Every piece of data that travels over the internet — from paragraphs in an email to 3D graphics in a virtual reality environment — can be altered by the noise it encounters along the way, such as electromagnetic interference from a microwave or Bluetooth device. The data are coded so that when they arrive at their destination, a decoding algorithm can undo the negative effects of that noise and retrieve the original data.
U.S. and Ireland’s researchers have now created the first silicon chip that is able to decode any code, regardless of its structure, with maximum accuracy, using a universal decoding algorithm called Guessing Random Additive Noise Decoding (GRAND).
By eliminating the need for multiple, computationally complex decoders, GRAND enables increased efficiency that could have applications in augmented and virtual reality, gaming, 5G networks, and connected devices that rely on processing a high volume of data with minimal delay.
One way to think of these codes is as redundant hashes added to the end of the original data. The rules for the creation of that hash are stored in a specific codebook. As the encoded data travel over a network, they are affected by noise or energy that disrupts the signal, which is often generated by other electronic devices. When that coded data and the noise that affected them arrive at their destination, the decoding algorithm consults its codebook and uses the structure of the hash to guess what the stored information is.
GRAND works by guessing the noise that affected the message and uses the noise pattern to deduce the original information. GRAND generates a series of noise sequences in the order they are likely to occur, subtracts them from the received data, and checks to see if the resulting codeword is in a codebook. While the noise appears random in nature, it has a probabilistic structure that allows the algorithm to guess what it might be.
The GRAND chip uses a three-tiered structure, starting with the simplest possible solutions in the first stage and working up to longer and more complex noise patterns in the two subsequent stages. Each stage operates independently, which increases the throughput of the system and saves power.
The device is also designed to switch seamlessly between two codebooks. It contains two static random-access memory chips, one that can crack codewords, while the other loads a new codebook and then switches to decoding without any downtime.
The researchers tested the GRAND chip and found it could effectively decode any moderate redundancy code up to 128 bits in length, with only about a microsecond of latency. Médard and her collaborators had previously demonstrated the success of the algorithm, but this new work showcases the effectiveness and efficiency of GRAND in hardware for the first time.
Developing hardware for the novel decoding algorithm required the researchers to first toss aside their preconceived notions. We could not go out and reuse things that had already been done. This was like a complete whiteboard. We had to really think about every single component from scratch. It was a journey of reconsideration. When we do our next chip, there will be things with this first chip that we will realise we did out of habit or assumption that we can do better.
– Lead Researcher
Since GRAND only uses codebooks for verification, the chip not only works with legacy codes but could also be used with codes that have not even been introduced yet. In the lead-up to 5G implementation, regulators and communications companies struggled to find consensus as to which codes should be used in the new network. Regulators ultimately chose to use two types of traditional codes for 5G infrastructure in different situations. Using GRAND could eliminate the need for that rigid standardisation in the future.
Moving forward, the researchers plan to tackle the problem of soft detection with a retooled version of the GRAND chip. In soft detection, the received data are less precise. They also plan to test the ability of GRAND to crack longer, more complex codes and adjust the structure of the silicon chip to improve its energy efficiency.
The trial Mobile Money service approved by the Prime Minister will set a precedent for applying a “sandbox” scheme for new services and professions in the digital society. Sandbox is a controlled institutional framework applied to new technologies, products, services, and business models. It is an environment for technology firms to try their new technological apps and business models. After the trial period, management agencies will review the trial implementation and then accept or reject it.
Using laws to set rules to deal with new issues arising from the application of new technologies is a challenge. As per a press release, the apps may have a rapid impact on society that management systems may not be able to keep up with. Many traditional business fields have changed, and businesses have to utilise technology to work more effectively. It is impossible to manage new services and business models within the existing framework because policies tend to lag behind practices. Therefore, a sandbox model is more advantageous.
According to an industry expert, it is impossible to demand state management agencies to create policies for the future. Many countries apply sandbox policies to encourage enterprises to develop new business models, with certain limitations in deployment. The Prime Minister has put into effect the pilot implementation of Mobile Money services – making payments for small-value goods and services with telecom accounts. The pilot programme will last two years.
This is the first service that the government has applied the sandbox mechanism managed by several ministries and branches. The government hopes the service will contribute to the development of non-cash payments, and promote the access and use of financial services, especially in rural areas. Businesses can only provide Mobile Money to remit money and make payments for legal goods and services in Vietnam in accordance with current laws. Mobile Money is only applied to domestic transactions with a monthly transaction value limit of VND10 million (US$4,397).
