Miracle-dz/UniFAR-FTUs huggingface dataset:
Long Range Planning

In this qualitative study, we explore how incumbent firms in traditional industries build dynamic capabilities for digital transformation. Digital transformation has been defined as the use of new digital technologies, such as mobile, artificial intelligence, cloud, blockchain, and the Internet of things (IoT) technologies, to enable major business improvements to augment customer experience, streamline operations, or create new business models. In making sense of digital transformation, we discovered that leaders in various industry circles use the term inconsistently to describe various strategizing and organizing activities; in addition, the term has gained limited scholarly attention as a context for study of strategic change. Drawing on senior executives' experiences with leading digitalization projects at incumbent firms, we propose a process model comprising of nine microfoundations to reveal the generic contingency factors that trigger, enable, and hinder the building of dynamic capabilities for digital transformation. Our findings reveal that digital transformation is an ongoing process of using new digital technologies in everyday organizational life, which recognizes agility as the core mechanism for the strategic renewal of an organization's (1) business model, (2) collaborative approach, and eventually the (3) culture.
Efficient Distance Sensitivity Oracles for Real-World Graph Data

A distance sensitivity oracle is a data structure answering queries that ask the shortest distance from a node to another in a network expecting node/edge failures. It has been mainly studied in theory literature, but all the existing oracles for a directed graph suffer from prohibitive preprocessing time and space. Motivated by this, we develop two practical distance sensitivity oracles for directed graphs as variants of Transit Node Routing. The first oracle consists of a novel fault-tolerant index structure, which is used to construct a solution path and to detect and localize the impact of network failures, and an efficient query algorithm for it. The second oracle is made by applying the A* heuristics to the first oracle, which exploits lower bound distances to effectively reduce search space. In addition, we propose additional speed-up techniques to make our oracles faster with a slight loss of accuracy. We conduct extensive experiments with real-life datasets, which demonstrate that our oracles greatly outperform all of competitors in most cases. To the best of our knowledge, our oracles are the first distance sensitivity oracles that handle real-world graph data with million-level nodes.
International Journal of Public Health Science (IJPHS)

Received Aug 13, 2021 Revised Aug 22, 2022 Accepted Aug 8, 2022 Globally, pesticides are essential substances that have significant importance in increasing food production and pest management. Although, the serious concern about the health risk of pesticide toxicity should be investigated. The aim of the study is to assess the knowledge and perception of health risks of pesticide usage among farmers. This online-based descriptive cross-sectional study was conducted among farmers in Namakkal district, Tamil Nadu, India. A validated questionnaire was prepared, assessing the sociodemographic and analyzing the level of awareness, perception of pesticide usage among farmers. There were 412 farmers participated, in which 98.5% use pesticides and among them, 72.4% of farmers do not use personal protective equipment (PPE) on pesticide application. Hence, 68% are not aware of the harmful effects of pesticides even though 94.5% experienced health related problems while using them. Therefore, 95.4% of farmers think it is necessary to create awareness about safe handling practices and health risks regarding the usage of pesticides. Our study revealed that farmers do not have adequate knowledge about safe pesticide handling and are not aware of pesticide toxicity levels along with the risk associated with the degree of toxicity which is essential for implementing strategies regarding pesticide safety education and training.
International Journal of Public Health Science (IJPHS)

Mohammad Aminul Islam, Monaemul Islam Sizear, Sharmin Akhtar, Monimul Huq Department of Media Studies and Journalism, Faculty of Social Science, University of Liberal Arts Bangladesh (ULAB), Dhaka, Bangladesh Public Health Foundation of Bangladesh (PHFBD), Dhaka, Bangladesh Department of Psychology and Social Counselling, Faculty of Business, Economic and Social Development, University Malaysia Terengganu, Terengganu, Malaysia Department of Statistics, Faculty of Science, University of Rajshahi, Rajshahi, Bangladesh
Using the Kohonen Algorithm for Quick Initialization of Simple Competitive Learning Algorithm.

