bluuebunny/crossref_metadata_2025 huggingface dataset:
Transfer Learning for Anomaly Detection in Rotating Machinery using Data-driven Key Order Estimation
Authors: Liang Jia , Shui Huanyi , Gupta Rajesh , Upadhyay Devesh , Darve Eric
Published: February 2024

Anomaly detection is an important task in industrial applications.
However, designing an accurate anomaly detector can be very challenging
in settings where anomalous labels are sparse or, in the worst case,
missing in the training data. To mitigate this issue of a lack of
anomalous labels in the domain of interest, existing approaches use
transfer learning, leveraging information from anomalous samples in a
closely related domain. Although previous studies have shown good
results from applying transfer learning, they do not specifically
address the issue of high false-positive rates, especially in industrial
settings. High false-positive rates can arise from misleading
information present in uninformative features. Inspired by this
observation, the paper focuses on identifying key input
features—termed as such due to their strong predictability in anomaly
detection. A transfer learning approach is introduced that leverages the
optimal fβ score for key feature estimation. This
approach involves a weight vector to amplify key features and attenuate
uninformative inputs during prediction. We demonstrate the capabilities
of our proposed method through an industrial application: anomaly
detection for rotating machinery. Based on our findings, anomaly
detection algorithms that utilize data-driven features obtained through
the proposed method outperform detectors based on features identified by
domain experts. More importantly, our proposed framework can work with
any downstream unsupervised anomaly detection algorithm, allowing us to
freely choose the best algorithm for the anomaly detection task.
PENGARUH OPINION SHOPPING, DAN DEBT DEFAULT TERHADAP PENERIMAAN OPINI AUDIT GOING CONCERN
Authors: Munzir Munzir , Nurfatimah Uswatul Fajar , Nisak Kamila Maulidiya
Published: February 2024

Penelitian ini bertujuan untuk menilai secara empiris pengaruh Opinion Shopping, dan Debt Default terhadap Penerimaan Opini Audit Going Concern. Penelitian ini berjenis penelitian kuantitatif. Penarikan hipotesis penelitian menggunakan basis teori Agensi dan teori atribusi, didukung oleh penelitian-penelitian sebelumnya yang mempunyai kesamaan variabel. Sampel Penelitian yaitu 11 Perusahaan Pertambangan yang terdaftar di Bursa Efek Indonesia. Jenis data yang digunakan adalah data sekunder hasil pengumpulan dokumen laporan keuangan. Menggunakan teknik statistik deskriptif dan Regresi Logistik berbantuan SPSS 25.0 untuk analisis data. Selain itu  penelitian ini menggunakan uji kelayakan model regresi. Hasil penelitian menunjukkan bahwa secara parsial Debt Default berpengaruh positif terhadap Penerimaan Opini Audit Going Concern. Sedangkan Opinion Shopping secara parsial berpengaruh negatif terhadap Penerimaan Opini Audit Going Concern
PENGARUH PEMERIKSAAN PAJAK BADAN TERHADAP PENINGKATAN PENERIMAAN PAJAK PADA KPP MADYA MAKASSAR
Authors: Difinubun Yusron , Hidayat Spica Miranda
Published: February 2024

Penelitian ini bertujuan untuk menilai secara empiris pengaruh Pemeriksaan Pajak terhadap Peningkatan Penerimaan Pajak. Penelitian ini berjenis penelitian kuantitatif. Penarikan hipotesis penelitian menggunakan basis teori Kontijensi, didukung oleh penelitian-penelitian sebelumnya yang mempunyai kesamaan variabel. Penelitian berlokasi di KPP MADYA Makassar. Jenis data yang digunakan adalah data Primer. Menggunakan teknik statistik deskriptif dan Regresi linear Moderasi dan uji asumsi klasik berbantuan SPSS 25.0 untuk analisis data. Hasil penelitian menunjukkan bahwa Pemeriksaan Pajak memiliki pengaruh positif terhadap Peningkatan peneriman Pajak pada KPP MADYA Makassar
Analisis Faktor-faktor yang mempengaruhi Kinerja Karyawan: Kompensasi, Motivasi Kerja, Lingkungan Kerja
Authors: Sanaba Hardiman F. , Andriyan Yoga , Munzir Munzir
Published: February 2024

Sumber Daya Manusia (SDM) merupakan manusia yang dipekerjakan di sebuah organisasi sebagai penggerak, pemikir dan perencana untuk mencapai tujuan organisasi. Kinerja merupakan hasil fungsi pekerjaan atau kegiatan seseorang dalam suatu organisasi yang dipengaruhi oleh berbagai faktor untuk mencapai tujuan organisasi dalam periode waktu tertentu. Kinerja adalah keberhasilan personel, tim atau unit organisasi dalam mewujudkan sasaran strategic yang telah ditetapkan sebelumnya dengan perilaku yang diharapkan. Penilitian ini bertujuan untuk menganalisis dan mengidentifikasi kajian literatur atau literatur review yang menggunakan dua puluh artikel ilmiah yang bersumber dari Mendley dan Scholar Google.  Penilitian ini menggunakan metode penilitian literature review dengan pendekatan desktiptif (descriptive literature review).  Faktor-faktor yang mempengaruhi kinerja karyawan adalah kompensasi, motivasi kerja, dan lingkungan kerja. Hasil penilitian menemukan bahwa terdapat (1) kompensasi memiliki pengaruh terhadap kinerja karyawan, (2) motivasi kerja memiliki pengaruh terhadap kinerja karyawan dan (3), lingkungan kerja memiliki pengaruh terhadap kinerja karyawan. Selain itu, tujuan penulisan  artikel  ini  guna  membangun  hipotesis  pengaruh antar  variabel  untuk  digunakan pada  riset  selanjutnya
KINERJA KEUANGAN PERUSAHAAN: Telaah Rasio Keuangan (Studi Pada PT. Jati Jaya Perkasa Mandiri Maros)
Authors: Iskandar Moch Resky , Nasir Nasir , Sismar Andi , Difinubun Yusron
Published: February 2024