Vietnam is not the first country that has accepted a new technology platform, but experts said that it has an advantage by learning lessons from predecessors. In Vietnam, the proportion of credit card users is still low, but mobile subscriber density is very high. 99% of transactions with a small value of below VND100,000 (US$4) are carried out in cash. Mobile Money will be a strong solution to promote non-cash payments in society.
The Minister of Information and Communications stated that Mobile Money is a convincing example that shows that telecom carriers can become platforms for many things, not only telecom infrastructure. They can become platforms for data, computing, digital content, authentication, IT services, and the Internet of Things (IoT).
Mobile Money is expected to help Vietnam become a digital society. The project is the first sandbox involving many ministries and sectors to be piloted to meet the needs of society. It will pave the way for more sandboxes to be applied to other new services and business models in the future. He added that Mobile Money is a great opportunity for mobile network operators to build an ecosystem to accelerate digital transformation.
A research team led by biomedical engineers at the City University of Hong Kong (CityU) has developed a new generation of microneedle patches made of ice that melt after the pain-free delivery of drugs.
Experiments using this ground-breaking invention on mice with cancers have shown that the animals’ immune responses were much better than those seen in conventional vaccination methods. The technology paves the way for developing an easy-to-use cell therapy and other therapeutics against cancers and other diseases.
Made from a cryogenic solution, these icy microneedles are less than 1mm long and can deliver living mammalian cells into the skin. The device is like a skin patch and the microneedles can detach from the patch base, melt and then penetrate the skin.
The research is led by Dr Xu Chenjie, Associate Professor in the Department of Biomedical Engineering (BME), and the findings were published in Nature Biomedical Engineering under the title “Cryomicroneedles for Transdermal Cell Delivery”.
Dr Xu explained that traditional cell therapy for skin disorders is invasive, painful, complicated, low-efficient, risks infection, and requires experienced professionals. The ready-to-use device can circumvent complex and redundant procedures during each drug administration. In addition, it can be stored for months in a refrigerator and is easily transported and deployed.
The applications for this device are not limited to the delivery of cells. It can package, store, and deliver any type of bioactive therapeutic agents such as proteins, peptides, mRNA, DNA, bacterial, and vaccines, and it can improve both the therapeutic efficacy and patient compliance during cell therapies.
As a proof-of-concept, the researchers explored cell-based cancer immunotherapy through the intradermal delivery of ovalbumin-pulsed dendritic cells. Experiments showed that vaccination using therapeutic cells through this technology elicited robust antigen-specific immune responses and provided strong protection against tumours in mice.
These results were superior to the therapeutic outcomes of conventional vaccination methods. One of the start-up teams supported by the Seed Fund of HK Tech 300, CityU’s flagship innovation and entrepreneurship programme, is working on transferring the technology into a product and to promote its application.
Dr Chang Hao, a former postdoc in CityU’s BME, is the first author of this study, and Dr Xu is the corresponding author. Other researchers include Professor Wang Dongan and Professor Shi Peng from BME. The research team collaborated with scientists from Nanyang Technological University and the National University of Singapore.
The cell therapy technologies market is projected to reach US$5.6 billion by 2025 from US$2.8 billion in 2020, at a CAGR of 14.4% from 2020 to 2025. The emerging economies such as Australia and China are expected to provide a wide range of growth opportunities for players in the market which is driven by their large and growing populations as well as an increase in the number of clinical trials and investments in the field of personalized medicine in these countries.
The outbreak of COVID-19 is expected to have a minimal or negligible negative impact on the cell therapy technologies market. The rise in the incidences of COVID has led to an increase in the need for an efficient drug or vaccine for COVID, which could help in reducing the severity of the cases.
Cell-based research is an essential step during the manufacturing of vaccines, which can help in the growth of the market.
In the initial months of the outbreak of COVID, disruption in the supply chain had been witnessed, which has delayed the clinical trials. This can negatively impact the market to a certain extent. For instance, biopharmaceutical companies and major players have announced clinical trial delays.
A film is not complete without relevant and good music in the background. Music establishes atmosphere and mood and influences the audience’s emotional reactions as well as their interpretation of the story. A research team at the USC Viterbi School of Engineering sought to objectively examine the effect of music on cinematic genres. Their study aimed to determine if AI-based technology could predict the genre of a film based on the soundtrack alone.
While past work qualitatively indicates that different film genres have their own sets of musical conventions—conventions that make that romance film sound different from that horror movie—Narayanan and team set out to find quantitative evidence that elements of a film’s soundtrack could be used to characterise the film’s genre.
