Miracle-dz/UniFAR-FTUs huggingface dataset:
Stable pushing manipulation with controlled two-point contact conditions for two-arm differential drive mobile robot

In this paper, we present a stable pushing manipulation of a large object with a differential-driving-mobile-base robot with two arms. To model the holding of an object with two arms, we consider the variation of friction at the two contact points between the robot and the object. This model allows us to find a relation between the location of the stable radius of pushing motion and the mobile robot wheel speeds. Also, this model unifies the grasping motion of the robot arm while pushing a large object stably, which can be done in the framework of mobile robot's pushing mechanism. The overall path planning is obtained from A* algorithm in a grid map. We verify the idea using V-rep simulation and show that the motion with shaper turns can be realized, thus the object can be pushed stably along an optimal path without switching the contact points.
Human Interactions Framework for Remote Ship Operations

The concept of unmanned ships capable of being controlled remotely is now beyond the idea and will start a revolution in maritime industry. In this context, remote ship operations refer to processes of controlling the vessels from distance such that operators obtain information from sensors. Thus, assessment and improvement of human interactions can enhance the overall performance of remote ship operations. However, there are unknown (i) human-human and (ii) human-machine relationships in remote ship operations, which increase the complexity of ship operations and therefore affect the overall system performance. This paper introduces a human interaction framework in remote ship operations domain in order to maximize system performance by minimizing conflicting operations. Hence, the proposed framework identifies the human interactions in remote control centers as well as the main differences between remote and non-remote ship operations. The current paper employed human system integration (HSI) approach in order to consider human as a sub-system. In this respect, literature review and human factor engineering technique (HFE) named similar system analysis were utilized to collect data and accordingly coding process was performed to analyze collected data. The proposed framework updated the earlier models of human-automated interactions and tailored to fit in the context of remote control centers. Besides, differences between remote and non-remote operations provide insight into human interactions in remote ship operations and consequently facilitates performance improvement actions. As a result, the proposed framework provides a solid understanding of human as a critical sub-system in remote ship domain so that gained knowledge could be used by designers and engineers.
Network Partition-Based Zonal Voltage Control for Distribution Networks With Distributed PV Systems

As the penetration level of distributed photovoltaic (PV) systems keeps increasing in distribution networks, overvoltage due to reverse power flow is an urgent issue to be addressed. This paper proposes a voltage regulation method by utilizing the voltage control capability of PV inverters. A novel network partition approach based on a community detection algorithm is presented to realize zonal voltage control in a shorter control response time using the minimum amount of reactive power compensation and active power curtailment. An improved modularity index that considers local reactive power balance is introduced to partition a distribution network into several clusters/communities with PVs based on the node voltage sensitivity analysis. An optimal reactive and active power control strategy is proposed for voltage control in each cluster. The voltage management of the overall system can be achieved by controlling each cluster separately. The proposed approach is applied to the voltage control of a practical 10 kV, 37-node feeder. Case studies on the real distribution network and a modified IEEE 123-node system are carried out to verify the feasibility and effectiveness of the proposed method.
End-User Software Engineering in K-12 by Leveraging Existing Curricular Activities

In recent years, an increasing number of people (called “end-users”) have started to perform a range of activities related to software development, such as coding with domain-specific languages. The research in the area of End-User Software Engineering (EUSE) aims at improving the quality of end-user-produced software by paying attention to the entire software life cycle. The increasing number of activities dedicated to the diffusion of coding in K-12 motivates the need of EUSE also in this environment. Students indeed will probably need to produce software in their future careers (even if not professionally), and the quality of their software may be crucial. In this work, we describe a didactic module in which the activities usually carried out in the existing study programme are exploited to introduce software engineering principles. The module does not shift the students’ attention from their main objectives and does not introduce additional lectures on software engineering topics. We describe the results of a first edition of the module that involved 17 students in a trilingual international high school. The results are promising and allow us to formulate hypotheses for further work, such as extending our approach to other activities and observe if and when students will develop a “software engineering mindset”, even without developing software.
Comparison of Constraint-handling Techniques Used in Artificial Bee Colony Algorithm for Auto-Tuning of State Feedback Speed Controller for PMSM

This article focuses on comparison of two constraint-handling techniques: Deb’s Rules (DR) and Augmented Lagrangian (AL) applied to Artificial Bee Colony (ABC) algorithm that is used for auto-tuning of state feedback speed controller (SFC) for permanent magnet synchronous motor (PMSM). The task of the optimization algorithm is to determine the elements of Q and R weighting matrices in linear quadratic regulator (LQR) optimization process. Chosen matrices guarantee the best performance according to given optimization criteria. Safety and proper operation of the motor requires the use of constraint-handling (C-H) technique. The ABC in its original version cannot handle the constrained optimization problems, therefore necessary modifications of considered optimization algorithm are depicted. Simulation and experimental results showed that AL technique allows to obtain a better convergence of ABC algorithm and a better performance of the PMSM drive than DR technique.
An Incentive-Based Multistage Expansion Planning Model for Smart Distribution Systems

