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Publications - 6674

Exploring factors of service adoption using SERVQUAL paradigm: Its impact on millennials’ adoption of services in the self-drive rental sector

Laszlo Vasa Vinod Sharma A. S. Suresh Yogesh Mahajan

Publication Name: Innovative Marketing

Publication Date: 2024-01-01

Volume: 20

Issue: 2

Page Range: 182-192

Description:

The self-drive rental sector has witnessed exponential growth in recent years due to rising demand for long and short-distance drives among millennials. This study aims to investigate the quality of services in the self-driving rental sector and its impact on customer adoption or rejection of service in India. The conceptual framework was developed using the SERVQUAL model and other important factors affecting consumers’ service adoption. A quantitative research method was deployed, and data were gathered through a survey method using a structured questionnaire (based on a 5-point Likert scale). The sample size comprised 385 respondents, 23-38 years old millennials (with 69% of males and 31% of females). The population sample was chosen from Delhi, Mumbai, and Bangalore, India. The data were collected in March 2023. The factor and regression analyses were applied along with chi-square and SEM analyses to test the research hypotheses. The results indicated that the absence of low prices (42%), customer assistance (28 %), and security issues is responsible for consumer rejection. The factors leading to dissatisfaction are the absence of consumer schemes and discounts, a lack of staff interaction and assistance, and poor service quality. The brands must focus on the negative impact arising from the absence of these factors and effectively address the areas of improvement to regain customer trust and garner customer loyalty.

Open Access: Yes

DOI: 10.21511/im.20(2).2024.15

Bacterial memetic algorithm for simultaneous optimization of path planning and flow shop scheduling problems

János Botzheim Yuichiro Toda Naoyuki Kubota

Publication Name: Artificial Life and Robotics

Publication Date: 2012-10-01

Volume: 17

Issue: 1

Page Range: 107-112

Description:

The paper deals with simultaneous optimization of path planning of mobile robots and flow shop scheduling problem. The goal of the path planning problem is to determine an optimal collision-free path between a start and a target point for a mobile robot in an environment surrounded by obstacles. The objective is to minimize the path length without colliding with an obstacle. On the other hand, shop scheduling problems deal with processing a given set of jobs on a given number of machines. Each operation has an associated machine on which it has to be processed for a given length of time. The problem is to minimize the overall time demand of the whole process. In this paper, we deal with two robots carrying items between the machines. Bacterial memetic algorithm is proposed for solving this combined problem. The algorithm is verified by experimental simulations and compared to classical techniques.

Open Access: Yes

DOI: 10.1007/s10015-012-0021-9

Enhancing UAV Autonomous Navigation in Indoor Environments Using Reinforcement Learning and Convolutional Neural Networks

Eniko Nagy Amirfarhad Farhadi Homayoun Safarpour Motealegh Mahalegi Gyorgy Molnar

Publication Name: Sisy 2024 IEEE 22nd International Symposium on Intelligent Systems and Informatics Proceedings

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 91-100

Description:

In recent years, the number of unmanned aerial vehicle (UAV) applications has increased. However, navigating them indoors is still tricky because no GPS signals are available, and the obstacles constantly change. This study exploits the collaboration between convolutional neural networks (CNNs) and reinforcement learning (RL) to overcome these challenges, improving the level of independence of UAVs in indoor settings. We present a new technique known as potential-based reward shaping, which directly incorporates expert knowledge into the reinforcement learning framework. This technique efficiently addresses the problem of sparse rewards that often hinder learning in conventional RL configurations. In addition, we have created a reflective reinforcement learning agent that systematically assesses its actions to prioritize those that result in the most substantial enhancements. We have extensively evaluated the performance of our method with the High-Definition Indoor Navigation (HDIN) dataset to show that our method continuously outperformed current non-introspective RL techniques in terms of decision-making speed and navigation accuracy in this evaluation. The results show that this new CNN-RL combination is feasible and suggests a scalable method for complex indoor navigation problems.

