bluuebunny/crossref_metadata_2025 huggingface dataset:
Contrastive intonation effects on word recall for information-structural alternatives across the sexes
Authors: Koch Xaver , Spalek Katharina
Published: May 2021

Focus highlights the fact that contextual alternatives are relevant for the interpretation of an utterance. For example, if someone says: “The meeting is on TUESDAY,” with focus marked by a pitch accent on “Tuesday,” the speaker might want to correct the assumption that the meeting is on Monday (an alternative date). Intonation as one way to signal focus was manipulated in a delayed-recall paradigm. Recall of contextual alternatives was tested in a condition where a set of alternatives was evoked by contrastive intonation. A control condition used intonation contours reported for broad focus in German. It was hypothesized that contrastive intonation improves recall, just as focus-sensitive particles (e.g., ‘only’) do, compared to sentences without such particles. Participants listened to short texts introducing a list of three elements from taxonomic categories. One of the three elements was re-mentioned in a subsequent critical sentence, realized with either a broad (H+!H*) or with a contrastive intonation contour (L+H*). Cued recall of the list elements was tested block-wise. Results show that contrastive intonation enhances recall for focus alternatives. In addition, it was found that the observed recall benefit is predominantly driven by females. The results support the assumption that contextual alternatives are better encoded in memory irrespective of whether focus is expressed prosodically or by a focus-sensitive particle. The results further show that females are more sensitive to pragmatic information conveyed through prosody than males.
Anaphoricity in emoji: An experimental investigation of face and non-face emoji
Authors: Kaiser Elsi , Grosz Patrick Georg
Published: May 2021

Emoji are widely used, but have received relatively little attention in psycholinguistic research. Upon encountering a message consisting of both text and emoji, readers presumably construct some link between emoji and text. Based on a psycholinguistic study on text-emoji relations, we argue for (at least) two types of emoji-text dependencies, related to referential dependencies known to exist in the linguistic domain, namely (i) the dependency between an expressive (e.g. wow, damn, f*king) and the individual whose opinion it expresses, and (ii) the dependency between a pronoun (or other pro-form) and its antecedent. We extend the discussion of these dependencies to emoji, and provide experimental data that face emoji resemble expressives in that they tend to be interpreted as expressing the opinion of a salient experiencer, while action emoji are interpreted based on principles of discourse coherence (e.g. discourse relations like explanation), similar to what coherence-based accounts of pronoun resolution predict.
Dijital Dünyada Kişisel Veri ve Etik: Gizlilik Politikası Bağlamında “#WhatsAppSiliyoruz” Krizinde Kullanıcı Tepkilerini Anlamak
Authors: TURANCI Eda
Published: May 2021

Her kriz çeşitli biçimlerde kişi ya da kurumları etkileyebilmekte, bu etkiler de farklı tepkilerin üretilmesine sebep olabilmektedir. Kamuoyunun tepkilerini incelemek, krizin kamusal alana nasıl yansıdığını ve değerlendirildiğini anlamak açısından önemlidir. Öte yandan son yıllarda dijital platformların gündelik yaşamdaki hâkimiyeti tartışmasız bir gerçektir. Dijital platformlar; sosyalleşmek, iletişim kurmak, eğlenmek, tepki ve düşünceleri paylaşmak, kendini ifade etmek gibi amaçlara hizmet etmekte ancak bir yandan da çeşitli sorunları gündeme getirmektedir. Son yıllarda sıkça tartışılan veri gizliliği ile kişisel verilerin korunması, paylaşılması ve depolanması konusu, dijital uygulamalar açısından hem etik hem de hukuki boyutları olan bir konudur. Kişisel verilerin saklanması, farklı mecralarla paylaşılması ve veri gizliliği bağlamında tartışılan WhatsApp krizi, çalışmanın konusunu oluşturmaktadır. Çalışmada, krize ilişkin kullanıcı tepkilerinin incelenmesi amaçlanmış olup bu amaçla Twitter’da #WhatsAppSiliyoruz hashtagi ile yapılan paylaşımlar, içerik analizi yöntemi ile incelenmiştir. İnceleme sonucunda tweetlerde en çok “mizahi” unsurlara yer verildiği, ikinci sırada “tepki” tweetlerinin ve üçüncü sırada “tepkileri eleştiren” tweetlerin olduğu görülmüştür. Konuya karşı tepki gösterme amaçlı atılan tweetlerin en çok “kişisel verilerin kullanılması sorununa” gönderme yaptığı, “dayatma”, “ayrımcılık” ve “güven kaybı, ihanet” vurgularına ise yakın oranlarda yer verildiği anlaşılmıştır. Tepkiyi eleştirmek amacıyla atılan tweetlerde ise en çok “tüm uygulamaların kişisel verileri kullandığı gerçeğine” dikkat çekildiği bulgulanmıştır.
Dijital Bilinç ve Etik Arayüzünde Transhümanizma: Altered Carbon Örneği
Authors: TOPAL Gökhan , ALANKA Ömer
Published: May 2021

