Miracle-dz/UniFAR-FTUs huggingface dataset:
Do CSR Activities Increase Firm Value? Evidence from the Korean Market

Corporate social responsibility has recently become a new metric of corporate performance. Some argue that corporate social responsibility should be used not only for corporate image improvement, but also as a major competitive strategy. Given this perspective, this study considers the effect of corporate social responsibility on firm value using data from all firms listed on the Korea Exchange from 2005 to 2015 that provide corporate social responsibility information. Specifically, we use the Korea Economic Justice Institution Index, which is an important metric for corporate social responsibility in Korea, to empirically analyze the relation between corporate social responsibility and firm value. Further, given the growing attention to the Korean manufacturing environment and the significant influence of the global manufacturing environment, we aim to determine the differential characteristics of manufacturing corporations using the relation between corporate social responsibility and firm value. The results strongly support a positive relation between corporate social responsibility and firm value. Furthermore, our detailed analysis of the manufacturing industry indicates some differential characteristics with respect to this relation. Overall, we find that every corporation should adopt corporate social responsibility as an active competitive strategy, taking the corporate condition into account.
Feasibility Analysis of Open-government Data for the Automated Calculation of the Micro-climatic Attributes of Urban Units of Observation in the City of Vienna

A quantified analysis of the urban climate in general and the urban heat island phenomena in particular is a complex endeavor and requires a variety of data streams. Urban units of observations are meant to specify well-defined spatial domains within a city toward the representation and study of the microclimatic conditions (e.g., via simulation applications). The European Union generally mandates the implementation of open data interfaces. Administrative data is made publicly accessible to increase transparency and to support participation and collaboration. The present contribution analyses the feasibility of open government data for the automated calculation of the microclimatic attributes of urban units of observation in the city of Vienna. The proposed algorithms and framework are briefly introduced to explain which data sources are needed and how the data is classified. Suitable data sources include georeferenced, twoand threedimensional vector, raster as well as semantic data. A sample application scenario presents the results of aspect ratio calculation using the example of the inner city of Vienna. Ratio
Analysis of Bank Customer Service Strategies in The Pandemic Time of Covid-19

This study aims to identify customer service strategies on the value of expectations and service satisfaction that customers receive. The research method used is quantitative, the research sample used is a simple random sampling method, with a size of 100 customers at Bank BRI KCP Taman Palem, West Jakarta. Indonesian. The collected data were analyzed using a Cartesian diagram. The results of the study were able to identify services and the level of customer satisfaction on the quality of company services from the five service measurement tools, the results were distributed into four quadrants, namely: the reliability dimension was in Quadrant I, the responsiveness dimension was in Quadrant II, the assurance dimension was in Quadrant III and empathy, and tangibility is in Quadrant IV. Based on these results, it is recommended that BRI Bank performs refinement and improvement of several current customer service strategies so that the five dimensions of customer service are at coordinate points in quadrant I.
Droplet evaporation in the context of interstage injection

Wet compression is a widely used approach to maximize the power rate of stationary gas turbines. This technique is practically realized by liquid water injection into the air main flow. Water is injected via a nozzle rack at the air inlet duct of the compressor. Only minor parts of the injected water evaporate on their way to the compressor inlet. Therefore, a multi-phase flow of humid air and water droplets enters a compressor operating in wet compression mode. Water injection between compressor stages is called interstage injection. This technique is challenging and rarely investigated yet. In this paper, a parametric study of the evaporation process with regard to the conditions of interstage injection is presented. Evaporation performance is calculated using the droplet vaporization model of Abramzon. The compression process is calculated using an axial compressor model. Physical limits referring to evaporation process and internal compressor cooling are discussed. A thermodynamic analysis of interstage injection is presented with focus on the amount of water required for optimized cooling.
An Empirical Study of Synchrophasor Communication Delay in a Utility TCP/IP Network

Abstract Although there is a plethora of literature dealing with Phasor Measurement Unit (PMU) communication delay, there has not been any effort made to generalize empirical delay results by identifying the distribution with the best fit. The existing studies typically assume a distribution or simply build on analogies to communication network routing delay. Specifically, this study provides insight into the characterization of the communication delay of both unprocessed PMU data and synchrophasors sorted by a Phasor Data Concentrator (PDC). The results suggest that a bi-modal distribution containing two normal distributions offers the best fit of the delay of the unprocessed data, whereas the delay profile of the sorted synchrophasors resembles a normal distribution based on these results, the possibility of evaluating the reliability of a synchrophasor application with respect to a particular choice of PDC timeout is discussed.
Stratigraphic and structural styles of half-graben offshore basins in Southern Italy: multichannel seismic and Multibeam morpho-bathymetric evidences on the Salerno Valley (Southern Campania continental margin, Italy)

