Vietnam Holds ASEAN Drill to Test Cybersecurity Incident Response

The Vietnam Computer Emergency Response Team (VNCERT) and the Authority of Information Security, under the Ministry of Information and Communications (MIC), recently presided over the deployment of the 2021 ASEAN Computer Emergency Response Team Drill (ACID 2021) for members of the emergency response network and IT units of ministries and agencies nationwide.

Attending the ACID 2021 were teams representing ASEAN member nations and five dialogue countries, namely Australia, China, India, Japan, and the Republic of Korea. According to a press release by MIC, the drill, entitled “Responding to attacks on supply chain targeting at corporations and organisations,” was hosted by Singapore. Participants in the exercise included key technical staff, who take part in international and domestic deployments from the Authority of Information Security, state-run group Viettel, VNPT, BKAV, Sacombank, support staff groups (technicians of VNCERT), and members of the national network information security incident response network.

This was an opportunity for technicians of Vietnamese agencies, organisations, and enterprises to practice their skills in dealing with, investigating, analysing, minimising damage, and reporting emergencies. It aimed to help them gain knowledge and experience in responding to cyber security incidents. The ACID 2021 drill used the latest cybersecurity trends as scenarios for teams to strengthen their preparedness in solving cybersecurity issues. After the drill, experts and domestic team members spent time exchanging and sharing situations and solutions to help participants have a better understanding of how to handle the incidents in a specific case.

As per data from the first six months of this year, cyberattacks in Vietnam decreased but the level of sophistication and damage was much greater. Vietnam recorded 2,915 cyber-attacks in the first six months of 2021, an increase of 898 compared with the same period last year. Earlier in May, the MIC Minister issued a directive on strengthening the prevention and combat of violations and crimes on the Internet. The Minister also requested the sector to continue to effectively implement the Prime Minister’s directive on enhancing safety measures on cybersecurity which aims to improve Vietnam’s rankings.

Vietnam jumped 25 places in two years to rank 25th out of 194 countries and territories worldwide in the Global Cybersecurity Index (GCI) in 2020, according to a report released recently by the International Telecommunications Union (ITU). Vietnam ranked seventh in the Asia-Pacific region and fourth among ASEAN countries. The country posted a score of 94.59 with improved scores in all five reviewed pillars. The country’s efforts to build long-term development projects in personnel for cybersecurity were recognised, along with achievements in the creating of an ecosystem for safe ‘Made in Vietnam’ products and cybersecurity. Vietnam surpassed Thailand to clinch the fourth spot in ASEAN after Singapore, Malaysia, and Indonesia. The leading countries in the Asia-Pacific region are the Republic of Korea and Japan both with 98.52 points.

Further, Vietnam’s e-security index improved by 54% since last year, according to the 2021 Digital Quality of Life Index (DQL) conducted by a cybersecurity company. The report has placed Vietnam 73^rd among 110 countries. Covering 90% of the global population, the study evaluates countries based on five fundamental digital wellbeing pillars. Vietnam ranked 51^st for Internet affordability, 86^th for Internet quality, 75^thfor e-government, 71^st for e-security, and 67^th for e-infrastructure.

Singapore Enhancing Robotics in Food Services

A*STAR, in collaboration with a local F&B-centric robotics and automation SME, has developed a joint research and innovation initiative to foster innovation in robotic platforms for the Food Services industry.

This programme will combine both parties’ Advanced Remanufacturing and Technology Centre’s (ARTC) skills to develop solutions that incorporate Food and Beverage (F&B) domain knowledge, as well as artificial intelligence (AI), robotics, and automation.

The F&B-centric robotics and automation SME and A*STAR’s ARTC will invest S$3.5 million in developing a modular vision platform that can assist robotised operations in F&B by assisting these robots to self-navigate and self-calibrate in dynamic and space-constrained environments such as restaurant kitchens.

The combined effort will also use a digital twin platform to establish a digital representation of the F&B robotic system, allowing for real-time analytics that enables remote monitoring and optimisation of operations, accelerating the deployment of new robotic systems and decreasing operational downtime.

The combined research and innovation project embodies both A*STAR’s and the firm’s desire to leverage mutual capabilities to perform research combining F&B domain expertise, robotics, automation, AI, vision, and digital twin technologies.