Transhümanizm tarafından tapınılan bilimsel aklın yarattığı dijital bilinç ile insan, ölümsüzlüğe erişerek mitik ve dinsel eksende arzuladığı ütopyalara kavuşmuştur. Ancak ölümün geçici bir hâl alması, kurgulanan ve tasarlanan bu dünyanın bir distopyaya dönüşüne tanıklık etmiştir. Dijital bilinç ile donatılan birey için ölümün geçici bir hâl alması sonucu topluma karşı ahlaki sorumluluk ortadan kalkmıştır. Kimlik bölünmeleri yaşanırken, insan ve doğası sömürülerek istismara açık hâle getirilmiştir. Tanrı tasavvuru maddileşmiştir. Bu doğrultuda Altered Carbon televizyon dizisi üzerinden görsel ve sözlü imgeler okunarak gerçekleştirilen bu çalışma, etik sorunsalını ütopik ve distopik imgeler üzerinden tartışırken, dijitalleşerek ölümsüzlük kazanan toplum biçimlerinin tehditkâr doğasına odaklanır.
Features of the legal regulation of the fight against drug trafficking in Ukraine (1999—2005)
Authors: Kotsur Mykola
Published: May 2021

The article considers contents of regulatory legal acts adopted in Ukraine, aimed at combating illicit trafficking in narcotic drugs. It is shown that key aspects of them influenced by the international documents ratified by Ukraine and the need to ensure that counter their proliferation, by establishing rules of implementation, storage, trade and prescription. Describes the main provisions of Section XIII of the criminal code of Ukraine 2001, the assessment of the structure of liabilities, the strictness of the regulations and additional penalties.

During the period 1999—2005 was adopted a significant number of different legal acts aimed at combating illegal turnover of narcotic drugs: the criminal Code of Ukraine 2001, National Programmes, resolutions of the Cabinet of Ministers of Ukraine, orders of Ministry of health and Ministry of agriculture of Ukraine.

A feature of the criminal code of Ukraine 2001, he was a systematization of the rules on criminal liability in this area in Section XIII, to the contents of this section included twenty articles, differing in the number of parts, with notes and additional punishments.

The national programme addressed the issues of implementation of the state policy in the sphere of struggle with illicit trafficking of these dangerous substances, we have established the necessity of improvement of normative legal base, exchange of information, experiences, treatment and rehabilitation of drug addicts.

Resolution of the Cabinet of Ministers of Ukraine has decided an important question regarding the list of narcotic drugs, psychotropic substances and precursors, which were systematized in the form of four tables and nine lists, and specified rules on trade, production, manufacture and issue of medicines, which included these dangerous substances.

Orders MOZ of Ukraine has established the procedure for the prescription, break away narcotic drugs, regulate the allocation table of amounts of narcotic drugs, as well as the order of protection, control, and storage of these dangerous substances.

Key words: drug, criminal Code, the national program, normative-legal acts, penalties.
Analysis and improvement of methods for detecting shellcodes in computer systems
Authors:   Moscow State Institute of International Relations (MGIMO), Erokhin Victor V. , Pritchina Larisa S. ,   Moscow State Institute of International Relations (MGIMO)
Published: May 2021

The article discusses the problem of detecting and filtering shellcode – malicious executable code that contributes to the emergence of vulnerabilities in the operation of software applications with memory. The main such vulnerabilities are stack overflow, database overflow, and some other operating system service procedures. Currently, there are several dozen shellcode detection systems using both static and dynamic program analysis. Monitoring of existing systems has shown that methods with low computational complexity are characterized by a large percentage of false positives. Moreover, methods with a low percentage of false alarms are characterized by increased computational complexity. However, none of the currently existing solutions is able to detect all existing classes of shellcodes. This makes existing shellcode detection systems weakly applicable to real network links. Thus, the article discusses the problem of analyzing shellcode detection systems that provide complete detection of existing classes of shellcodes and are characterized by acceptable computational complexity and a small number of false alarms. This article introduces shellcode classifications and a comprehensive method of detecting them based on code emulation. This approach expands the detection range of shellcode classes that can be detected by concurrently evaluating several heuristics that correspond to low-level CPU operations during execution of various shellcode classes. The presented method allows efficient detection of simple and metamorphic shellcode. This is achieved regardless of the use of self-modifying code or dynamic code generation on which existing emulation-based polymorphic shellcode detectors are based.
Antibacterial Activity of Mucilage of Linum usitatissimum L. Seeds
Authors: Mkedder Ilham , Bouali Waffa , Hassaine Hafida
Published: May 2021

Traditional medicine has a key role in health care worldwide; the research for antimicrobial agents from plants has been a growing interest in the last few decades. Several studies indicate the presence of potent antibacterial agents in the seeds of Linum usitatissimum L. In the present study, antibacte-rial properties of mucilage extract from Linum usitatissimum L. seeds were screened against against eight Gram positive and Gram negative pathogenic bacteria using agar well diffusion method and disk diffusion method. The extract showed good results against examined bacteria and the results ob-tained by agar well diffusion method were better than those obtained from disk diffusion method. The mucilage showed strong antibacterial properties against all strains tested except Listeria monocytogenes with; the diameter of the inhibition zones (IZD) varying from 8 to 12 mm.The results of this study suggested that the mucilage from L. usitatissimum L can be a source of natural antibacterial agent.
Improved Treatment of Host-galaxy Correlations in Cosmological Analyses with Type Ia Supernovae
Authors: Popovic Brodie , Brout Dillon , Kessler Richard , Scolnic Dan , Lu Lisa
Published: May 2021