New results on the seismic stratigraphy and morpho-bathymetry of the Pleistocene sedimentary basin of the Salerno Valley focused on the regional seismic stratigraphy of the Southern Campania passive continental margin (Southern Tyrrhenian sea, Italy) are presented here.Original data include Multibeam bathymetry as well as multichannel and single-channel seismic profiles, recently collected onboard the R/V Urania of the National Research Council of Italy (oceanographic cruise SISTERII). The Salerno Valley represents a half-graben sedimentary basin, whose identification has been controlled, during the Early Pleistocene, by the master fault Capri-Sorrento Peninsula, showing vertical throws of 1500 metres, which downthrows theMeso-Cenozoic carbonatic acoustic basement under the sedimentary basin.The geologic interpretation of multichannel seismic profiles has enabled the identification of amain unconformity, located at depths ranging from 3000 to 3500 metres under the sea bottom and correlated to the top of the Meso-Cenozoic carbonatic sequence,extensively cropping out onshore in the Sorrento Peninsula structural high. This unconformity bounds upwards the carbonatic acoustic basement, strongly deformed by normal faulting, and represents the base of the Pleistocene basin filling, the Salerno Valley. The basin filling, with an overall thickness exceeding 1000metres, is characterised by parallel and continuous seismic reflectors alternating with chaotic intervals, having acoustically-transparent seismic facies. The strong synsedimentary tectonics lasting up to Late Pleistocene times in correspondence to NNW-SSE trending listric normal faults triggered gravity mass instability processes, evident as chaotic acoustic intervals intercalated at various stratigraphic levels in the stratigraphic record shown by the multichannel seismic profiles.
Mindfulness predicts less depression, anxiety, and social impairment in emergency care personnel: A longitudinal study

Medical personnel working in emergency rooms (ER) are at increased risk of mental health problems and suicidality. There is increasing evidence that mindfulness-based interventions can improve burnout and other mental health outcomes in health care providers. In contrast, few longitudinal prospective studies have examined protective functions of dispositional mindfulness in this population. The objective of this study was to examine whether mindfulness prospectively predicts anxiety, depression, and social impairment in a sample of emergency care professionals. The authors administered online surveys to ER personnel prior to work in ER, and at 3 and 6 months follow up. Participants were 190 ER personnel (73% residents, 16% medical students, 11% nurses). Linear mixed effects regression was used to model longitudinal 3-month and 6-month follow up of depression, anxiety, and social impairment. Predictors included time-varying contemporaneous work stressors, perceived social support at work and life events, and baseline dispositional mindfulness, demographics, and workplace characteristics. Mindfulness indexed when starting ER work predicted less depression, anxiety, and social impairment 6 months later. Mindfulness remained a strong predictor of mental health outcomes after controlling for time-varying stressful events in emergency care, negative life events, and social support at work. Mindfulness moderated the adverse impact of poor social support at work on depression. To our knowledge, this is the first longitudinal study to show that mindfulness prospectively and robustly predicts anxiety, depression, and social impairment. Results support the role of mindfulness as a potential resilience factor in at-risk health care providers.
The Impact of Per-Capita Transfer Payment on the Stabilization of Local Fiscal Expenditure

The transfer payment should exert the economic and social stability effect. However, the empirical data show that the total amount of transfer payment varies greatly in different regions and deviates from the goal of the transfer payment system to a certain degree. If per-capita transfer payment is adopted as the analysis variable, from 1998 to 2015, 31 provincial government financial data were used to empirically test the impact of per-capita transfer payment on the stability of provincial fiscal expenditures. Based on the analysis of the influence of fiscal self-sufficiency and the 5 types of fiscal expenditures closely related to economic and livelihood stability, we can find that the per-capita transfer payment has a significant negative correlation with the stable effect of fiscal expenditure, while the effect of fiscal self-sufficiency on the provincial financial expenditure has no significant effect. Science and Technology Expenditure, Medical Expenditure on the stability of local fiscal expenditure has a more significant negative effect. The influence of Educational Expenses on the stabilizing effect of local fiscal expenditure is not significant. Social Security Expenditure has the same effect as Cultural Expenditure, and has a significant positive impact on the stability of local fiscal expenditure. In order to further enhance the stabilizing effect of transfer payment on local fiscal expenditure, we should improve the current transfer payment system and improve the fiscal expenditure structure of local governments.
Online Assessment: How Effectively Do They Measure Student Learning at the Tertiary Level?