Penelitian ini bertujuan Untuk mengetahui rasio keuangan perusahaan. Untuk mengadakan penilaian berdasarkan analisis rasio keuangan agar penyusun rencana untuk kebijaksanaan yang akan datang dapat diperbaiki Jenis penelitian adalah deskriptif kuantitatif, yaitu penulis menggambarakan hasil observasi dan menganalisis data-data yang diperoleh di lapangan. analisa yang digunakan adalah analisis rasio keuangan terdiri dari Liquidity  Ratio, Leverage Ratio , Aktivity ratio, dan Profitability Ratio, Hasil penelitian menemukan bahwa rasio likuiditas  pada tahun 2021 sebesar 133,1 % , kemudian pada tahun 2022 tingkat likuiditas menurun  menjadi 124,7 % atau turun sebesar 8,83 %.. Untuk solvabilitas PT Jati Jaya Perkasa Mandiri pada tahun 2021 berada pada level 232,6% , untuk tahun selanjutnya pada tahun 2022 solvabilitas sebesar 339,6% atau meningkat sebesar 107% dari tahun sebelumnya. Untuk rasio rentabilitas pada tahun 2021 sebesar 21,42% , kemudian pada tahun 2022 rentabilitas  perusahaan mengalami peningkatan  sebesar 10,79% atau berada pada level 32,21%. Untuk cash rasio pada tahun 2021 sebesar 73,1 % , kemudian pada tahun 2022 cash rasio  perusahaan mengalami penurunan  sebesar 7 % atau berada pada level 66,1 %. Kinerja keuangan  yang dicapai oleh perusahaan dengan menggunakan rasio likuiditas , solvabilitas dan rentabilitas  sudah cukup baik dari tahun ke tahun mengalami peningkatan dan sudah mendekati standar industri yaitu 1:2 atau berada diatas 100%. Dan jika dilihat dari cash rasionya kemampuan perusahaan untuk memenuhi kewajiban lancar dengan kas kurang baik.
Nilai Informasi Laporan Keuangan pada Aspek Pengendalian Intern dan Pengawasan Keuangan
Authors: Manhuri Fitri , Jumame Santrinita Trhessya , Sunarmi Sunarmi
Published: February 2024

Laporan keuangan dikatakan berkualitas apabila memenuhi kriteria yang relevan dan dapat diandalkan. Laporan keuangan mempunyai kredibilitas jika mempunyai nilai prediktif atau umpan balik dan disajikan tepat waktu. Namun, kriteria yang relevan terpenuhi jika laporan keuangan dapat diuji, netral, dan andal, sehingga pelaporan memerlukan sumber daya keuangan untuk mengoperasikan sistem yang ada. Adapun jenis data yang digunakan dalam penelitian ini adalah data primer. Data primer adalah data yang diperoleh penulis melalui observasi atau pengamatan langsung dari perusahaan, baik itu melalui observasi, kuisioner dan wawancara secara langsung dengan pimpinan dan staf perusahaan sesuai dengan kebutuhan dalam penelitian ini. Data primer yang diperoleh pada penelitian ini adalah hasil pengisian kuisioner oleh responden, yaitu kepala dan staf sub bagian akuntansi/penatausahaan keuangan dan bendahara pada BPKAD Kabupaten Luwu. Berdasarkan hasil penelitian diperoleh pengujian secara simultan menunjukkan bahwa Pengendalian Intern Akuntansi dan Pengawasan Keuangan Daerah secara simultan berpengaruh terhadap Nilai Informasi Pelaporan Keuangan Daerah. Hasil uji parsial menunjukkan bahwa Pengendalian Intern Akuntansi dan Pengawasan Keuangan Daerah berpengaruh terhadap Nilai Informasi Pelaporan Keuangan Daerah
AUDIT INTERNAL PEMERINTAH DAERAH: Telaah Faktor Kualitas Audit Inspektorat.
Authors: Hasan Fahmi Juandry
Published: February 2024

Penelitian ini bertujuan untuk menilai secara empiris pengaruh tekanan waktu, motivasi, pengalaman, dan skeptisme profesional, terhadap kualitas audit pada auditor di Inspektorat Kabupaten Maluku Tengah.. Penelitian ini berjenis penelitian kuantitatif. Penarikan hipotesis penelitian menggunakan basis teori atribusi, didukung oleh penelitian-penelitian sebelumnya yang mempunyai kesamaan variabel. Jenis data yang digunakan adalah data primer hasil pembagian angket. Menggunakan teknik statistik deskriptif dan Regresi linear berganda berbantuan SPSS 25.0 untuk analisis data. Selain itu dalam menjaga normalitas dan mencegah hetersokedastisitas, penelitian ini menggunakan uji asumsi klasik. Penelitian berlokasi di Inspektorat. Hasil penelitian menemukan bahwa Tekanan waktu berpengaruh negatif dan signifikan terhadap kualitas audit pada inspektorat Kabupaten Maluku Tengah. Motivasi berpengaruh positif dan signifikan terhadap kualitas audit pada inspektorat Kabupaten Maluku Tengah. Pengalaman berpengaruh positif dan tidak signifikan terhadap kualitas audit pada inspektorat Kabupaten Maluku Tengah. Skeptisme profesional berpengaruh positif dan tidak signifikan terhadap kualitas audit pada inspektorat Kabupaten Maluku Tengah.
Investigating the Ability of Immersive Virtual Environments to Facilitate Occupant Thermal State Data Collection Involving Face Masks
Authors: Rentala Girish Srivatsa , Zhu Yimin
Published: February 2024

