Detection Of Potential Hazards Research Articles

Application of ground penetrating radar in potential hazards detection of levee

Abstract Ground-penetrating radar, utilizing electromagnetic wave technology, stands as a crucial geophysical exploration method for analyzing hydraulic engineering defects. In the context of identifying potential hazards in a levee within Yunfu, Guangdong province, GPR technology is deployed. This study delves into the radar’s ability to discern characteristics such as inadequate soil compactness, voids, as well as interference from metal pipes and wires. By scrutinizing these radar signatures, the primary causes underlying the development of cracks and uneven settlement across multiple sections of the levee are identified. The insights garnered from this analysis serve as valuable reference points for leveraging ground-penetrating radar technology in the detection of potential hazards within hydraulic engineering contexts.

Invited Session IV: Extended reality--applications in vision science and beyond: Using a driving simulator to evaluate the effects of vision impairment and assistive technology.

Detection of potential hazards is critical to safe driving but is very difficult to evaluate in real-world driving situations because there is no control over if, when or where hazards might appear. Moreover, gaze tracking can be challenging in the varying environmental conditions of real-world driving. In contrast, driving simulators provide a safe, controlled, repeatable environment in which to study the effects of vision impairment and assistive technologies. Scenarios can be designed to probe specific aspects of the vision loss and can include situations that would be dangerous in the real world. This talk will summarize how we have used driving simulators to evaluate gaze behaviors and driving responses to potential hazards at mid-block locations and at intersections (including gaze tracking across a 180-degree field of view) for drivers with different kinds of visual field loss and for a variety of assistive devices, including optical devices (peripheral prism glasses and bioptic telescopes) and prototype vibro-tactile hazard warning systems. Using linked pedestrian and driving simulators we have attempted to create more realistic pedestrian hazard scenarios and have evaluated the effects of vision impairment on interactions between drivers and human-controlled, interactive pedestrians within the virtual environment.

Review on the Use of Satellite-Based Radar Interferometry for Monitoring Mining Subsidence in Urban Areas and Demographic Indicators Assessment

Abstract Mining activities represent one of the main causes leading to subsidence in the natural and urban environment. Sustainable urban planning and detection of potential hazards in mining areas involve the use of adequate instruments such as the continuous monitoring of land subsidence. The complexity of urban environment demands the utilization of new methods for monitoring and quantifying the effects of the mining processes. In the last decades, considering the technological developments from the remote sensing domain, the Synthetic Aperture Radar Interferometry (InSAR) techniques offer the opportunity for early detection and continuous monitoring of subsidence in mining areas, including urban centers. Considering various parameters of mining subsidence monitoring, a review of several tens of studies realized in different mining sites, based on InSAR techniques, is presented. As mining subsidence in urban areas has a direct impact on the quality of life, the review is completed with demographic indicators assessment, followed by a study case on the dynamics of the population in an urban mining area from Romania, Ocnele Mari.

Challenges in Hazard Detection for Commercial Motor Vehicle Drivers: A Driving Simulator Training Study

There are few research studies that have assessed the hazard detection (HD) challenges of experienced, skilled drivers. This paper presents the pilot study results of an HD training program, Commercial Driver Assessment and Training System (CDATS), developed for commercial motor vehicle (CMV) drivers. The training involved simulation-based videos that highlight potential vehicle, pedestrian, and visually hidden hazards during unprotected intersection maneuvers: left-turn, right-turn, and straight-thru. Low-fidelity driving simulations were designed to reinforce video lessons and increase the expectation and detection of potential hazards. Training efficacy was assessed using a driving simulator HD task presented to short-haul CMV drivers ( N = 16) at pre-/post-assignment to CDATS training or a control condition. Results suggested that CMV drivers had highest HD task accuracy (% correct) for vehicle hazards and lowest accuracy for visually hidden hazards. Performance for pedestrian hazards was dependent on the intersection maneuver, with performance decreases for left-turn, right-turn and straight-thru intersections, respectively. Post-test results suggested overall HD improvement in the CDATS training group with no change in the control group; however, there was no significant change in relative hazard type by intersection maneuver pattern. Similar to prior research, experienced CMV drivers may also exhibit challenges in HD, particularly for visually hidden and visible pedestrian hazards, and may benefit from HD training.

Early warning of hazard for pipelines by acoustic recognition using principal component analysis and one-class support vector machines

This paper proposes a method for early warning of hazard for pipelines. Many pipelines transport dangerous contents so that any damage incurred might lead to catastrophic consequences. However, most of these damages are usually a result of surrounding third-party activities, mainly the constructions. In order to prevent accidents and disasters, detection of potential hazards from third-party activities is indispensable. This paper focuses on recognizing the running of construction machines because they indicate the activity of the constructions. Acoustic information is applied for the recognition and a novel pipeline monitoring approach is proposed. Principal Component Analysis (PCA) is applied. The obtained Eigenvalues are regarded as the special signature and thus used for building feature vectors. One-class Support Vector Machine (SVM) is used for the classifier. The denoising ability of PCA can make it robust to noise interference, while the powerful classifying ability of SVM can provide good recognition results. Some related issues such as standardization are also studied and discussed. On-site experiments are conducted and results prove the effectiveness of the proposed early warning method. Thus the possible hazards can be prevented and the integrity of pipelines can be ensured.

Using Variance Analysis to Detect Hazards in a Bar-Code–Assisted Medication Preparation Process

Medication errors have received significant attention, with studies pinpointing problems in the physician ordering, pharmacy dispensing, and nurse administering processes. Yet, the nursing process for preparing medications, which typically occurs in a medication room on the unit, has not received much attention. This process is deceptively complex, and without proper design, it could break down at numerous points. Prospective hazard analysis methods allow the detection of potential hazards during the planning, assessment, and design phases of a process or technology. A specific technique-variance analysis-is used within one type of prospective hazard analysis, the sociotechnical systems analysis (STSA). STSA provides guidance to (1) analyze existing or planned systems to understand the social, technical, and environmental system components; (2) collect and analyze the system data; and (3) use the analysis to design or redesign the system. The STSA variance analysis is an additional tool that health care clinicians, administrators, and risk managers can use to proactively identify hazards for control. Although this larger analysis is more time consuming, it forces the analysts to conduct a true systems analysis before implementing technical, social, environmental, or organizational changes.

Preoperative Detection of Potential Hazards in Aortic Surgery

Preoperative Detection of Potential Hazards in Aortic Surgery

Detection of Potential Hazards at Different Phases of Fish and Prawn Processing Plants in Khulna

Frozen fish and prawns occupy the highest rank among the export commodities. Export market of frozen fish/prawn totally depends on the freshness of the commodity. In order to give quality assurance of frozen fish and prawns of Bangladesh, the HACCP system is needed for different mechanisms of processing and consumption. In the present investigation, a total of 10 critical points were identified with farm to processing plants. The identification of potential hazards at different phases (catch and storage at fishing area, transportation, prior to processing, factory hygiene, processing, freezing, packaging, storage and shipment and storage at shipping area) of fish and prawn shrimp processing, and implementation of Hazard Analysis Critical Control Points (HACCP) system in this industry is the only weapon which can increase the demand of fish and prawns of Bangladesh in export market. 
 
 Key words: Potential hazards, critical control points, HACCP, Fish processing plants 
 
 DOI: 10.3329.bjsir.v43i1.864 
 
 Bangladesh J. Sci. Ind. Res. 43(1),131-138, 2008