In a previous paper ([1], ESANN’97), we compared the Kohonen algorithm (SOM) to Simple Competitive Learning Algorithm (SCL) when the goal is to reconstruct an unknown density. We showed that for that purpose, the SOM algorithm quickly provides an excellent approximation of the initial density, when the frequencies of each class are taken into account to weight the quantifiers of the classes. Another important property of the SOM is the well known topology conservation, which implies that neighbor data are classified into the same class (as usual) or into neighbor classes. In this paper, we study another interesting property of the SOM algorithm, that holds for any fixed number of quantifiers. We show that even we use those approaches only for quantization, the SOM algorithm can be successfully used to accelerate in a very large proportion the speed of convergence of the classical Simple Competitive Learning Algorithm (SCL).
Problems Using Logic Synthesis and onfigurable Hardware

his paper presents new results on an ing satisfiability problems (SAT), i.e. cr uit that is specialized to solve each pro Field Programmable Gate Arrays (FPG ach becomes feasible due to the rece As and high-level logic synthesis. In t h SAT problem is automatically analyz nted on FPGAs. e have developed an algorithm whi implementing on a logic circuit. This ivalent to the Davis-Putnam procedure dynamic variable ordering heuristic. T s not have a large memory structure s sequential accesses to the memory d tleneck in algorithm execution. imulation results show that this metho d random 3-SAT problem with 400 varia utes at a clock rate of 1MHz.
Furion: Engineering High-Quality Immersive Virtual Reality on Today's Mobile Devices

Despite the growing market penetration, today's high-end virtual reality (VR) systems remain tethered, which not only limits users’ VR experience but also creates a safety hazard. In this paper, we perform a systematic design study of the “elephant in the room” facing the VR industry – is it feasible to enable high-quality VR apps on untethered mobile devices such as smartphones? Our quantitative, performance-driven design study makes two contributions. First, we show that the QoE achievable for high-quality VR applications on today's mobile hardware and wireless networks via local rendering or offloading is about 10X away from the acceptable QoE, yet waiting for future mobile hardware or next-generation wireless networks (e.g., 5G) is unlikely to help, because of power limitation and the higher CPU utilization needed for processing packets under higher data rate. Second, we present Furion, a VR framework that enables high-quality, immersive mobile VR on today's mobile devices and wireless networks. Furion exploits a key insight about the VR workload that foreground interactions and background environment have contrasting predictability and rendering workload, and employs a split renderer architecture running on both the phone and the server. Supplemented with video compression, use of panoramic frames, parallel decoding on multiple cores on the phone, and view-based bitrate adaptation we demonstrate Furion can support high-quality VR apps on today's smartphones over WiFi, with under 14 ms latency and 60 FPS (the phone display refresh rate).
Financial Thought Experiment: A GAN-based Approach to Vast Robust Portfolio Selection

Modern day trading practice resembles a thought experiment, where investors imagine various possibilities of future stock market and invest accordingly. Generative adversarial network (GAN) is highly relevant to this trading practice in two ways. First, GAN generates synthetic data by a neural network that is technically indistinguishable from the reality, which guarantees the reasonableness of the experiment. Second, GAN generates multitudes of fake data, which implements half of the experiment. In this paper, we present a new architecture of GAN and adapt it to portfolio risk minimization problem by adding a regression network to GAN (implementing the second half of the experiment). The new architecture is termed GANr. Battling against two distinctive networks: discriminator and regressor, GANr's generator aims to simulate a stock market that is close to the reality while allow for all possible scenarios. The resulting portfolio resembles a robust portfolio with data-driven ambiguity. Our empirical studies show that GANr portfolio is more resilient to bleak financial scenarios than CLSGAN and LASSO portfolios.
ASTROBEE: CURRENT STATUS AND FUTURE USE AS AN INTERNATIONAL RESEARCH PLATFORM

