Design of Block Transceivers with Decision Feedback Detection

This paper presents a method for jointly designing the transmitter-receiver pair in a block-by-block communication system that employs (intra-block) decision feedback detection. We provide closed-form expressions for transmitter-receiver pairs that simultaneously minimize the arithmetic mean squared error (MSE) at the decision point (assuming perfect feedback), the geometric MSE, and the bit error rate of a uniformly bit-loaded system at moderate-to-high signal-to-noise ratios. Separate expressions apply for the ``zero-forcing'' and ``minimum MSE'' (MMSE) decision feedback structures. In the MMSE case, the proposed design also maximizes the Gaussian mutual information and suggests that one can approach the capacity of the block transmission system using (independent instances of) the same (Gaussian) code for each element of the block. Our simulation studies indicate that the proposed transceivers perform significantly better than standard transceivers, and that they retain their performance advantages in the presence of error propagation.Comment: 14 pages, 8 figures, to appear in the IEEE Transactions on Signal Processin

Sustainability Issues in Benchmarking of Advanced Transit Bus Technologies

From reduced costs to improved efficiency, fleet managers are constantly striving to improve their operations in their transit bus systems. Hybrid electric buses have gained prominence among transit agencies due of their potential for improving fuel economy, reducing costs and increasing reliability over the traditional diesel bus. The question which must be asked is, are hybrid electric buses the best choice for every city? Are there single or multiple solutions which can satisfy the current and future requirements of the transit bus industry? This thesis aims to combine previous research, statistical data and survey results into a multiobjective analysis to determine an answer to these questions. Current and future technologies will be compared with each benefit and downside discussed and scored. For transit agencies looking to justify the significant capital cost increase for new technologies, this research will form the basis for an informed decision

The Chinese at work : collectivism or individualism?

One of the significant features of the national culture of the Chinese in China and other Chinese-majority societies is “collectivism” or “low individualism” (Hofstede, 1984; Hofstede and Bond, 1988; Hofstede, 1993). Does it imply that the Chinese at work are collective subjects, with “group orientation”? Different people may have different views on this question. This paper challenges such popular assumptions about Chinese work behavior of “collectivism”. Drawing on studies from P.R.C., Hong Kong, Taiwan and Singapore, it questions whether the logic of Chinese Confucian collectivism, prevailing in traditional Chinese family, still applies in today’s work organization. Based on the studies of collectivism and individualism in Chinese-majority societies, the controversial issue of collectivism is discussed, and implications for future studies of collectivism and individualism are also derived

Mammalian cells lack checkpoints for tetraploidy, aberrant centrosome number, and cytokinesis failure

BACKGROUND: Mammalian cells have been reported to have a p53-dependent tetraploidy checkpoint that blocks cell cycle progression in G1 in response to failure of cell division. In most cases where the tetraploidy checkpoint has been observed cell division was perturbed by anti-cytoskeleton drug treatments. However, other evidence argues against the existence of a tetraploidy checkpoint. Cells that have failed to divide differ from normal cells in having two nuclei, two centrosomes, a decreased surface to volume ratio, and having undergone an abortive cytokinesis. We tested each of these to determine which, if any, cause a G1 cell cycle arrest. RESULTS: Primary human diploid fibroblasts with intact cell cycle checkpoints were used in all experiments. Synchronized cells exhibited G1 arrest in response to division failure caused by treatment with either cytochalasin or the myosin II inhibitor blebbistatin. The role of tetraploidy, aberrant centrosome number, and increased cell size were tested by cell/cell and cell/cytoplast fusion experiments; none of these conditions resulted in G1 arrest. Instead we found that various drug treatments of the cells resulted in cellular damage, which was the likely cause of the arrest. When cytokinesis was blocked in the absence of damage-inducing drug treatments no G1 arrest was observed. CONCLUSIONS: We show that neither tetraploidy, aberrant centrosome number, cell size, nor failure of cytokinesis lead to G1 arrest, suggesting that there is no tetraploidy checkpoint. Rather, certain standard synchronization treatments cause damage that is the likely cause of G1 arrest. Since tetraploid cells can cycle when created with minimal manipulation, previous reports of a tetraploidy checkpoint can probably be explained by side effects of the drug treatments used to observe them

Does SNAP eligibility have racial or ethnic gradients: a geospatial social exploratory

Recently, much discussion has centred on disproportionate dependence of certain racial groups on SNAP programme. This racial overture is sparked by comments made during the Fox News-Wall Street Journal Republican Presidential debate by Newt Gingrich, former Speaker of the House, who asserted that President Obama is a ‘food stamp president’. This stereotypic SNAP overture is posting a larger narrative about government assistance and disproportionate dependence of some racial minority groups on government programmes. However, are majority of SNAP recipients fit minority profiling? We explain this overarching question through geospatial study of racial and spatial equity in government welfare programmes on food stamp. Specifically, this study explains the variations in participation votes in the food stamp programme using census tract data for counties and metropolitan areas as case examples. In addition to profiling the food stamp population across state, this study provides information required for developing the targeted nutrition education campaign

Proliferating Cloud Density through Big Data Ecosystem, Novel XCLOUDX Classification and Emergence of as-a-Service Era

Big Data is permeating through the bigger aspect of human life for scientific and commercial dependencies, especially for massive scale data analytics of beyond the exabyte magnitude. As the footprint of Big Data applications is continuously expanding, the reliability on cloud environments is also increasing to obtain appropriate, robust and affordable services to deal with Big Data challenges. Cloud computing avoids any need to locally maintain the overly scaled computing infrastructure that include not only dedicated space, but the expensive hardware and software also. Several data models to process Big Data are already developed and a number of such models are still emerging, potentially relying on heterogeneous underlying storage technologies, including cloud computing. In this paper, we investigate the growing role of cloud computing in Big Data ecosystem. Also, we propose a novel XCLOUDX {XCloudX, X…X} classification to zoom in to gauge the intuitiveness of the scientific name of the cloud-assisted NoSQL Big Data models and analyze whether XCloudX always uses cloud computing underneath or vice versa. XCloudX symbolizes those NoSQL Big Data models that embody the term “cloud” in their name, where X is any alphanumeric variable. The discussion is strengthen by a set of important case studies. Furthermore, we study the emergence of as-a-Service era, motivated by cloud computing drive and explore the new members beyond traditional cloud computing stack, developed over the last few years

Cloud and IoT-based emerging services systems

The emerging services and analytics advocate the service delivery in a polymorphic view that successfully serves a variety of audience. The amalgamation of numerous modern technologies such as cloud computing, Internet of Things (IoT) and Big Data is the potential support behind the emerging services Systems. Today, IoT, also dubbed as ubiquitous sensing is taking the center stage over the traditional paradigm. The evolution of IoT necessitates the expansion of cloud horizon to deal with emerging challenges. In this paper, we study the cloud-based emerging services, useful in IoT paradigm, that support the effective data analytics. Also, we conceive a new classification called CNNC {Clouda, NNClouda} for cloud data models; further, some important case studies are also discussed to further strengthen the classification. An emerging service, data analytics in autonomous vehicles, is then described in details. Challenges and recommendations related to privacy, security and ethical concerns have been discussed