bluuebunny/crossref_metadata_2025 huggingface dataset:
The welfare effects of asset mean‐testing income support
Authors: Wellschmied Felix
Published: January 2021

This paper studies the savings and employment effects of the asset means‐test in US income support programs using a structural life‐cycle model with productivity, disability, and unemployment risk. An asset means‐test incentivizes low‐income households to hold few financial assets making them vulnerable to predictable and unpredictable income changes. Moreover, it incentivizes relatively productive households that happen to have few financial assets to leave the labor force. However, it allows for relative generous transfers to households in most need. Moreover, it counteracts relatively productive households leaving the labor force after the age of 50. In terms of the welfare of an unborn household, the asset means‐test that optimally trades off these effects is $150,000, and abolishing it is close to optimal.
Partial identification of the distribution of treatment effects with an application to the Knowledge is Power Program (KIPP)
Authors: Frandsen Brigham R. , Lefgren Lars J.
Published: January 2021

We bound the distribution of treatment effects under plausible and testable assumptions on the joint distribution of potential outcomes, namely that potential outcomes are mutually stochastically increasing. We show how to test the empirical restrictions implied by those assumptions. The resulting bounds substantially sharpen bounds based on classical inequalities. We apply our method to estimate bounds on the distribution of effects of attending a Knowledge is Power Program (KIPP) charter school on student achievement, and find that a substantial majority of students' math achievement benefited from attendance, especially those who would have fared poorly in a traditional classroom.
The discretization filter: A simple way to estimate nonlinear state space models
Authors: Farmer Leland E.
Published: January 2021

Existing methods for estimating nonlinear dynamic models are either highly computationally costly or rely on local approximations which often fail adequately to capture the nonlinear features of interest. I develop a new method, the discretization filter, for approximating the likelihood of nonlinear, non‐Gaussian state space models. I establish that the associated maximum likelihood estimator is strongly consistent, asymptotically normal, and asymptotically efficient. Through simulations, I show that the discretization filter is orders of magnitude faster than alternative nonlinear techniques for the same level of approximation error in low‐dimensional settings and I provide practical guidelines for applied researchers. It is my hope that the method's simplicity will make the quantitative study of nonlinear models easier for and more accessible to applied researchers. I apply my approach to estimate a New Keynesian model with a zero lower bound on the nominal interest rate. After accounting for the zero lower bound, I find that the slope of the Phillips Curve is 0.076, which is less than 1/3 of typical estimates from linearized models. This suggests a strong decoupling of inflation from the output gap and larger real effects of unanticipated changes in interest rates in post Great Recession.
Robust inference in deconvolution
Authors: Kato Kengo , Sasaki Yuya , Ura Takuya
Published: January 2021

Kotlarski's identity has been widely used in applied economic research based on repeated‐measurement or panel models with latent variables. However, how to conduct inference for these models has been an open question for two decades. This paper addresses this open problem by constructing a novel confidence band for the density function of a latent variable in repeated measurement error model. The confidence band builds on our finding that we can rewrite Kotlarski's identity as a system of linear moment restrictions. Our approach is robust in that we do not require the completeness. The confidence band controls the asymptotic size uniformly over a class of data generating processes, and it is consistent against all fixed alternatives. Simulation studies support our theoretical results.
Comportamiento a fatiga de baja frecuencia del compuesto Rene®80 recubierto de aluminuro de platino cerca y por encima del DBTT
Authors: Mehdi Barjesteh Mohammad , Mehdi Abbasi Seyed , Zangeneh Madar Karim , Shirvani Kourosh
Published: January 2021

La superaleación Rene®80 a base de Ni se utiliza para fabricar álabes de turbinas de gas en motores a reacción. La vida útil de algunas palas de turbina de motores a reacción está limitada por la fatiga de baja frecuencia y esta propiedad se ha visto fuertemente afectada por los revestimientos. La temperatura de transición de dúctil a frágil (DBTT) es el factor más importante que afecta las propiedades mecánicas de las aleaciones recubiertas. En este estudio, se evaluó el comportamiento de fatiga a alta temperatura y baja frecuencia del compuesto Rene®80 sin recubrimiento y recubierto con aluminuro de platino (Pt-Al) a temperaturas de 871 °C (cerca del DBTT) y 982 °C (por encima del DBTT). Los resultados de las pruebas de fatiga, en condiciones de deformación controlada a 871 °C para R = 0 y una tasa de deformación de 2×10-3 s-1, en un intervalo de deformación total de 0,8%, mostraron una disminución de la resistencia a la fatiga de las muestras recubiertas de aproximadamente un 14%, en comparación con las no recubiertas. Sin embargo, el aumento de la temperatura de prueba de 871 °C a 982 °C, condujo a un aumento en el comportamiento a fatiga de baja frecuencia del compuesto Rene®80 recubierto en aproximadamente un 10% en comparación con las muestras sin recubrir.
ELECTROCARDIOGRAM DATA COMPRESSION TECHNIQUES IN 1D/2D DOMAIN
Authors: Pandey Anukul , Saini Barjinder Singh , Singh Butta
Published: January 2021