The partnership is sure that the technology they produce will assist support and building the digital and automation capabilities of F&B firms. Besides, they believe that this will help Singapore establish itself as a major F&B robotics and automation hub, increase the efficiency of Food Service personnel, and help address the sector’s manpower problem and rising operational expenses.

The collaborative effort intends to create solutions that will enable the Food Services industry to automate operations and boost efficiency, lowering the amount of repetitious and physically demanding work and allowing F&B personnel to focus on higher-value jobs.

A*STAR’s ARTC engages with local enterprises to co-develop breakthrough technologies and co-innovate industry solutions to seize new growth possibilities locally and worldwide, according to Dr David Low, CEO of A*STAR’s ARTC.

He added that such public-private collaborations are critical in bringing complementary expertise together to address problem statements and increase productivity and efficiency in the Fast-Moving Food Services industry and beyond.

The Food Services business is set to expand and evolve further. Digitalisation and automation are critical to assisting F&B businesses in thriving and overcoming obstacles such as a labour shortage.

This collaboration will develop solutions to assist F&B enterprises in optimising their operations. They anticipate more similar cooperation between innovation and IT ecosystem partners to boost F&B company growth.

Drive innovation is critical for the food services industry because it has the potential to revolutionise operations and address significant concerns. Innovation serves as fuel for growth and sustainability in an era characterised by technical advancements and shifting consumer expectations.

Automation streamlines operations and reduces reliance on manual labour. Tasks such as food preparation, cooking, and serving can be carried out more efficiently by adding robotics, AI, and automation technology, resulting in higher productivity and lower operational expenses.

Improved consumer experiences are made possible by innovation. From self-ordering kiosks and smartphone apps to personalised recommendations and delivery drones, technology advancements improve consumer convenience, speed, and personalisation. This results in increased client happiness and loyalty, which ultimately drives corporate success.

It is also critical in addressing labour shortages. With rising labour costs and a diminishing workforce, automation and robotics provide options to fill the gaps, allowing food service enterprises to remain efficient and successful.

In addition, food service industry innovation can reduce environmental effects. Through innovative technologies, sustainable practices such as waste reduction, energy efficiency, and eco-friendly packaging solutions can be integrated, leading to a greener and more socially responsible industry.

Vietnam’s Enhancing E-commerce Governance

Prime Minister Pham Minh Chinh has issued Directive No. 18/CT-TTg, which aims to enhance data connectivity and sharing to foster the growth of e-commerce, prevent tax loss, and safeguard monetary security.

The directive acknowledged that the rapid expansion of the e-commerce market has presented significant challenges in effectively managing e-commerce activities and tax administration. It emphasised the need for close collaboration among specialised management agencies to regulate payment transactions and verify the information of businesses, individuals, and taxpayers in response to the evolving digital business landscape.

The Prime Minister has assigned specific tasks to various ministries and agencies in the directive. They will enhance efficiency and facilitate digital transformation in the governance of e-commerce activities, digital platform trading, cross-border business, and data sharing among ministries and agencies for the advancement of e-commerce.

The Ministry of Finance (MoF) has been assigned the responsibility to collaborate with other relevant ministries in the process of amending legal documents pertaining to e-commerce. This includes streamlining administrative procedures and implementing strict measures to address tax and customs violations.

It has also been assigned the responsibility of developing a comprehensive plan for data connection and sharing with the Ministry of Industry and Trade (MoIT), the Ministry of Information and Communications (MoIC), the Ministry of Public Security (MoPS), the State Bank of Vietnam (SBV), and other relevant agencies. This plan aims to strengthen tax administration for e-commerce activities and the provision of cross-border digital products and services. The deadline for completing this plan is set for the third quarter of this year.

MoIC is tasked with coordinating efforts among ministries and agencies to standardise, digitise, connect, and share data pertaining to e-commerce. SBV has been directed to collaborate with MoF and other relevant agencies to establish a mechanism for overseeing payment transactions. This mechanism will specifically support tax administration for cross-border service provision, in accordance with the Law on Tax Administration and other related legislations.

MoPS has been urged to accelerate the integration of the national population database with the databases and information systems of ministries, agencies, and local authorities. This integration is crucial for implementing e-identification and e-authentication systems. The MoPS is also tasked with collaborating with relevant agencies to refine specialised laws and policies that safeguard e-commerce development and monetary security, as well as prevent tax loss.

