Peran Layanan Bimbingan Pranikah Dalam Meningkatkan Kesiapan Diri Calon Pengantin Di Kantor Urusan Agama (KUA) Desa Grogol Kecamatan Gunung Jati Kabupaten Cirebon

ABSTRAK Ali Shihab A Rahman, NIM: 1414363049 “Peran Layanan Bimbingan Pranikah Dalam Meningkatkan Kesiapan Diri Calon Pengantin Di Kantor Urusan Agama (KUA) Desa Grogol Kecamatan Gunung Jati Kabupaten Cirebon”. Layanan Bimbingan merupakan suatu kegiatan pemeberian bantuan yang disenggelarakan oleh KUA kepada calon pengantin guna meningkatkan pengetahuan kepada calon pengantin seputar pernikahan, agar lebih siap menjanlani rumah tangganya sehingga akan terwujud rumah tangga yang sakinah, mawwadah, warahmah. Kesiapan diri adalah suatu kondisi dimana individu merasa dirinya mampu untuk menghadapi tujuannya. Penelitian ini bertujuan untuk mengetahui layanan bimbingan pranikah di KUA Kecamatan Gungjati Kabupaten Cirebon, kondisi kesiapan diri calon pengantin di KUA Kecamatan Gungjati Kabupaten Cirebon, dan. peran layanan bimbingan pranikah dalam meningkatkan kesiapan diri calon pengantin di Kecamatan Gunungjati Kabupaten Cirebon. Metode penelitian yang digunakan oleh peneliti adalah metode penelitian kualitatif dengan pendekatan jenis penelitian deskriptif. Teknik pengumpulan data yang digunakan dalam penelitian ini adalah observasi, wawancara, dan dokumentasi. Sumber data penelitian meliputi data primer dan data sekunder. Kemudian analisis data yang digunakan adalah, reduksi data, penyajian data, dan kesimpulan atau verifikasi data. Dengan demikian kesimpulan pada penelitian ini dapat menjawab seluruh pertanyaan dalam rumusan masalah yang sudah dirumuskan sejak awal. Hasil dari penelitian ini menunjukan bahawasanya layanan bimbingan pranikah KUA Kecamatan Gunungjati Kabupaten Cirebon lebih banyak melakukan kegiatan bimbingan pra nikah dengan metode bimbingan kelompok. Pelaksanaan bimbingan dilakukan seperti KUA pada umumnya, setiap 10 hari kerja atau sebelum pelaksanaan perniakahan dengan durasi 1-2 jam di ruangan penghulu atau aula KUA. Kesipan diri calon pengantin di Kecamatan Gunungjati Kabupaten Cirebon sudah cukup baik. Secara Adminrasi, Jasmani dan Rohani sudah memenuhi kriteria kesiapan diri untuk menikah. Namun, ada rentan umur yang harus terus diperhatikan yaitu calon pengantin yang berumur dikisaran 18 sampai 24 tahuh, karena faktor emosional yang masih berlebih. Peran layanan bimbingan pranikah di KUA Kecamatan Gunungjati Kabupaten Cirebon dalam meningkatkaan kesiapan diri calon pengantin memiliki peran memberikan nasihat dan bimbingan kepada calon pengantian agar semakin paham, mantap dan optimis untuk membangun rumah tangga yang sakinah, mawadah dan warohmah. Kata Kunci: Layanan Bimbingan Pranikah, Kesiapan diri, Calon Penganti

Best S-box amongst differently sized S-boxes based on the avalanche effect in ‎the advance encryption standard algorithm

Substitution boxes are essential nonlinear modules that are popular in block ‎cipher algorithms. They ‎also play a significant role in the security area because of ‎their robustness to different linear ‎cryptanalysis. Each element of the state in a S-‎box is nonlinearly replaced using a lookup table. This ‎research presents the S-‎box, one of the fundamental parts of the advanced encryption standard ‎‎(AES) ‎algorithm. The S-box represents the confusion part in the AES. However, when ‎information ‎is shared between different devices in an authorized manner, the ‎algorithm should be able to ‎combine a sufficient number of confusion layers to ‎guarantee the avalanche effect (AE). ‎Subsequently, this research selects the best ‎S-box by comparing different sizes (4×4, 8×8, and ‎‎16×16) and measuring them ‎on the basis of the million-bit encryption. The AE is the main criterion ‎used in ‎choosing the best S-box. A robust and strong cryptography algorithm should be ‎able to ‎confirm the AEs. Results indicate that the 16×16 S-box with a 52% AE ‎ratio is the superior S-bo

Nonconformity Assessment in Building Construction Projects: A Fuzzy Group Decision-Making Approach

