bluuebunny/crossref_metadata_2025 huggingface dataset:
Speedy Management of Data Using MapReduce Approach
Authors: N. Ambika
Published: January 2023

The previous contribution utilizes two assignments in practical programming: Map and Reduce. MapReduce is another preparing structure. Hadoop is its open-source execution on a solitary processing hub or groups. Contrasted and existing preparing ideal models, MapReduce and Hadoop enjoy two benefits. The deficiency lenient capacity brings about dependable information handling by reproducing the registering errands and cloning the information lumps on various figuring hubs across the processing bunch. The high-throughput knowledge preparation employs a cluster handling structure and the Hadoop disseminated document framework. Information is put away in the HDFS and made accessible to the slave hubs for calculation. The suggested work uses hashing methodology to increase speed in searching the required data. The suggestion reduces the mapping using hashing method based on attributes by 29.6% compared to previous work.
Internet Search Behavior in Times of COVID-19 Lockdown and Opening
Authors: Kurpicz-Briki Mascha , Glauser Christoph , Schmid Loris
Published: January 2023

In this work, the authors study the search behavior and search volume on the internet of the Swiss population during the COVID-19 lockdown and in particular during the application of the step-wise exit plan of the Swiss Government after the first wave in 2020. The investigation concentrates on the general topics of interest, the sentimental state reflected in online searches and keywords related to active search patterns about the steps of the exit plan. The authors investigate how the interest in COVID-19 evolves over time, and how specific social and community topics are searched differently during lockdown and during the step-wise opening phase. Whereas the results were partially as the authors expected, others were surprising. They also found indication for cultural differences in online search behavior. The work shows how digital tools can be used to feel the sentiment of an entire population, especially interesting in crisis times such as a global pandemic.
Artificial Intelligence, Consumers, and the Experience Economy
Authors: Chang Hannah H. , Mukherjee Anirban
Published: January 2023

A fundamental challenge for businesses catering to the modern experience economy is to understand what consumers want in experiential products and services. The article discusses the nascent knowledge base on artificial intelligence (AI) and consumers in the context of experiential products and the emerging experience economy, which are key applications for marketing practice. Furthermore, it draws upon the formal academic literature and leading practitioner press to synthesize empirical evidence, with suggestions and recommendations for marketing practitioners and policymakers tasked with driving the deployment and success of AI in the experience economy.
Tracking Buying Behavior by Analyzing Electronic Word of Mouth
Authors: Khondkar Mubina
Published: January 2023

Word of mouth (WOM) communication has become popular as consumers have been sharing their experiences and opinions regarding products, services, brands, and related companies at increased frequency and volume than ever before, fostered by innovative social media and interactive web. It profoundly influences consumer buying behavior. With the advancement of digital technologies, methods, techniques, art, style, speed, and approaches to communication have changed considerably. Sophisticated digital technologies empowered consumers to become more creative to customize, team up, and disseminate information through the internet. This information work as electronic word of mouth (eWOM), in the forms of online reviews, tweets, blog posts, likes, pins, images, and video testimonials. eWOM provides consumers with convenient opportunities to share their feelings and opinions which has a profound power to influence consumers' buying decisions. This research presents the impacts of eWOM on the buying behavior of consumers in Bangladesh.
Artificial Intelligence-Based Behavioral Biometrics
Authors: Gupta Muskan , Tripathy B. K.
Published: January 2023

Recognition of reliability of people entering into a system has been a vital downside in numerous business concerns. Biometrics, which provides recognition of personnel using their distinctive traits, has the potential to become an authentic approach and hence are irreplaceable as a part of several identification systems. Uni-modal biometric systems have been designed to validate user identity. These systems use single biometric traits that can be used for recognition. But most of the drawbacks in uni-modal biometric system are due to the use of single attribute of biometric. As a solution to this problem, multimodal biometric identification systems have been developed recently, which are useful for authentication of the users. These systems avoid security threats better and provide higher security to the systems. In this article, the authors present these aspects of behavioral biometrics based on artificial intelligence and provide a comparative study of the existing approaches and systems. Also, some suggestions for future enhancements are presented for better security of the systems.
Machine Learning and Emotions
Authors: Fisogni Primavera
Published: January 2023

