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The purpose of this paper is to conduct a forensic analysis of Google Allo messenger on an Android-based mobile phone. The focus was on the analysis of the data stored by this application in the internal memory of the mobile device, with minimal use of third-party applications. The findings were compared with the already existing works on this topic. Android is the most popular operating system for mobile devices, and these devices often contain a massive amount of personal information about the user such as photos and contact details. Analysis of these applications is required in case of a forensic investigation and makes the process easier for forensic analysts.

Logical acquisition of the data stored by these applications was performed. A locked Android device was used for this purpose. Some scripts are presented to help in data acquisition using Android Debug Bridge (ADB). Manual forensic analysis of the device image was performed to see whether the activities carried out on these applications are stored in the internal memory of the device. A comparative analysis of an existing mobile forensic tool was also performed to show the effectiveness of the methodology adopted.

Forensic artifacts were recovered from Allo application. Multimedia content such as images were also retrieved from the internal memory.

As this study was conducted for forensic analysis, it assumed that the mobile device used already has USB debugging enabled on it, although this might not be the applicable in some of the cases. This work provides an optimal approach to acquiring artifacts with minimal use of third-party applications.

Most of the mobile devices contain messaging application such as Allo installed. A large amount of personal information can be obtained from the forensic analysis of these applications, which can be useful in any criminal investigation.

This is the first study which focuses on the Google Allo application. The proposed methodology was able to extract almost as much as the data obtained using earlier approaches, but with minimal third-party application usage.

This study aims to perform the experimental work on a laboratory-constructed steel truss bridge model on which hammer blows are applied for excitation. The vibration response signals of the bridge structure are collected using sensors placed at different nodes. The different damaged states such as no damage, single damage, double damage and triple damage are introduced by cutting members of the bridge. The masked noise with recorded vibration responses generates challenge to properly analyze the health of bridge structure.

The analytical modal properties are obtained from finite element model (FEM) developed using SAP2000 software. The response signals are analyzed in frequency domain by power spectrum and in time-frequency domain using spectrogram and Stockwell transform. Various low pass signal-filtering techniques such as variational filter, lowpass sparse banded (AB) filter and Savitzky–Golay (SG) differentiator filter are also applied to refine vibration signals. The proposed methodology further comprises application of Hilbert transform in combination with MUSIC and ESPRIT techniques.

The outcomes of SG filter provided the denoised signals using appropriate polynomial degree with proper selected window length. However, certain unwanted frequency peaks still appeared in the outcomes of SG filter. The SG-filtered signals are further analyzed using fused methodology of Hilbert transform-ESPRIT, which shows high accuracy in identifying modal frequencies at different states of the steel truss bridge.

The sequence of proposed methodology for denoising vibration response signals using SG filter with Hilbert transform-ESPRIT is a novel approach. The outcomes of proposed methodology are much refined and take less computational time.

This study aims to include the diagnosis of an old concrete deck steel truss rural road bridge in the damaged and retrofitted state through vibration response signals.

The analysis of the vibration response signals is performed in time and time-frequency domains using statistical features-root mean square, impulse factor, crest factor, kurtosis, peak2peak and Stockwell transform. The proposed methodology uses the Hilbert transform in combination with spectral kurtosis and bandpass filtering technique for obtaining robust outcomes of modal frequencies.

The absence or low amplitude of considered mode shape frequencies is observed both before and after retrofitting of bridge indicates the deficient nodes. The kurtosis feature among all statistical approaches is able to reflect significant variation in the amplitude of different nodes of the bridge. The Stockwell transform showed better resolution of present modal frequencies but due to the yield of additional frequency peaks in the vicinity of the first three analytical modal frequencies no decisive conclusions are achieved. The methodology shows promising outcomes in eliminating noise and visualizing distinct modal frequencies of a steel truss bridge.

The findings of the present study help in analyzing noisy vibration signals obtained from various structures (civil or mechanical) and determine vulnerable locations of the structure using mode shape frequencies.

The literature review gave an insight into few experimental investigations related to the combined application of Hilbert transform with spectral kurtosis and bandpass filtering technique in determining mode frequencies of a steel truss bridge.

The study is aimed at developing and testing a theoretical model where psychological capital acts as the intervening mechanism explicating the relationship between perceived overqualification (POQ) and turnover intention. It also explores how perceived supervisor support (PSS) influences the mediating role of psychological capital in the perceived overqualification and turnover intention association.

The authors test the model through a sample data of 314 workers employed in the Indian IT service sector. IBM SPSS and SPSS AMOS software were utilized for conducting analysis and testing the model involving first-stage moderated mediation.