Electrocardiogram (ECG) is one of the best representatives of physiological signal that provides the state of the autonomic nervous system, primarily responsible for the cardiac activity. The ECG data compression plays a significant role in localized digital storage or efficient communication channel utilization in telemedicine applications. The lossless and lossy compression system’s compressor efficiency depends on the methodologies used for compression and the quality measure used to evaluate distortion. Based on domain ECG, data compression can be performed either one-dimensional (1D) or two-dimensional (2D) for utilization of inter and inter with intra beat correlation, respectively. In this paper, a comparative study between 1D and 2D ECG data compression methods was taken out from the existing literature to provide an update in this regard. ECG data compression techniques and algorithms in 1D and 2D domain have their own merits and limitations. Recently, numerous research and techniques in 1D ECG data compression have been developed, including direct and transformed domain. Additionally, 2D ECG data compression research is reported based on period normalization and complexity sorting in recent times. Finally, several practical issues highlight the assessment of reconstructed signal quality and performance comparisons with an average comparative of exhaustive existing 1D and 2D ECG compression methods based on the utilized digital signal processing systems.
Child Online Pornography
Authors: Kumar Sachil , Saxena Geetika
Published: January 2021

Online child pornography is a ubiquitous predicament over the internet, and its pessimistic effects and steady growth are significant in today's society. Online CSAM trading has recently gained much attention as well as “moral outrage” for national and international governments and law officials due to the ease of availability and sustained connectivity. The chapter is structured to highlight a deeper understanding of the term “CSAM” that is more diverse than the stigmatized expression of word child pornography and addresses the dark internet modalities frequently used by pedophiles to attract innocent victims. The authors also explored numerous innovative digital technologies and methods used by law enforcement officers around the world, together with corporate and non-governmental organizations to combat this unseen enemy.
Resolving Conflicts and Preventing Violence in Italian Schools
Authors: Cerchia Alessia , Dal Pubel Luca , Casale Nicoletta
Published: January 2021

Phenomena of conflicts among students are on the rise everywhere in the world. According to a new report from the United Nations Children's Fund (UNCEF), half of the world's teenagers experience peer violence and bullying in and around the school. School violence affects learning and has a negative effect on students, schools, and the broader community. The effects on students are both psychical and phycological and often lead to isolation, depression, and in some cases to suicide. This chapter provides an overview of an alternative methodology approach to the teaching of dialogue and non-violent communication in schools. Furthermore, it examines a training model that uses mediation and Aikido to teach communication, conflict management, and conflict resolution to students and teachers. The training, called School of Mediation-Mediation for School (SMS), has been developed in Italy by a group of lawyers, mediators, and researchers. To date, the project has involved more than 600 students and 250 teachers with important results.
Peace Studies at a California Community College
Authors: Overly David Paul
Published: January 2021

This is a case study of the development of a new peace studies program at Citrus College in Glendora, California, the third such program at a California community college. The program began in the spring semester of 2016 when the cornerstone course, Humanities 123 – Introduction to Peace Studies, was taught for the first time. The course is an introduction to peace and conflict studies, with an emphasis on war's destructive impact on culture. The course examines the systematic approaches that combatants have historically used to obliterate the cultural heritage of their battlefield opponents. It encourages tolerance and respect for different perspectives, as well as hope for peaceful conflict resolution. The chapter reviews the course content, as well as student reactions to the material. Overall, the students find the course to be rewarding and are surprised at how interesting peace studies can be. The program is now being expanded to include a study abroad component in Oslo, Norway.
How to Create Sustainable Nonviolence Curriculum in Public Schools in Sweden
Authors: Wright Giuseppina
Published: January 2021

The author argues the urgent need for nonviolence training and the contemporary challenges of implementing such plans. Furthermore, the chapter briefly discusses the eruptions of violence and experienced in Europe, along with innovative ways to educate all stakeholders. In addition, the chapter includes a case study of Swedish schools, with research of contemporary nonviolence training and curriculum. The chapter will benefit a variety of entities and organizations, such as educators in public school systems and governmental organizations. Findings suggest a growing concern among educators, students, and parents due to escalating threats and acts of violence in school settings. Moreover, findings indicate partial integration of sustainable nonviolence curriculum into some Swedish schools. The author proposes to integrate and implement nonviolence training into the Swedish public school system as nationally-mandated integrated subjects. Further research suggests additional research conducted to measure qualitative and quantitative results nonviolence curriculum and training.
Nonviolent Discipline Practices Within Classrooms
Authors: Chitiyo Rufaro A. , Nyemba Florence , Ramsey Elizabeth A.
Published: January 2021

