bluuebunny/crossref_metadata_2025 huggingface dataset:
Generation and Enrichment of Pedestrian Maps with Vertical Shadows in Urban Environments from Mobile Laser Scanning Data
Authors: Balado Frias Jesus , Díaz-Vilariño Lucía , Frías Ernesto , González Elena
Published: January 2021

Cities are becoming more pedestrian-friendly, reducing traffic and promoting physical activity and walking. However, prolonged exposure to the sun can cause sunburn and skin problems, so minimizing exposure to the sun while travelling is especially relevant at certain latitudes and in the summer months. This paper proposes a method for modelling urban contours and generating pedestrian maps with the location of shaded areas and accessibility barriers. The proposed method uses as input data a point cloud of an urban environment acquired with Mobile Laser Scanning. First, the input point cloud is segmented in ground points, obstacle points, and points causing shadows. Then, the three segmented point clouds are rasterized and the corresponded images are combined to obtain the navigable ground and the shaded areas. Finally, from the navigable ground, a navigation map is generated for pedestrians. To check the usefulness of this navigation map, a pathfinding algorithm is applied. The results show a correct generation of the navigable ground, and routes prioritizing the trajectory by shadow areas. Depending on the weighting between sun and shaded areas, the routes obtained show differences in distance travelled and sun exposure. The proposed method is sensitive to the existence of obstacles and noise in the point clouds.
Internet-Based Text-Matching Software and EFL Preservice Teachers' Awareness of Academic Integrity
Authors: Kaçar Işıl Günseli , Işık-Güler Hale
Published: January 2021

Having been investigated from different perspectives across a broad range of disciplines, plagiarism in English as a Second Language (ESL)/English as a Foreign Language (EFL) contexts has not received much attention until very recently. This mixed-methods case study in the Turkish context is a critical analysis of EFL preservice teachers' perceptions, motives, knowledge of, and practices regarding plagiarism, as well as their academic integrity awareness and plagiarism detection ability in a freshman academic writing course at a state university. The quantitative data from the pre- and post-test questionnaires in the study were analyzed through descriptive statistics while the qualitative data from the questionnaires and semi-structured interviews with the preservice teachers were analyzed via thematic analysis. Findings suggested the favorable impact of Turnitin on preservice teachers' self-discovery to overcome and reduce possible plagiarism attempts in the Turkish context.
MCDM-Based Optimization of Performance Characteristics During µEDMing of SS 304
Authors: Mukhopadhyay Premangshu , Bose Goutam Kumar , Pain Pritam
Published: January 2021

Micro-EDM is most widely used for developing perfect drilled micro features/parts. Research was carried out to improve the material removal and tool wear of any conductive machined product by EDM and micro-EDM process. In this chapter, RSM was used for designing the experiments with 20 set of experiments. In this present research work, performance characteristics like MRR and Overcut have got a different level of importance. Here the stress was given on MRR rather than on OC. In this MCDM analysis, the weight of MRR is considered to be maximum (i.e., larger is better), and other weights of other responses are considered to be the minimum (i.e., smaller is better). Finally, in the midst of all the combinations of process parameters considered one that acquires the highest grey relational grade is the best parametric combination. The research findings in the area of machining of stainless steel 304 will be helpful to manufacturing engineers for selecting the optimized parametric combinations of micro-EDM process with stainless steel.
Multi-Objective Optimization in WEDM of Al 7075 Alloy Using TOPSIS and GRA Method
Authors: Mandal K. , Sarkar S. , Mitra S. , Bose Dipankar
Published: January 2021

In this research study, Taguchi grey relational analysis (GRA) has been coupled with the technique for order of preference by similarity to ideal solution (TOPSIS) to optimize the multi-performance characteristics in WEDM of Al 7075 alloy. The influence of process factors such as pulse duration (Ton), pulse interval (Toff), flushing pressure (Fp), and servo voltage (Sv) on output responses machining speed (Vc) and corner inaccuracy (Ce) have been considered. The analysis of variance (ANOVA) for the grey relational grade (GRG) and order of preference value generated by TOPSIS have been carried out to justify the optimal results. The recommended input factor settings are found to be Ton = 1.1 µs, Toff = 20 µs, Fp = 9 kg/cm2, and Sv = 20 volt from TOPSIS, and from GRA is Ton = 1.1 µs, Toff = 10 µs, Fp = 12 kg/cm2, and Sv = 40 volt. Finally, surface roughness and surface topography evaluation have been carried out in-depth understanding of influencing factors.
Finite Element-Based Optimization of Additive Manufacturing Process Using Statistical Modelling and League of Champion Algorithm
Authors: Sood Anoop Kumar
Published: January 2021