The study was the first to apply deep learning models to the music used in a film to see if a computer could predict the genre of a film based on the soundtrack alone. They found that these models were able to accurately classify a film’s genre using machine learning, supporting the notion that musical features can be powerful indicators in how people perceive different films.
This work could have valuable applications for media companies and creators in understanding how music can enhance other forms of media. It could give production companies and music supervisors a better understanding of how to create and place music in television, movies, advertisements, and documentaries in order to elicit certain emotions in viewers.
In their study, the team examined a dataset of 110 popular films released between 2014 and 2019. They used genre classification listed on the online database of information related to films to label each film as action, comedy, drama, horror, romance, or science-fiction, with many of the films spanning more than one of these genres.
They then applied a deep learning network that extracted the auditory information, like timbre, harmony, melody, rhythm, and tone from the music and score of each film. This network used machine learning to analyse these musical features and proved capable of accurately classifying the genre of each film based on these features alone.
The team also interpreted these models to determine which musical features were most indicative of differences between genres. The models didn’t give specifics as to which types of notes or instruments were associated with each genre, but they were able to establish that tonal and timbral features were most important in predicting the film’s genre.
The researchers examined the auditory information from each film using a technology known as audio fingerprinting. This technology allowed them to look at where the musical cues happen in a film and for how long. Using audio fingerprinting to listen to all of the audio from the film allowed them to overcome a limitation of previous film music studies, which usually just looked at the film’s entire soundtrack album without knowing if or when songs from the album appear in the film.
In the future, the team is interested in taking advantage of this capability to study how music is used in specific moments in a film and how musical cues dictate how the narrative of the film evolves over its course.
AI has been adopted in various areas, including healthcare. As reported by OpenGov Asia, U.S. Scientists have developed a new, automated, AI-based algorithm that can learn to read patient data from Electronic Health Records (EHR). The scientists, in a side-by-side comparison, showed that their method accurately identified patients with certain diseases as well as the traditional, “gold-standard” method, which requires much more manual labour to develop and perform.
Researchers from the Indian Institute of Technology in Bombay (IIT-Bombay) have developed a new data-processing technique to measure low amounts of soot accurately. This will help designers build better combustion-based devices such as internal combustion engines in cars.
Soot is tiny black particles that rise from a flame. Soot is formed when the fuel does not burn entirely. When fuel burns properly, a blue flame is emitted, whereas the flame is yellow when the soot is formed during burning and it becomes hot. Soot can cause cancer and respiratory and cardiac disorders and can also reduce the life of machine parts, a news report has explained.
Accurately measuring small amounts of soot can be a challenge and has spawned several research projects. The team from IIT-Bombay demonstrated a new technique to effectively reduce measurement errors when soot is present in low amounts. They analysed digital camera pictures of burning fuel to guess the temperature of the fuel and use the information to estimate the soot volume. The amount of soot can be measured using methods such as collecting and weighing the soot and studying a light beam shone on soot particles. The current study uses the last method. The researchers passed a beam of red laser light of a specific frequency, through a droplet of burning fuel and took images as it burnt. The light falling on the camera also contains the light from the burning fuel. The researchers used a narrow band filter to let only the laser light pass and filter out the light emitted by the burning fuel.
The report noted that when a flame having soot particles is shone with light, called background light, the particles absorb and scatter some of this light, so light reaching the camera is less bright. The researchers used the relation between the initial brightness of the laser light, the brightness of the light falling on the camera, and the soot volume to calculate the amount of soot. They then used a data-processing technique to compute the values of brightness from their images. Their challenge was to estimate the initial brightness of background light falling on soot particles since this isn’t directly captured in the images.
The team predicted the brightness of background light at every moment instead of using an average. They observed the flickers in background light at areas present outside the flame of the burning fuel, where there is no soot. They used it to estimate the background light falling on the soot particles. Using the new data processing technique, the team got lower errors, especially when the amount of soot produced is low. The technique does not require any additional equipment or extra expenditure, an added advantage.
The report added that to further reduce errors in the experiment, the researchers passed the laser light beam through a fixed and a rotating diffuser — a glass sheet that scatters light — before the light was incident on the burning fuel. A diffuser gives an evenly bright light and avoids the many speckles in the camera image. Speckles need to be removed while processing the data, leading to a loss of information. The researchers also validated their data processing technique. They used it to calculate the amount of soot for some previous measurements reported in the literature and verified the results. They also qualitatively checked their experimental observations.
