TECH OFFERS

Environmental pollution concerns and high fuel cost is driving the car industry towards Electric Vehicle (EV). Li-ion cell is a common adopted energy source for EV. However, Li-ion cells required proper temperature control to function properly. A key factor that affects the battery is temperature. < 0°C:  difficult or impossible for charging >60°C:  difficult for discharging and risk of degradation, shortened service life >70°C ~ 90°C:  will trigger a self-heating reaction with internal cell faults with risk of thermal runaway, presenting safety hazards. Most Li-ion battery achieves their rated capacity at 20~25°C and their capacity will drop ~10% for every increase of 10°C. Regulating the battery temperature during continuous charge and discharge is a challenge, especially in temperate climates. Existing cooling solutions consist of the battery modules sitting on or attached to heat sinks that are in turn cooled by a coolant loop. The drawbacks are that the cooling efficiency is low, and the effectiveness is poor, since only a small part of each module receives the cooling effect. Besides, heat sinks are generally thick and heavy due to the coolant loop. The result is that temperatures will differ from module to module, cell to cell. Even within the same cell, different regions may have different temperatures. Battery packs used in EVs are constrained by space and weight, so cooling systems for the battery packs must be compact and lightweight, and yet meeting the cooling requirements. Our patent granted technology is able to carry coolant to each individual cell in a compact structure. This ensures consistency and uniformity of heat transfer from each cell in a battery pack, extending their lifespan and safety by allowing them to operate in their optimum temperature range (10 ~ 35°C), Charging and discharging can also take place in all ambient temperature.

Network-based security systems have been the standard in the past for corporate security. Technology such as legacy SIEM-SOC (Security Information and Event Management - Security Operation Center) was thought as sufficient protection for cyber threats however it comes up short when it comes to responding to cyber attacks. Endpoint-based Monitoring and Incident Response (EMIR) enhances this approach by not only identifying threats but also providing a resolution to the threat.  SIEM SOC provides very little visibility of the threats because users are told whether the malicious code was accessed by the infected endpoint but not whether the code was executed. EMIR can tell what exactly happened, how it happened, and where the threat came from. It can also remediate the issue without the customers’ intervention.  Another limitation of SIEM SOC is that the incident response can only notify users of the incident. This incident may occur in the middle of the night and won’t be responded to until the staff responsible reports for work. This can leave hackers many hours to infiltrate and extract important data. EMIR works 24/7, 365 days a year remotely to notify users, intercept the attack, and remedy any damage that has occurred. This is of immense importance for companies of all sizes because cybercriminals are looking to make money from any enterprise that is vulnerable. The threat of cyber attacks for companies and individuals has never been higher than today. EMIR is the protection that companies need to be secure in today’s vulnerable cyber landscape.  

This technology offer is by a team with expertise in the development of solutions for measuring physiological and cognitive states. The team offers and develops software modules for measuring several physiological and cognitive states such as drowsiness, distraction, stress, cognitive load, and mind wandering. Monitoring of physiological and cognitive states enables a better understanding of human performances and errors.

This technology offer is a predictive diagnostic technology based on sound, for the early detection of machines which are going to break down. By analysing the sounds produced by machines in their routine operations, artificial intelligence (AI) algorithms are able to determine if these machines are functioning properly, or if they are on the verge of breaking down.

Use Face Tracking Technology to detect facial features and emotions in real time. Face Tracking can be used to add filters like hat, moustache and glasses automatically in photos and audio-visual effects in videos. These effects respond to facial emotions and actions such as an opening mouth, jaw drop, smiling, blinking eyes, pouted mouth and many customized gestures. Face Filters works with any real-time camera feed (both front and rear cameras).  

The company's pressure mat can sense applied pressure and its corresponding position on a flat or curved surface. Its pressure sensing layer is constructed with multiple rows and columns of piezoresistive sensor points. The piezoresistive sensor’s electrical resistance decreases when a pressure is applied to it. There is a certain relationship between a sensor point’s resistance and the applied pressure on it. By measuring each sensor point’s electrical resistance, the applied pressures at all the sensor points can be derived. The pressure mat can also be made stretchable to suit some applications.

The software platform that uses natural language processing & machine learning to synthesize and analyze massive text-based datasets. By leveraging the platform, strategists and researchers can spend less time searching, compiling and reading content and more time generating insights. The software's technology extracts key phrases and words from thousands of documents at a time and identifies similarities across unstructured text content. Using a similarity score, the software segments data to reveal patterns and trends where standard classification models and humans frequently misrepresent reality. This way, the software allows the user to avoid human bias which often plagues qualitative analysis when identifying market and narrative trends.  

The technology uses a deep learning neural network to determine landmarks for every face found in a picture. The model is pre-trained and optimized to run natively on the mobile and PC (with no internet required), thus preserving the privacy of users without uploading the photos to the cloud. It can scan a large number of photos (in thousands) and group all the detected and recognized faces into unique faces (unique persons).  Adult faces, in particular, are detected with a high degree of accuracy as facial landmarks for adults will be distinct. The model works well in the presence of partial occlusions that cover a face. This technology comes as an SDK with an extensive list of APIs to cater to 3 distinct use cases. SDK is a plug and play that can be quickly integrated into a mobile/PC environment.

A Polish company has built its own full stack blockchain/Distributed Ledger Technology (DLT) platform that demonstrates the unique high-performance architecture applicable in various business financial applications. Its solution is a universal platform that can store real (fiat) money, any data, and identity directly on-chain. It is an enterprise-grade platform that merges real money, identity, and data to enable agile business models. Its technology is compliant with EU’s e-money regulations, transacting national currencies inherently linked with end-user identity. It also processes any public and private documents on the chain for an embedded trusted solution in line with EU's GDPR, Durable Medium and MIFID II standards.  The solution is fully mobile-optimized, with full DLT nodes running on users’ smartphones and thus ideal for mass-market applications. The company has submitted seven distributed ledger related patents, like: obsolescence lock, consensus mechanism, currency supply control and on-chain data storage.