bluuebunny/crossref_metadata_2025_split huggingface dataset:
Information System Implementation in Healthcare: Case Study of Croatia
Authors: Osvaldić Josipa 
Published: April 2022

Abstract

Background: In today’s environment, health professionals are overwhelmed by the rapid pace of advancement in both information technology and medical practice.

Objectives: This paper aims to point out the importance of developing an electronic health record system that will meet the needs of all stakeholders in healthcare, support health professionals’ work, and enable continuous quality improvement at all levels and in all healthcare segments.

Methods/Approach: Non-systematic literature review has been used to develop a discussion on the healthcare systems’ usage.

Results: Close cooperation of participants at all levels is essential for the quality implementation and application of digital solutions in healthcare.

Conclusions: The paper highlights the factors that contribute to the acceptance of the public healthcare information system in the Republic of Croatia, which is being developed according to the EU regulations.
The Effects of Electronic Surveillance on Job Tension, Task Performance and Organizational Trust
Authors: Doğru Çağlar 
Published: April 2022

Abstract

Background: In contemporary work models, employees use the Internet and electronic devices more than ever. This phenomenon has also changed the way of monitoring employees and generated a new form called ‘electronic surveillance’.

Objectives: The central purpose of this paper is to reveal the effects of electronic surveillance on job tension, task performance, and employees’ organizational trust.

Methods/Approach: Survey research was applied as a quantitative method to collect data. Surveys were generated as Likert-type scales, and they were distributed by hand because the use of the in-person survey technique was employed throughout the study. The research sample was created using the purposive sampling technique, and it included 228 participants from fifteen different branches of one of the biggest private banks in Turkey.

Results: Electronic surveillance in the workplace has turned out to have positive effects on job tension and task performance, whereas it harms organizational trust.

Conclusions: When the degree of electronic surveillance increases, the job tension level of employees tends to increase as well. Additionally, task performance increases when electronic surveillance increases. But this is not the case with organizational trust since electronic surveillance affects it negatively.
The Co-innovation Bingo: An Object-Oriented Networking Mechanism to Foster Coupled Open Business Innovation
Authors: Grèzes Vincent , Bonazzi Riccardo , Grèzes-Bürcher Sandra 
Published: April 2022

Abstract

Background: A firm’s cooperative strategies are a fundamental issue in the search for business growth avenues, but a system that eases the emergence of coupled open innovation appears to be missing.

Objectives: This paper describes a business networking tool to foster coupled open innovation emergence.

Methods/Approach: We adopted a methodology based on design science comparable to grounded theory because solutions emerged by testing a design artefact with companies.

Results: We designed and tested an artefact designed as a game to encourage participants to meet as many partners as possible. It is based on collaborative innovation mechanisms and gets inspiration from fields such as organization design, service design, and prospective design. The proposed artefact comes as prescriptive rules that support managers’ open innovation opportunity elicitation.

Conclusions: From a practical point of view, we contribute by helping companies find emergent open innovation opportunities. From a theoretical point of view, this artefact is part of an emergent theory of object-oriented coupled open innovation mechanisms.
The Intertwined Functions of Advanced Information Systems and Management Control Practice in a Municipal Context
Authors: Bredmar Krister , Melin Ulrika 
Published: April 2022

Abstract

Background: Advanced, integrated information systems such as an enterprise resource planning (ERP) system have nowadays come to play such a crucial role for organizations and functions such as management accounting and control that in many cases, they would not function without the support of these systems. Public sector operations in general and municipal operations, in particular, are complex and require a lot of resources. Because of this, the managers working within this context need the support of advanced information systems to a large extent.

Objectives: This paper aims at understanding how these new systems and their users, accountants, and controllers, perceive the opportunities they bring in a municipal setting.

Methods/Approach: Out of 290 Swedish municipalities, 97 participated in the survey.

Results: The results show that these systems have come to play an important part in working with management accounting and control issues.

Conclusions: One conclusion that could be drawn from this study is that information supported by advanced information systems has become such an important necessity that management accounting as a function or phenomenon would not work without it. Therefore, the interdependency between information systems and management accounting and control practice could be described as intertwined.
Market Structure Development in a Regulated Market: The Case of the EU Rating Agencies
Authors: Meeh-Bunse Gunther , Schomaker Stefan 
Published: April 2022

Abstract

Background: The motivation for this article is the observation of political and private efforts to establish an EU-based rating agency as a counterweight to the three major agencies and observe other approaches to increase competition in the rating market.

Objectives: This article aims to analyse the potential regulatory impact of the oligopo-listic situation on the European Union (EU) rating market in the regulation imposed on the agencies.

Methods/Approach: Selected key figures are applied to observe if and how the dominance has changed. The different rating service range offered by the registered rating agencies in the EU is also considered in the analysis.

