Mathematical, Computational Intelligence and Engineering Approaches for Tourism, Agriculture and Healthcare

Frontmatter

Spectrum of Intelligent Tourist Destination Image Decision Information System

Abstract

The destination image of tourist places is an essential component that influences the thinking phenomenon of tourists regarding the selection of tourist places. The process of selection of tourist places among the various tourist destination is a vague and imprecise one, therefore, the decision-making process becomes more complex as it is influenced by many aspects such as brand awareness, brand attitude, adventure, romantic, spirituality, tourist loyalty, perceived quality, and destination image criteria as a significant component. The present article is focused on the design and development of an intelligent tourist destination image decision information system, and the system reflects the influence of criteria of selection of tourist destination based on destination image features. The system has an added advantage to redesign the tourist destination selection plan as per destination image criteria.

Pankaj Srivastava, Saurabh Srivastav, Yannakorn Toprayoon

Extensions of Some Known Differential and Integral Operators

Abstract

In this paper, the operator \(L^{m}:A\rightarrow A\) is introduced by \(L^{m}[f](z)=(1-\lambda )R^{m}[f](z)+\lambda I^{m}[f](z)\), \(z\in U\), a differential–integral operator where \(R^{m}\) is Ruscheweyh differential operator and \(I^{m}\) is Alexander integral operator. By using the operator \(L^{m}\) the class denoted by \(M^{m}(\lambda ,\beta )\), \(0\le \lambda \le 1\) , \(0\le \beta <1\) is defined. Using the operator \(L^{m}\), several differential subordinations are studied and from this study we obtain a condition for univalence of functions from class A.

Georgia Irina Oros

Two-Stage Neural Network-Structural Equation Modeling Approach to Studying Drivers for Hotel Objectives: With Implications

Abstract

This study demonstrates the practical, combined usage of neural network-structural equation modeling (SEM) data analysis methods, using hotel dataset, to validate the significant mediating role of organizational learning situated in between performance measurements, external network relationship, and operations management. A valid 151 dataset involves the perceptions and attitudes of the employees and management in hotels located in Aceh, Indonesia. Neural network provides a pre-run to statistical tests in suggesting the relationship structure between any hierarchies or layers of a theoretical model, and thus, it has proven to function as an inductive operator in the context of big data management to suggest a preliminary theoretical structure. The researchers and practitioners can then make use of the simulated structure for rigorous statistical tests. All the variables were subjected to validity and reliability assessments prior to neural network simulation and SEM assessments.

Chai Ching Tan, M. S. Julian

Computation of Ideals in N-Topology

Abstract

We would like to discuss the functioning of ideals in N-topological space and also apply various topological properties to ideal N-topology. While trying to achieve this purpose, we study the resultant notion of weak and strong forms of local functions and a computer programme along with its algorithm is derived to establish their relationship with one another.

M. Lellis Thivagar, V. Antonysamy, V. Ramesh

Arithmetic Functions, Convolution and Finite Fourier Series

Abstract

A convolution involving a summation over the greatest common divisor of two integers, which extends the classical Dirichlet convolution, is investigated, and basic properties are derived. Applying these results to a periodic function yields a Fourier series expansion, referred to as its finite Fourier series. Specializing a periodic function, a Fourier series of the greatest common divisor (gcd) function is obtained. Several recent results and applications related to the Fourier series of the gcd function are derived.

Vichian Laohakosol

Problem on Coefficients of Bi-Univalent Function Class Using Chebyshev Polynomials

Abstract

In the present paper, first, we introduced two new subclasses. Subsequently, initial coefficient estimations \(|a_{2}|\) and \(|a_{3}|\) are established by using Chebyshev polynomials expansions for these subclasses. Additionally, Fekete–Szegö inequality \(|a_{3}-\eta a_{2}^{2}|\) is derived for functions belonging to the first subclass. Further, we discuss the relevant consequences of these subclasses.

F. Müge Sakar, Ertuğrul Doğan

Transcendental Numbers Arising from Mahler’s Method

Abstract

By a 1937 method of K. Mahler, it is proved using the Thue–Siegel–Roth theorem that the decimal expansion 0.13579 11 13 15 17 19 21 23 25 27⋯ is a transcendental number but is not a Liouville number.

