Abstract: The vigilance of the driver is important for railway safety, despite not being included in the safety management system (SMS) for high-speed train safety. In this paper, a novel fatigue detection system for high-speed train safety based on monitoring train driver vigilance using a wireless wearable electroencephalograph (EEG) is presented. This system is designed to detect whether the driver is drowsiness. The proposed system consists of three main parts: (1) a wireless wearable EEG collection; (2) train driver vigilance detection; and (3) early warning device for train driver. In the first part, an 8-channel wireless wearable brain-computer interface (BCI) device acquires the locomotive driver’s brain EEG signal comfortably under high-speed train-driving conditions. The recorded data are transmitted to a personal computer (PC) via Bluetooth. In the second step, a support vector machine (SVM) classification algorithm is implemented to determine the vigilance level using the Fast Fourier transform (FFT) to extract the EEG power spectrum density (PSD). In addition, an early warning device begins to work if fatigue is detected. The simulation and test results demonstrate the feasibility of the proposed fatigue detection system for high-speed train safety.

Abstract: In certain electricity markets, because of nonconvexities that arise from their operating characteristics, generators that follow the independent system operator's (ISO's) decisions may fail to recover their cost through sales of energy at locational marginal prices. The ISO makes discriminatory side payments to incentivize the compliance of generators. Convex hull pricing is a uniform pricing scheme that minimizes these side payments. The Lagrangian dual problem of the unit commitment problem has been solved in the dual space to determine convex hull prices. However, this approach is computationally expensive. We propose a polynomially solvable primal formulation for the Lagrangian dual problem. This formulation explicitly describes for each generating unit the convex hull of its feasible set and the convex envelope of its cost function. We cast our formulation as a second-order cone program when the cost functions are quadratic, and a linear program when the cost functions are piecewise linear. A 96-period 76-unit transmission-constrained example is solved in less than 15 s on a personal computer.

Abstract: Smart home control system can be integrated into an existing home appliances to reduce the need for human intervention, increase security and energy efficiency. However, it is still an open problem due to difficulties such as network distance, signal interference, not user friendly, increased cost and power consumption. This paper reviews various topics on smart home technologies including control system, smart home network, smart home appliance and sensor technologies for smart home. In this research, the proposed prototype of home automation allows users to remotely switch on or off any household appliance based on Internet of Things (IoT) with the enhancement of solar charger. The smartphone and/or tablet replaces the manual use of personal computer without the need for high additional cost. This prototype uses four types of sensors i.e. PIR sensor, temperature sensor, ultrasonic sensor and smoke gas sensor for automatic environmental control and intrusion detection.

Abstract: Chemical property estimation is a key component in many industrial, academic, and regulatory activities, including in the risk assessment associated with the approximately 1000 new chemical pre-manufacture notices the United States Environmental Protection Agency (US EPA) receives annually. The US EPA evaluates fate, exposure and toxicity under the 1976 Toxic Substances Control Act (amended by the 2016 Frank R. Lautenberg Chemical Safety for the 21st Century Act), which does not require test data with new chemical applications. Though the submission of data is not required, the US EPA has, over the past 40 years, occasionally received chemical-specific data with pre-manufacture notices. The US EPA has been actively using this and publicly available data to develop and refine predictive computerized models, most of which are housed in EPI Suite™, to estimate chemical properties used in the risk assessment of new chemicals. The US EPA develops and uses models based on (quantitative) structure-activity relationships ([Q]SARs) to estimate critical parameters. As in any evolving field, (Q)SARs have experienced successes, suffered failures, and responded to emerging trends. Correlations of a chemical structure with its properties or biological activity were first demonstrated in the late 19th century and today have been encapsulated in a myriad of quantitative and qualitative SARs. The development and proliferation of the personal computer in the late 20th century gave rise to a quickly increasing number of property estimation models, and continually improved computing power and connectivity among researchers via the internet are enabling the development of increasingly complex models.