The study develops a 2D (two-dimensional) finite element model with a Gaussian heat source to simulate powder bed-based laser additive manufacturing process of Ti6Al4V alloy. The modelling approach provides insight into the process by correlating laser power and scan speed with melt pool temperature distribution and size. To tackle the FEA result in optimization environment, statistical approach of data normalization and regression modelling is adopted. Statistical treatment is not only able to deduce the interdependence of various objectives consider but also make the representation of objectives and constraint computationally simple. Adoption of a new stochastic algorithm namely league of a champion algorithm (LCA) together with penalty function approach for non-linear constraint handling reduces the effort required and computational complexity involved in determining the optimum parameter setting.
Synthesis and Characterization of Nanocomposites for the Application in Hybrid Solar Cell
Authors: Tyagi Sakshi , Singh Pawan Kumar , Tiwari Arun Kumar
Published: January 2021

In today's era, a lot of interest is gained by solar cell formed by combination of organic and inorganic nano-particle semiconductors mainly because of its major features such as scalable solar power conversion and cost effectiveness, which makes the cell a desirable photovoltaic device. This piece of work is an attempt to make a solar cells by the combination of zinc oxide (ZnO) and graphite. ZnO is a good n-type material for the application in photovoltaic (PV) devices due to its better optical, electrical, structural, and environmentally friendly properties, and on the other hand, graphite, an organic semiconductor, enhances the rate of charge transfer in the device. These materials are so designed to help bring in more understanding in a wider range of the solar spectrum. This work focuses on developing solid-state polymer and hybrid solar cells.
A Ranking Framework for Higher Education Institutions
Authors: Calitz Andre Paul , Cullen Margaret Diane , Kanyutu Teresia Watiri
Published: January 2021

The use of league tables and rankings (LTRs) as a tool to rank or measure the performance of higher education institutions (HEIs) has grown in popularity. Research indicates that these ranking criteria are often discussed from the standpoint of governments, the HEI management, and the ranking institutions producing these LTR publications. The opinions of the students on the suitable ranking criteria used by ranking institutions are generally omitted. This chapter investigates the applicable criteria for ranking HEIs in South Africa, from the perspective of students. A survey was conducted to determine the most relevant university ranking criteria considered by university students. The results indicate that the students perceive resources and infrastructure, accreditation, international orientation, research output, faculty quality, and teaching and learning as the most relevant criteria for ranking HEIs. Managerial recommendations are provided for HEIs to address the ranking criteria rated important by students.
Efficiency Assessment of University-Industry Collaboration
Authors: Yüksel Haliloğlu Ebru
Published: January 2021

Today, in addition to teaching and research roles, universities are one of major drivers of economic development and technological progress in society. To propagate technological innovation and industrial development, to implement output of academic research in practice universities should be in close cooperation with industry. University-industry collaborations have various benefits both for universities and industry. Universities gain additional funds for academic research, apply academic knowledge to industry; industry benefits from skilled human resources, new applications, and technological advances. Since university-industry collaborations have great mutual benefits for all partners, it is important to administer these operations effectively. Therefore, it is central to develop some efficiency indicators and efficiency measurement methods so that productive projects can be selected and funded more. This study aims to outline a framework on determinants of university-industry collaboration efficiency and construct a benchmark model to evaluate it using data envelopment analysis.
Collaboration Between Industries and Higher Education Institutions
Authors: Singh Chandrani , Nair Archana N.
Published: January 2021

In a year, nearly two million students pass out form higher educational institutes in India, of which the number of directly employable students is much less. There is a colossal vacuum created between industry and institutes with fourth industrial revolution picking up pace in India. HEIs need to cope with the digital skillsets required of their students. In this chapter, the authors have put together different strategies that can help fill these gaps. Many institutes have led from the front by implemented path braking methods that are giving the expected outcome. Practices that are followed and one that should be followed by institutions have been discussed. A view of how government, non-government, industrial, and educational entities in India work together to bring about Education 4.0 is explored.
A Synergized Education 4.0 Ecosystem Sustainably Aligned With Industry 4.0
Authors: Mehar Singh Manjet Kaur
Published: January 2021

Education is about creating sustainable innovations for future learning. This tagline emphasizes the role of education policymakers and educators to ensure successful learning for digital natives and neo digital natives as the education landscape is currently challenged by the great disruptors. Knowledge, as capital and technological innovations, has empowered the industry. As such, Industry 4.0 has created a vacuum in the education landscape today at education prepares to handle and embrace Industry 4.0. Therefore, this chapter discusses the role of education sector globally and selectively in some Asian countries such as Malaysia, Thailand, Myanmar, Singapore, etc. in improving its delivery in terms of being an Education 4.0 standard and equipping the global workforce citizens of the future to work in parallel with intelligent systems and robots.
Disease Interactome
Authors: Dawn Suma , Jain Nidhi , Gangwar Tulika
Published: January 2021

