A Comprehensive Survey on Comparisons across Contextual Pre-filtering, Contextual Post-filtering and Contextual Modelling Approaches

Recently, there has been growing interest in recommender systems (RS) and particularly in context-aware RS. Methods for generating context-aware recommendations are classified into pre-filtering, post-filtering and contextual modelling approaches. In this paper, we present the several novel approaches of the different variant of each of these three contextualization paradigms and present a complete survey on the state-of-the-art comparisons across them. We then identify the significant challenges that require being addressed by the current RS researchers, which will help academicians and practitioners in comparing these three approaches to select the best alternative according to their strategies

Investigating rendering speed and download rate of three-dimension (3D) mobile map intended for navigation aid using genetic algorithm

Prior studies have shown that rendering 3D map dataset in mobile device in a wireless network depends on the download speed. Crucial to that is the mobile device computing resource capabilities. Now it has become possible with a wireless network to render large and detailed 3D map of cities in mobile devices at interactive rates of over 30 frame rate per second (fps). The information in 3D map is generally limited and lack interaction when it’s not rendered at interactive rate; on the other hand, with high download rate 3D map is able to produce a realistic scene for navigation aid. Unfortunately, in most mobile navigation aid that uses a 3D map over a wireless network could not serve the needs of interaction, because it suffers from low rendering speed. This paper investigates the trade-off between rendering speed and download rate of the 3D mobile map using genetic algorithm (GA). The reason of using GA is because it takes larger problem space than other algorithms for optimization, which is well suited for establishing fast 3D map rendering speed on-the-fly to the mobile device that requires useful solutions for optimization. Regardless of mobile device’s computing resources, our finding from GA suggest that download rate and rendering speed are mutually exclusive. Thus, manipulated static aerial photo-realistic images instead of 3D map are well-suited for navigation aid

Financial Data and a New Generalization of the Skew-T Distribution

This work introduces a three-parameter hybrid model named the exponentiated half logistic skew-t distribution using the exponentiated half logistic generalised distributions. The hybrid model is appropriate for modelling skewed, heavy-and-long-tail datasets. The theoretical properties of the new model were investigated. Simulation studies performed to evaluate the finite sample performance of the parameter estimates using selected true parameter values showed that the estimates approached the true values as the sample size increased. The hybrid model efficacy, applicability and flexibility were demonstrated using the Nigeria inflation rate dataset, and the result indicated that the hybrid model outperformed several competing distributions

Investigating digital watermark dynamics on carrier file by feed-forward neural network

Carrier files are commonly described as host files in digital watermarking in which hidden files are embedded on it. As a result, new files are formed which contain the hidden files or messages. This paper aim at resolving the problem of capacity in Image watermarking and utilizes the bits ratios of the watermark and carrier file as the raw data for analysis. The data are obtained from the result of the first project undertaken to determine the implementation of different applications available in the public domain for embedding a watermark. Feed-forward neural network (FFNN) is used for analysis because is applicable to a wide range of forecasting problems and yields a high degree of accuracy for the bits ratios of watermark and host. The result indicates the relationship between the carrier file and the hidden file, which establishes a pattern where the larger the bits of the carrier file, the larger the watermark bits and vice versa. Although this is only in terms of Image watermarking. Further studies should apply the same technique on video and audio watermarkin

Throughput analysis of TCP congestion control algorithms in a cloud based collaborative virtual environment

Collaborative Virtual Environment (CVE) has become popular in the last few years, this is because CVE is designed to allow geographically distributed users to work together over the network. In CVE the state of the virtual objects is witnessing unprecedentant change. When a user performs an action in CVE, the information of the action needs to be transmitted to other users to maintain consistency in the cooperative work. TCP is the most widely used protocol in the design of CVE, and its throughput deteriorates in the network with large delay. Gital et al, 2014 proposes a cloud based architectural model for improving scalability and consistency in CVE. Therefore, this paper aim at evaluating and comparing the performance of different TCP variant (Tahoe, Reno, New Reno, Vegas, SACK, Fack and Linux) with the cloud based CVE architecture to determine the suitability of each TCP variant for CVE. A comparative analysis between the different TCP variants is presented in terms of throughput verses elapse time, with increasing number of users in the system. TCP with the cloud based model was found to be effective, promising and robust for achieving consistency requirement in CVE system