Abstract: Recent telehealth studies have demonstrated minor impact on patients affected by long-term conditions. The use of technology does not guarantee the compliance required for sustained collection of high-quality symptom and physiological data. Remote monitoring alone is not sufficient for successful disease management. A patient-centred design approach is needed in order to allow the personalisation of interventions and encourage the completion of daily self-management tasks. A digital health system was designed to support patients suffering from chronic obstructive pulmonary disease in self-managing their condition. The system includes a mobile application running on a consumer tablet personal computer and a secure backend server accessible to the health professionals in charge of patient management. The patient daily routine included the completion of an adaptive, electronic symptom diary on the tablet, and the measurement of oxygen saturation via a wireless pulse oximeter. The design of the system was based on a patient-centred design approach, informed by patient workshops. One hundred and ten patients in the intervention arm of a randomised controlled trial were subsequently given the tablet computer and pulse oximeter for a 12-month period. Patients were encouraged, but not mandated, to use the digital health system daily. The average used was 6.0 times a week by all those who participated in the full trial. Three months after enrolment, patients were able to complete their symptom diary and oxygen saturation measurement in less than 1 m 40s (96% of symptom diaries). Custom algorithms, based on the self-monitoring data collected during the first 50 days of use, were developed to personalise alert thresholds. Strategies and tools aimed at refining a digital health intervention require iterative use to enable convergence on an optimal, usable design. ‘Continuous improvement’ allowed feedback from users to have an immediate impact on the design of the system (e.g., collection of quality data), resulting in high compliance with self-monitoring over a prolonged period of time (12-month). Health professionals were prompted by prioritisation algorithms to review patient data, which led to their regular use of the remote monitoring website throughout the trial. Trial registration: ISRCTN40367841 . Registered 17/10/2012.

Abstract: Internet of Things offers user interoperability and connectivity between devices, systems, services, networks and in particularly control systems. IoT involves enhancing network to proficiently collect and analyze the data from various sensors and actuators then sends the data to the mobile phone or a personal computer over a wireless connection. Building IoT has progressed essentially in the last couple of years since it has created a new era in the world of information and communication technologies. Security is becoming an important issue nowadays as the possibilities of intrusion are increasing day by day. Safety from intrusion, theft, fire and leakage of flammable gas are the most important requirements of home security system for the people. The aim of this work is to provide security and surveillance to home through internet. In this work, the proposed system is designed using ARM-11 architecture and Linux OS based Raspberry Pi-3 board, USB camera and DC motor. The DC motor is interfaced with Raspberry Pi-3 board via driving circuit (L293D) to control the door while the camera is connected to the USB port of Raspberry Pi-3 board. A webpage is provided to the end user with username and password in order to allow the entry of only authorized users. After successful login, user is able to control the door by using open and close buttons and watch the live streaming video of the desired location i.e., the vicinity of the door. A capture button is also provided in order to take a snapshot of the running video.

Abstract: The current cheapening of next-generation sequencing has led to an enormous growth in the number of sequenced genomes and transcriptomes, allowing wet labs to get the sequences from their organisms of study To make the most of these data, one of the first things that should be done is the functional annotation of the protein-coding genes But it used to be a slow and tedious step that can involve the characterization of thousands of sequences Sma3s is an accurate computational tool for annotating proteins in an unattended way Now, we have developed a completely new version, which includes functionalities that will be of utility for fundamental and applied science Currently, the results provide functional categories such as biological processes, which become useful for both characterizing particular sequence datasets and comparing results from different projects But one of the most important implemented innovations is that it has now low computational requirements, and the complete annotation of a simple proteome or transcriptome usually takes around 24 hours in a personal computer Sma3s has been tested with a large amount of complete proteomes and transcriptomes, and it has demonstrated its potential in health science and other specific projects This article is protected by copyright All rights reserved

Abstract: Magnesium AZ31 alloys have been widely used in the aerospace, automotive, and personal computer industries due to their light weight and low density. However, high chemical reactivity, poor corrosion and wear resistance limit their further use in many other fields. The plasma electrolytic oxidation (PEO) process can produce a protective oxide layer on the Mg alloy to improve its mechanical property, wear resistance, and corrosion resistance. In this work, silicon nitride (Si 3 N 4 ) nanoparticles were added into the reaction electrolyte to study their influence on the microstructure, mechanical, and anticorrosion properties of PEO coatings on AZ31 Mg alloy. The breakdown voltage for igniting the plasma discharge decreased with increasing concentration of Si 3 N 4 nanoparticles. The PEO coating without Si 3 N 4 additives in the reaction electrolyte had mainly MgAl 2 O 4 and minor MgO phases. On the other hand, when Si 3 N 4 nanoparticles were included in the PEO reaction, a Mg 2 SiO 4 phase is present. In general, the coating thickness, surface roughness, hardness and elastic modulus increased with increasing Si 3 N 4 nanoparticle concentration up to 3 g/L. A maximum hardness of 16.4 GPa was found in the coating fabricated with 3 g/L Si 3 N 4 nanoparticles added. The PEO coating fabricated using 2 g/L of Si 3 N 4 nanoparticles in its electrolyte exhibited the best corrosion resistance, high hardness, good adhesion, and low coefficient of friction in this study.

