The Relationship Between Types of Probation Supervision and Recidivism of Offenders Under Electronic Monitoring System

2021 ◽  
Vol 90 ◽  
pp. 149-170
Keyword(s):  
Monitoring System ◽  
Electronic Monitoring ◽  
Probation Supervision ◽  
The Relationship

Shear Strength Monitoring System Based on Measurement of Shear Wave Velocity and Moisture Content

2014 ◽  
Vol 635-637 ◽  
pp. 750-754
Author(s):  
Peng Hu ◽  
Qing Li ◽  
Yi Wei Xu ◽  
Nan Ying Shentu ◽  
Quan Yuan Peng
Keyword(s):  
Shear Strength ◽  
Moisture Content ◽  
Shear Wave ◽  
Monitoring System ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Bender Elements ◽  
Strength Measurement ◽  
Soil Shear Strength ◽  
The Relationship

Expound the importance of soil shear strength measurement at mudslide hidden point to release the loss caused by the disaster, explain the relationship between shear wave velocity, moisture content and shear strength, design the shear strength monitoring system combining the shear wave velocity measured by Piezoelectric bender elements and moisture content.

scholarly journals The actual operation assessment of the railway bridge superstructure using a mobile monitoring system

2018 ◽  
Vol 5 (4) ◽  
Author(s):  
Timofey Baranov ◽  
Evgeniy Tolstikov
Keyword(s):  
Monitoring System ◽  
Theoretical Calculations ◽  
Monitoring Systems ◽  
Railway Bridge ◽  
Mobile Monitoring ◽  
Dynamic Factors ◽  
Actual Operation ◽  
Stress Ratios ◽  
Relationship Of ◽  
The Relationship

Deviations in the operation of the operated bridge structures on the railway are detected when damage occurs. At the same time, early detection and prognosis of damage progress can be obtained using monitoring systems. The article presents the methods and technologies for the use of mobile monitoring systems for assessing the actual operation of the metal superstructure of the railway bridge with the main driving trusses. The hardware of the measuring complex is considered, the main measuring instrument is the glued electrical strain gauges. The monitoring system kept a continuous record of sensor readings for 28 days. To process the data received by the monitoring system, specialized software has been developed that systematizes the incoming information. Analysis of the actual supertructure operation is carried out by finding the relationship of stresses in the various elements of the superstructure, arising under the same load. This approach allowed us to exclude the factor of unknown intensity of the temporary load. The results of monitoring the work of the superstructure are given. In total, over 680 train passage records were analyzed, which allowed for a statistical description of the data. The theoretical values of the relationship of stresses in the elements of the superstructure are determined using the apparatus of the influence lines obtained by a numerical method. The conclusions are made about the distribution of deformations of the superstructure under temporary load and about the degree of compliance with theoretical calculations. The construction factors and the values of their statistical scatter are determined, the actual dynamic factors are statistically calculated. The construction factors calculated from the stress ratios lie in the range of 0.8-1.116. Dynamic factors are within 1.13 and do not exceed the rated values.

Comparison of SVM method for picking up the microseismic events collected by fiber-optic and electronic monitoring system

2021 ◽  
Author(s):  
Meng Wang ◽  
Fei Liu ◽  
Yiqiang Li ◽  
Jiahao Huo ◽  
Jinhui Yuan ◽  
...  
Keyword(s):  
Monitoring System ◽  
Electronic Monitoring ◽  
Fiber Optic ◽  
Microseismic Events

Employee perceptions of fairness toward IoT monitoring

2018 ◽  
Vol 48 (4) ◽  
pp. 504-516 ◽  
Author(s):  
Maryam Al-Hitmi ◽  
Karma Sherif
Keyword(s):  
Oil And Gas ◽  
Electronic Monitoring ◽  
Oil And Gas Industry ◽  
Employee Perceptions ◽  
Future Research ◽  
Universal Theory ◽  
Content Type ◽  
Perceptions Of Fairness ◽  
The Relationship

Purpose This paper aims to explore Internet of Things (IoT)-enabled monitoring in a multi-national petrochemical organization in Qatar and finds that the technology does not negatively influence employee perceptions of fairness, challenging current propositions on monitoring and highlighting the emerging role of culture, competition and paradoxical leadership in moderating the relationship between IoT-enabled monitoring and perceptions of fairness. Design/methodology/approach The authors adopted qualitative research as the methodological premise to explore the relationship between IoT-enabled monitoring and perceptions of fairness. They collected data from an oil and gas organization in Qatar to test the validity of the proposed hypotheses. Findings While I0T-enabled monitoring was perceived as pervasive, tracking every move and recording conversations, the diffusion of the technology throughout Qatar desensitized employees who felt it was the new reality around workspaces. The following three important factors reshaped employees’ perceptions toward IoT-enabled monitoring: a culture that is driven by productivity and strongly adheres by policies and standards to reach set goals; a highly competitive job market; and a paradoxical leadership who balances between the competition and lucrative rewards. Research limitations/implications The limitation of this research is that the authors conducted a case study in similar organizations within the oil and gas industry in the State of Qatar to refute the theory that electronic monitoring of employees in the workspace elicits perceptions of unfairness. Future research can conduct quantitative surveys of employee perceptions in different industries within different cultures to be able to generalize and evolve a universal theory. Practical implications The research findings shed light on the escalating pressure global competition exerts on employees that nervousness about pervasive monitoring systems is replaced with fear of job loss and analytics on monitoring data is welcomed as a means of readjusting behavior to meet performance expectations. Originality/value The case study is the first to highlight the desensitization of employees to monitoring and the increasing pressure competition plays in motivating them to exceed expectations.

