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High-density development requires large land parcels, but fragmented land ownership can impede redevelopment. While earlier compact city development in Sydney occurred on large-scale brownfield sites, redeveloping and re-amalgamating older strata-titled properties is now integral to further densification. The purpose of this study is to examine collective sales activity in one Sydney suburb where multiple strata-titled redevelopments and re-amalgamations have been attempted. The authors explore how owners navigate the process of selling collectively, focusing on their experience of legislation introduced to facilitate this process, the Strata Schemes Development Act 2015 [New South Wales (NSW)].

By reviewing sales listings, development applications and media coverage, and interviewing owners, lawyers and estate agents, the authors map out collective sale activity in a case study area in Sydney’s northwest.

Strata collective sales are slow and difficult to complete, even when planning and market drivers align. Owners find the Strata Scheme Development Act 2015 (NSW) difficult to navigate and it has not prevented strategic blocking attempts by competing developers. The long timelines required to organise collective sales can result in failure if the market shifts in the interim. Nonetheless, owners remain interested in selling collectively.

This case study is important for understanding the barriers to redevelopment to achieve a more compact city. It highlights lessons for other jurisdictions considering similar legislative changes. It also suggests that legislative change alone is insufficient to resolve the planning challenges created by hyper-fragmentation of land through strata-title development.

The Accounting Information Systems (AIS) research field emerged around 30 years ago as a subfield of accounting but is at risk to develop further as an isolated discipline. However, given the importance of digitalization and its relevance for accounting, an amalgamation of the parent research field of accounting and the subfield of accounting information systems is pivotal for continuing relevant research that is of high quality. This study empirically investigates the distance between AIS research that is included in accounting literature and AIS research that prevails in dedicated AIS research outlets.

To understand which topics define AIS research, all articles published in the two leading AIS journals since 2000 were analyzed. Based on this topical inventory, all AIS studies that were published in the top 16 accounting journals, also since 2000, are identified and categorized in terms of topic, subtopic and research methodology. Next, AIS studies published in the general accounting field and AIS studies published in the AIS field were compared in terms of topics and research methodology to gain insights into the distance between the two fields.

The coverage of AIS topics in accounting journals is, to no small extent, concentrated around the topics “information disclosure”, “network technologies” and “audit and control”. Other AIS topics remain underrepresented. A possible explanation might be the focus on archival studies in accounting outlets, but other elements might play a role. The findings suggest that there is only a partial overlap between the parent accounting research field and the AIS subfield, in terms of both topic and research methodology diversity. These findings suggest a considerable distance between both fields, which might hold detrimental consequences in the long run, if no corrective actions are taken.

This is the first in-depth investigation of the distance between the AIS research field and its parent field of accounting. This study helped develop an AIS classification scheme, which can be used in other research endeavors. This study creates awareness of the divergence between the general accounting research field and the AIS subfield. Given the latter's relevance to the accounting profession, isolation or deterioration of the AIS research must be avoided. Some actionable suggestions are provided in the paper.

As historic cities evolve, change in their urban form can be expected. Yet, uncontrolled change of land plots, which represent a significant element of urban form, leads to uncontrolled change in buildings' configurations and typologies threatening accordingly the urban character of heritage contexts. Mechanisms controlling plot subdivision, however, can play an effective role in guiding developments and in controlling urban change in heritage settings. The present study seeks to assist decision-makers in their attempt to control urban change in heritage areas through a plot-based approach.

This paper is divided into three sections: the first focuses on plot subdivision as a key aspect of urban form; the second illustrates the case of the heritage village of New Gourna in Luxor and the third includes discussion and implications of adopting a plot-based morphological approach to control morphological transformation in heritage contexts. For the morphological analysis of New Gourna, the study relied on comparative cartographic analysis of original drawings of the village versus the situation in 2022. The morphological analysis focuses mainly on qualitative and quantitative aspects of plot configurations and building patterns.

Findings support the urgency of establishing a plot-based strategy to maintain urban character of heritage contexts in Egypt and call for a plot-based morphological approach to control change and inform new development attempts.

The present research provides an assessment of the morphological transformation of the heritage village of New Gourna. In addition, it proposes a plot-based approach for heritage contexts under transformation.

Bitcoin has indeed been universally acknowledged as an investment asset in recent decades, after the boom-and-bust of cryptocurrency values. Because of its extreme volatility, it requires accurate forecasts to build economic decisions. Although prior research has utilized machine learning to improve Bitcoin price prediction accuracy, few have looked into the plausibility of using multiple modeling approaches on datasets containing varying data types and volumetric attributes. Thus, this paper aims to propose a bitcoin price prediction model.