Improving the use of Type Ia supernovae (SNe Ia) as standard candles requires a better approach to incorporate the relationship between SNe Ia and the properties of their host galaxies. Using a spectroscopically confirmed sample of ∼1600 SNe Ia, we develop the first empirical model of underlying populations for SNe Ia light-curve properties that includes their dependence on host-galaxy stellar mass; we find a significant correlation between stretch population and stellar mass (99.9% confidence) and a weaker correlation between color and stellar mass (90% confidence). These populations are important inputs to simulations that are used to model selection effects and correct distance biases within the BEAMS with Bias Correction (BBC) framework. Here we improve BBC to also account for SNe Ia-host correlations, and we validate this technique on simulated data samples. We recover the input relationship between SNe Ia luminosity and host-galaxy stellar mass (the mass step, γ) with a bias of 0.004 ±0.001 mag, which is a factor of 5 improvement over previous methods that have a γ bias of ∼0.02 ± 0.001 mag. We adapt BBC for a novel dust-based model of intrinsic brightness variations, which results in a greatly reduced mass step for data (γ = 0.017 ± 0.008) and for simulations (γ = 0.006 ± 0.007). Analyzing simulated SNe Ia, the biases on the dark energy equation of state, w, vary from Δw = 0.006(5) to 0.010(5) with our new BBC method; these biases are significantly smaller than the 0.02(5) w bias using previous BBC methods that ignore SNe Ia-host correlations.
Star–Gas Misalignment in Galaxies. II. Origins Found from the Horizon-AGN Simulation
Authors: Khim Donghyeon J. , Yi Sukyoung K. , Pichon Christophe , Dubois Yohan , Devriendt Julien , Choi Hoseung , Bryant Julia J. , Croom Scott M.
Published: May 2021

There have been many studies aiming to reveal the origins of the star–gas misalignment found in galaxies, but there still is a lack of understanding of the contribution from each formation channel candidate. We aim to answer the question by investigating the misaligned galaxies in the Horizon-AGN simulation. There are 27,903 galaxies of stellar mass M
* > 1010
M
⊙ in our sample, of which 5984 are in a group in the halo mass of M
200 > 1012
M
⊙. We have identified four main formation channels of misalignment and quantified their levels of contribution: mergers (35%), interaction with nearby galaxies (23%), interaction with dense environments or their central galaxies (21%), and secular evolution, including smooth accretion from neighboring filaments (21%). We found in the simulation that the gas, rather than stars, is typically more vulnerable to dynamical disturbances; hence, misalignment formation is mainly due to the change in the rotational axis of the gas rather than stars, regardless of the origin. We have also inspected the lifetime (duration) of the misalignment. The decay timescale of the misalignment shows a strong anticorrelation with the kinematic morphology (V/σ) and the cold gas fraction of the galaxy. The misalignment has a longer lifetime in denser regions, which is linked with the environmental impact on the host galaxy. There is a substantial difference in the length of the misalignment lifetime depending on the origin, and it can be explained by the magnitude of the initial position angle offset and the physical properties of the galaxies.
Improving the Accuracy of Sepsis Screening by Nurses in Hospitalized Older Adults: A Pilot Interventional Study
Authors: Nieves Aldrin U. , Love Pamela J. , Estey Alisa J.
Published: May 2021

The current quality improvement interventional study aimed to determine whether an educational intervention focused on evidence-based practices of sepsis screening for RNs would increase accuracy of sepsis screenings performed among older adult patients in a 32-bed medical-surgical unit of a large urban trauma hospital. A total of 34 RNs participated in this study. Sepsis screenings of participants were collected and audited before and after the educational intervention to determine changes in sepsis screening accuracy. A dependent samples
t
test was used to assess the statistical difference between pre- and post-intervention sepsis screening scores. Results indicated that the educational intervention effectively increased sepsis screening accuracy in older adult patients at the study center (
p
= 0.007), with a mean increase of 22.06% accuracy. Accurate sepsis screening is crucial for early sepsis diagnosis and treatment to improve the clinical outcomes of older adult patients with sepsis, reduce health care costs, and decrease resource use. [
Journal of Gerontological Nursing, 47
(6), 27–34.]
Epimacular Inverted Retinal Flap Simulating an Epiretinal Membrane
Authors: Wang Jay C. , Chantarasorn Yodpong , Papakostas Thanos D. , Eliott Dean
Published: May 2021

A 66-year-old man was referred for management of a visually significant epiretinal membrane (ERM) with persistent cystoid macular edema after surgery for recurrent retinal detachment with proliferative vitreoretinopathy. The membrane was noted to be particularly thick and vascularized on preoperative optical coherence tomography. During the subsequent vitrectomy, the “membrane” was found to be an inverted retinal flap and successfully removed. The inverted retinal flap was thought to have been related to retinal slippage during prior surgery. This is the first report of an epimacular inverted flap simulating an ERM and highlights the importance of careful review of preoperative imaging.

