154 research outputs found
Performance analysis of the WiNC2R platform:
No full textA Cognitive Radio (CR) is an intelligent transceiver device, able to support multiple technologies, dynamic re-configurability, ease of programming and collaboration with other CR devices to improve the communication efficiency. The two key requirements for an efficient CR implementation are flexibility in operation/programming and speed.
WiNC2R (Winlab Network Centric Cognitive Radio) achieves high speed of operation using its hardware platform and flexibility using its software-configurable architecture. The current WiNC2R architecture implements an 802.11a-like OFDM flow. We evaluate the WiNC2R hardware architecture to see the modularity in the architecture, separation of data and control flow and the performance in terms of latency and throughput. To test the system, the Xilinx Bus Functional Model environment, which is designed to test the IBM standard bus-architecture-based hardware systems, is used. We use a simple ALOHA protocol in the MAC layer to communicate between two WiNC2R nodes and evaluate the performance under the best-case scenario, where the performance is only hindered by the architecture itself rather than external conditions like channel state.
The results of our basic experiments showed that for a single OFDM 802.11a-like flow, the Unit Control Modules (UCM) were idle for almost 80% of the total processing time.
We then tested the WiNC2R system to study the effects of changing the frame size. It was seen that the latencies in the WiNC2R transmitter are frame-size dependent while those in the receiver mainly depend on the size of the data in the last chunk rather than the size of the whole frame. We suggest that chunk size should be 2 OFDM symbols, and chunking be moved to MAC layer for better performance. We give analytical estimates of resulting performance improvement. In the next experiment, we describe virtualization in the WiNC2R by adding more flows. We describe the steps to implement the additional flows and estimate maximum number of concurrent flows possible.
In the last analysis, we show the effect of operating clock frequency on the performance. We prove that at 250 MHz operating frequency and 2 OFDM symbols per chunk, the current WiNC2R implementation will be able to satisfy the SIFS criterion.M.S.Includes bibliographical references (p. 72-73)by Sumit Satarka
Orthopaedic Case of the Month: A 25-Year-Old Man with a Paramedian Painful Lump over the Anterior Chest Wall
No full textEvaluation of incorporation of bone allograft at the site of implantation in various clinical conditions along with its complications
No full textBackground: Bone transplants have been used routinely in the present century for diverse purposes to unite fractures, fuse joints, and repair skeletal defects.Methods: Twelve patients with fracture, bone defect, deformity, difficulty in the fusion of bone, etc. were taken in the study for elective surgery with fresh frozen allograft in the orthopedics department with the incorporation of inclusion and exclusion criteria.Results: Out of 12 cases in this study, 7 cases were related to spinal fusion, 3 cases were of fractures with bone defects, 1 case of non-union neck femur fracture and 1 case was of revision hip arthroplasty with the acetabular bone defect. Seventy-five percent (9 patients) and 25% (3 patients) were graded fair and poor respectively in the preoperative phase. At 6 months, excellent results were obtained in 50% (6 patients), good in 25% (3 patients), fair in 25% (3 patients), while none were graded as poor in terms of clinical evaluation.Conclusions: Fresh frozen bone, a good source of abundant bone allograft, can be stored in -70° freezer for use in orthopedic surgery to fill any filling defect in the bone. Also, proper storage, better surgical technique, hospital infection control policy, antibiotic policy, preoperative use of antibiotics before surgery has a good clinical outcome
Query optimization in mobile environments
No full textWe consider the issue of optimizing queries for distributed processing in mobile environment. An interesting characteristic of mobile machines is that they depend on battery as a source of energy which may not be substantial enough. Hence, the appropriate optimization criterion in a mobile environment considers both resource utilization and energy consum- ption at the mobile client.
In this scenario, the optimal plan for a query depends on the residual battery level of the mobile client and the load at the server. We approach this problem by compiling a query into a sequence of candidate plans, such that for any state of the client-server system, the optimal plan is one of the candidate plans.
A general solution is proposed by adapting the partial order dynamic programming search algorithm (p.o dp) such that the coverset of the query is the set of candidate plans. We propose two novel algorithms, namely, the linear combinations algorithm and the linearset algorithm (referred to as the linear algorithms) that compute the linearset of a query. The linear- set of a query is an approximation to the coverset returned by p.o. dp.
We show, by means of simulation, that (1) the linearset is an excellent approximation of the coverset, (2) query compilation using the linear algorithms outperform query compilation using p.o. dp by factors ranging from 2 to 9, (3) the time taken to compile queries using the linear algorithms for the general optimization criterion is at most twice the time taken by a System R* like standard query optimizer search algorithm, and (4) the run time overhead incurred by the linear algorithms technique is minimal.