This study examines the capability of an immersive virtual environment (IVE–based) experimental protocol to support occupant thermal state (sensation, acceptability, and comfort) data collection when participants wear face masks. Specifically, the goal is to see if there is a change in local thermal states due to face covering and would such a change affect overall thermal states. A between-subject experiment was conducted with fifty-four participants (27 masked; 27 unmasked) who were exposed to three-step temperatures (18.3ºC, 23.8ºC, and 29.4ºC) in a climate chamber under both cooling and heating sequences. In masked IVE experiments, participants donned a face mask and viewed the chamber's virtual model on a head-mounted display. In contrast, in unmasked IVE experiments, participants didn't use a face mask. Skin temperatures and overall/local thermal state responses were collected during the experiments. They were then statistically compared between masked IVE and unmasked IVE experiments. The results suggest that forehead temperature was significantly different under all step temperatures in the cooling sequence, with mean forehead temperature being larger in masked IVE than in unmasked IVE experiments. Furthermore, in masked IVE experiments, thermal sensation in the forehead, neck, and upper-back increased while the thermal acceptability in those same skin sites decreased, but this difference was not statistically significant. Also, in masked IVE experiments, the overall thermal sensation increased, whereas both the overall thermal acceptability and comfort decreased when compared with unmasked IVE experiments. Nonetheless, this difference was not statistically significant. To summarize, wearing a face mask didn't affect the participant's overall and local thermal states in IVEs, although few statistical differences were observed in skin temperatures
Engineering Analysis Impact on Carbon Emission Reduction of an Infrastructure Project: A Case Study of Semantok Dam Project
Authors: Sentosa Gregorius Aji , Fajarwanto Agung , Widyastuti Amy Rachmadhani , Naufal Achmad Luthfi , Mahalia Ni Putu Pande Dhea Putri , Kadir Abdul Rahman , Amar Muhammad Yunus
Published: February 2024

Semantok Dam located in Semantok River Stream, Nganjuk District, East Java. Dominated by lowlands and mountains, the 1900-hectare fertile agricultural land will be irrigated by this nominated “The Longest Dam in Southeast Asia”. The construction of this three kilometers long dam requires enormous resources of rockfills as the dominant material to build the main dam body. While the process of excavation, mobilization, and material settings are the dominant contributor aspects of the project’s carbon footprint, at the same time this project encounter a challenge on insufficiency of existing quarry. This situation drives a comprehensive strategy not only to find the most efficient and accessible material, but also to minimize and mitigate environmental damage, ultimately by reducing the material carbon footprint. Thus, an innovative engineering solution is applied to overcome this challenge such as utilizing the available material in surrounding project site which is random rock soil by using geotechnical analysis tools for design optimization and material usage simulation also collaborating with Building Information Modeling (BIM) to visualize and calculate the estimated cost. Eventually, this analysis plays a big role in ensuring the environmental sustainability in an infrastructure project by deciding the appropriate alternative which produce the least carbon emission
Building Rooftop Analysis for Solar Panel Installation Through Point Cloud Classification - A Case Study of National Taiwan University
Authors: Pal Aritra , Chang Yun-Tsui , Chen Chien-Wen , Wu Chen-Hung , Kumar Pavan , Hsieh Shang-Hsien
Published: February 2024

As climate change intensifies, we must embrace renewable solutions like solar energy to combat greenhouse gas emissions. Harnessing the sun's power, solar energy provides a limitless and eco-friendly source of electricity, reducing our reliance on fossil fuels. Rooftops offer prime real estate for solar panel installation, optimizing sun exposure, and maximizing clean energy generation at the point of use. For installing solar panels, inspecting the suitability of building rooftops is essential because faulty roof structures or obstructions can cause a significant reduction in power generation. Computer vision-based methods proved helpful in such inspections in large urban areas. However, previous studies mainly focused on image-based checking, which limits their usability in 3D applications such as roof slope inspection and building height determination required for proper solar panel installation. This study proposes a GIS-integrated urban point cloud segmentation method to overcome these challenges. Specifically, given a point cloud of a metropolitan area, first, it is localized in the GIS map. Then a deep-learning-based point cloud classification model is trained to detect buildings and rooftops. Finally, a rule-based checking determines the building height, roof slopes, and their appropriateness for solar panel installation. While testing at the National Taiwan University campus, the proposed method demonstrates its efficacy in assessing urban rooftops for solar panel installation
Semi-Automatic Workflow for Air-Conditioning System Zoning and Simulation
Authors: Yang Yikun , Pan Yiqun , Suter Georg
Published: February 2024