Emotions play a primary role in shaping human intelligence. On the other side, for machines, it is impossible to have forms of knowledge that are not programmed, managed, or piloted by humans. Furthermore, for humans, the process of learning is deeply interwoven with the emotional ground of the living condition. And for machines? We could not improve the attitude of learning in digital devices without enhancing their capacity of sensing. There is a wide consensus among scholars that smart devices can learn emotions at different degrees; however, the rising of the emotional wave in digital devices has not yet been explored. Philosophy can feel the gap by investigating whether machines sense and how. The aim of this article is to indicate a zero degree of emotional power in smart devices: this ability does not exist per se but in the interaction with humans. The Onlife world, where the real and the digital are melted together, provides machines with an environment that makes possible the existence of an enlarged sensitivity. Thus, machines also sense in a specific mode.
Sentiment Analysis Using LSTM
Authors: Mukherjee Anweshan , Saha Rajarshi , Gupta Ashwin , Datta Debabrata , Acharya Anal
Published: January 2023

Sentiment analysis is a vast growing field as various branches of artificial intelligence are being used in different fields. Incorporating sentiment analysis in the field of psychology would be of great help to both doctors for easy diagnosis and patients for self-checking. The research work proposed in this article focuses on obtaining the dependency of one word with others in its current context using long short-term memory (LSTM) for obtaining the sentiment. The dataset used consists of 156060 movie reviews and a model was trained to classify the cleaned text data into three classes – Negative, Neutral, and Positive. The performance of the model was evaluated by checking the loss generated and the validation accuracy after each epoch. The model and its hyper parameters were also tuned to obtain the best model in terms of validation accuracy.
Data Science in the Database
Authors: Badia Antonio
Published: January 2023

An important part of the data lifecycle is preparing the data for analysis. This includes exploratory data analysis to find problems, data cleaning to solve problems related to 'dirty' data, and data transformation to achieve the format required by data analytics tools. Much data resides in databases, and it is beneficial for the data scientist to be able to carry out as much of this work as possible inside the database. This can be achieved using SQL. This article overviews some of the basic approaches to data exploration, cleaning and wrangling using SQL, including methods to deal with missing data, outliers, and bad values.
Data Science Methodology
Authors: Pohl Matthias , Haertel Christian , Staegemann Daniel , Turowski Klaus
Published: January 2023

An overview of common process models for the implementation of data science is presented in this article. Since the development of KDD and CRISP-DM, the central ideas have been examined from broader perspectives, and further frameworks have been created. In addition to the core activities that are conducted in the individual process phases, typical roles and project-supporting artifacts are outlined. In summary, a distinction can be made between four process phases that relate to ideation, data, analysis, and deployment. These phases are considered as a holistic methodology of data science. The overview is an orientation for data scientists and project managers in the preparation and realization of data science projects. However, many challenges need to be overcome to further specify and specialize the processes, which may also lead to new approaches to data science methodology in the future.
Decision-Making Systems
Authors: Nasserddine Ghalia , El Arid Amal A.
Published: January 2023

Decision-making systems are computer-based systems that interpret processed information to make the best choice. They choose an action or value from possible activities, each conducting to different outcomes. Some outcomes are favored over others based on the criteria of the decision maker. This article presents the existing technology used in decision-making systems. The authors focus then on explaining how to make the optimal decision based on the available information and criteria. The authors conclude that decision techniques are chosen based on the type of application and the quality of available data. Some techniques are simple but not accurate such as the fishbone and five whys techniques. Other methods, such as decision trees, are more complex to build, but unlike a fishbone diagram, it assists humans in evaluating upcoming choices. It forces the examination of all available outcomes of a decision and traces a possible path to the best alternative.
From DSS to Data Science
Authors: Gharaibeh Natheer Khleaf
Published: January 2023

This article highlights a group of concepts combined and traced over the past decades: decision support systems, business intelligence, big data, cloud computing, data science, web services, and many other aspects of Industry 4.0. The main objective of this work is to perform a theoretical analysis and discussion about these elements, thus providing an understanding of why and how they work together, giving us greater ability to come up with new ideas that contribute to Industry 4.0. It begins with the problem of data silos then displays the industrial revolutions. Sections 4 and 5 focus on integration shift within the IS discipline and DSS integral position within the IS discipline, and it finally ends with Section 6, “Dialectic of Technology and Business,” which shows the dialectic of technology and business, explaining the thesis of technology-driven and its antithesis of business-driven. It then synthesizes a more holistic paradigm in Industry 4.0.
Developing Machine Learning Skills With No-Code Machine Learning Tools
Authors: Djaba Emmanuel , Budu Joseph
Published: January 2023

No-code machine learning (ML) tools provide an avenue for individuals who lack advanced ML skills to develop ML applications. Extant literature indicates that by using such tools, individuals can acquire relevant ML skills. However, no explanation has been provided of how the use of no-code ML tools leads to the generation of these skills. Using the theory of technology affordances and constraints, this article undertakes a qualitative evaluation of publicly available no-code ML tools to explain how their usage can lead to the formation of relevant ML skills. Subsequently, the authors show that no-code ML tools generate familiarization affordances, utilization affordances, and administration affordances. Subsequently, they provide a conceptual framework and process model that depicts how these affordances lead to the generating of ML skills.
The Artificial Intelligence in the Sphere of the Administrative Law
Authors: Puzzanghera Alessandro
Published: January 2023

