Mehmet S. Unluturk

Modeling inactivation kinetics of liquid egg white exposed to UV-C irradiation.

The efficiency of UV-C irradiation as a non-thermal pasteurization process for liquid egg white (LEW) was investigated. LEW inoculated with Escherichia coli K-12 (ATCC 25253), pathogenic strain of Escherichia coli O157:H7 (NCTC12900) and Listeria innocua (NRRL B33314) were treated with UV light using a bench top collimated beam apparatus. Inoculated LEW samples were exposed to UV-C irradiation of known UV intensity of 1.314mW/cm(2) and sample depth of 0.153cm for 0, 3 5, 7, 10, 13, 17 and 20min. The populations of E. coli K-12, E. coli O157:H7 and L. innocua were reduced after 20min of exposure by 0.896, 1.403 and 0.960logCFU respectively. Additionally, the inactivation data obtained for each strain suspended in LEW was correlated by using Weibull (2 parameter), Log-Linear (1 parameter), Hom (2 parameter) and modified Chick Watson (2 parameter) models. The inactivation kinetics of E. coli K-12, E. coli O157:H7 and L. innocua were best described by modified Chick Watson model with the smallest root mean squared error (RMSE) (R(2)> or =0.92).

SEE: Improving Nurse-Patient Communications and Preventing Software Piracy in Nurse Call Applications

Nurse call system is an electrically functioning system by which patients can call upon from a bedside station or from a duty station. An intermittent tone shall be heard and a corridor lamp located outside the room starts blinking with a slow or a faster rate depending on the call origination. It is essential to alert nurses on time so that they can offer care and comfort without any delay. There are currently many devices available for a nurse call system to improve communication between nurses and patients such as pagers, RFID (radio frequency identification) badges, wireless phones and so on. To integrate all these devices into an existing nurse call system and make they communicate with each other, we propose software client applications called bridges in this paper. We also propose a window server application called SEE (Supervised Event Executive) that delivers messages among these devices. A single hardware dongle is utilized for authentication and copy protection for SEE. Protecting SEE with securities provided by dongle only is a weak defense against hackers. In this paper, we develop some defense patterns for hackers such as calculating checksums in runtime, making calls to dongle from multiple places in code and handling errors properly by logging them into database.

Process Neural Network Method: Case Study I: Discrimination of Sweet Red Peppers Prepared by Different Methods

This study utilized a feed-forward neural network model along with computer vision techniques to discriminate sweet red pepper products prepared by different methods such as freezing and pureeing. The differences among the fresh, frozen and pureed samples are investigated by studying their bio-crystallogram images. The dissimilarity in visually analyzed bio-crystallogram images are defined as the distribution of crystals on the circular glass underlay and the thin or the thick structure of crystal needles. However, the visual description and definition of bio-crystallogram images has major disadvantages. A methodology called process neural network (ProcNN) has been studied to overcome these shortcomings.

TAP.NET: A Windows Messaging Service for Nursing Staff

Nurses are the foundation of any healthcare system. It is essential to alert nurses on time so that they can offer care and comfort without any delay. Pager messages (short messages) represent an important part of the overall hospital communication network. These short messages are sent through data paging systems to direct nurses to patients. Telocator Alphanumeric Protocol (TAP) is used for submitting short messages to these data paging systems. In this paper, a windows messaging service (TAP.NET) is designed to connect to a data paging system using the TAP protocol. A Web application is also proposed that uses remote technology to transmit page requests to this messaging service. With this overall design, pager messages can be sent from any computer that has an Internet connection on the hospital network. A logging scheme is also introduced to assess the performance of the TAP.NET.

Advanced Nurse-Patient Communication System

Effective communication is the most important part of any healthcare organization. For many years, hospital nurse call solutions had been stand-alone systems with occasional integration to pocket paging for outputting patient call alerts to mobile staff. In the late 1990’s, technology enabled in-building wireless phones to supplement or replace paging systems as a means of not only sending alerts, but also enabling voice communication between mobile staff and patients. Today’s nurse call market requires integration of additional information from location and ADT (admit, discharge, transfer) systems into what have traditionally been nurse call applications. This system information is required not only at the nursing station, pagers, and phones, but also at PC’s placed on each patient care floor in hallways, nurse stations, and offices, and at areas away from the patients, including administrator and clinical engineering offices. It is crucial that nurses have the latest patient information in their hand wherever they go in the hospital. In this paper, MatchMaker.NET has been developed to integrate all these technologies into the hospital’s LAN to improve nurse-patient communication.

