How Business Intelligence Can Help You to Better Understand Your Customers

Companies can incur heavy losses when customers do not return; therefore, they need to have a better understanding of their customers' behaviors in order to improve service and products. And nowadays, there are multiple resources of customers' data especially with web services, such as websites, chatbots, emails, social media, PoS, ERP, CRM, SCM, therefore, it becomes difficult to collect all this huge data altogether and analyze it manually This paper highlights the role of business intelligence in improving the relationship with the customers, and explores the techniques used to analyze customers' data in order to predict their demands and reach their satisfaction

Leveraging on Digital Technologies to Up-Scale Tourism for Economic Growth in Africa

The application of digital technologies in various human endeavours today is unabated. This article presents information and communications technologies (ICTs) as a driving force for promoting tourism in Africa for accelerated economic growth. Descriptive methodology was used in the study. The study relied on the explored impacts of tourism on socio-economic development of the developing nations of Africa and encourages the adoption of persona models in implementing technological strategies geared toward the promotion of tourism products and services on the continent. The article advocates technology compliance by all tourism organizations and involvement of all stakeholders, agencies of governments and ICT drivers in making Africa a destination of choice to the world by adopting appropriate technological provisions

Evaluation of Multi-Peer and Self-Assessment in Higher Education: A Brunei Case Study

This article presents an evaluation of the use of peer and self-assessment as part of the learning process in a public speaking assessment coursework, with students from two departments taking part. Students were assessed by themselves, their peers and the lecturer using an online platform, Google forms, utilizing a set of rubrics. The marks were compared between markers to identify similarities and differences. After the process, student feedback on the experience was obtained using a questionnaire utilizing the Likert seven point scale to rate different questions. Analysis of the marks awarded found that whilst there might be correlations between different markers (i.e. peer – self) for marks on certain subsections of the work, there was no overall correlation between marks. Student perceptions to the exercise indicated that the use of rubrics was well received; students considered it a fair assessment method and it provided information on how to perform well in the assessment

Applying the Computational Intelligence Paradigm to Nuclear Power Plant Operation: A Review (1990-2015)

In the guise of artificial neural networks (ANNs), genetic/evolutionary computation algorithms (GAs/ECAs), fuzzy logic (FL) inference systems (FLIS) and their variants as well as combinations, the computational intelligence (CI) paradigm has been applied to nuclear energy (NE) since the late 1980s as a set of efficient and accurate, non-parametric, robust-to-noise as well as to-missing-information, non-invasive on-line tools for monitoring, predicting and overall controlling nuclear (power) plant (N(P)P) operation. Since then, the resulting CI-based implementations have afforded increasingly reliable as well as robust performance, demonstrating their potential as either stand-alone tools, or - whenever more advantageous - combined with each other as well as with traditional signal processing techniques. The present review is focused upon the application of CI methodologies to the - generally acknowledged as - key-issues of N(P)P operation, namely: control, diagnostics and fault detection, monitoring, N(P)P operations, proliferation and resistance applications, sensor and component reliability, spectroscopy, fusion supporting operations, as these have been reported in the relevant primary literature for the period 1990-2015. At one end, 1990 constitutes the beginning of the actual implementation of innovative, and – at the same time – robust as well as practical, directly implementable in H/W, CI-based solutions/tools which have proved to be significantly superior to the traditional as well as the artificial-intelligence-(AI)derived methodologies in terms of operation efficiency as well as robustness-to-noise and/or otherwise distorted/missing information. At the other end, 2015 marks a paradigm shift in terms of the emergent (and, swiftly, ubiquitous) use of deep neural networks (DNNs) over existing ANN architectures and FL problem representations, thus dovetailing the increasing requirements of the era of complex - as well as Big - Data and forever changing the means of ANN/neuro-fuzzy construction and application/performance. By exposing the prevalent CI-based tools for each key-issue of N(P)P operation, overall as well as over time for the given 1990-2015 period, the applicability and optimal use of CI tools to NE problems is revealed, thus providing the necessary know-how concerning crucial decisions that need to be made for the increasingly efficient as well as safe exploitation of NE

