Reservoir Based Distributed Machine Learning for Edge Operation

Current RF sensors lack the computational resources to support practical, in-situtraining for intelligent signal classification . Deepdelay Loop Reservoir Computing (DLR) delivers reductions in form factor, hardware complexity and latency compared to the State-ofthe- Art (SoA) neural nets . DLR enables mobile edge platforms to authenticate andthen track emitters with fast SEI retraining .…

An NCAP like Safety Indicator for Self Driving Cars

This paper proposes a mechanism to assess the safety of autonomous cars . It assesses the car’s safety in scenarios where the car must avoid collision with an adversary . Core to this mechanism is a safety measure, called Safe-KamikazeDistance (SKD), which computes the average similarity between sets of safeadversary’s trajectories and kamikazes close to the safetrajectories .…

Catalogs of C and Python Antipatterns by CS1 Students

Understanding students’ programming misconceptions is critical . We propose catalogs ofantipatterns for two programming languages: C and Python . We analyzed the codes of 166 CS1 engineering students when they were codingsolutions to programming exercises . We catalog 41 CS1antipAtterns from 95 cataloged misconceptions in C and .…

Neurological Status Classification Using Convolutional Neural Network

A Convolutional Neural Network (CNN) model is able to accuratelydiscriminate between 4 different phases of neurological status in a non-Electroencephalogram(EEG) dataset recorded in an experiment in which subjects are exposed to physical, cognitive and emotional stress . We show that CNN models outperformstradic classification methods such as SVM, and RF, in comparison to other methods, in robustnessto noise by 97.46% accuracy on a noisy dataset .…

Long Term Orbit Dynamics of Decommissioned Geostationary Satellites

In nominal mission scenarios, geostationary satellites perform end-of-lifeorbit maneuvers to reach suitable disposal orbits . This research investigates the long-term orbitevolution of decommissioned geostations . The model accounts for all the relevant harmonics of the gravity field and solar radiation pressure and third-body perturbations caused by the Moon and the Sun .…

Knowledge Trust Security and Covertness In Massively Distributed Social Platforms An Epistemic Networks Approach

Social networks seeded, crystallized and structured by large-scale social platforms exhibit complicated epistemic structures and dynamics that arise from the nature of interactive knowledge that users/participants possess, share and shape . We use a novel approach to characterize knowledge statesand flows in social networks, based on epistemic networks, or epinets, to study the relationship between the structure of platforms and the structures of socialnetworks that form on them .…

Formal Methods for the Informal Engineer Workshop Recommendations

Formal Methods for the Informal Engineer (FMIE) was a workshop held at the Broad Institute of MIT and Harvard in 2021 to explore the potential role of verified software in the biomedical software ecosystem . The motivation for FMIE was the recognition that the life sciences and medicine areundergoing a transition from being passive consumers of software and AI/ML technologies to fundamental drivers of new platforms, including those which will need to be mission and safety-critical .…

Proving Non termination by Program Reversal

We present a new approach to proving non-termination of non-deterministic integer programs . Our technique is rather simple but efficient . It relies on apurely syntactic reversal of the program’s transition system followed by aconstraint-based invariant synthesis with constraints coming from both the original and reversed transition system .…

Data driven balancing of linear dynamical systems

We present a novel reformulation of balanced truncation, a classical model reduction method . The principal innovation comes through theuse of system response data that has been either measured or computed, withoutreference to any prescribed realization of the original model .…

How Are Learned Perception Based Controllers Impacted by the Limits of Robust Control

The difficulty of optimal control problems has classically been characterized in terms of system properties such as minimum eigenvalues ofcontrollability/observability gramians . We revisit these characterizations in the context of the increasing popularity of data-driven techniques likereinforcement learning (RL) and in control settings where input observationsare high-dimensional images and transition dynamics are unknown .…

GRN Generative Rerank Network for Context wise Recommendation

Generative Rerank Network (GRN) has outperformed state-of-the-art point-wise and list-wise methods . GRN has achieved a performanceimprovement of 5.2% on PV and 6.1% on IPV metric after the successfuldeployment in one popular recommendation scenario of Taobao application . Empirical resultsshow that GRN consistently and significantly outperforms state- of theartpoint-wise .…

Deep Learning based Codebook Design for Code domain Non Orthogonal Multiple Access Achieving a Single User Bit Error Rate Performance

The codebook design for code-domain non-orthogonal multiple access (CD-NOMA) can be considered as a constellation design for multi-user multi-dimensionalmodulation (MU-MDM) This paper proposes an autoencoder (AE)-basedconstellation design for MU-MDm with the objective of achieving a comparablebit error rate (BER) performance to single-user multidimensional modulation (SU-M) It has been demonstrated that the proposed designachieves a single-users BER bound with only 0.2dB loss, equivalently outperforming the existing CD-NomA designs, while maintaining their overloadingfactor .…

Feature Driven Survey of Physical Protection Systems

A physical protection system (PPS) integrates people, procedures, and equipment to protect assets or facilities . PPSs have targeted various systems, including airports, rail transport, highways, hospitals, bridges, the electricity grid, dams, power plants, seaports, oil refineries, and water systems .…

