bluuebunny/crossref_metadata_2025 huggingface dataset:
Physicochemical characterization and oxidative stability of microencapsulated edible sacha inchi seed oil by spray drying
Authors: Landoni L. , Alarcon R. , Vilca L. , Chasquibol N. , Pérez-Camino M. C. , Gallardo G.
Published: November 2020

The aim of this work was to obtain sacha inchi oil (SIO) microcapsules from two different species, Plukenetia volubilis L. (SIVO) and Plukenetia huayllabambana L. (SIHO), using different biopolymers as wall materials and spray drying technology. The physicochemical characteristics such as encapsulation efficiency, particle size, morphology and oxidative stability were analyzed in order to select the best formulation that could potentially be used as an ingredient in the development of functional food. Bulk SIO and four formulations were tested for each oil ecotype, using different encapsulating agents: maltodextrin (MD), Arabic gum (AG), whey protein concentrate (WPC) and modified starch HI-CAP®-100 (H). Microcapsules made of H presented the highest oxidative stability and encapsulation efficiency compared to AG, AG:MD or AG:MD:WPC formulations.
Impact of ICT Adoption on Small and Medium Enterprises in Ilala District, Dar Es Salaam, Tanzania
Authors: Benard Masese
Published: November 2020

ICT plays a critical role in the growth and development of SMEs. Tanzania is a developing country where small and medium enterprises (SMEs) are perceived as the engine of growth, yet they have not attained the expected level. The adoption of ICT enables the SMEs to be more competitive. ICT plays a very important role in the current knowledge economy. The ICT sector presents a tremendous opportunity for economic growth. If ICT is adopted, it will significantly improve the performance and productivity of SMEs. The problem facing most of the SMEs is partial or non-adoption of technology. They have to adopt ICT in order to remain competitive and be competitive. The study investigates how the adoption of ICT could contribute to the success of small and medium enterprises (SMEs), examines impact of information and communication technologies in small and medium enterprises growth and development. Technology acceptance model was adopted by the researcher. The case study and cross-sectional survey research design was used to generate data. This is because with such a design it is easy to collect data in a short period of time from many respondents. The researcher used questionnaires to gather data from SMEs institutions covering Ilala district in Dar es Salaam, Tanzania. The researcher used the sample size of 82 respondents. Simple random sampling was used in sampling SMEs in Ilala district. The data collected from the survey was analyzed using simple percentage, mean, standard deviation, and regression analysis. The results show that T1 and T3 Pearson's correlation coefficient(r) equals .231*, indicating a strong relationship in terms of correlation. p< .037 and indicates that the coefficient is significantly different from 0. We can conclude that there is correlation between T1 and T3. In particular, it seems that the more the use of computer network it stimulates the growth and development of the SMEs (r = .231, p <.037). Also T1 and T2 Pearson's correlation coefficient(r) equals .196*, indicating a strong relationship in terms of correlation. p< .077 and indicates that the coefficient is significantly different from 0 (r = .196, p <.077). ICT has great potential in the growth and development of SMEs which is still untapped in Ilala district. The adaption of ICT in SMEs business has helped to transform business to another level, sharpen market intelligence, improve efficiency, reduce supply chain from B2C, B2B, and increase customer satisfaction.
Framework for Technology-Enriched Active Class Learning of Physics in Secondary Schools in Kenya
Authors: Abenga Elizabeth Sarange Bosire , Okono Elijah Owuor , Awuor Mzee , Otanga Sarah
Published: November 2020

Active learning transforms the learning process and activities from tutor focused to learner-cantered and is driven by the learner's learning ability. In other words, active learning provides an opportunity for self-directed learning that enables the learners to engage with the learning materials at personal level and pace. Thus, this chapter argues that active learning can provide equal learning opportunity for every single learner irrespective of the differences in their personality traits that would otherwise affect how they learn. Hence, this chapter proposes a framework for technology-enriched active learning for young learners that provides a personalized learning that deviates from the traditional “fit-for-all” classroom setups that tends to favour only the extrovert students. The proposed framework leverages advancement in technology such as personal learning network, virtual physics labs, massive open online courses, and crowd-sourced expert opinions to provide the learners with just-in-time active learning opportunity.
Gastroesophageal Reflux Disease
Authors: Naaman Rouba Khalil
Published: November 2020

This chapter discusses a gastroesophageal reflux disease (GERD) case. GERD is a common disorder affecting the gastrointestinal tract. It results from the relaxation of the lower esophageal sphincter, which leads to stomach acid reflux, which in turn causes heartburn and discomfort. Certain lifestyle factors and dietary choices aggravate this condition, leading to serious tissue damage. Management of GERD usually requires medications and lifestyle and dietary modifications. This case involves the symptoms and aggravating factors of GERD. It also shows the role of medical nutrition therapy in managing GERD symptoms. Moreover, it will allow dietetic professionals to assess GERD symptoms to plan for nutrition interventions and educate patients about the dietary manipulation required to reduce gastric acid secretions and relieve pain.
Inflammatory Bowel Diseases (Crohn's Disease)
Authors: Ajabnoor Sarah , Khayat Hebah
Published: November 2020

