Assessment of Chinese Cultural Influence and Market Potential in Malaysian Chinese-Language Films Based on Big Data Analysis and Predictive Models

The paper presents a comprehensive investigation into the dynamic interplay of Chinese cultural influence and market potential within the context of Malaysian Chinese-language films. Big data analysis and predictive modeling, the study explores various scenarios to unveil the underlying correlations between cultural elements, market opportunities, and box office success. With integrating Stochastic Gradient Descent (SGD) with Software-Defined Networking (SDN), the research enhances data processing accuracy and efficiency, providing a robust framework for decision-making in the film industry. Through a meticulous analysis of scenarios, the study reveals the intricate relationship between cultural impact and market potential, shedding light on how cultural influence contributes to box office revenue. Additionally, an evaluation of data processing aspects offers insights into optimizing computational strategies. This paper's findings offer valuable insights for film industry stakeholders seeking to navigate the intersection of culture, market dynamics, and datadriven decision-making, ultimately advancing the success of Chinese-language films in the Malaysian market. Our findings underscore the pivotal role of cultural impact in shaping market viability, as evidenced by high correlation coefficients (r > 0.97) between Cultural Influence and Market Potential Score. With a voluminous dataset, the study attains a fine-grained understanding of these films, reaffirming the symbiotic relationship between cultural narratives and box office achievements. Moreover, the research evaluates the practical dimensions of data processing, revealing the computational intricacies encapsulated by Processing Time, Memory Usage, and Input Data Siz

Novel Ultra-Compact Wide Stopband Microstrip Lowpass-Bandpass Triplexer for 5G Multi-Service Wireless Networks

This work presents a very compact microstrip lowpass-bandpass (LP-BP) triplexer, which is designed and analyzed based on a novel structure. Due to its complex design process, this type of triplexer is rarely designed. Compared to the previous LP-BP triplexers it has the most compact size of 0.006 λ 2 g , whereas an LP-BP triplexer with dimensions smaller than 0.01 λ 2 g has not been designed yet. This triplexer is designed based on a perfect mathematical method and optimization simultaneously. Its lowpass band has a cut-off frequency of 0.67 GHz, suitable for low-band 5G applications. The resonance frequencies of its bandpass channels are located at 2.15 GHz and 3.19 GHz. These bandpass channels make the proposed triplexer appropriate for 5G mid-band applications. This triplexer can suppress the harmonics from the first up to 8th harmonic. The bandpass channels are flat and wide with two fractional bandwidths (FBW) of 15% and 11.97%. To prove the designing process and its simulation results, the presented novel LP-BP triplexer is fabricated and experimentally measured. The comparison results show that the experimental measurement confirms the simulation results. The close alignment between the measurements and simulation results demonstrates a high level of accuracy of our designing method

Facebook’s Influence on the Effectiveness of Digital Advertising among Malaysian Youth

The growth of advanced technology has contributed to the digital advertising industry as Facebook's users are easily connected, and purchasing behaviours will be developed with the content of the products promoted in digital advertising. The older generation prefers traditional advertising due to technology's security and privacy aspects, leading to fewer choices in purchasing products. This study aimed to identify the relationship between the influence of Facebook and the effectiveness of digital advertising among Malaysian youth in Klang Valley. It was anticipated that this research would provide helpful information to the public and assist researchers in the future based on the findings of this topic area. Data was collected using a Google Form and distributed via social media like WhatsApp. The targeted respondents are between 15 and 34 years old and are located in the Klang Valley area. Statistical Package for the Social Sciences (SPSS) version 27 system was used to determine digital advertising characteristics electronically. T-test and ANOVA tests were applied in this study to examine the demographic factors that affect the relationship between the variables, as different backgrounds influence the perspectives and behaviours of the users. The findings show that the independent variable, the influence of Facebook, has a strong correlation with the dependent variable, the effectiveness of digital advertising among Malaysian youth in Klang Valley (r= 0.770). Socio-demographic factors such as age and educational level had an effect on the relationship between the variables. The effectiveness of digital advertising is influenced by the number of likes, comments, and shares by Facebook users

How do different values affect pro-environmental behaviours and happiness?

