Conceptual design and error analysis of a cable-driven parallel robot

This paper develops the conceptual design and error analysis of a cable-driven parallel robot (CDPR). The earlier error analysis of CDPRs generally regarded the cable around the pulley as a center point and neglected the radius of the pulleys. In this paper, the conceptual design of a CDPR with pulleys on its base platform is performed, and an error mapping model considering the influence of radius of the pulleys for the CDPR is established through kinematics analysis and a full matrix complete differential method. Monte Carlo simulation is adopted to deal with the sensitivity analysis, which can directly describe the contribution of each error component to the total orientation error of the CDPR by virtue of the error modeling. The results show that the sensitivity coefficients of pulleys’ geometric errors and geometric errors of the cables are relatively larger, which confirms that the cable length errors and pulleys’ geometric errors should be given higher priority in design and processing.

Investigating the transparency of reporting in two-sample summary data Mendelian randomization studies

Background: Two-sample Mendelian randomization (2SMR) is an increasingly popular epidemiological method that uses genetic variants as instruments for making causal inferences. Clear reporting of methods employed in such studies is important for evaluating their underlying quality. However, the quality of methodological reporting of 2SMR studies is currently unclear. Objectives: We aimed to assess the reporting quality of studies that used MR-Base, one of the most popular platforms for implementing 2SMR analysis. Methods: We searched Web of Science Core Collection, PsycInfo, MEDLINE, EMBASE and citations listed in Google Scholar of the MR-Base descriptor paper for any published MR study that used MR-Base during any component of the MR analysis. Studies were screened by two independent reviewers. We created a bespoke reporting checklist to evaluate reporting quality of 2SMR studies. Information was extracted by at least two independent reviewers. Results: 87 studies were included in the primary analysis, of which 14 had at least 10 phenotypes. Reporting quality was generally poor with a mean of 53% (SD = 14%) of items reported in each study. Many items required for evaluating the validity of key assumptions made in MR were poorly reported: only 44% of studies provided sufficient details for assessing if the variant associates with the exposure ('relevance' assumption), 31% for the assessing if there are any variant-outcome confounders ('independence' assumption), 89% for the assessing if the variant causes the outcome independently of the exposure ('exclusion restriction' assumption), and 32% for assumptions of falsification tests. We found no evidence of a change in reporting over time and findings were similar in a random sample of MR studies that did not use the MR-Base platform. Discussion: The quality of reporting of two-sample Mendelian randomization studies in our sample was generally poor. Journals and researchers should implement the STROBE-MR guidelines to improve reporting quality. Other: Funding: ESRC, Regression: This study pre-registered on the OSF, and the protocol can be found at DOI 10.17605/OSF.IO/NFM27

A review of data mining ontologies

PurposeThis work provides a generic review of the existing data mining ontologies (DMOs) and also provides a base platform for ontology developers and researchers for gauging the ontologies for satisfactory coverage and usage.Design/methodology/approachThe study uses a systematic literature review approach to identify 35 DMOs in the domain between the years 2003 and 2021. Various parameters, like purpose, design methodology, operations used, language representation, etc. are available in the literature to review ontologies. Accompanying the existing parameters, a few parameters, like semantic reasoner used, knowledge representation formalism was added and a list of 20 parameters was prepared. It was then segregated into two groups as generic parameters and core parameters to review DMOs.FindingsIt was observed that among the 35 papers under the study, 26 papers were published between the years 2006 and 2016. Larisa Soldatova, Saso Dzeroski and Pance Panov were the most productive authors of these DMO-related publications. The ontological review indicated that most of the DMOs were domain and task ontologies. Majority of ontologies were formal, modular and represented using web ontology language (OWL). The data revealed that Ontology development 101, METHONTOLOGY was the preferred design methodology, and application-based approaches were preferred for evaluation. It was also observed that around eight ontologies were accessible, and among them, three were available in ontology libraries as well. The most reused ontologies were OntoDM, BFO, OBO-RO, OBI, IAO, OntoDT, SWO and DMOP. The most preferred ontology editor was Protégé, whereas the most used semantic reasoner was Pellet. Even ontology metrics for 16 DMOs were also available.Originality/valueThis paper carries out a basic level review of DMOs employing a parametric approach, which makes this study the first of a kind for the review of DMOs.