Saeree Wananiyakul, Vichian Laohakosol, Janyarak Tongsomporn

Intelligent System for ECG Beat Classification

Abstract

In the present paper, we propose a soft computing diagnostic intelligent system that classifies ECG beats in different phases and enables us to identify the status of cardiac health normalities and abnormalities as per available ECG graphs. In order to design and develop an intelligent computing system, we have used some important parts of ECGs as fuzzy input variables for our diagnostic system, i.e. hexaxial system and R–R interval from different concerned patients’ ECG graph, which are useful to detect cardiac health status. Then, with the consultation of medical experts, we have developed a fuzzy rule base system with the input variables, which, in turn, are helpful in developing utility matrix. Using these fuzzy input variables and utility matrix, the diagnostic system detects various cardiac statuse of the concerned patient, which has been verified with the help of cardiac experts. The intelligent system will be very helpful to society.

Pankaj Srivastava, Neeraja Sharma

Efficient Algorithm in IoT for Drip Irrigation System

Abstract

It is an important domain in IoT to provide support to farmers. The objective of this paper is to utilize water resources in an efficient manner. The field type and weather at the field are different from crop to crop. In this scenario, we need to observe the types of crop, soil, region and weather conditions to decide the water requirement for crops. For effective water utilization, the drip irrigation method is efficient in water distribution. With the existing water resource, water requirements in the field can meet the available number of drip points. In order to avoid the wastage of water, we propose an algorithm for efficient utilization of water and check any wastage/leakage of it in the field. It helps the farmer for efficient and optimal utilization of water resources in any field.

S. Raji Reddy, M. V. Ramana Murthy

Computational Techniques on Totally Continuous Functions Via Čech Rough and Nano Soft Topological Spaces

Abstract

The aim of this paper is to introduce and study the concepts of totally continuous functions in Čech rough and nano soft topology with computing techniques. We establish the binary relation of the approximation space into a soft relation with the computational model and algorithm for nano soft topology. Furthermore, we discuss their properties and other results using the concepts of Čech rough closure and nano soft topology.

M. Lellis Thivagar, B. Tamilarasan, G. Kabin Antony

Error Estimates Using Higher Modulus of Smoothness in Lp Spaces

Abstract

The error estimate in terms of higher modulus of smoothness is obtained for hybrid-type operators obtained by combining the weight of Szasz and Baskakov operators. It is observed that by taking linear combination of our hybrid operators, the rate of convergence has been improved.

Anshul Srivastava, ShilpiBisht

Space-Time Admitting -Curvature Tensor

Abstract

In this paper, we have studied space-time with \(W_6\)-curvature tensor and proved that a four-dimensional relativistic space-time M has conservative \(W_{6}\)-curvature tensor if and only if the energy-momentum tensor is Codazzi tensor provided that the scalar curvature is constant in both the cases. It is also observed that in a four-dimensional relativistic \(W_{6}\)-flat space-time satisfying Einstein’s field equation with cosmological constant, the energy-momentum tensor is covariant constant.

S. P. Maurya, S. K. Pandey, R. N. Singh

General Characterization of at Most Twin Outer Perfect Domination Number with Colouring of Graphs

Abstract

Recently, the concept At most twin outer perfect domination number of a graph was introduced by Mahadevan et.al in (Int J Pure Appl Math 117(13):109–116, 2017). A set \(S \subseteq V\left( G \right)\) in a graph G is said to be an at most twin outer perfect dominating set in G, if for every vertex \(v \in V - S\),\(1 \le \left| {N\left( V \right) \cap S} \right| \le 2 and\left\langle {V - S} \right\rangle\) and has at least one perfect matching. The minimum cardinality of at most twin outer perfect dominating sets is called the At most twin outer perfect domination number and is denoted by \(\gamma_{atop} \left( G \right).\) In this paper, we characterize all graphs, for colouring, with At most Twin outer perfect domination number 2n-5 and 2n-6 for n ≥ 4.

G. Mahadevan

Computing Modelling of Quotient Supra Spaces

Abstract

Computing models are widely used in computer database management systems. The hierarchical network model delivers relational database systems to avoid bottlenecks and to enable network flexibility by its network model framework that is perfectly suited to the designers. This chapter introduces the new concept of quotient supra topology and studies its properties. Using this quotient supra topology we often construct a quotient supra space in terms of quotient set and originate the new notion of vivid supra topology, also proving its existence and uniqueness theorem. Moreover, we establish the universal property of vivid supra topology. Finally, we establish a new approach to the representation of concept hierarchy based on quotient supra space.