Schwartz’s Value Theory has brought about a rebirth of research on human values. However, the mediating role of pro-environmental behaviours and happiness on human values is inadequate. Thus, this study adopted the bipolar dimensions of human values organised by Schwartz, self-transcendence, and self-enhancement as the independent construct of values to explore the mediating role of pro-environmental behaviours and happiness. Data were taken from a random sample of Klang Valley residents (N = 700) in Malaysia. Partial least squares and structural equation modeling tools were used to achieve the aims. The study found that self-transcendence plays a vital role in affecting pro-environmental behaviours and happiness. Pro-environmental behaviours lead to happiness, and it is an important mediator between human value with happiness. Happiness leads to pro-environmental behaviours, and it is also an important mediator between human values and pro-environmental behaviours. The results confirm that psychological factors (happiness) regarding the environment play a prominent role in determining pro-environmental behaviours. Hence, cultivating self-transcendence values is crucial to foster pro-environmental behaviours and boosting happiness. Engaging with pro-environmental behaviours is important to generate positive feelings, which will eventually boost happiness. Nurturing a sense of happiness will motivate pro-environmental behaviours as well

Aspect-Level Sentiment Analysis through Aspect-Oriented Features

Aspect-level sentiment analysis is essential for businesses to comprehend sentiment polarities associated with various aspects within unstructured texts. Although several solutions have been proposed in recent studies in sentiment analysis, a few challenges persist. A significant challenge is the presence of multiple aspects within a single written text, each conveying its own sentiments. Besides this, the exploration of ensemble learning in the existing literature is limited. Therefore, this study proposes a novel aspect-level sentiment analysis solution that utilizes an ensemble of Bidirectional Long Short-Term Memory (BiLSTM) models. This innovative solution extracts aspects and sentiments and incorporates a rule-based algorithm to combine accurate sets of aspect and sentiment features. Experimental analysis demonstrates the effectiveness of the proposed methodology in accurately extracting aspect-level sentiment features from input texts. The proposed solution was able to obtain an F1 score of 92.98% on the SemEval-2014 Restaurant dataset when provided with the correct set of aspect-level sentiment features and an F1 score of 95.54% on the SemEval-2016 Laptop dataset when provided with the aspect-level sentiment features generated by the aspect-sentiment mapper algorithm

An e-Learning Recommendation System Framework

With the emergence of the digital era, the e-learning platform has become an effective tool for obtaining quality e-learning content. However, despite its potential, the true extent of its capabilities has yet to be fully explored. In order to attract users and maximize revenue, e-learning platforms are now expected to provide content tailored to their users' needs and preferences. These recommendations are generated by considering factors such as prior purchases, browsing history, demographic information, and more. By leveraging these advanced technologies, e-learning platforms can enhance the learning experience by providing users with content that is both engaging and relevant to their individual needs and interests. This paper explores the popular Machine Learning (ML) techniques employed in e-learning content recommender platforms. Two machine learning techniques, k-Nearest Neighbour Baseline (KNNBaseline) and Singular Value Decomposition (SVD), are selected and used to accurately forecast customer interests and preferences. By examining the data patterns and user behaviors, these ML techniques provide insights into the most relevant and personalized educational content for individual users, enhancing their learning experience. The item ratings predicted are generated based on the underlying pattern in past ratings of users. The performance of applied approaches was assessed using several evaluation metrics, which include root mean square error and mean absolute error

Effect of welding speed on micro-friction stir lap welding of ultra-thin aluminium and copper sheets

