Dr. Giovanni Bucci
Department of Industrial Engineering and Information and economy University of L’Aquila Italy.

ISBN 978-93-91312-84-8 (Print)
ISBN 978-93-91312-89-3 (eBook)
DOI: 10.9734/bpi/naer/v3

This book covers key areas of engineering research. The contributions by the authors include  high-resolution image, deep learning, Convolutional neural network (CNN), Feature extraction, image classification, Local binary pattern, graphene, graphite, carbon, bidimensional, biofuel, energy crops, annual, perennial, miscanthus, cardoon, switchgrass, SWOT analysis, hyperbolic paraboloid free roof, porosity, wind tunnel experiment, main wind force resisting system, wind force coefficient, codification, parameter design, load analysis, accelerated life testing, architecture, urbanism, digital games, cyberculture, constraint based routing, delay, localized routing, blocking probability, widest shortest path, underwater non-equilibrium electric discharge, plasma-chemical synthesis of a sorbent, plasma module, cesium and strontium radionuclides, disactivation of water and soil, hydroseparation, plasma treatment, solar plant monitoring, texas Instrument, internet of things, amazon web services, amazon IOT Core, Amazon S3 Bucket, amazon Kinesis, wireless communication, augmented reality, optical flow, hidden Markov model, and neural network processing and active appearance model, kinematics of robots, single link robotic arm, link flexibility, assumed modes method  and payload effect. This book contains various materials suitable for students, researchers and academicians in the field of engineering research.


Media Promotion:


It is very important to accurately classify high-resolution satellite images and to classify each section of the image separately. Complex patterns, on the other hand, are difficult to identify. The deep learning method is used to deal with this challenge. The goal of the deep learning method is to extract a large number of features without the need for human intervention. Nonetheless, integrating deep features with texture characteristics improves classification performance. Deep feature learning mixed with texture-based classification is made easier with the suggested system. Local Binary Pattern (LBP) is used to extract textural features, whereas Convolutional Neural Network is used to extract deep features (CNN). The main objectives of the proposed system are: (1) To efficiently combine deep features with texture features. (2) To increase the classification accuracy. (3) To classify the land cover/land map area of the remote sensing image correctly. The suggested method is implemented, and the results are checked to ensure its efficacy. When texture features are incorporated with a deep learning approach, experimental results demonstrate that classification performance has improved.

An Overview of Graphene Based Application

Giuliana Vinci, Marco Ruggeri

New Approaches in Engineering Research Vol. 3, 21 June 2021, Page 7-15

Graphene, a two-dimensional material with the thickness of an atom, has some surprising properties (hyperdensity, intrinsic mobility millions of times greater than silicon, high thermal and electrical conductivity, large surface area, is nearly 200 times stronger than steel, harder than diamond, and is extremely flexible and elastic) that have resulted in a profound change in the field of material science. and which make it an ideal candidate for a variety of applications. In this regard, the objective of this study is to present an overview of the main areas in which Graphene could be applied, as well as to have a brief discussion on its main methods of synthesis.

SWOT Analysis of Perennial vs Annual Energy Crops: A Case Study in Greece

Annoula Paschalidou, Michael Tsatiris

New Approaches in Engineering Research Vol. 3, 21 June 2021, Page 16-48

The EU bio-based economy needs sustainable biomass supply for multiple uses: pharmaceuticals, food, feed, bio-based materials and bioenergy. The yielding potential of the energy crops (annual and perennial) has to be as efficient as possible in order to minimize the competition for land. For the last two decades several perennial and annual energy crops have been cultivated for biofuel production at a European level. The main advantage of the annual energy crops is that agronomic management can be easily adapted from more traditional cultivation practices since they can easily fit in current (rotation) farming systems. On the other hand, perennial energy crops are being specifically developed for biomass production.

This paper aims to discuss the most socio-economical and environmentally suited crops for biofuel production in Greece and the Mediterranean area, by comparing some annual and perennial energy crops, through the SWOT Analysis. Our study focuses a) on three perennial energy crops: Miscanthus (Miscanthus giganteus), Cardoon (Cynara cardunculus), and Switchgrass (Panicum virgatum) and b) on four annual energy crops: Sunflower (Helianthus spp.), Kenaf (Hibiscus cannabinus L.), Rapeseed (Brassica napus), Sorghum (Sorghum bicolor).

The SWOT results show that the three perennial energy crops under study are an excellent alternative choice for marginal lands, especially since there is no need for annual installation. They have high biomass yields with generally low crop costs (cardoon, switchgrass) and a wide array of end uses. They are particularly beneficial to the environment because they have low chemical requirements (cardoon), high energy content and can be used for soil remediation (miscanthus) and phytoextraction of harmful or polluting substances. However, some have a high initial installation cost, (miscanthus, switchgrass) and some are potentially invasive species (miscanthus, cardoon) while almost all mature crops are particularly flammable.

