Ectopic thyroid is an uncommon embryological abnormality characterized by the presence of thyroid tissue in a site other than its usual pretracheal location. Of all ectopic thyroids 90% are found to be lingual. Lingual thyroid is estimated to occur in 0.2 per cent of normal children, being more common in females. It is a rare congenital anomaly appearing with prevalence of 1:100000. This embryological anomaly originates from failure of thyroid gland to descend from foramen caecum to its normal pre laryngeal site. Interestingly, only 0.01% of these patients present with any overt symptoms. If symptomatic: dyspnoea dysphagia, dysphonia and stomatolalia are some common clinical features associated with it. In females these symptoms manifest during stress as in pregnancy, puberty and menstruation. Some rare clinical presentations reported in literature are hyperthyroidism, malignancy and hemoptysis. Hereby authors are reporting a 7-year-old female child who presented to our department with dysphagia who on evaluation diagnosed to have lingual thyroid with hypothyroidism.

Parking space is one of the most critical needs of people’s lives, especially in Indonesia. According to the Central Statistics Agency, vehicle growth in Indonesia in the last ten years is 9% per year. Meanwhile, parking needs are being eroded by settlements, shops, and public service buildings. Limited parking lots make it hard for drivers to find available parking spaces. When looking for a parking space, it was causing impacts such as traffic jams, air pollution, causing noise and panic. The intelligent parking system is the solution to this problem. This system can provide information on available parking slots. In this study, parking locations are marked with a circle. If a circle is visible, then a parking lot is available, and if not, then the parking location has been filled by the vehicle. Circle objects in images taken using the camera can be identified by the Hough transformation method or feature extraction. These two methods are compared to measure the accuracy and speed of the process. Experiments and observations on the performance of both methods show that both methods can recognize the location of the available parking slot. The feature extraction method has a better detection speed with an average processing time of 1.1 seconds. The Hough transformation algorithm has an average processing time of 4.1 seconds. Then it can be concluded that the feature extraction method is better applied to the smart parking system.

Continuous monitoring of environmental parameters is necessary in order to achieve maximum plant growth in a greenhouse system. The aim of this study is to perform a real time data monitoring from multiple sensors in greenhouse using Arduino and Excel add-ins. DHT22 sensors, BH1750 sensor are the main sensors used in this study which give the exact value of temperature, humidity, and light intensity, respectively. Arduino Uno board provides multiple inputs analogs and I/O digitals were utilized to read the data sensor aforementioned that applied for the greenhouse. The level of accuracy of each sensor was compare to the standard device results. The results show that the accuracy of the sensors measurement is very good. This system design is real time, simple and low cost that given ability for user to monitor, collect, and to plot their greenhouse environments data in an Excel sheet.

Background: Seizures are a common problem evaluated in the pediatric emergency departments worldwide. Objective: The objective of the study was to study the etiology of convulsions in children aged 1 month–14 years. Methods: This cross-sectional study was done among 120 children admitted to the pediatric ward of a tertiary care hospital with convulsions during the period of June 2014–May 2015. Complete blood count, blood sugar, serum calcium, magnesium, and electrolytes were done for all the children. Mantoux, chest X-ray, liver biopsy, electroencephalograph, lumbar puncture and cerebrospinal fluid analysis, ultrasonography cranium, computed tomography brain, or magnetic resonance imaging brain were done based on the clinical situation. Results: We found that 46.7% of the children had febrile seizures, 19.2% had seizure disorder, 15% had cerebral palsy, 5.8% had viral encephalitis, 3.3% had pyogenic meningitis, 1.7% had neurocysticercosis, 0.8% had metabolic disorders, and 0.8% had traumatic brain injury, and the cause of seizures was unknown in 6.6% of the children. Conclusion: Children with seizures need a thorough evaluation to identify the underlying pathology causing seizures.

A female preponderance, less familial clustering, higher paucity of clinical manifestations and quick progression to hypothyroidism (in those without) were noted in the present series.