The disease interactome is a network of genes that are related to each other through some attributes. These genes, being part of various diseases, show a high correlation among many diseases. Genes being a major part of the interactome thus can be used to determine the relationship between various diseases, their symptoms, clinical similarity, and co-morbidity. Subgraphs and similarity factors such as Jaccardian distance, cosine similarities, and others have been exploited to calculate the relationship between two or more diseases. Many diseases that did not show much resemblance on the basis of gene similarity or symptom similarity were seen to be closely related according to network interactome. The quantitative analysis between disease-disease was also done. Clustering algorithms like hierarchical clustering involving single, complete, and average linkage were applied to get a visual representation in the form of a dendrogram. Thus, disease-disease interactome was created, analyzed for finding related secondary diseases, and their basic nature was understood.
In Vitro and in Vivo Models for Pathogenic Neisseria gonorrhoeae Infections
Authors: Ramalingam Karthikeyan , Ganesh Sucharithra
Published: January 2021

The prevalence of gonorrhea has not discontinued in several countries and still remains as one of the top sexually transmitted diseases (STD) and it's caused by Neisseria gonorrhoeae. This bacterium gains entry into the human host via receptors, and by the usage of several virulence factors, it manages to spread through the cells and leads to severe complications. The study of these bacteria in various in vitro and in vivo models have paved the way for gaining insights on various aspects of bacterial infection, such as the study of pathogenesis of the organism in the host. It also drove the development of more appropriate drugs for the treatment of the gonorrhea illness caused by this ‘superbug'. This chapter focuses on providing a concise overview on the general aspects of N. gonorrhoeaeas an update and the in vitro and in vivo models used for understanding this bacterium over the years. Despite gonorrhea not being a rare STD, it is still a big challenge for researchers, healthcare professionals, and communicators with public awareness to communicate effectively with the general community.
Enhanced Algorithm to Optimize QoS and Security Parameters in Ad hoc Networks
Authors: Sharma Tripti , Tabassum Mujahid
Published: January 2021

In ad hoc networks, it is essential and desirable that running applications offer appropriate QoS. However, it becomes a challenge, especially in wireless sensor networks. This chapter concentrates on integrating the security aspect with those of disconnection because of the excessive utilization of a particular node. It is seen that in ad-hoc networks that it is possible to enhance the network lifetime significantly by incorporating the battery properties in the routing protocol. So that will increase the network performance while routing protocol integrates the security with battery to support the simulation results. These results show that adaptive DSR protocol maintains useful network lifetime in addition to improved performance. The chapter attempts to improve the overall QoS of the MANET. It is well known that QoS provisioning is an intricate and challenging issue in mobile ad hoc networks, especially when there are multiple QoS constraints.
Macro and Micro Architectures for Network on Chip
Authors: Suresh P.
Published: January 2021

Network on chip (NoC) paradigm replaces traditional, dedicated, and proprietary bus architectures of system on chip (SoC), and it is widely accepted by the system-level designers. In this chapter, an overview of the NoC design is presented in two different dimensions called macro-architectures and micro-architectures based on the design perspectives. Macro-architectures adopt the concept of computer network along with new innovations in topologies, protocols, and routing algorithms and so on whereas micro-architectures involve in the development of schedulers, arbiters, routers, and network adapter with existing or new concepts. From the comparison result, most of the NoC prototypes are developed with 2-D mesh architecture with packed switched concept. Apart from mesh architectures, some of the complex and hybrid concepts are also developed and discussed in this chapter.
A Node Authentication Model in Wireless Sensor Networks With Locked Cluster Generation
Authors: Bharathi C. R. , Naresh Alapati , Peda Gopi Arepalli , Vejendla Lakshman Narayana
Published: January 2021

In wireless sensor networks (WSN), the majority of the inquiries are issued at the base station. WSN applications frequently require collaboration among countless sensor nodes in a network. One precedent is to persistently screen a region and report occasions. A sensor node in a WSN is initially allocated with an energy level, and based on the tasks of that sensor node, energy will be reduced. In this chapter, two proposed methods for secure network cluster formation and authentication are discussed. When a network is established then all the nodes in it must register with cluster head and then authentication is performed. The selection of cluster head is done using a novel selection algorithm and for authenticating the nodes. Also, a novel algorithm for authentication is used in this chapter. The validation and authorization of nodes are carried over by managing the keys in WSN. The results have been analyzed using NS2 simulator with an aid of list of relevant parameters.
Data Security and Privacy Requirements in Edge Computing
Authors: P. Chinnasamy , D. Rojaramani , V. Praveena , S. V. Annlin Jeba , B. Bensujin
Published: January 2021

Several researchers analyzed the information security problems in edge computing, though not all studied the criteria for security and confidentiality in detail. This chapter intends to extensively evaluate the edge computing protection and confidentiality standards and the different technical approaches utilized by the technologies often used mitigate the risks. This study describes the latest research and emphasizes the following: (1) the definition of edge computing protection and confidentiality criteria, (2) state-of-the-art strategies used to mitigate protection and privacy risks, (3) developments in technical approaches, (4) measures used to measure the efficiency of interventions, (5) the categorization of threats on the edge device and the related technical pattern used to mitigate the attackers, and (6) research directions for potential professionals in the field of edge devices privacy and security.
The Intellectual Soul Food Lunch Buffet
Authors: Robinson W. Russell
Published: January 2021