[
Ophthalmic Surg Lasers Imaging Retina
. 2021;52:293–295.]
CLÍTICOS PRONOMINAIS EM LÍNGUA PORTUGUESA
Authors: Gomes Amanda Santos , Kanthack Gessilene Silveira
Published: May 2021

Neste artigo, tratamos de um tipo de pronome que tem um comportamento bastante peculiar na língua portuguesa, os clíticos pronominais, denominados de pronomes átonos pelas gramáticas de orientação normativa. As pesquisas já feitas sobre esse tipo de pronome revelam, basicamente, duas propriedades: uma envolve a colocação adjunta ao verbo, e a outra, a redução do sistema de clíticos. A fim de certificar sobre essas propriedades, realizamos uma pesquisa cujo corpus foi constituído de livros da Bíblia Sagrada, Gênesis e Apocalipse, tendo como referências diferentes versões, uma de 1969 e outra de 2010, já que o objetivo principal foi verificar se mudanças envolvendo os clíticos impactam ou não na escrita dos textos analisados. As amostras evidenciam que, de fato, de uma época para outra, houve redução no uso dos clíticos e mudança na preferência do posicionamento em relação ao verbo. Esses resultados sinalizam que, num contexto de sala de aula, cabe ao professor também destacar as mudanças que são implementadas numa língua, abordando-as como fato linguístico.
DIFERENTES AFFORDANCES NOS ECOSSISTEMAS DIGITAIS
Authors: Glück Eduardo Paré
Published: May 2021

Ensaio
Application of Deep Learning Model Convolution Neural Network for Effective Web Information Retrieval
Authors: Chawla Suruchi
Published: May 2021

Convolution neural network (CNN) is the most popular deep learning method that has been used for various applications like image recognition, computer vision, and natural language processing. In this chapter, application of CNN in web query session mining for effective information retrieval is explained. CNN has been used for document analysis to capture the rich contextual structure in a search query or document content. The document content represented in matrix form using Word2Vec is applied to CNN for convolution as well as maxpooling operations to generate the fixed length document feature vector. This fixed length document feature vector is input to fully connected neural network (FNN) and generates the semantic document vector. These semantic document vectors are clustered to group similar document for effective web information retrieval. An experiment was performed on the data set of web query sessions, and results confirm the effectiveness of CNN in web query session mining for effective information retrieval.
Simple Linear Iterative Clustering (SLIC) and Graph Theory-Based Image Segmentation
Authors: Chowdhary Chiranji Lal
Published: May 2021

With the extensive application of deep acquisition devices, it has become more feasible to access deep data. The accuracy of image segmentation can be improved by depth data as an additional feature. The current research interests in simple linear iterative clustering (SLIC) are because it is a simple and efficient superpixel segmentation method, and it is initially applied for optical images. This mainly comprises three operation steps (i.e., initialization, local k-means clustering, and postprocessing). A scheme to develop the image over-segmentation task is introduced in this chapter. It considers the pixels of an image with simple linear iterative clustering and graph theory-based algorithm. In this regard, the main contribution is to provide a method for extracting superpixels with greater adherence to the edges of the regions. The experimental tests will consider biomedical grayscales. The robustness and effectiveness will be verified by quantitative and qualitative results.
COVID-19-Related Predictions Using NER on News Headlines
Authors: Hazarika Bidyut B. , Trivedi Urvish , Dahiya Harshita , Nandwani Nishtha , Gupta Aakriti
Published: May 2021

Today, all the newspapers and online news content are flooded with the news of coronavirus (i.e., COVID-19). The virus has spread across the globe at an alarming rate. Thus, people need to remain updated about news regarding the ongoing pandemic which has taken whole world by storm. Therefore, named entity recognition (NER) is applied to extract important information from these news headlines and articles and further used for more applications related to COVID-19 in India. This chapter uses the SpaCy module to categorize the tokens extracted from the news headlines database into various pre-defined tags. Further, four different machine learning models, namely CRF Model, LSTM Model, LightGBM Model, and AdaBoost Model, are applied for performing tagging. After that, these tags are used to predict different information regarding COVID-19. Some of these applications include finding nearby hospitals and pharmacies, predicting future potential hotspots in India, worst affected states of India, gender-based comparisons, age group-based comparisons, and area-based spreading of the virus.
Security Issues in Fog Computing and ML-Based Solutions
Authors: Sahu Himanshu , Gaytri
Published: May 2021

