Development of a New Welding Product Quality Control and Management System Model for China

The Chinese welding industry is growing every year due to rapid development of the Chinese economy. Increasingly, companies around the world are looking to use Chinese enterprises as their cooperation partners. However, the Chinese welding industry also has its weaknesses, such as relatively low quality and weak management. A modern, advanced welding management system appropriate for local socio-economic conditions is required to enable Chinese enterprises to enhance further their business development. The thesis researches the design and implementation of a new welding quality management system for China. This new system is called ‗welding production quality control management model in China‘ (WQMC). Constructed on the basis of analysis of a survey and in-company interviews, the welding management system comprises the following different elements and perspectives: a ‗Localized congenital existing problem resolution strategies‘ (LCEPRS) database, a ‗human factor designed training system‘ (HFDT) training strategy, the theory of modular design, ISO 3834 requirements, total welding management (TWM), and lean manufacturing (LEAN) theory. The methods used in the research are literature review, questionnaires, interviews, and the author‘s model design experiences and observations, i.e. the approach is primarily qualitative and phenomenological. The thesis describes the design and implementation of a HFDT strategy in Chinese welding companies. Such training is an effective way to increase employees‘ awareness of quality and issues associated with quality assurance. The study identified widely existing problems in the Chinese welding industry and constructed a LCEPRS database that can be used in efforts to mitigate and avoid common problems. The work uses the theory of modular design, TWM and LEAN as tools for the implementation of the WQMC system.

Interactions between the cholinergic and dopaminergic system during the production of ultrasonic vocalizations in rats

Rats produce ultrasonic vocalizations that can be categorized into two types of ultrasonic calls based on their sonographic structure. One group contains 22-kHz ultrasonic vocalization (USVs), characterized by relatively constant (flat) frequency with peak frequency ranging from 19 to 28-kHz, and a call duration ranging between 100 – 3000 ms. These vocalization can be induced by cholinomimetic agents injected into the ascending mesolimbic cholinergic system that terminates in the anterior hypothalamic-preoptic area (AH-MPO) and lateral septum (LS). The other group of USVs contains 50-kHz USVs, characterized by high peak frequency, ranging from 39 to 90-kHz, short duration ranging from 10-90 ms, and varying frequency and complex sonographic morphology. These vocalizations can be induced by dopaminergic agents injected into the nucleus accumbens, the target area for the mesolimbic dopaminergic system. 22-kHz USVs are emitted in situations that are highly aversive, such as proximity of a predator or anticipation of a foot shock, while 50 kHz USVs are emitted in rewarding and appetitive situations, such as juvenile play behaviour or anticipation of rewarding electrical brain stimulation. The activities of these two mesolimbic systems were postulated to be antagonistic to each other. The current thesis is focused on the interaction of these systems indexed by emission of relevant USVs. It was hypothesized that emission of 22 kHz USVs will be antagonized by prior activation of the dopaminergic system while emission of 50 kHz will be antagonized by prior activation of the cholinergic system. It was found that injection of apomorphine into the shell of the nucleus accumbens significantly decreased the number of carbachol-induced 22 kHz USVs from both AH-MPO and LS. Injection of carbachol into the LS significantly decreased the number of apomorphine-induced 50 kHz USVs from the shell of the nucleus accumbens. The results of the study supported the main hypotheses that the mesolimbic dopaminergic and cholinergic systems function in antagonism to each other.

A model of Distributed Ayurvedic Diagnosis and Therapy System for Hridroga Using Agents

Diagnosis of Hridroga (cardiac disorders) in Ayurveda requires the combination of many different types of data, including personal details, patient symptoms, patient histories, general examination results, Ashtavidha pareeksha results etc. Computer-assisted decision support systems must be able to combine these data types into a seamless system. Intelligent agents, an approach that has been used chiefly in business applications, is used in medical diagnosis in this case. This paper is about a multi-agent system named “Distributed Ayurvedic Diagnosis and Therapy System for Hridroga using Agents” (DADTSHUA). It describes the architecture of the DADTSHUA model .This system is using mobile agents and ontology for passing data through the network. Due to this, transport delay can be minimized. It is a system which will be very helpful for the beginning physicians to eliminate his ambiguity in diagnosis and therapy. The system is implemented using Java Agent DEvelopment framework (JADE), which is a java-complaint mobile agent platform from TILab.

Rotation Invariant Real-time Face Detection and Recognition System

In this report, a face recognition system that is capable of detecting and recognizing frontal and rotated faces was developed. Two face recognition methods focusing on the aspect of pose invariance are presented and evaluated - the whole face approach and the component-based approach. The main challenge of this project is to develop a system that is able to identify faces under different viewing angles in realtime. The development of such a system will enhance the capability and robustness of current face recognition technology. The whole-face approach recognizes faces by classifying a single feature vector consisting of the gray values of the whole face image. The component-based approach first locates the facial components and extracts them. These components are normalized and combined into a single feature vector for classification. The Support Vector Machine (SVM) is used as the classifier for both approaches. Extensive tests with respect to the robustness against pose changes are performed on a database that includes faces rotated up to about 40 degrees in depth. The component-based approach clearly outperforms the whole-face approach on all tests. Although this approach isproven to be more reliable, it is still too slow for real-time applications. That is the reason why a real-time face recognition system using the whole-face approach is implemented to recognize people in color video sequences.