This article proposes a debate on the use of artificial intelligence in the administrative field (from a computer used as an archive to a computer capable of making decisions), with particular attention to what the concepts, principles, and standards of legitimacy and control are also examining. Administrative law has two ways to face the new technological challenges: close completely and refuse any possibility of its application to the organization and to the administrative procedure or allow a very limited application.
Trust Management Mechanism in Blockchain Data Science
Authors: Gao Ge , Liu Ran
Published: January 2023

This article aims to apply blockchain data theories to trust management in a supply chain system to solve the trust crisis brought on by opportunistic behavior in supply chain management. Incremental implications are offered to increase supply chain managers' understanding of the underlying process of building trust using blockchain data technologies. A comprehensive literature review was undertaken to build a theoretical framework of how the trust management mechanism interacts with blockchain data and supply chain management. Design and methodology integrated multiple theories with the trust management application in supply malmanagement using blockchain data technology. This work identifies the coupling relationship between blockchain data and supply chain trust management and reveals the cultural, social, and economic attributes of trust manifested in interactions of the consensus-trust mechanism and interest motivations.
Using Machine Learning to Extract Insights From Consumer Data
Authors: Chang Hannah H. , Mukherjee Anirban
Published: January 2023

Advances in digital technology have led to the digitization of everyday activities of billions of people around the world, generating vast amounts of data on human behavior. A parallel trend has been the emergence of computational methods and analysis techniques needed to deal with these new sources of behavioral data—which tend to be more unstructured, of much larger scale, and noisier. As they are recent and emerging developments, many behavioral scientists and practitioners may be unaware or unfamiliar with these recent developments and opportunities to extract behavioral insights. The main objective of this article is to discuss machine learning methods for researchers and practitioners interested in addressing customer-relevant questions using new secondary data sources that are publicly available, such as data from crowdfunding, video streaming, crowdsourcing, and social media platforms. This article offers a primer on the application of computational social science for understanding consumer data for researchers and practitioners.
A Hybridized GA-Based Feature Selection for Text Sentiment Analysis
Authors: Tripathy Gyananjaya , Sharaff Aakanksha
Published: January 2023

Recent research work has described the effectiveness of various sentiment classification techniques ranging from simple lexicon-based methods to more complex machine learning techniques. Researchers of the article develop an integrated framework that bridges the gap between dictionary-based methods and machine learning methods to achieve better accuracy and more flexibility. To solve the problem of scalability that occurs as the feature set grows, a hybrid genetic algorithm (GA)-based dimensional reduction method is proposed. With the help of this novel approach, authors can reduce the size of the feature set by reaching a remarkable value of accuracy. Here the authors have compared the proposed feature reduction method with a widely used principal component analysis and singular value decomposition-based feature reduction algorithms. In addition, the proposed sentiment analysis model is tested in other metrics, including precision, recall, F1 score, and feature size.
Aircraft Maintenance Prediction Tree Algorithms
Authors: Alberg Dima , Hadad Yossi
Published: January 2023

The operation and maintenance of modern aircraft multi-sensor data fusion systems generate vast amounts of numerical and symbolic data. Learning useful and non-trivial insights from this data may lead to considerable savings, and detection and reduction of the number of faults, as a result increasing the overall level of aircraft safety. Several machine learning techniques exist to learn from big amounts of data. However, the use of these techniques to infer the desired readable and accurate interval regression tree models from the data obtained during the operation and maintenance of aircraft is extremely challenging. Difficulties that need to be addressed include data warehouse collection and preprocessing, machine learning model readability, setup, evaluation, and maintenance. This article presents the interval gradient prediction tree algorithm (INGPRET), which addresses these issues. As shown by the empirical evaluation of a real aircraft multi-sensor data set, the INGPRET algorithm provides better readability and similar performance in comparison to other machine learning algorithms.
Graph Data Management, Modeling, and Mining
Authors: Srinivasan Karthik
Published: January 2023

A graph or a network is an abstract representation of a set of objects where some pairs are connected by links. Graph analytics is the systematic computational analysis of graphs/networks. In contrast to tabular data analysis, graph analytics requires a different set of tools, techniques, and algorithms tuned towards representation of the graph structure. With increasingly complex phenomena in today's world such as systems biology, epidemics, social networks, organizational collusions, international trade relationships, and internet of things, the importance of modeling such networked systems is more than ever. Therefore, graph analytics is a necessary toolkit in data science and machine learning warranting exclusive research enquiry and pedagogy. This article introduces the reader to the breadth of analytics tools, techniques, algorithms, and software. After reading this article, the reader should be able to identify problems that can use a network approach as well as develop corresponding graph-based analytics solutions.
Nature-Inspired Algorithms and Smart City Applications
Authors: Millham Richard C. , Agbehadji Israel Edem , Freeman Emmanuel
Published: January 2023

