The physical characteristics of ultrasonically sprayed indium-doped zinc oxide (ZnO:In) thin films, with electrical resistivity as low as 3.42 × 10−3 Ω·cm and high optical transmittance, in the visible range, of 50%–70% is presented. Zinc acetylacetonate and indium chloride were used as the organometallic zinc precursor and the doping source, respectively, achieving ZnO:In thin films with growth rate in the order of 100 nm/min. The effects of both indium concentration and the substrate temperature on the structural, morphological, optical, and electrical characteristics were measured. All the films were polycrystalline, fitting well with hexagonal wurtzite type ZnO. A switching in preferential growth, from (002) to (101) planes for indium doped samples were observed. The surface morphology of the films showed a change from hexagonal slices to triangle shaped grains as the indium concentration increases. Potential applications as transparent conductive electrodes based on the resulting low electrical resistance and high optical transparency of the studied samples are considered.

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Indium doped zinc oxide [ZnO:In] thin films have been deposited at 430°C on soda-lime glass substrates by the chemical spray technique, starting from zinc acetate and indium acetate. Pulverization of the solution was done by ultrasonic excitation. The variations in the electrical, structural, optical, and morphological characteristics of ZnO:In thin films, as a function of both the water content in the starting solution and the substrate temperature, were studied. The electrical resistivity of ZnO:In thin films is not significantly affected with the increase in the water content, up to 200 mL/L; further increase in water content causes an increase in the resistivity of the films. All films show a polycrystalline character, fitting well with the hexagonal ZnO wurtzite-type structure. No preferential growth in samples deposited with the lowest water content was observed, whereas an increase in water content gave rise to a (002) growth. The surface morphology of the films shows a consistency with structure results, as non-geometrical shaped round grains were observed in the case of films deposited with the lowest water content, whereas hexagonal slices, with a wide size distribution were observed in the other cases. In addition, films deposited with the highest water content show a narrow size distribution.

With the growing information on web, online movie review is becoming a significant information resource for Internet users. However, online users post thousands of movie reviews on daily basis and it is hard for them to manually summarize the reviews. Movie review mining and summarization is one of the challenging tasks in natural language processing. Therefore, an automatic approach is desirable to summarize the lengthy movie reviews, and it will allow users to quickly recognize the positive and negative aspects of a movie. This study employs a feature extraction technique called bag of words (BoW) to extract features from movie reviews and represent the reviews as a vector space model or feature vector. The next phase uses Naïve Bayes machine learning algorithm to classify the movie reviews (represented as feature vector) into positive and negative. Next, an undirected weighted graph is constructed from the pairwise semantic similarities between classified review sentences in such a way that the graph nodes represent review sentences, while the edges of graph indicate semantic similarity weight. The weighted graph-based ranking algorithm (WGRA) is applied to compute the rank score for each review sentence in the graph. Finally, the top ranked sentences (graph nodes) are chosen based on highest rank scores to produce the extractive summary. Experimental results reveal that the proposed approach is superior to other state-of-the-art approaches.

A study on the propane gas-sensing properties of Cu-doped ZnO thin films is presented in this work. The films were deposited on glass substrates by sol-gel and dip coating methods, using zinc acetate as a zinc precursor, copper acetate and copper chloride as precursors for doping. For higher sensitivity values, two film thickness values are controlled by the six and eight dippings, whereas for doping, three dippings were used, irrespective of the Cu precursor. The film structure was analyzed by X-ray diffractometry, and the analysis of the surface morphology and film composition was made through scanning electron microscopy (SEM) and secondary ion mass spectroscopy (SIMS), respectively. The sensing properties of Cu-doped ZnO thin films were then characterized in a propane atmosphere, C3H8, at different concentration levels and different operation temperatures of 100, 200 and 300 °C. Cu-doped ZnO films doped with copper chloride presented the highest sensitivity of approximately 6 × 104, confirming a strong dependence on the dopant precursor type. The results obtained in this work show that the use of Cu as a dopant in ZnO films processed by sol-gel produces excellent catalysts for sensing C3H8 gas.

Acute Myeloid Leukemia (AML) is a kind of fatal blood cancer with a high death rate caused by abnormal cells’ rapid growth in the human body. The usual method to detect AML is the manual microscopic examination of the blood sample, which is tedious and time-consuming and requires a skilled medical operator for accurate detection. In this work, we proposed an AlexNet-based classification model to detect Acute Myeloid Leukemia (AML) in microscopic blood images and compared its performance with LeNet-5-based model in Precision, Recall, Accuracy, and Quadratic Loss. The experiments are conducted on a dataset of four thousand blood smear samples. The results show that AlexNet was able to identify 88.9% of images correctly with 87.4% precision and 98.58% accuracy, whereas LeNet-5 correctly identified 85.3% of images with 83.6% precision and 96.25% accuracy.

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In Distributed Hash Table (DHT)-based Mobile Ad Hoc Networks (MANETs), a logical structured network (i.e., follows a tree, ring, chord, 3D, etc., structure) is built over the ad hoc physical topology in a distributed manner. The logical structures guide routing processes and eliminate flooding at the control and the data plans, thus making the system scalable. However, limited radio range, mobility, and lack of infrastructure introduce frequent and unpredictable changes to network topology, i.e., connectivity/dis-connectivity, node/link failure, network partition, and frequent merging. Moreover, every single change in the physical topology has an associated impact on the logical structured network and results in unevenly distributed and disrupted logical structures. This completely halts communication in the logical network, even physically connected nodes would not remain reachable due to disrupted logical structure, and unavailability of index information maintained at anchor nodes (ANs) in DHT networks. Therefore, distributed solutions are needed to tolerate faults in the logical network and provide end-to-end connectivity in such an adversarial environment. This paper defines the scope of the problem in the context of DHT networks and contributes a Fault-Tolerant DHT-based routing protocol (FTDN). FTDN, using a cross-layer design approach, investigates network dynamics in the physical network and adaptively makes arrangements to tolerate faults in the logically structured DHT network. In particular, FTDN ensures network availability (i.e., maintains connected and evenly distributed logical structures and ensures access to index information) in the face of failures and significantly improves performance. Analysis and simulation results show the effectiveness of the proposed solutions.