This chapter focuses on nonviolent discipline practices within classroom settings. The authors draw upon a trauma-informed perspective as a means to encourage professionals working with children to engage in best practices as they decide how to best discipline children under their care. They also address a few examples of nonviolence in U.S. history because peace has worked multiple times as a means to solve social problems. In addition, they provide a brief history of discipline in U.S. schools and how that has evolved over time. Furthermore, they explain possible causes of trauma in children, how to discipline children with histories of trauma, how to implement trauma-informed care in K-12 settings, as well as provide examples of trauma-informed classroom strategies. Using a case study, they provide an example of how to guide teachers to use nonviolent discipline in their work with children with histories of trauma.
Climate Change and Its Impact on Soil Fertility and Life Forms
Authors: Biswal Trinath
Published: January 2021

Climate change can disturb the characteristics of the soil either indirectly, or directly, or both. The direct effects include changes in the soil properties and composition by organic carbon transformation, precipitation, temperature, and % of moisture. The indirect impact includes nutrient cycling, improved soil erosion rate due to an increase in rate and intensity of rainfall, irrigation facility, changes in the crop rotation, and spadework practices. The presence of soil organic carbon (SOC) greatly influenced by the climatic condition. The crop cultivation depends upon the exchange of carbon between the troposphere and soil, which also vastly influences the fertility of the soil. The use, development, and management of soil depend upon soil structure, soil texture, soil stability, water holding capacity of the soil, availability of the nutrients, and erosion of the soil. Hence, deterioration of soil fertility by climatic change may affect the several soil lifeforms like fauna and flora either directly, or indirectly through nutritional value of the soil.
Textile Industry and Health Hazards: Impact of Climate Change Issues and Fertility Potential
Authors: Naha Nibedita , Manickavachagam Gokul
Published: January 2021

Textile industry is one of the primarily concerned industries in the world generating huge revenues where both the skilled and unskilled labours are employed. Raw materials are mainly synthetic chemicals rather than the natural one. Several bleaching agents, additives are also used to get sufficiently high and uniform degree of whiteness in the textile materials. Environmental contamination is also common by the textile effluents. All these substances are mutagenic and carcinogenic, and cause enormous health hazards to humans, animals, and aquatic lives. Infertility, implantation failure, and miscarriage due to exposure to dyes, dye intermediates, and other raw materials are major concern worldwide as integrity of both the male and female gametes are massively affected by them. However, little or no attention has been paid in real life scenario, mainly in the developing and under developed countries including adaptation of successful and advanced mitigation strategies. Therefore, the chapter highlights the common issues and possible remedial measures of the textile industry exposure with respect to fertility potential and pregnancy outcome.
Chronodisruption and Loss of Female Reproductive Potential Due to Shift Work
Authors: Haldar Chandana , Pal Chowdhury Jayita
Published: January 2021

Entrainment of 24 hrs light/dark cycle is nowadays getting altered in corporate sector and even at home due to over exposure to artificial light at night (ALAN) and is commonly denoted as chronodisruption. Chronodisruption interferes with the daily physiology that is regulated by SCN/pineal-melatonin/Hypothalamo-Pituitary axis. In females, reduction in sleep due to shift work desynchronizes HPG-HPA axis induces a stress like condition, accompanied by increased free radical generation in ovary leading to polycystic ovaries, depletion of ovarian reserve, luteal phase defects, endometriosis, implantation failure, etc. Evidence suggest that there is remedial rescue by management of circulatory melatonin due to its chronobiotic/antioxidant/anti-inflamatory/antiapoptotic potentials and its role in ovarian folliculogenesis and steroidogenesis. Advancement in melatonin research suggests that it could be beneficial for commercial use, that is, (1) as an endogenous synchronizer, (2) to improve the quality of oocyte, and (3) for promoting success in the frequency of IVF.
The Effect of Temperature on Sperm Motility and Viability
Authors: Malik Junaid Ahmad
Published: January 2021

Sperm motility is a key factor in permitting us to decide semen quality and capacity to fertilize. Motility in semen is for the most part constrained by K+ in salmonids, and presumably additionally in sturgeons, and by osmotic pressure in other freshwater and seawater fish species; however, different elements, for example, combination of encircling metabolites and particles (Ca2+, Mg2+, and so on.), pH and temperature likewise impact motility attributes. In the chapter, the author has fundamentally surveyed and abridged the impacts of temperature on the motility of spermatozoa in some fish species (salmonids, cyprinids, and sturgeons) and of humans also. DSper fluxes are initiated by warm temperatures and intercedecation conductance, which shares a pharmacological profile suggestive of TRPV4. Together, these outcomes recommend that TRPV4 actuation triggers early membrane depolarization, encouraging both CatSper and Hv1 gating and, therefore, sperm hyperactivation.
Climate Change on Fertility and Reproductive Processes of Female Livestock
Authors: Nyika Joan Mwihaki
Published: January 2021