Results: The re-search results show that new agencies potentially impact the EU rating market. While the three major rating agencies still dominate the market, they do so within a chang-ing environment.

Conclusions: The employment of external ratings is significant in the financial sector. Ratings provide relevant information on the default risk of financial instruments and assess the solvency of issuers. The market for external ratings thereby can be classified as oligopolistic. Turbulences during the financial crisis of 2008 trig-gered stricter regulation of the credit rating agencies. Such regulation has now been in force for a good decade.
Motivational Factors and Retention of Talented Managers
Authors: Ahmić Azra , Čizmić Elvir 
Published: April 2022

Abstract

Background: In a contemporary fast-changing world, companies are facing growing global competition, volatile markets, altered workforce structure, and another technological reshifting, which generates enormous pressure on them to improve their business performance and imposes the necessity to highlight practices of talent management more seriously.

Objectives: In this study we explore interrelations between attraction/work motivational factors and talent retention, observed through talent engagement.

Methods/Approach: The methodology in this research focuses on the comprehensive resource-based view and encompasses quantitative analysis based on data gathered from talented managers in Bosnia and Herzegovina.

Results: The research results unveiled that talents were attracted to work for current companies primarily because of: good salary and company goodwill. The top three prevalent work motivational factors for talents included: (1) comfortable work environment, (2) enough autonomy and creativity in working and deciding, and (3) work-life balance. Furthermore, talent motivational factors related to talent retention in a statistically significant positive way.

Conclusions: This study furnishes available talent research and theory by relating attraction/work motivational factors to talent engagement; and by introducing the fundamental motivational factors which are of monumental importance for retaining talented managers in Bosnia and Herzegovina.
The Citizen Observatory: Enabling Next Generation Citizen Science
Authors: O’Grady Michael , O’Hare Gregory , Ties Stephanie , Williams Jamie 
Published: April 2022

Abstract

Background: Citizen science offers an attractive paradigm for addressing some of the complex problems facing society. However, translating the paradigm’s potential into meaningful action and sustainable impact remains a formidable challenge. Historically, the citizen science landscape was fractured into silos of activities; nonetheless, it has demonstrably delivered credible results. An innovative concept of the Citizen Observatory offers a tractable means of mitigating many of the recurring issues that historically afflicted citizen science initiatives, thus empowering a new generation of citizen scientists. Citizen Observatories may be regarded as open, standardised software platforms for community-based monitoring of any phenomenon of interest.

Objectives: This paper seeks to validate a Citizen Observatory in a traditional citizen science context, that of butterfly recording.

Methods/Approach: A case study was undertaken in a UNESCO-designated Biosphere Reserve.

Results: A community of citizen scientists successfully recorded various observations concerning butterflies, their feeding behaviours, and their habitat. The resultant dataset was made available to the local government environmental agency.

Conclusions: The Citizen Observatory model offers a realistic basis for enabling more sustainable participatory science activities. Such developments have implications for non-government organisations, businesses, and local governments.
Capital Market Returns and Inflation Nexus in Croatia: Wavelet Coherence Analysis
Authors: Bošnjak Mile , Novak Ivan , Bašić Maja 
Published: April 2022

Abstract

Background: Hedging against inflation assumes instruments such as gold, stocks, fixed income securities, and real estate. There still exists a lack of appropriate strategy to hedge against inflation.

Objectives: This paper examines the possibilities for hedging against inflation in Croatia offered by the Zagreb Stock Exchange indices.

Methods/Approach: Based on monthly data from January 2000 to September 2019 and using a wavelet coherence approach, this paper brings the results across time and frequency domains.

Results: Empirical results suggest that inflation was a leading variable in a statistically significant positive correlation between the inflation rate and Crobex returns in 2007-2011. The relationship between Crobex10, Crobis, and Crobistr returns on one side, and the inflation rate on the other side has statistically significant correlations only in specific and different periods, in which respective returns are a leading variable.

Conclusions: The results imply that hedging against inflation is rather problematic under current Croatian capital markets conditions. Zagreb Stock Exchange indices could serve as a hedge against inflation for some periods but not during the whole observation period.
Innovativeness of Family Businesses in Slovenia: Do Heirs follow the Founders?
Authors: Letonja Marina , Skok Marjana Merkač , Vrdoljak Ivana 
Published: April 2022

Abstract

Background: The innovativeness of founders and their heirs and family businesses (FBs) is a relatively unexplored field of research, and its understanding is incomplete and inconsistent.

Objectives: The goal is to compare the founders’ innovativeness and investigate the relationship of life-long learning with the innovativeness of heirs in FBs.