The deployment of smart grids has facilitated the integration of a variety of investor assets into power distribution systems, giving rise to the consequent necessity for positive and active interaction between those investors and local distribution companies (LDCs). This paper proposes a novel incentive-based distribution system expansion planning model that enables an LDC and distributed generation (DG) investors to work in a collaborative way for their mutual benefit. Using the proposed model, the LDC would establish a bus-wise incentive program based on long-term contracts, which would encourage DG investors to integrate their projects at specific system buses that would benefit both parties. The model guarantees that the LDC will incur minimum expansion and operation costs while concurrently ensuring the feasibility of DG investors’ projects. To derive appropriate incentives for each project, the model enforces several economic metrics including internal rate of return, profit investment ratio, and discounted payback period. All investment plans committed to by the LDC and the DG investors for the full extent of the planning period are then coordinated accordingly. Several linearization approaches are applied to convert the proposed model into an MILP model. The intermittent nature of both system demand and wind- and PV-based DG output power is handled probabilistically, and a number of DG technologies are taken into account. Case study results have demonstrated the value of the proposed model.
A Simulation-driven Approach in Risk-aware Business Process Management: A Case Study in Healthcare

Risk management in business process is a key factor of success for organization as risks are part of every business activity. Errors may bring to increased costs, loss of quality as well as time delays, which in healthcare can bring to serious damages. This paper proposes a methodological framework to investigate risks in organizations by adopting a Business Process Management perspective that includes modeling and simulation of business processes. We applied our methodology to processes in the Blood Bank department of a large hospital. Our results show that a simulation-driven approach is an effective way to intercept and estimate real risks and to provide a decision support to guide the of department’s managers.
Real-Time Cloud-Based Health Tracking and Monitoring System in Designed Boundary for Cardiology Patients

Telemonitoring is not a new term, in information technology (IT), which has been employed to remotely monitor the health of patients that are located not in common places, such hospitals or medical centers. For that, wearable medical sensors, such as electrocardiography sensors, blood pressure sensors, and glucometer, have commonly been used to make possible to acquire the real-time information from the remotely located patients; therefore, the medical information is further carried, via the Internet, to perform medical diagnosis and the corresponding treatments. Like in other IT sectors, there has been tremendous progress accounted in medical sectors (and in telemonitoring systems) that changes the human life protection against several chronic diseases, and the patient’s medical information can be accessed wirelessly via Wi-Fi and cellular systems. Further, with the advents of cloud computing technology, medical systems are now more efficient and scalable in processing, such as storage and access, the medical information with minimal development costs. This study is also a piece of enhancement made to track and monitor the real-time medical information, bounded in authorized area, through the modeling of private cloud computing. The private cloud-based environment is designed, for patient health monitoring called bounded telemonitoring system, to acquire the real-time medical information of patients that resided in the boundary, inside medical wards and outside medical wards, of the medical center. A new wireless sensor network scenario is designed and modeled to keep or monitor the patients’ health information whole day, 24 hours. This research is a new secured sight towards medical information access and gives directions for future developments in the medical systems.
Improved Distribution of Resistance Switching Through Localized Ti-Doped NiO Layer With InZnOx/CuOx Oxide Diode

Asymmetric sized single oxide diode (InZnO<sub>x</sub>/CuO<sub>x</sub>) with single resistor (Ti-doped NiO) device (1D-1R) was integrated into a crossbar array at room temperature to provide high current through the diode while keeping resistance switching localized in a small area. The Ti (0.1 wt %) doped NiO layer was fabricated inside an inverted cone-structure to localize switching and improve general device performance. We were able observe resistance switching up to around 100 cycles in the 1D-1R structure. In addition, the addition of the diode to the structure acted as an external resistance suppressing overflow current during Ti-doped NiO switching from a high resistance state to a low resistance state, thus improving switching distribution in both low (average = <inline-formula> <tex-math notation="LaTeX">$3.2\times 10^{-5} \Omega $ </tex-math></inline-formula>, standard deviation = <inline-formula> <tex-math notation="LaTeX">$1.3\times 10^{-6} $ </tex-math></inline-formula>) and high (average = <inline-formula> <tex-math notation="LaTeX">$2.8\times 10^{-6} \Omega $ </tex-math></inline-formula>, standard deviation = <inline-formula> <tex-math notation="LaTeX">$6.7\times 10^{-7}$ </tex-math></inline-formula>) resistance states.
Agent-Based Simulation for Coordination Emergency Response: A Review Study