The case study presented in this chapter is related to Crohn's disease (CD). CD is a type of inflammatory bowel diseases (IBD) affecting both small and large bowels. Several factors are involved in the aetiopathogenesis of CD. Individuals diagnosed with CD will typically experience periods of relapse and remission. Therefore, the main aim of medical therapy in CD is to induce and maintain remission. The case presented in this chapter will demonstrate the role of medical nutrition therapy in a recently diagnosed patient with CD who was admitted with abdominal pain for 6 weeks and acute flare for the disease, which is complicated by weight loss. Overall, the case study will assist the practice of clinical dietitians who are dealing with IBD patients. Mainly, it will allow them to assess the symptoms and associated nutritional complications of CD, and develop a nutrition support intervention plan. Also, it will support the process of patient's education for dietary modification to help alleviate the symptoms in CD.
The Positive Impact of Weight Management on Liver Cirrhosis
Authors: Sanousi Heba Abdulkarim , Hashim Almoutaz
Published: November 2020

Weight management offers patients with liver cirrhosis significant health benefits. This case study describes the treatment of liver cirrhosis through dietary interventions. A 48-year-old male presented at Doctor Soliman Fakeeh Hospital in Saudi Arabia, Jeddah. The patient was suffering from morbid obesity (BMI= 43.76 kg/m2), non-alcoholic steatohepatitis, and chronic hepatitis B viral infection. Sleeve gastrectomy surgery was not possible due to the patient having liver fibrosis (stage 4). Alternatively, he was offered a healthy lifestyle intervention involving advisement regarding dietary habits and the initiation of a regular exercise routine. FibroScan was repeated seven months after the dietary intervention, where it was observed that the liver fibrosis improved from stage 4 to stage 3 post-treatment. Additionally, the patient lost almost 29% of his original body weight. In this case, weight management through following a healthy, balanced diet and increasing physical activity for one year produced remarkable improvement in the patient's liver cirrhosis related to non-alcoholic steatohepatitis.
Smart Metering and Pricing Policy in Smart Grids
Authors: Dekhandji Fatma Zohra
Published: November 2020

Pricing policy is one of the tools allowing the involvement of customers in the balance between the supply and the demand in smart grids. The present chapter aims at presenting the smart metering action including the bidirectional measurement of energy for smart houses equipped with renewable energies as well as the way a smart meter communicates data at the required timing to and from the control center. A typical bill establishment explaining how the net billing is produced along with a discussion about different pricing policies that the utility may adopt to reduce the peak load demand is also presented. The work is concluded by a typical simulation of a smart city modeled in LABVIEW software.
Decentralized Energy Management System Enhancement for Smart Grid
Authors: Belaidi Hadjira , Rabiai Zakaria
Published: November 2020

In these last decades, electrical power grids become more intelligent. Hence, sophisticated software and hardware were introduced to the power grid, which makes it a smart grid. This chapter is an introduction on smart-grid technology; thus, microgrids are explained, and the use of multiagent system in centralized/decentralized energy management systems are discussed and compared. Smart agents are an emerging technology for decentralized computation and data storage. Hence, in this chapter, decentralized energy management system is created basing on multi-agent system technique where sources and loads are considered as separated agents each of them. After that, these sources and load create a microgrid and each microgrid can be considered as an agent. The work proposes an approach for load supplying optimization to decrease the microgrid cost and enhance its efficiency.
Application of Synchro-Phasor Measurement Unit in Smart Grid Including Renewable Energy
Authors: Mahboubi Meriem , Ouadi Abderrahmane
Published: November 2020

Renewable energy is one of the most abundant energies in our planet. In order to satisfy the world demand of electrical energy, solar and wind energy may be used. Identical to all other types of power generation plants, the integration of these renewable energy sources in smart power grid has an impact on its operation. Thus, when the electrical power is injected into the power grid by these energy sources, the system electrical parameters must be well monitored for synchronization purpose. This can be accomplished with the aid of synchro-phasors measurement units. The phase angle of the utility is a critical parameter for the operation of power devices feeding power into the grid such as PV and wind energy inverters. There are many techniques to obtain the grid phase angle such as the zero-crossing detection and the orthogonal phase locked loop. This research work discusses the use of PMUs (Phasor Measurement Unit) for providing this important parameter to system synchronization in the case of high penetration of solar or wind energy in the power grid.
A Study on the Policy of Cultivated Land Requisition-Compensation Balance of China With Q County R Railway Dry Port as an Example
Authors: Ding Hongbin , Gao Danli
Published: November 2020