Methods/Approach: The paper is based on research, including a survey on FBs in Slovenia. The differences in the innovativeness of the two groups – founders and heirs are compared, and the strength of the dependence of the life-long learning and innovativeness through the external training of heirs determined.

Results: The innovativeness of founders and heirs in FBs, measured by the number of new product and service lines and by the number of new processes that founders and heirs in FBs have developed or started marketing in the last five years, shows higher results for the founders. Life-long learning through external training correlates positively with the innovativeness of heirs.

Conclusions: An appropriate culture for innovation needs to be created in FBs to foster innovativeness among heirs, which can be supported by life-long learning.
Hiding Sensitive High Utility and Frequent Itemsets Based on Constrained Intersection Lattice
Authors: Vy Huynh Trieu , Hai Le Quoc , Long Nguyen Thanh , Chau Truong Ngoc , Hieu Le Quoc 
Published: April 2022

Abstract
Hiding high utility and frequent itemset is the method used to preserve sensitive knowledge from being revealed by pattern mining process. Its goal is to remove sensitive high utility and frequent itemsets from a database before sharing it for data mining purposes while minimizing the side effects. The current methods succeed in the hiding goal but they cause high side effects. This paper proposes a novel algorithm, named HSUFIBL, that applies a heuristic for finding victim item based on the constrained intersection lattice theory. This algorithm specifies exactly the condition that allows the application of utility reduction or support reduction method, the victim item, and the victim transaction for the hiding process so that the process needs the fewest data modifications and gives the lowest number of lost non-sensitive itemsets. The experimental results indicate that the HSUFIBL algorithm achieves better performance than previous works in minimizing the side effect.
Deterministic Centroid Localization for Improving Energy Efficiency in Wireless Sensor Networks
Authors: Vijayan Sneha , Munusamy Nagarajan 
Published: April 2022

AbstractWireless sensor networks are an enthralling field of study with numerous applications. A Wireless Sensor Network (WSN) is used to monitor real-time scenarios such as weather, temperature, humidity, and military surveillance. A WSN is composed of several sensor nodes that are responsible for sensing, aggregating, and transmitting data in the system, in which it has been deployed. These sensors are powered by small batteries because they are small. Managing power consumption and extending network life is a common challenge in WSNs. Data transmission is a critical process in a WSN that consumes the majority of the network’s resources. Since the cluster heads in the network are in charge of data transmission, they require more energy. We need to know where these CHs are deployed in order to calculate how much energy they use. The deployment of a WSN can be either static or random. Although most researchers focus on random deployment, this paper applies the proposed Deterministic Centroid algorithm for static deployment. Based on the coverage of the deployment area, this algorithm places the sensors in a predetermined location. The simulation results show how this algorithm generates balanced clusters, improves coverage, and saves energy.
A Proposal for Honeyword Generation via Meerkat Clan Algorithm
Authors: Yasser Yasser A. , Sadiq Ahmed T. , AlHamdani Wasim 
Published: April 2022

Abstract
An effective password cracking detection system is the honeyword system. The Honeyword method attempts to increase the security of hashed passwords by making password cracking easier to detect. Each user in the system has many honeywords in the password database. If the attacker logs in using a honeyword, a quiet alert trigger indicates that the password database has been hacked. Many honeyword generation methods have been proposed, they have a weakness in generating process, do not support all honeyword properties, and have many honeyword issues. This article proposes a novel method to generate honeyword using the meerkat clan intelligence algorithm, a metaheuristic swarm intelligence algorithm. The proposed generation methods will improve the honeyword generating process, enhance the honeyword properties, and solve the issues of previous methods. This work will show some previous generation methods, explain the proposed method, discuss the experimental results and compare the new one with the prior ones.
Enhancеd Analysis Approach to Detect Phishing Attacks During COVID-19 Crisis
Authors: Jafar Mousa Tayseer , Al-Fawa’reh Mohammad , Barhoush Malek , Alshira’H Mohammad H. 
Published: April 2022

Abstract
Public health responses to the COVID-19 pandemic since March 2020 have led to lockdowns and social distancing in most countries around the world, with a shift from the traditional work environment to virtual one. Employees have been encouraged to work from home where possible to slow down the viral infection. The massive increase in the volume of professional activities executed online has posed a new context for cybercrime, with the increase in the number of emails and phishing websites. Phishing attacks have been broadened and extended through years of pandemics COVID-19. This paper presents a novel approach for detecting phishing Uniform Resource Locators (URLs) applying the Gated Recurrent Unit (GRU), a fast and highly accurate phishing classifier system. Comparative analysis of the GRU classification system indicates better accuracy (98.30%) than other classifier systems.
Data Fusion and the Impact of Group Mobility on Load Distribution on MRHOF and OF0
Authors: Al-Qassas Raad S. , Qasaimeh Malik 
Published: April 2022