This chapter explores the intersections of media entrepreneurship and pedagogy, vis-à-vis a student-driven curriculum. The author uses an exploratory case study methodology to obtain first-hand accounts from students, instructors, and technical professionals to share experiences from within the academic enterprise. This chapter shares from the ground up how a class created and improved upon a student-driven media platform which was rooted in a pop culture studies curriculum. It is the hope that lessons gleaned from this chapter will inspire best practices within the communication/media studies space while at the same time promote future collaborations among historically minority-serving institutional (HMSI) scholars within the curriculum sphere of project-based learning.
No More War Stories
Authors: Harris Hamil R.
Published: January 2021

At a time when the field of journalism has radically changed, news veterans have opportunities to enter classrooms to marry traditional journalism and history with multi-platform technology and social media. But to be successful, journalist educators must retool themselves and work with a new generation of students who hold up members of the fourth estate, the press, and news media with high regard. Despite challenges, news veterans still have the potential to impact this new generation of journalists because so many college students simply don't know the role and purpose of journalists.
Missing Value Imputation Using ANN Optimized by Genetic Algorithm
Authors: Mishra Anjana , Naik Bighnaraj , Srichandan Suresh Kumar
Published: January 2021

Missing value arises in almost all serious statistical analyses and creates numerous problems in processing data in databases. In real world applications, information may be missing due to instrumental errors, optional fields and non-response to some questions in surveys, data entry errors, etc. Most of the data mining techniques need analysis of complete data without any missing information and this induces researchers to develop efficient methods to handle them. It is one of the most important areas where research is being carried out for a long time in various domains. The objective of this article is to handle missing data, using an evolutionary (genetic) algorithm including some relatively simple methodologies that can often yield reasonable results. The proposed method uses genetic algorithm and multi-layer perceptron (MLP) for accurately predicting missing data with higher accuracy.
Environmental Adaption Method
Authors: Chandila Anuj , Tiwari Shailesh , Mishra K. K. , Punhani Akash
Published: January 2021

This article describes how optimization is a process of finding out the best solutions among all available solutions for a problem. Many randomized algorithms have been designed to identify optimal solutions in optimization problems. Among these algorithms evolutionary programming, evolutionary strategy, genetic algorithm, particle swarm optimization and genetic programming are widely accepted for the optimization problems. Although a number of randomized algorithms are available in literature for solving optimization problems yet their design objectives are same. Each algorithm has been designed to meet certain goals like minimizing total number of fitness evaluations to capture nearly optimal solutions, to capture diverse optimal solutions in multimodal solutions when needed and also to avoid the local optimal solution in multi modal problems. This article discusses a novel optimization algorithm named as Environmental Adaption Method (EAM) foable 3r solving the optimization problems. EAM is designed to reduce the overall processing time for retrieving optimal solution of the problem, to improve the quality of solutions and particularly to avoid being trapped in local optima. The results of the proposed algorithm are compared with the latest version of existing algorithms such as particle swarm optimization (PSO-TVAC), and differential evolution (SADE) on benchmark functions and the proposed algorithm proves its effectiveness over the existing algorithms in all the taken cases.
Optimal Designs by Means of Genetic Algorithms
Authors: Nautiyal Lata , Shivach Preeti , Ram Mangey
Published: January 2021

With the advancement in contemporary computational and modeling skills, engineering design completely depends upon on variety of computer modeling and simulation tools to hasten the design cycles and decrease the overall budget. The most difficult design problem will include various design parameters along with the tables. Finding out the design space and ultimate solutions to those problems are still biggest challenges for the area of complex systems. This chapter is all about suggesting the use of Genetic Algorithms to enhance maximum engineering design problems. The chapter recommended that Genetic Algorithms are highly useful to increase the High-Performance Areas for Engineering Design. This chapter is established to use Genetic Algorithms to large number of design areas and delivered a comprehensive conversation on the use, scope and its applications in mechanical engineering.
T-Spanner Problem
Authors: Moharam Riham , Morsy Ehab , Ismail Ismail A.
Published: January 2021