Construction nonconformity assessment of buildings is critical to ensure the anticipated quality and living safety for their future occupants. Previous studies have paid less attention to identifying and analyzing building construction nonconformities (BCNs) in the design and construction (D&amp;C) phases. They considered expert judgments in nonconformity assessment, which are critiqued for human bias, uncertainty, and imprecision. In a BCN assessment, previous studies also did not consider the specific time frame to detect construction nonconformities. This study aims to prioritize nonconformities in the D&amp;C phases, addressing the limitations of expert judgment by applying the fuzzy group decision-making approach (FGDMA). The FGDMA computes the defuzzified scores of the nonconformities to prioritize and identify critical nonconformities. The defuzzified scores are explained further by associating them with the corresponding fuzzy numbers to address the limitations involved in expert judgments. The study also identifies the detection time of BCNs and analyzes 15 different Bangladeshi project scenarios to understand their context better. The critical nonconformities identified include premature stressing on concrete, inaccurate water-cement ratios, insufficient concrete compaction, lack of full-time site supervision, and the absence of stirrups in beam-column joints. Critical nonconformities are mostly identified during construction, and residential, commercial, and multipurpose buildings, regardless of ownership (i.e., public or private) and size, have experienced poor quality construction. This study will assist major stakeholders (owner, contractor, consultant, and regulatory authorities) to fully understand the critical nonconformities in different building projects from their preconstruction to construction phases for better quality assurance in providing a safe living and working environment for their future occupants. Practical Applications: The study identifies critical nonconformities and their frequency, severity, and detection times in different construction projects, including residential, commercial, and multipurpose buildings and mosques. It also studies 15 different project scenarios for analyzing the nonconformities of government and privately funded/owned buildings. The most common nonconformities are premature stressing on concrete (loading to concrete members before gaining their design strength), inaccurate water-cement ratios, insufficient concrete compaction, and the absence of stirrups in beam-column joints. These nonconformities all occur due to lack of full-time site supervision and poor workmanship during construction. The dominating detection time for identifying the critical nonconformities is "during construction."Thus, it is possible to control many by careful supervision and improved workmanship during construction. The project scenario analysis shows that residential, commercial, and multipurpose buildings, regardless of ownership (i.e., public or private), experience poor quality construction. These findings will assist stakeholders with different engagement levels in managing their roles in building projects to deliver a better quality of construction, and hence a sustainable and safe living and working environment. </p

GUT SYMPTOMS LINKED WITH COVID-19 : A SYSTEMATIC REVIEW

The most prevalent symptoms at the onset of COVID-19 are fever, cough, fatigue, myalgia, and dyspnea (shortness of breath). Initially, it was thought that the virus only causes respiratory distress in patients until the viral RNA has been detected in the patient's stool. Recently, several new studies have depicted that COVID-19 has impact on gut patients. We hypothesized that, there may have a link between gut symptoms and COVID-19. Therefore, the present study was reviewed to explore this study question; searches were conducted to identify the articles related to the association between gut symptoms and COVID-19, which were published between 2019 to 2020. Multiple searches were conducted in Google Scholar and ResearchGate using keywords. In this review, a total of 2639 cases of COVID-19 from 20 articles had been analyzed with special emphasize on gut symptoms. Among 20 studies, Diarrhea (highest 71.62% and lowest 2%) was the most prevalent symptoms, respectively, nausea (highest 17.1% and lowest 1%) & vomiting (highest 16.7% and lowest 1%), anorexia (highest 66.7% and lowest 17.9%), and abdominal pain (highest 8.8% and lowest 1.9%). Along with the main symptoms, we studied some commonly associated symptoms, such as, fever (highest 98.6% and lowest 55.6%) and coughing (highest 91.67% and lowest 35%) were heavily linked with COVID 19. Despite all the GI symptoms associated with COVID 19, there are currently no recommendations for a diagnostic approach in the presence of gastrointestinal symptoms associated with the corona virus, and there is no definitive knowledge of the role of COVID-19 in the gastrointestinal diseases. So, further studies are needed to identify the better relationship between gut symptoms and SARS-CoV-2 for suppressing the spread of COVID-19.Peer reviewe

