The Effectiveness of an Instructional Program based on SCAMPER Strategy in Improving English Speaking Skills among and Vocabulary Fifth-Grade Students in Jordan

Abstract: This quasi-experimental study aimed at investigating the effectiveness of an instructional program based on SCAMPER strategy in improving speaking skills and vocabulary among fifth-grade students. The participants of the study were chosen from Al-Marwa elementary school in First Educational Directorate of Zarqa district, which was selected purposefully.Sixty-two participants were distributed randomly into an experimental group (n=32) and control group (n=30). The experimental group received the SCAMPER strategy for eight weeks during the first semester of the academic year 2019-2020, while the control group was taught using the conventional method.Pre-post speaking test was applied to both groups to collect the data. The results of this study showed that there were statistically significant differences at (α=0.05) between the mean scores of the two groups in the speaking test in favor of the experimental group. Therefore, the researcher recommended training teachers to use SCAMPER strategy in teaching English skills

Statistical Information of the Increased Demand for Watch the VOD with the Increased Sophistication in the Mobile Devices,Communications and Internet Penetration in Asia

As the rapid progress of the media streaming applications such as video streaming can be classified into two types of streaming, Live video streaming, Video on Demand (VoD). Live video streaming is a service which allows the clients to watch many TV channels over the internet and the clients able to use one operation to perform is to switch the channels. Video on Demand (VoD) is one of the most important applications for the internet of the future and has become an interactive multimedia service which allows the users to start watching the video of their choice at anytime and anywhere, especially after the rapid deployment of the wireless networks and mobile devices. In this paper provide statistical information about the Internet, communications and mobile devices etc. This has led to an increased demand for the development, communication and computational powers of many of the mobile wireless subscribers/mobile devices such as laptops, PDAs, smart phones and notebook. These techniques are utilized to obtain a video on demand service with higher resolution and quality. Another objective in this paper is to see Malaysia ranked as a fully developed country by the year 2020.Comment: 17 pages, 17 figures, 4 tables; The International Journal of Multimedia & Its Applications (IJMA) Vol.3, No.4, November 201

A new proactive feature selection model based on the enhanced optimization algorithms to detect DRDoS attacks

Cyberattacks have grown steadily over the last few years. The distributed reflection denial of service (DRDoS) attack has been rising, a new variant of distributed denial of service (DDoS) attack. DRDoS attacks are more difficult to mitigate due to the dynamics and the attack strategy of this type of attack. The number of features influences the performance of the intrusion detection system by investigating the behavior of traffic. Therefore, the feature selection model improves the accuracy of the detection mechanism also reduces the time of detection by reducing the number of features. The proposed model aims to detect DRDoS attacks based on the feature selection model, and this model is called a proactive feature selection model proactive feature selection (PFS). This model uses a nature-inspired optimization algorithm for the feature subset selection. Three machine learning algorithms, i.e., k-nearest neighbor (KNN), random forest (RF), and support vector machine (SVM), were evaluated as the potential classifier for evaluating the selected features. We have used the CICDDoS2019 dataset for evaluation purposes. The performance of each classifier is compared to previous models. The results indicate that the suggested model works better than the current approaches providing a higher detection rate (DR), a low false-positive rate (FPR), and increased accuracy detection (DA). The PFS model shows better accuracy to detect DRDoS attacks with 89.59%

A novel adaptive schema to facilitates playback switching technique for video delivery in dense LTE cellular heterogeneous network environments

The services of the Video on Demand (VoD) are currently based on the developments of the technology of the digital video and the network’s high speed. The files of the video are retrieved from many viewers according to the permission, which is given by VoD services. The remote VoD servers conduct this access. A server permits the user to choose videos anywhere/anytime in order to enjoy a unified control of the video playback. In this paper, a novel adaptive method is produced in order to deliver various facilities of the VoD to all mobile nodes that are moving within several networks. This process is performed via mobility modules within the produced method since it applies a seamless playback technique for retrieving the facilities of the VoD through environments of heterogeneous networks. The main components comprise two servers, which are named as the GMF and the LMF. The performance of the simulation is tested for checking clients’ movements through different networks with different sizes and speeds, which are buffered in the storage. It is found to be proven from the results that the handoff latency has various types of rapidity. The method applies smooth connections and delivers various facilities of the VoD. Meantime, the mobile device transfers through different networks. This implies that the system transports video segments easily without encountering any notable effects.In the experimental analysis for the Slow movements mobile node handoff latency (8 Km/hour or 4 m/s) ,the mobile device’s speed reaches 4m/s, the delay time ranges from 1 to 1.2 seconds in the proposed system, while the MobiVoD system ranges from 1.1 to 1.5. In the proposed technique reaches 1.1026 seconds forming the required time of a mobile device that is switching from a single network to its adjacent one. while the handoff termination average in the MobiVoD reaches 1.3098 seconds. Medium movement mobile node handoff latency (21 Km/ hour or 8 m/s) The average handoff time for the proposed system reaches 1.1057 seconds where this implies that this technique can seamlessly provide several segments of a video segments regardless of any encountered problems. while the average handoff time for the MobiVoD reaches 1.53006623 seconds. Furthermore, Fast movement mobile node handoff latency (390 Km/ hour or 20 m/s). The average time latency of the proposed technique reaches 1.0964 seconds, while the MobiVoD System reaches to 1.668225 seconds

