The rapid expansion of internet of things (IoT) devices have created a pervasive ecosystem where encrypted wireless communications serve as the primary privacy and security protection mechanism. While encryption effectively protects message content, packet metadata and statistics inadvertently expose device identities and user contexts. Various studies have exploited raw packet statistics and their visual representations for device fingerprinting and identification. However, these approaches remain confined to the spatial domain with limited feature representation. Therefore, this paper presents CONTEX-T, a novel framework that exploits contextual privacy vulnerabilities using spectral representation of encrypted wireless traffic for IoT device characterization. The experiments show that spectral analysis provides new and rich feature representation for covert reconnaissance attacks, revealing a complex and expanding threat landscape that would require robust countermeasures for IoT security management. CONTEXT-T first transforms raw packet length sequences into time-frequency spectral representations and then utilizes transformer-based spectral analysis for the device identification. We systematically evaluated multiple spectral representation techniques and transformer-based models across encrypted traffic samples from various IoT devices. CONTEXT-T effectively exploited privacy vulnerabilities and achieved device classification accuracy exceeding 99% across all devices while remaining completely passive and undetectable.
We introduce a compact, physics-driven event representation, RMM-C46, designed to compress the high-dimensional rapidity mass matrix (RMM) into a low-dimensional, interpretable feature set suitable for physics-informed machine learning (ML) and quantum computing applications. The full RMM encodes detailed pairwise correlations among jets, b-jets, leptons, photons, and missing transverse energy but contains more than a thousand values per event, making it computationally heavy for large-scale training and incompatible with current low-qubit quantum devices. The proposed RMM-C46 input space for ML preserves the physical block structure of the RMM through aggregated invariant mass, rapidity difference, and transverse energy components, reducing the size of the original RMM by over an order of magnitude while maintaining interpretability. Applied to simulated proton-proton collisions at centre-of-mass energy of 13.6 TeV, these representations match or exceed the discriminative performance of the full RMM in both supervised and unsupervised ML tasks. Their compactness, stability, and physics transparency also make them naturally compatible with near-term quantum machine learning architectures. RMM-C46 provides a scalable, efficient, and quantum-ready alternative to the full RMM for next-generation collider physics analyses.
This research aims to analyze the Planning of the Muhammadiyah Regional Leadership of North Sumatra in Educating Teenagers about the Dangers of Online Gambling. The method used is qualitative research that analyzes facts in the field that produce data in the form of words and information from informants. The data collection techniques used in this research are observation, interview and documentation. The results of this study indicate that the North Sumatra Muhammadiyah Regional Leadership Planning has planned an educational program on the dangers of online gambling to teenagers. The planning includes collaborating with legal institutions, socialization, seminars, program development, khatib jum'at and youth coaching. Challenges faced such as the resistance of the parties to the practice of online gambling, the number of online gambling sites that have not been blocked and the limitations of PWM in reaching remote areas.
This project focuses on designing and verifying a synchronous FIFO First In First Out (FIFO) memory, a critical component in digital systems for temporary data storage and seamless data transfer. The FIFO operates under a single clock domain, ensuring synchronized read and write operations, making it suitable for systems requiring high-speed, reliable data buffering. This design includes FIFO's key features, such as read and write operations, full and empty flag generation, and pointer management for memory control. The FIFO was implemented using Verilog to define the Register Transfer Level (RTL) design, ensuring functionality and timing requirements were met. For verification, three approaches were employed: (1) UVM-based Verification: A Universal Verification Methodology (UVM) testbench was developed to test the FIFO design rigorously. The testbench includes components like interface, sequence item, driver, monitor, scoreboard, agent, and environment. Directed and random tests were performed to verify corner cases, such as simultaneous reads and writes, full and empty conditions, and overflow and underflow scenarios; (2) Traditional Verilog Testbench: A standalone Verilog testbench was also used to validate the functionality of the FIFO through directed test scenarios and waveform analysis; (3) FPGA implementation: Additionally, the design was implemented on an FPGA for real-time testing to verify its functionality and timing behavior in hardware. FPGA-based verification ensured the design performed as expected under practical conditions. The results confirmed the correct operation of the FIFO, including accurate data transfer, flag behavior, and timing synchronization. The project successfully demonstrated the robustness and reliability of the synchronous FIFO design, highlighting its importance in modern digital systems for efficient data handling and buffering.
This study aims to explore the influence of gender roles influenced by patriarchal culture and modernization on women's participation in the workforce in China. Using the literature review method, this study critically examines relevant previous studies to identify key factors affecting women's participation in the labor force and their implications for economic and social development in China. The results show that China's deep-rooted patriarchal culture has shaped gender stereotypes and social norms that limit women's role in the public sphere, including in the labor market. However, China's modernization process has driven social and economic transformations that have opened up opportunities for women to participate in the workforce. This research also reveals the disparities between urban and rural areas, as well as differences in education levels that affect women's access to and participation in the labor force. This research contributes to a deeper understanding of the dynamics of gender roles and their influence on women's labor force participation in China. The findings of this study can provide more effective policy recommendations to improve gender equality and empower women in economic and social development in China.