In this work, the technical feasibility of micro-friction stir lap welding to join 0.5-mm ultra-thin aluminium and copper sheets was studied. After identifying the processability windows of important parameters such as plunge depth, welding speed and material positioning, the effect of welding speed to join the ultra-thin AA5052 and C11000 sheets was assessed. Welding speeds were varied from 50 to 400 mm/min. The relationship of the welding speed to the joint quality, such as microstructure, tensile lap shear strength, weld surface roughness and joint electrical resistance was elucidated. It was found that the dissimilar sheets only joined when the copper sheet was placed on top of the aluminium sheet. Feasible welding was found at welding speeds of 50 mm/min and 70 mm/min, a constant rotational speed of 1500 rpm and a plunge depth of 0.55 mm. The welds possessed similar average tensile lap shear strength of 16 to 18 MPa but differed in microstructure and joint electrical resistance. More visible stir zones with lamella bands were found in the microstructure of welds produced at 50 mm/min, indicating a higher degree of mixing, albeit with excessive flashes and tunnel defects near the joint interface. On the other hand, the welds produced at 70 mm/min exhibited limited mixing and lamellar intermetallic compounds. Tunnel defects were mostly at the advancing side within the copper layer, and hook defects were absent. With selected processing parameters, micro-friction stir welding ultra-thin copper sheets to aluminium sheets is demonstrably feasible for less critical applications

Detecting and Extracting Illegal Signs from Video

This project focuses on developing an automated system to detect illegal signs in urban environments from videos. The system utilizes computer vision and machine learning techniques, specifically the YOLOv5 object detection framework, to accurately identify and locate illegal signs in video frames. It incorporates a verification process usingOptical Character Recognition (OCR) to differentiate between legal and illegal signs based on the extracted text information. The system is designed as a user-friendly web application, allowing users to upload videos or images for analysis and receive comprehensive results. The system can achieve a detection accuracy of up to 78.6%. With this system, authorities can effectively manage and regulate illegal signs in urban areas, contributing to better urban landscapes

Enhancing Work Performance: The Role of Communication and Leadership Styles

Effective communication styles are essential to encourage understanding of expectations, effective workforce management, and organisational growth to stimulate employee work performance. This study explores the complex relationships between leadership styles, work performance, and communication styles. Employee commitment is found to have implications for organisational commitment aspects like responsibility, loyalty, and trust. Effective interpersonal and leadership communication encompasses relationships beyond and within the workplace. This study uses a questionnaire-based survey to investigate how leadership styles mediate the relationship between the factors of communication styles and job performance in Malaysian organisations. The perceptions of communication style, the mediating effect of leadership styles, and the relationship between communication style and job performance are investigated using quantitative data analysis using descriptive, inferential, and correlation tests to perform mediation analysis. The findings indicate the need for communication-focused training and engagement programmes and the significance of assertive communication styles for improved work performance. The study also establishes the critical need for leaders to comprehend the needs, motivations, and efficiency drivers of each team member. The study offers directions for future research, including larger geographic coverage, more communication variables, mixed-method techniques, and the investigation of other indirect effects. The study's conclusions give leaders practical advice on how to improve organisational communication for improved work performance and encourage employee trust and commitment

Antecedents of Sustainable Tourism Development in Sundarbans, Bangladesh with the Moderation of Political Instability and Mediation of Destination Resilience

The study examines the antecedent of sustainable tourism development in the Sundarbans, Bangladesh context, using the influence of political instability as a moderator and destination resilience as a mediator. Social exchange theory and the complexity theory are underpinning theories. The study follows the positivism philosophy, quantitative method, and deductive approach. SmartPLS (4.0) analysed 339 responses using structural equation modelling (SEM). Findings evidenced that infrastructure development greatly affected destination resilience but had a negligible effect on sustainable tourism development. In contrast, place image and stakeholders’ integration had a negligible effect on destination resilience and sustainable tourism development, and political instability did not provide evidence of a moderating effect. Besides extending the applicability of the abovementioned theories, the study’s empirical findings will enhance the consciousness and proactivity among relevant stakeholders, tour operators, tourists, residents, businesses, policymakers and government regarding sustainable tourism and achieving sustainable development goals (SDGs) through the tourism industry