Post and Letters. 'Correos y cartas'.

Se presenta un secuencia didáctica en la que a través de una historia sencilla los niños aprenderán lo que pasa con las cartas desde que las echan en el buzón hasta que llegan a su destino.

The impact of a closed-loop electronic prescribing and administration system on prescribing errors, administration errors and staff time: a before-and-after study

Objectives: To assess the impact of a closed-loop electronic prescribing, automated dispensing, barcode patient identification and electronic medication administration record (EMAR) system on prescribing and administration errors, confirmation of patient identity before administration, and staff time. Design, setting and participants: Before-and-after study in a surgical ward of a teaching hospital, involving patients and staff of that ward. Intervention: Closed-loop electronic prescribing, automated dispensing, barcode patient identification and EMAR system. Main outcome measures: Percentage of new medication orders with a prescribing error, percentage of doses with medication administration errors (MAEs) and percentage given without checking patient identity. Time spent prescribing and providing a ward pharmacy service. Nursing time on medication tasks. Results: Prescribing errors were identified in 3.8% of 2450 medication orders pre-intervention and 2.0% of 2353 orders afterwards (p<0.001; χ2 test). MAEs occurred in 7.0% of 1473 non-intravenous doses pre-intervention and 4.3% of 1139 afterwards (p = 0.005; χ2 test). Patient identity was not checked for 82.6% of 1344 doses pre-intervention and 18.9% of 1291 afterwards (p<0.001; χ2 test). Medical staff required 15 s to prescribe a regular inpatient drug pre-intervention and 39 s afterwards (p = 0.03; t test). Time spent providing a ward pharmacy service increased from 68 min to 98 min each weekday (p = 0.001; t test); 22% of drug charts were unavailable pre-intervention. Time per drug administration round decreased from 50 min to 40 min (p = 0.006; t test); nursing time on medication tasks outside of drug rounds increased from 21.1% to 28.7% (p = 0.006; χ2 test). Conclusions: A closed-loop electronic prescribing, dispensing and barcode patient identification system reduced prescribing errors and MAEs, and increased confirmation of patient identity before administration. Time spent on medication-related tasks increased.

Clastic and core lava components of a silicic lava dome

The formation of a lava dome involves fractionation of the lava into core and clastic components. We show that for three separate, successive andesitic lava domes that grew at Soufrière Hills volcano, Montserrat, between 1999 and 2007, the volumetric proportion of the lava converted to talus or pyroclastic flow deposits was 50%–90% of the lava extruded. Currently, only 8% of the total magma extruded during the 1995–2007 eruption remains as core lava. The equivalent representation in the geological record will probably be even lower. Most of the lava extruded at the surface flowed no further than 150–300 m from the vent before disaggregation, resulting in a lava core whose shape tends to a cylinder. Moderate to high extrusion rates at the Soufrière Hills domes may have contributed to the large clastic fraction observed. Creating talus dissipates much of the energy that would otherwise be stored in the core lava of domes. The extreme hazards from large pyroclastic flows and blasts posed by wholesale collapse of a lava dome depend largely on the size of the lava core, and hence on the aggregate history of the partitioning process, not on the size of the dome.

A flexible monitoring and notification system for distributed resources

Resource monitoring in distributed systems is required to understand the 'health' of the overall system and to help identify particular problems, such as dysfunctional hardware, a faulty, system or application software. Desirable characteristics for monitoring systems are the ability to connect to any number of different types of monitoring agents and to provide different views of the system, based on a client's particular preferences. This paper outlines and discusses the ongoing activities within the GridRM wide-area resource-monitoring project.

Using a RESTful messaging and registry system to support a range a distributed applications

Tycho was conceived in 2003 in response to a need by the GridRM [1] resource-monitoring project for a ldquolight-weightrdquo, scalable and easy to use wide-area distributed registry and messaging system. Since Tycho's first release in 2006 a number of modifications have been made to the system to make it easier to use and more flexible. Since its inception, Tycho has been utilised across a number of application domains including widearea resource monitoring, distributed queries across archival databases, providing services for the nodes of a Cray supercomputer, and as a system for transferring multi-terabyte scientific datasets across the Internet. This paper provides an overview of the initial Tycho system, describes a number of applications that utilise Tycho, discusses a number of new utilities, and how the Tycho infrastructure has evolved in response to experience of building applications with it.

A camera based digit location and recognition system for garment tracking

Garment information tracking is required for clean room garment management. In this paper, we present a camera-based robust system with implementation of Optical Character Reconition (OCR) techniques to fulfill garment label recognition. In the system, a camera is used for image capturing; an adaptive thresholding algorithm is employed to generate binary images; Connected Component Labelling (CCL) is then adopted for object detection in the binary image as a part of finding the ROI (Region of Interest); Artificial Neural Networks (ANNs) with the BP (Back Propagation) learning algorithm are used for digit recognition; and finally the system is verified by a system database. The system has been tested. The results show that it is capable of coping with variance of lighting, digit twisting, background complexity, and font orientations. The system performance with association to the digit recognition rate has met the design requirement. It has achieved real-time and error-free garment information tracking during the testing.