The paradigm of the fourth industrial revolution has presented a unique opportunity to interconnect the cyber-physical space. The objective of this interconnection is to encourage the fusion of technologies from physical, digital, and biological spheres to encourage digitization of resources ranging from building, cars, hospital, schools, energy, and many more. It is expected that such resources can make independent decisions on their state to avoid human intervention in monitoring the state of these resources which have their direct and indirect cost implication. Having an intelligent resource monitoring regime forms the underlying structure of cyber-physical space. In this article, the authors focus on the future of integrated nature-inspired algorithms in helping create an optimized resource monitoring regime towards the smart city applications.
The Role of Metamodeling in Systems Development
Authors: Mustafa Balsam A. J. , Majid Mazlina Abdul
Published: January 2023

Software systems developers are encountering different challenges as systems become increasingly complex due to numerous customers' needs that lead to a system with rich functionalities to be delivered within a short schedule. Developers also have to manage a variety of implementation methods, design techniques, and development processes. Researchers proposed “languages” as a solution to these problems. Meta-modeling is a method for defining the abstract syntax of a language. It makes the development of a language simpler allowing the designers to directly map the classes identified in domain analysis to classes in the meta-model. The meta-model expresses what models include such as concepts, relationships between them, and maybe the rules of how these concepts can be interrelated. This article presents an overview of the role and importance of meta-models in system development and their relationship with modeling languages. It highlights different aspects of metamodels standards, categories, and challenges in the research of meta-modeling.
Binary Search Approach for Largest Cascade Capacity of Complex Networks
Authors: Meghanathan Natarajan
Published: January 2023

The cascade capacity of a network is the largest threshold fraction of neighbors that should have made a unanimous decision to result in a complete information cascade. The current approach (based on the intra cluster densities of the bridge nodes of the clusters) used to determine the cascade capacity of a network is independent of the choice of the initial adopters. The authors claim that the above approach gives only a lower bound for the cascade capacity of a network and show that the cascade capacity of a network could be indeed larger if the number and topological positions of the nodes chosen as initial adopters are taken into consideration. In this context, they propose a binary search algorithm that could be used to determine the largest possible cascade capacity of a network for a given set of initial adopters. They run the algorithm on 60 real-world networks of diverse domains and observe the cascade capacity of the networks to increase with the percentage of nodes chosen as initial adopters as well as vary with the choice of the centrality metric used to choose the initial adopters.
Usage of the Basic Facebook Features as Befitting Marketing Tools
Authors: Khanam Fahima , Al-Zadid Muhammad Omar , Ullah Mahmud
Published: January 2023

Among all of the existing social media platforms, Facebook has been playing the most dominant role right from its inception, specially over the last one decade or so. It has become an integral and inevitable part of human lives in almost every single country all around the world. Marketers have taken advantages of this ever-growing popularity with an enormous client base to market their products and services using this unique and vast social media platform. Consequently, doing research on effectiveness, importance, and utilities of Facebook, the basic Facebook features to be more specific, as befitting marketing tools has become an obvious option and opportunity. This article attempts to find the impact of different technological, visual, content, usage, etc. aspects of Facebook illustrated by some universally accepted Facebook or SNS terminologies or glossaries on the perception of the businesspeople and customers about Facebook as an online shopping platform, and on the ultimate purchase intention of the customers using this platform.
Blockchain Technology, Vanilla Production, and Fighting Global Warming
Authors: Fisher Robert Leslie
Published: January 2023

While most nations concur with the United Nations prediction that we face mass extinctions, flooding, and other catastrophic damage unless we reduce global warming by 1.5 degrees Celsius within the next decade, the developing nations are insisting that they should be allowed to give priority to economic growth and development over fighting global warming. Shyam Saran, an Indian policy scientist, champions this position but points out we can accomplish both the aims of development and fighting global warming by establishing a global technology platform to share planet friendly technology with the less developed nations. Many technologies could be shared in this way (e.g., making concrete in planet-friendly ways and manufacturing hydrogen-fueled trains). This article explores how the impoverished nation of Malagasy (better known as Madagascar) could grow its economy by using blockchain in the production of vanilla while also reducing the amount of carbon added to the atmosphere.
Digital Twins, Stress Tests, and the Need for Resilient Supply Chains
Authors: Tiwari Ronak R. , Vishnu C. R.  , Sridharan R. , Kumar P. N. Ram
Published: January 2023