In this research work, a bitcoin price prediction model is introduced by following three major phases: Data collection, feature extraction and price prediction. Initially, the collected Bitcoin time-series data will be preprocessed and the original features will be extracted. To make this work good-fit with a high level of accuracy, we have been extracting the second order technical indicator based features like average true range (ATR), modified-exponential moving average (M-EMA), relative strength index and rate of change and proposed decomposed inter-day difference. Subsequently, these extracted features along with the original features will be subjected to prediction phase, where the prediction of bitcoin price value is attained precisely from the constructed two-level ensemble classifier. The two-level ensemble classifier will be the amalgamation of two fabulous classifiers: optimized convolutional neural network (CNN) and bidirectional long/short-term memory (BiLSTM). To cope up with the volatility characteristics of bitcoin prices, it is planned to fine-tune the weight parameter of CNN by a new hybrid optimization model. The proposed hybrid optimization model referred as black widow updated rain optimization (BWURO) model will be conceptual blended of rain optimization algorithm and black widow optimization algorithm.

The proposed work is compared over the existing models in terms of convergence, MAE, MAPE, MARE, MSE, MSPE, MRSE, Root Mean Square Error (RMSE), RMSPE and RMSRE, respectively. These evaluations have been conducted for both algorithmic performance as well as classifier performance. At LP = 50, the MAE of the proposed work is 0.023372, which is 59.8%, 72.2%, 62.14% and 64.08% better than BWURO + Bi-LSTM, CNN + BWURO, NN + BWURO and SVM + BWURO, respectively.

In this research work, a new modified EMA feature is extracted, which makes the bitcoin price prediction more efficient. In this research work, a two-level ensemble classifier is constructed in the price prediction phase by blending the Bi-LSTM and optimized CNN, respectively. To deal with the volatility of bitcoin values, a novel hybrid optimization model is used to fine-tune the weight parameter of CNN.

This study aims to deal with the evaluation of institutional development and effectiveness of regional parliaments; it provides a scientific contribution to the development of the field of parliamentary studies by developing a set of indicators to present a parameter for evaluating regional parliaments with application to the Arab Parliament. The study concluded with the development of a parameter of 35 indicators to measure institutionally, efficiency and effectiveness of the institution, with application to the Arab Parliament, as well as developing an integrated assessment of the strengths and weaknesses in the institutional aspects and organizational efficiency.

The study is predicated on the principle of institutional approach and the systems analysis. The curriculum is applied to the Arab Parliament as an institution to quantify efficiency and efficacy according to the implementation of a set of proposed practical indicators. The study additionally applies both Huntington’s institutional standards such as Adaptability, Involution, Autonomy and Coherence, as well as the indicators of institutions efficiency according to PrePanti such as Openness, Reception (R), Autonomy (A), Balance (B), Congruence (C), Internal Efficacy (I), Reformulation (R) and Roles (R), which refer to the first seven Latin letters “First RABCIRR”.

The researcher endeavored to answer the main questions; How to quantify the degree of institutionalization, its impact on the efficiency and efficacy of regional parliaments. The researcher’s approaches and the standards of efficiency and efficacy figured a comprehensive set of indicators that composed an integrated parliamentary standard to assess the degree of institutionalization, efficacy and efficiency of regional parliaments as a scientific contribution based on the Arab Parliament that can be applied to all regional parliaments.

This research is an attempt to create a Parliamentary Index to complement the previous scientific initiatives and efforts in developing such an index, which consists of 35 indicators and its application to the Arab Parliament. This research uses the principles of institutional approach, system analysis methodology and efficiency. The approach is applied to the Arab Parliament as a regional parliament to measure efficiency and effectiveness by applying a set of the proposed indicators.

This paper seeks to demonstrate the value of using social media to capture fashion trends, including the popularity of specific features of clothing, in order to improve the speed and accuracy of supply chain response in the era of fast fashion.

This study examines the role that text mining can play to improve trend recognition in the fashion industry. Researchers used n-gram analysis to design a social media trend detection tool referred to here as the Twitter Trend Tool (3Ts). This tool was applied to a Twitter dataset to identify trends whose validity was then checked against Google Trends.

The results suggest that Twitter data are trend representative and can be used to identify the apparel features that are most in demand in near real time.

The 3Ts introduced in this research contributes to the field of fashion analytics by offering a novel method for employing big data from social media to identify consumer preferences in fashion elements and analyzes consumer preferences to improve demand planning.

The 3Ts improves forecasting models and helps inform marketing campaigns in the apparel retail industry, especially in fast fashion.

This study aims to address a comprehensive and integrated investigations pertaining to the preparation of AgNPs with well-defined nano-sized scale using the aforementioned poly (meth acrylic acid [MAA])–chitosan graft copolymer, which is cheap, nontoxic, biodegradable and biocompatible agent as a substitute for the traditionally used toxic reducing agents.