IoT requires data processing, which is provided by the cloud and fog computing. Fog computing shifts centralized data processing from the cloud data center to the edge, thereby supporting faster response due to reduced communication latencies. Its distributed architecture raises security and privacy issues; some are inherited from the cloud, IoT, and network whereas others are unique. Securing fog computing is equally important as securing cloud computing and IoT infrastructure. Security solutions used for cloud computing and IoT are similar but are not directly applicable in fog scenarios. Machine learning techniques are useful in security such as anomaly detection, intrusion detection, etc. So, to provide a systematic study, the chapter will cover fog computing architecture, parallel technologies, security requirements attacks, and security solutions with a special focus on machine learning techniques.
Thriving Through Disruption
Authors: Michalec Paul , Brunhofer Lindsay , O'Malley John A.
Published: May 2021

In this chapter, the authors will explore the ways COVID-19 initiated widespread reform in how faculty approach online teaching. The researchers will focus on how they addressed the shift from emergency remote teaching to faculty empowerment, centered on best practices in online learning. The change, like many campuses around the nation, happened quickly and with limited resources. A central argument of this chapter is that the pandemic created unexpected opportunities for collaboration and innovation across the divide between face-to-face and online instructional design. In tackling this challenge, the researchers were inspired by the community of inquiry framework. The framework is a social constructivist model describing the learning environment as the intersection of three key “presences”: teaching, social, and cognitive. Combining this framework with social-emotional learning theory suggests that online instructional designers consider the trinity of feeling, doing, and creating when designing and delivering faculty professional development.
Shifting to Online Learning Through Cognitive Flexibility
Authors: Erarslan Ali , Beliakova Irina E. , Kecherukova Marina
Published: May 2021

The chapter presents a review of the approaches to cognitive flexibility as an ability, behaviour, and executive function in psychology and neuroscience. In education, it was used to develop cognitive flexibility theory, which is treated as a pedagogical tool to enhance learners' information processing skills. The chapter also stresses the importance of cognitive flexibility in the context of transformation to distance learning in two universities of Russia and one in Turkey during the coronavirus pandemic in Spring-Fall 2020 when faculty members were forced to use flexible and creative solutions and approaches to resume the discontinued in-person learning online and maintain it.
Remote Teacher Preparation Amidst COVID-19
Authors: Chapman Lindsey A. , Mathien Tara
Published: May 2021

In March 2020, the World Health Organization declared COVID-19 a worldwide pandemic. As a result, teacher preparation programs faced an immediate shift from face-to-face instruction and field experiences to virtual learning with little lead time. This chapter presents a trauma-informed community of inquiry (CoI) framework with a specific focus on teacher preparation. It offers insights for course revision, pedagogy and instruction, and interactions with students during these unprecedented times through examining implementation and collaboration efforts within two programs.
What the Flip
Authors: Shelby-Caffey Crystal , Jafari Samaneh , Reyes Munguia Mildred
Published: May 2021

Given the abrupt shift to online learning when schools closed down due to the COVID-19 pandemic, this chapter provides insights gained during the transition. The purpose of this chapter is to explore the use of flipped learning in teacher education courses as the courses transitioned to a virtual model. The authors discuss their participation in virtual professional learning communities (VPLCs) as well as efforts to engage students in VPLCs. This chapter offers perspectives of both instructors and students as well as insights gained while teaching in a teacher education program and while teaching at a Nicaraguan university. A primary focus within the chapter is the use of various technologies and the collaboration among colleagues in and out of the United States to instruct teachers candidates and practicing teachers from primary level through higher education programs. Practical guidance is offered to those looking to begin or further the virtual teaching and learning.
The Adverse Effect of Electromagnetic Radiation From Cellular Base Stations in Nigeria
Authors: Arinze Ndidi Stella , Okafor Patrick Uche , Onah Osondu Ignatius
Published: May 2021

On a global scale, the telecommunication industry is experiencing tremendous growth in mobile phones. Mobile phones communicate with base stations that are erected by the telecommunication industry. The base station produces radio frequency and exposes the people near the base stations to radiation. The effect of electromagnetic radiation from four base stations located at the residential area was studied by measuring their electric field strength and calculating their magnetic field strength and power density at different distances covering a frequency range of 900MHz to 2100MHz. The obtained values showed that the four cellular base stations are operating above the standard values of the International Commission on Non-Ionizing Radiation Protection Electromagnetic Field Radiation. The specific absorption rate was measured to determine the amount of radio frequency electromagnetic radiation absorbed by the human body. The result which is in the range of 3.22-3.70 W/kg is higher than the acceptable 2 W/kg for localized specific absorption rate.
The Era of the Dragon
Authors: Tomás Maria João
Published: May 2021

The upcoming decades are expected to be marked by the rise and consolidation of the People's Republic of China, PRC, as the world's first economy, dethroning the U.S. and altering global economic geopolitics. The Dragon Age will mark the 21st century, with all the consequences that can come from it. This chapter analyzes the changes that are already underway and that prepare China to be the world's great economy. The departure point will be the examination of China's economic situation. Following, the authors move on to analyzing the Belt and Road Investment, the Chinese mega investment that aims to connect China to Europe inspired by the ancient Silk Road, making a geoeconomic analysis of the main world markets and how China has long prepared this economic rise and implicates a political and military ascension statement.
Cultural Impact on Global Trade
Authors: Thakur Anusha
Published: May 2021

