Showing papers on "Personal computer published in 2017"

Serious Games for Mental Health: Are They Accessible, Feasible, and Effective? A Systematic Review and Meta-analysis

Abstract: The development and use of serious games for mental health disorders are on the rise. Yet, little is known about the impact of these games on clinical mental health symptoms. We conducted a systematic review and meta-analysis of randomized controlled trials that evaluated the effectiveness of serious games on symptoms of mental disorder. Method: We conducted a systematic search in the Pubmed, PsycINFO and Embase databases, using mental health and serious games related keywords. Ten studies met the inclusion criteria and were included in the review, nine were included in the meta-analysis. Results: All of the serious games were provided via personal computer, mostly on CD-ROM without the need for an internet connection. The studies targeted age groups ranging from 7 to 80 years old. The serious games focussed on symptoms of depression (n = 2), post-traumatic stress disorder (n = 2), autism spectrum disorder (n = 2), attention deficit hyperactivity disorder (n = 1), cognitive functioning (n = 2) and alcohol use disorder (n = 1). The studies used goal-oriented (n = 4) and cognitive training games (n = 6). A total of 674 participants were included in the meta-analysis (380 in experimental and 294 in control groups). A meta-analysis of nine studies comprising ten comparisons, using a random effects model, showed a moderate effect on improvement of symptoms (g = 0.55 [95% CI 0.28 to 0.83]; P < 0.001), favoring serious games over no intervention controls. Discussion/Conclusion: Though the number of studies in the meta-analysis was small, these findings suggest that serious gaming interventions may be effective for reducing disorder related symptoms. More studies are needed in order to attain deeper knowledge of the efficacy for specific mental disorders and the longer term effects of this new type of treatment for mental disorders.

Data Exfiltration From Internet of Things Devices: iOS Devices as Case Studies

Abstract: Increasingly, big data (including sensitive and commercial-in-confidence data) is being accessible and stored on a range of Internet of Things (IoT) devices, such as our mobile devices. Therefore, any vulnerability in IoT devices, operating system or software can be exploited by cybercriminals seeking to exfiltrate our data. In this paper, we use iOS devices as case studies and highlight the potential for pairing mode in iOS devices (which allows the establishment of a trusted relationship between an iOS device and a personal computer) to be exploited for covert data exfiltration. In our three case studies, we demonstrate how an attacker could exfiltrate data from a paired iOS device by abusing a library and a command line tool distributed with iTunes. With the aim of avoiding similar attacks in the future, we present two recommendations.

Design of a Fatigue Detection System for High-Speed Trains Based on Driver Vigilance Using a Wireless Wearable EEG

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.

Hardware implementation of pseudo-random number generators based on chaotic maps

Abstract: We show the usefulness of bifurcation diagrams to implement a pseudo-random number generator (PRNG) based on chaotic maps. We provide details on the selection of the best parameter values to obtain high entropy and positive Lyapunov exponent from the bifurcation diagram of four chaotic maps, namely: Bernoulli shift map, tent, zigzag, and Borujeni maps. The binary sequences obtained from these maps are analyzed to implement a PRNG both in software and in hardware. The software implementation is realized using 32 and 64 bits microprocessor architectures, and with floating point and fixed point computer arithmetic. The hardware implementation is done by using a field-programmable gate array (FPGA) architecture. We developed a serial communication interface between the PRNG on the FPGA and a personal computer to obtain the generated sequences. We validate the randomness of the generated binary sequences with the NIST test suite 800-22-a both in floating point and fixed point arithmetic. At the end, we show that those chaotic maps are suitable to implement a PRNG but according to the hardware resources, the one based on the Bernoulli shift map is better. In addition, another advantage is that the required initial value for the sequences can be within the whole interval $$[-1,1]$$ , including its bounds.

PLACNETw: a web-based tool for plasmid reconstruction from bacterial genomes.

Abstract: Summary PLACNET is a graph-based tool for reconstruction of plasmids from next generation sequence pair-end datasets. PLACNET graphs contain two types of nodes (assembled contigs and reference genomes) and two types of edges (scaffold links and homology to references). Manual pruning of the graphs is a necessary requirement in PLACNET, but this is difficult for users without solid bioinformatic background. PLACNETw, a webtool based on PLACNET, provides an interactive graphic interface, automates BLAST searches, and extracts the relevant information for decision making. It allows a user with domain expertise to visualize the scaffold graphs and related information of contigs as well as reference sequences, so that the pruning operations can be done interactively from a personal computer without the need for additional tools. After successful pruning, each plasmid becomes a separate connected component subgraph. The resulting data are automatically downloaded by the user. Availability and implementation PLACNETw is freely available at https://castillo.dicom.unican.es/upload/. Contact delacruz@unican.es. Supplementary information A tutorial video and several solved examples are available at https://castillo.dicom.unican.es/placnetw_video/ and https://castillo.dicom.unican.es/examples/.