The Government Office will coordinate with relevant ministries in continuing to promote the integration and provision of online public services, and online payment in the fields of taxation and e-commerce on the National Public Service Portal.

Earlier this week, SBV urged banks, foreign bank branches, and intermediaries in payment services to actively support the advancement of cashless transactions and the implementation of the national digital transformation programme.

The move aims to aid the plan on developing the application of resident data and electronic identification and authentication to support the national digital transformation agenda during the period of 2022-2025, with a vision extending to 2030.

As OpenGov Asia reported, the banks, foreign bank branches, and intermediaries in payment services will persist in their efforts to devise favourable programmes and policies concerning payment and intermediary payment service fees for customers. The SBV has also urged them to waive account maintenance fees and cash withdrawal fees for customers entitled to the social security policy. They have been instructed to proactively engage in practical initiatives to commemorate Cashless Day 2023, which takes place on 16 June, and to continue their efforts throughout the entire month.

Remote Sensing for Sustainable Agriculture in Indonesia

Remote sensing has been widely used to identify and analyse various issues in agricultural land. One application of remote sensing has been conducted to estimate oil palm productivity by utilising satellite imagery from Sentinel-2.

A collaborative remote sensing research project for estimating the productivity of oil palm, modelling fire-prone areas, and studying oceanography in Lamandau Regency, Central Kalimantan, has been established by the National Research and Innovation Agency (BRIN) in collaboration with Lamandau Polytechnic from Lamandau Regency, Central Kalimantan.

The signing of the cooperation agreement between both parties was carried out by Rahmat Arief, Head of the Remote Sensing Research Center (PRPJ) at the Flight and Space Research Organization (ORPA) of BRIN, and A. Adhityawan Nugroho, Director of Lamandau Polytechnic, at the Teratai KST Soekarno Building in Cibinong.

Further research on estimating oil palm productivity using remote sensing is necessary to ensure more reliable accuracy of the results. It can estimate the productivity of oil palms and provide a deeper understanding of the factors that influence crop production. Such research involves the analysis of various variables such as climate, soil type, fertilisation, pest and disease management, and other cultivation practices. By deepening the understanding of these factors, more effective methods can be developed to optimise oil palm productivity and support the sustainable growth of the palm oil industry.

Rahmat stated that BRIN has the task of increasing partnerships to foster collaborations, particularly in research collaborations. The goal is to establish a research ecosystem as an economic foundation. An economy based on research is more resilient, especially when utilising advanced technology. Therefore, BRIN strives to establish a research ecosystem supported by policies, human resources, infrastructure, and business processes.

Technology is indeed closely related to infrastructure. BRIN has the concept of an open platform infrastructure where all sectors can access the infrastructure within BRIN. He continued that this includes High-Performance Computing (HPC), laboratories, data centres, and other facilities.

The income generated from oil palm in Lamandau Regency is substantial, and its exports are also significant. According to data from Regional Development Planning Agency (Bapeda), the agricultural sector, including oil palm, contributes 20% to the Gross Regional Domestic Product (PDRP) of Lamandau Regency.

Through remote sensing data, this research collaboration aims to establish a comprehensive understanding and accurate prediction of oil palm productivity in Bulik District, Lamandau Regency. By harnessing the power of remote sensing technology, the collaboration is anticipated to provide valuable insights and tools for palm oil companies to manage their plantations effectively and optimise production in line with their desired targets.

The successful implementation of this research collaboration holds excellent potential for the region’s development in both Lamandau Regency and Central Kalimantan Province.

Through utilising remote sensing data and the collaborative efforts of various stakeholders, including research institutions, government bodies, and palm oil companies, this research collaboration aims to establish a robust framework for accurate productivity estimation, effective plantation management, and sustainable development in Bulik District. By synergising scientific knowledge, technological advancements, and practical applications, the collaboration endeavours to positively impact the local community, foster economic growth and benefit the environment, particularly in the region.

Singapore Unveils AI Government Cloud Cluster

The Smart Nation and Digital Government Office (SNDGO) and a major cloud computing company have announced the launch of the Artificial Intelligence Government Cloud Cluster (AGCC), a comprehensive platform designed to accelerate AI adoption in Singapore’s public sector, advance local applied AI research efforts and support the growth of the local AI startup ecosystem.