With the acceleration of China's new urbanization and industrialization process, the expanding demand for construction land will continue to expropriate a large number of cultivated land. Under the strict land management system, the policy of land requisition and compensation balance will continue to protect China's food security and the bottom line of 1.8 billion mu of China's cultivated land. Based on China's land management law, agricultural law, and other land management policies, the authors analyzed the dilemma and development trend of China's policy of land requisition and compensation balance, combining with the case study of building R railway dry port in Q County, Western China. By analyzing the balance policy of land requisition and compensation, this chapter tries to find the defects and future development trend of China's cultivated land protection policy.
How and Why the Land Resources Changed
Authors: Manawadu Lasantha , Gunathilaka M. D. K. L. , Wijerathne V. P. I. S. , Gunathilake K. L. W. I.
Published: November 2020

Human activities have recognized in recent years as the most significant force shaping the biosphere. This is completely true concerning rapid changes in the land surface. Concerning land resources, it is important to understand how this change happens. Thus, this chapter aims to review how this change has occurred throughout the history of Sri Lanka. A piecemeal approach in the unsustainable manner of land resource utilization towards severe land changes illustrates and compares the land use and land cover changes in significant phases in the history of Sri Lanka. This was further revitalized as well as influenced by the land-use policies introduced throughout history. The absence of a clearly defined land-use policy in the country after independence is problematic when addressing land-related issues. Consequently, chronological changes in land use and land cover existed within the country has now doubled and more intensified than ever.
Challenges of the Internationalization Process
Authors: Carlos Carolina Teixeira , de Jesus Nicole Bento , Henriques Raquel Nogueira , Moreira António Carrizo
Published: November 2020

This chapter analyzes the internationalization strategy of a Portuguese knowledge-based service firm. It is based on a case study and the main objective is to discuss what internationalization theory best explains the company's internationalization strategy. The literature reviews the main internationalization patterns—Uppsala model, born globals, born again globals, and born regionals—so that a comparison of the main characteristics of each theory is discussed and analyzed. At the end of the chapter, a table summarizes the main characteristics of the internationalization process of each model presented. The case study is based on the analysis of both primary data from the firm and data obtained from an interview obtained with the CEO.
International Entrepreneurship in the Video Game Industry in Barcelona
Authors: Swirski de Souza Yeda , Olive-Tomas Antoni
Published: November 2020

Video game studios are an example of born global firms, companies that operate in international markets from the moment they are created. After providing an overview of the video game industry and a description of the video games business model, the Barcelona ecosystem is presented. A multiple case study is the chosen methodology and primary and secondary qualitative data are collected and analyzed. The purpose of the research is twofold: On the one hand, using the context of the effectuation theory to examine how video game developers transform means into effects. The first outcome of this study is a process model describing the mentioned transformation. On the other hand, the research explores the connection between microfoundations of routines and capabilities and international entrepreneurship (IE) to increase the understanding of how startups with scarce resources achieve launching games that have an international reach and, hence, become international entrepreneurs. The second outcome of this research is a model that sheds light on how microfoundations affect IE.
Using Main Courante and Daily Revenue Report Methods in Accounting of Daily Revenues in Touristic Accomodation Enterprises
Authors: Meriç Engin
Published: November 2020

In today's globalised world, internationalisation is an obligation beyond being a choice and it is inevitable for the small and medium-sized accommodation enterprises to take place in this process. Since utilising from global opportunities depends on the protection of themselves from threats, their incomes should be tracked daily, and their internal control mechanism must be strengthened. With this purpose, the study aims to realise the room revenues of SMEs with Main Courante and other unit revenues with DRRs. For the accounting of the revenues Main Courante offset is given place, whereas for the control accounts the daily revenue report offset is preferred. Documents related to income record that can be used in the flow of the process in SMEs have been included. With this method, it is aimed to prevent losses and leaks, provide data flow towards accounting internal control system, sustain competitive advantage and contribute to the internationalization efforts.
Foreign Direct Investments
Authors: Marjanović Darko , Domazet Ivana S.
Published: November 2020

Foreign direct investment is considered an effective way to enhance a country's comparative advantages. They are also a significant source of economic development, modernization, growth of production, exports, employment and income, and the main actors are multinational companies. Globalization of the market has increased the tendency for many companies to procure goods and services from different locations. The main goal of the paper is to present the structure and forms of FDI at the global level, as well as theories of FDI through the interconnectedness of multinational companies, their investments, and the economy of a country as an end user. The results of the research clearly indicate that it is in the interest of every country to attract as many FDI as possible, given that they are one of the success factors of the national economy in the global market. Therefore, the primary task of economic policy makers is to monitor world trends, harmonize domestic regulations and create an investment climate that will benefit foreign investors.
Market Structure of the Banking Sector and the Turkish Banking Sector
Authors: Güneş Nizamülmülk
Published: November 2020