AgNPs are prepared under a range of conditions, containing silver nitrate and poly (MAA)–chitosan graft copolymer concentrations, time, temperature and pH of the preparation medium. To classify AgNPs obtained under the various conditions, ultraviolet–visible spectroscopy spectra and transmission electron microscopy images are used for characterization of AgNPs instrumentally in addition to the visual color change throughout the work. The work was further extended to study the application of the so prepared AgNPs on cotton fabric to see their suitability as antibacterial agent as well as their durability after certain washing cycles.

According to the current investigation, the optimal conditions for AgNPs formation of nearly 3–15 nm in size are 5 g/l, poly (MAA)–chitosan graft copolymer and 300 ppm AgNO₃ in addition to carrying out the reaction at 60°C for 30 min at pH 12. Besides, the application of the so prepared AgNPs on cotton fabric displayed a substantial reduction in antibacterial efficiency against gram-positive and gram-negative bacteria estimated even after 10 washing cycles in comparison with untreated one.

To the best of the authors’ information, no comprehensive study of the synthesis of AgNPs using poly (MAA)–chitosan graft copolymer with a graft yield of 48% has been identified in the literature.

Fashion merchandising hold a paramount position within the realm of retail marketing. Currently, the purpose of this article is that the assessment of display effectiveness predominantly relies on the subjective judgment of merchandisers due to the absence of an effective evaluation method. Although eye-tracking devices have found extensive used in tracking the gaze trajectory of subject, they exhibit limitations in terms of stability when applied to the evaluation of various scenes. This underscores the need for a dependable, user-friendly and objective assessment method.

To develop a cost-effective and convenient evaluation method, the authors introduced an image processing framework for the assessment of variations in the impact of store furnishings. An optimized visual saliency methodology that leverages a multiscale pyramid model, incorporating color, brightness and orientation features, to construct a visual saliency heatmap. Additionally, the authors have established two pivotal evaluation indices aimed at quantifying attention coverage and dispersion. Specifically, bottom features are extract from 9 distinct scale images which are down sampled from merchandising photographs. Subsequently, these extracted features are amalgamated to form a heatmap, serving as the focal point of the evaluation process. The authors have proposed evaluation indices dedicated to measuring visual focus and dispersion, facilitating a precise quantification of attention distribution within the observed scenes.

In comparison to conventional saliency algorithm, the optimization method yields more intuitive feedback regarding scene contrast. Moreover, the optimized approach results in a more concentrated focus within the central region of the visual field, a pattern in alignment with physiological research findings. The results affirm that the two defined indicators prove highly effective in discerning variations in visual attention across diverse brand store displays.

The study introduces an intelligent and cost-effective objective evaluate method founded upon visual saliency. This pioneering approach not only effectively discerns the efficacy of merchandising efforts but also holds the potential for extension to the assessment of fashion advertisements, home design and website aesthetics.

This study aims to explore the potential impact of country-level governance in corporate financing structures.

A two-step system generalized method of moment was used due to the endogeneity issue. The whole sample comprises 3,761 firms in five economies – China, India, Pakistan, Singapore and South Korea – from 2007 to 2016.

The results indicate that the debt option for financing is not favorable under governments with an adequate governance arrangement. However, there is a direct and significant link between country governance and equity financing because in adequate governance arrangements, the possibilities of information asymmetry are minimal and businesses consider equity a more appropriate and safer financing instrument. In contrast, firms prefer to trade-credit financing in poor governance economies, which confirms an adverse link between trade credit and adequate governance.

The country’s governance should be considered a sensitive matter when deciding about corporate financing.

This arrangement of variables has not been previously analyzed in the literature, suggesting the study’s novelty.

The purpose of this paper is to investigate the performance of Passive Direct Methanol Fuel Cell (PDMFC) experimentally using various Membrane Electrode Assembly (MEA) shapes such as square, rectangle, rhombus, and circle with equal areas and equal perimeters. The variation in MEA shape/size is achieved by altering gasket openings in the dynamic regions.

In the equal areas of MEA shapes, gasket opening areas of 1963.5 (+/−0.2) mm2 are used. Whereas in the equal perimeters of shapes, gasket opening perimeters of 157.1 (+/−0.2) mm are used. In this experimentation, Nickel-201 current collectors with 45.3% of circular openings are used on both the anode and cathode sides. The experiment is carried out at a 5 molar methanol concentration to find out the highest power density of the cell.

In the equal areas, among the shapes that are chosen for investigation, the square shape opening consisting of a perimeter of 177.2 mm has developed a maximum power density of 6.344 mWcm⁻² and a maximum current density of 65.2 mAcm⁻². Similarly, in equal perimeters, the rhombus shape opening with an area of 1400 mm2 has developed a maximum power density of 7.714 mWcm⁻² and a maximum current density of 85.3 mAcm⁻².

The novelty of this research work is instead of fabricating various shapes and sizes of highly expensive MEAs, the desired shapes and sizes of the MEA are achieved by altering gasket openings over dynamic regions to find out the highest power density of the cell.