Supply Chain 4.0 strongly stresses on the viability of supply chains. A viable supply chain is one that is agile, resilient, and sustainable. This article focuses on the resilience aspect of supply chains. The article starts with a brief introduction to the term ‘digital twin' and how it can help supply chains of the future. The next section begins with an application of digital twin in conducting ‘stress tests' on supply chains and challenges associated with doing that. The last section describes the ideas of stress tests and digital twins as important enablers for building resilience in supply chains. Finally, the article concludes with a discussion on directions for future research and some recent metrics to quantify the resilience of a supply chain.
Statistical Model Selection for Seasonal Big Time Series Data
Authors: Wu Brian Guangshi , Drignei Dorin
Published: January 2023

Time series exhibiting seasonal behavior are common in areas such as environmental sciences and economics. Given the current capabilities to generate and store large amounts of data, in particular seasonal time series recorded at a large number of time points, new modeling and computational challenges arise. This article addresses statistical model selection for such big seasonal time series data as follows. A small sample of model orders is obtained, the corresponding time series models are fitted, and an information criterion for each of them is computed. Kriging-based methods are used to emulate the information criterion at any new set of model orders, followed by an efficient global optimization (EGO) algorithm to identify the optimal orders, thus selecting the model. Both simulated and real seasonal big time series data are used to illustrate the method, showing that the model orders are accurately and efficiently identified.
Identifying Disease and Diagnosis in Females Using Machine Learning
Authors: Pramanik Sabyasachi , Bandyopadhyay Samir Kumar
Published: January 2023

Here, the researchers are trying to prepare a model for identifying whether a patient is diabetic or not. The Pima Indian Dataset has been used in this case study. There are two types of diabetes. The research consists of two stages. The first is data pre-processing, and the other is classifier construction. After pre-processing, the data classifier will be constructed which will predict whether the patient is diabetic or not. Here the researchers plan to use decision tree classifier and random tree classifier. After studying the dataset, the researchers handled the missing values in optimum ways. All the types of proposed algorithm have been described in this article.
Green Orientation of Human Resource Management and Green Attitude of Employees: Moderation Effect of Personal Character
Authors: Renusha M.
Published: January 2023

This study is a systematic and scientific attempt to assess whether personal character moderates the relationship between green orientation of human resource management and green attitude of employees. The data were gathered using self-administered and structured questionnaires from 327 branch managers working in licensed commercial banks in Sri Lanka. There were two hypotheses developed in this paper based on the theoretical and empirical accounts regarding the green attitude of the employees. Accordingly, the findings revealed that green orientation of human resource management directs to employees’ green attitude and such relationship is significantly moderated by the personal character of employees. Based on this significant impact, it is possible to theorize that personal character of employees is an imperative concept that should be considered in the organizational contexts while making crucial decisions related to their attitude. Further, the findings are significant in terms of adding new knowledge to the literature and provide grounds to inquire the importance of green orientation of human resource management in explaining the deep understanding of green attitude of employees.
A century of research on micro-organisms from the inland waters of the largest Mediterranean island
Authors: Marrone Federico , Naselli-Flores Luigi
Published: January 2023

The first studies on the micro-organisms inhabiting Sicilian inland waters date back to the middle of the XIX century. However, these were based on single samples and mainly addressed at compiling faunistic and floristic inventories. It was in the first decades of the XX century that the first methodical studies were performed, which focussed on assessing microbial diversity in saline and hypersaline inland waters. Studies on plankton dynamics in ponds and reservoirs of the island started at the beginning of the 1980s and, since the end of the 1990s, temporary waters have also been intensively sampled, especially as regards phytoplankton and micro-crustaceans. These intensified sampling efforts contributed to increasing our knowledge of the composition, structure and functioning of the planktic compartment. On the contrary, studies on benthic microflora and fauna are still numerically scarce and mostly based on occasional collections. Also, running waters have received little attention and the methodical analysis of their micro-organisms is still in its infancy.
Rapid Diagnosis and Epidemiology of Fungal Rhinosinusitis in PostCOVID-19 Patients
Authors: Bapodra Mayuri K. , Navadiya Anamika J. , Baxi Seema N. , Gohil Mayuri Rajendra , Parmar Pankita K.
Published: January 2023

Background:

Fungal rhinosinusitis (FRS) cases are not exiguous for the world. However, their spike as a postCOVID sequelae has alarmed the world, especially India. Adding to the woes is the high mortality rate and poor prognosis associated with acute invasive fungal rhinosinusitis (AIFR) in such immunocompromised patients. In such a scenario, early and precise diagnosis of AIFR is what a patient and physician banks upon. KOH and histopathology are the two frontline investigations for the diagnosis of FRS. Our study aimed at analyzing the cases of FRS by histopathology and comparing these with KOH.

