FPGA applications in signal and image processing

The increasing demand for real-time and smart digital signal processing (DSP) systems, calls for a better platform for their implementation. Most of these systems (e.g. digital image processing) are highly parallelisable, memory and processor hungry; such that the increasing performance of today�s general-purpose microprocessors are no longer able to handle them. A highly parallel hardware architecture, which offers enough memory resources, offers an alternative for such DSP implementations

A single-chip FPGA implementation of real-time adaptive background model

This paper demonstrates the use of a single-chip FPGA for the extraction of highly accurate background models in real-time. The models are based on 24-bit RGB values and 8-bit grayscale intensity values. Three background models are presented, all using a camcorder, single FPGA chip, four blocks of RAM and a display unit. The architectures have been implemented and tested using a Panasonic NVDS60B digital video camera connected to a Celoxica RC300 Prototyping Platform with a Xilinx Virtex II XC2v6000 FPGA and 4 banks of onboard RAM. The novel FPGA architecture presented has the advantages of minimizing latency and the movement of large datasets, by conducting time critical processes on BlockRAM. The systems operate at clock rates ranging from 57MHz to 65MHz and are capable of performing pre-processing functions like temporal low-pass filtering on standard frame size of 640X480 pixels at up to 210 frames per second

DeepCough: A Deep Convolutional Neural Network in A Wearable Cough Detection System

In this paper, we present a system that employs a wearable acoustic sensor and a deep convolutional neural network for detecting coughs. We evaluate the performance of our system on 14 healthy volunteers and compare it to that of other cough detection systems that have been reported in the literature. Experimental results show that our system achieves a classification sensitivity of 95.1% and a specificity of 99.5%.Comment: BioCAS-201

Digital signal processing: the impact of convergence on education, society and design flow

Design and development of real-time, memory and processor hungry digital signal processing systems has for decades been accomplished on general-purpose microprocessors. Increasing needs for high-performance DSP systems made these microprocessors unattractive for such implementations. Various attempts to improve the performance of these systems resulted in the use of dedicated digital signal processing devices like DSP processors and the former heavyweight champion of electronics design – Application Specific Integrated Circuits. The advent of RAM-based Field Programmable Gate Arrays has changed the DSP design flow. Software algorithmic designers can now take their DSP algorithms right from inception to hardware implementation, thanks to the increasing availability of software/hardware design flow or hardware/software co-design. This has led to a demand in the industry for graduates with good skills in both Electrical Engineering and Computer Science. This paper evaluates the impact of technology on DSP-based designs, hardware design languages, and how graduate/undergraduate courses have changed to suit this transition

The community-level effects of women's education on reproductive behaviour in rural Ghana

Using survey and census data for rural Ghana collected in the 1980s, this study examines the ability of women’s education to increase interest in fertility regulation and contraception among all women, regardless of their individual and household features. The study finds that, net of her own characteristics, a woman’s interest in limiting fertility and using modern contraception increase with the percent of educated women in her community. These results suggest that female education has a greater capacity to introduce novel reproductive ideas and behaviors into rural areas of Africa and thereby transform the demographic landscape in the region than is currently believed. There is also evidence that female education may undermine existing methods of regulating fertility. Other community characteristics that increase women’s interest in regulating fertility and contraceptive use in this setting include access to transportation and proximity to urban areas. However, these are not as powerful as women’s education in transforming reproductive behavior.community-level determinants of fertility, contraception, contraceptive use, education, fertility regulation, reproductive behavior, rural areas, women’s education

FLOODING AND PHYSICAL PLANNING IN URBAN AREAS IN WEST AFRICA: SITUATIONAL ANALYSIS OF ACCRA, GHANA

The need to explore the causes of the increasing incidences of flooding in West Africa in recent years motivated the investigation carried out in this research. It is natural to want to attribute the situation to climate change and the increased occurrences of high intensity rainfall predicted as a consequence. However, flooding and the devastation caused by it are not just determined by rainfall and runoff; human influences which significantly modify the nature of the ground surface and its hydrological response to rainfall do also play a major role. The research used Accra as a case study city and involved a visit to the city to interview local experts, officials of agencies responsible for flooding matters and physical planning. The visit also involved collection of data relevant to the problem and afforded the physical inspection of the infrastructural facilities in place for coping with the flooding problems. Analysis of the data revealed that for the city, there is no evidence that unusual rainfall has been occurring recently that could explain the increased occurrences of flooding being experienced. Rather, the cause of the problem is the lack of, drainage facilities to collect the storm water for safe disposal. These could in turn be attributed to the ineffective planning regulations which either ignore or even condone the illegal erection of buildings and other structures on floodplains, and the unhealthy habit of dumping refuse and other solid wastes in the usually open channel drainage systems. It is recommended that in order to have a long-lasting solution to the flooding problems, the city and others in similar situation should embrace sustainable urban drainage systems.Flooding, planning, urban cities, waste dumping.

Is Retirement Depressing?: Labor Force Inactivity and Psychological Well-Being in Later Life

This paper assesses how retirement - defined as permanent labor force non-participation in a man's mature years - affects psychological welfare. The raw correlation between retirement and well-being is negative. But this does not imply causation. In particular, people with idiosyncratically low well-being, or people facing transitory shocks which adversely affect well-being might disproportionately select into retirement. Discontinuous retirement incentives in the Social Security System, and changes in laws affecting mandatory retirement and Social Security benefits allows the exogenous effect of retirement on happiness to be estimated. The paper finds that the direct effect of retirement on well-being is positive once the fact that retirement and well being are simultaneously determined is accounted for.

GAN Augmented Text Anomaly Detection with Sequences of Deep Statistics

Anomaly detection is the process of finding data points that deviate from a baseline. In a real-life setting, anomalies are usually unknown or extremely rare. Moreover, the detection must be accomplished in a timely manner or the risk of corrupting the system might grow exponentially. In this work, we propose a two level framework for detecting anomalies in sequences of discrete elements. First, we assess whether we can obtain enough information from the statistics collected from the discriminator's layers to discriminate between out of distribution and in distribution samples. We then build an unsupervised anomaly detection module based on these statistics. As to augment the data and keep track of classes of known data, we lean toward a semi-supervised adversarial learning applied to discrete elements.Comment: 5 pages, 53rd Annual Conference on Information Sciences and Systems, CISS 201