The existence of different approaches and viewpoints between Islamic schools has raised controversial interpretations of verses 32 and 33 of Surah Al-Noor. Based on some viewpoints, the word “Chastity" in verse 33 means refraining from committing sins, apart from marriage, and based on some other viewpoints, " Chastity " only means a state of piousness and paragon, which could be obtained through the marriage. This research which is done by descriptive-analytical method, shows that the first and foremost recommendation of Islam to all humankinds in satisfying their sexual instinct is marriage. The present article aims to answer the question whether the marriage recommendation in the verses and traditions is absolute or is relatively bound up by the condition of being wealthy? Islamic religions have contradictory viewpoints on this question. Some regard the decree of marriage binding and some others consider it as an absolute entity. According to the selected view, obtained from the sum of the Qur'anic and narrational data, the recommendation to chastity through the marriage is clearly evident.
Kahramanlık ve vatan savunmasıyla ilişkilendirilmesi nedeniyle askeri bir ünvan olan gaziliğe, manevi bir anlam atfedilmektedir. Gazilerin savaşın/terör olaylarının getirdiği zorlu deneyimlerle başa çıkabilmeleri ve hayata uyumlarını sürdürebilmeleri için manevi ihtiyaçlarının bilinmesi ve karşılanması oldukça önemlidir. Bilimsel çalışmalar gazilerin manevi ihtiyaçlarının karşılanması için yapılan çalışmaların süreçteki zorlukların aşılmasını kolaylaştırdığını göstermektedir. Bu araştırmada askerlik görevi sırasında gazi olan bireylere Değer Odaklı Manevi Güçlenme ve Bakım Programı (DOMAB) uygulanmış, programın gazilerin Yaradan algısı ve psikolojik sağlıkları üzerindeki etkisi incelenmiştir. Keşifsel ve deneysel desende hazırlanan araştırmaya toplamda 64 gazi katılmıştır. Bunların 32'si deney grubuna, 32'si ise kontrol grubuna dahil edilmiştir. Tema odaklı grup toplantılarıyla gerçekleştirilen manevi bakım oturumlarında Özdoğan (2019) tarafından geliştirilen DOMAB programında yer alan değerlerden azim, özveri, denge, özgürlük, irade, özgüven, olumlu bakış açısı ve barış sevgi, takva, dua, sabır, adalet, şükür ve insan kutsal kitap ilişkisi temaları ele alınmıştır. Uygulamada ön test-son test kontrol gruplu model yöntemi esas alınmıştır. Veri toplama aracı olarak Güler (2007) tarafından geliştirilen Tanrı Algısı Ölçeği ve Derogatis (1992) tarafından geliştirilen, Şahin ve Durak (1994) tarafından Türkiye uyarlaması, güvenirlik ve geçerlik çalışmaları yapılan Kısa Semptom Envanteri kullanılmıştır. Bulgular, uygulamanın gazilerin Tanrı algısı ve psikolojik sağlık puanlarını farklılaştırdığını göstermektedir. Buna göre araştırmanın temel hipotezi olarak belirlenen “Değer Odaklı Manevi Güçlenme ve Bakım Programı kapsamında gerçekleştirilen manevi bakım uygulamaları ile gazilerin Tanrı algısı puanları ve psikolojik sağlık düzeyi puanları farklılaşacaktır” tezi desteklenmiştir. Bulguların analizi sonucunda: (a) Tanrı algısı puanları, deney grubu gazilerinin lehine olacak şekilde farklılaşmıştır. Deney grubu katılımcılarının sevgi yönelimli Tanrı algısı son test puanlarında, ön test puanlarına göre artış görülürken, korku yönelimli Tanrı algısı son test puanlarında ise ön test puanlarına göre düşüş yaşanmıştır. Ayrıca, deney grubu katılımcılarına yapılan üç ay sonraki izleme testi sonuçları, manevi bakımın etkilerinin sürdüğünü ve uygulamanın korku yönelimli Tanrı algısı puanları üzerindeki etkisini koruduğunu göstermiştir. (b) psikolojik sağlık puanlarını deney grubu gazilerinin lehine olacak şekilde farklılaştırmıştır. Deney grubu katılımcılarının Kısa Semptom Envanteri son test puanlarında, ön test puanlarına göre düşüş olduğu görülmüştür. Bu uygulama sonucunda, katılımcıların anksiyete, depresyon, olumsuz benlik ve hostilite boyutlarında iyileşme yaşadığı açıkça görülmektedir. Üç ay sonra gerçekleştirilen izleme testi sonuçları, deney grubu katılımcılarında bu etkinin sürdüğünü ve katılımcıların Kısa Semptom Envanteri somatizasyon ve hostilite (öfke/düşmanlık) boyutlarında tespit edilen iyileşmenin devam ettiğini göstermiştir. Bununla birlikte, kontrol grubunun aynı ölçeklerin son testinden aldıkları puanlarda herhangi bir iyileşme gözlenmemiştir. Bu nedenle, gazilerin Tanrı Algısı Ölçeği ve Kısa Semptom Envanteri puanlarına bakılarak uygulanan programın gazilerin Tanrı algısı ve psikolojik sağlıkları üzerinde olumlu etkisinin olduğu ifade edilebilir.