Study Design and Materials and Methods:

Prospective longitudinal study including suspected postCOVID FRS patients over a period of 1.5 months. Their clinical, histopathological, and KOH findings were then correlated.

Results:

About 72.5% clinically suspected fungal infection specimens were found to be positive for fungal elements on histopathology. Of these, only 30 cases were positive by KOH mount. Maximum patients belonged to 40-70 years of age; males (67%) more than females. Sites involved were paranasal sinuses (100%), nasal (88%), and orbital (25%). Histopathology revealed mucormycosis (100%) and aspergillosis (16%). Angioinvasion was identified in 38% of the mucormycosis cases.

Conclusion:

In a state of crisis, when the gold standard for fungal identification i.e., culture can take as many as 21 days for final report and early and judicious antifungal treatment is sine qua non of recovery, histopathology has proved to be better than KOH as far as early and precise diagnosis of fungal elements and their invasion is concerned.
Future Doctor’s Perspective of Saving Lives through Blood Donation: A Cross-Sectional Study to Assess Knowledge, Attitude, and Blood Donation Practice among 2nd Year Medical Undergraduate Students
Authors: Ratnakar Ashwini V. , Gosavi Manasi A. , Bhat Pratik P. , Chavan Ramesh Y.
Published: January 2023

Background:

The requirement of blood and its components has always been on a rise, and meeting this growing demand can only be assured through the development of newer encouragement strategies for the recruitment and retention of more healthy voluntary young donors. Medical undergraduate students with an appropriate knowledge and a positive attitude can form an important part of this pool as well as help encourage others for the same.

Materials and Methods:

A questionnaire was provided to all 2nd year MBBS students who were posted to the Department of Pathology, KAHER’s J. N. Medical College, Belagavi, Karnataka, and willing to be a part of this study. Responses of the questionnaire were recorded and quantitative evaluation of the data was done using software Epi Info™ 7.2.2.6.

Results:

A total of 280 undergraduate MBBS students participated in the study. Knowledge: 88.2% and 86.1% of the students knew the correct donor selection criteria for minimum age and hemoglobin level, respectively. Practice: Only 21.1% of the students had donated blood before. Attitude: 96.1% favored voluntary donation. 95% were willing to donate blood in the future with 82.5% willing to encourage others to do the same.

Conclusion:

Medical students have a good knowledge and positive attitude toward blood donation, but the practice of the same was very poor. Hence, there is a need to educate and approach these students to create an awareness regarding the importance of blood donation as well as involve them in voluntary blood donation.
Tourism Destination Marketing Challenges and Prospects: The Case of the Southern Route of Ethiopia
Authors: Muluneh Dagnachew Wegayehu , Chiriko Amare Yaekob , Taye Tadesse Temesgen
Published: January 2023

Tourism destinations these days focus on tourism development with little marketing attention. This study’s main aim is to assess destination marketing challenges and prospects in the Southern Ethiopian Route. The study employed a descriptive research design with a mixed research approach. Data were collected from tourists, culture/tourism experts, security personnel, road authorities and tourism businesses through questionnaires, interviews and FGD who were approached through convenience and purposive sampling techniques. The study revealed tourists are more impressed by cultural diversity which is a motivating factor, hospitality and natural attractions. Security, accessibility and quality of service are aspects tourists wouldn’t like to recommend. Furthermore, seasonality, cost of media and security threats are the main challenges faced by tourism businesses. Previous image, accessibility and security are challenges faced by DMO. The destination is lagging in marketing activities compared with its immense tourism potential. The study approaches destination marketing in a tourist route context, which makes it unique from previous enquiry attempts. Theoretical and practical implications are also forwarded.
Survey on Parameterized Verification with Threshold Automata and the Byzantine Model Checker
Authors: Konnov Igor , Lazić Marijana , Stoilkovska Ilina , Widder Josef
Published: January 2023