The study confirms that perceptions of overqualification have a positive relationship with turnover intentions. Further, it finds that the positive association between POQ and turnover intention will be mediated by psychological capital. The results reflected that perceived supervisor support shall weaken the relationship between perceptions of overqualification and psychological capital.

The research is amongst the limited researches which look at the influence of psychological capital and perceived supervisor support with regards to POQ. It attempts to lay down the underlying psychological mechanism of POQ and highlight the role played by perceived supervisor support.

This study aims to examine the factors influencing user satisfaction with unified payment interface (UPI)-based payment systems during the COVID-19 pandemic in India. The study also aimed to examine whether the user satisfaction with UPI-based payment systems during the COVID-19 pandemic will transform into their continuance intention post-COVID-19 pandemic.

The study was performed in three phases, i.e. pre-testing (for developing questionnaire), pilot study (using exploratory factor analysis to ensure unidimensionality) and the main study. The main study was based on the feedback from a sample of 369 internet users who first used the UPI-based payment system during the COVID-19 pandemic. Data generated were analysed using the structural equation modelling approach.

The study findings suggest that the users who are satisfied with UPI-based transactions during the COVID-19 pandemic are likely to continue their use of this payment mode in future. Factors such as post-adoption perceived value, perceived usefulness and post-adoption perceived risk were observed to be key constructs in explaining user satisfaction and continued intention for UPI-based payment systems.

The study is one of the pioneering studies, in the sense that it investigated the continuance intention of UPI-based payment systems, which, surprisingly, did not gain much attention from past researchers.

In-situ aluminum metal matrix composites (AMMC) have taken over the use of ex-situ AMMC due to the generation of finer and thermodynamically stable intermetallic compounds. However, conventional processing routes pose inevitable defects like porosity and agglomeration of particles. This paper aims to study current state of progress in in-situ AMMC fabricated by Friction Stir Processing.

Friction stir processing (FSP) has successfully evolved to be a favorable in-situ composite manufacturing technique. The dynamics of the process account for a higher plastic strain of 35 and a strain rate of 75 per second. These processing conditions are responsible for grain evolution from rolled grain → dislocation walls and dislocation tangles → subgrains → dislocation multiplication → new grains. Working of matrix and reinforcement under ultra-high strain rate and shorter exposure time to high temperatures produce ultra-fine grains. Do the grain evolution modes include subgrain boundaries → subgrain boundaries and high angle grain boundaries → high angle grain boundaries.

Further, the increased strain and strain rate can shave and disrupt the oxide layer on the surface of particles and enhance wettability between the constituents. The frictional heat generated by tool and workpiece interaction is sufficient enough to raise the temperature to facilitate the exothermic reaction between the constituents. The heat released during the exothermic reaction can even raise the temperature and accelerate the reaction kinetics. In addition, heat release may cause local melting of the matrix material which helps to form strong interfacial bonds.

This article critically reviews the state of the art in the fabrication of in-situ AMMC through FSP. Further, FSP as a primary process and post-processing technique in the synthesis of in-situ AMMC are also dealt with.

The purpose of this paper is to derive mobile-government (m-government) service-quality factors in the Gulf Cooperation Council (GCC) and develop an integrated strategic plan for improving the quality of m-government services from a customer perspective in the GCC.

A quantitative approach was used in this case study of m-government services in the GCC. Data were collected using focus groups and questionnaires for three similar m-government applications (one from the United Arab Emirates, one from the Saudi Arabia and one from Oman). The house of quality tool, including technical benchmarking, was applied as part of the quality function deployment (QFD) approach to identify customer requirements, translate them to technical requirements and develop a strategic plan for improving the quality of m-government services.

The results revealed that “real time” had the highest priority for deployment, while “tangible service,” contrary to expectations, had the lowest priority for deployment.

Study findings are limited to the m-government services delivered to citizens. There is scope for further study into m-government services delivered both to businesses and other governments.

The findings imply that the m-government decision makers must involve citizens in all service-development processes to ensure that service delivery meets citizens’ expectations.

Most previous studies regarding m-government service-quality dimensions have used information system service-quality dimensions. This study is one of the pioneering studies to have successfully derived m-government service-quality factors using the QFD matrix.

The purpose of this paper is to develop an effective approach to decide design details using benchmarking to capture the existing practice in sustainable design.

This paper reports a systematic method for sustainable product design. The method uses benchmarks as references searching for design details to achieve sustainable solutions. Quality function deployment is used to guide the search process for competitive products using benchmarking to meet quantitative targets of product and to increase knowledge for sustainable design.