this article critically reviews the recent empirical literature on agent-based simulation for coordination emergency response. It provides an indication of the previous research related to coordination in crisis response with agent-based simulation. The goal of this paper is to propose a classification of the literature researches that based on emergency response. Our classification divides the researches into three areas. The first area is coordination in an emergency response, while the second area is coordination of emergency response with agent-based simulation; finally, the third area is agent-based simulation for emergency response. We present and analyze the works in each area supporting our presentation with the famous simulation models. As a result of our classification, we found that those works related to coordination mechanisms between multi agencies in emergency response are not covered well. Moreover, some of the researches still limited in simulating realistic agent behaviors in emergency response.
Association between Sun Exposure, Vitamin D Intake, Serum Vitamin D Level, and Immunoglobulin G Level in Patients with Neuromyelitis Optica Spectrum Disorder

Background: Neuromyelitis optica spectrum disorder (NMOSD) is a central nervous system inflammatory disorder in which immunoglobulin G (IgG) autoantibodies possibly play a pathogenic role against the aquaporin-4 water channel protein. Vitamin D may modulate B-cell function and decrease the IgG synthesis and may play a role in NMOSD as a crucial factor. The aim of this study was to investigate the relation between Vitamin D intakes from food, Vitamin D intake from sunlight exposure, blood Vitamin D levels, and IgG-neuromyelitis optica (NMO) level in serum of patients with NMOSD and NMO. Method: In this cross-sectional study, food Frequency Questionnaires (FFQ) and Sun Exposure Questionnaire (SEQ) were completed to evaluate of vitamin D intakes from food and sun light exposure. Moreover, serum levels of 25(OH) vitamin D3 and IgG-NMO were assessed in patients with NMOSD and NMO. Results: We assessed IgG-NMO levels in 29 patients with NMOSD that nine patients (n = 31%) were positive and for the rest it was negative. Sunlight exposure scale (P = 0.01) and 25(OH) D3 (P = 0.04) in IgG-NMO-negative patients were significantly more than patients with positive IgG-NMO. Age, gender, and latitude were not confounder variables. A positive significant correlation was observed between the sun exposure scale and serum levels of 25(OH) D3 in all participants (r = 0.747, P ≤ 0.001). Conclusions: Physiological variation in Vitamin D may apply a significant effect on IgG-NMO synthesis in patients with NMO. Vitamin D may have significant role in pathogenesis of NMOSD and NMO.
Security Concerns Towards Security Operations Centers

A security operations center (SOC) is a centralized place for monitoring and frequently managing the safety and security of the company's status. The primary purpose of SOC is to enable better incident detection, investigation, and response capabilities by using data from endpoint devices, logs, security systems, and network flows. Moreover, an efficient SOC can help the organizations enhance the ability of situational awareness and increase the deployment of enterprise resources to mitigate the security issues. However, the cyber threats are the significant challenges for SOC. In this paper, the authors expressed some security threats towards SOC and several solutions to fight against them.
EventQueue: An Event based and Priority aware Interprocess Communication for Embedded Systems

Modern embedded systems are targeting for isolated tasks and for an efficient Interprocess Communication (IPC). However, unifying both requirements is not a trivial challenge. In this paper, we propose EventQueue that unifies both requirements with the assistance of a hardware extension. With a message queue, the data is transferred from one task to another. Thereby, sending the data is performed in hardware, what eliminates the problem of an Operating System Priority Inversion (OS-PI) and concurrently enables the isolation of the tasks among each other. We implemented EventQueue into the mosartMCU, running in a Field Programmable Gate Array (FPGA). This is illustrated in performance evaluations. The evaluation shows a significant throughput improvement, what makes EventQueue well suitable for future real-time embedded systems.
Osteocyte‐intrinsic mTORC1 signaling restrains trabecular bone accrual in mice

Mechanistic target of rapamycin (mTOR) complex 1 (mTORC1) signaling plays important physiological roles in bone homeostasis by regulating multiple steps of osteoblast differentiation as well as its activity. However, its potential role in osteocytes has not been explored. In this study, we deleted Raptor, a specific and essential component of mTORC1, in osteocytes using Dmp1‐Cre. Deletion of Raptor in osteocytes did not affect bone development and growth, but caused compartment‐specific effects on bone mass. Osteocyte‐specific deletion of Raptor had no obvious effect on cortical bone compartments, but led to increased trabecular bone mass. Mechanistically, Raptor deletion resulted in decreased bone resorption without altering bone formation activity. Thus, our study revealed an unexpected role of osteocyte‐intrinsic mTORC1 signaling in limiting trabecular bone mass, suggesting that osteocyte‐specific inhibition of mTORC1 may be used as a novel approach to treatment of osteoporosis.
Resminostat in patients with relapsed or refractory Hodgkin lymphoma: results of the phase II SAPHIRE study