Deep Convolutional Neural Networks for Customer Churn Prediction Analysis

Several machine learning models have been proposed to address customer churn problems. In this work, the authors used a novel method by applying deep convolutional neural networks on a labeled dataset of 18,000 prepaid subscribers to classify/identify customer churn. The learning technique was based on call detail records (CDR) describing customers activity during two-month traffic from a real telecommunication provider. The authors use this method to identify new business use case by considering each subscriber as a single input image describing the churning state. Different experiments were performed to evaluate the performance of the method. The authors found that deep convolutional neural networks (DCNN) outperformed other traditional machine learning algorithms (support vector machines, random forest, and gradient boosting classifier) with F1 score of 91%. Thus, the use of this approach can reduce the cost related to customer loss and fits better the churn prediction business use case

Connecting Enterprise Architecture and Project Portfolio Management: A Review and a Model for IT Project Alignment

Enterprise architecture (EA) and project portfolio management (PPM) are key areas when it comes to connecting enterprise strategy and information technology (IT) projects. Both management disciplines enhance business capabilities, integrate skilled resources, and govern affiliated processes and functions. A skillful comprehension of the links between these managerial areas is essential for effective IT planning. This article elaborates on the common grounds and structural attachment of EA and PPM, showing the substantiated relations between them and demonstrating their cohesiveness. From strategic planning to solution delivery, a conceptual model for IT project alignment integrates these IT management disciplines over two levels. EA ascertains the technical goals and constraints, whereas PPM determines the organizational goals and constraints. The results from both sides are combined to jointly propose, select, prioritize, and schedule IT projects. Roadmapping is a suitable approach to bring EA and PPM together

Evaluation of Autopsy and Volatility for Cybercrime Investigation: A Forensic Lucid Case Study

In this article, the authors successfully created two new plugins one for Autopsy Forensic Tool, and the other for Volatility Framework. Both plugins are useful for encoding digital evidences in Forensic Lucid which is the goal of this work. The first plugin was integrated in Autopsy to generate a report for the case of a Brute Force Authentication attack by looking for evidence in server logs based on a key search. On the other hand, the second plugin named ForensicLucidDeviceTree aims to find whether a device stack has been infected by a root-kit or not expression is implied by the previous statement. The results of both plugins are shown in Forensic Lucid Format and were successfully compiled using GIPC compiler

Mobile Health and Telemedicine: Awareness, Adoption and Importance of Health Study

In 2016, the U.S. Government health expenditures reached $3.35 trillion and the cost per person stood at$10,345. Health is seen as impacting both one's quality of life and finances. The Affordable Care Act (ACA) (2008 - 2016) brought the issue of cost to the forefront for all people especially those in the health disparate communities. Advances in health informatics coupled with new approaches to healthcare delivery may hold promise for this large industry in the USA that critically needs to be cost effective in order to sustain itself. This paper reports a study that investigated importance of health, mobile health (m-Health) and telemedicine awareness along with its adoption in a health disparate community that has one of the Historical Black Colleges & Universities (HBCUs) in the country. The findings were that, all participants owned a mobile (cell) phone with smart features. Although a large number them indicated that their health was very important to them, there was lack of awareness and adoption of m-Health and telemedicine

The Utilization of Social Media by Small and Medium Food Vendors in Brunei Darussalam

This research examines the factors that contribute to the utilization of social media by the small and medium-sized enterprises (SMEs) operating in the food industry in Brunei Darussalam. It also investigates how social media provides opportunities to SMEs. This research was done using a quantitative method through primary research that was focused on small and medium-sized food vendors in Brunei Darussalam. Survey questions were distributed to food SMEs and vendors, who use social media to assist them in conducting their business, to serve as a guideline to understand how social media networks can lead to positive business outcomes and how understanding key factors may lead to optimizing product portfolios and to discover new opportunities for their business to expand. Based on the authors' research, cost effectiveness was found to influence social media usage among the small and medium food vendors in Brunei. Factors such as trust, interactivity and compatibility, however were not found to be the factors influencing the utilization of social media

Identity Authentication Security Management in Mobile Payment Systems

Mobile payment is a new payment method offering users mobility, reachability, compatibility, and convenience. But mobile payment involves great uncertainty and risk given its electronic and wireless nature. Therefore, biometric authentication has been adopted widely in mobile payment in recent years. However, although technology requirements for secure mobile payment have been met, standards and consistent requirements of user authentication in mobile payment are not available. The flow management of user authentication in mobile payment is still at its early stage. Accordingly, this paper proposes an anonymous authentication and management flow for mobile payment to support secure transaction to prevent the disclosure of users' information and to reduce identity theft. The proposed management flow integrates transaction key generation, encryption and decryption, and matching to process users' personal information and biometric characteristics based on mobile equipment authentication carrier