Miracle-dz/UniFAR-FTUs huggingface dataset:
The impact of human motion on TVOCs distribution for three ventilation modes

The study objectives of this paper are to investigate the influence of human motion and three different ventilation modes on indoor environment, Total Volatile Organic Compounds (TVOCs) dose and Contribution Ratio of Pollution (CRP) source index. According to the simulation results, human motion acts as the disturbance, has a noticeable effect on indoor environment including velocity, temperature and concentration spatial distribution fluctuation over a short period of time. The highest dose is obtained by simulating the side ventilation mode, the displacement ventilation leads to the lowest dose on the same boundary condition.
Graph-domain features and their application in rotating machinery fault diagnosis

To more effectively extract the non-stationary and non-linear fault features of mechanical vibration signals, a novel fault diagnosis method for rotating machinery is proposed combining time-domain, frequency-domain with graph-domain features. Different from the conventional time-domain and frequency-domain features, the graph-domain features generated from horizontal visibility graphs can extract the fault information hidden in the graph topology. Aiming at the problem that too many features will lead to information redundancy, the Fisher score algorithm is applied to select several of sensitive features which are then fed into the support vector machine to diagnose the faults of rotating machinery. Experimental results indicate features extracted from the three domains can be used to obtain higher diagnosis accuracy than that extracted from any single domain or dual domains.
Relocation of Dredged Material from Marano and Grado Lagoon: An Example of Sustainable Management

The high degree of dynamism of coastal and lagoon morphodynamic processes often implies the need for dredging operations to maintain the navigability of the main waterways towards harbours or sites which have important tourist or economical value. In particular, within sheltered and shallow lagoons this phenomenon is continuous and involves large volumes of material that requires to be properly managed. The dredged materials can provide sediments for environmental enhancement and they can be used, as an example, to create or improve habitats, mudflats and salt marshes. Numerical model can be a valuable tool to investigate the morphological evolution of the disposals, especially in the medium term, with the aim of verifying the sediment stability and the bed level changes. The present paper shows an example of sustainable management of cohesive materials dredged from two channels of the Marano and Grado lagoon. The non-linear interactions between tidal currents and locally generated wind waves are reproduced by means of a coupled spectral-hydrodynamic model associated with a transport equation to compute sediment load concentration. The comparison of the results confirms the validity of the adopted procedure.
Curing building related illnesses by using an emissions barrier

A new type of emissions barrier was used in premises with indoor air complaints due to emissions from the buildings in question. The emissions comprised chlorophenols/chloroanisoles and polycyclic aromatic hydrocarbons (PAH) from treated wood, and volatile organic compounds (VOC), mainly 2-ethylhexanol, from PVC flooring and the glue used to paste the flooring onto a concrete slab. Attaching the barrier at the surfaces from where the emissions were spread (floor, walls, ceiling) resulted in a fresh and odour-free indoor air. We conclude that using an emissions barrier in buildings made unhealthy by moisture is an efficient way of restoring a pleasant and healthy indoor air.
Real-time vehicle detection and computer intelligent recognition through improved YOLOv4

Vehicle detection is one of the key techniques of intelligent transportation system with high requirements for real-time and accuracy. To better balance the requirements, a vehicle detection algorithm based on the You Only Look Once (YOLO) v4 is proposed in this paper. On the one hand, the improved depthwise separable convolution is adopted to ensure the real-time performance. On the other hand, a novel feature fusion network is designed to gather more original feature information of different depth network layer. Experimental results show that the proposed algorithm can reduce the detection time by half while ensuring the accuracy, compared with the pristine YOLOv4.
IMPROVED DESCRIPTIVE ANSWER ASSESSMENT SYSTEM WITH MACHINE LEARNING: A REVIEW

: Online subjective tests are very rarely proposed . all the online subjective exams set for the students are pen and paper-based evaluated by the teachers manually. This paper presents a survey on the effective way of online subjective tests. In this, the answers are unstructured data that have to be evaluated. The evaluation is based on the semantic similarity between the faculty’s answers and student’s answers. Different techniques i.e. TF-IDF, keyword extraction are compared and new technique like LSA, SOM are used to proposed evaluate subjective test assessment of text
Dynamic wavelength tuning of channel-drop device in two-dimensional photonic crystal slab

Dynamic and external tuning of the operating wavelength of a channel add/drop device based on a two-dimensional photonic crystal slab is demonstrated. Thermo-optical effect, where the temperature increase is induced by the absorption of external light, is utilised for the tuning. The tuning speed is shown to be as fast as 20 µs.
Using Machine Learning Techniques to Reduce Data Annotation Time