Building information modeling (BIM) shows its potential in the performance driven design, where multiple design solutions are generated and selected against certain design goals. This paper proposes a workflow to generate and simulate multiple thermal zoning schemes toward a semi-automatic design process of air-conditioning (AC) system. Thermal zoning plays a pivotal role in the design thinking of engineers by synthesizing load calculation, equipment sizing, and pipe/duct layout. However, it is often done intuitively with influence on performance unknown at the initial stage. To make it quantitative, we decompose the zoning process into three levels (thermal/control/system) of space aggregation, joining both semantic and numeric characteristics. For the semantic part, space functions are considered by space labeling, accessibility, and adjacency. As to the numeric part, spaces are zoned based on their thermal response similarities, revealed by dynamic mode decomposition on simulated free-float temperature. Then, the system zoning is generated by rolling out convenient distribution network layouts, representing typical fan-coil or variable-air-volume systems. Variables at each level contribute to the "generative" zoning. Based on multiple zoning schemes, the configurations are serialized into EnergyPlus and Modelica inputs for co-simulation. Initial cost, energy consumption, and comfort level of conditioning join together for the zoning evaluation. The entire workflow is implemented in Grasshopper with self-developed plugins
Building’s Twin Reconstruction
Authors: Luschi Cecilia , Vezzi Alessandra
Published: February 2024

The work shows a process that starts from the digitization of cultural heritage and through analysis arrives at the subsequent diachronic holographic representation. The object of the study was the creation of two holograms of historical buildings: the church of St. Maria in Sovana with an interesting subsoil and the ruin of church of St. Francesco, attributed to Sangallo il Giovane in Pitigliano. However, the theoretical setting of the research is placed at due distance from the twin term. It has implications and meaning that are not matched by producing a digital copy, even a very high resolution one. The use of different cognitive technologies and the assembly of the various inputs in a digital model can never be defined as a twin of the original. Bearing in mind what has just been specified, the work was organized according to different levels of acquisition of cognitive data. Obtained from the survey and from historical studies the shape of the original state, a historical narrative interweaving of digital models has been created. The hologram is a three-dimensional and dynamic representation, which in the case of the church of San Francesco shows the reconstruction of the ancient architectural complex, visualizing the evolution of the studies of historical documents, up to the vision of today's ruin. For the church of S. Maria, the underground area is reconstructed through the geoelectric analysis of the subsoil and of the urban composition. Use of high detection technologies (GPR and HVNSR). The holographic of the artifact, promotes scientific divulgation and its dissemination sharing experience, it is not realized through device indeed, but thanks a holographic display
Blockchain-BPMN Integrated Framework for Construction Management
Authors: Ye Xuling , Tao Xingyu , Cheng Jack C. P. , König Markus
Published: February 2024

Implementing blockchain benefits various construction management processes, such as securing payments, enabling traceable design process, and enhancing information transparency in supply chain. However, blockchain implementation in construction is still in its infancy due to weak functionality of smart contracts, which are self-enforceable programs allowing iteration between external data and blockchain. In the context of construction management that embraces complex and dynamic business processes, smart contracts are currently designed based on specific and isolated functional requirements without considering the connection and execution logic between these functions. It leads to inefficient collaboration and even execution errors, thereby corrupting data quality and even causing business failure. Therefore, this paper proposes a Blockchain-BPMN (Business Process Model and Notation) integrated (BBI) framework for construction management. The framework poses two contributions. First, a BPMN-driven method is developed to design smart contracts supporting executing linked and logically connected business activities. Second, an access control strategy is integrated into smart contracts to safeguard the accessibility of sensitive business data in a blockchain environment. The BBI framework is validated in an actual BIM design collaboration scenario, and results show its feasibility and computational performance are acceptable. Several aspects for improvement and future directions are discussed in the end
A Systematic Review of the Impacts of Digitalization on Project Management
Authors: Zerafat Ailin , Daniel Emmanuel , Gyoh Louis
Published: February 2024

This article systematically reviews digitalization’s impacts on project management in the construction industry. The article discusses the challenges the construction industry in successfully applying digitalization during the construction phase, including high costs, subpar performance, low productivity, and sustainability issues. The article then outlines the research questions and methodology used to conduct the systematic review, including selecting acceptable research questions, selecting acceptable research questions, using a qualitative approach, and the content review approach. The study analyzed 21 papers and identified the primary research themes regarding the effects of digitalization on project management. The study found that digital technologies, such as smart building technology, digital twins, reality capture, and laser scanning, have positively impacted project management by increasing efficiency, accuracy, value, and safety. The study concludes that the construction industry must embrace digitalization to address its challenges and improve project management
Predictive Safety Monitoring for Lifting Operations with Vision-Based Crane-Worker Conflict Prediction
Authors: Wong Peter Kok-Yiu , Lam Chin Pok , Lee Yin Ni , Ting Chung Lam , Cheng Jack C. P. , Leung Pak Him
Published: February 2024

Construction industry has reported among the highest accident and fatality rates over the past decade. In particular, crane lifting is a notably hazardous operation on construction sites, causing fatal accidents like workers being struck by the boom or objects fallen from tower cranes. Manual monitoring by on-site safety officers is labour-intensive and error-prone, while incorporating computer vision techniques into surveillance cameras would enable more automatic and continuous monitoring of construction site operations. However, existing studies for lifting safety mainly detect the presence of individual objects (e.g. workers, crane components), while a methodology is needed to predict their potential collision more proactively before accidents happen. This paper develops a vision-based framework for predictive lifting safety monitoring, including three modules: (1) object detection and classification: targeting at hook and lifting materials to enable danger zone estimation, along with workers and their personal protective equipment; (2) worker movement tracking and prediction: analyzing the historical moving trajectory of each unique worker to foresee his/her future movement in certain period ahead; (3) multi-level safety assessment: issuing predictive warning in real-time upon any crane-worker conflict foreseen. The proposed framework is applicable to real-time site video processing and enables end-to-end lifting safety monitoring with instant alerting upon unsafe scenarios observed. Importantly, the proposed framework predicts the future movement of workers to proactively identify potential site hazard, in order to trigger earlier safety alert for more timely decision-making. With a large video dataset capturing tower crane operations, the proposed framework demonstrates competitive accuracy and computational efficiency in crane-worker conflict prediction, validating its practicality for real-time lifting safety monitoring
Computer Vision-Based Monitoring Framework for Forklift Safety at Construction Site
Authors: Abbas Muhammad Sibtain , Sabir Aqsa , Khan Nasrullah , Zaidi Syed Farhan Alam , Hussain Rahat , Yang Jaehun , Park Chansik
Published: February 2024

