Marek Kulbacki

Bio: Marek Kulbacki is an academic researcher from Polish-Japanese Academy of Information Technology. The author has contributed to research in topics: Motion capture & Cluster analysis. The author has an hindex of 8, co-authored 42 publications receiving 246 citations. Previous affiliations of Marek Kulbacki include Polish Academy of Sciences.

Survey of Drones for Agriculture Automation from Planting to Harvest

Abstract: Farmers explore the capabilities for applications of Robotic Process Automation (RPA) with image processing, pattern recognition and machine learning, so its logical to ask where best to apply this technology for maximum effect. Machines can do automated tasks better, cheaper and faster. One can use the camera from the sky and measure things on the earth especially on cropland from drones and satellites. Over time, drones have increased in capabilities and fallen in cost, and their use has greatly expanded especially in complex terrain. High quality remote sensing with spectral imaging using drones makes them interesting for regular use in Precision Agriculture (PA). Drones are often used in agriculture in ways that were highly controversial only a short time ago even there are no unified legislation on drones usage in agriculture. In this paper we address problem of Remote Sensing (RS) technologies combined with Unmanned Aerial System (UAS) platforms to support and develop selected agriculture operations like map or sensor-based Variable Rate Application (VRA).

Unsupervised Learning Motion Models Using Dynamic Time Warping

Abstract: This paper concerns essential, practical problem in automatic animation human-like figures with the support of informatics technologies connected with motion capture domain. The main problem we want to solve is partition set of primitive motions into appropriate groups according to similarity between motions. Up to now, experiments in systems of this kind, appeared be not too adequate to needs. In this situation, we had been faced with the necessity of creating new methods for supporting process of managing motion data. We construct motion models to easier extract features of given motions. Using these models we propose measure of discrepancy between motions. It shows how two motions are similar to each other, normalizes length of motions and decreases high dimension of considered motion data, so clustering may take place in dimensionally reduced space.

The Effect of Millisecond Pulsed Electric Fields (msPEF) on Intracellular Drug Transport with Negatively Charged Large Nanocarriers Made of Solid Lipid Nanoparticles (SLN): In Vitro Study

Abstract: Drug delivery technology is still a dynamically developing field of medicine. The main direction in nanotechnology research (nanocarriers, nanovehicles, etc.) is efficient drug delivery to target cells with simultaneous drug reduction concentration. However, nanotechnology trends in reducing the carrier sizes to several nanometers limit the volume of the loaded substance and may pose a danger of uncontrolled access into the cells. On the other hand, nanoparticles larger than 200 nm in diameter have difficulties to undergo rapid diffusional transport through cell membranes. The main advantage of large nanoparticles is higher drug encapsulation efficiency and the ability to deliver a wider array of drugs. Our present study contributes a new approach with large Tween 80 solid lipid nanoparticles SLN (i.e., hydrodynamic GM-SLN-glycerol monostearate, GM, as the lipid and ATO5-SLNs-glyceryl palmitostearate, ATO5, as the lipid) with diameters DH of 379.4 nm and 547 nm, respectively. They are used as drug carriers alone and in combination with electroporation (EP) induced by millisecond pulsed electric fields. We evaluate if EP can support the transport of large nanocarriers into cells. The study was performed with two cell lines: human colon adenocarcinoma LoVo and hamster ovarian fibroblastoid CHO-K1 with coumarin 6 (C6) as a fluorescent marker for encapsulation. The biological safety of the potential treatment procedure was evaluated with cell viability after their exposure to nanoparticles and EP. The EP efficacy was evaluated by FACS method. The impact on intracellular structure organization of cytoskeleton was visualized by CLSM method with alpha-actin and beta-tubulin. The obtained results indicate low cytotoxicity of both carrier types, free and loaded with C6. The evaluation of cytoskeleton proteins indicated no intracellular structure damage. The intracellular uptake and accumulation show that SLNs do not support transport of C6 coumarin. Only application of electroporation improved the transport of encapsulated and free C6 into both treated cell lines.

A Review on UAV-Based Applications for Precision Agriculture

Abstract: Emerging technologies such as Internet of Things (IoT) can provide significant potential in Smart Farming and Precision Agriculture applications, enabling the acquisition of real-time environmental data. IoT devices such as Unmanned Aerial Vehicles (UAVs) can be exploited in a variety of applications related to crops management, by capturing high spatial and temporal resolution images. These technologies are expected to revolutionize agriculture, enabling decision-making in days instead of weeks, promising significant reduction in cost and increase in the yield. Such decisions enable the effective application of farm inputs, supporting the four pillars of precision agriculture, i.e., apply the right practice, at the right place, at the right time and with the right quantity. However, the actual proliferation and exploitation of UAVs in Smart Farming has not been as robust as expected mainly due to the challenges confronted when selecting and deploying the relevant technologies, including the data acquisition and image processing methods. The main problem is that still there is no standardized workflow for the use of UAVs in such applications, as it is a relatively new area. In this article, we review the most recent applications of UAVs for Precision Agriculture. We discuss the most common applications, the types of UAVs exploited and then we focus on the data acquisition methods and technologies, appointing the benefits and drawbacks of each one. We also point out the most popular processing methods of aerial imagery and discuss the outcomes of each method and the potential applications of each one in the farming operations.

