CMFRI Annual Report 2017-2018

CMFRI in the year 2017-18 moved forward estimating the marine fish landings in the country as 3.88 million tonnes which is 6.9% more than the preceding year. Resource-wise estimation of potential yield from the depth zone up to 200 m for each maritime state was initiated by the committee constituted by Department of Animal Husbandry, Dairying and Fisheries (DADF) for revalidation of potential yield from the Indian EEZ

Marine Ecosystem Challenges & Opportunities (MECOS 3)

The Marine Biological Association of India (MBAI), established in 1958, is proud to gear up for MECOS3, the third symposium on Marine Ecosystems- Challenges and Opportunities during 7-10 January, 2020. The MBAI besides organising MECOS1 (2009) and MECOS2 (2014) has inculcated active interest and participation among its members by handling several national and international symposia/seminars, since its formation. The MBAI has 794 life members and 20 institutional members. The mandate of the MBAI is promotion of scientific research in the field of marine biology and allied sciences

Systems Support for Trusted Execution Environments

Cloud computing has become a default choice for data processing by both large corporations and individuals due to its economy of scale and ease of system management. However, the question of trust and trustoworthy computing inside the Cloud environments has been long neglected in practice and further exacerbated by the proliferation of AI and its use for processing of sensitive user data. Attempts to implement the mechanisms for trustworthy computing in the cloud have previously remained theoretical due to lack of hardware primitives in the commodity CPUs, while a combination of Secure Boot, TPMs, and virtualization has seen only limited adoption. The situation has changed in 2016, when Intel introduced the Software Guard Extensions (SGX) and its enclaves to the x86 ISA CPUs: for the first time, it became possible to build trustworthy applications relying on a commonly available technology. However, Intel SGX posed challenges to the practitioners who discovered the limitations of this technology, from the limited support of legacy applications and integration of SGX enclaves into the existing system, to the performance bottlenecks on communication, startup, and memory utilization. In this thesis, our goal is enable trustworthy computing in the cloud by relying on the imperfect SGX promitives. To this end, we develop and evaluate solutions to issues stemming from limited systems support of Intel SGX: we investigate the mechanisms for runtime support of POSIX applications with SCONE, an efficient SGX runtime library developed with performance limitations of SGX in mind. We further develop this topic with FFQ, which is a concurrent queue for SCONE's asynchronous system call interface. ShieldBox is our study of interplay of kernel bypass and trusted execution technologies for NFV, which also tackles the problem of low-latency clocks inside enclave. The two last systems, Clemmys and T-Lease are built on a more recent SGXv2 ISA extension. In Clemmys, SGXv2 allows us to significantly reduce the startup time of SGX-enabled functions inside a Function-as-a-Service platform. Finally, in T-Lease we solve the problem of trusted time by introducing a trusted lease primitive for distributed systems. We perform evaluation of all of these systems and prove that they can be practically utilized in existing systems with minimal overhead, and can be combined with both legacy systems and other SGX-based solutions. In the course of the thesis, we enable trusted computing for individual applications, high-performance network functions, and distributed computing framework, making a <vision of trusted cloud computing a reality

Comparative analysis of coal fatalities in Australia, South Africa, India, China and USA, 2006-2010

Coal mining (especially underground) is considered one of the most hazardous industries, and as a result considerable focus is applied to eliminating or mitigating hazards through careful mine planning, equipment selection and certification, and development of management systems and procedures. Regulatory agencies have developed in-house methods for reporting, classification and tracking of fatalities and other incidents according to the type of event, often including consideration of different hazard types. Unfortunately, direct comparison of mining safety statistics between countries is confounded by considerable differences in the way that individual countries classify specific fatalities or incidents. This paper presents a comparative analysis of coal mining fatality data in Australia, South Africa, India, China and the United States from 2006 to 2010. Individual classification definitions are compared between the five countries, and methods presented to normalise each country’s hazard definitions and reporting regimes around the RISKGATE framework of seventeen different priority unwanted events (or topics). Fatality data from individual countries is then re-classified according to the different RISKGATE topics, thereby enabling a comparative analysis between all five countries. This paper demonstrates the utility and value of a standard classification approach, and submits the RISKGATE framework as a model for classification that could be applied globally in coal mining. RISKGATE is the largest health and safety project ever funded by the Australian coal industry (http://www.riskgate.org) to build an industry body of knowledge to assist in managing common industry hazards. A comprehensive knowledge base has been captured for risk management of tyres, collisions, fires, isolation, strata underground, ground control open cut, explosions, explosives, manual tasks and slips/trips/falls. This has been extended to outburst, coal burst and bumps, interface displays and controls, tailings dams and inrush

Is carbon monoxide sensing an effective early fire detection option for underground coal mines?