Bhismo Aji Wibowo, Eni Restyowati, Annisa Ratnaningsih
et al.
This research aims to investigate the influence of students' interest in learning on statistics learning outcomes at SDN Wirun 3. The research uses a correlational approach to evaluate the relationship between students' interest in learning and statistics learning achievement. Data collection methods include surveys, academic records, and observations to understand students' learning interests. Data analysis uses correlation and regression techniques to assess the strength of the relationship between interest in learning and statistical learning achievement as well as other factors that influence it. The results of this work show a strong positive relationship between students' learning interest and their achievement in statistics courses, with approximately 49.8% of the variation in statistics achievement being explained by the level of learning interest. The data shows a high level of enthusiasm for learning among students, with average scores for interest in learning quite high and academic performance in moderate but strong statistics. The correlation coefficient of 0.706 between interest in learning and academic achievement indicates a significant correlation, underscoring the importance of building interest in learning to improve educational outcomes. These results confirm that increasing interest in learning can be a key strategy to advance students' academic achievement, especially in the subject of statistics.
Crafting effective deep learning models for medical image analysis is a complex task, particularly in cases where the medical image dataset lacks significant inter-class variation. This challenge is further aggravated when employing such datasets to generate synthetic images using generative adversarial networks (GANs), as the output of GANs heavily relies on the input data. In this research, we propose a novel filtering algorithm called Cosine Similarity-based Image Filtering (CosSIF). We leverage CosSIF to develop two distinct filtering methods: Filtering Before GAN Training (FBGT) and Filtering After GAN Training (FAGT). FBGT involves the removal of real images that exhibit similarities to images of other classes before utilizing them as the training dataset for a GAN. On the other hand, FAGT focuses on eliminating synthetic images with less discriminative features compared to real images used for training the GAN. Experimental results reveal that employing either the FAGT or FBGT method with modern transformer and convolutional-based networks leads to substantial performance gains in various evaluation metrics. FAGT implementation on the ISIC-2016 dataset surpasses the baseline method in terms of sensitivity by 1.59% and AUC by 1.88%. Furthermore, for the HAM10000 dataset, applying FABT outperforms the baseline approach in terms of recall by 13.75%, and with the sole implementation of FAGT, achieves a maximum accuracy of 94.44%.
Rifqatul Husna, Ach Zayyadi, Dwiki Oktafiana Wirendri
This paper aims to analyze the relationship between faith and tolerance in the film One Amen Two Faith, an example that the relationship between religion and tolerance plays a vital role in this millennial era, by using qualitative research methods that describe in-depth by watching the film by analyzing the sources which will later be analyzed by studying the living Qur'an. The results of the research on the film one amen, two faiths present the closeness of the relationship between religion and tolerance; several thoughts describe mutual respect, respect, and unity in differences, especially differences in beliefs, so that a series of things can be contemplated and learned from. This research implies the importance of implementing Islamic values in interacting with fellow human beings who have different religious, social, and cultural backgrounds to create benefits for all.
Andri Martiana, Zenza Chessara Novada Panena, Nasrul Fahmi Zaki Fuadi
This paper aims to analyze the potential of the Baitul Maal wat Tamwil (BMT) strategy to empower the lower-middle-class people and analyze the recommended strategy for making economic empowerment through more effective and efficient Islamic microfinance. This research uses the in-depth interview method and SWOT analysis as further analysis. The results indicated that BMT has great potential, especially in human resources development and a clear market share to empower the lower classes of society. However, it is necessary to have an appropriate economic empowerment model following the conditions of the lower classes of society and the need for government roles to support the existence of an Islamic microfinance institution in the form of Baitul Maal wat Tamwiil (BMT). Several economic empowerment strategies have been implemented by Baitul Maal wat Tamwil (BMT). This study adds the existing literature related to Islamic microfinance's role to have the suitable model that efficiently and effectively empowers the poor Indonesian society, especially those who live in Yogyakarta.