The t-spanner problem is a popular combinatorial optimization problem and has different applications in communication networks and distributed systems. This chapter considers the problem of constructing a t-spanner subgraph H in a given undirected edge-weighted graph G in the sense that the distance between every pair of vertices in H is at most t times the shortest distance between the two vertices in G. The value of t, called the stretch factor, quantifies the quality of the distance approximation of the corresponding t-spanner subgraph. This chapter studies two variations of the problem, the Minimum t-Spanner Subgraph (MtSS) and the Minimum Maximum Stretch Spanning Tree(MMST). Given a value for the stretch factor t, the MtSS problem asks to find the t-spanner subgraph of the minimum total weight in G. The MMST problem looks for a tree T in G that minimizes the maximum distance between all pairs of vertices in V (i.e., minimizing the stretch factor of the constructed tree). It is easy to conclude from the literatures that the above problems are NP-hard. This chapter presents genetic algorithms that returns a high quality solution for those two problems.
Genetic-Fuzzy Programming Based Linkage Rule Miner (GFPLR-Miner) for Entity Linking in Semantic Web
Authors: Singh Amit , Sharan Aditi
Published: January 2021

This article describes how semantic web data sources follow linked data principles to facilitate efficient information retrieval and knowledge sharing. These data sources may provide complementary, overlapping or contradicting information. In order to integrate these data sources, the authors perform entity linking. Entity linking is an important task of identifying and linking entities across data sources that refer to the same real-world entities. In this work, they have proposed a genetic fuzzy approach to learn linkage rules for entity linking. This method is domain independent, automatic and scalable. Their approach uses fuzzy logic to adapt mutation and crossover rates of genetic programming to ensure guided convergence. The authors' experimental evaluation demonstrates that our approach is competitive and make significant improvements over state of the art methods.
Implement Multichannel Fractional Sample Rate Convertor using Genetic Algorithm
Authors: Jain Vivek , Agrawal Navneet
Published: January 2021

In this paper reduce power of multichannel fractional sample rate convertor by minimized hamming distance between consecutive coefficients of filter using Genetic algorithm. The main component of multichannel fractional sample rate convertor is Cascaded multiple architecture finite impulse response filter (CMFIR filter). CMFIR is implemented by cascading of cascaded integrator-comb (CIC) & multiply accumulate architecture (MAC) FIR filter. Genetic algorithm minimizes the hamming distance between consecutive coefficients of CMFIR filter. By Minimizing the hamming distance of consecutive filter coefficient reduces the transaction from 0 to 1 or 1 to 0. These techniques reduce the switching activity of CMOS transistor which is directly reduces Dynamic power consumption by multichannel sample rate convertor, it also minimizes the total power consumption of multichannel fractional sample rate convertor. later than use genetic algorithm on 1 to 128 channel Down sample rate convertor total power reduced by 3.44% to 61.56%, dynamic power reduced by 9.09% to 56.25% .1 to 128 channel Up sample rate convertor total power reduced by 2.81% to 45.42%, dynamic power reduced by 4.76% to 56%, 1 to 128 channel fractional sample rate convertor total power reduced by 1.44% to 17.17%, dynamic power reduced by 6.25% to 19.92%.
Exploration of Fuzzy System With Applications
Authors: Mewada Shivlal , Sharma Pradeep , Gautam S. S.
Published: January 2021

Fuzzy system was altered from a ‘buzz word' to an important technological area, with various publications in international conferences and transactions. Several Japanese products applying fuzzy logic concepts, such as household appliances and electronic equipment, power engineering, robotics, and optimization have been manufactured. This system is capable to process and learn mathematical data as well as linguistic data. Fuzzy system user linguistic explanations for the variables and linguistic procedures for the I/P-O/P behavior. In this chapter, present the application of fuzzy system with data mining, neural networks, fuzzy automata, and genetic algorithms. It also presents the foundation of fuzzy data Mining, with the fuzzification inference procedure and defuzzification procedure, fuzzy systems and neural networks with feed forward neural network, FNN with it features generalization of Fuzzy Automata, and sixth fuzzy systems and genetic algorithms. The chapter explores a popular fuzzy system model to show complex systems and an application of fuzzy system.
Optimization Techniques Applications in Biochemical Engineering and Controlled Drug Delivery
Authors: Jujjavarapu Satya Eswari , Singh Bikesh Kumar
Published: January 2021

Before starting semi-pilot/pilot production plants for biochemical metabolites production, it is essential to optimize the fermentation media. This chapter discusses the classical and advanced techniques of media optimization. The statistical approaches save experimental time for developing processing and improving quality. Recent years have seen the growth of integrated approaches of microbial cultures. Optimization techniques such as response surface methodology, artificial neural network, genetic algorithms, differential evolution, ant colony optimization, etc. have received attention recently because of their major applications in various fields. Controlled release formulations have so many versatile applications in the field of pharmaceutical drugs that they have become important tools to apply the modern concept of therapeutic treatment. Process optimization of such formulations, mathematical modelling can play an important role. This chapter discusses various methodologies for optimization of formulation conditions for drug delivery.
Web Page Recommender System using hybrid of Genetic Algorithm and Trust for Personalized Web Search
Authors: Chawla Suruchi
Published: January 2021

