Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving pairwise comparison models using Empirical Bayes shrinkage

Comparison data arises in many important contexts, e.g. shopping, web clicks, or sports competitions. Typically we are given a dataset of comparisons and wish to train a model to make predictions about the outcome of unseen comparisons. In many cases available datasets have relatively few comparisons (e.g. there are only so many NFL games per year) or efficiency is important (e.g. we want to quickly estimate the relative appeal of a product). In such settings it is well known that shrinkage estimators outperform maximum likelihood estimators. A complicating matter is that standard comparison models such as the conditional multinomial logit model are only models of conditional outcomes (who wins) and not of comparisons themselves (who competes). As such, different models of the comparison process lead to different shrinkage estimators. In this work we derive a collection of methods for estimating the pairwise uncertainty of pairwise predictions based on different assumptions about the comparison process. These uncertainty estimates allow us both to examine model uncertainty as well as perform Empirical Bayes shrinkage estimation of the model parameters. We demonstrate that our shrunk estimators outperform standard maximum likelihood methods on real comparison data from online comparison surveys as well as from several sports contexts.
Application of Deep Learning for Infant Vomiting and Crying Detection

Obstruction of the nose and mouth by vomit or quilts is the main cause of sudden infant death. Different baby sleeping postures will increase the difficulty of face detection. Therefore, a deep learning neural network is adopted to detect baby faces and a novel algorithm is proposed to detect vomiting of infants in this paper. The SSD + mobilenet network in Teansorflow is adopted. Experimental results show reasonable detection results of the proposed method.
Specification-Based Protocol Obfuscation

This paper proposes a new obfuscation technique of a communication protocol that is aimed at making the reverse engineering of the protocol more complex. The obfuscation is based on the transformation of protocol message format specification. The obfuscating transformations are applied to the Abstract Syntax Tree (AST) representation of the messages and mainly concern the ordering or aggregation of the AST nodes. The paper also presents the design of a framework that implements the proposed obfuscation technique by automatically generating, from the specification of the message format, a library performing the corresponding transformations. Finally, our framework is applied to two real application protocols (Modbus and HTTP) to illustrate the relevance and efficiency of the proposed approach. Various metrics recorded from the experiments show the significant increase of the complexity of the obfuscated protocol binary compared to the non-obfuscated code. It is also shown that the execution time and memory overheads remain acceptable for a practical deployment of the approach in operation.
Spin Orbit Torque Device based Stochastic Multi-bit Synapses for On-chip STDP Learning

As a large number of neurons and synapses are needed in spike neural network (SNN) design, emerging devices have been employed to implement synapses and neurons. In this paper, we present a stochastic multi-bit spin orbit torque (SOT) memory based synapse, where only one SOT device is switched for potentiation and depression using modified Gray code. The modified Gray code based approach needs only N devices to represent 2N levels of synapse weights. Early read termination scheme is also adopted to reduce the power consumption of training process by turning off less associated neurons and its ADCs. For MNIST dataset, with comparable classification accuracy, the proposed SNN architecture using 3-bit synapse achieves 68.7% reduction of ADC overhead compared to the conventional 8-level synapse.
Film Grain Synthesis for AV1 Video Codec

Film grain is abundant in TV and movie content. It is often part of the creative intent and needs to be preserved while encoding. However, the random nature of film grain is difficult to compress using traditional coding tools. This paper describes a film grain modeling and synthesis algorithm proposed for the AV1 video codec. At the encoder, an autoregressive model of film grain is transmitted relative to a denoised signal, and the film grain strength is modeled as a function of intensity. The corresponding renoising at the decoder is implemented using an efficient block-based approach suitable for use in consumer electronic devices. Preliminary results indicate that the approach can give significant bitrate savings (up to 50%) on sequences with heavy film grain.
Designing Efficient Imprecise Adders using Multi-bit Approximate Building Blocks

