Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of an Infant Incubator for Cost Reduction and Improved Usability for Indian Health Care Centers

India is 2nd most populated country in the world and the birth rate is very high. According to market survey’s, in India every year 26 million infants are born. Out of 26million 2.6 Million infants are prematurely born with low birth weight (lbw). These LBW infants are generally kept in chambers referred to as “incubators” which are housings with controlled temperature and humidity. Since from the time incubators are introduced in the hospitals, the survival rate of premature babies have significantly raised up. Thus incubators are highly important device in Intensive Care Unit’s (ICU) at hospitals. This study is to design an Infant incubator with improved usability targeting low budget hospitals. To solve the problem, various data is collected, referred and documented from various websites, books and journals. Product study is carried out at a local hospital. Market study is carried to know about the available models. Leading model in the market is selected as benchmark product.Based on literature review, product study, market study and other analytical deisgn techniques, Product design specification (PDS) is generated. Based on the PDS, five concepts are developed. Final concept is selected based on Pugh’s method of concept selection. From the study the finalized concept has superior usability features compared to that in the present market.
ColorfulCurves: Palette-Aware Lightness Control and Color Editing via Sparse Optimization

Color editing in images often consists of two main tasks: changing hue and saturation, and editing lightness or tone curves. State-of-the-art palette-based recoloring approaches entangle these two tasks. A user's only lightness control is changing the lightness of individual palette colors. This is inferior to state-of-the-art commercial software, where lightness editing is based on flexible tone curves that remap lightness. However, tone curves are only provided globally or per color channel (e.g., RGB). They are unrelated to the image content. Neither tone curves nor palette-based approaches support direct image-space edits---changing a specific pixel to a desired hue, saturation, and lightness. ColorfulCurves solves both of these problems by uniting palette-based and tone curve editing. In ColorfulCurves, users directly edit palette colors' hue and saturation, per-palette tone curves, or image pixels (hue, saturation, and lightness). ColorfulCurves solves an L2,1 optimization problem in real-time to find a sparse edit that satisfies all user constraints. Our expert study found overwhelming support for ColorfulCurves over experts' preferred tools.
Leptin Level in Patients with Type 2 Diabetes as a Risk Factor for Cardiovascular Disease

Leptin Level Background: Investigating adipocytokine leptin (Lep) levels in type 2 diabetes mellitus (T2DM) and their association with 6 anthropometry, lipid profile parameters could lead to understanding the role of Lep in T2DM and related risk of cardiovascular complications; Moreover, could further help prevention and management of these complications.
Vision Architectures

Convθ Input: image x ∈ RC×H×W , number of output channels C′, filter size F ≤ min(H,W ), stride S ≥ 1, padding P ≥ 0 Parameters: three-dimensional filter Wo ∈ RC×F×F and bias bo ∈ R for all output channels o ∈ {1 . C′} Output: convolved y ∈ R ′×H′×W ′ where H ′ = ⌊ H+2P−F S ⌋ + 1 and W ′ = ⌊ W+2P−F S ⌋ + 1 (Lemma 1.1) 1. Pad the input x ∈ RC×H×W with P zeros on the edges to obtain x̃ ∈ RC×(H+2P )×(W+2P . 2. For o = 1 . . . C′: (a) Prepare to build a new matrix yo ← []. (b) For row i = 1, S, 2S, . (moving down in stride S) i. iend ← i+ F − 1 ii. If iend > H + 2P : continue iii. Prepare to build a new row yo,i ← []. iv. For column j = 1, S, 2S, . (moving right in stride S) A. jend ← j + F − 1 B. If jend > W + 2P : continue C. Compute the (i, j)-th Hadamard product for output channel o and append:
General overview of Intel SGX

Intel Secure Guard Extensions is a hardware feature available to Intel processors that provides a trusted execution environment fit for remote computation. It enables the creation of secure enclaves, handled by the trusted processor, that are isolated from all other software including the host’s system software. They also provide means for users to remotely attest the legitimacy of the enclaves. The mechanisms that were developed to achieve this will be presented in this overview.
Review for Feature Based Image Re-Ranking

: Search reranking is considered as a best and common way to improves retrieval precision. The images are retrieved using the associated textual information, such as surrounding text from the web page. The performance of such systems mainly relies on the relevance between the text and the images. However, they may not always match well enough, which causes noisy ranking results. For instance, visually similar images may have very different ranks. So reranking has been proposed to solve the problem. Image re-ranking, as an effective way to improve the results of web-based image search however the problem is not trivial especially when we are considering multiple features or modalities for search in image and video retrieval. This paper suggests a new kind of reranking algorithm, the circular reranking, that supports the mutual exchange of information across multiple modalities for improving search performance and follows the philosophy of strong performing modality could learn from weaker ones.
Socio-Technical Anti-Patterns in Building ML-Enabled Software (Supplementary Material)

