A scalable sparse Cholesky based approach for learning high-dimensional covariance matrices in ordered data

Machine Learning - Covariance estimation for high-dimensional datasets is a fundamental problem in machine learning, and has numerous applications. In these high-dimensional settings the number of...     

Development of an Innovative Bituminized Jute Paving Fabric (BJPF) Along with its Commercial Field Trials for Potential Application in the Field of Geotechnical Construction with an Eye Towards Global Concern

In the last quarter of the twentieth century, a new class of materials, Geosynthetics, emerged prospectively leading significant innovation in the design of geotechnical and geoenvironmental systems. Geotextiles have proven to be among the most versatile and techno-economically viable ground modification materials playing a significant role in modern pavement design and maintenance techniques. With the growing environmental concern across the globe, technologists, researchers have inclined towards the natural geotextile where Jute Geotextile (JGT) is one of the potential candidates. But, JGT has been restricted mainly as underlay in road construction. Hence, there is an urgent need to design and develop a precise innovative fabric as overlay on existing pavements and other emerging civil works to stay technically and economically competitive in the global market. Such a fabric will not only prove techno-economically viable but will also reduce the carbon foot-print generation to a large extent. This paper delineates the development of Grey Jute Paving Fabric (GJPF) followed by its bituminization with suitable type and grade of bitumen to develop Bituminized Jute Paving Fabric (BJPF). The BJPF will enhance the life of the overlay thereby reducing the cost of maintenance as well as serving as a partial substitute of bitumen mastic.     

Influence of surface energy on the nanoindentation response of elastically-layered viscoelastic materials

In the context of integrated nonlinear viscoelastic contact mechanics, a nonlinear finite element model is developed to predict and analyze the quasistatic response of nanoindentation problems of an elastically-layered viscoelastic materials considering the surface elasticity effects. Effects of surface energy are accounted for by employing the Gurtin–Murdoch continuum model for surface elasticity. The linear viscoelastic response is modeled by the Schapery’s creep model with a Prony’s series to express the transient component in the creep compliance. The viscoelastic constitutive equations are cast into a recursive form that needs only the previous time increment rather than the entire strain history. To satisfy the contact constraints exactly, the Lagrange multiplier method is adopted to enforce the contact conditions into the system. The equilibrium indentation configuration is obtained through the Newton–Raphson iterative procedure. The developed model is verified then applied to investigate the quasistatic nanoindentation response of two different indentation problems with different geometry and loading conditions. Results show the significant effects of surface energy and viscoelasticity on the quasistatic nanoindentation response.     

Optimize adaptive media playout using dynamic fuzzy logic control for video streaming

Multimedia Tools and Applications - Adaptive Media Playout (AMP) controls adapt playout rate to prevent buffer outage and to reduce delay in playout. Most AMP techniques use buffer fullness or its...     

Numerical investigation on the electronic components' cooling for different coolants by finite element method

In this study, we conducted a numerical simulation to examine the cooling performance of an aluminum finned heat sink attached to a silicon chip, placed in a chamber of a rectangular cross-section. The heat sink is cooled by convective heat transfer utilizing nine commercially available gaseous coolants, namely air, hydrogen, helium, nitrogen, oxygen, carbon dioxide, freon12 vapor, propane, and ammonia. To select an appropriate coolant for electronic devices in terms of thermal–hydraulic performance, the maximum temperature on the chip domain and the associated pressure drop in the cooling channel as a function of coolant velocity are analyzed for the aforementioned fluids. It has been found that the minimum temperature is recorded for propane and freon12 vapor, which is approximately 31.1°C, for a coolant velocity of 0.5 m/s, but freon12 vapor shows the highest pressure drop, approximately 900 mPa, among all coolants. In the overall velocity regime, hydrogen shows the best cooling performance in terms of both cooling capacity and hydrodynamic characteristics. But considering safety issues, helium can be a better alternative. This comprehensive study provides a better understanding of different coolant performances, which will aid engineers to develop an effective cooling technique to accommodate the inexorably rising power demand.     

Oil palm bunch ripeness classification using fluorescence technique

Oil palm is Malaysia’s major agriculture product and it covers approximately 5 million hectares of Malaysia’s land. Limited land resources have been an important factor that motivated the need to increase oil extraction rate (OER). OER of oil palm fresh fruit bunches (FFB) depends highly on their maturity stage. The ripe oil palm FFB will produce high OER while the under ripe and over ripe oil palm FFB will produce less oil. Thus, this paper presents a method of classification between oil palm FFB into ripe, under-ripe and over-ripe categories. This research was done at an oil palm plantation in peninsular Malaysia. A total of two-hundred and ten oil palm FFB that consist of seventy bunches for each category of under-ripe, ripe and over-ripe had been used. Each bunch was scanned ten times randomly with a hand-held multi-parameter fluorescence sensor called Multiplex®3. The parameter measured was the Blue-to-Red Fluorescence Ratio (BRR_FRF) obtained from blue-green (447 nm) and far-red (685 nm) emission signal by using ultraviolet (UV) light emitting diode as excitation light source. The novel contribution of this research is to prove that the oil palm FFB maturity can be determined using the Blue-to-Red Fluorescence ratio index. This is based to our finding of a significant difference among the three categories of ripeness based on the parameter. Classification and Regression Tree (C&RT) method was proposed in this paper. Hundred-fifty samples were used to develop the model by trained it using C&RT method and the remaining sixty samples for the test component. By using the C&RT method, the results show the best accuracy of overall testing classification is 90%. This research will be useful for future development of non-destructive, automatic and real time oil palm FFB grading system.     

Screening for lipid depositor of Indonesian microalgae isolated from seashore and peat-land

The screening for finding the lipid producer of indigenous Indonesian tropical microalgae that obtained from peat-land at Riau, Sumatra and seashore at Lombok has carried out. Preliminary screening was done by selection on faster growing algae from 44 (forty-four) isolates. 10 (ten) isolates were chosen for further analysis. Out of 10 selected isolates shows that five isolates have indication rapid growth and high content of lipid, furthermore those chose isolates were observed comprehensively, namely LIPI11-2-Al005, LIPI11-2-Al010, LIPI11-2-Al015, LIPI11-2-Al018, and LIPI11-2-Al019. The microalgae are belong to the eukaryotic microalgae and its seem to be closed to Chlorophytes that has cell nuclear with an envelope, light green chloroplast, thick cell wall, round and elongated cell features. Cultivation of the microalgae in laboratory condition (1 L) has shown that lipid content was about 20–35% base in cell dry weight. The highest lipid content was found in the isolate LIPI11-2-Al018 of 30.74% per dry weight cell. LIPI11-2-A1018 therefore was test for scale up cultivation reach the culture volume of 5 L in the cylindrical photobioreactor, and expected to be source of triglycerides and lipids for biodiesel ingredient.     

Minimising total cost with regular and emergency outsourcing sources: a neuro-dynamic programming approach

This study models and explains the business situation of an organisation which has regular and emergency outsourcing sources and where decisions have to be made at the beginning of every period regarding how much to order from these sources, so as to balance between different cost components of current and future periods. Previous works in this area have tried to attack this problem with dynamic programming. In this project, neuro-dynamic programming has been applied, and the reasons for doing so have been clearly stated. This model not only derives policies in order to minimise the expected total discounted cost over a period of time, but also enables the system to learn to make such decisions, and to improve its actions by using reinforcement learning. The performance of the present work has been measured quantitatively and has been compared with the models stated in literature. This study will be very useful for the organisations where such business problems exist or are likely to exist. This study will also be of great use to researchers, who are keen to understand and model the given business situation with distribution independent demand based models.