A Convex Primal Formulation for Convex Hull Pricing

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.

Mobile Health in Oncology: A Patient Survey About App-Assisted Cancer Care.

Abstract: Background: In the last decade, the health care sector has been enriched by numerous innovations such as apps and connected devices that assist users in weight reduction and diabetes management. However, only a few native apps in the oncological context exist, which support patients during treatment and aftercare. Objective: The objective of this study was to analyze patients’ acceptance regarding app use and to investigate the functions of an oncological app that are most required, and the primary reasons for patients to refuse app-assisted cancer care. Methods: We designed and conducted a survey with 23 questions, inquiring patients about their technical knowledge and equipment, as well as the possible advantages and disadvantages, data transfer, and general functionality of an app. Results: A total of 375 patients participated; the participation rate was 60.7% (375/618). Gender distribution was about 3:4 (female:male) with a median age of 59 years (range 18-92 years). Whereas 69.6% (261/375) of patients used mobile devices, 16.3% (61/375) did not own one, and 9.1% (34/375) only used a personal computer (PC). About half of the patients rated their usability skills as very good and good (18.9% 71/375; 35.2% 132/375), 23.5% (88/375) described their skills as intermediate, and 14.4% (54/375) as bad. Of all patients, 182 (48.5%, 182/375) were willing to send data to their treating clinic via an app, that is, to a server (61.0% 111/182) or as email (33.5%, 61/182). About two-thirds (68.7%, 125/182) believed that additional and regularly sent data would be an ideal complement to the standard follow-up procedure. Additionally, 86.8% (158/182) wished to be contacted by a physician when entered data showed irregularities. Because of lack of skills (34.4%, 56/163), concerns about the use of data (35.0%, 57/163), lack of capable devices (25.8%, 42/163), and the wish for personal contact with the treating physician (47.2%, 77/163), a total of 163 (43.5%, 163/375) patients refused to use an app. Pearson correlation showed a significant but mild relationship between age and app use (P=.03, r=−.12), favoring younger age; male gender correlated as well (P=.04; r=−.11). Conclusions: The results show that the introduction of mobile apps needs to follow different strategies depending on the patients’ attitude. Age and gender seem to be the strongest predictive factors. For oncology patients, our survey showed that about half of the patients were willing to send data via an app supporting their treatment. In the future, clinical data such as quality of life and treatment satisfaction recorded by mobile health (mHealth) devices could be used to evaluate and improve therapy workflow. Furthermore, apps could support classical visits, document adverse effects, and remind patients of treatment dates or drug intake. [JMIR Mhealth Uhealth 2017;5(6):e81]

History of EPI Suite™ and future perspectives on chemical property estimation in US Toxic Substances Control Act new chemical risk assessments

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.

Digital health system for personalised COPD long-term management

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.

Prototype design of smart home system using internet of things

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.

Sma3s: a universal tool for easy functional annotation of proteomes and transcriptomes

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

2011: Satellite CCRMA: A Musical Interaction and Sound Synthesis Platform

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.

IoT based home automation and surveillance system

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.

Plasma electrolytic oxidation coatings on AZ31 magnesium alloys with Si3N4 nanoparticle additives

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.

A real-time conflict solution algorithm for the train rescheduling problem

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.

Development of a fast fluid dynamics-based adjoint method for the inverse design of indoor environments

Abstract: The computational fluid dynamics (CFD)-based adjoint method may be appropriate for the inverse design of indoor environments, considering both accuracy and efficiency, but a single design still requires tens of hours with the use of a personal computer. To speed up the inverse design process, this study evaluated four fast fluid dynamics (FFD) models in terms of solving the Navier–Stokes equations, integration with turbulence models, and solving the adjoint equations. This study implemented the FFD solvers in OpenFOAM and validated them for predicting steady-state and transient indoor airflow. This study then validated the FFD solvers for solving the adjoint equations and the FFD-based adjoint method for inverse identification problems and inverse designs in indoor environments. The results showed that FFD was 20 times faster than CFD in predicting transient indoor airflow, and similar computational accuracy could be maintained; the FFD-based adjoint method was 4–16 times faster than the CFD-based adjoint...