The AGCC has been implemented by SNDGO and the cloud tech company for usage by Singapore’s government agencies and the research, innovation, and enterprise (RIE) ecosystem. The AGCC is hosted in Singapore in a specialised cloud computing environment.

Agencies can use the AGCC to build and deploy scalable and impactful AI applications rapidly, safely, ethically, and cost-effectively by leveraging an AI technology stack and a vast partner ecosystem of software-as-a-service firms, consultancies, and AI startups. AI technology stack capabilities include:

First, an AI-optimised infrastructure. High-performance A2 supercomputers powered by NVIDIA’s A100 GPUs and hosted in an open, scalable, secure, and energy-efficient infrastructure. This enables cloud developers to train computationally complex AI models at fast speeds while minimising costs and environmental impact.

Customisable first-party, third-party, and open-source AI models follow. A central repository enabling AI practitioners to access pre-trained generative AI models, with built-in features to assist users in customising these models for specific requirements.

The repository contains a wide range of first-party, third-party, and open-source models designed for certain needs. These include models for summarising and translating text in different languages, sustaining an ongoing discussion, converting audio to text, producing, and modifying software code, and generating and repairing written descriptions.

International AI businesses interested in making their foundation models available to Singapore government departments can collaborate with the Cloud computing company to store these models in the repository.

Another category is no-code AI development tools. A Generative AI App Builder enabling developers (especially those with limited technical expertise) to swiftly construct and seamlessly embed chatbots and enterprise search experiences driven by Cloud’s generative AI models.

Finally, there are explainable AI and data governance toolkits. A set of built-in technologies that can assist government agencies in using AI in a secure and responsible manner. This includes features for access control and content moderation, as well as novel mechanisms for incorporating human feedback to improve model performance and the ability to audit the sources of AI model outputs to detect and resolve potential bias and ensure that model behaviour is compliant with regulations.

The Government Technology Agency (GovTech) is Singapore’s first public-sector organisation to use the AGCC. Its Open Government Products (OGP) team has integrated with Vertex AI and is investigating the use of its models in Pair, which are large language model-powered assistants that civil servants can use to help them boost productivity while maintaining the confidentiality of government information.

To help government agencies deploy AI applications as effectively and responsibly as possible, the Cloud tech company will collaborate with GovTech to design and run whole-of-government Digital Academy programmes that will assist agencies in developing in-house data science and AI expertise, developing AI innovation strategies, and implementing data governance best practices.

The programmes will be delivered in a variety of specialised formats to 150,000 public servants from 16 ministries and over 50 statutory boards.

Government agencies in Singapore will be able to use the AGCC and other authorised services through the Government on Commercial Cloud (GCC) 2.0 platform beginning in June 2023. The GCC platform, developed by GovTech, offers agencies a standardised and regulated means to implement commercial cloud solutions.

GCC 2.0, the platform’s second generation, is integrated with cloud-native capabilities and cloud security practices, enabling agencies to access into a larger ecosystem of services and people to accelerate the development of new digital applications.

Australia: Renewed Collaboration for Sustainable Transport

Australia’s Minister for Infrastructure, Transport, Regional Development and Local Government and the Governor of Michigan jointly renewed and expanded cooperation between Australia and Michigan to foster collaborative efforts in preparing for a transport future that prioritises environmental sustainability, safety, enhanced connectivity, and improved accessibility for communities.

The Memorandum of Understanding (MoU) will serve as the foundation for continued collaboration between the automotive and technology sectors of Australia and Michigan, as well as policymakers from both regions.

The Memorandum of Understanding (MoU) highlights the shared dedication of the individual and Governor Gretchen Whitmer to address climate change by reducing emissions in the transport sector. It emphasises the importance of fostering collaboration in developing future technologies and enhancing supply chain connectivity within the sector.

Similar to Michigan, Australia has made a commitment to achieve net zero emissions by 2050. This MOU will facilitate future collaboration between the two jurisdictions, ensuring that the transport sector actively contributes to the overall goal of emissions reduction.

New and emerging transport technologies have the potential to enhance accessibility, safety, reduce congestion, and increase productivity. Recognising the significance of these advancements, the Australian Minister stated that the government assumes a strategic leadership role in facilitating the safe and lawful adoption of such technologies in Australia. In this endeavour, Michigan, known as a longstanding global hub for automotive industry innovation, becomes an important international partner in further advancing its collaborative efforts in the field of transport technology.