Manually annotating large databases in any domain is costly and time-consuming. We present a semi-automatic annotation tool for this purpose that uses Random Forests as bootstrapped classifiers. We describe an application of this tool on a large database of simulated driving data. The tool enables the user to verify automatically generated annotations, rather than annotating from scratch. This tool reduced the amount of time required to annotate one minute of video by a factor of six, down to approximately thirty-five seconds of annotation time per minute of video for a database of simulated driving data. The tool is limited in that its effectiveness is dependent upon the types of data collected, and the statistical boundaries between the different annotations.
Impact of hot injected beam on whistler mode with alternating electric field (AC) in the magnetosphere of Saturn

Whistlers are believed to be generated by its own and responsible to evolve dynamical properties of magnetized planetary environment. Growing whistler instability can cause other uncertainties in the magnetosphere and evident to be generated by mean of injection events and temperature variance in plasma environment. In this paper the empirical dispersion relation has developed for parallel propagating whistler mode instability in an infinite saturnian magneto plasma in the presence of perpendicular electric field for ring distribution function having non-monotonous nature. Method of characteristics solutions alongside kinetic approach found to be most suitable in order to achieve perturbed plasma states. The perturbed and unperturbed particle trajectories have taken into consideration to determine perturbed distribution function. A remarkable growth rate expression with added hot plasma injection has been calculated in inner magnetosphere near 6.18 Rs. The results obtained using demonstrative value of the parameters suited to the Saturnian magnetosphere have been computed and discussed. Pressure (Temperature) anisotropy is found to be a peculiar source of free energy for whistler mode instability. The AC frequency irrespective of its magnitude, affects the growth rate significantly. The bulk of energetic hot electrons injection influences the growth rate by increasing its peak value. The result obtained provide the important view of wave particle interaction and useful to analyze the VLF emissions observed over a wide frequency range.
Pedestrian Re-identity Based on ResNet Lightweight Network

With the development of deep learning technology, pedestrian re-identity technology has been widely used in multi-target tracking and cross mirror tracking tasks. In this paper, the classical deep learning ResNet18 network is used for pedestrian re-identity tasks. The advantage of the network is that it can easily realize lightweight deployment. In addition, the labeled smooth cross entropy loss function and migration learning technology are used in the process of training the network, which can realize the accuracy of map 67.8 on the Market1501 data set while lightening the network, and promote the engineering landing of pedestrian re-identity network.
Application of Recommendation Algorithm and Big Data Technology in Computer English Corpus Database

Corpus linguistics is one of the branches of modern linguistics. It is also a cutting-edge research problem of modern linguistics spawned by the background of the information technology era. Corpus linguistics can reset the teaching role of English majors. College English vocabulary teaching makes use of the corpus’s abundant real language materials and the computer’s ability to analyze and process large-scale corpus, guide students to explore the usage of vocabulary in the context, and use the corpus to deepen students’ autonomous learning. This article will start with the development of corpus linguistics, explain the necessity of combining corpus and English language teaching, and propose a corpus linguistics-based English language learning platform system in colleges and universities, and combine with semantic recommendation algorithms to verify that the system is in English learning.
Empowering energy flexibility and climate resilience using collective intelligence based demand side management (CI-DSM)

This work investigates the effectiveness of Collective intelligence (CI) in demand side management (DSM) in urban areas to cope with extreme climate events. CI is a form of distributed intelligence that emerges in collaborative problem solving and decision making. It is used in a simulation platform to control the energy performance of buildings in an urban area in Stockholm, through developing CI-DSM and setting certain adaptation measures, including phase shifting in HVAC systems and building appliances. CI-DSM is developed based on a simple communication strategy among buildings, using forward (1) and backward (0) signals, corresponding to applying and disapplying the adaptation measures. The performance of CI-DSM is simulated for three climate scenarios representing typical, extreme cold and extreme warm years in Stockholm. According to the results, CI-DSM increases the autonomy and agility of the system in responding to climate shocks without the need for computationally extensive central decision making systems. CI-DSM helps to gradually and effectively decrease the energy demand and absorb the shock during extreme climate events.
Endpoint detection and response using machine learning

The need for cybersecurity has increased manifold over the past decade due to an unprecedented shift towards digital. With the increase in the number and sophistication of threats, cybersecurity experts have been forced to seek out new and efficient ways to secure endpoints on a network. Machine learning provides one such solution. This paper discusses how IoT devices are threatened and the need for endpoint security. It overviews different Machine learning-based intrusion detection systems that are currently in use e.g., STAT, Haystack, etc., and other Endpoint Detection and Response Techniques.
Variation Characteristics Mathematical Calculation of O3 and Its Relationship with Meteorological Factors by Big Data Technology