AbstractMany routing algorithms proposed for IoT are based on modifications on RPL objective functions and trickle algorithms. However, there is a lack of an in-depth study to examine the impact of mobility on routing protocols based on MRHOF and OF0 algorithms. This paper examines the impact of group mobility on these algorithms, also examines their ability in distributing the load and the impact of varying traffic with the aid of simulations using the well-known Cooja simulator. The two algorithms exhibit similar performance for various metrics for low traffic rates and low mobility speed. However, when the traffic rate becomes relatively high, OF0 performance merits appear, in terms of throughput, packet load deviation, power deviation, and CPU power deviation. The mobility with higher speeds helps MRHOF to enhance its throughput and load deviation. The mobility allowed MRHOF to demonstrate better packets load deviation.
Citation and Similarity in Academic Texts: Colombian Engineering Case
Authors: Aguilera-Prado Marco , Salcedo Octavio , Fernández Eduardo Avendaño 
Published: April 2022

Abstract
This article provides the results of a citation determinants model for a set of academic engineering texts from Colombia. The model establishes the determinants of the probability that a text receives at least one citation through the relationship among previous citations, journal characteristics, the author and the text. Through a similarity matrix constructed by Latent Semantic Analysis (LSA), a similarity variable has been constructed to capture the fact that the texts have similar titles, abstracts and keywords to the most cited texts. The results show: i) joint significance of the variables selected to characterize the text; ii) direct relationship of the citation with similarity of keywords, published in an IEEE journal, research article, more than one author; and authored by at least one foreign author; and iii) inverse relationship between the probability of citation with the similarity of abstracts, published in 2016 or 2017, and published in a Colombian journal.
Combination of Resnet and Spatial Pyramid Pooling for Musical Instrument Identification
Authors: Dewi Christine , Chen Rung-Ching 
Published: April 2022

Abstract
Identifying similar objects is one of the most challenging tasks in computer vision image recognition. The following musical instruments will be recognized in this study: French horn, harp, recorder, bassoon, cello, clarinet, erhu, guitar saxophone, trumpet, and violin. Numerous musical instruments are identical in size, form, and sound. Further, our works combine Resnet 50 with Spatial Pyramid Pooling (SPP) to identify musical instruments that are similar to one another. Next, the Resnet 50 and Resnet 50 SPP model evaluation performance includes the Floating-Point Operations (FLOPS), detection time, mAP, and IoU. Our work can increase the detection performance of musical instruments similar to one another. The method we propose, Resnet 50 SPP, shows the highest average accuracy of 84.64% compared to the results of previous studies.
Hy-MOM: Hybrid Recommender System Framework Using Memory-Based and Model-Based Collaborative Filtering Framework
Authors: George Gina , Lal Anisha M. 
Published: April 2022

Abstract
Lack of personalization, rating sparsity, and cold start are commonly seen in e-Learning based recommender systems. The proposed work here suggests a personalized fused recommendation framework for e-Learning. The framework consists of a two-fold approach to generate recommendations. Firstly, it attempts to find the neighbourhood of similar learners based on certain learner characteristics by applying a user-based collaborative filtering approach. Secondly, it generates a matrix of ratings given by the learners. The outcome of the first stage is merged with the second stage to generate recommendations for the learner. Learner characteristics, namely knowledge level, learning style, and learner preference, have been considered to bring in the personalization factor on the recommendations. As the stochastic gradient approach predicts the learner-course rating matrix, it helps overcome the rating sparsity and cold-start issues. The fused model is compared with traditional stand-alone methods and shows performance improvement.
Long Short Term Memory Neural Network-Based Model Construction and Fne-Tuning for Air Quality Parameters Prediction
Authors: Barot Virendra , Kapadia Viral 
Published: April 2022

Abstract
Air pollution has increased worries regarding health and ecosystems. Precise prediction of air quality parameters can assist in the effective action of air pollution control and prevention. In this work, a deep learning framework is proposed to predict parameters such as fine particulate matter and carbon monoxide. Long Short Term Memory (LSTM) neural network-based model that processes sequences in forward and backward direction to consider the influence of timesteps in both directions is employed. For further learning, unidirectional layers’ stacking is implemented. The performance of the model is optimized by fine-tuning hyperparameters, regularization techniques for overfitting resolution, and various merging options for the bidirectional input layer. The proposed model achieves good optimization and performs better than the simple LSTM and a Recurrent Neural Network (RNN) based model. Moreover, an attention-based mechanism is adopted to focus on more significant timesteps for prediction. The self-attention approach improves performance further and works well especially for longer sequences and extended time horizons. Experiments are conducted using real-world data collected, and results are evaluated using the mean square error loss function.