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Localization Techniques Overview Towards 6G Communication
No full textWorldwide Researchers and scientist have started the investigation of the sixth generation (6G) while the fifth generation (5G) cellular system is being deployed. Under this main investigation the main aim of 6G is to provide intelligent and ubiquitous wireless connectivity with Terabits per second (Tbps) data rates. Accurate location information of the mobile devices is very much useful to accomplish these aims with the improvements of various parameters of wireless communication. The development in communication technology often creates new opportunities to improve the localization efficiency as demonstrated by the expected centimetre-level localization accuracy in 6G. While there are comprehensive literatures separately on wireless localization or communications, the 6G study is still in its inception. This article is therefore intended to provide an overview of localization techniques towards 6G wireless networks. Finally, some interesting future localization technique research directions are highlighted
Performance of Sentiment Classification on Tweets of Clothing Brands
No full textSocial media such as Facebook, Instagram, LinkedIn, and Twitter ease the sharing of ideas, thoughts, videos, and photos and information through the building of virtual networks and communities. This has allowed companies and products to reach a wider audience in terms of marketing and advertising, and to gauge feedback from the public. This research investigates clothing brand mentions on Twitter to perform sentiment analysis on users’ thoughts on three clothing brands, namely Asos, Uniqlo and Topshop. The data is collected by applying python libraries, Tweepy to access data from the Twitter streaming API. Following that, data pre-processing such as tokenization, filtering, stemming, and case normalization are performed to remove outliers. Then, the TextBlob algorithm is applied to label the tweet data into three classes; Positive, Negative and Neutral based on the polarity of the tweets. Word embeddings are also created using Word2Vec with TF-IDF. The word embeddings are fed into classification models namely Support Vector Machine (SVM), Naïve Bayes (NB), Random Forest (RF), Logistic Regression (LR) and Multilayer Perceptron (MLP) by comparing their accuracy performances. The models went through training and testing process on a curated tweet dataset comprising 24000 records with three clothing brands (Asos, Uniqlo, Topshop). The classification process was carried out by SVM, NB, RF, LR and MLP with a ratio of 50-50 and 70-30 train-test splits. Hyperparameter tuning was implemented by GridSearchCV to find the best parameters of classification models in order to optimize the best results. The evaluation of performance was measured with accuracy, precision, recall and F1-Score. In the 50-50 train-test splits, LR achieved the highest accuracy by scoring 82%, 87% and 87% on Asos, Uniqlo and Topshop respectively. In the 70-30 train-test splits, LR also achieved highest accuracy by scoring 85%, 90% and 90% for the three clothing brands respectively
The effects of transformational leadership and change management on civil servants’ motivation: A study at the Regional Secretariat of Sumedang Regency
No full textThis study aimed to analyse the effects of transformational leadership and change management on the motivation of civil servants, with a case study at the Regional Secretariat of Sumedang Regency. This study used quantitative and descriptive-causality analysis methods. The saturated sample of census technique was used, involving 200 civil servants in the Regional Secretariat of Sumedang Regency. It was concluded from this study that the application of transformational leadership in Sumedang Regency went very well. Change management has been very effective and the motivation of civil servants was very high. The implementation of transformational leadership should be prioritised within the Sumedang Regency to further encourage motivation among the state civil servants. The replication and adaptation of transformational leadership and change management must be implemented in all organisations and institutions within the Sumedang Regency, to produce a collective impact on regional progress
Illegal Roads Leading to Legal Ends: Bitcoin Mining in Malaysia
No full textA decade ago, no one would have envisioned that Bitcoin would be as lucrative as it is today. What many first thought of as a scam, has now turned out to be one of the fastest growing digital currency in the world. This paper attempts to explain the legal framework and implications of Bitcoin mining, mostly in Malaysia, while also citing examples of other nations. The research attempts to shed light on how mining actually becomes illegal, despite not being directly penalized under most laws. The second part of the paper aims to critically analyse the solutions and reforms that can be put into motion in order to further facilitate the growth of Bitcoin in Malaysia. While some nations have started amending existing laws and promulgating new laws to address the rapid growth of Bitcoin, most countries still have no clear guidelines outlining Bitcoin mining and the Bitcoin trade in general. This paper also attempts to shed light on how the Bitcoin mining process can be made more environmentally friendly, so as to benefit both miners as well as the public at large