—The artifacts described in this document belong to the paper ‘Socio-technical anti-patterns in building ML-enabled software: Insights from Leaders on the Forefront’. We conducted a large-scale qualitative analysis of existing videos from an online community employing reflexive thematic analysis. This way, we generated 17 anti-patterns in seven contexts and development activities with corresponding causes and recommendation. The artifacts contain initial, interim, and final themes and corresponding codes, showing the evolution of codes and naming of the themes.
Adaptive Learning Methods

We consider an online learning environment in which an algorithm, at each step t = 1, 2, 3, . , proposes a hypothesis wt ∈ R then immediately gets punished by lt(wt) ∈ R where lt : R → R is some unknown loss function (possibly adversarial, i.e., crafted against wt). In the beginning, the algorithm has no information and uses some initial hypothesis w1; at step t ≥ 1, it may use all the information so far to propose wt+1. Let u = arg minw∈Rd ∑T t=1 lt(w) denote the best hypothesis in retrospect. We want to bound the “regret” of the algoirthm as a function of the total number of steps T :
University of Birmingham Osteoprotegerin-Mediated Homeostasis of Rank+ Thymic Epithelial Cells Does Not Limit Foxp3+ Regulatory T Cell Development

In the thymus, medullary thymic epithelial cells (mTEC) regulate T cell tolerance via negative selection and Foxp3 + regulatory T cell (Treg) development, and alterations in the mTEC compartment can lead to tolerance breakdown and autoimmunity. Both the receptor activator for NF- k B (RANK)/RANK ligand (RANKL)/osteoprotegerin (OPG) axis and expression of the transcriptional regulator Aire are involved in the regulation of thymus medullary microenvironments. However, their impact on the mechanisms controlling mTEC homeostasis is poorly understood, as are the processes that enable the thymus medulla to support the balanced production of mTEC-dependent Foxp3 + Treg. In this study, we have investigated the control of mTEC homeostasis and examined how this process impacts the efﬁcacy of Foxp3 + Treg development. Using newly generated RANK Venus reporter mice, we identify distinct RANK + subsets that reside within both the mTEC hi and mTEC lo compartments and that represent direct targets of OPG-mediated control. Moreover, by mapping OPG expression to a subset of Aire + mTEC, our data show how cis - and tran s-acting mechanisms are able to control the thymus medulla by operating on multiple mTEC targets. Finally, we show that whereas the increase in mTEC availability in OPG-deﬁcient ( Tnfrsf11b 2 / 2 ) mice impacts the intrathymic Foxp3 + Treg pool by enhancing peripheral Treg recirculation back to the thymus, it does not alter the number of de novo Rag2pGFP + Foxp3 + Treg that are generated. Collectively, our study deﬁnes patterns of RANK expression within the thymus medulla, and it shows that mTEC homeostasis is not a rate-limiting step in intrathymic
Plasma cfDNA analysis can be facilitated by membrane based filtration of whole blood regardless of additive

Cell-free DNA (cfDNA) has emerged as a pivotal biomarker for various noninvasive screening applications such as noninvasive prenatal screening, minimum residual disease monitoring, and transplant rejection prediction. However, the efficacy of these applications is heavily reliant on the detection of minority nucleic acid species amidst a vast background of host DNA. Therefore, it is crucial to prevent the dilution of the desired cfDNA signal with genomic DNA originating from white blood cell (WBC) degradation. The most commonly adopted sample collection methods prevent WBC lysis by either adding a stabilizing agent to the collection tube, like Streck, or through immediate centrifugation following the collection of whole blood. In this study, we propose an alternative for plasma sample collection that involves membrane based filtration of plasma from cellular blood components at the point of collection. Our findings demonstrate that cfDNA recovered using this method performs equally or better compared to conventional methods and enables the implementation of novel and more accessible blood collection procedures.
Feasibility and reliability of online vs in-person cognitive testing in healthy older people

Early evidence in using online cognitive assessments show that they potentially offer a feasible and resource efficient alternative to in-person clinical assessments in evaluating cognitive performance, yet there is currently little understanding about how these assessments relate to traditional, in-person cognitive tests. We assess the feasibility and reliability of NeurOn, a novel online cognitive battery, measuring processing speed, executive functioning, spatial working memory, episodic memory, attentional control, visuospatial functioning and spatial orientation. 32 participants (mean age: 70.19) completed two testing sessions, unsupervised online and in-person, one-week apart. Participants were randomised in the order of testing appointments. For both sessions, participants completed questionnaires prior to a cognitive assessment. Test-retest reliability and concurrent validity of the online cognitive battery was assessed by comparing performance in repeated tasks across testing sessions as well as with traditional in-person cognitive tests. We found that global cognition in the NeurOn battery moderately validated against MoCA performance. The battery demonstrated moderate test-retest reliability as performance across repeated tasks did not show a significant difference. Concurrent validity was found only between the online and paper versions of the Trail Making Test -A, as well as global cognitive performance between online and in-person testing sessions. Overall, the NeurOn cognitive battery provides a promising tool for measuring cognitive performance online both longitudinally and across short retesting intervals within healthy older adults. When considering cost-effectiveness, flexible administration, and improved accessibility for wider populations, online cognitive assessments have the potential to improve future screening for neurodegenerative diseases.
Performance Analysis of Multiuser Downlink MIMO NOMA Wireless Communication System on Color Image Transmission

