A Greedy Clustering Algorithm Based on Interval Pattern Concepts and the Problem of Optimal Box Positioning
We consider a clustering approach based on interval pattern concepts. Exact algorithms developed within the framework of this approach are unable to produce a solution for high-dimensional data in a reasonable time, so we propose a fast greedy algorithm which solves the problem in geometrical reformulation and shows a good rate of convergence and adequate accuracy for experimental high-dimensional data. Particularly, the algorithm provided high-quality clustering of tactile frames registered by Medical Tactile Endosurgical Complex.
Background. Tactile perception is an essential source of information. However instrumental registration and automated analysis of tactile data is still at an initial point of the development. Recently a Medical Tactile Endosurgical Complex (MTEC) has been introduced into clinical practice as a universal instrument for intrasurgical registration of tactile images. Images registered by MTEC have very limited resolution both in terms of a number of tactile pixels and a number of discretization levels. In this study we investigated whether this resolution is sufficient for reliable pattern recognition. Methods. Our study used a set of artificial samples which included six sample types. In particular, four of these types directly tested the ability to discriminate patterns with the same embedment projection sizes but different curvatures, or similar curvatures but different projection sizes. Two widely used machine learning methods were evaluated: random forests and k-nearest neighbors. These methods were applied to points representing registered tactile images in a relatively low-dimensional feature space. Additionally an in-silico cloning of images was used to increase classification reliability. Results. Both classification methods – random forests and k-nearest neighbors – showed good classification reliability with accuracy 68.6% and 72.9% on the validation set, respectively. These values are more than four times higher than an accuracy of six-class “random classifier”. Random forests additionally provided evaluation of importance of features used for classification. Conclusion. Despite poor resolution of tactile images registered by MTEC a combination of conventional machine learning methods with a specific feature set and specific tricks provides highly reliable results of automated analysis of these images even in case of nontrivial tasks such as sample classification with very similar classes.
Introduction. Automated analysis of tactile images registered by specialized medical tools is a novel domain, which results promptly find their applications in clinical practice. Medical Tactile Endosurgical Complex (MTEC) is currently the only commercially available device for intraoperative instrumental mechanoreceptoric palpation. One of the main challenges related to processing data generated by MTEC is heterogeneity detection in tactile images. This problem is highly important because it is a key step of localization of visually undetectable pathologies using instrumental palpation. Objectives. One of the main difficulties related to the problem of heterogeneity detection is a possibility to vary contact angle between mechanoreceptor and sample during tactile examination, so the aim of the research was to develop a method for automated contact angle identification and detection of heterogeneity in tactile images registered by MTEC. Methods. The proposed method of a tactile press contact angle estimation is based on classification with a specifically designed feature space. For heterogeneity detection we developed two different approaches. The first one is based on separation of heterogeneity detector into several components corresponding to similar contact angles. The second approach uses standard classification approach with contact angle as a high weighted element of the feature space. Results. Validation on a set of samples modeling normal tissues and pathologies showed high accuracy for contact angle identification. Both methods of heterogenity detection provided approximately the same accuracy clearly outperforming previously available methods in case of significant deviations of a contact angle from zero. Conclusion. The methods developed provide an accurat solution for problems of contact angle identification and detection of heterogeneity even in case of significant contact angle deviations, and such deviations are unavoidable in clinical practice, especially in minimally-invasive surgery.
Background: Robotic surgery undergoes its wide acceptance achieved due to minimizing trauma to patients. However, currently robotic surgery lacks a tactile feedback, and it is an essential limiting factor for its further expansion. The problem can be solved by utilization of Medical Tactile Endosurgical complex (MTEC). This complex measures and displays tactile properties of tissues during endoscopic surgeries in real time. It was developed in Lomonosov Moscow State University and officially admitted for clinical use in 2012. Materials and method: MTEC palpation device performs tactile examinations via pressure sensors located in the operating head of the device under a soft membrane. Sensors wirelessly transmit measurement results to a computer in real time. Computer performs processing and output of tactile data to a standard monitor and to specialized tactile display from which data can be read simply via a finger. Processing includes automated analysis of registered tactile data aimed at the identification of heterogeneities which simplifies the identification of lesion boundaries. The utilization of MTEC in endoscopic surgery was tested from January 2015 to December 2015 in hospital No. 31 (Moscow). Nine elective surgeries were performed with da Vinci robotic system (Intuitive Surgical, USA): 2 gastrectomies, 2 stomach resections, 2 resections of pancreas, 2 prostatectomies and 1 right hemicolectomy. Patients’ ages were from 30 to 76. During the surgeries an assistant performed tactile examination under the guidance of surgeon. Operating surgeon identified boundaries of pathological process using a tactile display, and assistant inspected the visualization of tactile data. Results: MTEC was first tested on visually identifiable lesions in stomach and intestine (5 cases). In all cases it correctly localized boundaries of pathological processes. Then the method was applied to pancreas and prostate pathologies and also led to correct decisions in all cases, including a case in which the whole pancreas was involved in process and hence no boundaries were detectable. Conclusion: Utilization of MTEC provides a tactile feedback in robotic surgery thus increasing its capabilities by correct identification of boundaries of a pathological process in the absence of sufficient visual data.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
The geographic information system (GIS) is based on the first and only Russian Imperial Census of 1897 and the First All-Union Census of the Soviet Union of 1926. The GIS features vector data (shapefiles) of allprovinces of the two states. For the 1897 census, there is information about linguistic, religious, and social estate groups. The part based on the 1926 census features nationality. Both shapefiles include information on gender, rural and urban population. The GIS allows for producing any necessary maps for individual studies of the period which require the administrative boundaries and demographic information.
Existing approaches suggest that IT strategy should be a reflection of business strategy. However, actually organisations do not often follow business strategy even if it is formally declared. In these conditions, IT strategy can be viewed not as a plan, but as an organisational shared view on the role of information systems. This approach generally reflects only a top-down perspective of IT strategy. So, it can be supplemented by a strategic behaviour pattern (i.e., more or less standard response to a changes that is formed as result of previous experience) to implement bottom-up approach. Two components that can help to establish effective reaction regarding new initiatives in IT are proposed here: model of IT-related decision making, and efficiency measurement metric to estimate maturity of business processes and appropriate IT. Usage of proposed tools is demonstrated in practical cases.