The Impact of Brand Awareness, Digital Influencers, and Word of Mouth on Purchase Intentions: Evidence from Jordanian SMEs

Introduction: This study examines the definitional linkages between brand awareness, digital influencer marketing, word-of-mouth (WOM) communication, and purchase intentions within digital marketing contexts. The primary goal is to explore how these elements influence consumer purchasing decisions in the era of digital marketing. As the digital landscape continues to evolve, understanding the interplay between these factors becomes increasingly critical for marketers aiming to enhance customer engagement and drive sales.Methods: An online survey was distributed to 344 MSME (Micro, Small, and Medium Enterprises) owners, collecting data relevant to their perceptions of digital marketing, brand awareness, and their interactions with digital influencers and WOM communication. The research employed Partial Least Squares Structural Equation Modeling (PLS-SEM) for statistical analysis, using SmartPLS software to evaluate the relationships among the studied variables.Results: The findings indicate that digital influencer promotions, brand awareness, and WOM communication all exert strong positive effects on consumer purchase intentions. Specifically, digital influencer marketing and WOM interactions are significantly correlated with heightened brand awareness, which in turn positively influences consumer decisions to purchase. These results highlight the importance of leveraging digital marketing strategies that incorporate these elements to drive consumer buying intentions.Conclusions: The study demonstrates that digital marketing strategies based on brand awareness, influencer promotions, and WOM interactions can significantly enhance consumer purchase intentions. The findings offer new insights into how digital marketing approaches shape user behavior, providing valuable guidance for marketers to optimize their online marketing efforts. Further research should explore how these factors interact across different cultures and geographic regions, offering a broader understanding of their impact on global consumer behavior

Efficient approximate analytical methods for nonlinear fuzzy boundary value problem

This paper aims to solve the nonlinear two-point fuzzy boundary value problem (TPFBVP) using approximate analytical methods. Most fuzzy boundary value problems cannot be solved exactly or analytically. Even if the analytical solutions exist, they may be challenging to evaluate. Therefore, approximate analytical methods may be necessary to consider the solution. Hence, there is a need to formulate new, efficient, more accurate techniques. This is the focus of this study: two approximate analytical methods-homotopy perturbation method (HPM) and the variational iteration method (VIM) is proposed. Fuzzy set theory properties are presented to formulate these methods from crisp domain to fuzzy domain to find approximate solutions of nonlinear TPFBVP. The presented algorithms can express the solution as a convergent series form. A numerical comparison of the mean errors is made between the HPM and VIM. The results show that these methods are reliable and robust. However, the comparison reveals that VIM convergence is quicker and offers a swifter approach over HPM. Hence, VIM is considered a more efficient approach for nonlinear TPFBVPs

A Hybrid PSO-GCRA Framework for Optimizing Control Systems Performance

Optimization is essential for improving the performance of control systems, particularly in scenarios that involve complex, non-linear, and dynamic behaviors. This paper introduces a new hybrid optimization framework that merges Particle Swarm Optimization (PSO) with the Greater Cane Rat Algorithm (GCRA), which we call the PSO-GCRA framework. This hybrid approach takes advantage of PSO's global exploration capabilities and GCRA's local refinement strengths to overcome the shortcomings of each algorithm, such as premature convergence and ineffective local searches. We apply the proposed framework to a real-world load forecasting challenge using data from the Australian Energy Market Operator (AEMO). The PSO-GCRA framework functions in two sequential phases: first, PSO conducts a global search to explore the solution space, and then GCRA fine-tunes the solutions through mutation and crossover operations, ensuring convergence to high-quality optima. We evaluate the performance of this framework against benchmark methods, including EMD-SVR-PSO, FS-TSFE-CBSSO, VMD-FFT-IOSVR, and DCP-SVM-WO. Comprehensive experiments are carried out using metrics such as Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and convergence rate.  The proposed PSO-GCRA framework achieves a MAPE of 2.05% and an RMSE of 3.91, outperforming benchmark methods, such as EMD-SVR-PSO (MAPE: 2.85%, RMSE: 4.49) and FS-TSFE-CBSSO (MAPE: 2.98%, RMSE: 4.69), in terms of accuracy, stability, and convergence efficiency. Comprehensive experiments were conducted using Australian Energy Market Operator (AEMO) data, with specific attention to normalization, parameter tuning, and iterative evaluations to ensure reliability and reproducibility