The main function of banking is to contribute to economic growth by providing sectors outside of the finance section with financing that they need and fulfilling an intermediary role between lenders and borrowers. This intermediary function increases the importance of the banking sector compared to other sectors of the economy. Market structures are very significant in terms of firms' market entry and exit and stay on the market. Markets are subject to four different distinction as perfect competition, monopoly, oligopoly, and monopolistic competition markets. The objective in the market is to ensure efficiency in production and sales by pulling down the costs of production through competition. The factors determining the market structure are the numbers of firms in the sector, the degree of restriction on the entry and exit of firms in the industry, the number of those requesting products and homogeneity degree of product produced The banking sector, unlike other sectors, has unique characteristics. Competition policies which are valid in other sectors are not appropriate for the banking industry. Market openness for instability and market failures change the structure of competition. Asymmetric information, product replacement costs and externalities create barriers to entry which, allows banks to be in a dominant position in their markets. This study examines the main indicators showing concentration, effectiveness, depth, and intermediation functions of Turkish banking sector and investigates in which market structure the sector operates. In this regard, it has made policy recommendations over the results obtained.
Accounting Convergence, Mandatory Adoption of IFRS, and Accounting Quality
Authors: Ates Sinem
Published: November 2020

This chapter aims to investigate whether the mandatory adoption of international financial reporting standards (IFRS) leads to an increase in the accounting quality measured by value relevance and the role of the national institutional factors, namely development of the capital market, legal enforcement, cultural factors, legal systems, and book-tax conformity, in the change in value relevance after IFRS adoption. Towards this end, the price and financial data of listed firms from eleven EU countries for 15 years were examined by panel data methods. The results of this study indicate that mandatory adoption of IFRS leads to an increase in the value relevance of EPS however it has not a significant effect on the value relevance of BVPS. It is also found that, among the national institutional factors, legal enforcement, cultural factors, and book-tax conformity have a significant effect on the change in value relevance after IFRS adoption.
Corruption and Public Sector Borrowing in EU Transition Economies
Authors: Ozturk Omer Faruk
Published: November 2020

Corruption can be expressed as the abuse of public power for specific purposes and goals. The corruption in the public sector occurs as a result of state employees acting upon the private interests rather than public interest. The public borrowing policy is important for ensuring and maintaining the economic stability in a country. The high level of public borrowing is one of the important factors leading macroeconomic instability. Many institutional, economic, social, and political factors have been revealed as the determinants of public sector borrowing level. In this study, the causality relationship between corruption and public debt in 11 EU transition economies for the period of 2002-2017 was analyzed through causality tests of Kónya and Dumitrescu and Hurlin. Kónya panel bootstrap causality test revealed a one-way causality from public debt borrowing to corruption Croatia, Czechia, Hungary, Romania, and Slovenia and a one-way causality from corruption to public debt borrowing in Bulgaria, Estonia, Lithuania, Poland, Slovakia, and Slovenia. The Dumitrescu and Hurlin causality test discovered a bidirectional causality relationship between public debt borrowing and corruption.
The ICT Adoption in AMUL
Authors: Desai Pranav D.
Published: November 2020

The adoption of information communication technologies (ICT) in rural regions of Gujarat by the Gujarat Cooperative Milk Marketing Federation Limited (GCMMFL) can be considered as an iconic practice in the dairy industry in India. It is typically assumed that the efforts associated with the investment of ICT in rural area are not as effective as expected, though in the case of Amul, it was proved otherwise. Amul is a dairy farming company that produces a variety of milk products and GCMMF takes responsibility of distributing and marketing of the products of it. Amul has been a forerunner of rural India's adoption of ICT in dairy industry. This chapter shares the success story of Amul and how they utilized ICT in the dairy industry. The application of IT enabled Amul to get better control for the accumulated milk from scattered suppliers. The Amul case is a prime example for the enabling role of the technology for innovation.
The Challenges to Improving Public Services and Judicial Operations
Authors: Mustafa Cecep
Published: November 2020

This chapter explores judicial perspectives on sentencing minor drug offenders in Indonesia. As a basis for the framework for this study, a concept of Goffman on dramaturgy was used to explain the dramaturgical competence of the panel judges in their attempts to show accountability to their audiences (i.e., the sphere of politics, the public, and religion). Conceptualisation of this study stems from this author former self-identity as a judge but also from the author biography since the author more familiar with the practical pressure and challenges of lower court judges. This chapter contributes to knowledge by considering that the judicial awareness of the issues surrounding justice and public acceptance led to the situation where they were attempting to present a unique balance between pursuing justice and public service.
One Country, Two Organizations
Authors: Gökçe Ali Fuat , Chirindza Armando Carlos
Published: November 2020

