Some issues in the sliding mode control of rigid robotic manipulators

This thesis investigates the problem of robust adaptive sliding mode control for nonlinear rigid robotic manipulators. A number of robustness and convergence results are presented for sliding mode control of robotic manipulators with bounded unknown disturbances, nonlinearities, dynamical couplings and parameter uncertainties. The highlights of the research work are summarized below : • A robust adaptive tracking control for rigid robotic manipulators is proposed. In this scheme, the parameters of the upper bound of system uncertainty are adaptively estimated. The controller estimates are then used as controller parameters to eliminate the effects of system uncertainty and guarantee asymptotic error convergence. • A decentralised adaptive sliding mode control scheme for rigid robotic manipulators is proposed. The known dynamics of the partially known robotic manipulator are separated out to perform linearization. A local feedback controller is then designed to stabilize each subsystem and an adaptive sliding mode compensator is used to handle the effects of uncertain system dynamics. The developed scheme guarantees that the effects of system dynamics are eliminated and that asymptotic error convergence is obtained with respect to the overall robotic control system. • A model reference adaptive control using the terminal sliding mode technique is proposed. A multivariable terminal sliding mode is defined for a model following control system for rigid robotic manipulators. A terminal sliding mode controller is then designed based on only a few uncertain system matrix bounds. The result is a simple and robust controller design that guarantees convergence of the output tracking error in a finite time on the terminal sliding mode

D-Tunes: Configuration Engine for Geo-Replicated Cloud Storage

When developing a web-based application, developers are facing stringent requirements to balance the latency, scalability and availability for their cloud database. Application developers need a specific replication configuration strategy based on the requirement of their application. To deal with this problem, some geo-replicated cloud strategy systems have emerged recently, like Cassandra. This project serves to design a web tool that can help configure the best replication strategies for geo-distributed data stores, which uses quorum-based protocols. Currently, our web tool D-Tunes, require a minimum input from users and generate specific scripts based on the inputs user provided. The program running these scripts can output a text result and also map a figure showing the recommended replication strategy. The results of D-Tunes recommend the best replication strategies including the number of replicas, the location of replicas and read/write quorum size. Our web-tool also generates the applicable strategy, which is a simulation of the real experiment on EC2 and Probe test-bed with Cassandra system. In conclusion, this project has successfully provides cloud application developers a strategy of data-store configuration and has contributes to the ongoing research on cloud computing for Cassandra based solution

Energy Measurement of SPDY Protocol on Mobile Platform

The past few years have witnessed an explosive growth in mobile Internet data traffic with web browsing being one of the key activities on mobile devices. There is tremendous interest in optimizing mobile web. In this regard, a new protocol called SPDY was introduced by Google to augment web browsing, however it\u27s impact on the device energy consumption is not clearly understood. In this work we evaluate the energy characteristics of SPDY-based web browsing on mobile devices. In order to measure the energy consumption of web activities, we use AT&T’s ARO [1]. This tool is widely accepted and used by the industry as well as academia for radio (LTE) energy measurement. However the tool was initially designed as a GUI and hence the efficiency for handling large-scaled data was compromised. The first part of the project involves optimizing ARO so that the program runs automatically on a fairly large amount of data with minimum time. In this process we reduced the running time of ARO by a factor of 13 in average compared to the baseline GUI version. In the second part of the project, we set up a SPDY proxy to be used in our evaluations, since there are limited number of websites that support SPDY at this moment. Further we conduct an initial evaluation comparing SPDY proxy-based download to traditional HTTP-based download. Our initial analysis shows that for 18 out of 20 pages that we evaluated SPDY is doing better than the existing HTTP energy wise. E.g. for 50% of pages, SPDY reduces the LTE energy consumption by at least 3J (\u3e20%) while for few pages the benefits are small and sometimes it is doing worse than HTTP. As part of future work, we will extend our evaluation to get a comprehensive understanding on the energy characteristics of SPDY and compare it to other better approaches

A rare case of primary vaginal carcinoma in prolapsed uterus

Primary carcinoma is rare in gynaecological neoplasia. Vaginal carcinoma in prolapse uterus is extremely rare. We hereby present a case of 55-year-old P3L3 postmenopausal woman with complete uterine prolapse with fungating growth of 6x8 cm with two decubitus ulcers of 1x1 cm. Marginal biopsy showed well-differentiated squamous cell carcinoma of vagina. Investigation was done showed no metastasis. Patient was diagnosed with stage 2 disease. Patient underwent 5 cycles of chemotherapy with 2 cycles of radiotherapy and is being followed up. The importance of biopsy of ulcer in cases of UV prolapse in order to exclude malignancy to avoid incomplete treatment has been illustrated through this case. The need of careful evaluation of vaginal erosions in pelvic organ prolapse has been highlighted. As there is lack of well-defined treatment protocols for vaginal cancer with concurrent prolapse, the case also underlines the importance of a multidisciplinary approach involving gynaecological oncology, urogynaecology, medical oncology, surgical oncology and radiation oncology