On the other hand the four annual energy crops are some popular and well accepted plants (sunflower, rapeseed) as well some not so widespread ones (kenaf, sorghum as an energy crop). They can be included in the existing rotation farming schemes and most of them can be cultivated with techniques which are already familiar to farmers, similar to the winter cereals (rapeseed). They present an environmentally friendly alternative crop choice, in lands with poor or moderate water availability (sunflower, kenaf), with high yields and a multitude of possible uses, suitable both for small farmers’ cooperatives as well as large scale farming.

Choosing the ideal energy crop, annual or perennial, will depend on multiple factors, both socio-economic and environmental.

Study of Wind Loads on Porous Hyperbolic Paraboloid Free Roofs

Yasushi Uematsu

New Approaches in Engineering Research Vol. 3, 21 June 2021, Page 49-67

The objective of the present study is to propose wind force coefficients for designing the main wind force resisting systems of porous hyperbolic paraboloid (HP) free roofs with square plan based on a wind tunnel experiment, in which solid and porous models are used. The thickness of the models is only 1 mm. The porous model has a number of small circular holes. The porosity is changed from 0 (solid) to 0.4. The geometric parameters under consideration are the rise-to-span (or sag-to-span) ratio and the slope. A six-component force balance in a turbulent boundary layer is used to determine the overall aerodynamic forces and moments operating on a model. Based on a combination of the lift and aerodynamic moment coefficients, the design wind force coefficients, CNW* and CNL*, for the windward and leeward halves of the roof are proposed for diagonal wind directions. Focus is on the axial forces induced in the columns as the load effect for discussing the design wind loads, assuming that the roof is rigid and simply supported by four corner columns. It is found that the porosity reduces the wind loads on the roof significantly. The design wind force coefficients for a porous roof can be obtained by those for a solid roof with the same configuration multiplied by a reduction factor. The proposed wind force coefficients are validated by comparing the load effect predicted by the proposed wind force coefficients with the maximum load effect obtained from a dynamic analysis using the time history of lift and aerodynamic moment coefficients obtained from the wind tunnel experiment.

Study on Reliability Design of the Hinge Kit System Subjected to Repetitive Loading in a Commercial Refrigerator

Seongwoo Woo, Dennis L. O’Neal, Demise Molawork

New Approaches in Engineering Research Vol. 3, 21 June 2021, Page 68-81

This chapter develops parametric accelerated life testing (ALT) as a systematic reliability method to produce the reliability quantitative (RQ) specifications—mission cycle—for recognizing missing design defects in mechanical products such as hinge kit system (HKS) in a commercial refrigerator. It includes: (1) A parametric ALT plan formed on the system BX lifetime, (2) a fatigue failure and design, (3) customized ALTs with design alternatives, and (4) an assessment of whether the last design(s) of the system fulfills the objective BX lifetime. A BX life concept, a generalized life-stress model, and a sample size equation are suggested. Failure sites in the HKS were identified through returned products from the field. After lifetime of the new HKS was targeted to be B1 10 years, the first ALT confirmed a failure that occurred at the housing of HKS. The missing design parameters of HKS housing for the refrigerator were that it had no support ribs in the original design. The supporting structure of HKS in the refrigerator was modified based on the action plan. Cracks were identified in a second ALT that was generated in the torsional shaft. Due to it having squared off corners, the HKS torsional shaft did not have not enough strength to withstand repetitive stresses. The shaft was modified as a consequence of the ALTs. The lifetime of the redesigned HKS is now guaranteed as B1 10 years. The design methods - load analysis and three ALTs were very effective in identifying the missing design parameters during the design phase. The robust design method presented in this paper might be applicable to the other mechanical systems.

Architectural and Urban Dynamics in Video Games: From Playful to Collective Intelligence

Frederico Braida, Mariana Zancaneli, Antonio Colchete Filho, Mariane Unanue

New Approaches in Engineering Research Vol. 3, 21 June 2021, Page 82-89

This paper aims to demonstrate that video games, especially those played within a network, interconnected through the Internet, can contribute to the constitution of collective intelligence about a city's spatialities and urban ways of life. Thus, the article establishes a map of relations between Video Game Design, Architecture and Urbanism, from four categories of analysis, presenting games as tools for building collective intelligence, especially after the massification of the use of computers, the Internet, smartphones and locative media.

Study on Link Based Routing Algorithm for the Desired Quality of Service of a Network

R. Bhargava Rama Gowd, T. Someshwari, S. Thenappan, M. N. Giri Prasad

New Approaches in Engineering Research Vol. 3, 21 June 2021, Page 90-102

Routing algorithms play an important rolein the network performance calculation where Quality of service matters there are two types of routing algorithms:  Local and Global Routing. Local routing allows for more effective decision-making than global routing [1].  This methodology significantly reduces the overheads associated with maintaining global state data at each hub, thereby improving routing performance. We provide a Restricted QoS steering computation in this paper that takes the Probability of Blocking Link (LBP).We compare the performance of the algorithm w.r.t. 1) Delay between source and destination 2) Nodes 3)Consumed Energy 4)Alive Hubs 5) Dead Hubs 6) Dynamic Hubs 7) Rest Hubs 8) Routing Overhead 9) Packets Conveyed against the Constraint Based Routing(CBR) and Widest Shortest Path(WSP).