BRINGING C2 CLOUD SOLUTIONS ON THE MILITARY FIELD

There is a permanent demand from the operational military echelons to have C2 systems up and running in terms of hours from the moment of request. Even more, complementary C2 systems should be available in real time, all the time. The areas of specializations of different BOSs that a C2 system should integrate or make use of the exchanged data put a high pressure on the software architecture and the technological stack the C2 solution should be based on. We develop C2 software solutions that offer core services to military organizations, from tactical echelons to tactical-operational echelons. Deploying the same solution on several nodes is not an easy task. Maintaining, but improving with new functionalities a software solution already deployed on the field is a complex tax, requires a sophisticated logistic process, long planning and execution phases. In time, discrepancies could appear among different installed versions and is hard to maintain such configurations. Aiming to offer to Romanian Army a C2 software solution that is fast, modern, scalable, easy to deploy, capable to run online 24/24h we switched to a cloud technological stack for our C2 solution and we intend to have the same C2 base platform on all our future deployments.

Prosthodontics Using Removable Platform Switching Technologies (Multiunit, On1) as Exemplified by Conical Connection Implant Systems for Early and Immediate Loading

The removable platform switching technology (multiunit, Оn1) was tested intraoperatively using the passive placement technique as exemplified by a conical connection implant system, which makes it possible to visually control the placement of these platforms with respect to the alveolar bone in the correct orthopedic position. The technology is characterized by a rapid epithelialization of tissues around the base platform until the final integration of the implant, minimal trauma in the emergence profile zone, and an improved minimally invasive orthopedic protocol for working on a removable platform switching base.

Multiple Face Tracking using Kalman and Hungarian Algorithm to Reduce Face Recognition Computational Cost

Currently, research in face recognition systemsmainly utilized deep learning to achieve high accuracy. Usingdeep learning as the base platform, per frame image processingto detect and recognize faces is computationally expensive,especially for video surveillance systems using large numbers ofmounted cameras simultaneously streaming video data to thesystem. The idea behind this research is that the system does notneed to recognize every occurrence of faces in every frame. Weused MobileNet SSD to detect the face, Kalman filter to predictface location in the next frame when detection fails, andHungarian algorithm to maintain the identity of each face.Based on the result, using our algorithm 87.832 face that mustbe recognized is reduced to only 204 faces, and run at the realtime scenario. This method is proven to be used in surveillancesystems by reducing computational cost.

ROLE OF BASE PLATFORM TO PREPARE PARPATI KALPANA W.S.R. TO RASA PARPATI

Parpati Kalpana is one of the famous Kalpanas of Rasashastra which is widely used and considered as a boon for digestive disorders. The Parpati name is given to this Kalpana as per its Papad or Parpata – thin flake – like appearance. Parpati Kalpana is mainly divided into Sagandha and Nirgandha Parpati Kalpana. Rasa Parpati is the type of Sagandha Parpati Kalpana. To prepare Parpati kalpana, at least one ingredient should get liquefied at normal heating and should get solidified when it gets cooled down, not only that, to get the thin flake like structure specific pressure needs to be applied. In present study Rasa Parpati was prepared by using Samaguna Kajjali (Equal quantity of Parada and Gandhaka) and to check the cooling effect and the role of base platform; here three different platforms were made i.e. cow dung and wet clay mixed platform, only wet clay platform (Earthen platform) and ice block platform. Total nine samples of Rasa Parpati were prepared, three on each platform to check which platform is convenient to prepare Rasa Parpati. The average thickness of Rasa Parpati was found minimum (2.83 mm) on cow dung and wet clay mixed platform whereas the maximum (4 mm) on ice block platform i.e. 4 mm. Average thickness of Rasa Parpati made on earthen platform was 3.57 mm which is thicker than the Cow dung and wet clay mixed platform and thinner than the ice cube platform. Which indicates the best platform to make thinnest Parpati is cow dung and wet clay mixed platform.

How accessories add value to a platform: the role of innovativeness and nonalignability

Purpose This study aims to distinguish between the indispensable (software) versus discretionary (accessories) complementary products to a platform. It investigates the impact of accessories on increasing the perceived value and sales of a base platform. In particular, the role of two distinct characteristics of accessories – innovativeness and structural nonalignability – in driving the sales of the base platform. Design/methodology/approach Combining sales data from the US video gaming industry with primary data on the above two aspects of accessories, this study quantifies the effect of accessories portfolio on the sales of three brands of video gaming platforms. Findings A distinct network externality arises from accessories for video gaming platforms, above and beyond the effects of game titles. Importantly, the average level of innovativeness and nonalignability of the accessories portfolio, as well as the frequency of introduction of highly innovative and/or nonalignable accessories positively impact the sales of the platform. Research limitations/implications This research seeks to address the gap in the innovation literature on the role of discretionary complementary products (i.e. accessories) on platform sales. Future research should examine this in other platform contexts as well. Practical implications Managers of platform-mediated products should give due consideration to accessories, as an important driver of the sales of the platforms. Product managers can leverage the advantage of innovative and nonalignable accessories to enhance consumer demand for the platform. Originality/value This study is the first to conceptualize and empirically verify the network externality arising from accessories, a heretofore much neglected component of platform-based markets.