The wheat and cotton growth condition in Uzbekistan was observed using medium spatial and high temporal resolution satellite - Sentinel-2 and demonstrated potentiality of growth monitoring technique in the future. The satellite data are preprocessed and corrected by band spectral adjustment for integration of different sensor data. Through the correction improvements and operational processing technique, the satellite data have been harmonically processed and allow to capture crop growth conditions of different regions as Samarkand and Tashkent with different crop types as grain, cotton, rice and others.

Personality impressions of robots have been regarded as one of the crucial factors in human-robot interaction. To design the personality impressions, we should know how the visual, auditory, and tactile impressions determine the personality impressions. In this study, we investigated the relationships between touch sensations and personality impressions with a child-type android robot in two conditions where 40 Japanese participants touched a part of the robot with different appearance of the face. Factor and path analyses were conducted on the evaluation scores of the sensations and impressions provided by the participants. As a result, two significant positive causal relationships (p < 0.001) were found between the Preference and Resilience touch sensations, and the Likability and Capability personality impressions, respectively, in both robot conditions. On the other hand, several other causal relationships were found only in one condition. This suggests that there are appearance-dependent and appearance-independent relationships between touch sensations and personality impressions.

In recent high-density VLSIs, soft errors, particularly single event upsets (SEUs), frequently occur during system operation. In addition, the occurrence of delay faults caused by manufacturing defects is a significant problem. Thus, SEU tolerant design and delay fault testing are of increasing significance. This paper presents two types of SEU tolerant flip-flops (FFs). The proposed FFs tolerate SEUs caused by particles striking feedback loops in the FFs. Moreover, the proposed FFs allow enhanced scan delay fault testing. The proposed FFs are master-slave FFs, and the slave latches are constructed by modifying existing SEU tolerant latches, namely, SEH latches. The two proposed FFs tolerate particles with charges of 370 fC and of 369 fC or lower, whereas an existing SEU tolerant enhanced scan FF, called an ESFF-SEC, tolerates those of 431 fC or lower. Furthermore, the areas of the proposed FFs are 23.1% and 20.5% smaller than that of the ESFF-SEC. The CK-Q delay times are 44.4% and 41.1% shorter than that of the ESFF-SEC. Moreover, the average power consumptions of the proposed FFs during system operations are 55.6% and 53.3% lower than that of the ESFF-SEC.

An effective image retrieval system is developed based on the use of neural networks (NNs). It takes advantages of association ability of multilayer NNs as matching engines which calculate similarities between a user's drawn sketch and the stored images. The NNs memorize pixel information of every size-reduced image (thumbnail) in the learning phase. In the retrieval phase, pixel information of a user's drawn rough sketch is inputted to the learned NNs and they estimate the candidates. Thus the system can retrieve candidates quickly and correctly by utilizing the parallelism and association ability of NNs. In addition, the system has learning capability: it can automatically extract features of a user's drawn sketch during the retrieval phase and can store them as additional information to improve the performance. The software for querying, including efficient graphical user interfaces, has been implemented and tested. The effectiveness of the proposed system has been investigated through various experimental tests.

No abstract available.

Sinhalese is the major language in Sri Lanka, spoken by 15 million people. It has never been analysed by a computer. The paper describes an original computational linguistic analysis for Sinhalese. A machine representation of Sinhalese script is developed. It provides an easy means of input and facilitates the formalization of the linking phenomena. An analysis sytem for Sinhalese morphology is developed. A Sinhalese sentence consists of a few units separated by spaces. The unit structure is formalized as a root and suffixes. Connection rules and linking rules are developed. The grammatical features of a unit are characterized by a set of attributes, and a mechanism to compute these attributes is developed from the features of the root and suffixes. The unit structure involves much important grammatical information such as case and attributes. The analyser can handle any kind of Sinhalese unit efficiently. The system will be used as the base for machine processing of Sinhalese, its syntactic and semantic analysis, and other applications.