Gotowa bibliografia na temat „Tikrit Location Command Project”

Construction project completion and acceptance of environmental protection, fugitive emissions of air pollutants monitoring sites based on the Integrated emission Standard of air pollutants (GB16297-1996) and Technical guidelines for fugitive emission monitoring of air pollutants and the relevant technical documents. The main source of fugitive emissions was production equipment obsolete, unreasonable design, operational errors, improper command and poor management. Existing problems: too theoretical, poor operability, from monitoring sites to point measured project location far, representative is not strong. Recommendations that distribution specification,always pay attention to fugitive emissions sampling,scientific and rational way to find the maximum concentration, Monitoring points arrangement as far as possible with less points to achieve better representative monitoring data .

A GPS tracker through HF radio using FSK method for Blue Force Tracking (BFT) application was developed. The project aims to transmit and receive the location information which is obtained from the GPS data. The system used frequency range of 500 Hz to 2000 Hz for modulating and demodulating the GPS data using FSK method. The smallest frequency gap between characters without affecting the accuracy of the output is 100 Hz, but the transmission time per character must be set to 100 ms. The transmission speed was investigated to find the optimum speed of the system by varying the delay command in the program. The system can accurately transmit and receive the location data in 1350 ms per coordinate. In general, the developed system successfully maintains the performance of transmitting and receiving the location information which can be applied for the future advancement of the BFT.

Voice communication is the main channel to exchange information between pilots and Air-Traffic Controllers (ATCos). Recently, several projects have explored the employment of speech recognition technology to automatically extract spoken key information such as call signs, commands, and values, which can be used to reduce ATCos’ workload and increase performance and safety in Air-Traffic Control (ATC)-related activities. Nevertheless, the collection of ATC speech data is very demanding, expensive, and limited to the intrinsic speakers’ characteristics. As a solution, this paper presents ATCO2, a project that aims to develop a unique platform to collect, organize, and pre-process ATC data collected from air space. Initially, the data are gathered directly through publicly accessible radio frequency channels with VHF receivers and LiveATC, which can be considered as an “unlimited-source” of low-quality data. The ATCO2 project explores employing context information such as radar and air surveillance data (collected with ADS-B and Mode S) from the OpenSky Network (OSN) to correlate call signs automatically extracted from voice communication with those available from ADS-B channels, to eventually increase the overall call sign detection rates. More specifically, the timestamp and location of the spoken command (issued by the ATCo by voice) are extracted, and a query is sent to the OSN server to retrieve the call sign tags in ICAO format for the airplanes corresponding to the given area. Then, a word sequence provided by an automatic speech recognition system is fed into a Natural Language Processing (NLP) based module together with the set of call signs available from the ADS-B channels. The NLP module extracts the call sign, command, and command arguments from the spoken utterance.

As the increase use of smart phones protecting the smart phones from intruders is the challenging part. In this paper we are came up with application that is used to find the lost device by SMS command. The Mobile Anti-Theft is made for the benefits of the people for finding their device when lost using SMS commands. This project is able to locate the lost device and able to send the current location of device to the user. Using this application we can find the lost mobile phones without paying for any service in a cost efficient manner. It can also able to take the picture of the culprit who stole the mobile phone using both front and rear cameras.

Search and rescue operations can range from small, confined spaces, such as collapsed buildings, to large area searches during missing person operations. K9 units are tasked with intervening in such emergencies and assist in the optimal way to ensure a successful outcome for the mission. They are required to operate in unknown situations were the lives of the K9 handler and the canine companion are threatened as they operate with limited situational awareness. Within the context of the INGENIOUS project, we developed a K9 vest for the canine companion of the unit, aiming to increase the unit’s safety while operating in the field, assist the K9 handler in better monitoring the location and the environment of the K9 and increase the information provided to the Command and Control Center during the operation.

