43 research outputs found
The Risk Aversion of Banks in Emerging Credit markets: Evidence from India
No full textUsing bank-level data from India, for nine years (1995-96 to 2003-04), we examine banks’ behavior in the context of emerging credit markets. Our results indicate that the credit market behavior of banks in emerging markets is determined by past trends, the diversity of the potential pool of borrowers to whom a bank can lend, and regulations regarding treatment of NPA and lending restrictions imposed by the Reserve Bank of India. Finally, we find evidence that suggest that credit disbursal by banks can be facilitated by regulatory and institutional changes that help banks mitigate the problems associated with enforcement of debt covenants and treatment of NPA on the balance sheets. On the basis of these results, we speculate on some possible policy recommendations.Indian banking, Development, Credit-to-deposit ratio, Risk aversion
Blocked Transition And Post-Socialist Transformation: Serbia in the Nineties
No full textThis paper is showing that Serbia in the nineties was an interesting case of postsocialist transformation in spite of the greatly blocked transition. The key sign of the post-socialist transformation has been the formation of a new transformative social force – formation of entrepreneurs and of the strata of social owners. Initial transformation of ownership relations in Serbia began in the 1990-1991. period, with limited privatization of some 40% of all former “socially owned” enterprises . Privatization of such firms was practically blocked in 1992-2000. period. Some comments on ownership transformation after the regime change at the end of year 2000 are given in the paper. There was an autonomous growth of the private sector during the nineties generated by the formation of some 200.000 new private firms. It was shown in the paper that some branches, like retail trade, have been de facto privatized thanks to the predominance in trade business of new private retail trade firms. Social features of new entrepreneurs in Serbia have been analyzed, based on author’ s surveys. Positive impact of new entrepreneurs has been not only in generating and enforcing systemic changes by the end of nineties, but also in preventing overall aggravation of living conditions of people in Serbia in this period. New entrepreneurs were spreading new life orientations, innovativeness, readiness to take responsibility for one’s life, especially among the young generations. The author believes that post-socialist transformation in the nineties facilitated regime change in the Fall of year 2000.Serbia, post-socialist transformation, transition, blocked transition, entrepreneur, new entrepreneurs, spontaneous privatization
Impact of Derivatives Trading on Emerging Capital Markets: A Note on Expiration Day Effects in India
No full textThe impact of expiration of derivatives contracts on the underlying cash market ñ on trading volumes, returns and volatility of returns ñ has been studied in various contexts. We use an AR-GARCH model to analyse the impact of expiration of derivatives contracts on the cash market at the largest stock exchange in India, an important emerging capital market. Our results indicate that trading volumes were significantly higher on expiration days and during the five days leading up to expiration days (“expiration weeks”), compared with nonexpiration days (weeks). We also find significant expiration day effects on daily returns to the market index, and on the volatility of these returns. Finally, our analysis indicates that it might be prudent to undertake analysis of expiration day effects (or other events) using methodologies that model the underlying data generating process, rather than depend on comparison of mean and median alone.http://deepblue.lib.umich.edu/bitstream/2027.42/57243/1/wp863 .pd
Edge processing in IoT using approximate and in-memory computing
No full textWith a large number of sensors getting connected to the internet, scalability of
Internet of Things (IoT) has started to hinge on Edge computing-the ability to
partly process the raw data at the sensor on the edge of the network instead of
transmitting all data to the cloud. However, sensor nodes are typically highly
power-constrained due to the limited battery and also requires a long lifetime due
to difficulties in replacing nodes in many applications. Hence, this thesis focuses
on using different circuit and algorithmic techniques in particular approximate
computing, near and in-memory computing (IMC), dynamic voltage and frequency
scaling (DVFS) to reduce the energy consumption of edge devices in the Internet
of Things.
As a first example, we choose predictive maintenance (PdM), one of the most important
applications pertaining to IoT in Industry 4.0. Machine learning is used
to predict the failure of a machine before the actual event occurs. However, the
main challenges in PdM are (a) lack of enough data from failing machines to train
binary classifi ers, and (b) paucity of power and bandwidth to transmit sensor data
to cloud throughout the lifetime of the machine. In our work, we propose an
anomaly detection scheme that can be trained only using healthy machine data.
Our Anomaly Detection based Power Saving (ADEPOS) scheme is aimed at saving
energy by using approximate computing through the lifetime of the machine. At
the beginning of the machine's life, low accuracy computations are used when the
probability of the machine being healthy is high. However, on the detection of
anomalies, as time progresses, the anomaly detector is switched to higher accuracy
modes. Reduction in computation accuracy may be achieved in many ways,
such as reducing the number of neurons, reducing the bit width of data, dynamic
voltage frequency scaling, etc. Tested on the NASA bearing dataset, ADEPOS
demonstrates up to 8.8x reduction of neurons on average over the lifetime of bearings.
This resulted in 8.95x energy saving for microprocessor implementation and
~18.8x energy saving in an ASIC implementation, both in 65nm CMOS.