The Republic of Mozambique lived under Portuguese colony until 1975 as a country in the south of the African continent. The struggle for independence, which began in 1962 with the founding of the Mozambique Liberation Front (FRELIMO), ended in 1975. From that date on until 1992, there was a violent civil war between the Mozambique Liberation Front and the Mozambique National Resistance Movement (RENAMO) in 1976, which took power and became a legal, political party. During the civil war in 1992, more than a million people lost their lives. In this study, the relationship and conflict between the Mozambique Liberation Front, and the Mozambique National Resistance Movement which was established as a resistance organization against Portuguese colonial rulers will be evaluated in terms of the success and failures of their endeavours. In this direction, the literature will be explored using descriptive and historical research methods. After giving brief theoretical information about terror and terrorism, the conflict between (FRELIMO) and (RENAMO) will be examined.
Regression-Based Recovery Time Predictions in Business Continuity Management
Authors: Podaras Athanasios , Moirogiorgou Konstantia , Zervakis Michalis
Published: November 2020

Business continuity is crucial for modern public organizations. It enables the uninterrupted operation of critical business functions and services in the event of an unexpected crisis situation. A key business continuity activity is to set proactively and non-arbitrarily recovery priorities while computing the recovery time effort (RTE) for these functions. The specific activity requires the consideration of technical and environmental factors of individual business functions in order to compute mathematically their recovery time. A recently published formula stems from the business continuity points method. Its limitation has been the absence of real data during its conception. The purpose of the chapter is firstly, to use business continuity data from a public college in order to validate the initial formula and, secondly, to infer a new more accurate and robust RTE equation based on regression analysis techniques. The inferred RTE formula can be used as input for predicting service availability rates.
Machine Learning in Cyber-Physical Systems in Industry 4.0
Authors: Salih Ahmed Rania , Sayed Ali Ahmed Elmustafa , Saeed Rashid A.
Published: November 2020

Cyber-physical systems (CPS) have emerged with development of most great applications in the modern world due to their ability to integrate computation, networking, and physical process. CPS and ML applications are widely used in Industry 4.0, military, robotics, and physical security. Development of ML techniques in CPS is strongly linked according to the definition of CPS that states CPS is the mechanism of monitoring and controlling processes using computer-based algorithms. Optimizations adopted with ML in CPS include domain adaptation and fine tuning of current systems, boosting, introducing more safety and robustness by detection and reduction of vulnerabilities, and reducing computation time in time-critical systems. Generally, ML helps CPS to learn and adapt using intelligent models that are generated from training of large-scale data after processing and analysis.
Explainable Artificial Intelligence (xAI) Approaches and Deep Meta-Learning Models for Cyber-Physical Systems
Authors: Daglarli Evren
Published: November 2020

Today, the effects of promising technologies such as explainable artificial intelligence (xAI) and meta-learning (ML) on the internet of things (IoT) and the cyber-physical systems (CPS), which are important components of Industry 4.0, are increasingly intensified. However, there are important shortcomings that current deep learning models are currently inadequate. These artificial neural network based models are black box models that generalize the data transmitted to it and learn from the data. Therefore, the relational link between input and output is not observable. For these reasons, it is necessary to make serious efforts on the explanability and interpretability of black box models. In the near future, the integration of explainable artificial intelligence and meta-learning approaches to cyber-physical systems will have effects on a high level of virtualization and simulation infrastructure, real-time supply chain, cyber factories with smart machines communicating over the internet, maximizing production efficiency, analysis of service quality and competition level.
Malicious URL Detection Using Machine Learning
Authors: Catak Ferhat Ozgur , Sahinbas Kevser , Dörtkardeş Volkan
Published: November 2020

Recently, with the increase in Internet usage, cybersecurity has been a significant challenge for computer systems. Different malicious URLs emit different malicious software and try to capture user information. Signature-based approaches have often been used to detect such websites and detected malicious URLs have been attempted to restrict access by using various security components. This chapter proposes using host-based and lexical features of the associated URLs to better improve the performance of classifiers for detecting malicious web sites. Random forest models and gradient boosting classifier are applied to create a URL classifier using URL string attributes as features. The highest accuracy was achieved by random forest as 98.6%. The results show that being able to identify malicious websites based on URL alone and classify them as spam URLs without relying on page content will result in significant resource savings as well as safe browsing experience for the user.
Urban Green Innovation
Authors: Vargas-Hernández José G.
Published: November 2020