The techniques presented in the paper are of general applicability to multi-criterion optimization problems in distributed databases, where each criterion is an additive metric.Technical report lcsr-tr-21
Interactive machine learning for complex graphics selection
No full textThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 89-91).Modern vector graphics editors support the creation of a wonderful variety of complex designs and artwork. Users produce highly realistic illustrations, stylized representational art, even nuanced data visualizations. In light of these complex graphics, selections, representations of sets of objects that users want to manipulate, become more complex as well. Direct manipulation tools that artists and designers find accessible and useful for editing graphics such as logos and icons do not have the same applicability in these more complex cases. Given that selection is the first step for nearly all editing in graphics, it is important to enable artists and designers to express these complex selections. This thesis explores the use of interactive machine learning techniques to improve direct selection interfaces. To investigate this approach, I created Insight, an interactive machine learning selection tool for making a relevant class of complex selections: visually similar objects. To make a selection, users iteratively provide examples of selection objects by clicking on them in the graphic. Insight infers a selection from the examples at each step, allowing users to quickly understand results of actions and reactively shape the complex selection. The interaction resembles the direct manipulation interactions artists and designers have found accessible, while helping express complex selections by inferring many parameter changes from simple actions. I evaluated Insight in a user study of digital designers and artists, finding that Insight enabled users to effectively and easily make complex selections not supported by state-of-the-art vector graphics editors. My results contribute to existing work by both indicating a useful approach for providing complex representation access to artists and designers, and showing a new application for interactive machine learning.by Sumit Gogia.M. Eng
Optimizing queries for coarse grain parallelism
No full textWe consider the problem of optimizing select-project-join relational queries for minimum response time on parallel machines. The design of the optimizer is based on three ideas: (1) the concept and quantification of degree of coarse grain parallelism for an execution tree, (2) the design of a parallelizing scheduler for a tree of coarse grain operations which is provably near optimal, and (3) the analysis of the scheduling algorithm to obtain a cost formula for parallel execution time. The search algorithm of the optimizer is presented as a multi-dimensional dynamic programming algorithm. We present two three- dimensional search algorithms for the case when placement of relations in the parallel machine do not overlap. We propose the tree placement strategy and demonstrate, by means of examples, how the number of dimensions in the search can be significantly reduced, thereby increasing the efficiency of the search algorithm.Technical report lcsr-tr-21
Redox-Responsive Nanocapsules for the Spatiotemporal Release of Miltefosine in Lysosome: Protection against Leishmania
No full textLeishmaniasis, a vector-borne disease, is caused by intracellular parasite Leishmania donovani. Unlike most intracellular pathogens, Leishmania donovani are lodged in parasitophorous vacuoles and replicate within the phagolysosomes in macrophages. Effective vaccines against this disease are still under development, while the efficacy of the available drugs is being questioned owing to the toxicity for nonspecific distribution in human physiology and the reported drug-resistance developed by Leishmania donovani. Thus, a stimuli-responsive nanocarrier that allows specific localization and release of the drug in the lysosome has been highly sought after for addressing two crucial issues, lower drug toxicity and a higher drug efficacy. We report here a unique lysosome targeting polymeric nanocapsules, formed via inverse mini-emulsion technique, for stimuli-responsive release of the drug miltefosine in the lysosome of macrophage RAW 264.7 cell line. A benign polymeric backbone, with a disulfide bonding susceptible to an oxidative cleavage, is utilized for the organelle-specific release of miltefosine. Oxidative rupture of the disulfide bond is induced by intracellular glutathione (GSH) as an endogenous stimulus. Such a stimuli-responsive release of the drug miltefosine in the lysosome of macrophage RAW 264.7 cell line over a few hours helped in achieving an improved drug efficacy by 200 times as compared to pure miltefosine. Such a drug formulation could contribute to a new line of treatment for leishmaniasis.A. Das acknowledges SERB (India) Grants (CRG/2020/000492 and JCB/2017/000004) and DBT Grant (BT/PR22251/NNT/28/1274/2017) for supporting this research. N. Mukherjee acknowledges SERB (India) Grant PDF/2016/001437 and K. Das acknowledges the grant EMR/2015/001674 for supporting this research. Financial support from DST (DST/INSPIRE/03/2017/002477) is acknowledged by R.T. This manuscript bears CSMCRI registration no 7/2021.Pramanik, SK (corresponding author), CSIR Cent Salt & Marine Chem Res Inst, Bhavnagar 364002, Gujarat, India.
Mukherjee, N (corresponding author), CSIR Indian Inst Chem Biol, Canc Biol & Inflammatory Disorder Div, Kolkata 700032, India.
Chattopadhy, S (corresponding author), BITS Pilani, Pilani 403726, Goa, India.
Das, A (corresponding author), Indian Inst Sci Educ & Res Kolkata, Mohanpur 741246, W Bengal, India.
[email protected]; [email protected]; [email protected]
Fast search methods for biological sequence databases
No full textBiology researchers have a pressing need for data management technologies which will make the storage and retrieval of DNA and protein sequence data accurate and efficient. The volume of data generated by DNA sequencing is already massive and will continue to grow rapidly. Even if the current sequence databases are adequate today, they most assuredly will become inadequate in the future when far more sequence data has been determined. The direction of future research in sequence databases needs to be in the organization of information. This is so that the volume of data needing to be searched does not grow linearly with the volume of sequence data being discovered.
We propose to develop an index structure and retrieval system called PROXIMAL for biological sequence databases which promises to be efficient and general. This organization of the databases will complement other current efforts at sequence comparison and analysis, by providing an infrastructure in which other methods can be used to efficiently locate desired sequences. Our method relies on the use of reference strings to partition the database of sequences. It is efficient since the use of multiple reference strings for any given distance measure greatly reduces the number of sequences that must be examined, allowing us to quickly locate sequences based on a precomputed metric. It is general since multiple distance measures can be used. These include at least differing gap and mismatch weights for the basic edit distance calculation, or entirely different models of mutation. The only requirement is that there is a metric structure - mainly, that the calculations satisfy the triangle inequality. This is a weak requirement that is satisfied by many interesting measures, including those currently in wide use for sequence comparison.Technical report LCSR-TR-21
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