AbstractThe North Slope of Alaska borders on two arctic seas, the Beaufort Sea and Chukchi Sea, with a total shoreline length of approximately 6,000 km. Oil exploration and production facilities are close to the coast, and the risk of spilled oil reaching the coast is increasing. The North Slope coast is a challenging location for spill response as the coastal areas are ice-covered much of the year and subject to variable ice cover during the open-water season. In addition, the shoreline is highly complex and rapidly changing because of melting of permafrost. The North Slope Coastal Imagery Initiative developed an online, decision support tool for spill preparedness and Incident Command decision making. The online tool makes more than 16,000 high-resolution images and 30 hours of high-resolution videography available to Incident Command in the event of a spill. Such high-resolution imagery is extremely useful in providing situational awareness for personnel unfamiliar to the Arctic and for tactical response planning. The resolution of the imagery is much higher than typical shoreline mapping or satellite imagery and, as such, eliminates ambiguity in interpretation when developing the most appropriate response strategies. The project provides a consensus building tool for spill response.

The existing tower crane positioning layout mainly depends on the experience of construction personnel, and the best tower crane positioning can be found through a large number of manual data calculation. This manual method is time-consuming and impractical. In view of this, aiming at the current situation that building information modeling (BIM) software can only obtain the relative coordinates of components, this article puts forward the key technology of importing computer-aided design (CAD) graphics into geographic information system (GIS) software to automatically obtain the world coordinate information. By clarifying the transfer relationship between the component material supply point, the component initial positioning point, and the tower crane optional positioning point, as well as the cooperative relationship between each positioning point and the tower crane operation, the tower crane positioning optimization model is formed, and the firefly algorithm is used to automatically calculate and generate the best positioning layout method of the tower crane on the project site. In this study, the vertical transportation and positioning of components are studied, and intelligent construction is formed by integrating information technology. It can further enrich the functions of perception, analysis, decision-making, and optimization; realize the decision-making intelligence of industrial buildings; and achieve the organic unity of engineering construction execution system and decision-making command system.

Introduction There is a need to develop harmonized procedures and a Minimum Data Set (MDS) for cross-border Multi Casualty Incidents (MCI) in medical emergency scenarios to ensure appropriate management of such incidents, regardless of place, language and internal processes of the institutions involved. That information should be capable of real-time communication to the command-and-control chain. It is crucial that the models adopted are interoperable between countries so that the rights of patients to cross-border healthcare are fully respected. Objective To optimize management of cross-border Multi Casualty Incidents through a Minimum Data Set collected and communicated in real time to the chain of command and control for each incident. To determine the degree of agreement among experts. Method We used the modified Delphi method supplemented with the Utstein technique to reach consensus among experts. In the first phase, the minimum requirements of the project, the profile of the experts who were to participate, the basic requirements of each variable chosen and the way of collecting the data were defined by providing bibliography on the subject. In the second phase, the preliminary variables were grouped into 6 clusters, the objectives, the characteristics of the variables and the logistics of the work were approved. Several meetings were held to reach a consensus to choose the MDS variables using a Modified Delphi technique. Each expert had to score each variable from 1 to 10. Non-voting variables were eliminated, and the round of voting ended. In the third phase, the Utstein Style was applied to discuss each group of variables and choose the ones with the highest consensus. After several rounds of discussion, it was agreed to eliminate the variables with a score of less than 5 points. In phase four, the researchers submitted the variables to the external experts for final assessment and validation before their use in the simulations. Data were analysed with SPSS Statistics (IBM, version 2) software. Results Six data entities with 31 sub-entities were defined, generating 127 items representing the final MDS regarded as essential for incident management. The level of consensus for the choice of items was very high and was highest for the category ‘Incident’ with an overall kappa of 0.7401 (95% CI 0.1265–0.5812, p 0.000), a good level of consensus in the Landis and Koch model. The items with the greatest degree of consensus at ten were those relating to location, type of incident, date, time and identification of the incident. All items met the criteria set, such as digital collection and real-time transmission to the chain of command and control. Conclusions This study documents the development of a MDS through consensus with a high degree of agreement among a group of experts of different nationalities working in different fields. All items in the MDS were digitally collected and forwarded in real time to the chain of command and control. This tool has demonstrated its validity in four large cross-border simulations involving more than eight countries and their emergency services.