M. Sathyabama, A. Gracy

Design and Development of Intelligent Information System Using Hesitant Fuzzy Weighting Linguistic Term Sets for Computing with Words

Abstract

Impreciseness in information sharing is the most complicated and challenging issue and it has been observed that experts’ hesitation in sharing their opinion for rating a state of the system affects the results. Decision-makers are mostly in dilemma state about the weighting criterion of Linguistic terms and their scaling. The weighting criterion needs clarification that on what basses’ linguistic terms are being scaled by decision-makers to conclude the decision. The emergence of Hesitant Fuzzy Weighting Linguistic Term Set (HFLWTS) provides a new platform for decision-makers to conclude their decisions with proper scaling of linguistic terms and weighting criteria. The present paper deals with the design and development of an intelligent information system that runs on the knowledge base of the HFLWTS for computing with words with reference to decision-making phenomena.

Pankaj Srivastava, Rajkrishna Mondal

Totally -Continuous Maps in

Abstract

In this current paper, we introduced several generalized forms of continuous maps such as totally \({\upxi }_{\Im } \)-continuous maps, totally \({\upxi }^{*}_{\Im } \)-continuous, totally \({\upxi }^{*}_{\Im } \)-semi-continuous maps and totally \({\upxi }^{*}_{\Im } \)-pre-continuous maps in an Ideal generalized binary topological spaces \(\left( {{\text{I}}{\kern 1pt}\upxi _{{\text{T}}} {\text{S}}} \right)\) and investigated various relationships of these maps by making use of some examples.

Nazir Ahmad Ahengar, Jitendra Kumar Maitra, Roshani Sharma, Sujeet Chaturvedi, Mudasir Ahmad

Application of Soft Set Theory for Dimensionality Reduction Approach in Machine Learning

Abstract

Dimensionality reduction is the most popular technique, which is used in data analytics for the optimal solution over high-dimensional data. Many times some inconsistency and uncertainty are presented in huge data so to deal with such a type of data soft set theory is being developed. Soft set theory handles the difficulties of older theories like fuzzy set, rough set using new property that is parameterization reduction. This paper presents different soft set based NPR algorithms for information systems that give optimal solutions for big data. The goal of this article is to focus on the dimensionality reduction approach of data mining using soft set theory which can be applied to machine learning field. Thus normal dimensionality reduction of soft set (NDRSS) algorithm is proposed for real-time data to give a better optimal solution than existing soft set algorithms. The result shows that how-high dimensional data is to be reduced using soft set theory in machine learning.

P. D. Lanjewar, B. F. Momin

QoS Evaluation for Wireless Networks Using K-Nearest Neighbor (k-NN) Algorithm

Abstract

This research paper aims to assess and predict the Quality of Service (QoS) of wireless networks based on K- Nearest Neighbor (k-NN) Algorithm. QoS for the wireless network is mainly dependent on the parameters like packet loss, latency and jitter. In this paper, we have implemented classification of QoS and also ensured the accuracy of our results using regression analysis.

Siddharth Goutam, Srija Unnikrishnan

On the Generalized Fractional Calculus Operators Involving the H-Function of Several Variables

Abstract

In this paper, we introduced two fractional calculus operators involving the H-function of several variables of Srivastava and Panda (Srivastava and Panda in J. Reine Angew. Math. 288:129–145, 1976). The operators developed here also contain the Erdélyi–Kober operators of fractional calculus. Similar formulas for the one-dimensional H-function are already obtained by Saigo, Saxena and Ram (Saigo et al. in Ganita Sandesh 6:36–47, 1992), and are implied by our results. The fractional calculus operators studied here are quite general in nature, and therefore, would widely be applicable to several classes of higher transcendental functions.

Utpal Kumar Saha

Fuzzy Logic for Enhancing the Evaluation and Monitoring of Agile Artifacts in Cardiovascular Disease

Abstract

Cardiovascular disease is an amalgamated term to report heterogeneity of heart diseases and events that affect the heart. Agile along with software engineering will be beneficial for managing the inevitable uncertainties and changes in the cardiovascular care system. Fuzzy logic helps in finding severity using technical artifacts in cardiovascular disease. The proposed work uses agile software development methodology in association with fuzzy logic for evaluating technical artifacts. Here the experimentation is done on Cleveland Heart disease data sets present in the UC Irvine repository. This research contributes to identifying severity technically when cardiovascular disease symptoms are defined in terms of artifacts.