The effects of climate change continues to be a growing modern-day challenge. Climate change-induced heat stress disrupts reproductive and fertility systems in livestock. In males, it modifies the physiology of the spermatogenic cycle resulting to poor quality semen and high prevalence of secondary sperm defects. In female livestock, heat stress decreases the production of gonadotrophins, results to hormonal imbalance, decreases the quality of oocytes, and lengthens the oestrous period leading to infertility. These effects can be reversed through genetic modifications, nutritive supplementation, physical cooling mechanisms, and hormonal therapies. The successful implementation of the ameliorative strategies is pegged on improved research and their combined administration. Ultimately, climate change mitigation and adaptation are indispensable to overcome fertility problems in livestock among other environmental effects of the climate variations.
Multidimensional Impact of Climate Change on Human Reproduction and Fertility
Authors: Choudhari Ranjana Hanumant
Published: January 2021

Research has identified a multidimensional, interactive relationship between climate change variables and an adverse (mostly) impact on the mammalian reproductive systems, reproductive organs, and fertility in animals, but direct evidence establishing the impact of climate change on reproductive health and fertility in humans is limited. Climate change has established direct or indirect linkages with re-emergence, geospatial redistribution of pathogens of likely reproductive health significance in humans. Similarly, alterations in growth, mortality rate, reproduction, and spatiotemporal distribution of vectors (e.g., zika virus – Aedes aegypti) and intermediate hosts (e.g., Schistosomiasis – snail) of certain infectious diseases of reproductive health importance are influenced by climate change variables like temperature, precipitation, and humidity. The exposure channels or effect pathways, through which the regional and global climate change can directly or indirectly influence the human reproductive ability, health, fertility, progeny, and thus, ultimately, demography can broadly be classified as physical variables, chemical hazards, biological agents, factors related to psycho-socio-behavior, and economy. The chapter is an overall account of how each of these factors, as an inherent component of climate change has the potential to cause a variable degree of impact on human reproduction from a medical point of view. As human reproductive systems are highly vulnerable to diseases and other post-catastrophic effects of extreme climate change events, so it is high time to understand the adversity and resort to proper and sustainable control measures for a healthy reproductive life of future generations.
The Praxis of Cultural Narratives in International Mobility
Authors: Premat Christophe Emmanuel
Published: January 2021

Many discourses encourage the international mobility of students as a proof of intercultural openness. The studies abroad are included in all the curricula and satisfy the international profile of future candidates coming in the labour market. In this context, the international mobility of high school pupils is also promoted to acquire a form of personal autonomy with the acquisition of a new language. There is a strong mobility of international pupils that spend a year abroad in another educational system. In Sweden, the choice of a high school depends on the grades obtained earlier but also on what the high schools offer in terms of short international mobility (study trip to England). The programme “One Year in France/Spain/Germany/Austria” was created at the end of the 1980s with the board of international programmes from the Swedish Ministry of Education, some embassies and cultural centres from the concerned countries, the Swedish Institute in Paris. The chapter analyzes the narratives of the students who took part in the programme.
Religious Narrative in Turkey
Authors: Karakoca Okan , Sarı Engin
Published: January 2021

This chapter examined how religious opinion leaders guide people on religious issues and inform them how they should live shape the social segments they address. According to this review, four religious opinion leaders were selected, and their profiles on social media platforms were put into content analysis. As a result of the analysis, the forms of conservatism represented by religious opinion leaders were determined, and the characteristics of the Muslim identity they had built were determined. In this context, the similarities and differences of the identities revealed have been deduced. In this way, data was collected that could be used in other studies on religious opinion leaders.
Are You an Observer or a Supporter of War?
Authors: Akaydin Aydin Aysegul , Eksioglu Sarilar N. Beril
Published: January 2021

This chapter presents a framework for narratives of war news in consideration of Galtung's war and peace journalism theories. News narratives are discussed in the light of BBC's ethical principles of war journalism. Additionally, transformation of war journalism with the advances in communication technologies is analysed. The method of research is through review of literature and interviews in depth. Five war journalists were interviewed. These five Turkish journalists witnessed five different eras. Ergin Konuksever is the oldest war journalist in Turkey. He was reporting the news from Cyprus Peace Operation in 1974. İsmail Umut Arabacı is the first journalist to announce ‘Operation Peace Spring' live from the border. Cem Tekel is the editor and war journalist who joined the operation. Coşkun Aral is an international Turkish photographer and war journalist. He won SIPA PRESS award in 1977 with his photograph of 1st May National Labor Day. Kerim Ulak is an A Haber editor and journalist who joined the operation. His news about the operation turned out to be fake.
Security and Privacy Challenges in Big Data Environment
Authors: Manikandakumar M. , Ramanujam E.
Published: January 2021