This chapter has the objective to analyze the elements of urban green innovation based on the guarantee the public interest, decentralize the infrastructure to democratize the territory, and innovating the institutional design to address the complexity of the challenges in the city. The method employed is the critical analysis supported by a review of the literature and consult to experts in the field. It is concluded that the urban green innovation capacity planning has a critical role in urban innovation development in specific areas of economic growth, social inclusion and equality, environmental sustainability, health, education, business, etc. To achieve these aims, urban green innovation requires to guarantee the public interest, the democratization of the territory, and the new institutional design.
African Cities Cultural Heritage, Urban Fragmentation, and Territorial Spatial Development
Authors: Laotan-Brown Tokie
Published: November 2020

The contemporary African city tends to become a geographic platform for establishing and showing a territorial spatial–social identity. This shows that global openness and accessibility may run parallel to closed and fragmented cultural clusters. Urban scholarship calls for a broader orientation in the field of cultural heritage dynamics, with a focus on the following: citizenship and identity, economic creative activities and innovation, the impact of popular culture, and the interface between traditional societal perspectives and open attitudes regarding contemporary interwoven cultures. Against this background, African cities have always been meeting places for people of different cultures, education, and talents. The contemporary African city is an open milieu, where ideas from a diversity of cultures and nations come together. The major challenge for a modern African city will be to turn possible tensions in such a intercultural milieu into positive synergetic energy.
Literary Tourism
Authors: Falcone Paola
Published: November 2020

The chapter intends to provide an overview on literary tourism valorization. The first part identifies its main benefits, main literary places (book locations, book film adaptation sets, places related to writers, literary attractions), and literary events (festivals, book fairs, and other events). The second part presents some issues on the demand side and provides the description of two possible literary journeys, with different connections with both literary places and products. The third part of the chapter is focused on how to effectively valorize literary tourism, through the design of valuable experiences.
Portugality as Heritage and Touristic Resource in New Jersey (United States of America)
Authors: Diogo Helder
Published: November 2020

Due to its dimension, cultural matrix, and its roots in the diverse regions worldwide, Lusitanian communities may enhance dynamics of tourism development in such globalization. Indeed, Portugality is present in the distinct ethnic neighborhoods of strong concentration of the Lusitanian population the North American territory as it in the state of New Jersey, where approximately 72,000 Portuguese people of live (data from 2012). This community presents in the local landscape a concentration of architectural, economic, and cultural elements. Such landscape elements may be explored and valued by local community and also by all the tourism stakeholders of both sides of Atlantic for the development of a particular type of tourism such as ethnocultural. Defining touristic resource, as well as special and identity singularities, the present work aims to demonstrate how diaspora may have an ultimate role in the arrival and development of touristic products for both lusophones and lusophiles communities.
Contemporary Architecture of the Periphery
Authors: Llano Fabian Andrés , Pérez Oscar Mauricio , Barón Pulido Mireya
Published: November 2020

This chapter analyzes of two types of social and cultural development in the context of peripheral regions. The projects analyze a library, Biblioteca España (2007-2015), and a cultural center, La Casa de La Lluvia (2013-present). The library was designed by El Equipo Mazzanti, a design firm, as part of the social urbanism policy framework that characterized the city of Medellin between 2004 to 2007. The cultural center was built by Arquitectura Expandida, a design collective that has been in operation since 2010 and whose headquarters is located in the city of Bogota. This analysis is unique in how it applies a sociological analysis to two architectural projects. It also seeks to demonstrate how two cultural models of habitat development that seem to be incompatible, in regard to their design and implementation, share a common goal: attain the social wellbeing of the communities living in peripheral regions.
Genius Loci and Cultural Heritage
Authors: Torsi Silvia , Ardito Carmelo , Rebek Cristina
Published: November 2020

One of the main challenges of cultural heritage is to enhance the visit to ancient ruins, in which what remains is difficult to interpret. For this reason, the authors designed an alternate reality game by making use of tangible devices to improve the experience of wandering around the ruins of Egnatia (Fasano, Brindisi, Italy). They tried to evoke the “Genius Loci,” the sacral spirit of a territory, that is analysed according to its dimensions in the field of human-computer interaction. Those dimensions are enchantment, ambiguity, bodily experience, topology of the place, the dialogue between the past and the present, and the perceptual gestalt.
A Robust and Efficient MCDM-Based Framework for Cloud Service Selection Using Modified TOPSIS
Authors: Tiwari Rohit Kumar , Kumar Rakesh
Published: November 2020

