Optimization of Drinking Water Treatment Processes Using Artificial Neural Network

Drinking water treatment is the process of removing microorganisms and solid from water through different methods such as coagulation and filtration. Artificial neural network (ANN) was developed for process and cost optimization of drinking water treatment processes. Results obtained from ANN model showed that ANN is a suitable tool for the improvement of overall process performance and cost effectiveness in drinking water treatment. There was cost reduction, process safety improvement, and high stability in ANN application of water treatment

Fraud Detection In Mobile Communications Networks Using User Profiling And Classification Techniques

Fraud detection is an important application, since network operators lose a relevant portion of their revenue to fraud. The intentions of mobile phone users cannot be well observed except through the call data. The call data is used in describing behavioural patterns of users. Neural networks and probabilistic models are employed in learning these usage patterns from call data by detecting changes in established usage patterns or to recognize typical usage patterns of fraud. The methods are shown to be effective in detecting fraudulent behaviour by empirically testing the methods with data from real mobile communications networks.Keywords: Call data, fraud detection, neural networks, probabilistic models, user profilin

Incentive issues in the South African construction industry: Preliminary findings from project stakeholders

Incentives are regarded as motivational tools which can be used to propel construction workforces to achieve project objectives. This article contributes to the existing body of knowledge by evaluating the current practices of incentive mechanisms in the South African construction industry and identifying the challenges confronting the use of incentives. The study adopts both qualitative and quantitative methods for data collection. For the quantitative approach, a total number of 52 project stakeholders practising in Gauteng participated in the survey by completing the structured questionnaire. The questionnaire survey is used to obtain information from respondents, in order to assess their perceptions on the impact of current practices of incentives on work productivity and the construction industry. For the qualitative approach, personal interviews were conducted with selected respondents to clarify their answers. The findings reveal ‘unattainable project goals’, ‘poor communication processes’, and ‘inappropriate contractual arrangement’ as the most significant challenges confronting the use of incentives in the South African construction industry. The findings reported in this article show problems frustrating the absolute absorption of incentives in the industry, and also contribute to redesigning the incentive plan so as to improve project performance

Route optimization for solid waste collection: Onitsha (Nigeria) case study

Routing of solid waste collection vehicles in developing countries poses a challenging task. New decision procedure for solid waste collection problem was introduced in this study. The problem objective was to minimize the overall cost, which was essentially based on the distance travelled by vehicle. The study proposed heuristic method to generate feasible solution to an extended Capacitated Arc Routing Problem (CARP) on undirected network, inspired by the refuse collection problems in Nigeria. The heuristic procedure consists of route first, cluster second method. The computational experience with the heuristic in Onitsha was presented. The technique was compared with the existing schedule with respect to cost, time and distance travelled. The adoption of the proposed heuristic in Onitsha resulted in reduction of the number of existing vehicles, a 22.86% saving in refuse collection cost and 16.31% reduction in vehicle distance travelled per day. The result revealed a good performance of the proposed heuristic method, which would be useful in vehicle scheduling. @ JASE

A Hybrid Web Caching Design Model for Internet-Content Delivery

The need for online contents (or resources) to be shared and distributed in a large and sophisticated networks of users, geographical dispersed location of servers and their clients, time taken to fulfil clients requests pose major challenge. Therefore the choice of suitable architecture forInternet-based content delivery (ICD) technologies readily comes to mind. To achieve this, Akamai and Gnutella Web technologies are extensively reviewed to identify their strengths and weakness because of their popularity across the world for delivering contents. This new design for Internet-based content distribution is called AkaGnu because of the extra layer (Gnutella network)inserted into Akamai architecture, which provides greater Internet edge over each technology deployed independently. The paper presents a new ICD technology that performs better than Akamai system as a result of new features and behaviours introduced that reduce network traffic, more clients Internet connectivity, increase file sharing, improved speed of contents deliveries, andenhanced network security.Keywords/Index Terms- ICD, Akamai, Gnutella, peer-to-peer, AkaGnu, network traffic, security, architecture, technolog

Modeling for incentive payoffs in the Nigerian construction industry

Incentives are mechanisms used to create genuine opportunity for contracting parties to work together to achieve good results, rational returns and bear appropriate risks. The question of how to motivate the construction workforce rightly so as to achieve best performance has remained paramount to project owners. This paper investigates on how to model for incentive payoffs in the Nigerian construction industry in order to effectively utilise the benefits of incentive mechanisms. The collected data are analysed using descriptive and inferential statistics, such as frequency counts, charts and principal component analysis. The findings reveal the metrics for measuring organisational incentive payoff and the scaling factor for each metric. The study further develops the employee incentive payoff models for both operational workers and management staff in the construction sector. This study provides a practical solution to the application of incentive mechanisms in construction projects. The paper recommends the need for restructuring of incentive mechanisms to significantly impact on other performance criteria therefore contributing to best performance in project delivery.http://www.emeraldinsight.com/loi/jedthb2017Construction Economic

Construction employees’ perspectives on workforce motivational drivers in Akwa Ibom State of Nigeria