Background: In an earthquake situation, medical response communities such as field and referral hospitals are challenged with injured victims’ identification and tracking. Materials and Methods: In our project, a patient tracking platform (PTP) was developed where first responders triage the patients with an electronic tag that report the location and some information of each patient during his/her movement. This platform includes: 1) Near Field Communication (NFC) tags (ISO 14443), 2) Smart mobile phones (Android-based version 4.2.2), 3) Base station laptops (Windows), 4) Server software, 5) Android software to use by first responders, 5) Disaster Command software, and 6) System Architecture. Results: Our model has been completed through literature review, Delphi technique, focus group, design the platform, and implementation in an earthquake exercise. Test and evaluation of PTP platform were done collaborating with Red Cross staff successfully. Conclusion: It is demonstrated the robustness of the patient tracking platform (PTP) in tracking six patients in a simulated earthquake situation in the yard of the relief and rescue department of Isfahan’s Red Crescent.

ABSTRACT This paper will describe the online cataloging of oil spill equipment that has taken place on the West Coast of the United States. A collaborative effort, the cataloging project was developed as a Northwest ad hoc undertaking to meet the equipment-listing requirement of the Area Contingency Plan. The intent was to assemble Oil Spill Response Organizations (OSROs) equipment lists into an Excel® spreadsheet format. Project participants in Washington and Oregon began equipment listing and over time, the process expanded to new members in California and Canada. Individual owners of equipment keep the data up-to-date. All equipment-location moves and acquisition changes are posted to the Internet site, yielding a current resource inventory that can be easily accessed 2417. The computer allows this equipment to be displayed, sorted by type, location, and tracked by date/time. The Excel® spreadsheet data can easily be manipulated to accurately tabulate, among other things, how much boom is available or in use, how much oil can be recovered, and how much oil storage is available. Hard copy equipment lists, which soon became outdated, are a thing of the past. The spreadsheets are used on a weekly basis for drill and spill applications as a tool to assist the Incident Command System's (ICS) Operation, Planning and Logistic sections to assemble, track and order specialized response equipment. The states of Washington and Oregon are using the list as a “database of record.” This is a great tool for the ICS Situation Unit when filling out the Incident Status Summary (ICS Form 209). In addition, individual lines of equipment or equipment systems can easily be printed onto ICS T-cards from Excel® by using a mail-merge program. A uniform Excel®-formatted response-equipment list is flexible, simple to use and easy to access. Undoubtedly, it has contributed to improving response management in the Pacific Northwest.

Abstract This descriptive chapter highlights the organization and functioning of the Rapid Action Force, or RAF. After briefly underscoring the hierarchy within which the Force operates, and its position as a subsidiary of the CRPF, the chapter uses data from the Armed Conflict Location & Event Data Project (ACLED) and the Times of India archive to understand personnel deployments. Then, it presents a brief case study as well as information gleaned through qualitative interviews about the Force’s role during the 2016 Haryana reservation agitation. It points to certain challenges that may moderate the Rapid Action Force’s agility, including resource deficits, a lack of coordination between the Center and states about deployment, the Force’s inability to retain organizational command during riot-like situations, and political considerations that make policymakers hesitant about seeking assistance about addressing law and order from the federal government.

The large fires that have occurred in recent years around the World have shown that the management of these events becomes much more difficult when the extension of the burnt area or the location of the fire fronts, among other fundamental information for those managing operations in theatre, is not known. In addition, the large involvement of firefighting resources often challenges the operability of the communications system, sometimes making it dysfunctional or with limited operability. This was a reality seen in several large fires, from which we highlight the Fire of Pedrógão Grande that occurred in Portugal in June 2017. Aware of the need to improve operational technology for fire monitoring, the Eye in the Sky Project has been developed. Our approach within this project is to design and develop an easy to deploy kit that can be launched from anywhere and fulfil these needs, providing quality real-time aerial imagery of the wildfires and guaranteeing emergency communications. The proposed solution consists of a high-altitude balloon that will carry a flying wing unmanned aerial vehicle with two different high-value types of payloads that meet these two specific functions of imagery collection in the visible and infrared ranges and communications repeater. The authors like to refer to the Eye in the Sky solution as a satellite dedicated to a specific fire. Naturally, the development of such solution raises several challenges, particularly in terms of the operational functioning of this solution, the optimised use of the balloon/glider pair with the associated payload, the capture, automatic detection of the fire images and their georeferencing, and the communications system between the payload, the ground station and the users in the command centre. The several challenges that have arisen in the development of this solution, as well as the current developments, are hereby exposed.

