PEMBINAAN PENGENALAN BASIC ENGLISH CONVERSATION AT THE AIRPORT KEPADA STAF BANDARA HANG NADIM BATAM

English is an international language which is very important for smooth bilingual interaction. Along with the times, the ability to speak English is required in all aspects of life to develop. One that is experiencing rapid development is the air transportation industry, which has a similar impact on the development of the airport aspect as a facility for providing aircraft transportation services. One of the important airports in the Riau Archipelago is Batam's Hang Nadim Airport. The airport was officially opened to the public on January 1, 1995 under the name "Hang Nadim International Airport. Since then until today, Hang Nadim airport has grown rapidly and has become one of the largest and busiest airports in Sumatra. With the rapid development of Hang Nadim Airport This, of course requires the use of an international language, namely English as the most commonly used communication medium. It has become a must for airport staff to be able to master English for the smooth operation of the technical process of aircraft and air flight systems. All airport workers are required to have good English language skills. it is appropriate to create conducive working conditions, but in reality on the ground, not all staff who work at airports have basic English skills, especially regarding the basic conversation part in English at the airport. If they are not equipped with basic English skills then they will not be able to speak English. can work optimally. Therefore, it is very important to initiate a dedication to provide a basic introduction to English for staff at Hang Nadim Airport, Batam City, Riau Islands.

Women in Electrochemistry- Contributions, Challenges and Potential Solutions

The perspectives gained over the years by women working in electrochemistry are described in order to throw light on their history and current status and achievements in this field, the potential that the future holds, and the role that well-established female electrochemists and the electrochemical societies can play in improving upon the under-representation and under-recognition of women in electrochemistry. Here, a hopeful and optimistic future is presented, in which men and women, both equally contribute to this field, which encompasses our entire life, from corrosion and life of materials to transportation industry.

Big Data in Railway O&M

Railway systems are complex with respect to technology and operations with the involvement of a wide range of human actors, organizations and technical solutions. For the operations and control of such complexity, a viable solution is to apply intelligent computerized systems, for instance, computerized traffic control systems for coordinating airline transportation, or advanced monitoring and diagnostic systems in vehicles. Moreover, transportation assets cannot compromise the safety of the passengers by only applying operation and maintenance activities. Indeed, safety is a more difficult goal to achieve using traditional maintenance strategies and computerized solutions come into the picture as the only option to deal with complex systems interacting among them and trying to balance the growth in technical complexity together with stable and acceptable dependability indexes. Big data analytics are expected to improve the overall performance of the railways supported by smart systems and Internet-based solutions. Operation and Maintenance will be application areas, where benefits will be visible as a consequence of big data policies due to diagnosis and prognosis capabilities provided to the whole network of processes. This chapter shows the possibilities of applying the big data concept in the railway transportation industry and the positive effects on technology and operations from a systems perspective.

Hydrogen application technologies and environmentally friendly smart energy system

Climate change and fossil fuel depletion are the main reasons for many countries around the world to develop and implement energy transition strategies. Being a very clean burning fuel (generating steam only), hydrogen will play an important role in the transition from fossil energy to CO2-free energy. The paper introduces recent advances of hydrogen technology applied in transportation, industry, and power generation in the world; challenges regarding hydrogen safety and technology; barriers in social perception; and some recommendations for the development of hydrogen technology and environmentally friendly smart energy systems in Vietnam.

The impact of COVID-19 on the transportation and logistics industry

In this present age of globalization, the logistics and transportation industry has become an integral part of most businesses/firms as it is aimed at ensuring the effective movement of people, distribution of goods and services from one location to another on time. Therefore, this paper aims to analyze the impact of COVID-19 on the logistics and transportation sectors. The qualitative research approach was adopted using analysis and synthesis of scientific literature, data from news reports, organizational sites, and a case study of data contents. The paper presented the analysis of negative and positive effects of COVID-19 on the logistics and transportation industry. The study also discusses possible strategies and further steps for improvement of the logistics and transportation sector, including the automation and introduction of other technologies, a sustainable and flexible transportation system, cooperation of logistics and transportation business. Findings regarding the positive implications of COVID-19 show noticeable advancements in the logistics and transportation sector, such as the rise of e-commerce businesses with efficient delivery options, and the development of 3rd party logistics services as more companies outsource supply chain operations. The study revealed the importance of strategic planning with a joint effort from the research centers, public sector, private sector, and educational institutions as one of the proposed solutions for the logistics and transportation industry.

Autonomous Braking System: for Automobile Use

Road fatality and injury are a worldwide issue in the transportation industry. Road traffic accidents are becoming increasingly significant due to higher mortality, injury, and disability across the world, particularly in developing and transitional economies. Eighty-five percent of the total road traffic fatalities occur in developing nations, with Asia-Pacific accounting for roughly half of them. A variety of factors influence road safety, including technological, physical, social, and cultural factors. The purpose of this research was to design an autonomous braking system (AuBS). Using the Adaptive Neuro-Fuzzy Intelligent System (ANFIS), a DC motor, sensors, and SAuBS have been developed to customize the traditional hydraulic braking system. The genetic algorithm has been developed to simulate the fundamental characteristics of the automotive braking system. The AuBS system goal is to slow the car without the driver's help infrequent braking when the vehicle is moving at slower speeds. When the ANFIS performance is compared to that of the AuBS model, it is discovered that the ANFIS performs roughly 15% better.

Vehicle Destination Prediction Using Bidirectional LSTM with Attention Mechanism

Satellite navigation has become ubiquitous to plan and track travelling. Having access to a vehicle’s position enables the prediction of its destination. This opens the possibility to various benefits, such as early warnings of potential hazards, route diversions to pass traffic congestion, and optimizing fuel consumption for hybrid vehicles. Thus, reliably predicting destinations can bring benefits to the transportation industry. This paper investigates using deep learning methods for predicting a vehicle’s destination based on its journey history. With this aim, Dense Neural Networks (DNNs), Long Short-Term Memory (LSTM) networks, Bidirectional LSTM (BiLSTM), and networks with and without attention mechanisms are tested. Especially, LSTM and BiLSTM models with attention mechanism are commonly used for natural language processing and text-classification-related applications. On the other hand, this paper demonstrates the viability of these techniques in the automotive and associated industrial domain, aimed at generating industrial impact. The results of using satellite navigation data show that the BiLSTM with an attention mechanism exhibits better prediction performance destination, achieving an average accuracy of 96% against the test set (4% higher than the average accuracy of the standard BiLSTM) and consistently outperforming the other models by maintaining robustness and stability during forecasting.