As technology continues to develop, computer vision (CV) applications are becoming increasingly widespread in the intelligent transportation systems (ITS) context. These applications are developed to improve the efficiency of transportation systems, increase their level of intelligence, and enhance traffic safety. Advances in CV play an important role in solving problems in the fields of traffic monitoring and control, incident detection and management, road usage pricing, and road condition monitoring, among many others, by providing more effective methods. This survey examines CV applications in the literature, the machine learning and deep learning methods used in ITS applications, the applicability of computer vision applications in ITS contexts, the advantages these technologies offer and the difficulties they present, and future research areas and trends, with the goal of increasing the effectiveness, efficiency, and safety level of ITS. The present review, which brings together research from various sources, aims to show how computer vision techniques can help transportation systems to become smarter by presenting a holistic picture of the literature on different CV applications in the ITS context.

Lysinuric protein intolerance (LPI; McKusick 222700) is a rare hereditary condition characterized by impaired transport of dibasic amino acids in renal tubuli, intestine, and liver. The increased renal clearance and poor intestinal absorption of these amino acids lead to low plasma levels (Rajantie et al 1980). The patients complain of vomiting, diarrhoea and aversion to protein-rich foods. Hepatosplenomegaly, failure to thrive and hypotonia are the most frequent findings at physical examination. Disturbance of dibasic amino acids uptake by liver cells, and reduced urea-cycle intermediates, arginine and ornithine lead to periodic hyperammonaemia that is responsible for most of the clinical symptoms. Postprandial hyperammonaemia, usually associated with coma, increased urinary excretion of lysine, ornithine and arginine, and low plasma concentrations of these dibasic amino acids, reveals the diagnosis of LPI (Simell 1995).A 35-day-old girl was a normal delivery at term following a normal pregnancy to a 23-year-old woman. The parents are first-degree cousins. Birth weight was 3000g. She had feeding difficulty and generalized convulsions. The previous child died at 24 days from sepsis. Clinical examination revealed hypotonia, depressed newborn reflexes, oral moniliasis and hepatomegaly but no other abnormality.Complete blood count was Hb 8.2g/dl, Hct 28%, white blood cells 5800/ram 3. Urine was negative for ketones and glucose and showed trace proteinuria. Serum electrolyte determinations and liver and renal function tests were normal. C-reactive protein and all cultures were negative. Cranial computed tomographic scan revealed hyperlucent areas of periventricular white matter and increased pericerebral distance. The plasma ammonia level was 255 umol/L (normal range 50-67). Plasma amino acid analysis showed decreased levels of arginine (8 #mol/L, control t01), lysine (2t6 u mol/L, control 309) and omithine (80 g mot/L, control 128). Urine amino acid analysis revealed increased excretion of arginine (7.2/~mol/24h, control 0.1), tysine (81.7,umol/24h, control 8.3) and ornithine (3.4pmol/24h, control 0.8).Daily protein intake was restricted. Double-volume exchange transfusion was carried out seven times and peritoneal dialysis was performed in order to reduce high plasma ammonia levels. She died at 55 days. At autopsy, grossly the thymus was replaced by fibroadipose tissues. Several sections were performed and thymic lobules in fibroadipous tissues were seen in a few. Thus the thymus was markedly reduced in size (hypoplasia). However, its microscopic appearance was normal.About 80 patients with LPI have been reported worldwide, almost half of them in Finland. Nagata and colleagues (1987) reported an 8-year-old girl with LPI with immuno-372

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Custom made tiling cDNA microarrays have been developed for high resolution HLA genotyping. The array comprises tens of thousands of sequence-specific oligonucleotide probes (SSOP) that hybridize with HLA sequences. Sophisticated methods for analyzing the multidimensional complex data are needed due to large amounts of data generated from the microarray experiments. Moreover, the inconsistencies, noise, and outliers in the probe signals add additional complexities. We proposed data cleaning methods for the identification of uninformative and misinformative probes to improve the performance of HLA typing process.

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