Healthcare data is sensitive and requires great protection. Encrypted electronic health records (EHRs) contain personal and sensitive data such as names and addresses. Having access to patient data benefits all of them. This paper proposes a blockchain-based distributed healthcare application platform for Bangladeshi public and private healthcare providers. Using data immutability and smart contracts, the suggested application framework allows users to create safe digital agreements for commerce or collaboration. Thus, all enterprises may securely collaborate using the same blockchain network, gaining data openness and read/write capacity. The proposed application consists of various application interfaces for various system users. For data integrity, privacy, permission and service availability, the proposed solution leverages Hyperledger fabric and Blockchain as a Service. Everyone will also have their own profile in the portal. A unique identity for each person and the installation of digital information centres across the country have greatly eased the process. It will collect systematic health data from each person which will be beneficial for research institutes and health-related organisations. A national data warehouse in Bangladesh is feasible for this application and It is also possible to keep a clean health sector by analysing data stored in this warehouse and conducting various purification algorithms using technologies like Data Science. Given that Bangladesh has both public and private health care, a straightforward digital strategy for all organisations is essential.
The percentage of urban areas dedicated to streets and public spaces is a crucial feature of the spatial planning of cities. By 2050 urban mobility will be one of the biggest confronts for global cities. This study has been carried out to assess the ratio of public space allocated to the streets in some cities of Bangladesh. The length, width, area, and number of street crossings have been counted for the city core and its suburban area as an indicator of the form and pattern of the street layout. This exercise does not consider the rest of the public spaces, like gardens and general public spaces for amenities, including sports. The methodology of data collection has been through Google Earth and GIS software. For precise results, other more sophisticated software is essential. Nevertheless, even at these levels of precision, very interesting city patterns emerge. The findings of this study show that Bogra, Rangpur, and Dinajpur are better cities having higher land allocation rates for streets, including sufficient crossings. Nilphamari and Thakurgaon have lower land areas for roads; tend to have lower connectivity and productivity. The rest of the cities have an average land area for roads and an average number of street crossings.
Quiddity questions are of the main five questions of historical investigations focusing on the discovery of the quiddity of historical events.
The concept of quiddity questions and the strategies taken to answer them are considered as the most important issues being worth to be reflected.
This article tries to investigate these issues relying on the historical-analytical method and referring to the data collected through the library method.
The findings of research reveal that, the historian is supposed to consider the linguistic and semantic changes as well as the application of important instruments such as valid sources and hermeneutic science to answer the quiddity questions
The graph coloring problem (GCP) is one of the most studied NP-HARD problems in computer science. Given a graph , the task is to assign a color to all vertices such that no vertices sharing an edge receive the same color and that the number of used colors, is minimal. Different heuristic, meta-heuristic, machine learning and hybrid solution methods have been applied to obtain the solution. To solve this problem we use mutation of evolutionary algorithm. For this purpose we introduce binary encoding for Graph Coloring Problem. This binary encoding help us for mutation, evaluate, immune system and merge color easily and also reduce coloring dynamically. In the traditional evolutionary algorithm (EA) for graph coloring, k-coloring approach is used and the EA is run repeatedly until the lowest possible is reached. In our paper, we start with the theoretical upper bound of chromatic number, that is, maximum out-degree + 1 and in the process of evolution some of the colors are made unused to dynamically reduce the number of color in every generation. We test few standard DIMACS benchmark and compare resent paper. Maximum results are same as expected chromatic color and few data sets are larger than expected chromatic number
Federated learning enables machine learning algorithms to be trained over a network of multiple decentralized edge devices without requiring the exchange of local datasets. Successfully deploying federated learning requires ensuring that agents (e.g., mobile devices) faithfully execute the intended algorithm, which has been largely overlooked in the literature. In this study, we first use risk bounds to analyze how the key feature of federated learning, unbalanced and non-i.i.d. data, affects agents' incentives to voluntarily participate and obediently follow traditional federated learning algorithms. To be more specific, our analysis reveals that agents with less typical data distributions and relatively more samples are more likely to opt out of or tamper with federated learning algorithms. To this end, we formulate the first faithful implementation problem of federated learning and design two faithful federated learning mechanisms which satisfy economic properties, scalability, and privacy. Further, the time complexity of computing all agents' payments in the number of agents is $\mathcal{O}(1)$. First, we design a Faithful Federated Learning (FFL) mechanism which approximates the Vickrey-Clarke-Groves (VCG) payments via an incremental computation. We show that it achieves (probably approximate) optimality, faithful implementation, voluntary participation, and some other economic properties (such as budget balance). Second, by partitioning agents into several subsets, we present a scalable VCG mechanism approximation. We further design a scalable and Differentially Private FFL (DP-FFL) mechanism, the first differentially private faithful mechanism, that maintains the economic properties. Our mechanism enables one to make three-way performance tradeoffs among privacy, the iterations needed, and payment accuracy loss.