The proposed method can meet both functional and sustainable requirements of product design. 18.55 percent reduction in carbon equivalent emissions is achieved compared to benchmarks in wheelchair design. The research reveals that when weight, material and number of components used in product decrease, environmental footprints and cost of the product improve.

The research improves the existing method of sustainable product design. Both sustainable requirements and functional demands of product are identified from qualitative criteria to quantitative metrics using benchmarking and the life cycle assessment.

Small retail stores in the luxury market face significant challenges due to fluctuations in market demand. This task turns challenging as it requires effectively coordinating and translating customer needs into specific requirements that align with retail goals and available resources. However, limited empirical research exists investigating how managers can address service value and quality attributes in small retail stores. This article aims to bridge this gap by investigating the role of quality function deployment (QFD) in improving market and quality requirements management in small retail stores.

Based on the case study, a customer survey was initially conducted to gather information on critical characteristics valued in the luxury retail segment. QFD was used to assist the company in identifying and prioritizing key quality attributes to meet customer requirements effectively.

The findings demonstrate that implementing QFD in small luxury retail stores empowers managers to identify previously neglected product and service quality aspects. The article shows that QFD informs organizational adaptations that align with the demands of the retail market, leading to an improved ability to meet customer expectations and enhance customer value through the development of enhanced products and services. The study showcases the efficacy of the tested methodology in effectively capturing and prioritizing both tangible and intangible customer needs in retail.

Findings offer valuable insights to retail managers of small luxury stores, providing actionable market-oriented strategies. By implementing the recommended practices, managers can improve the store’s competitiveness and better cater to the customer base.

This study contributes to bridging persistent knowledge gaps by addressing the unique context of small luxury retail stores and introducing the application of QFD in this setting. The insights gained from this research are relevant to both retailing and quality management literature. Considering the growing prevalence of transformations in the retail industry, the study provides practical implications for retail managers in effectively navigating these changes.

The “quality” of any product or service defines the agility of the product and its life cycle in dynamic environment. The demand of high “quality” becomes an imperative concern, when “software” is acting as a product or a service. Since the nature of the software is intangible and more complex, therefore the assurance of providing accurate results is anxiety for companies. The overall quality of the software is based upon many individual factors (or attributes) that makes software reliable, inclined and a long-lasting product in the marketplace. But how these factors can influence each other is significant to identify. Therefore, the purpose of this paper is to study the quality aspect of the software and analyse the interrelationship of impactful attributes.

The analysis has been done through responses sought from software development teams/clients in India. The questionnaire related to the software quality was administered to the sample population. Interconnection among impactful characteristics has been analysed by using a qualitative technique called interpretive structural modelling (ISM). The driving and dependency of the attributes under consideration has been classified using cross-impact matrix multiplication applied to classification (MICMAC) analysis. The procedure of applying ISM method has been automated and provided it as package “ISM” using R software.

In general, it is very complex job to determine the most impactful attribute of software quality. By applying ISM and MICMAC analysis on the set of attributes under consideration, it has been found that “reliability” along with “usability” and “performance” is the most influential attribute of software quality and preferred most.

Though ISM provides an organized modelling framework yet its results are considered less statistically significant. Therefore, it would be interesting to concatenate the present findings with the findings of any analytical methodology; which gives statistically significant results.

The present proposal deals with the interpretation of the software quality attributes and their contextual relationship but with more effective and efficient manner. It can help management to understand the complexity of relationship amongst attributes (which are quality attributes here) more accurately and precisely. Since today is an era of automation, the manual part is being substituted so as to reduce the labour cost, improve safety, security and product quality to increase production. This study is, therefore, an effort and a helping hand in making the hassle free calculations for obtaining intermediate matrices and doing eventual calculations.

n numbers of parameters can be selected to analyse the interrelationship of any project/study. Eradication human errors in applying transitivity law or applying any other operation in solving problem. The package created here can save precious time of users. Provides well-formatted and readable excel output files that make interpretation easier.

Software is one such product/service which plays a significant role in this high-technological world, where each and every firm try their best to be on the top of the list of consumers’ preference. For this purpose, companies reduce manual efforts by converting it into qualitative software that provides deliverables in a systematic manner. Therefore, it becomes imperative to study various interrelated quality attributes of the software. On the similar platform, ISM is a widely used technique and just to provide a helping hand in quantification of the qualitative attributes this paper facilitates the readers with algorithm developed using R software.