Efficient forklift operation is critical for construction site safety and project progress; yet, the construction industry deals with recurrent issues, including unauthorized forklift operation, operator drowsiness, visibility challenges, blind spots, and load placement errors. This paper introduces the "iSafe ForkLift," a comprehensive safety framework powered by computer vision, specifically designed to tackle these multifaceted safety challenges associated with forklift operations. The framework provides an array of integrated solutions, encompassing facial recognition for authorization, anomaly detection for behavior monitoring, stereo cameras for improved visibility, blind spot solutions, and load placement monitoring. Aligned with OSHA safety standards, it offers opportunities for enhanced forklift safety by addressing a broad spectrum of potential risks within a single, efficient framework. Systematically addressing multiple safety risks within this unified framework significantly elevates overall safety. Future studies should prioritize enhancing technology by merging computer vision with IoT to boost precision and safety, especially on challenging terrains, thereby elevating construction industry standards' reliability
Scheduling Optimization of Electric Ready Mixed Concrete Vehicles Using an Improved Model-Based Reinforcement Learning
Authors: Chen Zhengyi , Song Changhao , Zhang Xiao , Cheng Jack C. P.
Published: February 2024

Decarbonizing the construction sector has become an imperative global agenda, with electric machinery playing a pivotal role in realizing this objective. This research concentrates on devising an operational scheduling optimization method for electric ready-mixed concrete vehicles (ERVs) – a groundbreaking, eco-friendly intervention for the construction sector. We commence by outlining a systematic problem definition for the ERV operational process, considering the distinctive characteristics of electric vehicles and ready-mixed concrete (RMC) delivery tasks. The entire process is then conceptualized as a Markov decision problem (MDP), which enables sequential decision-making. We subsequently develop an enhanced model-based reinforcement learning technique, named parallel-masked-decaying Monte Carlo Tree Search (PMD-MCTS), for efficient resolution of the MDP. The entire system is authenticated via a real-world case study, and the PMD-MCTS's performance is juxtaposed against existing benchmarks. The results demonstrate the appropriateness of the proposed MDP formulation for tackling RMC delivery tasks. The PMD-MCTS algorithm and one of its ablation algorithms (PM-MCTS) have demonstrated superior performance compared to other benchmarks in either cost reduction or delay minimization, with PMD-MCTS requiring 30% less computation time than PM-MCTS
Extracting Information from Construction Safety Requirements Using Large Language Model
Authors: Tran Si , Khan Nasrullah , Kimito Emmanuel Charles , Pedro Akeem , Soltani Mehrtash , Hussain Rahat , Yoo Taehan , Park Chansik
Published: February 2024

The construction industry has long been recognized for its complex safety regulations, which are essential to ensure the well-being of on-site employees. However, navigating these regulations and ensuring compliance can be challenging due to the volume and complexity of the documents involved. This study proposes a novel approach to extracting information from construction safety documents utilizing Large Language Models (LLM), called CSQA, to provide real-time, precise answers to queries related to safety regulations. The approach comprises three modules: (1) the construction safety investigation module (CSI) collects safety regulations for building the information needed. By leveraging a collection of safety regulation PDFs, the system follows a process of text extraction, preprocessing, and global indexing for efficient search. (2) The safety condition identification module (SCI) retrieves the CSI database; after that, the LLM, with its extensive training, processes user queries, searches the indexed regulations, and retrieves pertinent information. (3) the safety information delivery (SID) would provide the answer to the user and incorporate a feedback mechanism to further refine system accuracy based on user responses. Preliminary evaluations reveal the system's superior performance over traditional search engines, owing to its ability to grasp query context and nuances. The CSQA presents a promising method for accessing safety regulations, with potential benefits including reduced non-compliance incidents, enhanced worker safety, and streamlined regulatory consultations in construction
Consistency Verification Between Cost and Geometric Information Based on IFC: Application on Structural Elements
Authors: Cassandro Jacopo , Mirarchi Claudio , Pavan Alberto , Donatiello Maria Grazia , ZANCHETTA CARLO
Published: February 2024

Cost estimation for tendering is one of the leading causes of legal disputes in the architecture, engineering, construction, and facilities management (AEC/FM) industry.
The lack of a standardised support procedure to verify the association of cost data with the objects model causes waste of time and inaccuracy in the cost estimation.
This research work, starting from a previous study where the research group integrated a cost domain in the IFC data schema, investigated the possible applications of this IFC based cost domain integrated with an IFC geometrical information model. The current paper investigates a specific case study focused on a structural model to verify current and future applications.
Furthermore, rules for BIM information requirements will be defined through the Information Delivery Specification (IDS) to ensure an easy way for humans and computers to understand it. This will allow to specify which data must be present in the geometric model to subsequently ensure validation and verification of uniqueness of the cost data associated with geometric data.
The results show the possibility to define a structured cost items in IFC associated through relationships to other entities and then verify their association to geometric data to guarantee its consistency and uniqueness
A Review of Computer Vision-Based Progress Monitoring for Effective Decision Making
Authors: Lan Roy , Sulbaran Tulio
Published: February 2024