Robotic Surgery in Gynecology: An Updated Systematic Review

The introduction of da Vinci Robotic Surgery to the field of Gynecology has resulted in large changes in surgical management. The robotic platform allows less experienced laparoscopic surgeons to perform more complex procedures. In general gynecology and reproductive gynecology, the robot is being increasingly used for procedures such as hysterectomies, myomectomies, adnexal surgery, and tubal anastomosis. Among urogynecology the robot is being utilized for sacrocolopexies. In the field of gynecologic oncology, the robot is being increasingly used for hysterectomies and lymphadenectomies in oncologic diseases. Despite the rapid and widespread adoption of robotic surgery in gynecology, there are no randomized trials comparing its efficacy and safety to other traditional surgical approaches. Our aim is to update previously published reviews with a focus on only comparative observational studies. We determined that, with the right amount of training and skill, along with appropriate patient selection, robotic surgery can be highly advantageous. Patients will likely have less blood loss, less post-operative pain, faster recoveries, and fewer complications compared to open surgery and potentially even laparoscopy. However, until larger, well-designed observational studies or randomized control trials are completed which report long-term outcomes, we cannot definitively state the superiority of robotic surgery over other surgical methods

Cost-aware multi data-center bulk transfers in the cloud from a customer-side perspective

Many cloud applications (e.g., data backup and replication, video distribution) require dissemination of large volumes of data from a source data-center to multiple geographically distributed data-centers. Given the high costs of wide-area bandwidth, the overall cost of inter-data-center communication is a major concern in such scenarios. While previous works have focused on optimizing the costs of bulk transfer, most of them use the charging models of Internet service providers, typically based on the 95th percentile of bandwidth consumption. However, public Cloud Service Providers (CSP) follow very different models to charge their customers. First, the cost for transmission is flat and depends on the location of the source and receiver data-centers. Second, CSPs offer discounts once customer transfers exceed certain volume thresholds per data-center. We present a systematic framework, CloudMPcast, that exploits these two aspects of cloud pricing schemes. CloudMPcast constructs overlay distribution trees for bulk-data transfer that both optimizes dollar costs of distribution, and ensures end-to-end data transfer times are not affected. CloudMPCast monitors TCP throughputs between data-centers and only proposes alternative trees that respect original transfer times. After an extensive measurement study, the cost savings range from 10 to 60 percent for both Azure and EC2 infrastructures, which potentially translates to millions of dollars a year assuming realistic demandsThis material is based upon work supported in part by the National Science Foundation (NSF) under Award No.1162333, . J. L. Garc ıa-Dorado is thankful for the financial support of the Jos e Castillejo Program (CAS12/00057

Antipsychotic augmentation with modafinil or armodafinil for negative symptoms of schizophrenia: systematic review and meta-analysis of randomized controlled trials

We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) of modafinil or armodafinil (ar/mod) augmentation in schizophrenia. We searched PubMed, clinical trial registries, reference lists, and other sources for parallel group, placebo-controlled RCTs. Our primary outcome variable was the effect of ar/mod on negative symptom outcomes. Eight RCTs (pooled N = 372; median duration, 8 weeks) met our selection criteria. Ar/mod (200 mg/day) significantly attenuated negative symptom ratings (6 RCTs; N = 322; standardized mean difference [SMD], −0.26; 95% CI, −0.48 to −0.04). This finding remained similar in all but one sensitivity analysis – when the only RCT in acutely ill patients was excluded, the outcome was no longer statistically significant (SMD, −0.17; 95% CI, −0.51 to 0.06). The absolute advantage for ar/mod was small: just 0.27 points on the PANSS-N (6 RCTs). Ar/mod attenuated total psychopathology ratings (7 RCTs; N = 342; SMD, −0.23; 95% CI, −0.45 to −0.02) but did not influence positive symptom ratings (5 RCTs; N = 302; mean difference, −0.58; 95% CI, −1.71 to 0.55). Although data were limited, cognition, fatigue, daytime drowsiness, adverse events, and drop out rates did not differ significantly between ar/mod and placebo groups. Fixed and random effects models yielded similar results. There was no heterogeneity in all but one analysis. Publication bias could not be tested. We conclude that ar/mod (200 mg/day) is safe and well tolerated in the short-term treatment of schizophrenia. Ar/mod reduces negative symptoms with a small effect size; the absolute advantage is also small, and the advantage disappears when chronically ill patients or those with high negative symptom burden are treated. Ar/mod does not benefit or worsen other symptom dimensions in schizophrenia