Parallel Sampling-Pipeline for Indefinite Stream of Heterogeneous Graphs using OpenCL for FPGAs

In the field of data science, a huge amount of data, generally represented as graphs, needs to be processed and analyzed. It is of utmost importance that this data be processed swiftly and efficiently to save time and energy. The volume and velocity of data, along with irregular access patterns in graph data structures, pose challenges in terms of analysis and processing. Further, a big chunk of time and energy is spent on analyzing these graphs on large compute clusters and/or data-centers. Filtering and refining of data using graph sampling techniques are one of the most effective ways to speed up the analysis. Efficient accelerators, such as FPGAs, have proven to significantly lower the energy cost of running an algorithm. To this end, we present the design and implementation of a parallel graph sampling technique, for a large number of input graphs streaming into a FPGA. A parallel approach using OpenCL for FPGAs was adopted to come up with a solution that is both time- and energyefficient. We introduce a novel graph data structure, suitable for streaming graphs on FPGAs, that allows time- and memory-efficient representation of graphs. Our experiments show that our proposed technique is 3x faster and 2x more energy efficient as compared to serial CPU version of the algorithm

Power-Efficient and Highly Scalable Parallel Graph Sampling using FPGAs

Energy efficiency is a crucial problem in data centers where big data is generally represented by directed or undirected graphs. Analysis of this big data graph is challenging due to volume and velocity of the data as well as irregular memory access patterns. Graph sampling is one of the most effective ways to reduce the size of graph while maintaining crucial characteristics. In this paper we present design and implementation of an FPGA based graph sampling method which is both time- and energy-efficient. This is in contrast to existing parallel approaches which include memory-distributed clusters, multicore and GPUs. Our strategy utilizes a novel graph data structure, that we call COPRA that allows time- and memory-efficient representation of graphs suitable for reconfigurable hardware such as FPGAs. Our experiments show that our proposed techniques are 2x faster and 3x more energy efficient as compared to serial CPU version of the algorithm. We further show that our proposed techniques give comparable speedups to GPU and multi-threaded CPU architecture while energy consumption is 10x less than GPU and 2x less than CPU

Interprofessional Education: A Basic Need of Healthcare Department in Pakistan

Inter professional education (IPE) is the core concept of healthcare department in most of the developed countries on both student and professional level. There is no objection on its necessity. Top ranking universities of the world, especially of developed countries are working on IPE. But some of developing countries like Pakistan are almost unaware of this concept. No one is having the basic concept of IPE, except few, and they are not practicing in IPE so far. Talking about Punjab, there is no awareness for the concept of IPE. It is the need of our healthcare department that we must introduce IPE to improve healthcare quality. This survey was conducted to check the readiness for IPE among pharm D and MBBS students in different institutes of medicine and pharmacy of Lahore. Team went to different pharmacy and medical colleges and asked the students to fill in a questionnaire having 19 items, which was rated by the students on Likert scale. The result shows a conflict in the opinion of pharmacy and medical students. Team also interviewed the respondents shortly. This interview showed many reasons explained by medical students for their response but the most prominent one was the superiority complex. The need of the hour is to introduce IPE in universities for changing the attitude of medical students towards IPE

Predictability of extreme daily returns and Preference for lottery-like stocks in an emerging market

This study investigates the presence of the MAX effect – stocks with extreme daily (positive) return in the current month perform poorly in the following month – in the Pakistani stock market (PSX). Similar to the US, Europe, and Chinese stock markets, we find a negative effect of MAX on risk-adjusted returns. Furthermore, we find that the MAX effect persists even if we extend the holding period to three- and six-month. Our results are robust for both portfolio-level and firm-level cross-sectional analyses and across subperiods, size groups, and alternative factor definitions and models. Interestingly, contrary to findings reported elsewhere, we find that the MAX effect in Pakistan exists only when the overall economy is in an expansion state. A battery of tests suggests that triviality in MAX effect during economic contraction in Pakistan is driven by the more negative subsequent performance of low-MAX stocks (short-leg), whereas, in other markets, more negative subsequent performance of high-MAX stocks (long-leg) is evident during economic downturns. Our potential explanation is partially supported by the theoretical model of Palfrey & Wang, who find that demand for speculative stocks (i.e. lottery-like stocks) is higher during ‘good’ economic news (expansion) than ‘bad’ economic news (contraction)

Tracheal inujry due to blunt chest trauma: a rare surgical emergency

Tracheal injury is a rare complication of blunt chest trauma. The patients usually present with signs of respiratory distress. Primary repair is the treatment of choice in case of large defects, while small tears can be managed conservatively. Immediate operation is recommended to improve deteriorating pulmonary function. The decrease in mortality and long-term morbidity depends on early diagnosis. We report a case of tracheal injury due to non-penetrating thoracic trauma which was successfully managed with surgery

STOCK MARKET COINTEGRATION: EVIDENCE FROM DEVELOPED AND DEVELOPING EQUITY MARKETS

This study examined the relationship between KSE and stockmarkets of developed and developing countries for the period of 2000-2012. Cointegration approach showed that one cointegrationequation exists in KSE and developed countries equity markets andtwo cointegration equations exist in KSE and developing countriesequity markets case. Granger causality test showed a uni-directionalrelationship between KSE and developed and developing markets,and a bi-directional relationship with Taiwan’s equity market.Variance decomposition analysis showed that most of the changes inKSE are due to its own dynamics in both the developed and developingmarkets. Correlation matrix shows that there is a weak or nocorrelation between the KSE and developed and developing countriesso the benefit of diversification can be achieved by investing in KSE

PERFORMANCE EVALUATION OF A MULTICARRIER MIMO SYSTEM BASED ON DFT-PRECODING AND SUBCARRIER MAPPING

The ever-increasing end user demands are instigating the development of innovative methods targeting not only data rate enhancement but additionally better service quality in each subsequent wireless communication standard. This quest to achieve higher data rates has compelled the next generation communication technologies to use multicarrier systems e.g. orthogonal frequency division multiplexing (OFDM), while also relying on the multiple-input multiple-output (MIMO) technology. This paper is focused on implementing a MIMO-OFDM system and on using various techniques to optimize it in terms of the bit-error rate performance. The test case considered is a system implementation constituting the enabling technologies for 4G and beyond communication systems. The bit-error rate optimizations considered are based on preceding the OFDM modulation step by Discrete Fourier Transform (DFT) while also considering various subcarrier mapping schemes. MATLAB-based simulation of a 2 × 2 MIMO-OFDM system exhibits a maximum of 2 to 5 orders of magnitude reduction in bit-error rate due to DFT-precoding and subcarrier mapping respectively at high signal-to-noise ratio values in various environments. A 2-3dBs reduction in peak-to-average power ratio due to DFT-precoding in different environments is also exhibited in the various simulations

A comprehensive review of vehicle detection using computer vision

A crucial step in designing intelligent transport systems (ITS) is vehicle detection. The challenges of vehicle detection in urban roads arise because of camera position, background variations, occlusion, multiple foreground objects as well as vehicle pose. The current study provides a synopsis of state-of-the-art vehicle detection techniques, which are categorized according to motion and appearance-based techniques starting with frame differencing and background subtraction until feature extraction, a more complicated model in comparison. The advantages and disadvantages among the techniques are also highlighted with a conclusion as to the most accurate one for vehicle detection