In this information era, big data is revolutionizing business. The data are generated by each and every user from servers, terminals, smart phones, appliances, satellites, and a range of other sensors on vehicles: military, agriculture, and the like. Anything the end users does online can be traced, stored, and analyzed. It is also possible to analyze from various diverse sources such as social media postings, credit card or e-cash purchases, internet searches, mobile phone locations, etc. Users are willing to provide their private information, linked to their real-life identities, in exchange for faster or better digital services. But, the companies yet may not have the fundamental rights of the user from a security perspective. More risks are associated with big data security. The main purpose of this chapter is to explore the security concerns and privacy issues in big data environments.
An Effective Cybersecurity Training Model to Support an Organizational Awareness Program
Authors: Sabillon Regner , Serra-Ruiz Jordi , Cavaller Victor , Jeimy J. Cano M.
Published: January 2021

Traditional cybersecurity, security or information security awareness programs have become ineffective to change people's behavior in recognizing, failing to block or reporting cyberthreats within their organizational environment. As a result, human errors and actions continue to demonstrate that we are the weakest links in cybersecurity. This article studies the most recent cybersecurity awareness programs and its attributes. Furthermore, the authors compiled recent awareness methodologies, frameworks and approaches. The authors introduce a suggested awareness training model to address existing deficiencies in awareness training. The Cybersecurity Awareness TRAining Model (CATRAM) has been designed to deliver training to different organizational audiences, each of these groups with specific content and separate objectives. The authors concluded their study by addressing the need of future research to target new approaches to keep cybersecurity awareness focused on the everchanging cyberthreat landscape.
Quantum-Computing-Inspired Algorithms in Machine Learning
Authors: Kaul Deeksha , Raju Harika , Tripathy B. K.
Published: January 2021

In this chapter, the authors discuss the use of quantum computing concepts to optimize the decision-making capability of classical machine learning algorithms. Machine learning, a subfield of artificial intelligence, implements various techniques to train a computer to learn and adapt to various real-time tasks. With the volume of data exponentially increasing, solving the same problems using classical algorithms becomes more tedious and time consuming. Quantum computing has varied applications in many areas of computer science. One such area which has been transformed a lot through the introduction of quantum computing is machine learning. Quantum computing, with its ability to perform tasks in logarithmic time, aids in overcoming the limitations of classical machine learning algorithms.
A Survey on Intrusion Detection System for Software Defined Networks (SDN)
Authors: Hande Yogita , Muddana Akkalashmi
Published: January 2021

Presently, the advances of the internet towards a wide-spread growth and the static nature of traditional networks has limited capacity to cope with organizational business needs. The new network architecture software defined networking (SDN) appeared to address these challenges and provides distinctive features. However, these programmable and centralized approaches of SDN face new security challenges which demand innovative security mechanisms like intrusion detection systems (IDS's). The IDS of SDN are designed currently with a machine learning approach; however, a deep learning approach is also being explored to achieve better efficiency and accuracy. In this article, an overview of the SDN with its security concern and IDS as a security solution is explained. A survey of existing security solutions designed to secure the SDN, and a comparative study of various IDS approaches based on a deep learning model and machine learning methods are discussed in the article. Finally, we describe future directions for SDN security.
An Encryption Methodology for Enabling the Use of Data Warehouses on the Cloud
Authors: Lopes Claudivan Cruz , Cesário-Times Valéria , Matwin Stan , Ciferri Cristina Dutra de Aguiar , Ciferri Ricardo Rodrigues
Published: January 2021

A cloud data warehouse (cloud DW) is a subject-oriented, integrated, time-variant, voluminous, nonvolatile and multidimensional distributed database that is hosted in a cloud. A solution to ensure data confidentiality for a cloud DW is cryptography. In this article, the authors propose an encryption methodology for a cloud DW stored according to the star schema, considering both the data confidentiality maintenance of the DW and the capability of processing analytical queries directly over the encrypted DW. The proposed encryption methodology comprises an encryption strategy for DW called MV-HO (MultiValued and HOmomorphic) for the definition of how the different types of DW's attributes must be encrypted. The proposed MV-HO encryption strategy was compared with encryption strategies based on symmetric encryption, order preserving symmetric encryption and homomorphic encryption. Results indicated that MV-HO is the best solution found, as MV-HO is pareto-optimal with respect to other strategies investigated.
A Secure and Privacy-Preserving Approach to Protect User Data across Cloud based Online Social Networks
Authors: Neelu khare  , Kumaran U.
Published: January 2021

The tremendous growth of social networking systems enables the active participation of a wide variety of users. This has led to an increased probability of security and privacy concerns. In order to solve the issue, the article defines a secure and privacy-preserving approach to protect user data across Cloud-based online social networks. The proposed approach models social networks as a directed graph, such that a user can share sensitive information with other users only if there exists a directed edge from one user to another. The connectivity between data users data is efficiently shared using an attribute-based encryption (ABE) with different data access levels. The proposed ABE technique makes use of a trapdoor function to re-encrypt the data without the use of proxy re-encryption techniques. Experimental evaluation states that the proposed approach provides comparatively better results than the existing techniques.
Standards and Guides for Implementing Security and Privacy for Health Information Technology
Authors: Akowuah Francis E. , Land Jonathan , Yuan Xiaohong , Yang Li , Xu Jinsheng , Wang Hong
Published: January 2021

