Miracle-dz/UniFAR-FTUs huggingface dataset:
Mediating Role of Absorptive Capacity in the Relationship between Institutional Pressure Dimensions and Supplier Relationship Management: An Empirical Evidence Study in Kazakhstan

The purpose of this study is to examine the mediating role of absorptive capacity in the relationship between institutional pressure dimensions and supplier relationship management in Kazakhstan. From the literature, it has been observed that the supplier relationship management and absorptive capacity are essential facets for the decline in institutional pressure and increase in the firm performance. The firms who have strong and better relationships with suppliers will relish better performance. In this study, the author of this paper used a quantitative research method and collected the data from employees working in different manufacturing organizations in Kazakhstan. The researcher collected the data from 272 employees. A cross sectional study was conducted by the researcher of this paper. The results show that supplier relationship management is vital for decreasing institutional pressure. Additionally, the findings reveal that absorptive capability significantly mediates the association between institutional pressure and supplier relationship management. From this study, the manufacturing firms currently working in Kazakhstan will be aware of the importance of the supplier management relationship. This study used a cross sectional approach and the recommendation is that future research should use a longitudinal study.
CHALLENGES FACED BY KENYA NATIONAL POLICE SERVICE IN CONFLICT MANAGEMENT IN GARISSA AND BARINGO COUNTIES, KENYA

Over the years Garissa County in Kenya has experienced increased religious and ethnic conflicts. Research conducted indicate that increased radicalization of the youth and attacks by Al-Shabaab in the county has compounded the conflict situation in Garissa. In Baringo County ethnic conflict has escalated radicalization of the youth resulting to increased conflicts. The Kenya National Police Service has a mandate to maintain law and order hence the focus on conflict management and radicalization in the two counties. The purpose of this study is to access the effectiveness of Kenya National Police Service strategies and mechanisms in managing conflict in Garissa and Baringo counties in the context of radicalization. The study adopts integrated research design composed of descriptive and correlational dispositions. The target population of the study was 697 Village Elders, 415 Chiefs and Assistant Chiefs, 55 County Muslim clergies, 100 Police Reservists, 48 County Police Commanders, 65 Christian clergies, 8 Ant-Terrorist Police Unit Operational Commanders and 6 National Crime Research Center field managers. Purposive and simple random sampling techniques were used to sample the study respondents. Questionnaires, interviews and Focus Group Discussions were used to collect data. Qualitative data was analyzed based on study objectives. The study findings revealed that radicalization in both counties led to violent conflicts influencing the police to use violent approaches. Study findings also inform policy on National Police strategies unique to each county due to the uniqueness of the forms of radicalization. The study also inform policy on government’s provision of adequate personnel and equipment for conflict management in the two counties. Finally, the study adds knowledge on the influence of radicalization on crime management in the two counties.
EPR Hiding in Medical Images with CDCS and Energy Thresholding

— Confidentiality of patient’s data is important in telemedicine applications, which involves transferring of medical images along with the corresponding Electronic Patient’s Report (EPR) data in inter or intra hospital network for diagnosis. Embedding EPR in medical images has advantages like less memory requirement, removal of mapping between images and corresponding EPR data. However, as the size of EPR increases, security and robustness of the embedded information becomes major issue to monitor. This paper proposes high capacity, robust blind data hiding technique in Discrete Cosine Transform (DCT) domain. A new coding technique called Class Dependent Coding Scheme (CDCS) is used to increase the embedding capacity. High imperceptibility is achieved by selecting efficient DCT blocks for embedding. Experimental results show that the proposed scheme exhibits high imperceptibility as well as low perceptual variations in Stego-images. The embedding scheme also takes care of sensitive part of the medical image responsible for accurate diagnosis called Region of Interest (ROI). Security and robustness have been tested against various image manipulation attacks
Distributed acoustic sensing as a tool for exploration and monitoring: a proof-of-concept