Abstract: We consider the real-time resolution of conflicts arising in real-world train management applications. In particular, given a nominal timetable for a set of trains and a set of modifications due to delays or other resources unavailability, we are aiming at defining a set of actions which must be implemented to grant safety, e.g., to avoid potential conflicts such as train collisions or headway violations, and restore quality by reducing the delays. To be compatible with real-time management, the required actions must be determined in a few seconds, hence specialized fast heuristics must be used. We propose a fast and effective parallel algorithm that is based on an iterated greedy scheduling of trains on a time-space network. The algorithm uses several sortings to define the initial train dispatching rule and different shaking methods between iterations. The performance is further enhanced by using various sparsification methods for the time-space network. The best algorithm configuration is determined through extensive experiments, conducted on a set of instances derived from real-world networks and instances from the literature. The resulting heuristic proved able to consistently resolve the existing conflicts and obtaining excellent solution quality within just two seconds of computing time on a standard personal computer, for instances involving up to 151 trains and two hours of planning time horizon.

Abstract: This paper describes a new Beagle Board-based platform for teaching and practicing interaction design for musical applications. The migration from desktop and laptop computer-based sound synthesis to a compact and integrated control, computation and sound generation platform has enormous potential to widen the range of computer music instruments and installations that can be designed, and improves the portability, autonomy, extensibility and longevity of designed systems. We describe the technical features of the Satellite CCRMA platform and contrast it with personal computer-based systems used in the past as well as emerging smart phone-based platforms. The advantages and trade-offs of the new platform are considered, and some project work is described.

Abstract: We present a fully digital procedure of designing reflective coding metasurfaces to shape reflected electromagnetic waves. The design procedure is completely automatic, controlled by a personal computer. In details, the macro coding units of metasurface are automatically divided into several types (e.g. two types for 1-bit coding, four types for 2-bit coding, etc.), and each type of the macro coding units is formed by discretely random arrangement of micro coding units. By combining an optimization algorithm and commercial electromagnetic software, the digital patterns of the macro coding units are optimized to possess constant phase difference for the reflected waves. The apertures of the designed reflective metasurfaces are formed by arranging the macro coding units with certain coding sequence. To experimentally verify the performance, a coding metasurface is fabricated by automatically designing two digital 1-bit unit cells, which are arranged in array to constitute a periodic coding metasurface to generate the required four-beam radiations with specific directions. Two complicated functional metasurfaces with circularly- and elliptically-shaped radiation beams are realized by automatically designing 4-bit macro coding units, showing excellent performance of the automatic designs by software. The proposed method provides a smart tool to realize various functional devices and systems automatically.