Improving communication among nurses and patients

Patients use nurse call systems to signal nurses for medical help. Traditional push button-flashing lamp call systems are not integrated with other hospital automation systems. Therefore, nurse response time becomes a matter of personal discretion. The improvement obtained by integrating a pager system into the nurse call systems does not increase care efficiency, because unnecessary visits are still not eliminated. To obtain an immediate response and a purposeful visit by a nurse; regardless of the location of nurse in hospital, traditional systems have to be improved by intelligent telephone system integration. The results of the developed Nurse Call System Software (NCSS), the Wireless Phone System Software (WPSS), the Location System Software (LSS) and the communication protocol are provided, together with detailed XML message structures. The benefits of the proposed system are also discussed and the direction of future work is presented.

Manual nurse messaging with patient information using a mobile whiteboard system

Nurses are the backbone of hospitals. They are mobile all the time and they can be anywhere in the hospital. To improve the communication between nurses, publicly visible displays such as manual whiteboards are heavily used in the nursing units. However, HIPAA limits the information displayed in these public displays. In this paper, a software solution called whiteboard which is HIPAA compliant is developed to replace these manual public displays. The software whiteboard is visible only to the nurses and integrates the staff assignments from the nurse call system, the patient and the bed information from the ADT (admission-discharge-transfer) interface, and the staff location information from the location server. Nurses can use this information to improve the staff communication, do the planning, and see the bed occupancy status in their nursing units.

Capillary Dynamolysis Image Discrimination Using Neural Networks

Quality differences between organic and conventional fresh tomatoes (unprocessed) and frozen tomatoes (processed) are evaluated by using a capillary rising picture method (capillary dynamolysis). The best pictures showing the differences most sharply between organic and conventional samples were prepared with 0.25-0.75% silver nitrate, 0.25-0.75% iron sulphate and 30-100% sample concentration. But visual description and analysis of these images is a major challenge. Therefore, a novel methodology called Gram-Charlier Neural Network methodology (GCNN) has been studied to classify these images. Two separate GCNNs have been created for fresh and frozen cases. They are trained with the pictures of organic and conventional tomato samples from these two cases. The 2048 x 1536 pixel chromatogram images were acquired in a lab and cropped to 1400 x 900 pixel images depicting either a conventional tomato or an organic tomato for each case. A set of 20 images from each case was utilized to train each Gram- Charlier Neural Network. A new set of 4 images from each case was then prepared to test each GCNN performance. In addition, Hinton diagrams were utilized to display the optimality of the GCNN weights. Overall, the GCNN achieved an average recognition performance of 100%. This high level of recognition suggests that the GCNN is a promising method for the discrimination of capillary dynamolysis images and its performance does not depend on whether the tomato sample is fresh or frozen.

Performance evaluation of the neural networks for moisture detection using GPR

Ground penetrating radar (GPR) is a highly researched area; however, despite this, there is a lack of knowledge about the well-known problem of moisture distorting the results of GPR surveys. This research analyses the results of a GPR survey on a Case Study Bridge structure in order to analyse this effect, specifically when checking for the positioning of rebar. The expected distortions of the GPR results due to the presence of moisture were indeed present, as further evidenced by subsequent destructive testing and velocity analysis. Furthermore, neural networks were also utilised to detect moisture ingress from the GPR raw data.

Using HL7 in hospital staff assignments

Hospital staff assignments are the instructions that allocate the hospital staff members to the hospital beds. Currently, hospital administrators make the assignments without accessing the information regarding the occupancy of the hospital beds and the acuity of the patient. As a result, administrators cannot distinguish between occupied and unoccupied beds, and may therefore assign staff to unoccupied beds. This gives rise to uneven and inefficient staff assignments. In this paper, the hospital admission-discharge-transfer (ADT) system is employed both as a data source and an assignment device to create staff assignments. When the patient data is newly added or modified, the ADT system updates the assignment software client with the relevant data. Based on the relevant data, the assignment software client is able to construct staff assignments in a more efficient way.