Open Access: Yes

DOI: 10.1109/SISY62279.2024.10737528

Parametric approximation of fuzzy exponent for computationally intensive problems

János Botzheim Péter Földesi

Publication Name: International Journal of Innovative Computing Information and Control

Publication Date: 2012-08-01

Volume: 8

Issue: 8

Page Range: 5725-5744

Description:

The paper deals with the investigation of the critical non-linear factors and NP-hard problems of real-life decision-making processes. When using non-linear utility/objective functions to represent the value of various options in the search space or when NP-hard problems arise, often soft computing techniques must be applied for optimization. Many times significant uncertainty must be handled as well, so the use of fuzzy numbers can be an efficient method to cope with ambiguity and lack of information. The fuzzy extensions for heuristic based optimizing algorithms often face the problem of an increased number of calculations required to find the solutions. Appropriate representation of the fuzzy power function for non-linear cases is to be used so that it can keep the required computation time and resources at a reasonable level. © 2012 ICIC International.

Open Access: Yes

DOI: DOI not available

LlFSAE one-cylinder engine intake system optimization with simulation methods and test bench validation through low- and high-pressure indication system measurements

Boros Máté Tóth Máté Pesthy Márk

Publication Name: Journal of the Brazilian Society of Mechanical Sciences and Engineering

Publication Date: 2026-02-01

Volume: 48

Issue: 2

Page Range: Unknown

Description:

This research paper aims to optimize the intake system’s plenum and intake manifold length. The paper discusses the importance of the precisely calculated intake plenum volume, which significantly impacts the internal combustion engine performance. The design of the plenum, besides the chosen volume should assure the desired airflow quantity and quality through the whole system. 1D simulations do these particular analytic calculations and the CFD tool is used to determine the laminarity of the airflow. The second part of this paper intends to explain the intake pipe, restrictor calculations and why it is crucial for a precisely tuned race engine. Validation of the simulation results with engine test bench measurements and explanation of different engine performance plotting techniques via indication data.

Open Access: Yes

DOI: 10.1007/s40430-025-06152-1

Computer-aided Molecular and Process Design (CAMPD) for Ionic Liquid Assisted Extractive Distillation of Refrigerant Mixtures

M. M.Faruque Hasan Ashfaq Iftakher Rafiqul Gani

Publication Name: Computer Aided Chemical Engineering

Publication Date: 2024-01-01

Volume: 53

Issue: Unknown

Page Range: 1303-1308

Description:

Computer-aided Molecular and Process Design, CAMPD, is a technique that simultaneously optimizes the choice of materials, such as solvents, and the corresponding process configurations for many chemical separation processes. The technique involves formulating an equation-oriented optimization model representing the overall design problem, which then can be solved in many ways depending on the chemicals involved, the property and process models, and the complexity and size of the problem, among others. Due to the complexity and large-size of the problem, and a lack of predictive property models, we have applied a decomposition-based CAMPD strategy that involves solving a series of subproblems sequentially to reduce the overall search space, thereby reducing the computational burden. We illustrate our strategy through a case study involving the design of ionic liquids (ILs) as solvents for the extractive-distillation based separation of an azeotropic refrigerant mixture, R-410A. Separation of such mixtures is gaining increased interest due to the need to remove, substitute or reuse constituent refrigerant chemicals that have undesirable properties (such as high global warming potential, flammability, etc.). ILs are considered because of their designable properties as functions of their molecular structures. Based on available measured data, group-contribution based predictive property models have been developed and interfaced with the workflow of the proposed strategy. A set of promising ILs have been identified and their performance verified through process simulation.