Alka Gulati, Kanak Saxena, Umesh Banodha

Development of Dust-Repellent Coating for Solar Panel and Evaluation of Energy Efficiency

Abstract

Dust accumulation on the solar panel is the most common problem for solar panels. It effectively reduces the efficiency and life of the solar photovoltaic. To increase the efficiency of solar panel, superhydrophobic coatings were developed by silica nanoparticle sol prepared by using methyltrimethoxysilane as precursor and low-energy nanoparticle modification was done by using polydimethylsiloxane (PDMS) on the surface. The coated surface was characterized by contact angle analysis, scanning electron microscopy (SEM) and Atomic Force Microscopy (AFM) of the coated surface. The analysis showed that the coatings were superhydrophobic having a nanostructural surface. These coatings on the solar panel showed better performance compared to uncoated panel, as no dust, water adhesion were observed on the surface after applying modified silica coating. The efficiency of the coated and uncoated surface was also analyzed and found to be better for coated surface.

Neha Bhatt, Abhilasha Mishra, Rekha Goswami, Arun Pratap Singh Rathod

A Study of Nanoscale Zeolitic Imidazole Framework-8 in Removal of Humic Acid from Wastewater by Adsorption

Abstract

Wastewater contains natural organic matter which consists of various kinds of acids such as humic acid, amino acid, fulvic acid, etc. Humic acid can easily dissolve in water and impart brownish color thus this very compound draws our attention. Humic acid has other problems such as converting into toxic compounds during chlorination and increasing the concentration of manganese and iron in groundwater. Therefore, humic acid causes health issues for drinking water and needs to be removed. To remove the humic acid, we developed an efficient adsorbent known as Zeolitic imidazole framework-8 (ZIF-8). ZIF-8 is mainly selected as it has a very high surface area and high stability in the aqueous medium. Regeneration of ZIF-8 can be done by using an easy ethanol-washing process and it can be reused too for humic acid adsorption. Hence, ZIF-8 is a stable and efficient adsorbent for the removal of humic acid from water owing to these factors. The characterization of ZIF-8 was done using Fourier transform infrared spectroscopy (FT-IR) and scanning electron microscopy (SEM). Factors that affect the adsorption of humic acid were observed, including temperature, mixing time, solid-to-liquid ratio, and pH. The removal efficiency increased from 27 to 83% as we increased the S/L ratio from 0.5 to 2.5. The removal efficiency is also increased with time and decreased with temperature as expected.

Shikha Solanki, Malayaj Srivastava, Saransh Bhatnagar, Surendra Sasi Kumar Jampa

Management of High-Volume Clashes During Clash Detection

Abstract

Typically in construction projects, design drawings are usually developed by different trade teams like architectural, structural, and mechanical, electrical, and plumbing and fire-fighting (MEPF). Hence, when these drawings are integrated it results in clashes between various trade-specific components. Conventionally clashes are found by overlapping the drawings and resolved by manually coordinating between the different departments which is a chaotic and time-consuming process. The efficiency of this process is low and can even lead to conflicts between different departments. These clashes if not resolved before the construction lead to reworks on-site which results in time and cost overruns. This problem can be effectively overcome by using Building Information Modelling’s (BIM) Clash Detection (CD) application, which identifies clashes from the 3D building models by integrating them. A Clash detection test usually identifies a large number of relevant and non-relevant clashes. Amongst these, the relevant clashes need to be resolved before construction to avoid rework and idle time during construction and the non-relevant clashes can be dealt with in site during construction. For resolving the relevant clashes, they have to be notified to different departments. Due to their large volume and multiple stakeholders involved, many challenges are faced by BIM manager and hence scientific management of clashes is crucial for better segregation and streamlining. In this study, a method of codifying clashes is presented for effective and efficient management of clashes and to eradicate issues associated with it. The developed method was applied to a sample project to validate.

Sagar Malsane, M. J. Merin, G. J. Gokul, P. Nithin Dev, Smitha Treesa Babu

Design of a Circular Ring Slot Patch Antenna at 2.45 GHz for Hyperthermia Applications

Abstract

Hyperthermia plays an important role in the treatment of cancer. A circular ring slot patch antenna for Hyperthermia applications is presented at 2.45 GHz. The proposed antenna shows return loss without significant detuning or impedance mismatch with different positions concerning a phantom muscle model. The simulation study is done by a Finite Element Method (FEM) based on Ansoft’s HFSS software. The antenna penetration depth, return loss, and the specific absorption rate (SAR) pattern are evaluated for various antenna orientations concerning the phantom muscle model.