The ability of carbon monoxide (CO) sensing to detect early stage smouldering of fixed plant fires in underground coal mines was recently assessed as part of an ongoing fire detection research project. Experiments were carried out to record the level of CO concurrent at the time of alarm activation of a Video Based Fire Detection (VBFD) system. The tests were carried out under simulated mine conditions within the SIMTARS facility at Redbank, Queensland. The experimental setup initially located the CO sensors in the positions at where they would typically be installed underground. On testing the experimental setup, it was found that the amount of CO produced from simulated overheating conveyor belt bearing housings did not display a reading on the CO sensors. The VBFD system however detected smoke and alarmed on each of the trial tests. To enable the experiments to proceed and a comparison to be made, the CO sensors were moved considerably closer to the weak pyrolysis fire source. The question of CO sensor capability in typical operational mine positions was highlighted as a result of this experiment. Computational Fluid Dynamics (CFD) modelling was used to estimate the fire size required to activate CO sensors under typical mining conditions. This modelling reinforced the limitations in using CO detectors on fixed plant. As such, the study presented here indicates that CO sensing may not be the most effective early fire detection option available, and that further research and development work with VBFD should be undertaken

Commissioning adiabatic oven testing - an inter-laboratory comparison

Adiabatic oven testing for spontaneous combustion assessment has been a primary method used by the Australian and New Zealand coal industries for input to the development of Principal Hazard Management Plans for mining operations. Consistency of results is important to ensure that the ratings obtained are accurate and reliable for maintaining the integrity of the database used to compare between mines and for obtaining site specific relationships. This paper presents the results from commissioning tests of four new adiabatic ovens at two different laboratories, which show the high level of reproducibility and repeatability needed for confidence in planning of future mining operations. The results cover a range of coal self-heating rates to show the validity of the testing and the reliability of the adiabatic ovens

RISKGATE and Australian coal operations

The major Australian Coal Association Research Program (ACARP) project, RISKGATE has now completed three years of knowledge capture and system development. The body of knowledge for risk management of tyres, collisions, fires, isolation, strata underground, ground control open cut, explosions, explosives underground, explosives open cut, manual tasks and slips/trips/falls was launched in December 2012. Recently, the project added knowledge about outbursts, coal bumps and bursts, human-machine interface, tailings dams, occupational hygiene and inrush to the original 11 topics. In 2014, the project plans (pending ACARP funding approval) to focus on issues around Fitness for Work. RISKGATE provides an environment for knowledge capture and knowledge exchange to drive innovation and cross industry sharing of current practice in the identification, assessment and management of risk. By capturing operational knowledge from industry experts, RISKGATE provides a cumulative corporate memory at a time of high personnel turnover in the coal industry. RISKGATE is the largest single ACARP Occupational Health and Safety (OHS) initiative to date. This paper presents an overview of the first seventeen topics, topic structures, and contrasts and inter-relationships between topics. The second part of the paper discusses some early steps that companies are taking to integrate RISKGATE into their operations; and conclude with some thoughts on where RISKGATE can go in the future

Optimisation of waste-dump lift heights for pre-strip operations

The optimisation of waste dump design parameters is a vital aspect that has the potential to significantly influence operational costs within mining operations. This research study investigates the effects waste dump lift height has on a truck-shovel coal mining operation. The analysis focusses upon simulating various dump lift heights in a truck-shovel operation in order to determine the optimal overall dump lift height. The dump lift height is the height to which each dump level or lift is constructed. The optimal height will therefore be determined by plotting the simulated cost results for each height and undergoing a comparative study. Additional factors incorporated within the simulation results include the cost of haulage, and ancillary equipment works (dozers, graders and water cartsto maintain the dump and construct haul roads to each new dump lift. Generating results from the research analysis to closely resemble real world applications, current mine data is incorporated within each simulation, including dig, dump and equipment data obtained from King 2 North pit of the Meandu mine located in Queensland

Personality Identification from Social Media Using Deep Learning: A Review

Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed

Recent Development of Hybrid Renewable Energy Systems

Abstract: The use of renewable energies continues to increase. However, the energy obtained from renewable resources is variable over time. The amount of energy produced from the renewable energy sources (RES) over time depends on the meteorological conditions of the region chosen, the season, the relief, etc. So, variable power and nonguaranteed energy produced by renewable sources implies intermittence of the grid. The key lies in supply sources integrated to a hybrid system (HS)