Beyond the formal/informal economy binary hierarchy

Purpose – This paper aims to evaluate critically the conventional binary hierarchical representation of the formal/informal economy dualism which reads informal employment as a residual and marginal sphere that has largely negative consequences for economic development and needs to be deterred. Design/methodology/approach – To contest this depiction, the results of 600 household interviews conducted in Ukraine during 2005/2006 on the extent and nature of their informal employment are reported. Findings – Informal employment is revealed to be an extensively used form of work and, through a richer and more textured understanding of the multiple roles that different forms of informal employment play, a form of work that positively contributes to economic and social development, acting both as an important seedbed for enterprise creation and development and as a primary vehicle through which community self-help is delivered in contemporary Ukraine. Research limitations/implications – This survey reveals that depicting informal employment as a hindrance to development and deterring engagement in this sphere results in state authorities destroying the entrepreneurial endeavour and active citizenship that other public policies are seeking to nurture. The paper concludes by addressing how this public policy paradox might start to be resolved. Originality/value – This paper is one of the first to document the role of informal employment in nurturing enterprise creation and development as well as community exchange.

Binary sparse nonnegative matrix factorization

This paper presents a fast part-based subspace selection algorithm, termed the binary sparse nonnegative matrix factorization (B-SNMF). Both the training process and the testing process of B-SNMF are much faster than those of binary principal component analysis (B-PCA). Besides, B-SNMF is more robust to occlusions in images. Experimental results on face images demonstrate the effectiveness and the efficiency of the proposed B-SNMF.

40-Gbaud 16-QAM transmitter using tandem IQ modulators with binary driving electronic signals

We propose a novel 16-quadrature amplitude modulation (QAM) transmitter based on two cascaded IQ modulators driven by four separate binary electrical signals. The proposed 16-QAM transmitter features scalable configuration and stable performance with simple bias-control. Generation of 16-QAM signals at 40 Gbaud is experimentally demonstrated for the first time and visualized with a high speed constellation analyzer. The proposed modulator is also compared to two other schemes. We investigate the modulator bandwidth requirements and tolerance to accumulated chromatic dispersion through numerical simulations, and the minimum theoretical insertion attenuation is calculated analytically.

All-optical binary counter

We experimentally demonstrate an all-optical binary counter composed of four semiconductor optical amplifier based all-optical switching gates. The time-of-flight optical circuit operates with bit-differential delays between the exclusive-OR gate used for modulo-2 binary addition and the AND gate used for binary carry detection. A movie of the counter operating in real time is presented.

A non-linear encoder using a binary counterfor pulse-code modulation

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A hierarchy of phase transitions in optimal neuronal coding:from binary to M-ary discrete optimal codes

We have investigated how optimal coding for neural systems changes with the time available for decoding. Optimization was in terms of maximizing information transmission. We have estimated the parameters for Poisson neurons that optimize Shannon transinformation with the assumption of rate coding. We observed a hierarchy of phase transitions from binary coding, for small decoding times, toward discrete (M-ary) coding with two, three and more quantization levels for larger decoding times. We postulate that the presence of subpopulations with specific neural characteristics could be a signiture of an optimal population coding scheme and we use the mammalian auditory system as an example.

Biomedical relation extraction:from binary to complex

Biomedical relation extraction aims to uncover high-quality relations from life science literature with high accuracy and efficiency. Early biomedical relation extraction tasks focused on capturing binary relations, such as protein-protein interactions, which are crucial for virtually every process in a living cell. Information about these interactions provides the foundations for new therapeutic approaches. In recent years, more interests have been shifted to the extraction of complex relations such as biomolecular events. While complex relations go beyond binary relations and involve more than two arguments, they might also take another relation as an argument. In the paper, we conduct a thorough survey on the research in biomedical relation extraction. We first present a general framework for biomedical relation extraction and then discuss the approaches proposed for binary and complex relation extraction with focus on the latter since it is a much more difficult task compared to binary relation extraction. Finally, we discuss challenges that we are facing with complex relation extraction and outline possible solutions and future directions.