Miracle-dz/UniFAR-FTUs huggingface dataset:
Mines and human casualties: a robotics approach toward mine clearing

An estimated 100 million landmines which have been planted in more than 60 countries kill or maim thousands of civilians every year. Millions of people live in the vast dangerous areas and are not able to access to basic human services because of landmines’ threats. This problem has affected many third world countries and poor nations which are not able to afford high cost solutions. This paper tries to present some experiences with the land mine victims and solutions for the mine clearing. It studies current situation of this crisis as well as state of the art robotics technology for the mine clearing. It also introduces a survey robot which is suitable for the mine clearing applications. The results show that in addition to technical aspects, this problem has many socio-economic issues. The significance of this study is to persuade robotics researchers toward this topic and to peruse the technical and humanitarian facets of this issue.
Application of C4.5 Algorithm in Evaluation of Railway Large Maintenance Machinery Construction

With improvement of the level of modernization and mechanization of railway infrastructure maintenance, Railway large maintenance machinery (RLMM) is considered to be one of the main equipment. We have accumulated large amounts of RLMM construction data. How to mine valuable information from these data has become an important research subject. The C4.5 algorithm of decision tree is a useful method of data mining and classification. The paper solves evaluation of RLMM construction problem based on the C4.5 algorithm. By means of extracting the attribute with maximum gain ratio as the root node of the decision tree from training sample data, the evaluation decision tree was constructed. The decision tree modeling of evaluation of RLMM construction was gained by the post-pruning approach. The experimental results and analysis show that this model has high precision and credibility.
Parasites Acquired Beta Satellite DNAs from Hominid Hosts via Horizontal Gene Transfer

Beta satellite DNA (satDNA) sequences are repeated DNA elements located in primate centromeres and telomeres, and might play roles in genome stability and chromosome segregation. Beta satDNAs mainly exist in great apes. Previous studies suggested that beta satDNAs may originate in old world monkeys. In this study, we searched both GenBank and SRA database, and identified beta satDNA sequences from the genomic sequences of 22 species. The beta satDNA sequences found in Prosimian, Dermoptera and Scandentia indicated that the origin of beta satDNAs might be as early as 80 MYA. Strikingly, beta satDNA sequences were also found in a number of some species evolutionarily far from primates, including several endoparasites of human and other great apes, which could be the results of multiple horizontal gene transfer (HGT) events. The similar phylogenic profiles between beta satDNAs in the parasite genomes and the human genome indicates that the parasite beta satDNAs have undergone similar concerted evolution and play similar roles as the beta satDNAs in primates. Highlights The ever largest scale analysis on beta satDNAs. The origin of beta satDNAs was traced back to ∼80 MYA. Mass existence of beta satDNAs in non-primate species was contributed by multiple HGT events.
Commutation instant detector for sensorless drive of BLDC motor

A commutation instant detection circuit has been designed and implemented for use in the sensorless drive of a brushless DC (BLDC) motor. The circuit consists simply of differential amplifiers and comparators, and detects the zero-crossing point of the back electromotive force difference. The circuit output is identical to that of the Hall sensor signal.
Multiobjective Optimal Structural Vibration Control using Fuzzy Logic Control System

Fuzzy logic control systems have been applied as an effective control system in various fields, including vibration control of structures. The advantage of this approach is its inherent robustness and ability to handle nonlinearities and uncertainties in structural behavior and loading. In this paper, the design of a multiobjective optimal fuzzy logic controller (FLC) for seismically excited building structures has been discussed. Acceleration and velocity information have been used as feedback to the FLC. Minimization of the peak acceleration and displacement response of the structure, nondimensionalized by an uncontrolled peak acceleration and displacement response, respectively, have been used as the two objectives. A two-branch tournament genetic algorithm has been used to find a set of Pareto-optimal solutions. The proposed multiobjective optimal FLC has been verified on a benchmark problem, namely, a "scaled model of a three-story building with an active mass driver system," and the results have been compared with the results from other control methods reported in the literature. It has been shown that the use of acceleration information, in addition to velocity as a feedback for the FLC, results in better structural performance.
Artificial neural networks modelling of the performance parameters of the Stirling engine

The Stirling engine can theoretically be very efficient to convert heat into mechanical work at Carnot efficiency. Various parameters could affect the performance of the addressed Stirling engine which is considered in optimisation of the Stirling engine for designing purpose. Through addressed factors, torque has the highest effect on the robustness of the Stirling engines. Due to this fact, determination of the referred parameters with low uncertainty and high precision is needed. To solve the mentioned obstacle, throughout this paper, a generation of intelligent model called ‘artificial neural network’ (ANN) was implemented to estimate the torque of the Stirling heat engine. In addition, highly accurate actual values of the required parameters which were gained from open literature surveys from previous studies were implemented to develop a robust intelligent model. Based on the outcomes of the ANN approach, the output results of an ANN model were close to relevant actual values with a high degree of performance.
RELIABILITY AND SENSITIVITY ANALYSIS OF A CONDITION MONITORING TECHNIQUE