Abstract. We use PoroTOMO experimental data to compare the performance of Distributed Acoustic Sensing (DAS) and geophone data in executing standard exploration and monitoring activities. The PoroTOMO experiment consists of two "seismic systems": (a) a 8.6 km long optical fibre cable deployed across the Brady geothermal field and covering an area of 1.5 x 0.5 km with 100 m long segments, and (b) an array of 238 co-located geophones with an average spacing of 60 m. The PoroTOMO experiment recorded continuous seismic data between March 10th and March 25th 2016. During such period, a ML 4.3 regional event occurred in the southwest, about 150 km away from the geothermal field, together with several microseismic local events related to the geothermal activity. The seismic waves generated from such seismic events have been used as input data in this study. For the exploration tasks, we compare the propagation of the ML 4.3 event across the geothermal field in both seismic systems in term of relative time-delay, for a number of configurations and segments. Defined the propagation, we analyse and compare the amplitude and the signal-to-noise ratio (SNR) of the P-wave in the two systems at high resolution. For testing the potential in monitoring local seismicity, we first perform an analysis of the geophone data for locating a microseismic event, based on expert opinion. Then, we a adopt different workflow for the automatic location of the same microseismic event using DAS data. For testing the potential in monitoring distant event, data from the regional earthquake are used for retrieving both the propagation direction and apparent velocity of the wavefield, using a standard plane-wave-fitting approach. Our results indicate that: (1) at a local scale, the seismic P-waves propagation and their characteristics (i.e. SNR and amplitude) along a single cable segment are robustly consistent with recordings from co-located geophones (delay-times δt ∼ 0.3 over 400 m for both seismic systems) ; (2) the interpretation of seismic wave propagation across multiple separated segments is less clear, due to the heavy contamination of scattering sources and local velocity heterogeneities; nonetheless, results from the plane-wave fitting still indicate the possibility for a consistent detection and location of the event; (3) at high-resolution (10 m), large amplitude variations along the fibre cable seem to robustly correlate with near surface geology; (4) automatic monitoring of microseismicity can be performed with DAS recordings with results comparable to manual analysis of geophone recordings (i.e. maximum horizontal error on event location around 70 m for both geophones and DAS data) ; and (5) DAS data pre-conditioning (e.g., temporal sub-sampling and channel-stacking) and dedicated processing techniques are strictly necessary for making any real-time monitoring procedure feasible and trustable.
Public deliverable report

INTRODUCTION: Numerous studies have collected AD cohort datasets. To achieve reproducible, robust results in data-driven approaches, an evaluation of the present data landscape is vital. METHODS: Previous efforts relied exclusively on metadata and literature. Here, we evaluate the data landscape by directly investigating nine patient-level datasets generated in major clinical cohort studies. RESULTS: The investigated cohorts differ in key characteristics, such as demographics and distributions of AD biomarkers. Analyzing the ethnoracial diversity revealed a strong bias towards white/caucasian individuals. We describe the measured data modalities and compare them across cohorts. Finally, the available longitudinal data for important AD biomarkers is evaluated. All results are explorable at https://adata.scai. fraunhofer.de DISCUSSION: Our evaluation exposed critical limitations in the AD data landscape that impede comparative approaches across multiple datasets. Comparing our results to those gained by metadata-based approaches highlights that thorough investigation of real patient-level data is inevitable to assess a data landscape.
Corrosion study of superhydrophobic magnesium alloy AZ31 surfaces prepared by wet chemical etching process

Superhydrophobic surfaces were fabricated on magnesium alloy (AZ31) substrates by chemical etching using H2SO4 and H2O2 solutions, successively. The generated surface layer was characterized using grazing incidence X-ray diffraction, X-ray photoelectron spectroscopy and micro-Raman spectroscopy, and magnesium hydroxide was found to be the chief component. Field emission scanning electron microscopy displayed flower-like microstructure with two types of nanostructures, viz., nanoneedles in dense cluster form and nanosheets in the form of a network. As a result, the etched specimens were very rough and porous. Due to entrapped air in the pores, the droplets were present in Cassie state and so the contact angle measurements demonstrated high static water contact angles (about 154°). The superhydrophobic property was lost after a few minutes immersion in water, due to a transition to the Wenzel state. A decrease in corrosion resistance of the superhydrophobic samples as compared to the polished substrate was also observed through potentiodynamic polarization measurements.
Solidarity and conflict: Prosody as interactional resource in intra- and intercultural communication involving power differences

Prosody has shown to be an important though perhaps underresearched resource interaction participants produce and use to make their face-to-face interaction work. Here we investigate the role of prosody in intraand intercultural communication in situations of institutional differences that are resources for the production of power differences. The corpus was constituted from two large databases: (a) seven years of research in large inner-city school of a major U.S. metropolitan area, where teachers of different cultural backgrounds taught together in different cultural combinations science classes attended by African American students; and (b) an interview study involving two research assistants with 37 research scientists. The data were transcribed using the GAT transcription convention designed for prosodic analysis and analyzed in terms of pitch (F0), speech intensity, and speech rates using the PRAAT software. The use and display of prosodic resources along three major dimensions is reported. (a) Resistance to comply with the standard conversation formats—e.g., during hedging moves—is associated with diverging pitch levels; solidary efforts are associated with special efforts in matching pitch levels, even if these are out of the normal range of the speaker. (b) In situations where new teachers learn to teach in difficult inner-city schools, successful teacher-teacher collaborations are characterized by prosodic expressions that converge over time, which is simultaneously a matching of prosody characteristic of students. (c) Both within and across culture, conflict is both expressed in and accelerated by considerable increases in pitch levels, speech intensities, and speech rates; the resolution of conflict is both expressed in and accelerated by the coordination of pitch levels. These results are discussed in terms of pathos in interaction and the sociology of emotion, conflict, and solidarity.
Deep Reinforcement Learning Applied to a Racing Game