1MEI, NASA Ames Research Center, USA, andres.moravargas@nasa.gov 2USRA, NASA Ames Research Center, USA, ruben.m. garciaruiz@nasa.gov 3Massachusetts Institute of Technology, USA: peterwof@mit.edu, vivekk@mit.edu 4California State University LA, USA, bvanros@calstatela.edu 5Wyle Labs, NASA Ames Research Center, USA, aric.j.katterhagen@nasa.gov 6SGT Inc, NASA Ames Research Center, USA, jonathan.s. barlow@nasa.gov, lorenzo.fluckiger@nasa.gov 7NASA Ames Research Center, USA, jose.v. benavides@nasa.gov, trey.smith@nasa.gov, maria.bualat@nasa.gov
Adaptive Wavelet Transforms via Lifting by

Wavelet transforms have proven very useful for a variety of signal and image processing tasks. The wedgelet transform also shows promise for certain edge-dominated images. However, in many applications we desire to introduce adaptivity and nonlinearities into the transforms. These are powerful extensions, but difficult to control within the wavelet framework. The lifting scheme provides a new, spatial intuition into the wavelet transform that simplifies the introduction of adaptivity. In this thesis, we develop several new adaptive wavelet transforms and adaptive multiresolution wedgelet transforms. The lifting construction permits control over the multiresolution properties of these transforms despite the adaptivity. We demonstrate the power of our new adaptive lifted transforms with successful applications to signal denoising and compression problems. Adaptive Wavelet Transforms via Lifting Roger L. Claypoole, Jr. i J>V^'. /^ CD* <> „ tr-\ \\\^ . X * v V I \ V>'; . _/x 5 ^ ,^» | yt J*. \ "(• s \ ,„_ if Jx\ ' -*■) i \ ■ * \ ■•''i "i 111/'' JC^P Xr,-»k ^C^«»J t _y , -** \. ^^ \ -. _,. % v'SJsA ' —/* \. -t v. ->\> ;^' ^C^ZI» «JSP''' Thesis: DOCTOR OF PHILOSOPHY Electrical and Computer Engineering Rice University, Houston, Texas (October 1999)
Breaking the Design and Security trade-of of Look-up Table-based Obfuscation

Logic locking and Integrated Circuit (IC) camoulaging are the most prevalent protection schemes that can thwart most hardware security threats. However, the state-of-the-art attacks, including Boolean Satisiability (SAT) and approximationbased attacks, question the eicacy of the existing defense schemes. Recent obfuscation schemes have employed reconigurable logic to secure designs against various hardware security threats. However, they have focused on speciic design elements such as SAT hardness. Despite meeting the focused criterion such as security, obfuscation incurs additional overheads, which are not evaluated in the present works. This work provides an extensive analysis of Look-Up-Table (LUT)-based obfuscation by exploring several factors such as LUT technology, size, number of LUTs, and replacement strategy as they have a substantial inluence on Power-Performance-Area (PPA) and Security (PPA/S) of the design. We show that using large LUT makes LUT-based obfuscation resilient to hardware security threats. However, it also results in enormous design overheads beyond practical limits. Tomake the reconigurable logic obfuscation eicient in terms of design overheads, this work proposes a novel LUT architecture where the security provided by the proposed primitive is superior to that of the traditional LUT-based obfuscation. Moreover, we leverage the security-driven design low, which uses of-the-shelf industrial EDA tools to mitigate the design overheads further while being non-disruptive to the current industrial physical design low. We empirically evaluate the security of the LUTs against state-of-the-art obfuscation techniques in terms of design overheads and SAT-attack resiliency. Our indings show that the proposed primitive signiicantly reduces both area and power by a factor of 8× and 2×, respectively, without compromising security.
Experimental Evaluation of Wireless Simulation Assumptions