Enhancement of satellite image compression using a hybrid (DWT–DCT) algorithm

Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) image compression techniques have been utilized in most of the earth observation satellites launched during the last few decades. However, these techniques have some issues that should be addressed. The DWT method has proven to be more efficient than DCT for several reasons. Nevertheless, the DCT can be exploited to improve the high-resolution satellite image compression when combined with the DWT technique. Hence, a proposed hybrid (DWT–DCT) method was developed and implemented in the current work, simulating an image compression system on-board on a small remote sensing satellite, with the aim of achieving a higher compression ratio to decrease the onboard data storage and the downlink bandwidth, while avoiding further complex levels of DWT. This method also succeeded in maintaining the reconstructed satellite image quality through replacing the standard forward DWT thresholding and quantization processes with an alternative process that employed the zero-padding technique, which also helped to reduce the processing time of DWT compression. The DCT, DWT and the proposed hybrid methods were implemented individually, for comparison, on three LANDSAT 8 images, using the MATLAB software package. A comparison was also made between the proposed method and three other previously published hybrid methods. The evaluation of all the objective and subjective results indicated the feasibility of using the proposed hybrid (DWT–DCT) method to enhance the image compression process on-board satellites.e nutritional and antioxidant properties of underutilized BRF as a food ingredient

DeepLocalization: Using change point detection for Temporal Action Localization

In this study, we introduce DeepLocalization, an innovative framework devised for the real-time localization of actions tailored explicitly for monitoring driver behavior. Utilizing the power of advanced deep learning methodologies, our objective is to tackle the critical issue of distracted driving-a significant factor contributing to road accidents. Our strategy employs a dual approach: leveraging Graph-Based Change-Point Detection for pinpointing actions in time alongside a Video Large Language Model (Video-LLM) for precisely categorizing activities. Through careful prompt engineering, we customize the Video-LLM to adeptly handle driving activities' nuances, ensuring its classification efficacy even with sparse data. Engineered to be lightweight, our framework is optimized for consumer-grade GPUs, making it vastly applicable in practical scenarios. We subjected our method to rigorous testing on the SynDD2 dataset, a complex benchmark for distracted driving behaviors, where it demonstrated commendable performance-achieving 57.5% accuracy in event classification and 51% in event detection. These outcomes underscore the substantial promise of DeepLocalization in accurately identifying diverse driver behaviors and their temporal occurrences, all within the bounds of limited computational resources.This is a preprint from Rahman, Mohammed Shaiqur, Ibne Farabi Shihab, Lynna Chu, and Anuj Sharma. "DeepLocalization: Using change point detection for Temporal Action Localization." arXiv preprint arXiv:2404.12258 (2024). doi: https://doi.org/10.48550/arXiv.2404.12258. Copyright 2024 The Authors. CC-BY

BaDLAD: A Large Multi-Domain Bengali Document Layout Analysis Dataset

While strides have been made in deep learning based Bengali Optical Character Recognition (OCR) in the past decade, the absence of large Document Layout Analysis (DLA) datasets has hindered the application of OCR in document transcription, e.g., transcribing historical documents and newspapers. Moreover, rule-based DLA systems that are currently being employed in practice are not robust to domain variations and out-of-distribution layouts. To this end, we present the first multidomain large Bengali Document Layout Analysis Dataset: BaDLAD. This dataset contains 33,695 human annotated document samples from six domains - i) books and magazines, ii) public domain govt. documents, iii) liberation war documents, iv) newspapers, v) historical newspapers, and vi) property deeds, with 710K polygon annotations for four unit types: text-box, paragraph, image, and table. Through preliminary experiments benchmarking the performance of existing state-of-the-art deep learning architectures for English DLA, we demonstrate the efficacy of our dataset in training deep learning based Bengali document digitization models

Review of intelligence for additive and subtractive manufacturing: current status and future prospects

Additive manufacturing (AM), an enabler of Industry 4.0, recently opened limitless possibilities in various sectors covering personal, industrial, medical, aviation and even extra-terrestrial applications. Although significant research thrust is prevalent on this topic, a detailed review covering the impact, status, and prospects of artificial intelligence (AI) in the manufacturing sector has been ignored in the literature. Therefore, this review provides comprehensive information on smart mechanisms and systems emphasizing additive, subtractive and/or hybrid manufacturing processes in a collaborative, predictive, decisive, and intelligent environment. Relevant electronic databases were searched, and 248 articles were selected for qualitative synthesis. Our review suggests that significant improvements are required in connectivity, data sensing, and collection to enhance both subtractive and additive technologies, though the pervasive use of AI by machines and software helps to automate processes. An intelligent system is highly recommended in both conventional and non-conventional subtractive manufacturing (SM) methods to monitor and inspect the workpiece conditions for defect detection and to control the machining strategies in response to instantaneous output. Similarly, AM product quality can be improved through the online monitoring of melt pool and defect formation using suitable sensing devices followed by process control using machine learning (ML) algorithms. Challenges in implementing intelligent additive and subtractive manufacturing systems are also discussed in the article. The challenges comprise difficulty in self-optimizing CNC systems considering real-time material property and tool condition, defect detections by in-situ AM process monitoring, issues of overfitting and underfitting data in ML models and expensive and complicated set-ups in hybrid manufacturing processes