Multimedia and its relevance to education

The use of multimedia services in education is playing a vital role in the recent advancement in educational sector. The growth in the use of multimedia in Malaysian educational sector has increased rapidly in recent years and expected to continue in the future. It is believe that using multimedia elements in teaching and learning is pleasing and motivates students to acquire knowledge

A review on soft set-based parameter reduction and decision making

Many real world decision making problems often involve uncertainty data, which mainly originating from incomplete data and imprecise decision. The soft set theory as a mathematical tool that deals with uncertainty, imprecise, and vagueness is often employed in solving decision making problem. It has been widely used to identify irrelevant parameters and make reduction set of parameters for decision making in order to bring out the optimal choices. In this paper, we present a review on different parameter reduction and decision making techniques for soft set and hybrid soft sets under unpleasant set of hypothesis environment as well as performance analysis of the their derived algorithms. The review has summarized this paper in those areas of research, pointed out the limitations of previous works and areas that require further research works. Researchers can use our review to quickly identify areas that received diminutive or no attention from researchers so as to propose novel methods and applications

Utilising key climate element variability for the prediction of future climate change using a support vector machine model

This paper proposes a support vector machine (SVM) model to advance the prediction accuracy of global land-ocean temperature (GLOT), which is globally significant for understanding the future pattern of climate change. The GLOT dataset was collected from NASA’s GLOT index (C) (anomaly with base: 1951–1980) for the period 1880 to 2013. We categorise the dataset by decades to describe the behaviour of the GLOT within those decades. The dataset was used to build an SVM Model to predict future values of the GLOT. The performance of the model was compared with a multilayer perceptron neural network (MLPNN) and validated statistically. The SVM was found to perform significantly better than the MLPNN in terms of mean square error and root mean square error, although computational times for the two models are statistically equal. The SVM model was used to project the GLOT from the pre-existing NASA’s GLOT index (C) (anomaly with base: 1951–1980) for the next 20 years (2013–2033). The projection results of our study can be of value to policy makers, such as the intergovernmental organisations related to environmental studies, e.g., the intergovernmental panel on climate change (IPCC)

Visualisation of a three-dimensional (3D) object’s optimal reality in a 3D map on a mobile device

Prior research on the subject of visualisation of three-dimensional (3D) objects by coordinate systems has proved that all objects are translated so that the eye is at the origin (eye space). The multiplication of a point in eye space leads to perspective space, and dividing perspective space leads to screen space. This paper utilised these findings and investigated the key factor(s) in the visualisation of 3D objects within 3D maps on mobile devices. The motivation of the study comes from the fact that there is a disparity between 3D objects within a 3D map on a mobile device and those on other devices; this difference might undermine the capabilities of a 3D map view on a mobile device. This concern arises while interacting with a 3D map view on a mobile device. It is unclear whether an increasing number of users will be able to identify the real world as the 3D map view on a mobile device becomes more realistic. We used regression analysis intended to rigorously explain the participants’ responses and the Decision Making Trial and Evaluation Laboratory method (DEMATEL) to select the key factor(s) that caused or were affected by 3D object views. The results of regression analyses revealed that eye space, perspective space and screen space were associated with 3D viewing of 3D objects in 3D maps on mobile devices and that eye space had the strongest impact. The results of DEMATEL using its original and revised version steps showed that the prolonged viewing of 3D objects in a 3D map on mobile devices was the most important factor for eye space and a long viewing distance was the most significant factor for perspective space, while large screen size was the most important factor for screen space. In conclusion, a 3D map view on a mobile device allows for the visualisation of a more realistic environment

An Alternative Algorithm for Soft Set Parameter Selection using Special Order

The outcome of the reduction of soft data is dependent on the quality and discount evidence that increases with optimization analysis. There is a set of techniques that can be used to reduce the data, but the different techniques showed different results as each technique is focused on solving a particular problem. This paper proposed a parameter reduction algorithm, known as 3C algorithm, to circumvent the false frequent object in reduction. Results indicated that the proposed algorithm is easy to implement and perform better than the state-of-the-art parameter reduction algorithm. Also, the proposed algorithm can be used as an effective alternative method for reducing parameters in order to enhance the decision making process. Comparative analysis were performed between the proposed algorithm and the state-of-the-art parameter reduction algorithm using several soft set in terms of parameter reductio