A condition monitoring technique based on vibration measurements and evaluation by means of neural networks has previously been investigated. Preliminary results were promising. In this work, the reliability and the sensitivity of the method are discussed. This study has used a simulation approach to study the sensitivity. An experimentally verified simulation model which yields the internal forces in the pump has been used in combination with experimentally found transfer functions to find the vibration on the surface of the pump housing. Different designs of the valve plate have been studied to simulate an increased internal leakage in the pump. For the evaluation of simulation or measurement results, neural networks are used.
Supply Chain Performance in Electronics Manufacturing Industry

It is still not clear how supply chain management can be applied to enhance and improve the performance of the supply chain. Consequently, the purpose of this research is to investigate the effect of five different factors in supply chain on its performance. This research studies the relationship between the selected variables (i.e. quality, time, information, flexibility, and integration) and supply chain management performance. This research takes a step forward to better understand the relationship between supply chain management factors and supply chain performance by incorporating these variables into the industrial landscape of electronics manufacturing in Malaysia. Specifically by using a combination model of a unified framework combining SCOR Model (Supply Chain Council, 1997) and system approach model (Min &Mentzer, 2004). As such, the analysis in this study contributes to the empirical literature of supply chain management, policy progress, as well as managerial implications. The outcome of this study also signifies the contribution it has given towards a new shift in upgrading the manufacturing best practices in developing countries through effective supply chain management practices.
On-line leakage current monitoring of 400 kV insulator strings in polluted areas

The author replies to comments by Danikas about the paper he co-authored with I. Ramirez-Vazquez and G. Montoya-Tena (see ibid., vol.143, no.6, p.560-4, 1996) regarding the recovery period for RTV-coatings. He points out that the results were obtained on standard- and flat-type porcelain insulators without any RTV-coating, However, several tests have been carried out using the same insulator profiles with RTV-coating. The results obtained were very similar to those for uncoated insulators in a continuous salt fog test (1000 h) following the procedure mentioned in IEC1109.
A formative approach to the strategies analysis phase of cognitive work analysis

Strategies Analysis, the third phase of Cognitive Work Analysis, helps investigators consider the range of ways in which workers can perform control tasks. Most existing approaches to Strategies Analysis identify a limited number of domain-specific strategies. We present a two-phase formative Strategies Analysis method intended to expose the range of strategies possible within a work system and the likelihood that different types of strategies will be selected in different contexts. The first phase, the preparatory phase, identifies generalised constraints that affect the range and selection of strategies, and the categories of strategies that may be applied to any domain. In the second phase, the application phase, investigators use the outputs of the preparatory phase to explore the impact that different work situations, tasks and workers have on the categories of strategies most likely to be adopted.
Potential diagnostic value of novel circular RNA hsa_circ_0060927 in human colorectal cancer

Background CYP24A1 plays a role in strictly regulated vitamin D metabolism pathway and has been nominated as a prognostic biomarker for colorectal cancer (CRC). Increasing evidence suggests that circular RNAs (circRNAs) are involved in cancer initiation and progression; however, their diagnostic values in cancers as the new potential biomarkers are still not fully understood. Methods and Results In the present study, by using quantitative real-time polymerase chain reaction (qRT-PCR), we demonstrated that CYP24A1 and hsa_circ_0060927 were only transcribed in 33 and 25 out of 83 CRC tissues, respectively. In these samples, we demonstrated that CYP24A1 was up-regulated in both linear and circular forms ( P < 0.05). Furthermore, we showed that CYP24A1 and hsa_circ_0060927 transcription were induced after vitamin D treatment in HCT-116 and HT-29 colon cancer cell lines. Importantly, analysis of the ROC curve in expressed samples indicated that CYP24A1 and hsa_circ_0060927 could serve as the potential diagnostic markers of CRC, but due to the fact that these genes are not expressed in many samples, the diagnostic role of these genes could be rejected. Conclusion Taken together, for the first time, the results of our study illustrated the expression levels hsa_circ_0060927 in CRC; however, further studies are required to validate the present results.
Free vibration analysis of tall buildings with outrigger-belt truss system

