Evolving Recurrent Neural Network using Cartesian Genetic Programming to Predict The Trend in Foreign Currency Exchange Rates

Forecasting the foreign exchange rate is an uphill task. Numerous methods have been used over the years to develop an efficient and reliable network for forecasting the foreign exchange rate. This study utilizes recurrent neural networks (RNNs) for forecasting the foreign currency exchange rates. Cartesian genetic programming (CGP) is used for evolving the artificial neural network (ANN) to produce the prediction model. RNNs that are evolved through CGP have shown great promise in time series forecasting. The proposed approach utilizes the trends present in the historical data for its training purpose. Thirteen different currencies along with the trade-weighted index (TWI) and special drawing rights (SDR) is used for the performance analysis of recurrent Cartesian genetic programming-based artificial neural networks (RCGPANN) in comparison with various other prediction models proposed to date. The experimental results show that RCGPANN is not only capable of obtaining an accurate but also a computationally efficient prediction model for the foreign currency exchange rates. The results demonstrated a prediction accuracy of 98.872 percent (using 6 neurons only) for a single-day prediction in advance and, on average, 92% for predicting a 1000 days’ exchange rate in advance based on ten days of data history. The results prove RCGPANN to be the ultimate choice for any time series data prediction, and its capabilities can be explored in a range of other fields.     

Enhanced dynamic credential generation scheme for protection of user identity in mobile-cloud computing

To improve the resource limitation of mobile devices, mobile users may utilize cloud-computational and storage services. Although the utilization of the cloud services improves the processing and storage capacity of mobile devices, the migration of confidential information on untrusted cloud raises security and privacy issues. Considering the security of mobile-cloud-computing subscribers’ information, a mechanism to authenticate legitimate mobile users in the cloud environment is sought. Usually, the mobile users are authenticated in the cloud environment through digital credential methods, such as password. Once the users’ credential information theft occurs, the adversary can use the hacked information for impersonating the mobile user later on. The alarming situation is that the mobile user is unaware about adversary’s malicious activities. In this paper, a light-weight security scheme is proposed for mobile user in cloud environment to protect the mobile user’s identity with dynamic credentials. The proposed scheme offloads the frequently occurring dynamic credential generation operations on a trusted entity to keep minimum processing burden on the mobile device. To enhance the security and reliability of the scheme, the credential information is updated frequently on the basis of mobile-cloud packets exchange. Furthermore, the proposed scheme is compared with the existing scheme on the basis of performance metrics i.e. turnaround time and energy consumption. The experimental results for the proposed scheme showed significant improvement in turnaround time and energy consumption as compared to the existing scheme.     

Chronic growth faltering amongst a birth cohort of Indian children begins prior to weaning and is highly prevalent at three years of age

Background  

Poor growth of children in developing countries is a major public health problem associated with mortality, morbidity and developmental delay. We describe growth up to three years of age and investigate factors related to stunting (low height-for-age) at three years of age in a birth cohort from an urban slum.     

Immobilization of acrylamide-modified oligonucleotides by co-polymerization

A flexible chemistry for solid phase attachment of oligonucleotides is described. Oligonucleotides bearing 5'-terminal acrylamide modifications efficiently co-polymerize with acrylamide monomers to form thermally stable DNA-containing polyacrylamide co-polymers. Co-polymerization attachment is specific for the terminal acrylamide group. Stable probe-containing layers are easily fabricated on supports bearing exposed acrylic groups, including plastic microtiter plates and silanized glass. Attachment can be accomplished using standard polyacrylamide gel recipes and polymerization techniques. Supports having a high surface density of hybridizable oligonucleotide (approximately 200 fmol/mm2) can be produced.     

Standardization of work-a statistical approach using spreadsheet

One of the techniques of work study is work measurement employed to ensure the best possible use of human in carrying out a specific activity. Using appropriate measurement procedures, a work standard can be set which will reflect the gross time required by a normal operator working under normal conditions and with normal pace to complete a unit of work satisfactorily. One of the approaches in setting the work standard is based on the statistical analysis of time data. This paper presents a method of establishing work standard by generating statistical control chart using Excell -- an integrated spreadsheet and graphics software for the Apple-Macintosh.     

Eliciting information about organizational culture via laddering

Abstract. Eliciting information about organizational culture is an important part of system analysis and design. However, eliciting knowledge of this sort is difficult. Laddering is an established technique that is particularly suitable for eliciting information about goals and for eliciting explanations, which are important issues when investigating organizational culture. This paper describes the method, its strengths and limitations, its use in several case studies and its relation to other elicitation techniques. Recommendations for further work are given.     

Use of radial basis functions for estimating monthly mean daily solar radiation

The present study utilizes the radial basis functions technique for the estimation of monthly mean daily values of solar radiation falling on horizontal surfaces and compares its performance with that of the multilayer perceptrons network and a classical regression model. In this work, we use solar radiation data from 41 stations that are spread over the Kingdom of Saudi Arabia. The solar radiation data from 31 locations are used for training the neural networks and the data from the remaining 10 locations are used for testing the estimated values. However, the testing data were not used in the modeling or training of the networks to give an indication of the performance of the system at unknown locations. Results indicate the viability of the radial basis for this kind of problem.     

Forced migration of soluble and suspended materials by freezing front in aqueous systems

Migration of soluble and suspended materials by directional freezing of aqueous systems has been studied qualitatively. Slow freezing was employed vertically as well as horizontally through solutions and suspensions. In all cases, the impurities (soluble salts as well as suspended materials) were appreciably forced out by dynamic freezing front. The phenomenon worked for concentrating/separating inorganic ions, soluble organic compounds and dyes in synthetic solutions as well as in natural streams. Various analytical techniques were employed to monitor the migrating species through the freezing media. It was found that separation efficiency depends on different factors like rate of cooling, pH and concentration. Model experiments were designed and exercised successfully to employ the technique for treatment of dye-polluted water.