In this chapter, the authors survey security standards and guides applicable to healthcare industry including control objective for information and related technologies (COBIT), ISO/IEC 27001:2005 (which has been revised by ISO/IEC 27001:2013), ISO/IEC 27002:2005 (which has been revised by ISO/IEC 27002:2013), ISO 27799:2008 (which has been revised by ISO 27799:2016), ISO 17090:2008 (which has been revised by ISO 17090:2015), ISO/TS 25237:2008, HITRUST common security framework (CSF), NIST Special Publication 800-53, NIST SP 1800, NIST SP 1800-8, and building code for medical device software security. This survey informs the audience of currently available standards that can guide the implementation of information security programs in healthcare organizations, and provides a starting point for IT management in healthcare organizations to select a standard suitable for their organizations.
Image Encryption Method Using Dependable Multiple Chaotic Logistic Functions
Authors: Gupta Ranu , Pachauri Rahul , Singh Ashutosh K.
Published: January 2021

This article explores an efficient way of image encryption using chaotic logistic function. A set of two chaotic logistic functions and a 256 bit long external secret key are employed to enhance the security in the encrypted images. The initial condition of first logistic function has been obtained by providing the suitable weights to all bits of the secret key. The initial condition of second logistic function has been derived from first chaotic logistic function. In this proposed algorithm, ten different operations are used to encrypt the pixel of an image. The outcome of the second logistic map decides the operation to be used in the encryption of the particular image pixel. Various statistical parameter comparisons show that the proposed algorithm provides an image encryption method with better security and efficiency for all real-time applications.
A Quantum Key Distribution Technique Using Quantum Cryptography
Authors: Sharma Meenakshi , Thind Sonia
Published: January 2021

In order to protect and secure the sensitive data over the internet, the current data security methods typically depend on the cryptographic systems. Recent achievements in quantum computing is a major challenge to such cryptography systems. In this way, the quantum key distribution (QKD) technique evolves as a very important technique which gives un-conditional data security. This technique is based on the laws of quantum physics for its security. This article gives a detailed description of the QKD technique. This technique secures the encryption key delivery between the two authenticated parties from the unauthorized access. In the next phase, quantum cryptography model is discussed. Finally, some important application areas and limitations of this technology are be discussed.
Machine Learning for Internet of Things
Authors: Kashyap Ramgopal
Published: January 2021

Fast advancements in equipment, programming, and correspondence advances have permitted the rise of internet-associated tangible gadgets that give perception and information estimation from the physical world. It is assessed that the aggregate number of internet-associated gadgets being utilized will be in the vicinity of 25 and 50 billion. As the numbers develop and advances turn out to be more develop, the volume of information distributed will increment. Web-associated gadgets innovation, alluded to as internet of things (IoT), keeps on broadening the present internet by giving network and cooperation between the physical and digital universes. Notwithstanding expanded volume, the IoT produces big data described by speed as far as time and area reliance, with an assortment of numerous modalities and changing information quality. Keen handling and investigation of this big data is the way to creating shrewd IoT applications. This chapter evaluates the distinctive machine learning techniques that deal with the difficulties in IoT information.
Intelligent Malware Detection Using Deep Dilated Residual Networks for Cyber Security
Authors: Roseline S. Abijah , Geetha S.
Published: January 2021

Malware is the most serious security threat, which possibly targets billions of devices like personal computers, smartphones, etc. across the world. Malware classification and detection is a challenging task due to the targeted, zero-day, and stealthy nature of advanced and new malwares. The traditional signature detection methods like antivirus software were effective for detecting known malwares. At present, there are various solutions for detection of such unknown malwares employing feature-based machine learning algorithms. Machine learning techniques detect known malwares effectively but are not optimal and show a low accuracy rate for unknown malwares. This chapter explores a novel deep learning model called deep dilated residual network model for malware image classification. The proposed model showed a higher accuracy of 98.50% and 99.14% on Kaggle Malimg and BIG 2015 datasets, respectively. The new malwares can be handled in real-time with minimal human interaction using the proposed deep residual model.
Network Security Approaches in Distributed Environment
Authors: Sinha Keshav , Paul Partha , Amritanjali
Published: January 2021