Importantly, within the Memorandum of Understanding (MoU), Australia’s commitment to enhancing the engagement of First Nations businesses in the automotive sector, including future transport business opportunities, is outlined.

This commitment aligns with the Albanese Government’s dedication to ensuring that Australia’s foreign policy reflects the country’s complete identity. The continuation of the collaboration between Australia and Michigan is eagerly anticipated, as it will contribute to the achievement of a better and safer transport future that forms the foundation of prosperity for both regions.

Smart transport, also known as intelligent transport, refers to an advanced infrastructure for transportation that aims to offer innovative services for managing traffic and transport. It encompasses various applications like parking management and guidance, passenger information, and traffic control. The global smart transportation market is anticipated to expand to US$251.0 billion by 2030, with a compound annual growth rate (CAGR) of 10.2% from 2021 to 2030.

Intelligent transportation systems (ITS) are advanced applications that provide ground-breaking services for transportation and traffic management. These systems allow multiple users to be better coordinated and informed through the use of technologies such as car navigation, traffic signal control systems, speed cameras, and real-time data analysis. Achieving this intelligent transportation information involves enhancing infrastructure, implementing sustainable fuels for public transport vehicles, and efficiently providing mobility services in rapidly growing cities.

The COVID-19 pandemic has had a profound impact on the transportation industry, causing widespread uncertainty and disruption. Despite these challenges, market players in the smart transportation industry have embraced innovative strategies to capitalise on growth opportunities. There is a growing demand for effective traffic management systems and improved transportation infrastructure to ensure passenger safety.

As the world gradually recovers and implements new restrictions and policies, the transportation sector, particularly in the retail industry, is expected to witness a significant recovery. This recovery, coupled with technological advancements in vehicle safety, is likely to have a positive impact on the smart transportation market.

Moreover, the advent of cloud-based technologies and advancements in vehicle-to-vehicle (V2V) and vehicle-to-grid infrastructure (V2I) have facilitated the realisation of smart transportation. These technologies are designed to offer ground-breaking services in various aspects of transportation and traffic management. They empower users to access improved information and use transport networks more safely and efficiently.

India: University Implements AI/ML for Efficient Tracking

State-run Osmania University in Hyderabad has embraced artificial intelligence and machine learning (AI/ML) to revolutionise its attendance marking process. Now, the tedious waiting to sign attendance registers or use biometric systems is no longer required. Employees simply need to enter the building, and their attendance will be automatically recorded. This is made possible through CCTV cameras equipped with AI and ML technologies, which accurately mark employees’ attendance, log-in and log-out times, as well as their entry and exit from the building.

The functionality of these cameras relies on an integrated facial recognition system. Leveraging cognitive AI capabilities, they identify facial biometrics and synchronise them with the current database to accurately document employee attendance. This innovative solution has been implemented as a pilot project in the main administrative building of the university for its employees. In the future, the university plans to expand the deployment of these cameras to other campus facilities, including offices, classrooms, and hostels.

According to an official from the university, under the manual system, employees often mark their attendance in the morning, leave the office, and return later to record their log-out time. However, with the implementation of CCTV camera-based attendance, this process will undergo a significant change. The cameras continuously capture movement and simultaneously store employees’ log details, eliminating the need for manual recording. To achieve this, AI and ML technologies have been integrated into two cameras.

Additionally, the official noted that the CCTV cameras also capture the log-in information of visitors entering the administrative building. This means that the log details of all visitors are systematically recorded in the database, providing a comprehensive attendance tracking system.

The introduction of CCTV-based attendance eliminates the need for manual attendance registers or time-consuming biometric systems, streamlining the entire process. Students simply need to enter the designated areas covered by CCTV cameras, and their attendance is promptly recorded. This not only saves time but also reduces the chances of errors or misinterpretations.

Moreover, these AI-powered cameras not only capture the presence of students but also provide additional functionalities. Some universities have integrated facial recognition systems to ensure authentication and prevent proxy attendance. The cameras analyse facial biometrics, matching them against the existing database to ensure accurate identification. It can also enable the university to track attendance patterns, identify areas that require improvement, and take proactive measures to enhance student engagement and performance.