Reconfigurable smart water quality monitoring system in IoT environment

Abstract: Since the effective and efficient system of water quality monitoring (WQM) are critical implementation for the issue of polluted water globally, with increasing in the development of Wireless Sensor Network (WSN) technology in the Internet of Things (IoT) environment, real time water quality monitoring is remotely monitored by means of real-time data acquisition, transmission and processing. This paper presents a reconfigurable smart sensor interface device for water quality monitoring system in an IoT environment. The smart WQM system consists of Field Programmable Gate Array (FPGA) design board, sensors, Zigbee based wireless communication module and personal computer (PC). The FPGA board is the core component of the proposed system and it is programmed in very high speed integrated circuit hardware description language (VHDL) and C programming language using Quartus II software and Qsys tool. The proposed WQM system collects the five parameters of water data such as water pH, water level, turbidity, carbon dioxide (CO2) on the surface of water and water temperature in parallel and in real time basis with high speed from multiple different sensor nodes.

Additive manufacturing surface defect, internal defect and shape composite detection method and device

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

Building the Evidence Base for Remote Data Collection in Low- and Middle-Income Countries: Comparing Reliability and Accuracy Across Survey Modalities

Abstract: Background: Given the growing interest in mobile data collection due to the proliferation of mobile phone ownership and network coverage in low- and middle-income countries (LMICs), we synthesized the evidence comparing estimates of health outcomes from multiple modes of data collection. In particular, we reviewed studies that compared a mode of remote data collection with at least one other mode of data collection to identify mode effects and areas for further research. Objective: The study systematically reviewed and summarized the findings from articles and reports that compare a mode of remote data collection to at least one other mode. The aim of this synthesis was to assess the reliability and accuracy of results. Methods: Seven online databases were systematically searched for primary and grey literature pertaining to remote data collection in LMICs. Remote data collection included interactive voice response (IVR), computer-assisted telephone interviews (CATI), short message service (SMS), self-administered questionnaires (SAQ), and Web surveys. Two authors of this study reviewed the abstracts to identify articles which met the primary inclusion criteria. These criteria required that the survey collected the data from the respondent via mobile phone or landline. Articles that met the primary screening criteria were read in full and were screened using secondary inclusion criteria. The four secondary inclusion criteria were that two or more modes of data collection were compared, at least one mode of data collection in the study was a mobile phone survey, the study had to be conducted in a LMIC, and finally, the study should include a health component. Results: Of the 11,568 articles screened, 10 articles were included in this study. Seven distinct modes of remote data collection were identified: CATI, SMS (singular sitting and modular design), IVR, SAQ, and Web surveys (mobile phone and personal computer). CATI was the most frequent remote mode (n=5 articles). Of the three in-person modes (face-to-face [FTF], in-person SAQ, and in-person IVR), FTF was the most common (n=11) mode. The 10 articles made 25 mode comparisons, of which 12 comparisons were from a single article. Six of the 10 articles included sensitive questions. Conclusions: This literature review summarizes the existing research about remote data collection in LMICs. Due to both heterogeneity of outcomes and the limited number of comparisons, this literature review is best positioned to present the current evidence and knowledge gaps rather than attempt to draw conclusions. In order to advance the field of remote data collection, studies that employ standardized sampling methodologies and study designs are necessary to evaluate the potential for differences by survey modality. [J Med Internet Res 2017;19(5):e140]

Newspaper Consumption in the Mobile Age: Re-assessing multi-platform performance and market share using “time-spent”

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...

Shaping electromagnetic waves using software-automatically-designed metasurfaces

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.

Leaf-GP: an open and automated software application for measuring growth phenotypes for arabidopsis and wheat

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 .

Determination of Rice Storage Time with Colorimetric Sensor Array

Abstract: Aroma of rice greatly affects palatability as well as consumer acceptability and is one of the main factors of rice quality. In this work, gas chromatography mass spectrometry (GC-MS) was used to investigate the volatile organic compounds (VOC) of rice samples with different storage time. It was found that the compounds of benzaldehyde, 2-fluoro-5-methylaniline increased remarkably during storage, while hexanal, octaethylene glycol and monododecyl ether continuously decreased. And then, colorimetric sensor array composed of 12 sensitive dyes were used for rice sample discrimination. A CCD camera was employed to capture the images of colorimetric sensor array, and the difference map of sensor array before and after exposure VOC was obtained. The red (R), green (G), and blue (B) components images were extracted from the difference map. Moreover, the images were further processed and turned into digital data for subsequent analysis. Recently harvested rice and that stored for 6 and 12 months samples were distinguished with three dimensional spaces personal computer assistant cluster trend. Linear discriminant analysis (LDA) model based on PCA scores was used to discriminate the storage time of rice samples, and the result indicates 85 % of samples were correctly identified.

Use of facial emotion recognition in e-learning systems

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.