Distributed computing is one of the thrust areas in the field of computer science, but when we are concerned about security a question arises, “Can it be secure?” From this note, the authors start this chapter. In the distributed environment, when the system is connected to a network, and the operating system firewall is active, it will take care of all the authentication and access control requests. There are several traditional cryptographic approaches which implement authentication and access control. The encryption algorithms such as Rijndael, RSA, A3, and A5 is used for providing data secrecy. Some of the key distribution techniques have been discussed such as Diffie Hellman key exchange for symmetric key, and random key generation (LCG) technique is used in red-black tree traversal which provides the security of the digital contents. The chapter deals with the advanced versions of the network security techniques and cryptographic algorithms for the security of multimedia contents over the internet.
Vulnerabilities and Threats in Smart Grid Communication Networks
Authors: Lopes Yona , Fernandes Natalia Castro , Bornia de Castro Tiago , Farias Vitor dos Santos , Noce Julia Drummond , Marques João Pedro , Muchaluat-Saade Débora Christina
Published: January 2021

Advances in smart grids and in communication networks allow the development of an interconnected system where information arising from different sources helps building a more reliable electrical network. Nevertheless, this interconnected system also brings new security threats. In the past, communication networks for electrical systems were restrained to closed and secure areas, which guaranteed network physical security. Due to the integration with smart meters, clouds, and other information sources, physical security to network access is no longer available, which may compromise the electrical system. Besides smart grids bring a huge growth in data volume, which must be managed. In order to achieve a successful smart grid deployment, robust network communication to provide automation among devices is necessary. Therefore, outages caused by passive or active attacks become a real threat. This chapter describes the main architecture flaws that make the system vulnerable to attacks for creating energy disruptions, stealing energy, and breaking privacy.
It's Not My Fault
Authors: Wang Tawei , Wang Yen-Yao , Yen Ju-Chun
Published: January 2021

This article investigates the transfer of information security breach information between breached firms and their peers. Using a large data set of information security incidents from 2003 to 2013, the results suggest that 1) the effect of information security breach information transfer exists between breached firms and non-breached firms that offer similar products and 2) the effect of information transfer is weaker when the information security breach is due to internal faults or is related to the loss of personally identifiable information. Additional tests demonstrate that the effect of information transfer exhibits consistent patterns across time and with different types of information security breaches. Finally, the effect does not depend on whether the firms are IT intensive. Implications, limitations, and future research are discussed.
Side-Channel Attacks in the Internet of Things
Authors: Zankl Andreas , Seuschek Hermann , Irazoqui Gorka , Gulmezoglu Berk
Published: January 2021

The Internet of Things (IoT) rapidly closes the gap between the virtual and the physical world. As more and more information is processed through this expanding network, the security of IoT devices and backend services is increasingly important. Yet, side-channel attacks pose a significant threat to systems in practice, as the microarchitectures of processors, their power consumption, and electromagnetic emanation reveal sensitive information to adversaries. This chapter provides an extensive overview of previous attack literature. It illustrates that microarchitectural attacks can compromise the entire IoT ecosystem: from devices in the field to servers in the backend. A subsequent discussion illustrates that many of today's security mechanisms integrated in modern processors are in fact vulnerable to the previously outlined attacks. In conclusion to these observations, new countermeasures are needed that effectively defend against both microarchitectural and power/EM based side-channel attacks.
Deep Learning in Cybersecurity
Authors: Imamverdiyev Yadigar N. , Abdullayeva Fargana J.
Published: January 2021

In this article, a review and summarization of the emerging scientific approaches of deep learning (DL) on cybersecurity are provided, a structured and comprehensive overview of the various cyberattack detection methods is conducted, existing cyberattack detection methods based on DL is categorized. Methods covering attacks to deep learning based on generative adversarial networks (GAN) are investigated. The datasets used for the evaluation of the efficiency proposed by researchers for cyberattack detection methods are discussed. The statistical analysis of papers published on cybersecurity with the application of DL over the years is conducted. Existing commercial cybersecurity solutions developed on deep learning are described.
Knowledge Extraction on the Nexus Between Terrorism Criteria and Attacks on Private Citizens and Property
Authors: Atsa'am Donald Douglas , Wario Ruth
Published: January 2021

This study extracted knowledge on the association between terrorism inclusion criteria and one of the terrorism target/victim types known as “private citizens and property.” Three criteria determine what constitutes a terror attack: Criterion 1: the action is done with intention to attain a political, economic, religious, or social goal; Criterion 2: the action is done with the intention to coerce, intimidate or publicize to larger audience(s); Criterion 3: the action is outside international humanitarian law. Literally, all terror incidents satify Criterion 3. As for Criteria 1 and 2, the odds ratio was deployed on the global terrorism database, consisting of 170,350 records of terrorist attack incidents, to evaluate the nexus between each of these criteria and terror attacks on private citizens and property. The results showed that any terror attack on private citizens and property is 2.2 times more likely to have been perpetrated by a terror group in order to achieve Criterion 2 than to achieve Criterion 1. The implications of the outcome in counterterrorism are discussed.
Informing About CSR Initiatives on the Corporate Website or Staying Invisible?
Authors: Mangani Andrea
Published: January 2021

