This paper presents novel approach to the Huffman’s asynchronous sequential circuit two valued Boolean switching system design. The algorithm is implemented as software using distributed, service oriented application model with means of the web service component design. It considers method implementation challenges, both towards Moore and Mealy structures with particular respect to the estimation of the Huffman’s minimization algorithm computational complexity. The paper provides implementation details, theoretical model estimation and experimental results that acknowledge the theoretical approach in practice. This paper also examine the multistep design process implementation and its problems inherent in web service based environment both for development and educational purposes.

There is an increased interest in using automatic milking systems (AMS) to indirectly assess the welfare of dairy cows, but knowledge on analyzing the association between lameness, milk yield characteristics, and reproductive performance in cows is still insufficient. The main aims of this study were to evaluate the influence of lameness on several AMS variables and reproduc- tive performance indicators during the early stage of lactation and estrus in Lithuanian Black and White dairy cows, as well as to assess the associations between lameness, productivity and repro- ductive efficiency. A total of 418 milking cows (50.3±1.2 d postpartum) without any apparent reproductive disorder were monitored for hoof health status. Cows were assigned to two groups on the basis of visual locomotion scoring: “non-lame“cows (group 1; 74.20%) and cows presen- ting “lameness“ (lame cows) (group 2; 25.80%).

Productive and milking performances of dairy cows were recorded from 50 to 100 days in milk (DIM) and 1 day after the first estrus. The lameness was predominantly localized on the hind feet (79.60%) and less frequently - on the front feet (20.40%; p<0.001). Furthermore, the lameness had a tendency to decrease milk production (4.24%; p<0.05) and increase the diffe- rence in milk yield between rear and front quarters of the udder (1.20%; p<0.05). The frequency of milking (5.19%) was lower in lame cows (p<0.05). The lame cows during estrus showed a more pronounced decrement in milk yield and milking frequency (p<0.05), and also higher milk progesterone concentration values (1.55-1.76 time’s; p<0.001), and an increasing number of inseminations (11.69%; p<0.05) were observed. The results highlighted that analysis of data from AMS programs can be a successful tool for reducing risk factors related to the effective management of reproductive performance and hoof health of dairy cows.

This paper focuses on automatic locking of tracking filters used in optical frequency transfer systems. General concept of such a system is briefly described and the problems with its automatic startup, originating in the use of the analog phase locked loop to filter weak, received signal, are discussed. A supervisory circuitry and algorithm to solve these problems is proposed. The frequency of the signal to be filtered is measured indirectly and the output frequency of the tracking filter is monitored. In the case of lack of synchronism (i:e: after the startup) a significant difference of these frequencies is measured and the supervisory algorithm forces the filter to tune into the right frequency and then allows it to synchronize. A system with the proposed solution was implemented and tested experimentally on a fiber optic link with high attenuation and multiple optical connectors. Transient signals during locking were recorded to investigate the system’s behavior in real environment. The system was evaluated in the link causing synchronization losses every 17 min on average. During measurements over 3 days, the whole system was synchronized for over 99.98% of time despite these difficult conditions.

The aim of the present study was to explore the role of temporal intelligence in English as a Foreign Language (EFL) learners’ self-regulation and self-efficacy. To this end, a general temporal intelligence (GTI-S) scale was designed based on the subconstructs of time in the literature. The scale, along with the learning self-regulation questionnaire (SRQ-L) and the English self-efficacy scale was administered to 520 EFL learners. To validate the GTI-S, confirmatory factor analysis (CFA) was run. The results of Pearson product-moment correlations demonstrated significantly positive relationships between temporal intelligence and controlled self-regulation, automatic self-regulation and self-efficacy (p<.05). Moreover, the findings of multiple regressions revealed that Linearity of Time, Economicity of Time, and Multitasking are the most important subconstructs of time with relation to these variables.

Low-power consumption and long-distance transmission are two problems that have to be solved by the application of broadband power line communication for the automatic meter reading system. To reduce the power consumption of the communication module, based on the analysis of the composition of the power consumption, some methods are proposed. From the communication chip level and the module circuit level, the design scheme of low-power consumption is given. To solve the problem of transmission distance, a frequency band of 2.44 MHz~5.6 MHz is used as the main working frequency band. The communication module supports multiple frequency bands. Using this feature, the optimal frequency band is adaptively selected for communication and automatic switching, which further improve the transmission distance. Field application shows that the above methods effectively decrease the power consumption of the communication module and extend the transmission distance.

To avoid of manipulating search engines results by web spam, anti spam system use machine learning techniques to detect spam. However, if the learning set for the system is out of date the quality of classification falls rapidly. We present the web spam recognition system that periodically refreshes the learning set to create an adequate classifier. A new classifier is trained exclusively on data collected during the last period. We have proved that such strategy is better than an incrementation of the learning set. The system solves the starting–up issues of lacks in learning set by minimisation of learning examples and utilization of external data sets. The system was tested on real data from the spam traps and common known web services: Quora, Reddit, and Stack Overflow. The test performed among ten months shows stability of the system and improvement of the results up to 60 percent at the end of the examined period.