scholarly journals An RFID-Based Automated Individual Perching Monitoring System for Group-Housed Poultry

2019 ◽  
Vol 62 (3) ◽  
pp. 695-704 ◽  
Author(s):  
Kailao Wang ◽  
Kai Liu ◽  
Hongwei Xin ◽  
Lilong Chai ◽  
Yu Wang ◽  
...  
Keyword(s):  
Body Weight ◽  
Monitoring System ◽  
Radio Frequency Identification ◽  
Laying Hens ◽  
Well Being ◽  
Load Cell ◽  
Commercial Application ◽  
Group Setting ◽  
The Relationship ◽  
Cell Module

Abstract. Perching is a natural behavior of poultry. Considerable research has been done to explore the relationship between group overall perch usage and well-being of laying hens. To quantify the potential cause-effect relationship on individual hens with different health or well-being status (e.g., keel bone deformation, foot pad lesion, social ranking) in a group, it is necessary to identify the perching behavior of individual birds. However, continuously monitoring individual birds in a group poses considerable challenges. To enable such research and potential commercial application, this study developed and validated a radio frequency identification (RFID) based automated perching monitoring system (APMS) for characterizing individual perching behaviors of group-housed poultry. The APMS consisted of an RFID module, a load cell module, and a round wooden perch. The RFID module was comprised of a high-frequency RFID reader, three customized rectangular antennas placed under the perch, and RFID transponders attached to the birds. The load cell module was comprised of a data acquisition system and two load cells supporting both ends of the perch. The daily number of perch visits (PV) and perching duration (PD) for individual birds were used to delineate perching behavior. Three identical experimental pens, five hens per pen, were equipped with the monitoring system. Two RFID transponders were attached to each hen (one per leg), and a distinct color was marked on the bird’s head for video or visual identification and validation. Performance of the APMS was validated by comparing the system outputs with manual observation and labeling over an entire day. Sensitivity and specificity of the system were shown to improve from 97.77% and 99.88%, respectively when using only the RFID module to 99.83% and 99.93% when incorporating weight information from the load cell module. Using this system, we conducted a preliminary trial on the relationship of perching behavior and body weight of laying hens, which revealed little effect of body weight but considerable variability in perching behavior among the individual hens. The study demonstrated that the APMS had excellent performance in measuring perching behaviors of individual birds in a group. The APMS offers great potential for delineating individual differences in perching behavior among hens with different social status or health conditions in a group setting. Keywords: Individual perching behavior, Laying hen, Load cell, Precision livestock farming, RFID, Welfare.

scholarly journals Low-Power Distributed Data Flow Anomaly-Monitoring Technology for Industrial Internet of Things

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2804 ◽  
Author(s):  
Han ◽  
Tian ◽  
Shi ◽  
Huang ◽  
Li
Keyword(s):  
Internet Of Things ◽  
Low Power ◽  
Monitoring System ◽  
Data Flow ◽  
Real Data ◽  
Communication Overhead ◽  
Distributed Data ◽  
Flow Monitoring ◽  
Industrial Use ◽  
The Relationship

. In recent years, the industrial use of the internet of things (IoT) has been constantly growing and is now widespread. Wireless sensor networks (WSNs) are a fundamental technology that has enabled such prevalent adoption of IoT in industry. WSNs can connect IoT sensors and monitor the working conditions of such sensors and of the overall environment, as well as detect unexpected system events in a timely and accurate manner. Monitoring large amounts of unstructured data generated by IoT devices and collected by the big-data analytics systems is a challenging task. Furthermore, detecting anomalies within the vast amount of data collected in real time by a centralized monitoring system is an even bigger challenge. In the context of the industrial use of the IoT, solutions for monitoring anomalies in distributed data flow need to be explored. In this paper, a low-power distributed data flow anomaly-monitoring model (LP-DDAM) is proposed to mitigate the communication overhead problem. As the data flow monitoring system is only interested in anomalies, which are rare, and the relationship among objects in terms of the size of their attribute values remains stable within any specific period of time, LP-DDAM integrates multiple objects as a complete set for processing, makes full use of the relationship among the objects, selects only one “representative” object for continuous monitoring, establishes certain constraints to ensure correctness, and reduces communication overheads by maintaining the overheads of constraints in exchange for a reduction in the number of monitored objects. Experiments on real data sets show that LP-DDAM can reduce communication overheads by approximately 70% when compared to an equivalent method that continuously monitors all objects under the same conditions.

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