Abstract: Plants demonstrate dynamic growth phenotypes that are determined by genetic and environmental factors. Phenotypic analysis of growth features over time is a key approach to understand how plants interact with environmental change as well as respond to different treatments. Although the importance of measuring dynamic growth traits is widely recognised, available open software tools are limited in terms of batch image processing, multiple traits analyses, software usability and cross-referencing results between experiments, making automated phenotypic analysis problematic. Here, we present Leaf-GP (Growth Phenotypes), an easy-to-use and open software application that can be executed on different computing platforms. To facilitate diverse scientific communities, we provide three software versions, including a graphic user interface (GUI) for personal computer (PC) users, a command-line interface for high-performance computer (HPC) users, and a well-commented interactive Jupyter Notebook (also known as the iPython Notebook) for computational biologists and computer scientists. The software is capable of extracting multiple growth traits automatically from large image datasets. We have utilised it in Arabidopsis thaliana and wheat (Triticum aestivum) growth studies at the Norwich Research Park (NRP, UK). By quantifying a number of growth phenotypes over time, we have identified diverse plant growth patterns between different genotypes under several experimental conditions. As Leaf-GP has been evaluated with noisy image series acquired by different imaging devices (e.g. smartphones and digital cameras) and still produced reliable biological outputs, we therefore believe that our automated analysis workflow and customised computer vision based feature extraction software implementation can facilitate a broader plant research community for their growth and development studies. Furthermore, because we implemented Leaf-GP based on open Python-based computer vision, image analysis and machine learning libraries, we believe that our software not only can contribute to biological research, but also demonstrates how to utilise existing open numeric and scientific libraries (e.g. Scikit-image, OpenCV, SciPy and Scikit-learn) to build sound plant phenomics analytic solutions, in a efficient and effective way. Leaf-GP is a sophisticated software application that provides three approaches to quantify growth phenotypes from large image series. We demonstrate its usefulness and high accuracy based on two biological applications: (1) the quantification of growth traits for Arabidopsis genotypes under two temperature conditions; and (2) measuring wheat growth in the glasshouse over time. The software is easy-to-use and cross-platform, which can be executed on Mac OS, Windows and HPC, with open Python-based scientific libraries preinstalled. Our work presents the advancement of how to integrate computer vision, image analysis, machine learning and software engineering in plant phenomics software implementation. To serve the plant research community, our modulated source code, detailed comments, executables (.exe for Windows; .app for Mac), and experimental results are freely available at https://github.com/Crop-Phenomics-Group/Leaf-GP/releases .

Abstract: Since the personal computer usage and internet bandwidth are increasing, e-learning systems are also widely spreading. Although e-learning has some advantages in terms of information accessibility, time and place flexibility compared to the formal learning, it does not provide enough face-to-face interactivity between an educator and learners. In this study, we are proposing a hybrid information system, which is combining computer vision and machine learning technologies for visual and interactive e-learning systems. The proposed information system detects emotional states of the learners and gives feedback to an educator about their instant and weighted emotional states based on facial expressions. In this way, the educator will be aware of the general emotional state of the virtual classroom and the system will create a formal learning-like interactive environment. Herein, several classification algorithms were applied to learn instant emotional state and the best accuracy rates were obtained using kNN and SVM algorithms.

Abstract: This article combines data from the British National Readership Survey, the Audit Bureau of Circulations, and comScore to calculate how much audience attention newspapers’ print, personal computer (PC), and mobile platforms attract. The results show that, of the time spent with 11 UK national newspaper brands by their British audiences, 88.5 per cent still comes via their print editions, 7.49 per cent via mobiles, and just 4 per cent via PCs. The study reveals that the “share of consumption” of UK national newspaper brands (when measured by time spent) is less evenly distributed than commonly understood, conforming better to a logarithmic pattern than a linear one, and that a single brand—The Mail—has close to a 30 per cent market share. Such data should inform debates on, and the regulation of, media plurality. For publishers, this research calls into question the transition from print to online, showing how “dead-tree” editions are their most important platform. However, the circulation of print edition...

Abstract: In this paper Wireless Sensor Home Area Network (WSHAN) with ZigBee interfaced smart meter is designed and implemented Because of the increasing demands on electricity, traditional electric grid needs to be replaced with intelligent, robust, reliable and costly effective smart grid applications Wireless Sensor Networks (WSN) has a critical role to set up a reliable and costly effective smart electric power grid applications Our system measures energy usage, logs data real time and shows time of use (TOU) values The system also controls any device connected to power outputs While powering on and off, zero-cross of AC signal is detected to calculate phase shift The smart meter provides correct power usage and transmits data with ZigBee to PC (Personal Computer) The user monitors the power information and remotely controls the system

Abstract: Autonomous agriculture robot is one of the promising solutions for precision agriculture. This paper presents the proposed sensor and vision based agricultural robot for sowing seeds. This prototype can navigate it on any agricultural land and perform seed sowing operation simultaneously. The onboard sensors along with vision system and vision based approaches achieves the navigation and localization tasks. Self-awareness of the robot's position is determined by the global and local maps generated from Global Positioning System (GPS) and on-board vision system paired with a personal computer. This paper also presents the proposed sensor based precision seed metering and sowing mechanism. The proposed robot is a micro planter whose primary task would be to sow seeds at prefixed seeding intervals in the field. The dimensions of the proposed robot are 26.5 × 18.5 × 19.65 mm as L × B × H respectively. A suspension system has been used to maintain the stability of the vehicle and prevent it from toppling in motion.