All analytical and simulation research on ad hoc wireless networks must necessarily model radio propagation using simplifying assumptions. A growing body of research, however, indicates that the behavior of the protocol stack may depend significantly on these underlying assumptions. The standard response to this problem is a call for more realism in designing radio models. But how much realism is enough? This study is the first to approach this question by validating simulator performance (both at the physical and application layers) with the results of real-world data. Referencing an eXtensive set of measurements from a large outdoor routing eXperiment, we start by evaluating the relative realism of common assumptions made in radio model design, identifying those which provide a reasonable approXimation of reality. Although several such investigations have been made for static sensor networks, radio behavior in mobile network deployments is a much less-studied topic. We then reproduce our eXperimental setup in our simulator, and generate the same application-layer metrics under progressively smaller sets of these assumptions. By comparing the simulated outcome to the outcome of our eXperiment, we are able to discern at what point our balance of simplification and realism captures the real behavior of our target environment.
IMS Collections Pushing the Limits of Contemporary Statistics : Contributions in Honor of

In statistical exercises where there are several candidate models, the traditional approach is to select one model using some data driven criterion and use that model for estimation, testing and other purposes, ignoring the variability of the model selection process. We discuss some problems associated with this approach. An alternative scheme is to use a model-averaged estimator, that is, a weighted average of estimators obtained under different models, as an estimator of a parameter. We show that the risk associated with a Bayesian model-averaged estimator is bounded as a function of the sample size, when parameter values are fixed. We establish conditions which ensure that a model-averaged estimator’s distribution can be consistently approximated using the bootstrap. A new, data-adaptive, model averaging scheme is proposed that balances efficiency of estimation without compromising applicability of the bootstrap. This paper illustrates that certain desirable risk and resampling properties of model-averaged estimators are obtainable when parameters are fixed but unknown; this complements several studies on minimaxity and other properties of post-model-selected and model-averaged estimators, where parameters are allowed to vary.
THE BOOTSTRAP OF THE MEAN FOR DEPENDENT HETEROGENEOUS ARRAYS

Presently, conditions ensuring the validity of bootstrap methods for the sample mean of (possibly heterogeneous) near epoch dependent (NED) functions of mixing processes are unknown. Here we establish the validity of the bootstrap in this context, extending the applicability of bootstrap methods to a class of processes broadly relevant for applications in economics and finance. Our results apply to two block bootstrap methods: the moving blocks bootstrap of Künsch (1989, Annals of Statistics 17, 1217–1241) and Liu and Singh (1992, in R. LePage & L. Billiard (eds.), Exploring the Limits of the Bootstrap, 224–248) and the stationary bootstrap of Politis and Romano (1994a, Journal of the American Statistical Association 89, 1303–1313). In particular, the consistency of the bootstrap variance estimator for the sample mean is shown to be robust against heteroskedasticity and dependence of unknown form. The first-order asymptotic validity of the bootstrap approximation to the actual distribution of the sample mean is also established in this heterogeneous NED context.
Retrievals of the Far Infrared Surface Emissivity Over the Greenland Plateau Using the Tropospheric Airborne Fourier Transform Spectrometer (TAFTS)

The Tropospheric Airborne Fourier Transform Spectrometer measured near surface upwelling and downwelling radiances within the far infrared (FIR) over Greenland during two flights in March 2015. Here we exploit observations from one of these flights to provide in situ estimates of FIR surface emissivity, encompassing the range 80–535 cm−1. The flight campaign and instrumental setup are described as well as the retrieval method, including the quality control performed on the observations. The combination of measurement and atmospheric profile uncertainties means that the retrieved surface emissivity has the smallest estimated error over the range 360–535 cm−1 (18.7–27.8 μm), lying between 0.89 and 1 with an associated error that is of the order ±0.06. Between 80 and 360 cm−1, the increasing opacity of the atmosphere, coupled with the uncertainty in the atmospheric state, means that the associated errors are larger and the emissivity values cannot be said to be distinct from 1. These FIR surface emissivity values are, to the best of our knowledge, the first ever from aircraft‐based measurements. We have compared them to a recently developed theoretical database designed to predict the infrared surface emissivity of frozen surfaces. When considering the FIR alone, we are able to match the retrievals within uncertainties. However, when we include contemporaneous retrievals from the mid‐infrared (MIR), no single theoretical representation is able to capture the FIR and MIR behaviors simultaneously. Our results point toward the need for model improvement and further testing, ideally including in situ characterization of the underlying surface conditions.
Fisheries Management of Diplodus Sargus in the East of North Sinai