They burnt a droplet of toluene (a carbon-based fuel) and compared their experimental observations with that in the literature. The team observed a similar peak value of the amount of soot. As expected, they saw high amounts of soot slightly inside the outer edges of the flame, where temperatures and fuel concentration are high, a researcher explained. The quantification of soot is crucial from an environmental perspective. This is an effective method to quantify soot to help identify strategies to mitigate combustion-based practices in India.
To achieve its targets to become a modernity-oriented industrialised nation by 2030 and a developed country with high income by 2045, Vietnam must succeed in the digital transformation process, in which agriculture is one of the priority areas, the Minister of Foreign Affairs stated at the Vietnam Agricultural Digital Transformation International Forum 2021.
The event was co-organised via videoconference by the Ministry of Foreign Affairs, the Vietnam Digital Agriculture Association (VIDA), and an e-newspaper outlet under the theme “Keeping up with market trends, ensuring the pivotal role of the economy during and after the COVID-19 pandemic.” The forum was an activity within the framework of the Vietnam International Agricultural Exhibition 2021 (AgriTech Expo 2021).
According to a news report, the forum consisted of two discussions that focussed on policy orientations and the theme “Shaping Vietnam’s digital agriculture until 2035” with the presentation of 20 speakers representing local authorities and leaders of businesses and corporations. Participants at the event shared scenarios of Vietnam’s agricultural digital transformation; key issues in Vietnam’s agricultural development strategies towards digitalisation given the complicated effects from the COVID-19 pandemic, supply chain disruption, and climate change.
The Minister of Foreign Affairs noted that the Vietnamese government should proactively and actively participate in the fourth industrial revolution and speed up the digital transformation process. The country must consider it a vital solution and an opportunity to make a breakthrough in socio-economic development.
Speaking at the event, the Minister of Agriculture and Rural Development pledged to offer all resources and the most favourable policies for businesses, aiming to bring added value to Vietnamese agricultural products and improve their trademarks. The Ministry will strongly support the digital transformation process and replace agricultural technology models as the Vietnamese agricultural sector is not only the “backbone” of the economy in difficult times but also a measurement of sustainability, the Minister said.
Representatives of foreign diplomatic agencies in Vietnam and from research institutes and socio-economic organisations attended the event. Also, domestic and foreign experts in the field of agricultural digital transformation from Japan, the Netherlands, Israel, and the World Bank as well as those from business associations and enterprises.
In August, the Ministry of Information and Communications (MIC) unveiled a plan to put farming households on e-commerce sites. Farming households will be supported to enter e-commerce sites to connect, advertise, and introduce their products. This will help them access new distribution channels and expand to domestic and international markets. Vietnam has nine million agricultural production households and four million private business households. All the households will be brought onto e-commerce sites, and this will be the first breakthrough to be made in developing the digital agricultural economy.
As OpenGov Asia reported, through e-commerce sites and digital platforms, farming households will receive useful information about farm produce markets, predicted demand and production capacity, weather forecasts, and seed and fertilizer supply. High-quality input materials and tools for agriculture production will be introduced to farmers via the platforms. Overall, MIC will put 12-13 million agricultural production and private business households on e-commerce sites. The targeted figure is five million households by the end of the year.
The President of Indonesia had unveiled a three-pronged strategy to boost Indonesia’s economic growth, providing insight into the direction of government policy for the remainder of his term. The green economy, the digitalisation of micro, small, and medium-sized enterprises (MSMEs), and the development of downstream industries are the three key aspects. Regarding the first of those three, he mentioned that the government intends to construct a “green industrial park” by October 2021 to produce “green products” using only renewable energy.
We know that the future of green products looks promising, and we have a great opportunity in this.
– President of Indonesia
The government also wants all 60 million MSMEs to be able to sell their goods and services on e-commerce and other digital platforms. Elaborating on the third key point, the President stated that the government began downstream industrial development in early 2020 with a ban on one of an ore export, which increased steel exports to US$10.5 billion. The scheme would be expanded to include additional goods and services such as bauxite, gold, copper, and palm oil.
The President’s speech represents the next step in a long-term shift in economic policymaking for a government that has previously appeared to be focused on short-term gains from extractive industries with little regard for environmental consequences. As per the Finance Ministry, the main sources of revenue from export levies and non-tax income are coal, crude palm oil (CPO), and raw mineral exports.
