Design of Non-Mapping Code in Spectral and Special Domain With Variable Weight and OFDM System

Paper has been proposed the design of non-mapping code in spectral and spatial domain with variable weight coding system and new hybrid concept of OFDM–SAC OCDMA was also explored in spectral and spatial domain. The one dimensional non mapping coding system has been extended in spectral as well as in spatial domain. Extension of code in two dimensional domains enlarges the performance, in comparison to the existing systems. The performance of system is justified by measuring the bit error rate of system against the optical system parameters. The BER is affected by varying the numbers of subscriber, data rate and power requirement for the system. The BER performance was evaluated with above mentions parameters and systems shows the better performance as compared to reported methods 2D-DPD, 2D-MD and 1D-Non mapping code. The user’s accommodation in system is higher than the 2D-DPD, 2D-MD and 1D-Non mapping code. The suggested system supports the 201% and 146% users as compared to the published methods 2D-DPD and 2D-MD Code at10-12 BER and similarly the power requirement at optimum BER is very low and system sustainability at high date rate also increases as compare to the existing schemes. The required received power for system is-12.8 dBm at 10-12 BER, which is lower as compared to the 2D-DPD and 2D-MD Codes. The system performance was determined with variation in weights in spectral and spatial dimension. The outputs observation for hybrid of OFDM with spectral/spatial OCDMA also executed where proposed system outputs effectively improve.

PERSPECTIVELE SPIRITUALE ALE MINŢII UMANE LA SFÂNTUL MAXIM MĂRTURISITORUL

The human mind is the subject of research for various fields of activity. Socio-human research fields investigate the brain's relationship with the mind, its circumstantial and relational functionality, the biological support and the complex processes of the soul, the principles of its formation and the relationship with consciousness, as well as its mode of action at the level of the human communities. Besides these perspectives, there is a special domain of mind research: that of Christian patristic spirituality. But what are the research objectives of Christian spirituality with regard to the human mind? And why did the uman mind come to the attention of the holy Fathers of the Church? From the texts of Christian anthropology and spirituality it follows that the mind has become a subject of research because the most intimate union between man and God is at its level. This study is centered on the analysis of St. Maximus the Confessor's observations about the human mind and its spiritual possibilities. The research methods relate both to the relationship between St. Maximus' observations and the previous Greek and Patristic philosophical tradition, and to their comparison with the results of modern thoughts about the mind. It can be said that the spiritual perspectives described by St. Maximus fundamentally complements the current research of about mind, because it discovers her cognitive and sensitive ability to develop in personal relationship with God.

Multidimensional Self-Attention for Aspect Term Extraction and Biomedical Named Entity Recognition

Wide attention has been paid to named entity recognition (NER) in specific fields. Among the representative tasks are the aspect term extraction (ATE) in user online comments and the biomedical named entity recognition (BioNER) in medical documents. Existing methods only perform well in a particular field, and it is difficult to maintain an advantage in other fields. In this article, we propose a supervised learning method that can be used for much special domain NER tasks. The model consists of two parts, a multidimensional self-attention (MDSA) network and a CNN-based model. The multidimensional self-attention mechanism can calculate the importance of the context to the current word, select the relevance according to the importance, and complete the update of the word vector. This update mechanism allows the subsequent CNN model to have variable-length memory of sentence context. We conduct experiments on benchmark datasets of ATE and BioNER tasks. The results show that our model surpasses most baseline methods.

Objects of Choice

Rational agents are supposed to maximize expected utility. But what are the options from which they choose? I outline some constraints on an adequate representation of an agent’s options. The options should, for example, contain no information of which the agent is unsure. But they should be sufficiently rich to distinguish all available acts from one another. These demands often come into conflict, so that there seems to be no adequate representation of the options at all. After reviewing existing proposals for how to construe decision-theoretic options and finding them all wanting, I suggest that our model of rational agents should include a special domain of ‘virtual’ option propositions to serve as formal objects of deliberation and choice.

An Improved FBPN-Based Detection Network for Vehicles in Aerial Images

With the development of artificial intelligence and big data analytics, an increasing number of researchers have tried to use deep-learning technology to train neural networks and achieved great success in the field of vehicle detection. However, as a special domain of object detection, vehicle detection in aerial images still has made limited progress because of low resolution, complex backgrounds and rotating objects. In this paper, an improved feature-balanced pyramid network (FBPN) has been proposed to enhance the network’s ability to detect small objects. By combining FBPN with modified faster region convolutional neural network (faster-RCNN), a vehicle detection framework for aerial images is proposed. The focal loss function is adopted in the proposed framework to reduce the imbalance between easy and hard samples. The experimental results based on the VEDIA, USCAS-AOD, and DOTA datasets show that the proposed framework outperforms other state-of-the-art vehicle detection algorithms for aerial images.

Part IV The Governance of Human Rights, 20 Human Rights Co-Ordination Within the UN System

This concluding chapter looks at human rights co-ordination within the UN system. For a long time, human rights in the United Nations tended to be treated as a special domain, one which might be of growing importance, but which did not necessarily need to be a consistent focus of the entire UN machinery. The importance of co-ordination and coherence for human rights promotion, however, has steadily become clearer, as the perception has grown that the human rights ‘issue area’ cannot be successfully dealt with in a vacuum or in isolation. The focus here, accordingly, is on the relationship of human rights to various relevant parts of the UN system—‘inter-regime’ co-ordination—rather than on co-ordination among human rights activities undertaken by the various members of the UN family of institutions—‘intra-regime’ co-ordination. It is the former aspect of co-ordination that has proved to be most problematic and had achieved the least progress until the recent period.

The Learning Space in Tutoring

Following the relational turn that has been observed in the areas of therapy and medical care (cf. Dinis 2010), a similar trend is beginning to develop in education. One didactic manifestation is in academic tutoring, and can be considered as a prototype of personalized education, which is founded on interactivity, dialogicality, and languaging. In our text, we focus on the phenomenon of interactivity and, predominantly, languaging as the substrate for the emergence of a special domain. Here, the learning space is defined as “a cognitive situation where a learner attunes in his/her own epistemic change.” We observe that a learning space occurs as a teacher/tutor engages with aspects of the student’s/tutee’s epistemic frame by questioning, commenting on, or perspectivizing the utterances of the student. It follows that a learning space can be necessary but not sufficient for effective learning. As we show, some research into tutoring excessively idealizes it as an effective teaching tool. In the course of our brief scrutiny we find that success of the learning process also draws on factors like: being prepared being good at hearing and using hints being willing to improvise a learning trajectory allowing some degree of interdependence with the tutor using many kinds of first-order activity