As in any international business relation, factors such as political, economic, social, technological, and legal dimensions are expected to significantly impact trade activities. Social factors include the cultural aspects of exports and imports along with the differences among foreign markets. Culture poses to be complementary to FDI and exports. Cultural components include food, language, clothing, values, traditions, and beliefs, which differ from region to region across the world. When the countries are culturally different, investing and trading becomes a risk. Hence, in today's scenario, it is very important for the organizations to understand cultural differences in order to compete with their competitors. Understanding these cultural differences owes the opportunity to make or break the success of a foreign trade opportunity. The global businesses need to adhere to the demands and perceptions of different cultures in the countries when they purchase different products.
Gastronomic Entrepreneurial Profile and Factors Influencing the Potential of Business Internationalization
Authors: Vargas-Hernández José G. , Zazueta-Félix Mario Guadalupe
Published: May 2021

The current challenge for the survival and growth of international businesses is the appropriation of innovation in all its senses. This chapter attempts to analyze the contextual framework of international entrepreneurship and the importance of the entrepreneur's profile that influences the potential to generate innovative environments in relation to success in doing business abroad. This analysis aims to answer the questions of strategic thinking that can be a critical factor in business competitiveness and contribute to its success.
Challenges of COVID-19 During 2020 and Opportunities for FinTech in 2021 for Digital Transformation of Business and Financial Institutions in India
Authors: Bhasin Narinder Kumar , Gulati Kamal
Published: May 2021

Fintech/TechFin/financial and banking sector achieved the new digital disruptions and transformation milestones in India, underlining the various opportunities in the last year, 2020, when the world was struggling with the COVID-19 pandemic, an extended period of lockdown, job loss, and unemployment. India has emerged as the fastest-growing second largest leading fintech hub in the world after the United States. This chapter will explain the various challenges faced in the year 2020 and opportunities for fintech in 2021. The chapter also explains the emerging technology trends and growth of finechs in India during the COVID pandemic.
Wearable Devices and Privacy Concerns
Authors: Dincelli Ersin , Zhou Xin , Yayla Alper , Jafarian Haadi
Published: May 2021

Wearable devices have evolved over the years and shown significant increase in popularity. With the advances in sensor technologies, data collection capabilities, and data analytics, wearable devices now enable interaction among users, devices, and their environment seamlessly. Multifunctional nature of this technology enables users to track their daily physical activities, engage with other users through social networking capabilities, and log their lifestyle habits. In this chapter, the authors discuss the types of sensor technologies embedded in wearable devices and how the data collected through such devices can be further interpreted by data analytics. In parallel with abundance of personal data that can be collected via wearable devices, they also discuss issues related to data privacy, suggestions for users, developers, and policymakers regarding how to protect data privacy are also discussed.
A Data Privacy Governance Model
Authors: Stoll Margareth
Published: May 2021

The importance of data privacy, information availability and integrity are increasingly recognized. The new EU general data protection regulation 679/2016 obligates stringent legal requirements with high sanctions for noncompliance. Most organizations worldwide are affected directly or indirectly. It requires overall a risk and evidence-based data privacy management as part of corporate governance. More than 1.6 million organizations worldwide are implementing a standard-based management system, such as ISO 9001 or others. To implement the new data protection regulation in an effective, efficient and sustainable way, the author provides design-oriented guidelines on how to integrate the legal requirements into standard based management systems. The holistic data privacy governance model integrates different information security governance frameworks with standard based management systems in order to comply the regulation. In that way data privacy is part of all strategic, tactical and operational business processes, promotes corporate governance, legal compliance and living data protection.
Big Data Governance in Agile and Data-Driven Software Development
Authors: Aunimo Lili , Alamäki Ari V. , Ketamo Harri
Published: May 2021

Constructing a big data governance framework is important when a company performs data-driven software development. The most important aspects of big data governance are data privacy, security, availability, usability, and integrity. In this chapter, the authors present a business case where a framework for big data governance has been built. The business case is about the development and continuous improvement of a new mobile application that is targeted for consumers. In this context, big data is used in product development, in building predictive modes related to the users and for personalization of the product. The main finding of the study is a novel big data governance framework and that a proper framework for big data governance is useful when building and maintaining trustworthy and value adding big data-driven predictive models in an authentic business environment.
Anonymous Authentication for Privacy Preserving of Multimedia Data in the Cloud
Authors: Almuairfi Sadiq J. , Alenezi Mamdouh
Published: May 2021

Cloud computing technology provides cost-saving and flexibility of services for users. With the explosion of multimedia data, more and more data owners would outsource their personal multimedia data on the cloud. In the meantime, some computationally expensive tasks are also undertaken by cloud servers. However, the outsourced multimedia data and its applications may reveal the data owner's private information because the data owners lose control of their data. Recently, this thought has aroused new research interest on privacy-preserving reversible data hiding over outsourced multimedia data. Anonymous Authentication Scheme will be proposed in this chapter as the most relatable, applicable, and appropriate techniques to be adopted by the cloud computing professionals for the eradication of risks that have been associated with the risks and challenges of privacy.
Security and Privacy Issues in IoT
Authors: Sekhar S. R. Mani , Bysani Sharmitha S. , Kiranmai Vasireddy Prabha
Published: May 2021