Abstract This open-label, single-arm phase II study examined efficacy, safety, pharmacokinetics, and biomarkers of histone deacetylase (HDAC) inhibitor resminostat in patients with relapsed or refractory Hodgkin lymphoma. Thirty-seven heavily pretreated patients received 600 (19 patients) or 800 mg (18 patients) oral resminostat daily for the initial 5 days of 14-day treatment cycles. Objective response rate (ORR) (primary) was 34% reaching disease control in 54% patients. Most patients (69%) showed reduced tumor size and reduced [18F]-FDG uptake in target lesions (71%). Median progression-free survival (PFS) was 2.3 months (95%CI [1.3; 3.3]) and median overall survival (OS) was 12.5 months (95%CI [9.6; 18.6]). Patients who responded or stabilized under resminostat had a 10-month longer OS than patients who progressed. Efficacy assessment, pharmacodynamics, and exploratory biomarker results followed plasma levels, showed target engagement and epigenetic modulations. Common drug-related adverse events (AEs) were nausea, vomiting, anemia, thrombocytopenia, and fatigue, mainly grade 1 or 2.
Deep Learning Based Intelligent Robot Grasping Strategy

For human, grasping is based on learning. Kids generally have poor grasping strategy compared to a grown up individual who essentially learns better grasping strategy based on experience. This research presents a vision based humanoid learning strategy for robot grasping. Given the RGB-D information of a scene with an object to be grasped, the problem of estimating the optimal grasp of a rectangle has been addressed. To solve this problem a model based on deep-learning approach with convolutional neural network has been developed. For training the model Cornell Grasping Dataset [9] has been used. The implementation involves pre-processing, whitening, normalizing and flattening the data before the features being fed to a deep neural network. The research has been implemented on Intel i7–6700HQ with RAM: 16GB, GPU: Nvidia GTX960M 4GB. Our model performs extremely well on the dataset and produces an accuracy of 94.1%. The model is characterized by simplicity, robustness, generic nature having sufficient scalability.
A ${H_\infty }$ Robust Active and Reactive Power Control Scheme for a PMSG-Based Wind Energy Conversion System

This paper presents a new <inline-formula><tex-math notation="LaTeX">${H_\infty }$</tex-math></inline-formula> based robust control scheme applied to a permanent magnet synchronous generator (PMSG) based wind energy conversion system (WECS) to regulate the active and reactive power. During the operation, parameters of the PMSG may vary which may lead to variation in the WECS dynamics, thus, the control of active power and reactive power becomes difficult. The proposed robust <inline-formula><tex-math notation="LaTeX">${H_\infty }$</tex-math></inline-formula> control scheme is designed for a WECS to achieve effective control of active and reactive power flow between WECS and grid. The effectiveness of this controller is verified by simulation and then through experimentation on a PMSG based WECS developed in laboratory. From the obtained simulation and experimental results, it is envisaged that the proposed <inline-formula><tex-math notation="LaTeX">${H_\infty }$</tex-math></inline-formula> control scheme provides excellent active and reactive power control in face of parametric uncertainties with satisfactory steady state and dynamic performances. The performances of the proposed controller is compared with that of a second order sliding mode controller. It is found that the proposed controller exhibits superior active and reactive power control performance.
Human vision inspired multi-scale line segments merging and filtering

A novel method for merging and filtering line segments which is designed based on line segments detector (LSD) is proposed. Compared to state-of-the-art, our algorithm reduces the complexity of the algorithm by implementing the property of cross product between two vectors, thus improves the speed. And inspired by human vision, a further multi-scale filtering step is conducted to capture predominant line segments and leave out trivial segments in different scaled images. Experiments on both synthetic and real images show that the merging and filtering line segments are closer to human-marked ground-truth and consistent with that of human vision system.
Sign Language Interpreter: Classification of Forearm EMG and IMU Signals for Signing Exact English *

The deaf often find themselves unable to converse with hearing people due to the presence of a severe language barrier. In this project, a system that can bridge the communication gap between the hearing and the deaf was designed. Using a single Myo armband with accelerometer, gyroscope, magnetometer and surface electromyography (sEMG) sensors, spatial information on the hand signs are collected and sent to MATLAB for processing. These raw data are filtered using wavelet denoising techniques and segmented using Teager-Kaiser energy operator (TKEO) thresholds. Various time and frequency-domain features are extracted from the processed signal. The tested artificial neural network classifier achieved a average classification rate of 97.12% for a 48 word Signing Exact English (SEE-II) lexicon.