Energy-efficiency has become a major concern in designing computer systems. One of the most promising solutions to enhance power and energy-efficiency in error tolerant applications is approximate computing that balances accuracy, area, delay, and power consumption based on the computational needs. By trading accuracy of computation, approximate computing may achieve significant improvements in speed, power, and area consumption. Adders are important arithmetic units widely used in almost every digital processing system, which contribute to significant amounts of power dissipation. With the emergence of deep learning tasks and fault tolerant big data processing in every aspect of today's computing, the demand for low-power and energy-efficient approximate adders has increased significantly. Numerous designs have been proposed in the literature that build multi-bit adders using novel approximate full adder circuits. Regrettably, relying on single-bit building blocks only limits the design space of approximate adders and prevents the designers from achieving the most significant benefits of approximate circuits. This paper presents a novel approach to designing imprecise multi-bit adders, based on four novel approximate 2 and 3-bit adder building blocks. The proposed circuits are evaluated and compared with the existing low power adders in terms of various design characteristics, such as area, delay, power, and error tolerance. Our simulation results indicate that the proposed adders achieve more than 60% reduction in power and area consumption compared to the state-of-the-art approximate adders while introducing 12-17% less error in computation.
SDExplorer: A Generic Toolkit for Smoothly Exploring Massive-Scale Sequence Diagram

To understand program's behavior, using reverse-engineered sequence diagram is a valuable technique. In practice, researchers usually record execution traces and generate a sequence diagram according to them. However, the diagram can be too large to read while treating real-world software due to the massiveness of execution traces. Several studies on minimizing/compressing sequence diagrams have been proposed; however, the resulting diagram may be either still large or losing important information. Besides, existing tools are highly customized for a certain research purpose. To address these problems, we present a generic toolkit SDExplorer in this paper, which is a flexible and lightweight tool to effectively explore a massive-scale sequence diagram in a highly scalable manner. Additionally, SDExplorer supports popular features of existing tools (i.e. search, filter, grouping, etc.). We believe it is an easy-to-use and promising tool in future research to evaluate and compare the minimizing/compressing techniques in real maintenance tasks.
Social Innovation and Resilience: exploring the dynamics and impacts on the digital transformation of governance & society

This paper is set out to establish the foundations for developing a framework to assess the potential impact of social policy innovation to contribute to the debate on the future of welfare systems. This calls in fact for monitoring the evolution of social innovations and the implications on the social protection systems that are due to the combined effect of the digital transformation and the emergence of innovative governance paradigms. Building on an extensive systematization of the state of the art and conceptualization work, the paper discusses findings from the review of the literature, linking the relevant theoretical debates on social innovation and resilience with the debate on welfare state reforms. Thus, it presents the interpretative framework proposed, which builds on key dimensions of ICT-enabled innovation and digital governance, discussing the applicability of the framework and outlining policy implications and future research directions.
FinFET External Resistance Analysis by Extended Shift-and-Ratio Method

Extraction and analysis of external resistance (<inline-formula> <tex-math notation="LaTeX">${R}_{\textsf {ext}}$ </tex-math></inline-formula>) have become increasingly important in modern CMOS technology research. We show that with certain assumptions, the well-known shift-and-ratio method can be extended and still be useful for <inline-formula> <tex-math notation="LaTeX">${R}_{\textsf {ext}}$ </tex-math></inline-formula> extraction in short-channel devices. Its application to advanced FinFET devices in both simulation and hardware is presented.
SLoG: Large-Scale Logging Middleware for HPC and Big Data Convergence

Cloud developers traditionally rely on purpose-specific services to provide the storage model they need for an application. In contrast, HPC developers have a much more limited choice, typically restricted to a centralized parallel file system for persistent storage. Unfortunately, these systems often offer low performance when subject to highly concurrent, conflicting I/O patterns. This makes difficult the implementation of inherently concurrent data structures such as distributed shared logs. Yet, this data structure is key to applications such as computational steering, data collection from physical sensor grids, or discrete event generators. In this paper we tackle this issue. We present SLoG, shared log middleware providing a shared log abstraction over a parallel file system, designed to circumvent the aforementioned limitations. We evaluate SLoG's design on up to 100,000 cores of the Theta supercomputer: the results show high append velocity at scale while also providing substantial benefits for other persistent backend storage systems.
Surface Reconstruction Adopting Laser Plane of Linear Path System Registered by Parallel Constraint

A surface reconstruction technology, which is contributed from the parallel constraint between two laser planes, is introduced and achieved by a laser projector guided by a linear path system. The projection geometry is constructed by the projection planes, the target planes, the laser planes, the image planes, and the intersection lines. First, the angle between the direction of the projector translation and the normal vector of the laser plane is contributed by the bilinear product operator of the intersection line and the projection matrix. Second, the distance errors are generated from the points on two laser planes and parameterized by the angle and the laser plane for the optimization. Finally, the surface reconstruction is realized by the optimized angle and laser plane. The experiments are conducted to prove the validity of the surface measurement method. The mean of the reconstruction errors is 0.78 mm in the test, which indicates the application potentials from the experimental investigations.
Transforming Legal Documents for Visualization and Analysis