It is generally recognised that future Moon landing platforms will require a “global access” capability. That means being able to land precisely at any location on the Moon on various types of terrains, potentially hazardous for the Lander. To do that, future Lander systems will require a Hazard Detection and Avoidance (HDA) capability. The HDA function analyses the terrain topography to identify landing hazards (roughness, large slopes, shadowed areas). It commands the sensors (scanning Lidar and camera), processes the sensor data, reconstructs the terrain topography, generates surface hazard maps for slope, roughness and shadow, and combines this information to recommend a safe landing site meeting all the safety and Lander manoeuvrability constraints. An important challenge for the HDA function is the need for motion compensation. The acquisition of the scanning Lidar data takes several seconds and the Lander is moving (in both attitude and translation) during this process. The Lidar measurements appear “distorted” due to the change of relative pose during the scan time. The HDA function thus relies on the outputs of the navigation system for processing the sensor measurements and to actively command the sensor to maintain the desired coverage and resolution. The integration of navigation and HDA components is key to achieve the required hazard detection reliability and to enable accurate retargeting toward the identified target. Such landing platforms typically baseline the use of optical navigation for the descent and landing operations. The validation of the integration between this optical navigation system and the HDA system is an important challenge. The validation of the interaction requires the navigation to produce flight-representative state estimation performance, which requires flight-representative image and sensor inputs. A Hardware-in-the-Loop (HIL) test campaign had previously been performed in a scaled dynamic environment to demonstrate system integration and real-time operation. The integrated navigation and HDA system was tested in NGC’s Landing Dynamic Test Facility (LDTF). The LDTF consists of a 6-degree of freedom robotic arm mounted on a linear rail, surface mock-ups, and a dedicated lighting system. The prototype payload was mounted at the end effector of the robot. The LDTF is capable of reproducing realistic, but scaled, landing trajectories along the lunar surface mock-up. The primary objective of the dynamic testing was to perform the demonstration of the motion compensation function, i.e., the ability to process Lidar and camera measurements in real-time considering the Lander motion during the scanning process. For that matter, the test campaign included a series of the tests with incremental complexity, ranging from simple static tests to axis per axis isolated motion (in both translation and angular rate) to nominal landing trajectories with 6-DoF motion. High rate cases were also run to identify the limits of the system. Such testing however suffers from scaling limitations. Lidar sensors have an absolute range measurement error which does not scale down when the measured range is small. Applying a scaling factor on the Lidar range measurement has the effect of artificially amplifying the range measurement error. In the particular context of the system lab testing, this error amplification factor means that the functionality and the integration of the HDA system can be demonstrated, but that quantitative slope and roughness performance are not representative of the actual system performance at full scale. The sensor measurement performance is degraded, relatively speaking, with respect to the dimensions of the actual mission. The test campaign did nevertheless demonstrate the ability to reconstruct terrain slope using measurements taken from a moving Lander to the expected level of accuracy considering the scaling effects on range measurement noise. The HIL test campaign led to the identification of several paths of improvement which were addressed in the following project development phase. First, it was identified that the implemented formulation of the image processing function measurement update did not perform as expected when there is little or no motion along the boresight axis of the camera due to a singularity in the solution. Second, the need to inject an altimeter measurement to stabilise the vertical channel was demonstrated. The proposed solution consists of using the Lidar sensor as a laser altimeter when it is not used for HDA purposes in order to feed the navigation filter, provide the required observability of the distance to ground and solve for the scale. Finally, it was also identified that the execution rate of the image processing had to be increased. In order to maintain feature tracking at angular rates of up to 3 deg/s or more, the image processing rate had to be increased to a rate which is not achievable with a pure software implementation on the identified processor. The identified solution was to migrate some of the image processing subroutines on the FPGA co-processor. The identified improvements have been implemented and integrated in the prototype system. A full scale demonstration campaign of the system on a small UAV is currently under preparation. This will enable system performance quantitative assessment as the scaling limitations will be removed. The paper will highlight the status of the integration and results of the full-scale demonstration of the system on a UAV.