Higher education institutions (HEIs) are increasingly adopting online learning procedures to facilitate and hopefully, enhance learning outcomes. However, concerns are arising regarding the reliability of this platform in measuring students learning outcomes. Unfortunately, these concerns are mainly linked with technological and administrative failures that are likely to occur before or during the assessment process, and not with the actual attainment of the learning objectives. Using literature review as the research method, this paper provides some perspectives on the effectiveness of online assessment in measuring student learning at the tertiary level. Examples from the authors’ own teaching experience are also provided to support the premise of the discussion. The research findings indicate that while both formative and summative online assessments are useful in measuring student learning at the tertiary level, there is no consensus on whether online platforms can be used effectively in both types of evaluation, with studies associating these platforms with various strengths and weaknesses. This study concludes that HEIs, having little choice at the current time, should take advantage of online platforms strengths in measuring certain types of student learning while at the same time, ponder on the questions raised in this study on the need to institute remedial procedures to mitigate these platforms limitations in measuring other types of learning that are difficult to capture using online assessment.
Change Impact Analysis as required by safety standards, what to do?

Authors: Thor Myklebust, Tor Stålhane, Geir Kjetil Hanssen and Børge Haugset a SINTEF ICT, b IDI NTNU _____________________________________________________________________________________ Abstract: Change Impact Analysis related to safety of products and systems is used by companies in many industries and is required by several standards. The International Electrotechnical Commission (IEC) has issued several standards with requirements and guidelines for the establishment of analysis like FMECA (IEC 60812), FTA (IEC 61025), Design review (IEC 61160), HAZOP (IEC 61882), Markov (IEC 61165) and RBD (IEC 61078) but no standard for Change Impact Analysis. Based on the aforementioned standards, a literature study and experience from several projects, this paper proposes a Change Impact Analysis Report adapted to the specific characteristics of the Railway and Process industry domains. The purpose of this paper is to serve as a tool to aid manufacturers in performing a Change Impact Analysis at the appropriate level which will be approved by assessors and certification bodies. This is important since the Change Impact Analysis report is one of the main inputs to the assessor/certification body. The paper starts by presenting and clarifying relevant terms and definitions, as these differ from standard to standard. The main part of the paper structures and describes the relevant topics for a Change Impact analysis report. Using the described approach will save time and cost and reduce the risk of having to re-issue the Change Impact analysis, thus ending up with a product having hidden defects. Using the mindset from SafeScrum a method that introduces elements from agile into safety-related software development, will result in further savings. This work is part of a series of Railway and IEC 61508 certification projects and the SUSS Research projects.
Parametric Studies of Melt Electrospinning Poly ε (caprolactone) Fibers for Tissue Engineering Applications

The process of electrospinning has received remarkable amount of attention as this technique can be used to fabricate suitable scaffolds for cells. In order to control morphology of scaffold, parametric studies are necessary in customized melt electrospinning. In this study, we demonstrate that fiber di- ameter could be controlled by customized nozzle and param- eters which are temperature, voltage, and distance influence to fiber diameter. Moreover, we culture and seed murine CE3 stem cells derived from D3 embryonic stem cell line on fab- ricated scaffolds. Overall, scaffold controlled by parameter studies holds a promising strategy for superb cell attachment and proliferation.
Three-Phase Three-Level Flying Capacitor PV Generation System with an Embedded Ripple Correlation Control MPPT Algorithm

This paper presents the implementation of a maximum power point tracking (MPPT) algorithm in a multilevel three-phase photovoltaic (PV) system using the ripple correlation control (RCC) method. Basically, RCC adopts the inherent oscillations of PV current and voltage as perturbation, and it has been predominantly used for single-phase configurations, where the oscillations correspond to the 2nd order harmonics. The implementation of an RCC-MPPT algorithm in a three-phase system has not been presented yet in the literature. In this paper, the considered three-phase three-level converter is a three-level flying capacitor (FC) inverter. The proffered RCC method uses the 3rd harmonic components of PV current and voltage for the estimation of the voltage derivative of the power dPpv/dVpv (or current, dIpv/dVpv), compelling the PV array to operate at or very close to the maximum power point. The analysis and calculation of the low-frequency PV current and voltage ripple harmonic components in the three-phase flying capacitor inverter is presented first, with reference to centered carrier-based three-level PWM. The whole grid-connected PV generation scheme has been implemented by MATLAB/Simulink, and detailed numerical simulations verified the effectiveness of the control method in both steady-state and dynamic conditions, emulating different sun irradiance transients.
Robust RFID Localization in Multipath With Phase-Based Particle Filtering and a Mobile Robot