Abhijeet Singh, Pushpendra Singh, S. P. Singh

An Exploratory Study of the Spirituality-Oriented Experiences of Tourists

Abstract

The extant literature demonstrates a gap in topics relating to spiritual and pilgrimage tourism in the domain of “tourist experience”. This study fills the gap based on a stimulus-organism-response (S-O-R) framework, and highlights the spiritual experience as the domain of stimulus. The organism construct, which states the tourists’ inner states of perceptions, cognition, and affection towards the stimulation, is represented by the overall image, significance of experiences, and life satisfaction. The response examines the revisit intention of tourists. Structural equation modeling (SEM) was performed based on 170 valid data sets, and the results support the significant functions of both cognitive and affective tourist experiences in contributing to the formation of positive tourist impressions in spirituality-oriented tours.

Chai Ching Tan, Phrapalad Somchai Damnoen, Yannakorn Toprayoon, Nittaya Dabjan, Kanthita Damkam

A Correlational Analysis of the Factors Influencing the Transfer of Research and Development to Entrepreneurs

Abstract

Investments in research and development play an important role in giving entrepreneurs an edge over their fellow competitors. This paper provides a correlational study of the factors influencing the ability of entrepreneurial undertakings to make use of the research findings conducted in their field. An analysis of the data from 49 countries indicates that the availability of entrepreneurial finance, government entrepreneurship programmes, adequate provision of physical infrastructure, entrepreneurial education, entrepreneurial motivation and cultural and social norms has a positive and significant correlation with the transfer of research and development to entrepreneurs. A relatively weak and insignificant correlation is found between the transfer of R&D and the existence of internal dynamics within markets. The correlation of the existence of internal market dynamics with R&D transfer is very weak and not significant. Several interesting policy implications are shed light on, such as incorporating entrepreneurial education and skills related to it in the curriculum of school and post-school institutions, providing financial concessions to enterprises who keep abreast and make use of the latest R&D findings in their field and providing adequate infrastructure facilities in order to facilitate the transfer of R&D.

Charmaine Savia Siqueira Lobo

Some Common Fixed Point Theorems in Generalized Fuzzy Metric Spaces for Weakly Compatible with CLRST Property

Abstract

The aim of this paper is to foreground the role of “Common Limit Range property” to find out the presence of a common fixed point in generalized fuzzy metric spaces. Some illustrative example is outfitted, which show the legitimacy of the theories and level of utility of our outcomes. We determine a fixed point theorem for four limited families of self-mappings, which can be used to infer common fixed point theorems including any limited number of mappings. Our outcomes improve and expand a large group of recently realized outcomes incorporating the ones contained in Imdad et al.

V. Vinoba, V. Pazhani, M. Jeyaraman

Performance Prediction of Technical Artifacts in Heart Disease Diagnosis

Abstract

In the modern era, due to the increase in stress levels, lack of exercise, food habits, there is a rapid increase in heart disease. Nowadays there is a risk of heart disease at any age. An important facet of medical diagnosis problem is uncertainty and the signs and symptoms of an individual may vary and hence uncertain. There are a number of prediction methods that use the data from the various medical organizations/institutes, to aware the patients well in advance. The information may be direct as well hidden and to make the decision effective the methods must be required to extract the hidden information. These heart disease attacks are so instant that a person gets hardly time to be treated. In this paper, we have proposed computational techniques for the investigation of severity of heart diseases technically using technical artifacts. We have technically reduced the number of artifacts. This work will help in diagnosing optimized risk factors in a low resource setting.

Alka Gulati, Kanak Saxena

Nonstandard Analysis of Almost Periodicity

Abstract

Nonstandard Analysis was introduced by Abraham Robinson in 1966 and Edward Nelson gave an axiomatic approach to it in 1977. The advantages of nonstandard analytic viewpoint are manyfold. To name a few, one is that it gives a natural insight into mathematical structures; another is that it reduces infiniteness to finiteness and infinitesimals to concrete objects.

Many a time, we try to study mathematical entities by approximating them by elementary objects. For example, we try to approximate continuous functions by polynomials. Almost periodicity is a study of approximating functions on locally compact abelian groups by trigonometric polynomials. In [9], the notion of Almost periodicity is carried out for operators also. In this paper, we nonstandardized Almost periodicity for the ‘traditional’ functions and then finally for the operators too.

S. Alagu, R. Kala