Threshold guards are a basic primitive of many fault-tolerant algorithms that
solve classical problems in distributed computing, such as reliable broadcast,
two-phase commit, and consensus. Moreover, threshold guards can be found in
recent blockchain algorithms such as, e.g., Tendermint consensus. In this
article, we give an overview of techniques for automated verification of
threshold-guarded fault-tolerant distributed algorithms, implemented in the
Byzantine Model Checker (ByMC). These threshold-guarded algorithms have the
following features: (1) up to $t$ of processes may crash or behave Byzantine;
(2) the correct processes count messages and make progress when they receive
sufficiently many messages, e.g., at least $t+1$; (3) the number $n$ of
processes in the system is a parameter, as well as the number $t$ of faults;
and (4) the parameters are restricted by a resilience condition, e.g., $n >
3t$. Traditionally, these algorithms were implemented in distributed systems
with up to ten participating processes. Nowadays, they are implemented in
distributed systems that involve hundreds or thousands of processes. To make
sure that these algorithms are still correct for that scale, it is imperative
to verify them for all possible values of the parameters.
The development of sentence complexity in the writing of young learners of L3 Spanish in Norway
Authors: Drange Eli-Marie Danbolt
Published: January 2023

This article explores the development of sentence complexity in the writing of young learners of Spanish as the third language (L3) learned in Norwegian schools. Learning to write in a foreign language is a complex process, and a novice learner will start to write simple sentences that develop over time. To track this development, the present study investigates texts written by learners of Spanish from the first and second year of upper secondary school (school years 11-12, ages 16-17) as their ordinary schoolwork. The texts are collected as part of the TRAWL (Tracking Written Learner Language) corpus and show how learners write in an authentic school context. To address sentence development, the use of coordinating and subordinating conjunctions is analyzed. The findings indicate that most pupils use y (and) and pero (but) to coordinate clauses. In subordinate clauses, que is frequently used to introduce relative clauses and porque to introduce causal clauses. There are only a few examples of a more varied use of conjunctions, indicating individual differences in the process of developing sentence complexity.  The studied features are estimated to be acquired at the A1 level in the Common European Framework of Reference for Languages (CEFR), while the pupils in this study are expected to be at the A2 level. The findings show that there may be a discrepancy between the pupils’ actual knowledge and the expected knowledge according to the reference levels.
Writing in German as a foreign language in Norwegian upper sec-ondary school: An investigation of patterns of language choices for meaning-making
Authors: Hamann Veronika
Published: January 2023

The main objective of this article is to identify and describe characteristic patterns of language choices in texts written by Norwegian upper secondary school students of German as a foreign language (GFL) (age 16/17, school year 12, 5th year of FL learning). The study maps language choices in a set of 12 learner responses to a writing prompt about interpreting a film title. The aim of the study is to describe these choices in terms of how the learners use ideational meaning-making resources to arrive at meaningful content. The study takes a systemic functional linguistics (SFL) approach and analyses the responses in terms of the following lexicogrammatical and discourse semantic systems of resources: Transitivity, taxonomic and logico-semantic relations. The study finds several strategies and language choices that presented themselves as particularly relevant for meaning-making. For example, the learners reach an interpretation through clauses relating two messages to each other, and one of those two messages is typically structured in a complex way. Overall, the study provides insights into relevant patterns for expository writing in general and such that seem important to the particular context in which the response was situated. The article also points to the sophistication of the learners’ language use and the linguistic demands regarding the task at hand. In line with existing research, the current study also shows how SFL and genre theory can be successfully applied to the analysis of responses by beginner to intermediate GFL learners.
Influence of the state reform of primary education on the professional training of future teachers
Authors: Kryvylova Olena , Oleksenko Karina , Kotelianets Natalka , Kotelianets Yulia , Kindei Lesya , Kushnirova Tetiana
Published: January 2023

The purpose of the study was the analysis of the implementation of the reform of primary education as a structural model of the formation of the preparation of the future elementary school, for the design of the educational environment. The research methodology used included the analysis of legislative documentation to determine the requirements for the professional activity of an elementary school teacher. The procedure and features of actions for the development of a structural-functional model, of the formation of the readiness of future elementary school teachers to design an educational environment include: analysis of objects; choice of the form of the model; theoretical, methodical, spatio-temporal, material-technical, legal substantiation; the choice of a factor of formation of the system; establishment of connections and dependencies of the main components. The content of the developed main blocks of the model: meta - purpose and task; methodological - approaches and principles; content-procedure - updated content of the discipline content of the vocational and practical training cycle, forms of organization of the educational process, methods, means of training and diagnostics; organizational and pedagogical conditions; stages: adaptation, intensification and identification. It is concluded that the developed model reflects the actual educational process of achieving the expected results.
The role of budgets in strengthening the financial base of local self-governments
Authors: Khudolei Veronika , Karpenko Oksana , Tarnovska Iryna , Biriukov Iegor , Smyrnov Ivan
Published: January 2023