Students' Virtual Learning Challenges and Learning Satisfaction during COVID-19 Pandemic: A Conceptual Framework
No full textVirtual learning is an excellent way for students and teachers to interact and share information. Many educational institutions utilise virtual classrooms as their primary platform for interactive knowledge sharing. However, some students lack computer and technological abilities, lack self-motivation, or have trouble adapting to these virtual classrooms. All these factors reduce their learning satisfaction. The goal of this paper is to provide a conceptual framework to research the relationship between virtual learning challenges and students’ learning satisfaction. The Shannon-Weaver Data Transmission Model and Learning Satisfaction Theory are the overarching theories underlying this investigation. The Shannon-Weaver model's technological layers are critical for integration into today's digital communication technologies, allowing the continuation of critical educational activities. "Noise" as understood in the Shannon-Weaver Data Transmission Model is used to examine students' learning satisfaction. In brief, by forming the conceptual framework, it may provide a second step for further investigation on the correlation between virtual learning challenges and students’ learning satisfaction during the COVID-19 pandemic
The Determinants of House Prices in Malaysia: DOI: https://doi.org/10.33093/ijomfa.2021.2.1.1
No full textThis paper studied how house prices were affected by macroeconomic factors from Q1 2009 to Q4 2018. The short and long-run effects of real income, nominal interest rates, inflation rate and stock prices on house prices in Malaysia were examined with the autoregressive distributed lag (ARDL) of a restricted error correction model (ECM). It was discovered that the selected macroeconomic factors were cointegrated with house prices. Income, represented by real Gross Domestic Product (GDP), significantly affected house prices in the short and long-run. Inflation and interest rate, proxied by Consumer Price Index (CPI) and Overnight Policy Rate (OPR), respectively, affected house prices significantly in the long-run. The stock market, tracked by Kuala Lumpur Composite Index (KLCI), had no significant impact on house prices signifying no wealth effect. Through the findings of an inelasticity of demand and an undesirable result of monetary policies, this paper concluded that more effective solutions needed to be carried out to ensure affordability of house ownership in Malaysia
Driving Inclusiveness from the Grassroots: The Tambunan Inventors: DOI: https://doi.org/10.33093/ijomfa.2021.2.1.6
No full textReviews of recent studies indicated the growing importance of development and attainment of inclusive societies via inclusive innovations. This is especially relevant for addressing the disenfranchised or those at the base of the economic pyramid (BOP). Gaps in the literature pointed to; l) the need for understanding of inclusive innovation processes among small, medium and micro enterprises vis-à-vis among local entrepreneurs, ll) there is a lack of studies on inclusive innovation movement in Malaysia. Specifically under the SME Masterplan 2012-2020, there are a number of high impact programmes defined to drive numerous aims. Specifically, for driving inclusive innovation among Small and Medium Entreprises (SMEs) in Malaysia, the High Impact Programme 6 (HIP6) is designed with the focus on development of grassroots innovations. In order to get some insights, case studies were carried out among participants of the HIP6. Cases were recommended by the lead agency entrusted with the implementation of the initiative. Among the cases, a cluster in the area of Tambunan in the state of Sabah, Malaysia was identified. Thus, this paper presents the cases of the Tambunan grassroots inventors
Vision Based Indoor Surveillance Patrol Robot Using Extended Dijkstra Algorithm in Path Planning
No full textVision based patrol robot has been with great interest nowadays due to its consistency, cost effectiveness and no temperament issue. In recent times, Global positioning system (GPS) has been cooperated with Global Navigation Satellite System (GNSS) to come out with better accuracy quality in positioning, navigation, and timing (PNT) services to locate a device. However, such localization service is yet to reach any indoor facility. For an indoor surveillance vision based patrol robot, such limitation hinders its path planning capabilities that allows the patrol robot to seek for the optimum path to reach the appointed destination and return back to its home position. In this paper, a vision based indoor surveillance patrol robot using sensory manipulation technique is presented and an extended Dijkstra algorithm is proposed for the patrol robot path planning. The design of the patrol robot adopted visual type sensor, range sensors and Inertia Measurement Unit (IMU) system to impulsively update the map’s data in line with the patrol robot’s current path and utilize the path planning features to carry out obstacle avoidance and re-routing process in accordance to the obstacle’s type met by the patrol robot. The result conveyed by such approach certainly managed to complete multiple cycles of testing with positive result.
Manuscript Received: 18 October 2021, Accepted:4 November 2021, Published: 15 December 202