—This is an outline of the approach taken to implement the project for the Artiﬁcial Intelligence course. Autonomous driving has recently become an active area of research, with the advances in robotics and Artiﬁcial Intelligence technology. Therefore, the aim of the project was to apply a Deep Reinforcement Learning technique to a racing game to investigate the performance on autonomous driving tasks. Our goal is to understand if reinforcement learning is a viable algorithm genre for self-driving cars in addition to deep learning through the use of the Outrun simulator as a ﬁrst step. Several algorithms were considered, and we include an extensive survey of the related work; but only one algorithm could be trained due to time and GPU-resource constraints. The Deep Deterministic Policy Gradient algorithm was chosen for the ﬁnal implementation on account of actor-critic algorithms generally outperforming value-based algorithms, both in terms of the time and the resources required for training the algorithm. The game used was the CannonBall OutRun, which is a reimplementation of the classical SEGA Out Run without any timing constraints or the presence of trafﬁc or opposing racers. The algorithm is evaluated based on the improvements in the rewards received during the training period. For our implementation, we used the open source neural networks API, Keras, running TensorFlow in the backend. Quantitative results are provided along with several screenshots of the game during training.
Management Research and Practice

Social entrepreneurship has become fairly popular as an innovative approach to addressing complex social needs although it is often a misunderstood concept. Social entrepreneurship is frequently assumed simply as to be starting and managing a social enterprise, at best considering at least the risks involved in these activities. Indeed, social entrepreneurs can be viewed as a subgroup of genus entrepreneurs. However, the combination of managerial competencies needed for successful social business implementation can significantly differ from the standard model of a prosperous private business. Social entrepreneurship may also require specific personality characteristics in order to thrive. The current article aims to examine the impact of factors on young people aged 15 to 29 in relation to their motivation to develop social entrepreneurship. 477 young people in Slovakia filled in a questionnaire and multinomial logistic regression was used to evaluate the data. The results of the analysis show that the positive relationship of young people to social entrepreneurship is mainly influenced by the level of awareness, the use of social enterprise products and services, their scope, presence of entrepreneurs and people with special needs in the family as well as their status and the region in which they live.
Displaying Fan Identity to Make Friends

This paper examines the functional benefits of being a fan as mediators between identification with the fan interest (i.e., fanship) and display of group membership to others. After a series of principal components analyses and a factor analysis on an initial pool of fandom function items, we arrived at a measure containing three factors representing the benefits of being a fan including (1) the purpose or meaning in life, (2) the escape from everyday life stressors, and (3) establishing and maintaining social connections. The relationship between identification with the fan interest (i.e., fanship) and display of fan identity was mediated by purpose in life and social connections. The results support the notion that fans display fan group membership to engender connections with friends and family.
Hybrid Fuzzy-Genetic Load Balancing Scheme for Cloud Computing

Cloud computing is the recently emerging technology trend in the information technology industry which aims to provide utility-based services over the internet. The prevalent access of cloud technology needs attentions to some of the essential metrics to its accessible resource under service and utilization. Among the parameters load balancing, energy consumption, makespan, quality of service, resource allocation and resource utilization are of the primary concern. Efficient load balancing mechanism can realize customer’s requirement, and enhance resource allocation and utilization and reduce the make span, thereby improving the overall performance of the cloud-computing environment. In this paper, we proposed a hybrid algorithm based on Fuzzy set theory and Genetic algorithm. The proposed scheme aims to realize optimal load balancing by minimizing execution time, decreasing the makespan, and maximizing resource utilization. The proposed load balancing approach employs in cloud-based environment an enhanced execution time, load imbalance factor, better resource utilization and minimum makespan for improving the performance of the system by making efficient allocation of computational resources based on their capacity to perform the tasks. Simulation results proved that the resourceutilizationratio is 0.6 and the value resides in the high utilization range.
INNOVATIVE OPTOMECHATRONIC TECHNOLOGIES IN THE TOBACCO INDUSTRY