In this paper a simple mathematical model is presented for estimating the natural frequencies and corresponding mode shapes of a tall building with outrigger-belt truss system. For this purposes an equivalent continuum system is analyzed in which a tall building structure is replaced by an idealized cantilever continuum beam representing the structural characteristics. The equivalent system is comprised of a cantilever shear beam in parallel to a cantilever flexural beam that is constrained by a rotational spring at outrigger-belt truss location. The mathematical modeling and the derivation of the equation of motion are given for the cantilevers with identically paralleled and rotational spring. The equation of motion and the associated boundary conditions are analytically obtained by using Hamilton`s variational principle. After obtaining non-trivial solution of the eigensystem, the resulting is used to determine the natural frequencies and associated mode shapes of free vibration analysis. A numerical example for a 40 story tall building has been solved with proposed method and finite element method. The results of the proposed mathematical model have good adaptation with those obtained from finite element analysis. Proposed model is practically suitable for quick evaluations during the preliminary design stages.
Locally optimum detector for MIMO radar in non-Gaussian clutter

The optimum Gaussian detector of MIMO radar no longer works well in non-Gaussian clutter environment. Therefore, a locally optimum (LO) detector based on alpha stable distribution is proposed for the signal detection of MIMO radar. The proposed method assumes that the MIMO radar clutter satisfies alpha stable distribution, according to the multiple-input multiple-output characteristics of the signal model, a locally optimum detection statistics for MIMO radar is presented based on the generalized Neyman-Pearson lemma. Both theoretical analysis and simulation results show that the optimum Gaussian detector suffers serious performance degradation in non-Gaussian clutter, whereas the proposed detector can achieve good performance and outperforms the Gaussian detector significantly.
Non Stationary, Broad-band Waveforms for CSEM - An Analysis with Synthetic Data

Controlled source electromagnetic (CSEM) methods are sensitive to the subsurface conductivity structure and thus had led to its use in resource exploration. Since the frequency for peak sensitivity and the exact location of an exploration target is normally unknown prior exploration, it is desirable to acquire the transfer functions for a broad range of frequencies and in a wide area. Investigations in both directions have been driven by optimising properties of the Fourier transform in order to enhance the frequency range and the source-receiver distances. Recent research on non-stationary (NS) time series analysis tools significantly enhanced processing of NS time series. This work assesses the possibility of NS source waveforms by presenting a chirp source that is highly customisable in amplitude and frequency range in order to accommodate any frequency range in combination with virtually any amplitude for each frequency (e.g. in order to counter attenuation by decreasing power from low frequencies to increase high frequency power assuming constant energy supply). A numeric example illustrates the NS waveform and that robust NS time series processing may lead reliably to the transfer functions of a 1D conductivity model. Lastly, the advantages of a freely customisable waveform design are discussed.
Vertical Position Control for Top Tensioned Riser with Active Heave Compensator

The top and bottom angles of a marine riser are of crucial importance during e.g. drilling and workover operations. A vertical position control with active heave compensator (AHC) is proposed to maintain the safety of the riser when subjected to environmental excitations. The possibility of reducing the maximum angular response level by adjusting the vertical rod position by means of an active heave compensator is investigated with a positioning algorithm based on adaptive backstepping. Riser top and bottom angles are dealt with by the algorithm in order to minimize both angles.
Finite Element Analysis of Broken Fiber Effects on Hollow Active Fiber Composites

The finite element method was used to study the performance of hollow active fiber composites (HAFC) and the effect of the fiber damage on this performance. The finite element model was developed for the simulation of the PZT-5H hollow fiber-epoxy matrix composite with single and dual electrode ‘bus’ systems. The simulations were performed for the actuation and sensing functions of the composites with healthy and broken fibers. The results of the healthy HAFC models were compared to the experimental data and numerical results found in the literature. The effect of broken fibers in the composite structure on both the actuation and sensing performance was studied. The results demonstrate that a gap in the fiber leads to actuation performance loss. The loss in the performance is directly related to the location of the fiber and its proximity to the electric potential source. The results also demonstrate that this loss could be minimized by applying a dual electrode system at both ends of the composite. In the sensing application utilizing HAFC, it was shown that these types of composites have several advantages over solid active fiber composites.
Laboratory and field trials of Coriolis mass flow metering for three-phase flow measurement

A new three-phase flow metering technology is discussed in this paper, which combines Coriolis mass flow and water cut readings and without applying any phase separation [1]. The system has undergone formal laboratory trials at TUV NEL (National Engineering Laboratory), UK and at VNIIR (National Flow Laboratory), Kazan, Russia; a number of field trials have taken place in Russia. Laboratory trial results from the TUV NEL will be described in detail. For the 50mm (2") metering system, the total liquid flow rate ranged from 2.4 kg/s up to 11 kg/s, the water cut ranged from 0% to 100%, and the gas volume fraction (GVF) from 0 to 50%. In a formally observed trial, 75 test points were taken at a temperature of approximately 40 °C and with a skid inlet pressure of approximately 350 kPa. Over 95% of the test results fell within the desired specification, defined as follows: the total (oil + water) liquid mass flow error should fall within ± 2.5%, and the gas mass flow error within ± 5.0%. The oil mass flow error.
Extrinsic Calibration of Camera and Rotating LIDAR Using Two Planes