Abstract: The invention discloses an additive manufacturing surface defect, internal defect and shape composite detection device which comprises a surface defect detection system, an internal defect detection system, a shape three-dimensional measurement system and a clamping device, wherein the surface defect detection system comprises a first CMOS industrial camera; the internal defect detection system comprises an air cylinder and a detection probe; the detection probe is used for generating a magnetic field to be close to the detected surface and establish magnetic mutual action with a workpiece to form a magnetic disturbance environment; the shape three-dimensional measurement system comprises a line laser, a light filter and a second CMOS industrial camera The device can perform real-time and comprehensive detection on the surface defect, the internal defect and the shape three-dimensional size in additive manufacturing, transmits data to an industrial personal computer for analysis, interacts with forming milling composite route planning software, and can control a shaping device in real time to perform formation and generate a milling code and control a milling cutter to perform milling on the additive manufacturing surface

Abstract: This article is intended to present an evaluation on the automation capability in the analysis of insulators of conventional grid by processing the signals generated by ultrasound detectors. The insulators analyzed were removed from the electrical system in various conditions, as well as new insulators. The methodology adopted was a practical analysis of qualitative and quantitative way. The audible noise generated by the output of ultrasound equipment is connected to a personal computer to obtain the FFT signal through LabVIEW software. The characteristic of the FFT signal is used to classify inspected components online, allowing for quick and precise procedure, as shown in the results obtained in this study.

Abstract: Urban flooding has become more serious and worldwide in recent years, especially in the big cities of developing countries. This study uses a multi-criteria analysis (MCA) approach to evaluate the applicability of sustainable urban drainage systems (SUDS), a flood control measure, in the central part of Ho Chi Minh City, Vietnam. The output of the personal computer storm water management model along with interviews with 140 households was used to assess the efficacy and acceptability of four SUDS alternatives: rainwater harvesting, green roof, urban green space and pervious pavement. On technical performance, green roof was the best alternative, followed by pervious pavement, urban green space and rainwater harvesting. Results of the social survey, however, diverged largely from the results of the technical assessments. In particular, people generally prefer public SUDS such as urban green space and pervious pavements to household solutions. With respect to the MCA, we applied four different procedures: Borda count, pair-wise voting, range of value and analytic hierarchy process. Despite some differences, the integrated results from MCA largely agree that urban green space is the most favourable type of SUDS, followed by green roof, pervious pavement and rainwater harvesting.

Abstract: In internet of things (IT) environment, a sensor interface device is essential for data collection in wireless sensor network (WSN) system for water quality monitoring (WQM) as the water pollution is a critical issue globally. This paper presents the design of a WSN based reconfigurable smart sensor interface device for WQM system in an IoT environment. The system consists of Field Programmable Gate Array (FPGA) design board, sensors, ZigBee based wireless communication module and personal computer (PC). The FPGA board performs as the heart of the proposed WQM system and it is programmed in very high speed integrated circuit hardware description language (VHDL) and C++ using Qsys tool and Nios-II SBT for Eclipse in Quartus II software. The proposed system collects the data of water quality such as water pH, water level, turbidity, carbon dioxide (CO 2 ) on the surface of water and water temperature in parallel and in real-time basis with high speed from five different sensor nodes. The performance of the proposed reconfigurable WSN system is verified through computer simulation and laboratory experiments.

Abstract: Groove is one of the key structures of end mills. Some of them could be machined by standard grinding wheels (1A1 or 1V1 type), some others must design new wheel profiles. Based on the enveloping and analytic geometry theories, a novel algorithm was proposed to calculate the wheel profiles for special groove machining. The machining process was analyzed, the contact line principles were discussed, and the calculation procedure was detailed. In addition, the algorithm was implemented on a personal computer by using the MATLAB programming language. Therefore, the desired wheel profile could be computed automatically with four input parameters, namely, the groove lead, the wheel axial vector, the point coordinates on the wheel axis, and the discrete points on the groove profile (or groove profile expression). The proposed algorithm and the corresponding program were finally verified by three different examples. The results demonstrated good agreements with the practical wheel profiles.