Emerging Trends for Global DevOps A New Zealand Perspective

The DevOps phenomenon is gaining popularity through its ability to supportcontinuous value delivery and ready accommodation of change . However, given therelative immaturity and general confusion about DevOps, a common view of expectations is lacking . Through investigation of online job advertisements, combined with interviews, we identified key Knowledge Areas,Skills and Capabilities for a DevOps role and their relative importance in New Zealand’s job market .…

Use of off the shelf information extraction algorithms in clinical informatics a feasibility study of MetaMap annotation of Italian medical notes

Study tested feasibility of using ‘off the shelf’ information extraction algorithms to identify medical concepts from Italian clinical notes . We used MetaMap to map medical concepts to the Unified Medical Language System (UMLS) Results in EXP1 showed that theItalian UMLS Metathesaurus sources covered 91% of the medical terms of the’Disorders’ semantic group, as found in the studied dataset .…

Tusom2021 A Phonetically Transcribed Speech Dataset from an Endangered Language for Universal Phone Recognition Experiments

There is growing interest in ASR systems that can recognize phones in alanguage-independent fashion . However, there is a paucity of realistic data that can be used to test such systems andtechnologies . This paper presents a publicly available, phoneticallytranscribed corpus of 2255 utterances (words and short phrases) in the endangered Tangkhulic language East Tusom (no ISO 639-3 code), a Tibeto-Burman variety spoken mostly in India .…

Monitoring of Particle Flux and LET Variations with Pulse Stretching Inverters

This work investigates the use of pulse stretching inverters for monitoring the variation of flux and Linear Energy Transfer (LET) of energetic particles . The basic particle detector consists of two cascaded pulse stretching(skew-sized) inverters designed in CMOS technology . The proposed solution is intended to operate as an on-chip particledetector within the self-adaptive multiprocessing systems .…

Fairness in Network Friendly Recommendations

Mobile traffic is dominated by content services (e.g., video), which typically use recommendation systems . NFR increase the network performance at the cost of being unfair towards certain contents when compared to the standard recommendations . Fair-NFR can achieve high network gains (similar to non-fair) with little unfairness, authors say .…

Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks

Social media platforms generate alot of real-time text information regarding public events with differenttopics . Mining social events is challenging because events typically exhibit heterogeneous texture and metadata are often ambiguous . We propose a novel Pairwise Popularity Graph Convolutional Network,named as PP-GCN, based on weighted meta-path instance similarity and textualsemantic representation as inputs .…

Tactile RL for Insertion Generalization to Objects of Unknown Geometry

We study the problem of aligning the object and environment with a tactile-based feedback insertion policy . The insertion process is modeled as an episodic policy that iterates between insertion attempts followed by pose corrections . We show that the optimalconfiguration of the learning agent (RL + curriculum + tactile flow) exposed to4 training objects yields an insertion policy that inserts 4 novel objects with over 85.0% success rate and within 3~4 attempts .…

MetricNet Towards Improved Modeling For Non Intrusive Speech Quality Assessment

The objective speech quality assessment is usually conducted by comparingreceived speech signal with its clean reference . Human beings are capable of evaluating the speech quality without any reference, such as in the meanopinion score (MOS) tests . We propose a novel non-intrusive speech quality measurement model, MetricNet, which combines label distribution learning and joint speech reconstruction learning .…

Hybrid Policy Learning for Energy Latency Tradeoff in MEC Assisted VR Video Service

Virtual reality (VR) promising to fundamentally transform a broad spectrum of industry sectors and the way humans interact with virtual content . Despite unprecedented progress, current networking and computing infrastructures are incompetent to unlock VR’s full potential . In this paper, we consider delivering the wireless multi-tile VR video service over a mobileedge computing (MEC) network .…

SMORES EP a Modular Robot with Parallel Self assembly

This paper presents aframework for SMORES types of modular robots to efficiently self-assemble intotree topologies . These modular robots form kinematic chains that have been shown to be capable of a large variety of manipulation and locomotion tasks . A desired kinematictopology can be mapped onto a planar pattern with optimal module assignment .…

Some Combinatorial Problems in Power law Graphs

The power-law behavior is ubiquitous in a majority of real-world networks . It has been shown to have a strong effect on various combinatorial, structural,and dynamical properties of graphs . In this paper, we study analytically several combinatorials problems for two power law graphs .…

From banks to DeFi the evolution of the lending market

The Internet of Value (IOV) with its distributed ledger technology (DLT)underpinning has created new forms of lending markets . Lending protocols are gaining traction, holding an aggregate liquidity supply of over $40 billion . We discuss the persisting reliance of DeFi lending on the traditional financial system, and conclude with the outlook of the lending market in the IOV era .…

An Evaluation of the Archive of Formal Proofs

Archive of Formal Proofs (AFP) is an online repository of formal proofs . It serves as a central location for publishing, discovering, and viewing libraries of proofs . Long-term users of the website are generally satisfied with the AFP but that there are anumber of areas, such as navigation, search and script browsing, that need improvement .…

A Formal Analysis of the MimbleWimble Cryptocurrency Protocol

MimbleWimble (MW) is a privacy-oriented cryptocurrency technology which provides security and scalability properties that distinguish it from other protocols of its kind . We present and discuss those properties and outline thebasis of a model-driven verification approach to address the certification of the correctness of the protocol implementations .…