Based on the data of environmental monitoring stations and meteorological stations in Qinhuangdao from May 2017 to May 2020, the variation characteristics of O3 and precursors (NO2 and CO) as well as their relationship with meteorological elements were analyzed. The results showed that the daily average concentration of O3-8 h in Qinhuangdao increased year by year. The monthly average concentration of O3-8 h was high in summer and low in winter, and the peak appeared in June. The diurnal variation of O3 concentration was unimodal structure, and the concentration increased in the afternoon, but it decreased at night. The concentration of NO2 and CO was inversely correlated with O3, and the peak value of NO2 in March could be related to frequent cold air activity and increased burning of loose coal. The meteorological elements favorable for the occurrence of ozone pollution weather in Chengde were total solar radiation irradiance greater than 1000W/m2, the daily maximum temperature greater than 33 °C, and the daily minimum relative humidity less than 40% and 65%∽80%, southerly wind or southwest wind.
Wind Energy Collection System Based on Phase Change System and Deformable Materials

The purpose of this paper is to design and discover a new system, which can realize the collection, transformation and storage of energy from wind energy in the environment ^ temperature/physical deformation → material phase change → energy storage, so as to achieve the effect of green energy saving. At the same time, it can provide theoretical support and design basis for the design of high-rise Garden residential suite in cold region. Wind energy is collected through the narrow channel effect. With the help of deformation induced ferrite phase transformation technology and memory alloy materials, the collected energy is stored in the new colloid/graphene battery equipment. With the help of the relevant content research parameters, a systematic digital model is formed, and the basic database is established to simulate the external environment of high-rise Garden residential buildings in cold areas. Through the design of a new wind energy collection system and embedded in the simulation environment, the wind energy utilization in cold, low sunshine, low wind speed or unstable wind speed areas is realized, and the green energy conservation, environmental protection and sustainable development in such areas are realized. Then, the feasibility and effectiveness of the system are demonstrated according to the experimental results, and a systematic theory is formed.
Application of STATCOM for damping torsional oscillations in series compensated AC systems

This paper presents the results of a study on the application of the recently developed FACTS device, the static compensator (STATCOM), for the damping of torsional oscillations that occur in a series compensated AC system. The IEEE first benchmark system is considered for this study. In order to suppress unstable torsional mode oscillations, a STATCOM with a PI controller to regulate the bus voltage, and with an auxiliary signal derived from the generator speed deviations is employed at the generator terminal. The eigenvalue analysis technique is used for small signal analysis and optimization of the control system parameters is done through step response studies. In addition, dynamic performance of the nonlinear system with optimized STATCOM controller is evaluated under a three-phase fault. Results from the analytical and digital simulation studies reveal the technical feasibility of using STATCOM for damping of turbine-generator torsional oscillations in series compensated AC systems.
Proposal of an Innovative Electric Power Distribution System based on Packet Power Transactions

Recently, the introduction of decentralized generators, such as photovoltaic power generations, has been promoted rapidly. In the future, extensive use of PV is thought to give rise to the daytime surplus electricity, and a household will manage the surplus electricity rationally. The purpose of this research is to propose an innovative electric power distribution system based on packet power transactions. First, this paper explains distributed markets of which the price can easily reflect the geographical diversity of renewable energy availability and load curve characteristic within the local area. Second, this paper exemplifies the specific electronic circuit that makes pulse-shaped power transmission to develop the packet power distribution system. Finally, this paper shows the results of multi-agent simulations of electricity trading to evaluate the usefulness of the proposed system.
Search for requirements for the width of pedestrian roads in the context of the classification of public space

Walking has long been the primary means of human transport. Nevertheless, in recent decades, the insufficient emphasis has been placed on it in the creation and renewal of public space. It focuses mainly on the needs of road transport, the volume of which is constantly growing enormously. It is only in recent years that the view begins to be re-evaluated and trends in the organization of public space gradually changed, as it is true that a larger supply generates a greater demand. Therefore, leading architects are gradually changing their approaches to the organization of public space and put humans, pedestrian transport, and its requirements first. In the Czech Republic, the trend is gradually changing, as it is worldwide. Walking again plays an important role in the creation of sustainable mobility plans for the cities of the Czech Republic. The main problems arise in the actual implementation of these ideas, as the legislative requirements are formulated only in general, unlike the requirements for road transport, which sets out the requirements for minimum road profiles in the context of design speed and traffic intensity in a given cross-section. These requirements are set out in Decree No. 501/2006 Coll. on general requirements for land use and also in CSN 73 6110 Design of local roads (CSN is Czech technical norm). However, such a categorization of requirements for pedestrian roads is not yet solved uniformly for the entire territory of the Czech Republic, even though CSN 73 6110 deals with sidewalks (functional group D roads). ). So far, this categorization is replaced only by seldom locally valid methodologies, manuals, or requirements and regulations in the town plans of individual cities. This paper aims to search for current approaches, legislative requirements, and approaches to addressing the width requirements for pedestrian roads in public space in the context of the classification of this area.
Self-learning PID Control for X-Y NC Position Table with Uncertainty Base on Neural Network