Regulations, laws, norms, and other documents of legal nature are a relevant part of any governmental organisation. During digitisation and transformation stages towards a digital government model, information and communication technologies are explored to improve internal processes and working practices of government infrastructures. This paper introduces preliminary results on a research line devoted to developing visualisation techniques for enhancing the readability and comprehension of legal texts. The content of documents is conveyed to a well-defined model, which is enriched with semantic information extracted automatically. Then, a set of digital views are created for document exploration from both a structural and semantic point of view. Effective and easier to use digital interfaces can enable and promote citizens engagement in decision-making processes, provide information for the public, and also enhance the study and analysis of legal texts by lawmakers, legal practitioners, and assorted scholars.
Smart Cities Depictions in Wikipedia Articles: Reflections from a Text Analysis Approach

Discussions about smart cities continue to attract much attention from researchers, practitioners and citizens at large. As the literature continues to grow the number of indicators and frameworks for "smartness" are becoming more robust and perspectives on what makes a city smart continue to evolve. This exploratory research analyzes text from 51 Wikipedia articles that describe cities considered "smart" according to three globally recognized and independent rankings of cities. By comparing findings on word frequencies and word associations found in Wikipedia articles with terminology found in academic literature on smart cities, this study intends to determine to what extent data about smart cities produced through Wikipedia's crowdsourcing approach relates to theoretical developments in the field. This inductive approach may open avenues to the application of automated text analysis methods in theorizing and empirical efforts with information produced about smart cities. This exploratory work may facilitate conceptual understanding of the properties and features of smart cities and may also open avenues to future applications of alternative conceptualization methods.
Different Shades—Different Effects? Consequences of Different Types of Destructive Leadership

Destructive leadership comes in many shapes and forms. From reviewing the literature, we conclude that three major forms of destructive leader behaviors are described: (1) follower-directed destructive behaviors, i.e., genuine abusive forms of destructive leadership, (2) organization-directed behaviors, i.e., behaviors such as stealing from the organization or embezzlement, and (3) self-interested destructive leader behavior, i.e., leader who exploit others to reach their goals. One can easily imagine that these three types of leader behavior have very different effects on followers. Unfortunately, so far, there is no empirical evidence to support this, since comparative research in the field of destructive leadership is scarce. With this paper, we aim to address this gap: In two studies, an experimental and a field study, we examine the differential impact of these three different destructive leader behaviors on two important outcomes: first, their impact on different emotional reactions of followers, the most proximal outcome to a social interaction. Second, we examine a key outcome in leadership research: followers' turnover intention. The results suggest that different types of destructive leader behavior do impact followers differently. Whereas all three behaviors had a positive relationship with negative affect, follower-directed destructive behaviors had the strongest relation out of the three. As expected, all three types of destructive behavior relate to turnover intention, yet, the results of our study suggest that different types of destructive leader behavior relate to different urgencies of turnover intention. We conclude that a tailored approach to destructive leadership, whether in research or practice, seems necessary, as diverse types of destructive leader behaviors affect employees differentially.
Novel Method to Measure Common Mode Transient Immunity of Isolators

Common Mode Transient Immunity (CMTI) is one of the most important key parameters of an isolator. CMTI describes the ability of an isolation barrier to withstand fast common mode transients applied between two isolated circuits and thus to maintain the system integrity. To measure the CMTI, very fast voltage changes between the two isolated circuit grounds must be generated. This paper presents a novel method to generate the transients and measure the CMTI. A DC-DC converter is used with a high voltage switch in addition to an appropriate regulation circuit using only passive elements to generate the desired voltage level and slope. The method was implemented on an evaluation board to evaluate a few commercial digital isolators. Measurement results are presented and discussed.
Development and Validation of a Virtual Reality Tutor to Teach Clinically Oriented Surgical Anatomy of the Ear

Virtual reality (VR) is being increasingly used in medical education. However, investigations into its effectiveness in this field have yielded mixed results, indicating that no general conclusions can be drawn in this regard. Therefore, the suitability of a system to teach a given task has to be investigated on a case-by-case basis. In this paper, we focus on teaching clinically oriented surgical ear anatomy, as it is important to provide a well-rounded view of ear anatomy as a foundation for understanding clinical surgery. Although there are some VR systems that teach basic ear anatomy, for example, identification of structures and spatial relationships, to our knowledge, those that deliver a complete clinical understanding of ear anatomy do not yet exist. As such, we discuss the design and development of a 3D interactive VR tutor with integrated haptic capability to teach clinically oriented surgical anatomy of the ear and establish its effectiveness through a user study.
Optimum Gain Selection of Sliding Mode Control using Grey Wolf Optimization Technique

