Khaled Moghalles, Zaid Al-Huda, Dalal AL-Alimi
et al.
Abstract The automated segmentation of buildings from remotely sensed imagery has undergone extensive research and application across various industrial domains. Despite this, several challenges persist, including incomplete internal extraction, low accuracy in edge segmentation, and difficulties in predicting irregular targets. We have introduced a novel approach to address these issues: an end-to-end residual U-structure embedded within a U-Net, enhanced by a frequency attention module and a hybrid loss function. The novel residual U-structure is introduced to replace the encode-decode blocks of traditional U-Nets, and the hybrid loss function is utilized to guide segmentation for more complete and accurate segmentation masks. A frequency attention module is also implemented to emphasize essential features and minimize irrelevant ones. A comparison of the proposed framework with other baseline schemes was conducted on four benchmark data sets, and the experimental results demonstrate that our framework performs better segmentation than other baseline state-of-the-art schemes.
Ayda Mussa Yousif Abdulrahman, Rafiduraida binti Abdul Rahman
This research aims to investigate the current operational status of the Ajman Police, focusing on identifying elements and issues that affect operational excellence. Using change management models, including Kotter's 8 Step Model and the ADKAR Model, the paper critically examines the hierarchical structure of the Ajman Police, its specialist groups, and their performance indicators. The problem statement highlights the negative impact of traditional and rigid organizational structures on innovation, responsiveness, and the limitations of implementing effective public safety measures, prevention, and community policing. The research design adopted is a qualitative methodology, and a sample of senior police officers was interviewed to record their views on the issues of operation and preparedness to change. In conducting the study, Semi-structured interviews were conducted with 10 participants. Results indicate that the Ajman Police has already ventured into technological advancements and civil policing. However, there are still gaps in continuous development, innovation, and the implementation of modern change management practices. The research proposes a culturally, operationally, and technologically oriented framework for change management, specifically tailored to the context of the Ajman Police. The study makes a significant research contribution to both the practice and theory fields by providing a guideline for a change management roadmap for the Ajman Police and other similar agencies, ensuring operational excellence in fast-changing environments.
Management information systems, Economic history and conditions
Dwi Ratna Puspita Sari, Sirli Fahriah, Kurnianingsih
et al.
Gold is one of the most favored investment instruments due to its stability and its ability to preserve value against inflation. However, its price movements are volatile and influenced by various global economic factors, currency exchange rates, and geopolitical conditions, making gold price forecasting a significant challenge. This study aims to develop a gold price forecasting system using the Long Short-Term Memory (LSTM) algorithm, a variant of the Recurrent Neural Network (RNN) that excels in processing time-series data. The dataset consists of historical daily gold buying and selling prices from 2015 to 2025, collected from Yahoo Finance, Logam Mulia, and the official website of Bank Indonesia. The modeling process follows the CRISP-DM methodology, which includes business understanding, data preparation and exploration, modeling, and evaluation stages. Time Series Cross Validation (TSCV) is used to validate the model. LSTM performance is compared with other models such as GRU, CNN-1D, and Simple RNN to identify the best-performing architecture. Evaluation results indicate that LSTM achieved the highest performance with an R² score of 0.99 for selling prices and 0.98 for buying prices on the final test dataset. The system is deployed online, making it accessible in real-time. This research is expected to assist investors, financial analysts, and the general public in making smarter investment decisions based on valid historical data and advanced forecasting technology.
Information technology, Electronic computers. Computer science
Mainstream Natural Language Processing (NLP) research has ignored the majority of the world's languages. In moving from excluding the majority of the world's languages to blindly adopting what we make for English, we first risk importing the same harms we have at best mitigated and at least measured for English. However, in evaluating and mitigating harms arising from adopting new technologies into such contexts, we often disregard (1) the actual community needs of Language Technologies, and (2) biases and fairness issues within the context of the communities. In this extended abstract, we consider fairness, bias, and inclusion in Language Technologies through the lens of the Capabilities Approach. The Capabilities Approach centers on what people are capable of achieving, given their intersectional social, political, and economic contexts instead of what resources are (theoretically) available to them. We detail the Capabilities Approach, its relationship to multilingual and multicultural evaluation, and how the framework affords meaningful collaboration with community members in defining and measuring the harms of Language Technologies.
This study investigates how decentralization and transparency offered by blockchain technology could revolutionize traditional finance. Even with the rise of well-known cryptocurrencies such as Bitcoin and Ethereum, a general understanding of blockchain’s influence on the financial industry is still lacking. We identified five major application cases—transparent credit scoring, effective consumer identification, expedited insurance settlements, improved cybersecurity, and the emergence of decentralized finance—where blockchain technology is well positioned to tackle persistent issues. We show how blockchain technology may address problems such as opaque credit scoring, poor customer identity, convoluted insurance settlement procedures, and susceptibility to cyberattacks by thoroughly examining various use cases. According to our research, a greater number of traditional financial institutions need to embrace and integrate blockchain innovations into their functions to promote inclusivity, transparency, and decentralization.
Emissions from thermal power plants have always been the central consideration for environmental protection. Existing optical sensors in thermal power plants usually measure the total mass concentration of the particulate matter (PM) by a single-wavelength laser, bearing intrinsic errors owing to the variation in particle size distribution (PSD). However, the total mass concentration alone cannot characterize all the harmful effects of the air pollution caused by the power plant. Therefore, it is necessary to measure the mass concentration and PSD simultaneously, based on which we can obtain multi-particle-size channel mass concentration. To achieve this, we designed an optical sensor based on the three-wavelength technique and tested its performance in a practical environment. Results showed that the prototype cannot only correctly measure the mass concentration of the emitted PM but also determine the mean diameter and standard deviation of the PSDs. Hence, the mass concentrations of PM<sub>10</sub>, PM<sub>2.5</sub>, and PM<sub>1</sub> are calculated, and the air pollutants emission by a thermal power plant can be estimated comprehensively.
Hajar Ebrahimi, Fahimeh Babalhavaeji, Dariush Matlabi
et al.
Objective: This study aims to investigate the factors influencing professional publishing and propose a model for professional book publishing in Iran.
Method: The research was conducted using a survey method with a researcher-developed questionnaire. The statistical population consisted of professional publishing managers in the country, totaling 581 publishers, from which 231 were selected as a sample based on Cochran's formula. Ultimately, 211 questionnaires were completed and analyzed. Data processing was carried out using SPSS software, employing exploratory the factor analysis and multiple regression test.
Findings: Based on exploratory factor analysis, nine factors have been identified as influential in professional publishing: the economics of publishing, the supply and display of publishing products, government support and backing, adherence to copyright, publishing evaluation and auditing, advertising, marketing and branding, publishing management, and the creation of publishing content. Additionally, five factors have been recognized as dimensions of professional publishing, which include technical elements, cultural and literary circles and centers, authors and audiences, electronic systems, and distribution and marketing elements. Ultimately, in the regression model, five independent variables were included in the equation due to their significance level being below .05.
Conclusion: The findings of this research contribute to enhancing the awareness and understanding of audiences regarding publishing processes. They also assist publishers and industry managers in recognizing successful trends and existing challenges within the field, as well as in formulating supportive policies and strategies for publishing by relevant authorities.
Bibliography. Library science. Information resources, Information technology