The manufacturing of production machinery for the tobacco industry is an area in which particularly intensive research and development works are carried out aimed at increasing the quality of products in accordance to the zero-fault policy, while ensuring high production efficiency. Achieving the highest process parameters is possible thanks to innovative optomechatronic technologies. The review of selected key achievements in the field of optomechatronic technologies and our own achievements presented in the article include methods and inspection systems used for quality inspection in the tobacco industry, as well as other industries where similar or analogous problems of detecting and identifying product defects occur. As examples of the authors’ research and implementation achievements presented are advanced optomechatronic systems for the inspection of tobacco semi-finished products. Cognitive problems and technical barriers as well as methods of solving them are presented. The developed systems meet the highest requirements in terms of accuracy and speed of measurements. Their qualities were confirmed during tests in industrial conditions. The summary presents the main trends in the implementation of innovative optomechatronic technologies for the inspection of products in mass production in the tobacco industry and other areas of the economy, as well as the directions of further research and development carried out by the authors. Innowacyjne technologie optomechatroniczne w przemyśle tytoniowym Słowa kluczowe: przemysł tytoniowy, kontrola jakości, technologie optomechatroniczne. Streszczenie: Branża maszyn produkcyjnych dla przemysłu tytoniowego jest obszarem, w którym prowadzone są szczególnie intensywne prace badawcze i rozwojowe ukierunkowane na podwyższanie jakości wyrobów zgodnie z zasadą „zero braków” przy jednoczesnym zapewnieniu wysokich wydajności produkcji. Osiągnięcie najwyższych parametrów procesu umożliwiają innowacyjne technologie optomechatroniczne. Przedstawiony w artykule przegląd wybranych najważniejszych osiągnięć w obszarze technologii optomechatronicznych oraz własnych dokonań w tym zakresie obejmuje metody i systemy inspekcji zastosowane do kontroli jakości w branży tytoniowej, a także innych branżach, gdzie występują analogiczne lub zbliżone zagadnienia wykrywania i identyfikacji wad produktów. Jako przykłady autorskich osiągnięć badawczych i wdrożeniowych przedstawiono zaawansowane systemy inspekcji optomechatronicznej półproduktów tytoniowych. Zaprezentowano występujące problemy poznawcze i bariery techniczne oraz metody ich rozwiązywania. Opracowane systemy spełniają najwyższe wymagania w zakresie dokładności i szybkości pomiarów. Ich walory zostały potwierdzone w trakcie testów w warunkach przemysłowych. W podsumowaniu przedstawiono główne trendy we wdrażaniu innowacyjnych technologii optomechatronicznych na potrzeby inspekcji wyrobów w produkcji masowej w branży tytoniowej oraz innych obszarach gospodarki, a także kierunki dalszych prac badawczo-rozwojowych prowadzonych przez autorów. 24 Journal of Machine Construction and Maintenance | 3/2018
FutureID – Shaping the Future of Electronic Identity

The FutureID project builds a comprehensive, flexible, privacy-aware and ubiquitously usable identity management infrastructure for Europe, which integrates existing eID technology and trust infrastructures, emerging federated identity management services and modern credential technologies to provide a user-centric system for the trustworthy and accountable management of identity claims. The FutureID infrastructure will provide great benefits to all stakeholders involved in the eID value chain. Users will benefit from the availability of a ubiquitously usable open source eID client that is capable of running on arbitrary desktop PCs, tablets and modern smart phones. FutureID will allow application and service providers to easily integrate their existing services with the FutureID infrastructure, providing them with the benefits from the strong security offered by eIDs without requiring them to make substantial investments. This will enable service providers to offer this technology to users as an alternative to username/password based systems, providing them with a choice for a more trustworthy, usable and innovative technology. For existing and emerging trust service providers and card issuers, FutureID will provide an integrating framework, which eases using their authentication and signature related products across Europe and beyond. To demonstrate the applicability of the developed technologies and the feasibility of the overall approach FutureID will develop two pilot applications and is open for additional application services who want to use the innovative FutureID technology. This paper provides a short overview of the FutureID project.
Enhanced C2 and C3 Product Selectivity in Electrochemical CO2 Reduction on Carbon-Doped Copper Oxide Catalysts Prepared by Deep Eutectic Solvent Calcination

Copper and its oxides are the main catalyst materials able to promote the formation of hydrocarbons from the electrocatalytic CO2 conversion. Herein, we describe a novel preparation method for carbon-doped copper oxide catalysts based on an oxidative thermal treatment of copper-containing deep eutectic solvents (DES). XRD and EDX analysis of the samples show that thermal treatment at 500 °C in air for a prolonged time (60 min) provides exclusively carbon-doped copper(II) oxide catalysts, whereas shorter calcination time leads to a mixture of less oxidized forms of copper (Cu2O and Cu0), CuO, and a higher carbon content from the DES. Chronoamperometry of the electrode containing the prepared materials in 0.5 M KHCO3 electrolyte show the reduction of CuO to less oxidized copper species. The materials prepared by the use of different DES, copper precursors and calcination times were used as electrocatalysts for the electrochemical CO2 reduction. Chemical analysis of the products reveals an enhanced selectivity toward C2 and C3 products for the catalyst prepared from the DES galactose-urea with copper nanoparticles and calcination for 60 min in air. The electrocatalytic activity of the prepared materials were compared to commercial CuO and showed a higher product concentration at −1.7 V vs. Ag/AgCl, with formation rates of 7.4, 6.0, and 10.4 µmol h−1 cm−2 for ethanol, n-propanol, and ethylene, respectively.