Open Access: Yes

DOI: 10.1016/B978-0-443-28824-1.50218-0

Predictive Maintenance and Predictive Repair of Road Vehicles—Opportunities, Limitations and Practical Applications †

Istvan Lakatos Jozsef Nagy

Publication Name: Engineering Proceedings

Publication Date: 2024-01-01

Volume: 79

Issue: 1

Page Range: Unknown

Description:

With drastic increases in the complexity of road vehicles, increasing environmental and cost pressures have led to the obsolescence of previous fixed-schedule maintenance systems. The aerospace industry, following the road vehicle industry, is also beginning to use the predictive maintenance method increasingly widely. A possible next step for critical breakdowns could be a predictive service. While preventive maintenance is able to be used more frequently, the possibility of preventive repair is also limited to the fault symptoms, and is unsuitable for preventing fast-running breakdowns. Due to the current state of technological development in this area, it will take a few more years for lower-priced cars to catch up to the sensor and data structures of current premium-series vehicles, such that the mass use of these methods in road vehicles can become widespread.

Open Access: Yes

DOI: 10.3390/engproc2024079027

PROMOTING ORGANISATIONAL CITIZENSHIP BEHAVIOUR THROUGH CORPORATE GOVERNANCE

Mohammad Fakhrul Islam Linus Adama Friday Ogbu Edeh Ebere Rejoice Okocha Nicholas Ihentuge Achilike Collins Okechukwu Irem Ifeoma Gloria Duruzor Ozor Kelechukwu Colman Gladys Owere Onah Filep Balint Nwali Obinna Benneth

Publication Name: Corporate Governance and Organizational Behavior Review

Publication Date: 2024-01-01

Volume: 8

Issue: 2

Page Range: 103-112

Description:

Corporate governance is a major topic of debate among scholars from different parts of the world, but little has been empirically investigated on the impact of corporate governance on the discretionary work behaviour of employees in selected deposit money banks in Nigeria. Therefore, the purpose of this study is to examine the impact of corporate governance on the organizational citizenship behaviour of employees in deposit money banks. A cross-sectional survey design was used, which supports the use of questionnaire to collect data from the participants. Data were collected from 224 participants from 18 deposit money banks operating in south-east Nigeria. The study employed frequency distribution and linear regression to analyse respondents’ profiles and research hypotheses. Results of the study revealed that corporate governance dimensions predicted organisational citizenship behaviour indicators. The practical significance of this study lies in the possibility of improving organizational citizenship behaviour in organizations by integrating the main recommendations of this study into the corporate governance of organizations. This study concludes that corporate governance (measured in terms of leadership quality, accountability, board size, board effectiveness, and board independence) influences and improves organizational citizenship behaviour that is driven by altruism, integrity, sportsmanship, courtesy, and civic virtue.

Open Access: Yes

DOI: 10.22495/cgobrv8i2p10

Noise, Vibration, and Harshness (NVH) Challenges in Hydrogen Internal Combustion Engine Vehicles

Krisztian Horvath Krisztián Horváth

Publication Name: Energy Science and Engineering

Publication Date: 2026-02-01

Volume: 14

Issue: 2

Page Range: 1067-1080

Description:

This paper presents a state-of-the-art literature review on noise, vibration, and harshness (NVH) in hydrogen-fuelled internal combustion engines. Studies published between 2011 and 2025 were screened, covering fundamental flame physics, test-bench work, and recent prototype vehicles. The review links hydrogen's core properties—high flame speed, wide flammability, low ignition energy, strong diffusivity—to specific NVH outcomes such as rapid pressure rise, knock, back-fire, and block resonance. For each pathway we summarise measured noise levels, vibration signatures, and psycho-acoustic findings. Mitigation methods are then grouped: lean premixing, direct injection, adaptive ignition timing, exhaust tuning, and structural damping. Results show that, with these measures, hydrogen engines can approach the NVH envelope of modern gasoline units. Remaining gaps lie in long-term durability under high-frequency loading and in full-vehicle sound quality. Overall, the review clarifies current knowledge, highlights consistent trends, and points to research still needed for quiet, smooth hydrogen mobility.

Open Access: Yes

DOI: 10.1002/ese3.70400