The purpose of this study was to justify the role of local budgets in strengthening the financial base of local self-government in modern conditions of social development, oriented to the processes of democratization and decentralization of political power. The research methodology used was an integral approach, which allowed investigating the role of local budgets in strengthening the financial base of local self-government from an economic, organizational and legal point of view. A comprehensive approach allows to systematically address the definition of the role of local budgets and to highlight their specific characteristics. It is concluded that, scientifically identifying the various aspects of the functioning of local budgets allowed to distinguish their essence from the point of view of combining organizational, economic and legal approaches to, at the same time, consider them as a multifunctional system of financial, economic, legal and social relations, which provides for the possibility of redistribution of income due to the creation and use of monetary funds of the authorities of local authorities, to meet the public needs of the population and sustainable development of the territories.
Legal and organizational foundations for delivering e-government
Authors: Khomyshyn Iryna , Lesko Nataliia , Skochylias-Pavliv Olha , Lukіanova Halyna , Malets Marta
Published: January 2023

The aim of the research was to analyze the legal and organizational foundations of e-government. The introduction of e-government in Ukraine is regulated by a large number of normative legal acts in the field of information society development. The analysis of information sources-legal norms by using general scientific and special scientific methods led to the conclusion that the provisions of administrative legislation also belong to the information legislation. It was concluded that the legal framework for the implementation of e-government should not only be harmonized with generally recognized international standards, but also, developed and adopted in the context of the Sustainable Development Goals until 2030. Based on the assessment and comparison of the main trends in the development of digital economy, simplification, decentralization, deregulation, institutional capacity development and communication support are attributed to the main achievements and digital capabilities of Ukraine in the direction of e-government. Definitely, the need to improve e-governance mechanisms in the sphere of telecommunication networks at the state level is emphasized.
European experience of preventive activities performed by law enforcement agencies: administrative aspect and theoretical-legal aspect
Authors: Ishchenko Ivan , Buhaichuk Kostiantyn , Tokarchuk Olha , Rudoi Kateryna , Tsareva Iryna
Published: January 2023

The aim of the research was to reveal the peculiarities of preventive activities carried out by law enforcement agencies in the countries of the European Union. Attention is paid to the known methods of preventive work carried out by the police of different countries, which make it possible to prevent crimes and arrest criminals when they are still preparing to commit a crime. In this regard, models of preventive activities used in continental European countries are described. The methodological basis of the research is presented in comparative-legal and systematic analysis, formal-legal method, method of interpretation, hermeneutic method, as well as methods of analysis and synthesis. In the conclusions attention is paid to the peculiarities of prevention applied by individual members of the European Union, in particular, the policy of prevention by the Polish police, in terms of recidivism of persons who have already committed crimes. This policy is developed by borrowing from the European experience, because in some countries the emphasis is on extending the powers of police officers, in others - on maximum interaction with the society involved to help implement some police functions.
Application of the method of computer forensic simulation of crimes in the course of an armed conflict
Authors: Tymchyshyn Andriy , Zvonarov Oleh , Mokhonko Olena , Postryhan Vitalii , Popovych Olena
Published: January 2023

The objective of the study was to determine the characteristics and perspectives of the use of computer simulation as a method for investigating crimes committed in the course of an armed conflict. In addition, the study involved a system approach, descriptive analysis, systematic sampling, doctrinal approach and prognostic methods. The author chooses the technological direction of application of the simulation (prospective or retrospective) and simulates the characteristics of the event, the identity of the offender, the victim of the crime and the sequence of the investigation process. In the course of hostilities, computer simulation can be performed by representatives of national and international law enforcement agencies, depending on the type of crime. Computer simulation in the course of armed conflict requires standardization of procedures and improvement of the substantive and instrumental components of the application of this method. It is concluded that this model has different perspectives for its development, which include: standardization of procedures with due regard to the specifics of the crime committed and the offender; details of information sources; technological direction of simulation; possible types of models; and, the need/appropriateness of involving international coordination assistance.
The role of digital technologies for the canine units involved in the law enforcement in European countries
Authors: Polián Pavel , Polián Petr , Kopotun Igor
Published: January 2023

The aim of the article was to consider the role of digital technologies in law enforcement by canine units in European countries. Comparison and observation methods were the main methodological tools. The research showed that European K9 units assist in rescue operations, detection of prohibited substances, firearms and ammunition. Their activity is necessary during the tracking and arrest of criminal suspects. European canine units are responsible for protecting service dogs from undue risk. It was found that tactile interfaces, UAV-based surveillance sensors, video surveillance systems and GPS are becoming components of European requirements for canine service activities. Projects implemented as part of the European research and innovation program Horizon 2020 aim to develop technologies for rapid response services. It is concluded that, the INGenIOuS Project resulted in the development of an effective K9 vest for a search dog, which is based on a complex of modern digital technologies. In addition, the installation of devices in patrol cars can help to save a working dog.