The second part of this research explores the near and in-memory computing (IMC)
to reduce the data movement between the storage and processing elements for video
processing in the application of traffic surveillance. Generally, image frames from a
camera undergo image denoising, region proposal, object classi cation, and object
tracking steps for traffic surveillance and monitoring. However, a realization of this
data-intensive computing following traditional von Neumann architecture involves
a higher energy dissipation and more substantial execution time due to the enormous
data movement between computing and storage units. Further, for stationary
cameras, there exists signi cant temporal redundancy which can be exploited by
event-driven or neuromorphic vision sensors (NVS) that report data only when
there is activity in the scene. However, due to the presence of noise, NVS pixels report
events even in the absence of actual activity. In this dissertation, a 6T-SRAM
in-memory computing based image denoising for event-based binary image (EBBI)
frame from a neuromorphic vision sensor (NVS) is presented. We suggest a nonoverlap
median lter (NOMF), an approximation of a traditional median lter for
image denoising. The NOMF enables us to implement image denoising leveraging
the inherent read disturb phenomenon of the 6T-SRAM. Besides, detecting zero
frames is easily done by IMC techniques tracking bit line voltage during ltering
operation and this can be used now to shut off the rest of the processor for ~2x
energy bene ts in urban traffic settings. Fabricated in 65nm CMOS, this chip
produces denoised frames with an energy efficiency of 51.3 TOPS/W and a peak
throughput of 134.4 GOPS at 70MHz.
As a next step, we propose a 9T-SRAM near and in-memory computing based
region proposal network for the event-based binary image frame to exploit spatial
redundancy in the valid frames. The region proposal network nds out the bounding
box encapsulating of an object which reduces the computation of an object
recognition deep neural network (DNN) by con ning the computing region surrounding
the object instead of the whole image frame. The proposed 9T-SRAM
cell enables a 1-D projection of objects on the horizontal and vertical axes of an
image. An iterative and selective search of the rising and falling edges of 1-D
projection yields the coordinates of a bounding box encapsulating an object. Simulated
in 65nm CMOS, this chip produces up to 16 region proposals per frame
and achieves ~682x energy savings compared to the digitally implemented connected
component labeling (CCL) algorithm and throughput of 1.17 frames/usec
at 200MHz.
In summary, we presented a set of algorithms and hardware solutions for energy
efficient edge computing that use approximate and in-memory compute techniques.
We have demonstrated the results in two different applications of predictive maintenance
and traffic monitoring.Doctor of Philosoph
A Cross-sectional Study of Work-Related Musculoskeletal Disorders among Construction Workers in Bangladesh
No full textThis thesis is submitted to the Department of Mechanical Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Mechanical Engineering, December 2019.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 54-58).The construction activities are closely associated with many occupational injuries. Work-related musculoskeletal disorders (WMSDs) are the most common occupational injuries faced by construction workers. WMSDs refer to a set of painful illnesses of human body muscles, tendons, nerves, ligaments, joints, etc. The construction workers also face injuries from the work site accidents. Most of the accident occurs in the construction site by falling objects on the worker’s body, workers fall from the height, electrocution, etc.. The workers feel pain in different body parts, sometimes become partial or permanent disable due to worksite accidents. There are many factors associated with the occupational injuries. Different researchers from different countries have studied the work-related musculoskeletal disorders of construction workers. As far, I know, no researchers have studied these types of disorders on Bangladeshi construction workers. Keeping this view in mind, the study investigated the work-related musculoskeletal disorders and accidental injuries among the Bangladeshi construction workers. This study also tried to find out the factors associated with Work-related musculoskeletal disorders (WMSDs). For this purpose, a cross-sectional study was conducted through a structured and Modified Nordic Questionnaire. The structured questionnaire contained the socio-demographic characteristics, the physical risk factors, environmental risk factors, and the equipment risk factors. The Modified-Standardized Nordic Questionnaire (MNDQ) is used to identify the musculoskeletal pains on different body parts over the previous year. All the questionnaires were two categories as an open-end and yes/no. In this study, a total of 450 (362 males and 88 females) construction workers aged between 18 to 65 years old were taken from the different construction sites at Jashore, Khulna and Satkhira, Bangladesh. Their main activities were mixing sand and cement, ironwork, lifting and carrying mortar, bricklaying, plastering, concrete laying and tiles fitting. The results found that overall 70.2% of workers reported that they had suffered at least one body part injury over the last 12 months. Among the nine body parts, lower back (49.80%) was the highest suffered body part and a thigh (9.60%) was the lowest suffered part. It is found the occurrences of work-related musculoskeletal disorders (WMSDs) were associated with socio-demographic characteristics such as gender, age, work experiences, working time, and working types. To minimize the work-related musculoskeletal disorders workers suggested to provide safety aid (26.70%), provide proper training and education (19.50%), to design hand tools in ergonomically (24.90%), ensuring good working environment (26.40%), and proper use of the personal protective equipment (21.80%). Most of the workers (32.20%) did not specify how to prevent work-related musculoskeletal disorders.
About 60.70% of the participant experienced with accidents during their work in the construction site. Most of the accidents occurred by the falling objects on the worker’s body (19.10%), workers fall from the height (25.30%), electrocution (3.30%) respectively. Based on the data most of the workers (29.80%) injured in different body regions due to the worksite accidents. The workers also identified the causes of accidents such as personal negligence, lack of work experience, improper use of PPE (Personal Protective Equipment), absence of a good working environment, the overload of work, and lack of safety facilities. Above allcauses, the lack of safety facilities (42.80%) reported as the highest reason behind the accidents. It is found from this study that the prevalence of work-related musculoskeletal
disorders and accidental injuries among the Bangladeshi construction workers are high. Finally, the author had made some recommendations for both workers and management of the construction sites.Md. Sumon RahmanMaster of Science in Mechanical Engineerin
Comparison of performance of shell-and-tube heat exchangers with plain and annular-finned tube bundle
No full textComparison of performance of shell-and-tube heat exchangers with conventional segmental baffles and continuous helical baffle
No full textIs my Neural Network Neuromorphic? Taxonomy, Recent Trends and Future Directions in Neuromorphic Engineering
No full textVideo for A 75kb SRAM in 65nm CMOS for In-Memory Computing Based Neuromorphic Image Denoising
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