This work revisits particle filtering RFID localization methods, solely based on phase measurements. The reader is installed on a low-cost robotic platform, which performs autonomously (and independently from the RFID reader) open source simultaneous localization and mapping (SLAM). In contrast to prior art, the proposed methods introduce a weight metric for each particle-measurement pair, based on geometry arguments, robust to phase measurement noise (e.g., due to multipath). In addition, the methods include the unknown constant phase offset as a parameter to be estimated. No reference tags are employed, no assumption on the tags’ topology is assumed and special attention is paid for reduced execution time. It is found that the proposed phase-based localization methods offer robust performance in the presence of multipath, even when the tag phase measurements are variable in number and sporadic. The methods can easily accommodate a variable number of reader antennas. Mean absolute 3D localization error in the order of 24 cm for RFID tags in a library was shown, even though the system did not exploit excessive bandwidth or any reference tags. As a collateral dividend, the proposed methods also offer a concrete way to classify the environment as multipath-rich or not.
Cognitive computing with non-volatile memory devices

The extreme flexibility of digital circuits has allowed modern processors based on the Von Neumann architecture to not only efficiently implement algorithms for a wide variety of problems, but to consistently improve system performance at an exponential rate. However, with continued aggressive device scaling constrained by powerand voltage-considerations, the time and energy spent transporting data between memory and processor (across the so-called “Von-Neumann bottleneck”) has become problematic for data-centric applications such as real-time image recognition and natural language processing. One example of Non-Von Neumann (Non-VN) computing is the human brain. Characterized by its massively parallel architecture and adaptive elements (e.g. its synapses), the brain can outperform modern processors on many tasks involving unstructured data classification and pattern recognition. Artificial Neural Networks (ANNs), first conceived in the mid-1940s to mimic what was then known about neural systems, perform computations in a naturally parallel fashion. Modern Graphical Processing Units (GPUs) have greatly increased both the size of the networks and the datasets that can be trained in reasonable time. In turn, this has commensurately improved classification performance to the point that these systems are now becoming commercially pervasive. In contrast to powe-hungry GPUs, IBM’s TrueNorth chip is a flexible and modular non-VN tool for implementing forward inference of large ANNs at ultra-low power. Synaptic weights are typically trained off-line and transferred onto digital SRAM arrays to perform forward propagation of large and complex ANNs. One path for extending such Non-VN systems towards full on-chip learning – and thus to provide accelerated ANN training at lower power than GPUs – is to move from reliable but binary SRAM devices to dense and analog (but less reliable) Non-Volatile Memory (NVM). Such research has been explored here at IBM Research-Almaden for the past several years, including a mixed hardware-software demonstration of a three-layer feedforward fully-connected ANN with 165000 synapses. However, these experiments have been built around unidirectional phase-change memory (PCM). Because PCM only offers incremental conductance change in one direction, ANN training must be paused periodically and every single conductance measured and adjusted, which is inherently inefficient. In my internship work, I used our customized ANN simulator to study the potential of bidirectional ReRAM devices based on PrxCa1-xMnO3 (“PCMO”) materials for such on-chip learning applications. Real device data from our collaborators in Korea is used to obtain highlyrepresentative simulations of expected ANN performance. I obtained high classification accuracy for several different weight-update schemes and synaptic architectures. Several improvements over our previously published implementations will be discussed.
The expiration day effect of indexoptions and index futures on the underlying shares

This paper studies the effect of the expiration day of index options and futures on the trading volume, variance and price of the underlying shares. The data consists of all trades for the underlying shares in the FOX-index for expiration days during the period October 1995 to the mid of yer 1999. The main results seem to support the findings of Kan 2001, i.e. no manipulation on a larger scale. However, some indication of manipulation could be found if certain characteristics are favorable. These characteristics include: a) a large quantity of outstanding futures or at/in the money options contracts, b) there exists shares with high index weight but fairly low trading volume. Lastly, there is some indication that manipulation might be more popular towards the end of the examined time period. JEL Classification: G14, G24