Cloud computing has become a business model and organizations like Google, Amazon, etc. are investing huge capital on it. The availability of many organizations in the cloud has posed a challenge for cloud users to choose a best cloud service. To assist the cloud users, we have proposed a MCDM-based cloud service selection framework to choose a best service provider based on QoS requirement. The cloud service selection methods based on TOPSIS suffers from rank reversal problem as it ranks optimal service provider to non-optimal on addition or removal of a service provider and deludes the cloud user. Therefore, a robust and efficient TOPSIS (RE-TOPSIS)-based novel framework has been proposed to rank the cloud service providers using QoS provided by them and cloud user's priority for each QoS. The proposed framework is robust to rank reversal problem and its effectiveness has been demonstrated through a case study performed on a real dataset. Sensitivity analysis has also been performed to show the robustness against the rank reversal phenomenon.
Gaussian Distribution-Based Machine Learning Scheme for Anomaly Detection in Healthcare Sensor Cloud
Authors: Dwivedi Rajendra Kumar , Kumar Rakesh , Buyya Rajkumar
Published: November 2020

Smart information systems are based on sensors that generate a huge amount of data. This data can be stored in cloud for further processing and efficient utilization. Anomalous data might be present within the sensor data due to various reasons (e.g., malicious activities by intruders, low quality sensors, and node deployment in harsh environments). Anomaly detection is crucial in some applications such as healthcare monitoring systems, forest fire information systems, and other internet of things (IoT) systems. This paper proposes a Gaussian distribution-based supervised machine learning scheme of anomaly detection (GDA) for healthcare monitoring sensor cloud, which is an integration of various body sensors of different patients and cloud. This work is implemented in Python. Use of Gaussian statistical model in the proposed scheme improves precision, throughput, and efficiency. GDA provides 98% efficiency with 3% and 4% improvements as compared to the other supervised learning-based anomaly detection schemes (e.g., support vector machine [SVM] and self-organizing map [SOM], respectively).
Rummage of Machine Learning Algorithms in Cancer Diagnosis
Authors: Johri Prashant , Saxena Vivek sen , Kumar Avneesh
Published: November 2020

With the continuous improvement of digital imaging technology and rapid increase in the use of digital medical records in last decade, artificial intelligence has provided various techniques to analyze these data. Machine learning, a subset of artificial intelligence techniques, provides the ability to learn from past and present and to predict the future on the basis of data. Various AI-enabled support systems are designed by using machine learning algorithms in order to optimize and computerize the process of clinical decision making and to bring about a massive archetype change in the healthcare sector such as timely identification, revealing and treatment of disease, as well as outcome prediction. Machine learning algorithms are implemented in the healthcare sector and helped in diagnosis of critical illness such as cancer, neurology, cardiac, and kidney disease as well as with easing in anticipation of disease progression. By applying and executing machine learning algorithms over healthcare data, one can evaluate, analyze, and generate the results that can be used not only to advance the prior health studies but also to aid in forecasting a patient's chances of developing of various diseases. The aim in this article is to present an overview of machine learning and to cover various algorithms of machine learning and their present implementation in the healthcare sector.
fMRI Feature Extraction Model for ADHD Classification Using Convolutional Neural Network
Authors: De Silva Senuri , Dayarathna Sanuwani Udara , Ariyarathne Gangani , Meedeniya Dulani , Jayarathna Sampath
Published: November 2020

Biomedical intelligence provides a predictive mechanism for the automatic diagnosis of diseases and disorders. With the advancements of computational biology, neuroimaging techniques have been used extensively in clinical data analysis. Attention deficit hyperactivity disorder (ADHD) is a psychiatric disorder, with the symptomology of inattention, impulsivity, and hyperactivity, in which early diagnosis is crucial to prevent unwelcome outcomes. This study addresses ADHD identification using functional magnetic resonance imaging (fMRI) data for the resting state brain by evaluating multiple feature extraction methods. The features of seed-based correlation (SBC), fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo) are comparatively applied to obtain the specificity and sensitivity. This helps to determine the best features for ADHD classification using convolutional neural networks (CNN). The methodology using fALFF and ReHo resulted in an accuracy of 67%, while SBC gained an accuracy between 84% and 86% and sensitivity between 65% and 75%.
An Ensemble Deep Neural Network Model for Onion-Routed Traffic Detection to Boost Cloud Security
Authors: Tiwari Shamik
Published: November 2020

Anonymous network communication using onion routing networks such as Tor are used to guard the privacy of sender by encrypting all messages in the overlapped network. These days most of the onion routed communications are not only used for decent cause but also cyber offenders are ill-using onion routings for scanning the ports, hacking, exfiltration of theft data, and other types of online frauds. These cyber-crime attempts are very vulnerable for cloud security. Deep learning is highly effective machine learning method for prediction and classification. Ensembling multiple models is an influential approach to increase the efficiency of learning models. In this work, an ensemble deep learning-based classification model is proposed to detect communication through Tor and non-Tor network. Three different deep learning models are combined to achieve the ensemble model. The proposed model is also compared with other machine learning models. Classification results shows the superiority of the proposed model than other models.
An Automated Self-Healing Cloud Computing Framework for Resource Scheduling
Authors: Dewangan Bhupesh Kumar , Venkatadri M.  , Agarwal Amit , Pasricha Ashutosh , Choudhury Tanupriya
Published: November 2020