Security and privacy issues are the challenging areas in the field of internet of things (IoT) and fog computing. IoT and fog has become an involving technology allowing major changes in the field of information systems and communication systems. This chapter provides the introduction of IoT and fog technology with a brief explanation of how fog is overcoming the challenges of cloud computing. Thereafter, the authors discuss the different security and privacy issues and its related solutions. Furthermore, they present six different case studies which will help the reader to understand the platform of IoT in fog.
An Improvised Framework for Privacy Preservation in IoT
Authors: Hussain Muzzammil , Kaliya Neha
Published: May 2021

Data privacy is now-a-days a special issue in era of Internet of Things because of the big data stored and transmitted by the public/private devices. Different types and levels of privacy can be provided at different layers of IoT architecture, also different mechanisms operate at different layers of IoT architecture. This article presents the work being done towards the design of a generic framework to integrate these privacy preserving mechanisms at different layers of IoT architecture and can ensure privacy preservation in a heterogeneous IoT environment. The data is classified into different levels of secrecy and appropriate rules and mechanisms are applied to ensure this privacy. The proposed framework is implemented and evaluated for its performance with security and execution time or primary parameters. Various scenarios are also evaluated, and a comparison is done with an existing mechanism ABE (Attribute Based Encryption). It has been found that the proposed work takes less time and is more secure due to short key length and randomness of the parameters used in encryption algorithm.
A Survey of Methodologies for Protecting Privacy of User Data Within Enterprise Information Infrastructure
Authors: Manna Asmita , Sengupta Anirban , Mazumdar Chandan
Published: May 2021

During recent years, especially after the introduction of data protection regulations by different countries, protecting the privacy of user data has become an important research topic. Different threads of information privacy research have emerged, particularly in the areas of eliciting privacy requirements, incorporating privacy by design, performing privacy impact assessments, developing privacy enhancement techniques, implementing those techniques for privacy compliance, verifying privacy compliance, etc. Privacy engineering is integral to all phases of data lifecycle, right from privacy requirement elicitation to compliance verification. This chapter covers a brief survey of notable privacy researches and models proposed for different phases of privacy engineering (i.e., privacy requirement engineering, privacy by design, privacy impact assessment, privacy compliance, and modeling approaches for privacy in enterprise infrastructure). Models and frameworks have been chosen based on the relevance of their applicability in modeling and implementing privacy within an enterprise.
Designing Privacy-Aware Intelligent Transport Systems
Authors: Kalloniatis Christos , Kavroudakis Dimitris , Polidoropoulou Amalia , Gritzalis Stefanos
Published: May 2021

Intelligent transport systems (ITSs) play a key role in people's daily activities. ITSs significantly improve mobility offering a variety of services to a vast number of users that increase on a daily basis, as more and new services are introduced. These services are based on advanced information and communication technologies (ICTs) and rely strongly on connectivity and computing resources. However, technical vulnerabilities of the technologies used in ITS, as well as the increase in users' awareness has brought security and privacy concerns to the forefront. This article aims at identifying a set of privacy concepts that provide the bases for designing trustworthy ITS services identifying possible threats and users' privacy concerns. A key contribution of the article is a roadmap that presents in detail how for every ITS function corresponding to privacy concepts can be realized for overcoming specific threats and users' privacy concerns in a smart city context.
Web Analytics and Online Retail
Authors: Ogunmola Gabriel Ayodeji , Kumar Vikas
Published: May 2021

Currently, all major e-retailers and even the start-ups have incorporated web analytics services on their websites to monitor customer behaviour while extracting personal data. However, the web analytics data collection methods and the applications of such collected data have raised a lot of concerns regarding the ethical use of this data. The present work identifies some important ethical challenges and unethical practices that have cropped up with the usage of these techniques. The research also suggests the measures to reduce the volume and type of personal data that can be monitored by the websites/applications at the user level. It also elaborates on measures and requirements that need to be undertaken by the online retailers at the policy level to meet the country and industry standards, while keeping their practices ethical.
Algorithms for Selecting the Optimum Dataset While Providing Personalized Privacy and Compensation to its Participants
Authors: Kumar Rajeev
Published: May 2021

The privacy preserving microdata sharing literature has proposed several techniques that allow a database administrator to share a dataset in a privacy preserving manner. This paper considers the implications of adding a market layer to that setting. In this setting, individuals (data providers) can receive a market-determined compensation in exchange for their information while they also receive a personalized privacy protection. The computational burdens of satisfying a variety of privacy requirements of individuals (sellers) and dataset requirements of the data receiver (buyer) are analyzed in this paper. The author presents a polynomial time reformulation procedure that proves that the “optimum information product” creation problem reduces to multiple-choice knapsack problem, which is a weakly NP hard problem. The problem of various instance sizes is solved using FICO Xpress 7.0 optimization software. The insights presented in the paper can be utilized for creating a market of individual information in different settings.
Optimal Privacy Preserving Scheme Based on Modified ANN and PSO in Cloud
Authors: Amma N.G. Nageswari , Dhanaseelan F. Ramesh
Published: May 2021