Construction Progress Monitoring (CPM) is a significant aspect of project management aimed to align planned design with the actual construction on site, the process ensures that the project is well within the control of the stakeholders involved and ensures the project is completed complying with the construction documents, on time, and within budget. Despite how central progress monitoring is to attaining project success and advances in technology, the progress monitoring is majorly implemented manually, which requires manual retrieving and processing of site data to compare with the planned design. This manual process is both time-consuming and prone to errors. Automating the task of progress monitoring involving real-time data acquisition and timely information retrieval can assist the project managers for effective decision making to the successful delivery of the project. Thus, the objective of this research was to assess the impact of computer vision (CV) – based progress monitoring as a driver for effective decision-making in project management. A qualitative methodology was implemented for this research using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to review and analyze studies on the application of computer vision (CV). The study reviews studies of CV based CPM process, highlighting its benefits against the traditional method of progress and the limitation to its adoption. Research findings from this paper provide an increased understanding and have a broader scope on the application of computer vision-based progress monitoring
Semi-Automated Visual Quality Control Inspection During Construction or Renovation of Railways Using Deep Learning Techniques and Augmented Reality Visualization
Authors: Gounaridou Apostolia , Pantraki Evangelia , Dimitriadis Vasileios , Tsakiris Athanasios , Ioannidis Dimosthenis , Tzovaras Dimitrios
Published: February 2024

The construction industry stands to greatly benefit from the technological advancements in deep learning and computer vision, which can automate time-consuming tasks such as quality control. In this paper, we introduce a framework that incorporates two advanced tools - the Visual Quality Control (VQC) tool and the Digital Twin visualization with Augmented Reality (DigiTAR) tool - to perform semi-automated visual quality control in the construction site during the execution phase of the project. The VQC tool is a backend service that detects potential defects on images captured on-site using the Mask R-CNN algorithm trained on annotated images of concrete and railway defects. The surveyor, aided by the Augmented Reality (AR) technology through the DigiTAR tool, can in-situ confirm/reject the detected defects and propose remedial actions. All the quality control results are recorded in the relevant BIM model and can be viewed on-site overlaid on the physical construction elements. This solution offers a semi-automated visual inspection that can speed up and simplify the quality control process, especially in case of large linear infrastructures, illustrating the added value of AR-based applications in Digital Twins
Optimal Number of Cue Objects for Photo-Based Indoor Localization
Authors: Chung Youngsun , Gil Daeyoung , Lee Ghang
Published: February 2024

Building information modeling (BIM) is widely used to generate indoor images for indoor localization. However, changes in camera angles and indoor conditions mean that photos are much more changeable than BIM images. This makes any attempt at localization based on the similarity between real photos and BIM images challenging. To overcome this limitation, we propose a reasoning-based approach for determining the location of a photo by detecting the cue objects in the photo and the relationships between them. The aim of this preliminary study was to determine the optimal number of cue objects required for an indoor image. If there are too few cue objects in an indoor image, it results in an excessive number of location candidates. Conversely, if there are too many cue objects, the accuracy of object detection in an image decreases. Theoretically, a larger number of cue objects would improve the reasoning process; however, too many cue objects could lead to declining object detection performance. The experimental results demonstrated that of two to five cue objects, three cue objects is most likely to yield optimal performance
Multimodal Discourse Analysis of Visual Fake News Images
Authors: Babi Bello Alim
Published: February 2024

Social media is a powerful source of information. The spread of fake news on social media has both immediate and long-term effects on its users, who may be reluctant to share and post genuine news for fear that it, will be misrepresented. This study examines five visual fake news images that were selected for investigation from a variety of social media sources. Multimodal discourse analysis theories are used to evaluate fake news photographs and explain their meaning potential by using the three semiotic functions of - representational, interactional, and compositional. The most essential goals of the fake news image are to invite cooperation and persuasion in the social relationships between the personalities and the viewers. The use of news captions, positive language, questions, and short phrases are the main features of the analyzed fake news discovered.
An Assessment of the Contribution of the Agricultural Sector to the GDP of Kaduna State
Authors: W Wali Adam , A. Nuhu , M Mahmud B.
Published: February 2024

The performance of agriculture in every economy cannot be overemphasized. This is especially true as it forms part of the macroeconomic variables or growth indicators –the GDP. This paper assessed the performance of the agricultural sector on the growth or otherwise of the GDP of Kaduna state. The Secondary type of data was used for the assessment, where data from the outcome of the report of the Kaduna State Bureau of Statistics in collaboration with the National Accounts was collected and used. The data is a time series (2013-2015). The report covers major aggregates of State GDP under forty-two (42) activities at current 2013 to 2014 prices; but with more emphasis on the agricultural sector. KDGDP was computed as gross output minus intermediate consumption. Therefore, the study found out that the agricultural sector’s performance was significant, playing a vital role in the GDP of Kaduna state. Despite that in some quarters of 2014, some subsectors of agriculture recorded a decline, yet, the figures rose with some subsectors such as crop production and fishing in 2015. This concludes that the agricultural sector’s performance on the GDP of Kaduna state is an economic key player therein. And therefore remains the major contributing sector in Kaduna State over the three years.
Vaccination status and outcomes in critical COVID-19 patients
Authors: Nogueira Costa1 Pedro , Oliveira Pereira1 João , Higon Cañigral2 Aurea , Martinez Quintana2 Elena , Miguel Sanchez-Nieto2 Juan , Bayoumy Delis2 Pablo , Renedo Villarroya2 Ana , Lopez Gomez2 Laura , Alonso Fernandez2 Nuria , Carrillo Alcaraz2 Andrés
Published: February 2024