Five to six scales were removed below the pectoral fin, washed and stored dry in individually labeled container. In the laboratory, scales were washed with sodium hydrochloride (5%) and cleaned with pure water and mounted dry between two glass slides, examined under a microscope (5X) to determine the age. The total scale radius and the distance from the focus to each annulus were measured using an eye piece micrometer.
A High-Level Synthesis Tool for the Assignment of Storage Values to Sequential Read-Write memories

Sequential read-write memories (SRWMs) could be used as an alternative to register files in data-path synthesis. They can be considered RAMs without address decoder. A shift register is used instead to sequentially point at memory locations for read or write. Although SRWMs behave similarly to the memory structures recently proposed by Aloqeely and Chen, they are more interesting because of their lower power consumption. Algorithms are presented to check whether a set of storage value fit in a single SRWM (exactly by means of branch-and-bound) and to automatically map storage values in as few SRWMs as possible (by means of heuristics). As opposed to Aloqeely and Chen, also good benchmark results have been obtained for applications with a low degree of “regularity”.
A study of waste and delivery valve design modification to the pump performance

This paper objective is to share design revolution of waste and delivery valve that contribute to the overall pump performance. In this paper, 3 new designs of waste and delivery valve pump are presented with comprehensive internal flow analysis using computational fluid dynamics (CFD) simulation over 4 cases that have been deeply study for one of the design chosen. 4 cases involving opening and closing both valve or either one. 0.265m height size of customized waste valve with an opening limiter and spring was used to demonstrate cyclic closing and opening valve operation extended up to 0.164m gap. Based on result, this characteristics contribute to 10-20% waste water reduction and enhancement of flow rate height up to 80m. Apart from that this paper also share some of pressure (dynamic, total, static), velocity (x, y, z axis) simulation including the vector flow were under different flow cases.
Concise Definitive Review

of a range of additional potentially associated factors, along with published bibliographies, to find papers suggesting illustration of key points in the structuring and analysis of clinical “big data,” with special focus on outcomes prediction and major clinical concerns in critical care. Study Selection: Three reviewers independently screened preliminary citation lists. Data Extraction: Summary data were tabulated for review. Data Synthesis: To date, most relevant big data research has focused on development of and attempts to validate patient outcome scoring systems and has yet to fully make use of the potential for automation and novel uses of continuous data streams such as those available from clinical care monitoring devices. Conclusions: Realizing the potential for big data to improve critical care patient outcomes will require unprecedented team building across disparate competencies. It will also require clinicians to develop statistical awareness and thinking as yet another critical judgment skill they bring to their patients’ bedsides and to the array of evidence presented to them about their patients over the course of care. ( Crit Care Med 2019; 47:840–848)
Exploring Techniques for Providing Privacy in Location-Based Services Nearest Neighbor Query

Increasing numbers of people are subscribing to locationâ€"based services, and as the popularity grows so do the privacy concerns. Varieties of research exist to address these privacy concerns. Each technique tries to address different models with which locationâ€"based services respond to subscribers. In this work, we present ideas to address privacy concerns for the two main models, the snapshot nearest neighbor query model and the continuous nearest neighbor query model.
Digital Mindsets: Recognizing and Leveraging Individual Beliefs for Digital Transformation

Employees’ beliefs about technological change, their “digital mindsets,” are likely to influence their engagement in, or withdrawal from, their company’s digital transformation initiatives. Employees’ beliefs regarding the malleability of personal ability (fixed/growth mindset) and their beliefs about the availability of situational resources (zero-sum/expandable-sum mindset) influence the extent to which they see new technologies as providing opportunities for professional growth or as encroaching on their ability to display competency. This article examines the implications for managing digital transformation.