The main challenge to effective information retrieval is to optimize the page ranking in order to retrieve relevant documents for user queries. In this article, a method is proposed which uses hybrid of genetic algorithms (GA) and trust for generating the optimal ranking of trusted clicked URLs for web page recommendations. The trusted web pages are selected based on clustered query sessions for GA based optimal ranking in order to retrieve more relevant documents up in ranking and improves the precision of search results. Thus, the optimal ranking of trusted clicked URLs recommends relevant documents to web users for their search goal and satisfy the information need of the user effectively. The experiment was conducted on a data set captured in three domains, academics, entertainment and sports, to evaluate the performance of GA based optimal ranking (with/without trust) and search results confirms the improvement of precision of search results.
Delay Optimization Using Genetic Algorithm at the Road Intersection
Authors: Sharma Bharti , Kumar Sachin
Published: January 2021

Metropolitan road traffic mechanisms in developing countries are a critical problem due to fast motorization. The optimization of traffic control is one method to decrease this problem. In this study, a genetic algorithm was implemented to minimize delay at an intersection by finding red and green cycle intervals at an intersection. The objective function minimizes the delay at an intersection and increases progressive flows of traffic on roads. The study was done on real data collected from three t- intersections in the city of Hardwar, India. Traffic data for traffic flows, queue sizes, and traffic speed are collected using video detection systems in the study area. The digital images from the camera were analyzed in real time. The results show that the traffic control performance is improved up to 85% over existing algorithms proposed by the same author.
The Genetic Algorithm
Authors: Mercangöz Burcu Adıguzel , Eroglu Ergun
Published: January 2021

The portfolio optimization is an important research field of the financial sciences. In portfolio optimization problems, it is aimed to create portfolios by giving the best return at a certain risk level from the asset pool or by selecting assets that give the lowest risk at a certain level of return. The diversity of the portfolio gives opportunity to increase the return by minimizing the risk. As a powerful alternative to the mathematical models, heuristics is used widely to solve the portfolio optimization problems. The genetic algorithm (GA) is a technique that is inspired by the biological evolution. While this book considers the heuristics methods for the portfolio optimization problems, this chapter will give the implementing steps of the GA clearly and apply this method to a portfolio optimization problem in a basic example.
An Efficient Batch Scheduling Model for Hospital Sterilization Services Using Genetic Algorithm
Authors: Xu Shubin , Wang John
Published: January 2021

A major challenge faced by hospitals is to provide efficient medical services. The problem studied in this article is motivated by the hospital sterilization services where the washing step generally constitutes a bottleneck in the sterilization services. Therefore, an efficient scheduling of the washing operations to reduce flow time and work-in-process inventories is of great concern to management. In the washing step, different sets of reusable medical devices may be washed together as long as the washer capacity is not exceeded. Thus, the washing step is modeled as a batch scheduling problem where washers have nonidentical capacities and reusable medical device sets have different sizes and different ready times. The objective is to minimize the sum of completion times for washing operations. The problem is first formulated as a nonlinear integer programming model. Given that this problem is NP-hard, a genetic algorithm is then proposed to heuristically solve the problem. Computational experiments show that the proposed algorithm is capable of consistently obtaining high-quality solutions in short computation times.
Implementing Genetic Algorithms to Assist Oil and Gas Pipeline Integrity Assessment and Intelligent Risk Optimization
Authors: Calzada-Orihuela Gustavo , Urquiza-Beltrán Gustavo , Ascencio Jorge A , Reyes-Salgado Gerardo
Published: January 2021

Oil and gas industry, worldwide, needs to monitor, control and assess the elements that are involved in the general oil transportation and production processes. However, these processes are not risk free. The project proposes an intelligent support system that provides optimized projections for effective risk management. The project focuses on the development of a set of Genetic Algorithms (GAs), a branch of AI systems that assists to optimize the usage and distribution of resources. GAs will reduce the latent risks and potential dangers as much as possible. The main purpose is to minimize the risk levels in a pipeline segment based on their condition and by detecting optimal variable configurations: their Risk of Failure (RoF), Probability of Failure (PoF), Consequence of Failure (CoF), and their sub elements (threats and impacts). The heuristic results generated by this set of GAs show a significant reduction on the risk assessment measures, by finding “optimized” configurations of these variables.
Solving Flow Shop Scheduling Problems with Blocking by using Genetic Algorithm
Authors: Kumar Harendra , Kumar Pankaj , Sharma Manisha
Published: January 2021

Flow shop scheduling problems have been analyzed worldwide due to their various applications in industry. In this article, a new genetic algorithm (NGA) is developed to obtain the optimum schedule for the minimization of total completion time of n-jobs in an m-machine flow shop operating without buffers. The working process of the present algorithm is very efficient to implement and effective to find the best results. To implement the proposed algorithm more effectively, similar job order crossover operators and inversion mutation operators have been used. Numerous examples are illustrated to explain proposed approach. Finally, the computational results indicate that present NGA performs much superior to the heuristics for blocking flow shop developed in the literature.
Use SUMO Simulator for the Determination of Light Times in Order to Reduce Pollution
Authors: Born Míriam Blank , Adamatti Diana Francisca , Sanchotene de Aguiar Marilton , Schiavon de Souza Weslen
Published: January 2021