Most educational institutions across the country are embracing the advancements brought by AI. Numerous schools and colleges have incorporated AI-based learning techniques to simplify the process of education and effectively teach intricate subjects to students. Additionally, AI’s adaptable learning methods assist teachers in providing personalised attention to each student.

Last year, the Indian Institute of Technology Madras (IIT-Madras) and the Tamil Nadu State Department of School Education announced they would collaborate to improve and update the digital learning platform for school students to an assessment-focused Learning Management System. It was deployed in high-tech labs in 6,000 government schools, as OpenGov Asia reported. It aimed to improve the quality of learning for around nine million students.

Education in Tamil Nadu’s schools was previously supplemented through a digital learning platform called the Education Management Information System. Researchers from the Indian Institute of Technology Madras used their AI and data science expertise to come up with ways to improve the way assessments are conducted and develop a framework to disseminate educational material.

U.S: Enhancing Autonomous Machine Learning

When in the learning process, humans are nurtured by teachers or mentors to acquire knowledge more quickly. Students can grasp when the teacher showed a good or substandard example. Additionally, they can only imitate the teacher’s actions precisely if they exert greater effort to achieve the same level of proficiency. Just like humans, computer scientists can also use “teacher” systems to train another machine to complete a task.

Researchers from MIT and Technion, the Israel Institute of Technology, have embarked on developing an algorithm that automatically and independently determines when the student should mimic the teacher (imitation learning) and when it should learn through trial and error (reinforcement learning). The researchers made the machine learn from other machines without a third party anymore to teach, causing it to save a lot of time and energy.

Several current approaches attempting to find a middle ground between imitation learning and reinforcement learning often rely on a laborious process of brute force trial-and-error. Researchers select a weighted blend of the two learning methods, execute the entire training procedure, and iterate the process multiple times to discover the optimal balance. However, this approach is inefficient and often incurs substantial computational costs, rendering it impractical in many cases.

When the researchers embarked on their simulation, it was proved that the combination of trial and error learning allowed students to learn faster and more efficiently than the imitating methodology, as the student can explore more in many ways. By simulating the combination methodology, which uses the experiment and exploration by the student itself, students can combine dots that intersect to produce a comprehensive conclusion.

“Integrating trial-and-error learning and following a teacher yields a remarkable synergy. It grants our algorithm the capability to tackle highly challenging tasks that cannot be effectively addressed by employing either approach independently,” said Idan Shenfeld, an electrical engineering and computer science (EECS) graduate student and Lead Author of a paper on this technique.

The innovative approach enables the student machine to deviate from imitating the teacher’s behaviour when the teacher’s performance is either good or not good. However, the student can later revert to mimicking the teacher’s actions during the training process if it proves to be more beneficial, leading to improved outcomes and accelerated learning.

The proposed approach entails training two separate students. The first student is taught using a combination of reinforcement learning and imitation learning, with the learning process being guided by various techniques.

On the other hand, the second student is trained solely using reinforcement learning, relying exclusively on this approach to learn the same task, minimising the need for extensive parameter adjustments, and delivering exceptional performance.

To give their algorithm an even more difficult test, a simulated environment was established, involving a robotic hand equipped with touch sensors but without visual perception. The objective was to reorient the pen to the correct position. The teacher solely accessed real-time orientation data, while the student relied on touch sensors to determine the pen’s orientation.

Rishabh Agarwal, Director of a private research laboratory in the US and an assistant professor in the Computer Science and Artificial Intelligence Laboratory underscores that the ability to reorient objects is just one example of the various manipulation tasks that a future household robot would be required to accomplish. “This research introduces a compelling method, leveraging previous computational efforts in reinforcement learning.”

“I am very optimist about future possibilities of applying this work to ease our life with tactile sensing,” Abhishek Gupta, an Assistant Professor at the University of Washington, concluded.

June 3, 2023

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Vietnam Holds ASEAN Drill to Test Cybersecurity Incident Response

Singapore Enhancing Robotics in Food Services

Vietnam’s Enhancing E-commerce Governance

Remote Sensing for Sustainable Agriculture in Indonesia

Singapore Unveils AI Government Cloud Cluster

Australia: Renewed Collaboration for Sustainable Transport

India: University Implements AI/ML for Efficient Tracking

U.S: Enhancing Autonomous Machine Learning

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Singapore Enhancing Robotics in Food Services

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Vietnam’s Enhancing E-commerce Governance

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