This paper studies the communication of the corporate social responsibility (CSR) behaviour of 1,054 Italian small and medium-sized enterprises (SMEs). Manufacturing companies in controversial industries have a greater propensity to communicate corporate CSR practices, and CSR information increases with firm size, but only slightly. At the same time, the empirical analysis shows that companies in controversial industries have a lower probability of having a website. This raises issues regarding the propensity of controversial firms to set up a website, since it could expose them to public scrutiny and criticism.
A Multisided Value Proposition Canvas for Online Platforms
Authors: Belleflamme Paul , Neysen Nicolas
Published: January 2021

Operators of digital platforms have to convince potential users that their intermediation and matchmaking services bring additional value in the market. To do so, they need to formulate a strong value proposition, which convinces users that joining the platform brings them larger value than staying out. In recent years, a number of frameworks have been developed to help entrepreneurs reflect on which elements should be included (or not) in their value proposition. In this paper, the authors argue that such tools do not necessarily offer a satisfactory answer, as they miss the specificities of platform-based business models. Hence, they propose an alternative tool that overcomes the limitations they identified and is more appropriate for nascent multisided platforms. They argue that it is crucial to identify the complementarities and potential conflicts between the wants, needs, and fears of the different groups of users that the platform connects, so as to formulate a set of interlocked value propositions.
Numerical Study in Three Dimensions of Influence of the Fluids Nature and Obstacle Position on the Electronic Component Cooling
Authors: Chadi Kamel , Belghar Nourredine , Guerira Belhi , Zied Driss
Published: January 2021

In this work, we have studied numerically the influence of the nature of nanofluids and the obstacle position, within the mini-channel of dimensions (10 x 10 x 108 mm3) on the electronic component cooling. The power of the electronic component is constant. In these simulations we have considered the Al2O3-water, SiO2-water and TiO2-water as coolants. The numerical results are obtained by choosing a Reynolds number (Re) between 300 and 500 and considering that the flow regime is stationary. The simulation was performed using the software, ANSYS FLUENT.The analysis of the simulation results shows that the position of obstacles within the mini-channel has considerable effects on the improvement of the electronic component temperature. The results also showed that among the nanofluids studied, the liquid containing nanoparticles Al2O3-water is the best for the electronic component cooling.
Heat Transfer Enhancement of Heat Sources at its Optimum Position in a Square Enclosure with Ventilation Ports
Authors: Benouis Fatima Zohra , Yacine Ould Amer
Published: January 2021

Forced convection in a ventilated enclosure with aspect ratio 2 is studied. Three heat sources simulating electronic component are placed in the bottom wall of the cavity, all walls are kept insulated. With varying the inlet and the outlet location of cold air firstly then swapping the location of the heat sources, the optimal cooling strategy was identified. Consideration was given to steady two-dimensional laminar flow and Reynolds number (Re) in the range 10–1500. The governing equations along with the boundary conditions are solved by using the control volume method. Calculations showed that enhancement in heat transfer occurred, and the results indicate that there exists an optimal location of ventilation ports and an optimal disposition of heat sources for which the heat transfer is maximized for all ranges of Reynolds numbers.
Ventilation of Square Cavity Containing a Heat Source
Authors: Chati Djelloul , Bouabdallah Said , Ghernaout Badia
Published: January 2021

A numerical simulation of turbulent mixed convection of a ventilated cavity containing a heat source placed of the center has been carried out. This cavity is outfitted along couple holes: one placed within the lower left corner and the other in the top right corner. The width of the hole "H" represents is 1/5 of the length of the cavity side. The diameter regarding the round heat source "D" is equal in accordance with the breadth of the inlet gap’s H (D = H). The walls of the cavity considered are maintained adiabatic, while the temperature of the heat source T is higher than the ambient temperature. The turbulence model k-ε was used for governing equations of turbulent mixed convection inside the cavity. The finite volume method was used for numerical resolution. The parameters of flow are: the Grashof number is set to Gr = 109 and the Reynolds number (Re) varies so that the number of Richardson (Ri) takes the values Ri = 0.01, 0.05, 0.1, 1, 2, 5, 10, 20 and 30 (Ri = Gr/ Re2). The effect of thermo-dynamic parameters and the shape geometric cavity effect are investigated.
Upper Openings Ventilation System Study of the Building by the Lattice Boltzmann Model
Authors: Bouayed Zine Elabidine , Houat Samir
Published: January 2021

We present in this work a numerical study of a ventilation system in a room with two openings in the ceiling and a floor heating indicated by constant heat temperature. The double population thermal lattice Boltzmann method is used, with nine velocities model D2Q9 for the dynamic field and a five velocities model D2Q5 for the temperature field. The results are presented in the form of streamlines, temperature contour and velocity profile, and analysed as a function of the Richardson number.