Nowadays, urban mobility and air quality issues are prominent, due to the heavy traffic of vehicles and the emission of pollutants dissipated in the atmosphere. In the literature, a model of optimal control of traffic lights using Genetic Algorithms (GA) has been proposed. These algorithms have been introduced in the context of control traffic. In order to search for possible solutions to the problems of traffic lights in major urban centers. Thus, the study of the dispersion of pollutants and Genetic Algorithms with simulations performed in Urban Mobility Simulator SUMO (Simulation of Urban Mobility), seek satisfactory solutions to such problems. The AG uses the crossing of chromosomes, in this case the times of the traffic lights, featuring the finest green light times and the sum of each of the pollutants each simulation cycle. The simulations were performed and the results compared analyzes showed that the use of the genetic algorithm is very promising in this context.
Genetic-Algorithm-Based Performance Optimization for Non-Linear MIMO System
Authors: Xavier Anitha Mary
Published: January 2021

Environmental regulations demand efficient and eco-friendly ways of power generation. Coal continues to play a vital role in power generation because of its availability in abundance. Power generation using coal leads to local pollution problems. Hence this conflicting situation demands a new technology - Integrated Gasification Combined Cycle (IGCC). Gasifier is one of the subsystems in IGCC. It is a multivariable system with four inputs and four outputs with higher degree of cross coupling between the input and output variables. ALSTOM – a multinational and Original Equipment Manufacturer (OEM) - developed a detailed nonlinear mathematical model, validated made this model available to the academic community and demanded different control strategies which will satisfy certain stringent performance criteria during specified disturbances. These demands of ALSTOM are well known as “ALSTOM Benchmark Challenges”. The chapter is addressed to solve Alstom Benchmark Challenges using Proportional-Integral-Derivative-Filter (PIDF) controllers optimised by Genetic Algorithm.
A Controlled Stability Genetic Algorithm With the New BLF2G Guillotine Placement Heuristic for the Orthogonal Cutting-Stock Problem
Authors: Abou-Msabah Slimane , Baba-Ali Ahmed-Riadh , Sager Basma
Published: January 2021

The orthogonal cutting-stock problem tries to place a given set of items in a minimum number of identically sized bins. Combining the new BLF2G heuristic with an advanced genetic algorithm can help solve this problem with the guillotine constraint. According to the item order, the BLF2G heuristic creates a direct placement of items in bins to give a cutting format. The genetic algorithm exploits the search space to find the supposed optimal item order. Other methods try to guide the evolutionary process. A new enhancement guides the evolutionary process, enriching the population via qualified individuals, without disturbing the genetic phase. The evolution of the GA process is controlled, and when no improvements after some number of iterations are observed, a qualified individual is injected to the population to avoid premature convergence to a local optimum. A generated set of order-based individuals enriches the evolutionary process with qualified chromosomes. The proposed method is compared with other heuristics and metaheuristics found in the literature on existing data sets.
A Hybrid Tabu Genetic Metaheuristic for Selection of Security Controls
Authors: Ramkumar Sarala , Godandapani Zayaraz , Vivekanandan Vijayalakshmi
Published: January 2021

In the modern world, globalization has made way for easy access to information systems for running businesses effectively. The misuse of information systems may lead to loss of productivity, revenue, and sometimes to legal liabilities. Therefore, information security is a major concern for running the business successfully. It is the responsibility of the information security personnel of an organization to develop strategies, and identify the suitable controls to mitigate the risks to which the organization is exposed to. Selection of a suitable set of security controls depends upon, the risks to be addressed, the impact of the risks in terms of revenue, and the cost incurred in implementing the selected controls. To assist in the selection of optimal security controls a hybrid intelligent approach combining the tabu search technique and genetic algorithm has been proposed. The obtained results prove that the proposed approach provides better results in the selection of optimal counter measures.
The Immediate Effects of Tai Chi via a Video Platform Delivery on the Postural Stability of Healthy Young Adults
Authors: Cordingley Zachary A. M. , Sanzo Paolo , Zerpa Carlos
Published: January 2021

Tai chi is effective for improving the postural stability of older adults, but the effects on healthy young adults has yet to be investigated. Currently, the use of virtual delivery platforms for various exercise prescriptions to patients has had to be quickly introduced related to the onset of the COVID-19 pandemic and physical distancing requirements. This study attempted to explore the pre-/post-test measures of postural stability from 15 healthy young adult participants under eyes open (EO) and eyes closed (EC) and firm/foam surface conditions after learning a battery of tai chi exercises and forms delivered by instructional video. Center of pressure-based measures of mean sway velocity (MSV) and 95% elliptical sway area (EA) were assessed. Three-way ANOVAs were conducted to determine if MSV and EA were significantly different across the eye conditions, surface conditions, and time. Both EA and MSV were found to significantly increase from EO to EC on a foam surface; however, only MSV under EC conditions was found to decrease significantly following the intervention.
Implementation of IoT-Based Generator Management System Using GPy
Authors: Verma Deepak Sheshbadan , Pai Sumit Satish , Vishwakarma Krishna Nagendra
Published: January 2021