PURPOSE: The global demand for increase in construction activity necessitates the improvement of project performance. In the construction industry, motivation is seen as an intermediate variable between principle project activity and project performance. This paper assesses the positive motivational drivers that can propel construction employees’ behaviours towards achieving project success. METHODOLOGY: The literature scan between 2000 and 2012 reveals thirty-three employee motivational drivers; these were selected for the research. The study adopts qualitative and quantitative methods to evaluate current practices and identifies the most significant motivating drivers in the Akwa Ibom State of Nigeria. FINDINGS: The results show that the majority of respondents agreed on the use of rewards for achieving optimal outputs. The professional and personal developments of employees have not been promoted efficiently by their employers. Prospects of promotion, participation in decision making and respect for people are ranked as the most significant employee motivational drivers. VALUE OF RESEARCH: The findings create an insight for the construction practitioners to gain better understanding of the key areas to focus on in order to achieve optimal outputshttp://asocsa.org/publications.htmam201

Incentive issues in the South African construction industry : preliminary findings from project stakeholders

Incentives are regarded as motivational tools which can be used to propel construction workforces to achieve project objectives. This article contributes to the existing body of knowledge by evaluating the current practices of incentive mechanisms in the South African construction industry and identifying the challenges confronting the use of incentives. The study adopts both qualitative and quantitative methods for data collection. For the quantitative approach, a total number of 52 project stakeholders practising in Gauteng participated in the survey by completing the structured questionnaire. The questionnaire survey is used to obtain information from respondents, in order to assess their perceptions on the impact of current practices of incentives on work productivity and the construction industry. For the qualitative approach, personal interviews were conducted with selected respondents to clarify their answers. The findings reveal ‘unattainable project goals’, ‘poor communication processes’, and ‘inappropriate contractual arrangement’ as the most significant challenges confronting the use of incentives in the South African construction industry. The findings reported in this article show problems frustrating the absolute absorption of incentives in the industry, and also contribute to redesigning the incentive plan so as to improve project performance.Aansporingsmaatreëls word as motiveringswerktuig beskou wat gebruik kan word om die werkerskorps aan te spoor om sodoende prestasiedoelwitte te bereik. Hierdie artikel dra by tot die kennisgebied deur huidige praktyke van aansporingsmeganismes in die Suid-Afrikaanse konstruksiebedryf te evalueer asook die uitdagings wat met die gebruik van aansporingsmaatreëls gepaard gaan. Die studie maak gebruik van beide kwalitatiewe en kwantitatiewe metodes vir data-insamelingdoeleindes. Vir die kwalitatiewe benadering het ‘n totaal van 52 projekbelanghebbendes, wat in Gauteng praktiseer, aan die opname deelgeneem deur die gestruktureerde vraelys te voltooi. Die vraelysopname is gebruik om inligting van respondente te bekom om sodoende hul waarneming oor die impak van huidige praktyke van aansporingsmaatreëls op produktiwiteit van arbeid en die konstruksiebedryf te toets. Vir die kwalitatiewe benadering is persoonlike onderhoude gevoer met sommige van die respondente om antwoorde te verklaar. Die bevindinge toon “onbereikbare projekdoelwitte”, “swak kommunikasieprosesse” en “nie-toepaslike kontraktuele ooreenkomste” as die belangrikste uitdagings waarmee die aansporingskwessies in die Suid-Afrikaanse konstruksiebedryf te make het. Die bevindinge wat in hierdie artikel uitgelig word, dui op probleme wat ondervind word met die volkome aanvaarding en dwarsboming van aansporingsmaatreëls in die bedryf. Verder dra die artikel ook by tot ‘n nuwe benadering vir die herontwerp van die aansporingsplan om projekprestasie te verbeter.http://reference.sabinet.co.za/sa_epublication/structam201

Neural network and classification approach in identifying customer behavior in the banking sector: A case study of an international bank

The customer relationship focus for banks is in development of main competencies and strategies of building strong profitable customer relationships through considering and managing the customer impression, influence on the culture of the bank, satisfactory treatment, and assessment of valued relationship building. Artificial neural networks (ANNs) are used after data segmentation and classification, where the designed model register records into two class sets, that is, the training and testing sets. ANN predicts new customer behavior from previously observed customer behavior after executing the process of learning from existing data. This article proposes an ANN model, which is developed using a six-step procedure. The back-propagation algorithm is used to train the ANN by adjusting its weights to minimize the difference between the current ANN output and the desired output. An evaluation process is conducted to determine whether the ANN has learned how to perform. The training process is halted periodically, and its performance is tested until an acceptable result is obtained. The principles underlying detection software are grounded in classical statistical decision theory

Comparative Studies of Different Imputation Methods for Recovering Streamflow Observation

Faulty field sensors cause unreliability in the observed data that needed to calibrate and assess hydrology models. However, it is illogical to ignore abnormal or missing values if there are limited data available. This study addressed this problem by applying data imputation to replace incorrect values and recover missing streamflow information in the dataset of the Samho gauging station at Taehwa River (TR), Korea from 2004 to 2006. Soil and Water Assessment Tool (SWAT) and two machine learning techniques, Artificial Neural Network (ANN) and Self Organizing Map (SOM), were employed to estimate streamflow using reasonable flow datasets of Samho station from 2004 to 2009. The machine learning models were generally better at capturing high flows, while SWAT was better at simulating low flows.open