-In this paper, a comprehensive study has been made to evaluate the performance of 2 × 2 multiantenna configured MIMO NOMA wireless communication system. The simulated system incorporatesvarious types of signal processing techniques (Channel coding: LDPC & Convolutional, Digital modulation: QPSK, DQPSK & 4-QAM, Signal detection: ML decoding based QR channel decomposition aided SIC). On considering downlink transmission of encrypted color image of each of two users in a hostile fading channel, it is noticeable from MATLAB based simulation study that the system is very much robust and effective in retrieving transmitted color images underutilization of LDPC channel coding and 4-QAM digital modulation techniques. The performance of the simulated downlink MIMO NOMA wireless communication system has been evaluated in terms of bite error rate(BER) under scenario of various receive signal to noise ratio(SNR) ranging from 0dB to 16dB.
LIDAR-based Detection of Furrows for Agricultural Robot Autonomous Navigation

Robust and accurate autonomous navigation is a main challenge in agricultural robotics. This paper presents a LIDAR-based processing system for autonomous robot navigation in crops with high vegetation density. The method detects and locates the crop furrows and provides them to the robot con-trol system, which guides the robot such that its caterpillar tracks move along the furrows preventing damages in the crop. The proposed LIDAR-based processing pipeline includes various inconsistencies removal and template matching steps to deal with the high noise level of LIDAR scans. It has been implemented in C++ using ROS Noetic and validated in two different plantations with different crop growth status.
Lost and Found System with Open Vocabulary Object Detector

Hong Kong International Airport (HKIA) as one of the busiest airports in the world, daily number of passengers passing through is very high, which results in the high usage of the lost and found service of HKIA. Currently, the lost and found service is labour intensive and a more efficient method is needed. This goal of this project is to propose an autonomous method to provide the lost and found service. Such approach could reduce the lost and found system’s labour dependency level and improve overall efficiency. In this project, an open-vocabulary object detection model will be developed, tested, and added to the smart patrol robots of HKIA. The open-vocabulary object detection model involves image and text embedding, which could be done by Vision and Language Knowledge Distillation (ViLD). ViLD has been tested for this project and the results show that it could be used as an open-vocabulary object detection model for a lost and found system. Different image and text encoders such as ‘You Only Look Once’ model (YOLO) and Region-Convolutional Neural Network (R-CNN) will be tested in future in order to maximize the accuracy and efficiency of the model.
Hector: A Framework to Design and Evaluate Scheduling Strategies in Persistent Key-Value Stores

Key-value stores distribute data across several storage nodes to handle large amounts of parallel requests. Proper scheduling of these requests impacts the quality of service, as measured by achievable throughput and (tail) latencies. In addition to scheduling, performance heavily depends on the nature of the workload and the deployment environment. It is, unfortunately, difficult to evaluate different scheduling strategies consistently under the same operational conditions. Moreover, such strategies are often hard-coded in the system, limiting flexibility. We present Hector, a modular framework for implementing and evaluating scheduling policies in Apache Cassandra. Hector enables users to select among several options for key components of the scheduling workflow, from the request propagation via replica selection to the local ordering of incoming requests at a storage node. We demonstrate the capabilities of Hector by comparing strategies in various settings. For example, we find that leveraging cache locality effects may be of particular interest: we propose a new replica selection strategy, called Popularity-Aware, that supports 6 times the maximum throughput of the default algorithm under specific key access patterns. We also show that local scheduling policies have a significant effect when parallelism at each storage node is limited.
DASH: Asynchronous Hardware Data Processing Services

As databases need to strike a good balance of high performance at low costs, hardware-accelerators like FPGAs are increasingly considered to improve core database operations. In this paper we complement previous research, where hardware accelerators are tightly integrated with the host CPU, and expose the FPGA as a hardware data processing service to a cluster of databases to delegate the asynchronous execution of compute-intensive database operations. We apply our novel architecture, called DASH, to the use case of string dictionary compression using the compute-intensive RePair compression and demonstrate its benefit in this distributed architecture. We also explain how DASH can be applied to other database scenarios and propose a research agenda.
Algorithms in Discrepancy Theory and Lattices