This paper presents a new methodology for the selection of controller gains in sliding mode control. The goal is to create an adaptive gain sliding mode control mechanism that is robust to uncertainty and perturbations without knowing the bounds of the uncertainties (only the boundedness feature is known). In addition, the approach should work with higher-order sliding mode controllers. The proposed method uses Grey Wolf Optimization (GWO), a new evolutionary algorithm that has been proved to outperform existing swarm intelligent optimization algorithms. Optimization characteristics assures that the gain is not overestimated. The effectiveness of the proposed approach is proven in an example using a robotic manipulator.
Blockchain Technology: Is this the Solution to EMR Interoperability and Security Issues in Developing Countries?

The burden of disease is higher by far in developing countries than in the developed world. Developing countries today are turning to technology as the silver bullet or remedy. Indeed, Information and Communication Technology has turned into a key-enabling tool in the enhanced healthcare management. The electronic health records or electronic medical records (EMR) a key component of medical informatics symbolize potential solutions for enhanced healthcare. However, interoperability and security of EMR systems has been the two main challenges of EMR in the healthcare industry. By analyzing existing literature using scoping review research approach this paper explored the potential use of blockchain technology in improving the interoperability and security of EMR systems for the benefit of different stakeholders in health sector in developing countries such as Kenya. To achieve our main objective, five databases were searched and 204 papers screened for inclusion. As a result of the search and screen process, we identified 25 relevant articles.
Domain-Specific Design of Patient Classification in Cancer-Related Cachexia Research

We apply an IDE for user-level process design and composition to a real-life case study: a complex workflow from an ongoing global cancer-related cachexia research project. Originally buried in a manually operated spreadsheet, the process is now fully automated and integrated into the project database, ensuring the immediate availability, consistency and reproducibility of the outcomes. Our integrated solution enables the scientists to immediately execute the processes and easily customize both processes and data model to continuously changing experimental setups. The data modeling is provided by the Dynamic Web Application framework and the process modeling functionalities by the Java Application Building Center, both following the paradigm of eXtreme Model-Driven Design for model-driven software development.
Characterization and Optimization of Inverted-T FinFET Under Nanoscale Dimensions

In this paper, a p-type inverted-T FinFET (IT FinFET) has been optimally structured. Focus is made on analyzing the inferior characteristics reported from the previously fabricated IT FinFETs, and obtaining better performances through a novel structure. IT FinFET has a higher layout efficiency and can thus provide larger drain current (<inline-formula> <tex-math notation="LaTeX">${I}_{D}$ </tex-math></inline-formula>) under the same dimension as that of a silicon-on-insulator (SOI) FinFET by securing the extended channels of ultrathin body (UTB) on the field region. We closely observe the leverages of fin width (<inline-formula> <tex-math notation="LaTeX">${W}_{\textsf {fin}}$ </tex-math></inline-formula>), UTB height (<inline-formula> <tex-math notation="LaTeX">${H}_{\textsf {UTB}}$ </tex-math></inline-formula>), and gate length (<inline-formula> <tex-math notation="LaTeX">${L}_{g}$ </tex-math></inline-formula>) on the operation characteristics using a 3-D technology computer-aided design simulation with quantum-mechanical models. <inline-formula> <tex-math notation="LaTeX">${W}_{\textsf {fin}}$ </tex-math></inline-formula> below 10 nm is evaluated to be suitable for strong gate controllability. We first examine a critical <inline-formula> <tex-math notation="LaTeX">${H}_{\textsf {UTB}}$ </tex-math></inline-formula>, beyond which a higher drive current is not obtained even with a greater channel width than that of FinFET. When <inline-formula> <tex-math notation="LaTeX">${H}_{\textsf {UTB}} = \textsf {3}$ </tex-math></inline-formula> and 10 nm, IT FinFET yields 13.3% and 142% of saturation current improvement compared with SOI FinFET under the same footprint. At extremely scaled <inline-formula> <tex-math notation="LaTeX">${L}_{g}$ </tex-math></inline-formula>, although the immunity against short-channel effects is slightly weaker than that of SOI FinFET, optimally designed IT FinFET can produce a higher current and demonstrates shorter intrinsic delay times.