An adaptive radical basis function (RBF) neural network PID control scheme for X-Y position table is proposed by the paper. Firstly, X-Y position table model is established, controller based on neutral network is used to learn adaptive and compensate uncertainty model of X-Y position table, neutral network is used to study model. PID neural network controller base on augmented variable method is designed. PID controller is used as assistant direction error controller, neural network parameters base on stochastic gradient algorithm can be adjust adaptive on line. The simulation results show that the presented controller has important engineering value.
Abnormalities Detection of IMU Based on PCA in Motion Monitoring

Inertial measurement units (IMU) are used as an affordable and effective remote measurement method for health monitoring in body sensor networks (BSNs) based on tracking people’s daily motions and activities. These inertial sensors are mostly micro-electro-mechanical systems with a combination of multi-axis combinations of precision gyroscopes, accelerometers, and magnetometers to sense multiple degrees of freedom (DoF). Unfortunately in the process of motion monitoring actual sensor outputs may contain some abnormalities, which might result in the misinterpretations of activities. In this paper, we use Principal component analysis (PCA) combined with Hotelling’s T2 and SPE statistic to detect abnormal data in the process of motion monitoring with IMU to ensure the reliability and accuracy in application. The simulated results prove this method is effective and feasible.
Up/Down in (Im)possible Flight Attitude Indicators - Some Effects of Colour, Shape and Pattern -

Based upon general complaints from pilots, as well as suspicions that misinterpretations of the flight attitude indicator(FAI) had contributed to some crashes, some research was initiated. The first studies concerned minor revisions of the layout of the current electromechanical spherical FAI. The results indicated that many pilots wanted some improvements of the FAI and that the present colour combination (black and white) could not be considered optimal for the Swedish pilot population. The studies were continued with more hypothetical constructs, aiming at finding possible coding principles for future computer-generated flight attitude information. The basic idea was to try to find some visual coding dimension(s) that would trigger spontaneous interpretations of the spatial up/down dimension. In a series of experiments a number of combinations of colours, shapes and patterns were tested on both volontary civilian subjects and military pilots. It was found that most of the tested people expressed very strong spatial associations to some of the combinations, but also that the agreement between individuals sometimes was practically negligible. Colour and shape tended to elicit the strongest responses, with the tested patterns acting more as minor moderators. Unfortunately, however, the large individual differences do not indicate that the design of a single “optimal” combination would be easy.
Building APMv3 Map Visualization Using Nagios Host Data

Nowadays, having a network monitoring is becoming an important thing for a growing or big company which should also have a network infrastructure inside it. Network monitoring is the use of a system that constantly monitors a computer network for slow or failing components and that notifies the network administrator in case of outages. Acknowledge Proactive Monitoring (APM), one of the sub-departments in Acknowledge, focuses on developing a network monitoring system using Nagios tool. However, one of its main feature called Map Visualization is not really efficient in terms of its map management. The current stable version of the system is called APMv2 and the team is developing a new version called APMv3 which needs a better Map Visualization. The application made in this project was a proof of concept that will later be used on APMv3. It is a web-based application which has a separate frontend written in HTML and JavaScript, a separate RESTful backend written in PHP, and uses some frameworks such as jQuery UI, jCanvas, Twitter Typeahead, and Bootstrap 3. All necessary data within this application are exchanged asynchronously using AJAX. NOTE: The paper had been withdrawn and the revised version published in JIRAE .
Quad Tilt Rotor Download And Power Measurements In Ground Eect

This paper explores the performance characteristics of a Quad Tilt Rotor (QTR) in hover and low speed forward flight, in ground eect (IGE) and out of ground eect (OGE), by employing a somewhat unique experimental testing method, i.e., using an instrumented moving test apparatus. Airframe download and rotor performance data were acquired by testing a 0.031-scale QTR aircraft model in hover and low speed forward flight, in and out of ground eect. Rotor downwash velocity profiles were measured and compared with full-scale V-22 rotor measurements. The range of rotor wake skew angles (non-dimensionalized forward speeds) being tested, was extended by reducing the thrust level of the vehicle, which increases the rotor wake skew angle for a given forward velocity. The upload on the vehicle, observed at low heights above the ground, did not disappear with an increase in forward speed. The small-scale fixed-pitch variable-rpm rotor power measurements were corrected using an analytical procedure to obtain the equivalent power of a variable-pitch fixed-rpm rotor and to remove the profile power contributions.