate the efficiency of the EICA in solving CFP problems.

Mobile App versus Website: A Comparative Eye-Tracking Case Study of Topshop

The UK is leading in online retail and mobile adoption. However, there is a dearth of information relating to mobile apparel retail, and developing an understanding about consumer browsing and purchase behaviour in m-retail channel would provide apparel marketers, mobile website and app developers with the necessary understanding of consumers’ needs. Despite the rapid growth of mobile retail businesses, no published study has examined shopping behaviour on fashion mobile apps and websites. A mixed method approach helped to understand why fashion consumers prefer websites on smartphones, when diverse mobile apps are also available. The following research methods were employed: survey, eye-tracking experiments, observation, and interview with retrospective think aloud. The mobile gaze tracking device by SensoMotoric Instruments was used to understand frustrations in navigation and other issues facing consumers in mobile channel. This method helped to validate and compliment other traditional user-testing approaches in order to optimize user experience and enhance the development of mobile retail channel. The study involved eight participants - females aged 18 to 35 years old, who are existing mobile shoppers. The participants used the Topshop mobile app and website on a smart phone to complete a task according to a specified scenario leading to a purchase. The comparative study was based on: duration and time spent at different stages of the shopping journey, number of steps involved and product pages visited, search approaches used, layout and visual clues, as well as consumer perceptions and expectations. The results from the data analysis show significant differences in consumer behaviour when using a mobile app or website on a smart phone. Moreover, two types of problems were identified, namely technical issues and human errors. Having a mobile app does not guarantee success in satisfying mobile fashion consumers. The differences in the layout and visual clues seem to influence the overall shopping experience on a smart phone. The layout of search results on the website was different from the mobile app. Therefore, participants, in most cases, behaved differently on different platforms. The number of product pages visited on the mobile app was triple the number visited on the website due to a limited visibility of products in the search results. Although, the data on traffic trends held by retailers to date, including retail sector breakdowns for visits and views, data on device splits and duration, might seem a valuable source of information, it cannot explain why consumers visit many product pages, stay longer on the website or mobile app, or abandon the basket. A comprehensive list of pros and cons was developed by highlighting issues for website and mobile app, and recommendations provided. The findings suggest that fashion retailers need to be aware of actual consumers’ behaviour on the mobile channel and their expectations in order to offer a seamless shopping experience. Added to which is the challenge of retaining existing and acquiring new customers. There seem to be differences in the way fashion consumers search and shop on mobile, which need to be explored in further studies.

An Innovative Approach to Improve Skills of Students in Qatar University Spending in Virtual Class through Learning Management System

In this study, students’ learning has been investigated and satisfaction in one of the course offered at Qatar University Foundation Program. Innovative teaching has been implied methodology that emphasizes on enhancing students’ thinking skills, decision making, and problem solving skills. Some interesting results were found which could be used to further improvement of the teaching methodology. In Fall 2012 in Foundation Program Math department at Qatar University has started implementing new ways of teaching Math by introducing MyMathLab (MML) as an innovative interactive tool in addition of the use Blackboard to support standard teaching such as Discussion board in Virtual class to engage students outside of classroom and to enhance independent, active learning that promote students’ critical thinking skills, decision making, and problem solving skills through the learning process.

CFD Analysis of Passive Cooling Building by Using Solar Chimney System

This research presents the design and analysis of solar air-conditioning systems particularly solar chimney which is a passive strategy for natural ventilation, and demonstrates the structures of these systems’ using Computational Fluid Dynamic (CFD) and finally compares the results with several examples, which have been studied experimentally and carried out previously. In order to improve the performance of solar chimney system, highly efficient sub-system components are considered for the design. The general purpose of the research is to understand how efficiently solar chimney systems generate cooling, and is to improve the efficient of such systems for integration with existing and future domestic buildings.

MCDM Spectrum Handover Models for Cognitive Wireless Networks

Spectrum handover is a significant topic in the cognitive radio networks to assure an efficient data transmission in the cognitive radio user’s communications. This paper proposes a comparison between three spectrum handover models: VIKOR, SAW and MEW. Four evaluation metrics are used. These metrics are, accumulative average of failed handover, accumulative average of handover performed, accumulative average of transmission bandwidth and, accumulative average of the transmission delay. As a difference with related work, the performance of the three spectrum handover models was validated with captured data of spectrum occupancy in experiments performed at the GSM frequency band (824 MHz - 849 MHz). These data represent the actual behavior of the licensed users for this wireless frequency band. The results of the comparison show that VIKOR Algorithm provides a 15.8% performance improvement compared to SAW Algorithm and, it is 12.1% better than the MEW Algorithm.