Algorithms in Discrepancy Theory and Lattices Harishchandra Ramadas Chair of the Supervisory Committee: Assistant Professor Thomas Rothvoß Department of Mathematics This thesis deals with algorithmic problems in discrepancy theory and lattices, and is based on two projects I worked on while at the University of Washington in Seattle. A brief overview is provided in Chapter 1 (Introduction). Chapter 2 covers joint work with Avi Levy and Thomas Rothvoß in the field of discrepancy minimization [28]. A well-known theorem of Spencer shows that any set system with n sets over n elements admits a coloring of discrepancy O( √ n). While the original proof was non-constructive, recent progress brought polynomial time algorithms by Bansal, Lovett and Meka, and Rothvoß. All those algorithms are randomized, even though Bansal’s algorithm admitted a complicated derandomization. We propose an elegant deterministic polynomial time algorithm that is inspired by Lovett-Meka as well as the Multiplicative Weight Update method. The algorithm iteratively updates a fractional coloring while controlling the exponential weights that are assigned to the set constraints. A conjecture by Meka suggests that Spencer’s bound can be generalized to symmetric matrices. We prove that n × n matrices that are block diagonal with block size q admit a coloring of discrepancy O( √ n · √ log(q)). Bansal, Dadush and Garg recently gave a randomized algorithm to find a vector x with entries in {−1, 1} with ‖Ax‖∞ ≤ O( √ log n) in polynomial time, where A is any matrix whose columns have length at most 1. We show that our method can be used to deterministically obtain such a vector. In Chapter 3, we discuss a result in the broad area of lattices and integer optimization, in joint work with Rebecca Hoberg, Thomas Rothvoß and Xin Yang [22]. The number balancing (NBP) problem is the following: given real numbers a1, . , an ∈ [0, 1], find two disjoint subsets I1, I2 ⊆ [n] so that the difference | ∑ i∈I1 ai − ∑ i∈I2 ai| of their sums is minimized. An application of the pigeonhole principle shows that there is always a solution where the difference is at most O( √ n 2n ). Finding the minimum, however, is NP-hard. In polynomial time, the differencing algorithm by Karmarkar and Karp from 1982 can produce a solution with difference at most n−Θ(logn), but no further improvement has been made since then. We show a relationship between NBP and Minkowski’s Theorem. First we show that an approximate oracle for Minkowski’s Theorem gives an approximate NBP oracle. Perhaps more surprisingly, we show that an approximate NBP oracle gives an approximate Minkowski oracle. In particular, we prove that any polynomial time algorithm that guarantees a solution of difference at most 2 √ /2 would give a polynomial approximation for Minkowski as well as a polynomial factor approximation algorithm for the Shortest Vector Problem.
Fast and Robust Resource-Constrained Scheduling with Graph Neural Networks

Resource-Constrained Project Scheduling Problems (RCPSPs) are NP-complete, which makes it challenging to efficiently solve large instances and robustify solutions in the presence of uncertainty. To remedy this, we learn to efficiently mimic the solutions produced by Constraint Programming (CP) solver, using a Graph Neural Network (GNN) architecture designed to capture the structure of RCPSPs. Since the GNN solution may violate constraints, we ensure schedule feasibility at inference time by extracting the task ordering from the GNN schedule and post-processing it with the well-known Schedule Generation Scheme (SGS). We find that SIREN, the resulting algorithm, produces schedules that are of higher quality than those produced by the CP solver within the same computation time budget. The speed and solution quality of SIREN make it suitable as a component of an on-line scenario-based optimisation procedure for RCPSPs with stochastic durations. This leads to the SERENE system, which robustly selects, in real-time, the best next tasks to start in order to minimise the average makespan over the scenarios. Empirically, SERENE achieves better average makespan over different realisations of uncertainty than deterministic algorithms that continuously reschedule on the basis of either the worst, best or average task durations.
SuperCut: Communication-Aware Partitioning for Near-Memory Graph Processing

The parallel execution of many graph algorithms is frequently dominated by data communication overheads between compute nodes. This bottleneck becomes even more pronounced in Near-Memory Processing (NMP) architectures with multiple memory cubes as local memory accesses are less expensive. Existing near-memory architectures typically use graph partitioning methods with a fixed vertex assignment, which limits their potential to improve performance and reduce energy consumption. Here, we argue that an NMP-based graph processing system should also consider the distribution of vertices onto memory cubes. We propose SuperCut, a framework for near-memory architectures to effectively reduce communication overheads while maintaining computational balance. We evaluate SuperCut via architectural simulation with 6 real-world datasets and 4 representative applications. The results show that it provides up to 1.8x total energy reduction and 2.6x speedup relative to current state-of-the-art approaches.