In the era of digital devices, many industries still use traditional methods of pen and paper to maintain records. One such industry is the diesel generator industry where these generators are operated without any proper supervision. The current management of these generator vans is highly unorganized. This causes a lot of miscommunication between the owners and the customers. The idea focuses on monitoring the different parameters of a diesel generator using internet-connected sensors. Parameters such as fuel consumption, AC power ON time, RPM of the turbine, and temperature are measured in real time. The system helps the owners to monitor their generators vans through one mobile application rather than depending on the on-site operators. Both the owners and customers can see how much power was consumed and how their bill was generated. Rather than using pen and paper to maintain records in the current method, the new system completely transforms the old methods into a highly digitalized modern business.
ICT Uptake as a Determinant of Antenatal Care Utilization in Uganda
Authors: Namatovu Hasifah Kasujja , Oyana Tonny J.
Published: January 2021

Few studies have investigated information and communication technologies (ICTs) as determinants of ANC utilization, yet ICTs in health can improve patient outcome, tackle health systems challenges, and improve client-to-provider relationship. A cross-sectional design using both quantitative and qualitative data collection approaches was used to ascertain whether ICT uptake can determine ANC utilization. Women aged 18-50 years who were pregnant had given birth two years preceding the survey and who had at least a primary school education participated in this study. Data was analyzed using Pearson's Chi-square and descriptive discriminant analysis. Results from this study suggest an association between ICT uptake and ANC utilization (χ2 = 19.3, ρ <0.001) and a statistically significant relationship between the discriminant function and the grouping variable at p=.012 (Wilks's ᴧ = .822; χ2 = 28.62 (14df), p<0.05, valid n = 164). Control measures and interventions should be geared towards integrating ICTs in women's routine antenatal care practices.
A Collective and Comparative Study of Various Routing Protocols and the Threats in MANET
Authors: Ramadass Parthasarathy , Sankar Manjula , Shanmugapriyan J.
Published: January 2021

A collection of mobile nodes deployed with a temporary intention is called mobile ad hoc network (MANET). Every deployed node has the capable of connecting the network communication, and every node has the capable of configuring network communication. There are many routing procedures to discover the proper route from source to destination. The routing protocol helps to channelize the route from one point to other for establishment of the communication. This paper discusses the detailed and the elaborated study of the MANET security issues and the various routing protocols. Moreover, it describes about the OSI model with the relationship of security systems. The elaborated and the detailed approach of the various protocol helps to build a progressive idea of the MANET security. Various issues and the overcomes help to find the loopholes of the threats, and it clearly explains the analysis of the MANET efficiency. The simulation analysis helps to know the comparison analysis of various protocols.
Super Lightweight Mobile RFID Authentication Protocol for Bit Replacement Operation
Authors: Hou Yubao , Liang Hua , Liu Juan
Published: January 2021

In the traditional RFID system, the secure wired channel communication is used between the reader and the server, and the new mobile RFID system is different from the traditional RFID system. The reader and the server communicate based on the wireless channel. This makes authentication protocols applicable to traditional RFID systems not applicable to mobile RFID systems. To solve this defect, a two-way authentication protocol MSB is proposed for ultra-lightweight mobile radio frequency identification system based on bit replacement operation. MSB (most significant bit) encrypts information based on bitwise operations, and the amount of computation of the communication entity is reduced. Tags, readers, and servers first authenticate and then communicate. MSB can be resistant to common attacks. The security analysis of the protocol shows that the protocol has high security attributes, and the performance analysis of the protocol shows that the protocol has the characteristics of low calculation volume. The formal analysis of the protocol is given based on GNY logic.
A Vision-Based Framework for Spotting and Segmentation of Gesture-Based Assamese Characters Written in the Air
Authors: Choudhury Ananya , Sarma Kandarpa Kumar
Published: January 2021

The task of automatic gesture spotting and segmentation is challenging for determining the meaningful gesture patterns from continuous gesture-based character sequences. This paper proposes a vision-based automatic method that handles hand gesture spotting and segmentation of gestural characters embedded in a continuous character stream simultaneously, by employing a hybrid geometrical and statistical feature set. This framework shall form an important constituent of gesture-based character recognition (GBCR) systems, which has gained tremendous demand lately as assistive aids for overcoming the restraints faced by people with physical impairments. The performance of the proposed system is validated by taking into account the vowels and numerals of Assamese vocabulary. Another attribute to this proposed system is the implementation of an effective hand segmentation module, which enables it to tackle complex background settings.