HOT: Higher-Order Dynamic Graph Representation Learning with Efficient Transformers

Many graph representation learning (GRL) problems are dynamic, with millions of edges added or removed per second. A fundamental workload in this setting is dynamic link prediction: using a history of graph updates to predict whether a given pair of vertices will become connected. Recent schemes for link prediction in such dynamic settings employ Transformers, modeling individual graph updates as single tokens. In this work, we propose HOT: a model that enhances this line of works by harnessing higher-order (HO) graph structures; specifically, k-hop neighbors and more general subgraphs containing a given pair of vertices. Harnessing such HO structures by encoding them into the attention matrix of the underlying Transformer results in higher accuracy of link prediction outcomes, but at the expense of increased memory pressure. To alleviate this, we resort to a recent class of schemes that impose hierarchy on the attention matrix, significantly reducing memory footprint. The final design offers a sweetspot between high accuracy and low memory utilization. HOT outperforms other dynamic GRL schemes, for example achieving 9%, 7%, and 15% higher accuracy than - respectively - DyGFormer, TGN, and GraphMixer, for the MOOC dataset. Our design can be seamlessly extended towards other dynamic GRL workloads

Stateful Detection of Adversarial Reprogramming

Adversarial reprogramming allows stealing computational resources by repurposing machine learning models to perform a different task chosen by the attacker. For example, a model trained to recognize images of animals can be reprogrammed to recognize medical images by embedding an adversarial program in the images provided as inputs. This attack can be perpetrated even if the target model is a black box, supposed that the machine-learning model is provided as a service and the attacker can query the model and collect its outputs. So far, no defense has been demonstrated effective in this scenario. We show for the first time that this attack is detectable using stateful defenses, which store the queries made to the classifier and detect the abnormal cases in which they are similar. Once a malicious query is detected, the account of the user who made it can be blocked. Thus, the attacker must create many accounts to perpetrate the attack. To decrease this number, the attacker could create the adversarial program against a surrogate classifier and then fine-tune it by making few queries to the target model. In this scenario, the effectiveness of the stateful defense is reduced, but we show that it is still effective

How cybernetics explains behavioural tensegrity and its advantages for society

This article explains the crucial role of the paradoxical dual contrary~complementary but interdependent properties of tensegrity. It is a neglected phenomenon in understanding how living things and their social organisations can become self-regulating and self-governing. Tensegrity is a defining feature of the architecture of nature. It is the driver of evolution. Organisations that include tensegrity into a polycentric self-governing process identified by Ostrom establish a basis from which to form an ecological form of governance for citizens to self-govern the sustainability of their host bioregions for the global common good. This requires engineering system scientists working with social scientists in educating students to become governance architects to custom design ecological firms. Research opportunities are identified in six hypotheses that include fundamental aspects of the universe

Behavior synthesis for high speed 3D color interpolation using VHDL

The purpose of this thesis is to study the methodology of behavioral synthesis and evaluate its usefulness compared to Register Transfer Level (RTL) synthesis. Custom IC design uses high-powered synthesis tools. Engineers have traditionally used RTL level descriptions of their circuits as input to these synthesis tools. As new Behavioral Synthesis tools are becoming more powerful, the option to describe their circuitry in a higher and more abstract level is becoming a more feasible option. Describing circuitry at a higher level has many advantages. It is easier to make architecture changes and higher level descriptions generally have significantly less lines of code and faster development times. To study behavioral synthesis a tri-linear interpolation algorithm is used. An RTL style and two different behavioral styles are used. Each are compared for area, power consumption, synthesis time, code length and throughput. The design is simulated before and after synthesis to verify the accuracy of the design using VHDL. Behavioral Compiler from Synopsys will be used to synthesize the design from VHDL to the gate level. It was found that behavioral synthesis can produce results nearly as good as an RTL described circuit. The results were generally 20% - 30% worse for this implementation using behavioral synthesis

Beyond the blueprint : a critical view on plans for transit-oriented development (TOD) in the new indonesian capital

Indonesia is relocating its capital city from Jakarta to a new city built from scratch called IKN (Ibu Kota Negara/Nusantara). Starting with the prioritized Government Precinct, the full relocation will be completed by 2045. The master plan emphasizes Transit-oriented Development (TOD) principles to encourage walking and transit, including incorporating the 10-minute concept. Meanwhile, South Korea has been moving the administrative capital city to Sejong City since 2007 and will be finished by 2030. Both cities share similar goals and approaches to implementing TOD; however, TOD can have pros and cons. While TOD can reduce traffic congestion, improve health, spur economic benefits and foster a sense of community, it can lead to gentrification, limited parking space that discourages early dwellers and vacant districts that induces negative impacts. Moreover, walking in Indonesia is unpopular due to the lack of safe, comfortable, and reliable transit modes, motorcycle and ride-hailing service dependence, and thermal comfort issues. Therefore, this thesis aims to identify the TOD aspects in IKN walkability and transit planning that may face issues after the city is developed based on the study case of pre- and post-construction Sejong so that IKN can anticipate and prepare. The Government Precinct encourages walking and transit by providing various types of pedestrian environments, permeable edges, and multiple transit systems, including BRT. The planned walking environments and transit nodes accommodate the 15-minute radius. Still, the planners must also consider the local context for the walkable distance, provide amenities that enhance thermal comfort, support modal shift facilities, and be vibrant with activities all time of the day and week so it is not vacant after working hours. Learning from Sejong, forcing people to walk in the interconnected walkways and limiting the parking lot to encourage people to use BRT is inefficient and inconvenient. Adopting a design adaptable to unforeseen challenges is crucial to promote social interaction, active mobility by walking and transit, and reducing automobile dependency. IKN must also implement non-physical interventions by enforcing strict policies, maximizing public transport frequency, and conducting regular assessments. A successful IKN plan can be a template for other TOD megaprojects globally