Objective: To analyze the clinical characteristics and outcomes of patients with COVID-19-related acute respiratory failure on the basis of their vaccination status at the time of ICU admission. Methods: We conducted a retrospective observational study using a prospective database of patients admitted to the ICU of a university hospital in the city of Murcia, in Spain, between January 1, 2021 and September 1, 2022. Clinical, analytical, and sociodemographic data were collected and analyzed on the basis of patient vaccination status. We adjusted for confounding variables using propensity score matching and calculated adjusted ORs and 95% CIs. Results: A total of 276 patients were included in the study. Of those, 8.3% were fully vaccinated, 12% were partially vaccinated, and 79.7% were unvaccinated. Although fully vaccinated patients had more comorbidities, partially vaccinated patients had higher disease severity. The proportion of patients with severe acute respiratory failure was higher in the unvaccinated group, followed by the partially vaccinated group. No significant differences were found among the different groups regarding complications, duration of ventilatory support, or length of ICU/hospital stay. In the sample selected by propensity score matching, the number of patients with severe complications and the in-hospital mortality rate were higher in unvaccinated patients, but the differences were not significant. Conclusions: This study failed to show a significant improvement in outcomes in critically ill COVID-19 patients vaccinated against SARS-CoV-2. However, the CIs were wide and the mortality point estimates favored patients who received at least one dose of COVID-19 vaccine.
Use of Healthcare Claims Data to Generate Real-World Evidence on Patients With Drug-Resistant Epilepsy: Practical Considerations for Research
Authors: Stamas Nicole , Vincent Tom , Evans Kathryn , Li Qian , Danielson Vanessa , Lassagne Reginald , Berger Ariel
Published: February 2024

Objectives: Regulatory bodies, health technology assessment agencies, payers, physicians, and other decision-makers increasingly recognize the importance of real-world evidence (RWE) to provide important and relevant insights on treatment patterns, burden/cost of illness, product safety, and long-term and comparative effectiveness. However, RWE generation requires a careful approach to ensure rigorous analysis and interpretation. There are limited examples of comprehensive methodology for the generation of RWE on patients who have undergone neuromodulation for drug-resistant epilepsy (DRE). This is likely due, at least in part, to the many challenges inherent in using real-world data to define DRE, neuromodulation (including type implanted), and related outcomes of interest. We sought to provide recommendations to enable generation of robust RWE that can increase knowledge of “real-world” patients with DRE and help inform the difficult decisions regarding treatment choices and reimbursement for this particularly vulnerable population. Methods: We drew upon our collective decades of experience in RWE generation and relevant disciplines (epidemiology, health economics, and biostatistics) to describe challenges inherent to this therapeutic area and to provide potential solutions thereto within healthcare claims databases. Several examples were provided from our experiences in DRE to further illustrate our recommendations for generation of robust RWE in this therapeutic area. Results: Our recommendations focus on considerations for the selection of an appropriate data source, development of a study timeline, exposure allotment (specifically, neuromodulation implantation for patients with DRE), and ascertainment of relevant outcomes. Conclusions: The need for RWE to inform healthcare decisions has never been greater and continues to grow in importance to regulators, payers, physicians, and other key stakeholders. However, as real-world data sources used to generate RWE are typically generated for reasons other than research, rigorous methodology is required to minimize bias and fully unlock their value.
Profesorowie pedagogiki i psychologii na uniwersytetach II Rzeczypospolitej
Authors: Przeniosło Małgorzata , Przeniosło Marek , Kosno Sara
Published: February 2024

W każdym z sześciu istniejących w okresie międzywojennym uniwersytetów funkcjonowały katedry o profilu pedagogicznym i psychologicznym. Zwykle ich charakter i nazewnictwo było niejednolite. W artykule przedstawiono portret zbiorowy profesorów stojących na czele wspomnianych katedr. Takich osób było 16 (Stefan Baley, Zygmunt Bielawski, Stefan Błachowski, Ludwik Chmaj, Antoni Danysz, Ludwik Jaxa Bykowski, Stanisław Kobyłecki, Mieczysław Kreutz, Zygmunt Bolesław Kukulski, Stanisław Łempicki, Marian Massonius, Zygmunt Mysłakowski, Bogdan Nawroczyński, Bogdan Suchodolski, Stefan Szuman i Władysław Witwicki). Międzywojenni profesorowie pedagogiki i psychologii na tle innych kierowników katedr uniwersyteckich byli grupą dość typową. Dotyczyło to m.in. wykształcenia uzyskanego często na więcej niż jednej uczelni, a także sposobu i okoliczności przechodzenia przez kolejne szczeble awansu naukowego i zawodowego. Były jednak także obszary, które wyróżniały profesorów interesujących nas specjalności. Przede wszystkim trzeba zwrócić uwagę na wyjątkowo dużą różnorodność wybieranych kierunków kształcenia przygotowujących do przyszłej pracy zawodowej. Oprócz pedagogiki lub/i psychologii większość osób przed objęciem katedry kształciła się zwykle także w zakresie innych dyscyplin, nie tylko pokrewnych. Dzięki temu duża część z nich była faktycznie badaczami interdyscyplinarnymi.
Tranzycja do macierzyństwa u kobiet w perspektywie biegu ich życia
Authors: Kuryś-Szyncel Karolina , Błachnio Aleksandra
Published: February 2024

