FogStore: Toward a Distributed Data Store for Fog Computing

Stateful applications and virtualized network functions (VNFs) can benefit from state externalization to increase their reliability, scalability, and inter-operability. To keep and share the externalized state, distributed data stores (DDSs) are a powerful tool allowing for the management of classical trade-offs in consistency, availability and partitioning tolerance. With the advent of Fog and Edge Computing, stateful applications and VNFs are pushed from the data centers toward the network edge. This poses new challenges on DDSs that are tailored to a deployment in Cloud data centers. In this paper, we propose two novel design goals for DDSs that are tailored to Fog Computing: (1) Fog-aware replica placement, and (2) context-sensitive differential consistency. To realize those design goals on top of existing DDSs, we propose the FogStore system. FogStore manages the needed adaptations in replica placement and consistency management transparently, so that existing DDSs can be plugged into the system. To show the benefits of FogStore, we perform a set of evaluations using the Yahoo Cloud Serving Benchmark.Comment: To appear in Proceedings of 2017 IEEE Fog World Congress (FWC '17

The Fog Makes Sense: Enabling Social Sensing Services With Limited Internet Connectivity

Social sensing services use humans as sensor carriers, sensor operators and sensors themselves in order to provide situation-awareness to applications. This promises to provide a multitude of benefits to the users, for example in the management of natural disasters or in community empowerment. However, current social sensing services depend on Internet connectivity since the services are deployed on central Cloud platforms. In many circumstances, Internet connectivity is constrained, for instance when a natural disaster causes Internet outages or when people do not have Internet access due to economical reasons. In this paper, we propose the emerging Fog Computing infrastructure to become a key-enabler of social sensing services in situations of constrained Internet connectivity. To this end, we develop a generic architecture and API of Fog-enabled social sensing services. We exemplify the usage of the proposed social sensing architecture on a number of concrete use cases from two different scenarios.Comment: Ruben Mayer, Harshit Gupta, Enrique Saurez, and Umakishore Ramachandran. 2017. The Fog Makes Sense: Enabling Social Sensing Services With Limited Internet Connectivity. In Proceedings of The 2nd International Workshop on Social Sensing, Pittsburgh, PA, USA, April 21 2017 (SocialSens'17), 6 page

CNN-Based Projected Gradient Descent for Consistent Image Reconstruction

We present a new method for image reconstruction which replaces the projector in a projected gradient descent (PGD) with a convolutional neural network (CNN). CNNs trained as high-dimensional (image-to-image) regressors have recently been used to efficiently solve inverse problems in imaging. However, these approaches lack a feedback mechanism to enforce that the reconstructed image is consistent with the measurements. This is crucial for inverse problems, and more so in biomedical imaging, where the reconstructions are used for diagnosis. In our scheme, the gradient descent enforces measurement consistency, while the CNN recursively projects the solution closer to the space of desired reconstruction images. We provide a formal framework to ensure that the classical PGD converges to a local minimizer of a non-convex constrained least-squares problem. When the projector is replaced with a CNN, we propose a relaxed PGD, which always converges. Finally, we propose a simple scheme to train a CNN to act like a projector. Our experiments on sparse view Computed Tomography (CT) reconstruction for both noiseless and noisy measurements show an improvement over the total-variation (TV) method and a recent CNN-based technique

Polymerized ionic liquids by condensation polymerization: Stimuli responsive polyurethane gels and dispersions

Ionic liquids have been used in free radical polymerizations to make polymerized ionic liquid (PIL) materials of various types. PIL gels based on imidazolium cations have been found to exhibit an anion-exchange induced stimuli responsiveness. This thesis explores incorporation of ionic liquids in polyurethane (PU) polymers to make PIL PU gels and dispersions through condensation polymerization. PIL gels are synthesized through a single-pot approach that show stimuli response to solvents. This approach allows one to make these gels rapidly and cheaply on-site. These gels can reversibly porate in different solvents and are found to be porous when analyzed by scanning electron microscope (SEM). PIL based resins are also made in two steps, that show self-dispersion properties in water forming thermodynamically stable nano-scale particles. These materials can be transported as 100% solid resins, where they can be transformed into polyurethane dispersions (PUDs) onsite. These particles also show stimuli responsiveness to different anions and solvents

Reconfigurable Inspection in Manufacturing: State of the Art and Taxonomy

This article provides an overview of the evolution of the product quality and measurement inspection procedure with emphasis on the Reconfigurable Inspection System and Machine. The major components of a reconfigurable manufacturing system have been examined, and the evolution of manufacturing processes has been briefly discussed. Different Reconfigurable Inspection Machines (RIMs) and their arrangement in an assembly line as an inspection system have been carefully studied and the modern inspection system equipped in RMS has been compared to the traditional techniques commonly used in inspection of product quality. A survey of evolving inspection techniques is offered from the standpoint of technological challenges and advancement affecting manufacturing over time. As per authors' knowledge, the review on Reconfigurable Inspection in Manufacturing and taxonomy of reconfigurable inspection systems is rare. Considering the studies done in this domain, there is still resourceful taxonomy for this paradigm. Therefore, different types of inspection procedures have been discussed, their features and applications have been compared to arrive at the taxonomy of the RIS based on the understanding of the nature of a RIS after a critical review.Comment: 7th International Conference on Automation, Control and Robotics (ICACR) 202

BrainStorm @ iREL at #SMM4H 2024: Leveraging Translation and Topical Embeddings for Annotation Detection in Tweets

The proliferation of LLMs in various NLP tasks has sparked debates regarding their reliability, particularly in annotation tasks where biases and hallucinations may arise. In this shared task, we address the challenge of distinguishing annotations made by LLMs from those made by human domain experts in the context of COVID-19 symptom detection from tweets in Latin American Spanish. This paper presents BrainStorm @ iRELs approach to the SMM4H 2024 Shared Task, leveraging the inherent topical information in tweets, we propose a novel approach to identify and classify annotations, aiming to enhance the trustworthiness of annotated data.Comment: Accepted at SMM4H, colocated at ACL 202

Ceftriaxone induced neurotoxicity: a word of caution for elderly and patients with renal impairment

Ceftriaxone is a third-generation cephalosporin commonly used in inpatient settings and is associated with both hepatic and renal excretion. The cephalosporin group, particularly the fourth generation, including cefepime, has been commonly associated with encephalopathy, but recent literature has also suggested an increasing trend of encephalopathy related to ceftriaxone