Light detection and ranging (LIDAR) sensors are widely used in robotics. In this paper, we deal with the extrinsic calibration between camera and rotating LIDAR. It is necessary to fuse information of each system into one common coordinate system. LIDAR sensors give dense and accurate depth information than stereo system. But, camera can give more diverse information including brightness distribution and color about scene. We present extrinsic calibration algorithm using two planes where they are configured vertically compared to each other. A LIDAR is rotated using a motor to have full 3D information about the calibration structure. We find the extrinsic parameter of LIDAR with respect to the world on vertical plane using 3D information. Extrinsic parameter of camera with respect to the world can be found using traditional calibration algorithm. Finally, we can compute the extrinsic parameter between camera and LIDAR. Experimental results show the feasibility of presented algorithm.
Study on Fault Diagnosis of Ship Power System Based on Multi-Source Information Fusion Technology

This paper firstly establishes a mathematical model of ship power system, and then analyzes the characteristics and common faults of ship power system. D-S evidence theory method is used on research of common faults of the ship power system, to enhance the pertinence of fault diagnosis. By using multi-source information fusion diagnosis, the need for quantities of electrical data is reduced, and, it can effectively reduce the impact of protection or switch malfunction on the fault diagnosis of ship power system and thus improve the accuracy of diagnosis.
Historic Disposal of Munitions in U.S. and European Coastal Waters, How Historic Information Can Be Used in Characterizing and Managing Risk

Until the 1970s, disposing of industry and government waste at sea was internationally accepted as a safe and efficient practice. Salvage, destruction by open burying or open detonation, and burial on land or at sea were the only options available for addressing excess, obsolete, and unserviceable munitions prior to the 1970s. Until the Convention on the Prevention of Marine Pollution by Dumping of Wastes and Other Matter was enacted in 1972 and its protocol prohibiting sea disposal of chemical and biological agents was enacted in 1995, sea disposal of conventional and chemical munitions and other waste material was considered appropriate. A similar ban was contained in the 1993 Chemical Weapons Convention. Two types of risk are posed by sea-disposed munitions. These are chronic - adverse health impacts that result from prolonged exposure to munition constituents - and acute - injury or death caused by either detonation or direct exposure to chemical agents. Sea disposed munition type and configuration; disposal location; water body depth, current and other properties; as well as water body usage (e.g. commercial fishing, recreation, pipeline construction) are factors in determining relative risk posed by munitions. More efficient investigation and management of risks from sea-disposed munitions may be allowed through collection, analysis, and sharing of historical information.
Clinician Preimplementation Perspectives of a Decision-Support Tool for the Prediction of Cardiac Arrhythmia Based on Machine Learning: Near-Live Feasibility and Qualitative Study

Background Artificial intelligence (AI), such as machine learning (ML), shows great promise for improving clinical decision-making in cardiac diseases by outperforming statistical-based models. However, few AI-based tools have been implemented in cardiology clinics because of the sociotechnical challenges during transitioning from algorithm development to real-world implementation. Objective This study explored how an ML-based tool for predicting ventricular tachycardia and ventricular fibrillation (VT/VF) could support clinical decision-making in the remote monitoring of patients with an implantable cardioverter defibrillator (ICD). Methods Seven experienced electrophysiologists participated in a near-live feasibility and qualitative study, which included walkthroughs of 5 blinded retrospective patient cases, use of the prediction tool, and questionnaires and interview questions. All sessions were video recorded, and sessions evaluating the prediction tool were transcribed verbatim. Data were analyzed through an inductive qualitative approach based on grounded theory. Results The prediction tool was found to have potential for supporting decision-making in ICD remote monitoring by providing reassurance, increasing confidence, acting as a second opinion, reducing information search time, and enabling delegation of decisions to nurses and technicians. However, the prediction tool did not lead to changes in clinical action and was found less useful in cases where the quality of data was poor or when VT/VF predictions were found to be irrelevant for evaluating the patient. Conclusions When transitioning from AI development to testing its feasibility for clinical implementation, we need to consider the following: expectations must be aligned with the intended use of AI; trust in the prediction tool is likely to emerge from real-world use; and AI accuracy is relational and dependent on available information and local workflows. Addressing the sociotechnical gap between the development and implementation of clinical decision-support tools based on ML in cardiac care is essential for succeeding with adoption. It is suggested to include clinical end-users, clinical contexts, and workflows throughout the overall iterative approach to design, development, and implementation.