Study on Plasma-Stimulated Remediation of Radioactively Contaminated Soil

Petrov Stanislav V., Zabulonov Yuriy L., Masato Homma

New Approaches in Engineering Research Vol. 3, 21 June 2021, Page 103-115

The article is devoted to the problem of rehabilitation of soils and waste waters contaminated with Cs134, Cs137and Sr90 radionuclides. To extract radionuclides from aqueous solutions, we used the method of precipitation of cesium and strontium by selective sorbents of transition metal ferrocyanides with their plasma activation. Sorbents of this type are obtained by precipitation of ferrocyanides of the corresponding metal in the presence of finely dispersed calcium and strontium carbides synthesized in the plasma treatment zone. Such finely dispersed sorbents have an increased selectivity and extraction rate (more than 100 times). This is a consequence of the fact that the coprecipitation of micro amounts of cesium and strontium coincides with the synthesis and activation of the sorbent in the chemically active zone of the plasma discharge.  In addition, the concomitant oxidation of organic substances eliminates their negative effect on sorbents. A pilot plant was developed and tested using a nonequilibrium electric discharge in a flowing aqueous solution with plasma-chemical synthesis of a sorbent to reduce the amount or remove radioactive materials from soils and wastewater contaminated as a result of the accident at the Fukushima Daiichi nuclear power plant. It is shown that this method of plasma-chemical synthesis and activation of the sorbent makes it possible to effectively purify wastewater with different composition and concentration of radionuclides in the presence of surfactants and organic pollutants, as well as soil with a combination of hydroseparation.

Wi-Fi Based Solar Plant Monitoring System

T. J. Jeyaprabha, G. Sumathi, D. Sneha, C. Reshma, K. S. Sai Nykhil

New Approaches in Engineering Research Vol. 3, 21 June 2021, Page 116-133

Nowadays, renewable energy systems are becoming the best way to generate electricity. Generally, the solar plants are in decentralized nature, hence it is difficult to monitor them. This paper presents a cost effective prototype for real time monitoring of the solar plant which collects the values of current, voltage and power from the sensors using Wi-Fi. The proposed system consists of two main components- the first part is the hardware interface modules where the end module receives the data through RS232 interface from string combiner. Then, it is enabled to scan, discover and connect through AP to the main module. The second part is the web server, which represents the core system that manages controls and monitor’s solar plant.

Studies on Magic Mirror Using Augmented Reality: Review

Ruchira Kurve Dabhade

New Approaches in Engineering Research Vol. 3, 21 June 2021, Page 134-141

A magic mirror paradigm is an augmented reality (AR) system where a camera and display device act as a mirror where one can see a reflection of oneself and virtual objects together. The proposed system has a camera to capture the viewer’s facial expression. By analyzing the expressions, the system is able to determine the emotion of the viewer. If the viewer is in a negative emotion, the system then speaks positive sentences and plays the viewer’s favourite music to alleviate his/her emotion. The proposed system can serve as a calendar for event reminding. Hardware like USB Web Cam (8 MP or higher) & Computer System are used for this project. There are three modes in this system that is mirror mode, alleviation mode, silent mode, reminder mode.

Objective of this project is to recognize the mood of a person & to give them support as a digital  friend. This project gives a reliable friend that will motivate you, keeps you always happy. Social signals reveal individual emotions toward of a person by facial expressions, vocal intonations and outbursts, body gestures and postures, etc. However, we only focus the research scope in the facial expression (Sad, angry, happy, surprise) for the purpose of simplifying the problem.

Facial expression is achieved through various methods such as optical flow, hidden Markov model, and neural network processing and active appearance model. For example, the Face Reader recognizes facial expressions by distinguishing six basic emotions (happy, angry, sad, surprised, scared, disgusted), plus neutral. Positive word inspiration, alleviating negative emotions, and affairs reminding is done through optical flow, hidden Markov model, neural network processing and active appearance model.

Study on the Effect of Link Flexibility on Tip Position of a Single Link Robotic Arm

E. Madhusudan Raju, L. Siva Rama Krishna, Y. Sharath Chandra Mouli, V. Nageswara Rao

New Approaches in Engineering Research Vol. 3, 21 June 2021, Page 142-151

In comparison to traditional industrial rigid link robots, flexible robots are frequently employed in space applications owing to their rapid reaction, reduced energy consumption, smaller total mass, and high-speed operation. These robots are inherently flexible, so that the kinematics of flexible robots cannot be solved with rigid body assumptions. The flexibility in links and joints affects end-point positioning accuracy of the robot. It is important to model the link kinematics with precision which in turn simplifies modelling of dynamics of flexible robots. The major goal of this article is to see how link extensibility affects the tip location of a single link robotic arm for a certain motion. The joint is assumed to be rigid and only link flexibility is considered. The kinematics of flexible link problem is evaluated by Assumed Modes Method (AMM) using MATLAB Programming. To evaluate the effect of link flexibility (with and without payload) of robotic arm, the normalized tip deviation is found for flexible link with respect to a rigid link. Finally, the limiting inertia for payload mass is found if the allowable tip deviation is 5%.