In the cloud, various privacy-preserving and security threats on data retrieval processes exist. In this article, the authors propose an efficient method for secure privacy preserving in cloud. Initially, the shared file is encrypted using a Vigenere encryption algorithm before uploading. For creating the privacy map, the efficient classification algorithm is recommended. Here, a Modified Artificial Neural Network (MANN) is used to generate the privacy map. The weight value of the neural network is optimized using a Particle Swarm Optimization (PSO) algorithm. While retrieving files initially, the authorization of the person is verified by providing basic information, then the OTP of the respective files is verified. Since the user can retrieve the files only after authorization, verification and decryption of the files is highly secured and privacy is preserved. The performance of the proposed method is evaluated in terms of time and accuracy.
Secure Anonymous Query-Based Encryption for Data Privacy Preserving in Cloud
Authors: Konan Martin , Wang Wenyong
Published: May 2021

Data privacy protection is a paramount issue in cloud applications for the last decade. In addition, data encryption, which is the primary method to impart security in clouds, is proved insufficient to guarantee data privacy protection from some security issues like homogeneity and background knowledge attacks. Therefore, it is important to provide a security mechanism that provide not only anonymous data but also anonymous continuous queries. So, this paper proposes a new scheme (Moye) that tackles this challenge by protecting queries to be linked to specific sensitive data. Specifically, the proposed solution is based on the design of a hybrid implementation of public key encryption with keyword search (PEKS) and subset membership encryption (SME) cryptosystem to enhance both data and query privacy protection. In addition, this approach provides an efficient and anonymous data processing by using an optimized k-anonymity scheme. Doing so, the authors protect searchable keywords and queries from inside and outside guessing attacks for the effectiveness of the proposed solution.
Privacy Preserving and Efficient Outsourcing Algorithm to Public Cloud
Authors: Kumar Malay , Vardhan Manu
Published: May 2021

The growth of the cloud computing services and its proliferation in business and academia has triggered enormous opportunities for computation in third-party data management settings. This computing model allows the client to outsource their large computations to cloud data centers, where the cloud server conducts the computation on their behalf. But data privacy and computational integrity are the biggest concern for the client. In this article, the authors attempt to present an algorithm for secure outsourcing of a covariance matrix, which is the basic building block for many automatic classification systems. The algorithm first performs some efficient transformation to protect the privacy and verify the computed result produced by the cloud server. Further, an analytical and experimental analysis shows that the algorithm is simultaneously meeting the design goals of privacy, verifiability and efficiency. Also, found that the proposed algorithm is about 7.8276 times more efficient than the direct implementation.
Metrics for Ensuring Security and Privacy of Information Sharing Platforms for Improved City Resilience
Authors: Radianti Jaziar , Gjøsæter Terje
Published: May 2021

City resilience is a pressing issue worldwide since the majority of the population resides in urban areas. When disaster strikes, the consequences will be more severe in the cities. To achieve resilience, different organizations, agencies and the public should share information during a disaster. ICT-based community engagement is used for strengthening resilience. The authors propose a set of metrics for assessing the security and privacy of information sharing tools for resilience. They then apply the selected metrics to a selection of information sharing tools. The authors' main finding is that most of them are reasonably well-protected, but with less than private default settings. They discuss the importance of security and privacy for different important categories of users of such systems, to better understand how these aspects affect the willingness to share information. Security and privacy is of particular importance for whistle-blowers that may carry urgent information, while volunteers and active helpers are less affected by the level of security and privacy.
Association Rule Hiding in Privacy Preserving Data Mining
Authors: Mohan S. Vijayarani , Angamuthu Tamilarasi
Published: May 2021

This article describes how privacy preserving data mining has become one of the most important and interesting research directions in data mining. With the help of data mining techniques, people can extract hidden information and discover patterns and relationships between the data items. In most of the situations, the extracted knowledge contains sensitive information about individuals and organizations. Moreover, this sensitive information can be misused for various purposes which violate the individual's privacy. Association rules frequently predetermine significant target marketing information about a business. Significant association rules provide knowledge to the data miner as they effectively summarize the data, while uncovering any hidden relations among items that hold in the data. Association rule hiding techniques are used for protecting the knowledge extracted by the sensitive association rules during the process of association rule mining. Association rule hiding refers to the process of modifying the original database in such a way that certain sensitive association rules disappear without seriously affecting the data and the non-sensitive rules. In this article, two new hiding techniques are proposed namely hiding technique based on genetic algorithm (HGA) and dummy items creation (DIC) technique. Hiding technique based on genetic algorithm is used for hiding sensitive association rules and the dummy items creation technique hides the sensitive rules as well as it creates dummy items for the modified sensitive items. Experimental results show the performance of the proposed techniques.