OpenGov Asia in an article reported that in recent years, the Indonesian government has taken concrete policy steps to advance its digital transformation agenda, and while steady progress has been made in that direction, the good news is that the pace of change is expected to accelerate. To address this, Indonesia’s President has pledged to press ahead with economic reform plans, despite the heavy burden that COVID-19 has imposed on the country since the outbreak began.
In his speech, the President stated that in today’s disruptive world, the spirit to change, the spirit to make changes, and the spirit to innovate has become the foundation for building an advanced Indonesia. In this context, the president’s agenda remained focused on structural reforms designed “to promote inclusive and sustainable economic development.” Repeating the promises made at the beginning of his second term, he added that the development of “quality human capital” and infrastructure development will remain priorities, the latter a hallmark of his seven years in power.
The Indonesian leader also expressed hope that reform would help the country begin the transition to a more sustainable economy. “A significant change in our economy will be the transition to new and renewable energy, as well as the acceleration of an economy based on green technology. The President believes that using clean energy and green technology will contribute to the development of a more environmentally friendly economy. As a result, efforts will be made to strengthen national research to align with the country’s development agenda.
Meanwhile, according to the Energy and Mineral Resources Ministry, renewable energy sources accounted for 11.2% of the national energy mix in 2020, with the remainder coming from fossil fuels. As per the executive director of the Institute for Essential Services Reform (IESR), the idea of environmental economics should be accompanied by responsibilities to reduce emissions, waste, and natural resource extraction.
“The term ‘green’ must not just be a slogan; there is a lot to do to [justify] such a claim,” IESR executive director told. The concept, he said, should be incorporated into a clear transition for all industries in Indonesia, reducing reliance on natural resources and extractive industry exports. He went on to say that one industrial park is insufficient to [declare] a green economy. As a result, the entire industry must follow suit.
Minnesota is among the latest states to introduce a secure digital option for residents to provide proof of vaccination against COVID-19. Using an app called Docket, Minnesotans can now view and share their immunisation records with local businesses, restaurants and other public venues where COVID vaccination is required.
The release of the app comes after the state Department of Health has been flooded with requests for vaccination records. So far this year, there have been more than 33,000 vaccine record requests, with 19,000 coming since July 1.
We recognise the importance of having a secure and convenient way to find, view, and share people’s their your family’s immunisation records, such as needing records for school or child care.
– Minnesota Department of Health, Infectious Disease Division Director
Residents who were vaccinated within the state can use the app to pull up their records through the Minnesota Immunisation Information Connection (MIIC), a confidential system that stores electronic immunisation records. The app then gives users the option of saving and distributing a PDF document of the record as they see fit.
The app allows residents to access a digital copy of their vaccination records without having to sign up for an app specifically intended for verifying COVID-19 vaccines. Docket uses two-factor security and searches for immunisation records based on a person’s name and date of birth.
The app also gives state residents a faster way to access their immunisation records. The volume of recent records requests to the health department means it is taking weeks for people to get their vaccination records back, but the app gives an option for people to more directly and quickly access their immunisation information.
Efforts to provide U.S. residents with digital versions of their immunisation records have picked up steam in recent months as employers and retail businesses increasingly require such proof. Reports of individuals providing fake COVID vaccine records have pushed states to launch their own verification apps to give residents a state-verified digital option for proving their vaccination status.
Residents who do not have a smartphone or do not want to use the app can still request a record of their vaccinations from the state or their health care provider. Those requests are currently taking weeks because of increased demand.
Virginia has also announced the addition of QR codes to its vaccination records. The code, which can be scanned using a smartphone, provides the same information as the paper records – however, since it is digitally signed by the Virginia Department of Health, it cannot be altered or forged. Virginia is the fifth state to adopt the secure SMART Health format.
As reported by OpenGov Asia, the COVID-19 pandemic revealed how big data and analytics technologies are being used in the public health sector. For example, governments and organisations developed contact tracing, where phone numbers and location data from mobile devices were combined with lab results in public health systems to issue alerts when an individual came in contact with a confirmed COVID patient. This information empowered people to preemptively self-isolate and/or head for rapid testing.
Public health agencies must understand how to use data effectively as the use of big data during the pandemic is essential. They should start working on plans to protect the privacy of the end-user and comply with the evolving laws around personal data privacy.
Additionally, organisations should determine what they will do with the data they are gathering. Data is only worthwhile if the organisations use the right tools to read and interpret it. Artificial Intelligence (AI) is vital for processing the vast amounts of data collected by today’s technology.