In cloud computing, applications, administrations, and assets have a place with various associations with various goals. Elements in the cloud are self-sufficient and self-adjusting. In such a collaborative environment, the scheduling decision on available resources is a challenge given the decentralized nature of the environment. Fault tolerance is an utmost challenge in the task scheduling of available resources. In this paper, self-healing fault tolerance techniques have been introducing to detect the faulty resources and measured the best resource value through CPU, RAM, and bandwidth utilization of each resource. Through the self-healing method, less than threshold values have been considering as a faulty resource and separate from the resource pool. The workloads submitted by the user have been assigned to the available best resource. The proposed method has been simulated in cloudsim and compared the multi-objective performance metrics with existing methods, and it is observed that the proposed method performs utmost.
Quantitative Analysis of the Impact of Inter-Line Conveyor Capacity for Throughput of Manufacturing Systems
Authors: Dhurpate Priyanka Raosaheb , Tang Herman
Published: November 2020

The objective of this study is to identify the impact of an inter-line conveyor on the throughput performance of manufacturing systems and determine the capacity of an inter-line conveyor to improvise productivity. First, manufacturing system for an automotive assembly line is modeled by adopting the methodology of two lines with an inter-line conveyor system. A quantitative analysis of an inter-line conveyor capacity is carried out under different conditions and capacities using discrete event simulation (DES). The initial results are obtained to justify the purpose of an inter-line conveyor followed by introducing a random failure of a station for the duration of 10 minutes, 30 minutes, and catastrophic breakdown of two hours at upstream and downstream line separately. The case study outcomes show that, 20 unit is an optimum capacity resulting in improved productivity. The findings of the different stoppage and catastrophic breakdown study show the buffering of an inter-line conveyor may serve as a new approach and guideline to the buffer stack design and scheduling maintenance.
Evaluation and Repair of Cracks on Statically Loaded Beams Using Piezoelectric Actuation
Authors: Roy Goutam , Panigrahi Brajesh Kumar , Pohit Goutam
Published: November 2020

In the present work, damage produced by a crack in a statically loaded beam is first evaluated. Subsequently, an attempt is made to repair the effect of the crack by attaching a piezoelectric patch to the beam as an actuator. Static analysis of PZT patched cracked beam along with rotational spring is performed using Ritz method. Subsequently, a finite element analysis is performed by using ABAQUS 6.12 to collate the analytical results. It is shown in the study that when PZT patch is subjected to external electric field, it yields a local reactive moment, which counters the crack effects. An equation is procured in order to compute the required actuation voltage for repairing of cracks. A parametric study is performed for various boundary conditions and loading patterns. It is distinctly noticed that the technique nullifies the discontinuity in slope curve which develops due to a crack.
Irregular Ecologies
Authors: Ollong Kingsly Awang
Published: November 2020

Cameroon, since 2016, has been witnessing what is now commonly referred to as the Anglophone Crisis (or the Ambazonia War) that has kept economic and social activities in the Anglophone Regions of Cameroon at bay with serious socio-economic implications on the local communities and the economic tissue of the regions. This paper explores the socio-economic challenges faced by the North West and South West Regions of Cameroon through the provision of a comprehensive analysis of the trends and economic implications of Anglophone Crisis. Moreover, the nature of conflicts has changed, with traditional civil wars giving way to non-state-based conflicts, including the targeting of civilians through terrorist attacks. The paper recommends that Cameroon, with the help of her partners, should focus on limiting the loss of human and physical capital by protecting social and development spending.
NetPlus
Authors: Kneppers Ben Robert , Laruccia Moacyr Bartholomeu
Published: November 2020

Once seen as a miracle material, petroleum-based plastics are now arguably one of the largest sources of pollution on the planet. With 80% of land-based litter ending up in our oceans, ocean plastic is now reported to be on track to outweigh fish by 2050. Conservationists have been able to identify the most harmful form of ocean plastic pollution for marine mammals, turtles, and seabirds worldwide to be discarded fishing gear. Bureo, a company operating between Chile and California in partnership with sustainable outdoor retailer Patagonia, is addressing this issue by transforming this harmful material into high-value products. Through their shared-value business model and life cycle thinking, they have built a network of partnering fishing communities across the coast of Chile committed to return their fishing nets at their end of life in exchange for compensation towards community programs. Through their innovative supply chain and the living product challenge framework, Bureo is setting out to achieve the first plastic with a net positive impact on the environment and people.