Celem artykułu jest opisanie różnic w postrzeganiu przez kobiety przejścia do macierzyństwa na różnych etapach dorosłości. Problem badawczy dotyczył tego, czy i w jakim stopniu zmienia się znaczenie przejścia do macierzyństwa dla kobiet z różnych kohort urodzeniowych. Próba badawcza obejmowała matki z trzech kohort pokoleniowych: 50 kobiet we wczesnej dorosłości (M = 27,5), 50 kobiet w średniej dorosłości (M = 47,66) i 52 kobiety w późnej dorosłości (M = 69,35). Wyniki analizowano za pomocą jakościowych metod analizy danych, w tym analizy frekwencyjnej i jakościowej analizy narracyjnej. Na podstawie przeprowadzonych analiz stwierdzono, że kategoria przejścia do macierzyństwa jest cechą wspólną dla wszystkich badanych kobiet – we wczesnej, średniej i późnej dorosłości. W obu starszych pokoleniach niektóre kobiety wspominały narodziny pierwszego dziecka jako radzenie sobie ze zmianą. Z ich narracji wyodrębniono wskaźniki krytyczności: potencjalną ambiwalencję, nieprzewidywalność konsekwencji i długowieczność zmian w życiu. Wyniki pokazały, że pokolenie kobiet w późnej dorosłości wykazywało znacznie mniejsze trudności związane z własnym macierzyństwem. Dominantą semantyczną badanych narracji jest macierzyństwo jako branie odpowiedzialności za drugiego człowieka.
Udział w strajku szkolnym w świetle indywidualnego doświadczenia biograficznego młodzieży urodzonej pod koniec XIX wieku
Authors: Cybulska Kamila
Published: February 2024

W niniejszym artykule przyjęto za przedmiot badań doświadczenie indywidualne młodzieży, która brała bezpośredni udział w strajku szkolnym 1905 r. Dzięki analizie ego-dokumentów osób urodzonych pod koniec XIX wieku, podjęto próbę interpretacji roli i miejsca wydarzeń strajku szkolnego w indywidualnym doświadczeniu ludzi dorastających w atmosferze walki o tożsamość narodową i autonomię ziem polskich. Artykuł ma na celu ukazanie udziału młodzieży w strajku szkolnym jako doświadczenia formatywnego dla biografii indywidualnych jego uczestników. Istotne jest także pytanie o sferę symboliczną, związaną z przypisywaniem w narracjach autobiograficznych zdarzeniom 1905 roku konkretnych ról i znaczeń, które determinują ich miejsce w ego-dokumentach tworzonych w cyklu życia.
Przejawy pokory i skromności odzwierciedlone w losach oraz dorobku pedagogicznym Księdza Franciszka Blachnickiego
Authors: Żywczok Alicja
Published: February 2024

Artykuł stanowi rekonstrukcję biograficzną oraz propozycję interpretacji tej części dziedzictwa ks. Franciszka Blachnickiego, która dotyczy problematyki pokory i skromności, mieszczącej się w specyfice aksjologii i aretologii. Zaprezentowaniu wyników badań służy odpowiednia struktura artykułu. W jego części początkowej sprecyzowano zasadnicze pojęcia, podano założenia metodologiczne, a także nakreślono wizerunek ks. Franciszka Blachnickiego jako człowieka pokornego po to, by fakty biograficzne usytuować w szerszym kontekście. Następnie dokonano uściśleń, w wyniku których ukazano jego postrzeganie pokory i skromności. Opisano znaczenie pokory i skromności w procesie wychowania młodych ludzi oraz wyodrębniono przeciwieństwa tych cech odnalezione w dorobku Blachnickiego. Przekaz ten wzbogacono wskazówkami, które można uznać za sugestie etyczne, społeczne i wychowawcze Blachnickiego skierowane do współczesnych ludzi. Spuścizna ta stanowi oryginalne, inspirujące studium duchowe, dlatego warto zadbać o odpowiednie odczytywanie przez kolejne pokolenia zawartego w nim pouczenia moralnego oraz przesłania.
Wiara w cieniu śmierci. Obóz zagłady Treblinka II
Authors: Rusiniak-Karwat Martyna
Published: February 2024

Na podstawie wspomnień dziesięciu byłych więźniów obozu zagłady Treblinka II (Abrahama Jakuba Krzepickiego, Eddiego Weinsteina, Jankiela Wiernika, Jerzego Rajgrodzkiego, Tanhema Grinberga, Eliasza Rozenberga, Oskara Strawczyńskiego, Jechiela Rajchmana, Richarda Glazara i Samuela Willenberga) został pokazany stosunek do wiary i jej praktykowania w warunkach ekstremalnych. Z perspektywy bezpośredniego świadka zostały opisane reakcje ludzi, którzy szli na śmierć – ich modlitwy. Na przykładzie opisu przeżyć w obozie ocalałych zostało pokazane praktykowanie przez nich i ich współtowarzyszy niedoli zasad judaizmu: modlenie się i obchodzenie świąt w cieniu komór gazowych, ale także zwątpienie w Boga. Modlitwy i pieśni były też formą komunikacji pomiędzy więźniami, którzy pochodzili z różnych państw. Natomiast załoga niemiecka w obozie narzucała praktykowanie wiary więźniom w celach rozrywki jak i też, aby jeszcze bardziej ich poniżyć i pokazać, że to Niemcy są wszechmocni niczym Bóg.