Investigation into ultraviolet radiations from modern electric light sources

Due to concerns of increasing electrical energy demand and government regulations, traditional incandescent lamps are being replaced by energy-efficient lamps, such as compact fluorescent lamps (CFLs) and light emitting diodes (LEDs). The widespread adoption of new solid-state light sources requires investigation into several effects associated with these alternative light sources. One of the important concerns is ultraviolet (UV) radiations coming out of these new light sources. This brief report presents the experimental data obtained on UV radiations from CFLs and LEDs.     

Hydrogenation of l-Arabinose and d-Galactose Mixtures Over a Heterogeneous Ru/C Catalyst

Complete hydrogenation of d-galactose and l-arabinose mixtures on a Ru/C catalyst was achieved with excellent selectivities exceeding 95?%. No unexpected effects of temperature and pressure were observed. A detailed kinetic model was derived to describe the simultaneous hydrogenation of the monomeric sugars.     

Effect of polyethyleneimine on the growth of ZnO nanorod arrays and their application in dye-sensitized solar cells

A series of oriented hexagonal wurtzite ZnO nanorod-array films were grown on fluorine-doped tin oxide (FTO) coated glass substrates by chemical process. The effect of polyethyleneimine (PEI) on the structure and micro-morphology of ZnO nanorod array films, as well as the photoelectric conversion properties in dye-sensitized solar cells (DSSCs) was analyzed. It was found that with the addition of PEI in growth solution, the ZnO nanorods became smaller in diameter and longer in length and hence the dye absorption and the photovoltaic performance of DSSCs were improved. A power conversion efficiency of 2.30% had been achieved on a DSSC based on a 7.9 μm-long nanorod array film prepared by a growth solution containing the PEI.     

Distribution of Alpha Thalassaemia Gene Variants in Diverse Ethnic Populations in Malaysia: Data from the Institute for Medical Research

Alpha thalassaemia is highly prevalent in the plural society of Malaysia and is a public health problem. Haematological and molecular data from 5016 unrelated patients referred from various hospitals to the Institute for Medical Research for α thalassaemia screening from 2007 to 2010 were retrieved. The aims of this retrospective analysis were to describe the distribution of various alpha thalassaemia alleles in different ethnic groups, along with their genotypic interactions, and to illustrate the haematological changes associated with each phenotype. Amongst the patients, 51.2% (n = 2567) were diagnosed with α thalassaemia. Of the 13 α thalassaemia determinants screened, eight different deletions and mutations were demonstrated: three double gene deletions, – – ^SEA, – – ^THAI, ––^FIL; two single-gene deletions, α–^3.7 and – α^4.2; and three non-deletion mutations, Cd59G > A (haemoglobin [Hb] Adana), Cd125T > C (Hb Quong Sze) and Cd142 (Hb Constant Spring). A high incidence of α–^3.7 deletion was observed in Malays, Indians, Sabahans, Sarawakians and Orang Asli people. However, the – – ^SEA deletion was the most common cause of alpha thalassaemia in Chinese, followed by the α–^3.7 deletion. As many as 27 genotypic interactions showed 1023 α thalassaemia silent carriers, 196 homozygous α⁺ thalassaemia traits, 973 heterozygous α⁰ thalassaemia carriers and 375 patients with Hb H disease. Statistical analysis showed a significant difference in the distribution of α thalassaemia determinants amongst the various ethnic groups. Hence, the heterogeneous distribution of common determinants indicated that the introduction of an ethnicity-targeted hierarchical α thalassaemia screening approach in this multi-ethnic Malaysian population would be effective.     

Humidity sensing properties of Cu2O-PEPC nanocomposite films

In this study, the blend of copper oxide nanopowder (Cu2O), 3 wt.% and poly-N-epoxypropylcarbazole (PEPC), 2 wt.% in benzol were drop-casted on glass substrates with pre-deposited surface-type silver electrodes for the fabrication of Cu2O-PEPC nanocomposite thin films. The thicknesses of the Cu2O-PEPC films were in the range of 10-13 μm. The effect of humidity on the electrical properties of the nanocomposite films was investigated by measurement of the capacitance and dissipation of the samples at two different frequencies of the applied voltage: 120 Hz and 1 kHz. The AC resistance of the samples was determined from values of dissipation. The DC resistance was measured directly. The effect of ageing on the humidity sensing properties of the nanocomposite was observed. After the ageing it was observed that at 120 Hz and 1 kHz, under humidity of up to 86% RH , the capacitance of the cell increased by 85 and 8 times and resistance decreased by 345 and 157 times, accordingly, with respect to 30% RH conditions. It was found that with increase of the frequency, the capacitance and resistance of the samples decreased. It is assumed that the humidity response of the cell is associated with diffusion of water vapors and doping of the semiconductor nanocomposite by water molecules.     

Characterization of vanadyl phthalocyanine based surface-type capacitive humidity sensors

This study presents the fabrication and characterization of novel surface-type capacitive humidity sensors using vanadyl phthalocyanine (VOPc) as the active material. The devices, which comprise three different thicknesses,have been fabricated using the thermal evaporation technique. A thin film of VOPc is deposited on thoroughly cleaned glass substrates with pre-pattemed Ag electrodes. The capacitive effect of the samples under humidity has been in-vestigated. Comparison of the samples with different thicknesses shows that the thinnest device seems more sensitive towards humidity. The humidity dependent capacitance properties of the sensor make it beneficial for use in commercial hygrometers.     

Autonomous Parking-Lots Detection with Multi-Sensor Data Fusion Using Machine Deep Learning Techniques

The rapid development and progress in deep machine-learning techniques have become a key factor in solving the future challenges of humanity. Vision-based target detection and object classification have been improved due to the development of deep learning algorithms. Data fusion in autonomous driving is a fact and a prerequisite task of data preprocessing from multi-sensors that provide a precise, well-engineered, and complete detection of objects, scene or events. The target of the current study is to develop an in-vehicle information system to prevent or at least mitigate traffic issues related to parking detection and traffic congestion detection. In this study we examined to solve these problems described by (1) extracting region-of-interest in the images (2) vehicle detection based on instance segmentation, and (3) building deep learning model based on the key features obtained from input parking images. We build a deep machine learning algorithm that enables collecting real video-camera feeds from vision sensors and predicting free parking spaces. Image augmentation techniques were performed using edge detection, cropping, refined by rotating, thresholding, resizing, or color augment to predict the region of bounding boxes. A deep convolutional neural network F-MTCNN model is proposed that simultaneously capable for compiling, training, validating and testing on parking video frames through video-camera. The results of proposed model employing on publicly available PK-Lot parking dataset and the optimized model achieved a relatively higher accuracy 97.6% than previous reported methodologies. Moreover, this article presents mathematical and simulation results using state-of-the-art deep learning technologies for smart parking space detection. The results are verified using Python, TensorFlow, OpenCV computer simulation frameworks.     

Experimenting with a Question Answering System for the Arabic Language

The World Wide Web (WWW) today is so vast that it has become more and more difficult to find answers to questions using standard search engines. Current search engines can return ranked lists of documents, but they do not deliver direct answers to the user. The goal of Open Domain Question Answering (QA) systems is to take a natural language question, understand the meaning of the question, and present a short answer as a response based on a repository of information. In this paper we present QARAB, a QA system that combines techniques from Information Retrieval and Natural Language Processing. This combination enables domain independence. The system takes natural language questions expressed in the Arabic language and attempts to provide short answers in Arabic. To do so, it attempts to discover what the user wants by analyzing the question and a variety of candidate answers from a linguistic point of view.