Drug Delivery Strategies for Platinum-Based Chemotherapy

Abstract: Few chemotherapeutics have had such an impact on cancer management as cis-diamminedichloridoplatinum(II) (CDDP), also known as cisplatin. The first member of the platinum-based drug family, CDDP’s potent toxicity in disrupting DNA replication has led to its widespread use in multidrug therapies, with particular benefit in patients with testicular cancers. However, CDDP also produces significant side effects that limit the maximum systemic dose. Various strategies have been developed to address this challenge including encapsulation within micro- or nanocarriers and the use of external stimuli such as ultrasound to promote uptake and release. The aim of this review is to look at these strategies and recent scientific and clinical developments.

Using derivatives in time series classification

Abstract: Over recent years the popularity of time series has soared. Given the widespread use of modern information technology, a large number of time series may be collected during business, medical or biological operations, for example. As a consequence there has been a dramatic increase in the amount of interest in querying and mining such data, which in turn has resulted in a large number of works introducing new methodologies for indexing, classification, clustering and approximation of time series. In particular, many new distance measures between time series have been introduced. In this paper, we propose a new distance function based on a derivative. In contrast to well-known measures from the literature, our approach considers the general shape of a time series rather than point-to-point function comparison. The new distance is used in classification with the nearest neighbor rule. In order to provide a comprehensive comparison, we conducted a set of experiments, testing effectiveness on 20 time series datasets from a wide variety of application domains. Our experiments show that our method provides a higher quality of classification on most of the examined datasets.

Vision-Based Detection of Unsafe Actions of a Construction Worker: Case Study of Ladder Climbing

Abstract: About 80–90% of accidents are caused by the unsafe actions and behaviors of employees in construction. Behavior management thus plays a key role in enhancing safety, and particularly, behavior observation is the most critical element for modifying workers’ behavior in a safe manner. However, there is a lack of practical methods to measure workers’ behavior in construction. To analyze workers’ actions, this paper uses an advanced and economical depth sensor to collect motion data and then investigates consequent motion-analysis techniques to detect the unsafe actions of workers, which is the main focus of this paper. First, motion data are transformed onto a three-dimensional (3D) space as a preprocess, motion classification is performed to identify a typical prior, and the selected prior is used to detect the same action in a testing data set. As a case study, motion data for unsafe actions in ladder climbing (i.e., backward-facing climbing, climbing with an object, and reaching far to a side) are...

The value of ultrasonography in predicting arthritis in auto-antibody positive arthralgia patients: a prospective cohort study

Abstract: IntroductionUltrasonography (US) has better sensitivity than clinical evaluation for the detection of synovitis in early rheumatoid arthritis (RA). Patients presenting with arthralgia and a positive anti-citrullinated protein antibodies (ACPA) and/or Rheumatoid Factor (IgM-RF) status are at risk for developing RA. In the present study, US utility and predictive properties in arthralgia patients at risk for the development of arthritis were studied.Methods192 arthralgia patients with ACPA and/or IgM-RF were included. Absence of clinical arthritis was confirmed by two physicians. US was performed by one of two trained radiologists of any painful joint, and of adjacent and contralateral joints. Joint effusion, synovitis and power Doppler (PD) signal in the synovial membrane of the joints and tenosynovitis adjacent to the joint were evaluated and classified on a 4-grade semi-quantitative scale. Grade 2-3 joint effusion, synovitis, tenosynovitis and grade 1-3 Power Doppler signal were classified as abnormal.ResultsForty-five patients (23%) developed arthritis after a mean of 11 months. Inter-observer reliability for synovitis and PD was moderate (kappa 0.46, and 0.56, respectively) and for joint effusion low (kappa 0.23). The prevalence of tenosynovitis was too low to calculate representative kappa values. At joint level, a significant association was found between US abnormalities and arthritis development in that joint for joint effusion, synovitis and PD. At patient level, a trend was seen towards more arthritis development in patients who had US abnormalities for joint effusion, synovitis, PD and tenosynovitis.ConclusionsUS abnormalities were associated with arthritis development at joint level, although this association did not reach statistical significance at patient level. US could potentially be used as a diagnostic tool for subclinical arthritis in seropositive arthralgia patients. However, further research is necessary to improve test characteristics.