Original scientific paperLateral flow immunochromatographic assay (LFIA) testing is essential for accurate detection and diagnoses of diseases and physical conditions. However, the existing LFIA strip reader equipped with high cost of hardware confines its simplicity and portability. Therefore, this study develops a simple, low cost LFIA strip reader comprising 4 major modules -mechanical, optical, processing and control modules. The mechanical module pulls in and out the test strip automatically to be read by the optical module and the data processing module provides the test results by analyzing the data sent by the optical module. All the individual modules are controlled by a control module. To reduce the hardware budget and control complexity, a time-triggered cooperative (TTC) scheduler implemented on an 8051 IP core was chosen as control system. In addition, special, high sensitivity C-reactive protein (CRP) strips with 10 different concentrations were tested to evaluate the performance of the system. Further, a commercial ESEQuant lateral flow reader (QIAGEN, Germany) was tested as a comparative study. The test results show that the proposed reader was stable with a coefficient of variation (CV) factor within 3%. To test the qualitative performance of the system, each of the CRP concentration were examined for 10 times, which indicates that the system has a large dynamic detection range and good detection linearity (R 2 = 0.998). In short, the proposed LFIA strip reader has high potential relative to existing readers, especially in simplicity and cost. Imunokromatografsko testiranje lateralnog toka (LFIA)čitača trake temeljeno na rasporedu i 8051 IP jezgri. Imunokromatografsko testiranje lateralnog toka (LFIA) nužno je za preciznu detekciju i dijagnozu oboljenja te psihičkih stanja. Meutim, postojeći LFIA opremljeni s hardverom visoke cijene limitiraju jednostavnost i prenosivost. Ovo istraživanje razvija jednostavni, niske cijene,čitač traka koji se sastoji od 4 glavna dijelamehanički, optički, procesni i upravljački. Mehanički modul povlači testnu traku automatski kako bi optički modul mogaočitati. Procesni modul analizira podatke dobivene s optičkogčitača. Svaki modula upravlja se upravljačkim modulom. Vremensko ovisno kooperativni raspored implementiran je na 8051 IP jezgri kako bi se smanjili računski zahtjevi. Dodatno, visoko osjetljiva CRP traka s deset različitih koncentracija korištena je u svrhe evaluacije sustava. Rezultati su usporeeni s komercijalnimčitačem lateralnog toka ESEQuant (QIAGEN, Njemačka). Rezultati pokazuju da je predložena metoda stabilna s koeficijentom varijacije unutar 3%. Kako bi se kvalitativno testirao sustav, svaka od CRP koncentracija testirana je deset puta, što ukazuje da sustav veliki dinamički raspon detekcije te dobru linearnost detekcije (R 2 = 0.998). Predloženi LFIAčitač traka ima dosta potencijala u usporedbi s postoječimčitačima, posebno u smislu jednostavnosti i cijene.

Recently, global change research has reflected the great challenge of massive distributed remote sensing image processing. Faced with such challenge, massive pixel-level remote sensing image processing reconstruction based on Hadoop is proposed, which focuses on the support of data format and the design of paralle computing. In order to support a variety of formats of remote sensing images and simplify the process of data parse, the processing flow transforms the remote sensing image into image information in binary format, as well as metadata information in xml format. Compared with converting to text format, there are two advantages for this conversion, reducing the amount of data after converted and remaining metadata information. To avoid MapReduce parallel computing performance interference caused by the algorithmic complexity, remote sensing image point operation is selected to do research about the design of parallel computing. The experimental results show that the proposed method has good scalability in the distributed Hadoop environment, along with the changing of the data quantity.