Miracle-dz/UniFAR-FTUs huggingface dataset:
Challenges and Opportunities of Predicting Musical Emotions with Perceptual and Automatized Features

Music information retrieval (MIR) is a fast-growing research area. One of its aims is to extract musical characteristics from audio. In this study, we assumed the roles of researchers without further technical MIR experience and set out to test in an exploratory way its opportunities and challenges in the specific context of musical emotion perception. Twenty sound engineers rated 60 musical excerpts from a broad range of styles with respect to 22 spectral, musical, and cross-modal features (perceptual features) and perceived emotional expression. In addition, we extracted 86 features (acoustic features) of the excerpts with the MIRtoolbox (Lartillot & Toiviainen, 2007). First, we evaluated the perceptual and extracted acoustic features. Both perceptual and acoustic features posed statistical challenges (e.g., perceptual features were often bimodally distributed, and acoustic features highly correlated). Second, we tested the suitability of the acoustic features for modeling perceived emotional content. Four nearly disjunctive feature sets provided similar results, implying a certain arbitrariness of feature selection. We compared the predictive power of perceptual and acoustic features using linear mixed effects models, but the results were inconclusive. We discuss critical points and make suggestions to further evaluate MIR tools for modeling music perception and processing.
Research on Testability of Marine Diesel Engine Based on Multi-Signal Model

Considering the equipment testability from top-design,whole-system and life-cycle is an effective way to avoid serious accident and reduce life cycle cost.Based on analyzing the testability characteristic and status quo of warship diesel engines,a multi-signal model is introduced to the testability modeling of the lubrication system.And we propose improvements design to detect and isolate faults comprehensively.The study can provide scientific and reasonable guidance for making testing project.
Increasing Smoke Classifier Accuracy using Naïve Bayes Method on Internet of Things

This paper proposes fire alarm system by implementing Naïve Bayes Method for increasing smoke classifier accuracy on Internet of Things (IoT) environment. Fire disasters in the building of houses are a serious threat to the occupants of the house that have a hazard to the safety factor as well as causing material and non-material damages. In an effort to prevent the occurrence of fire disaster, fire alarm system that can serve as an early warning system are required. In this paper, fire alarm system that implementing Naïve Bayes classification has been impelemented. Naïve Bayes classification method is chosen because it has the modeling and good accuracy results in data training set. The system works by using sensor data that is processed and analyzed by applying Naïve Bayes classification to generate prediction value of fire threat level along with smoke source. The smoke source was divided into five types of smoke intended for the classification process. Some experiments have been done for concept proving. The results show the use of Naïve Bayes classification method on classification process has an accuracy rate range of 88% to 91%. This result could be acceptable for classification accuracy.
Efficient Multiphysics Design Workflow of Synchronous Reluctance Motors

This paper proposes a new design strategy for Synchronous Reluctance machines, with cooperative design in the two environments SyR-e and Motor-CAD. The paper proposes to use the open-source SyR-e for initial, equation based design of the machine. Then, the design is validated and refined in Motor-CAD, in multiple physical domains. This synergy complements both design environments and turns into a comprehensive design package, not yet available in the literature, assembling accessible design equations, magnetic and mechanical FEA and drive operating profiles evaluation to the trademark thermal analysis of Motor-CAD. The cooperative design strategy is described in the paper with reference to the case of a Pure Synchronous Reluctance motor prototype for vehicular traction.
Structural Optimization and Measurement of Chinese Employeesr Perception of Being Trusted

In order to develop an employee perception of being trusted scale based on our cultural background ,in-depth interviews with seven state-owned enterprises and six privatelyowned enterprise personnel; using the grounded theory to construct a structural model of employees’ perception of being trusted; exploratory factor analysis and confirmatory factor analysis were used to develop the scale; which ultimately established the three dimensions of competence recognition, establishment of intimate relationships, and leadership support. The theoretical structural model was verified and developed the scale that have typical Chinese cultural characteristics, which provides a research tool for continuing to explore the perception of being trusted of employees in China. Keywords—Perception of being trusted; Grounded theory; Structural model; Scale development
Air conditioner component optimum operation point search through a deep reinforcement learning algorithm

A deep reinforcement machine learning algorithm is applied to an energy-efficient optimal operation point search of an inverter air conditioner. The combination of the two factors of compressor output (COM) and electronic expansion valve (EEV) opening, which have a major influence on the efficiency (EER) of an air conditioner, is analyzed with the algorithm over 5 days. It displays a repetitive stabilization pattern 12 hours after the commencement of the deep learning algorithm, and finds the optimal (COM, EEV) combination with the maximum EER. An arbitrary case (600, 400) that satisfies the target cooling capacity (9200 W) is started with an initial value to reach (420, 230) with the optimal EER at a given condition (given product specification, standard test condition (T1 condition)). In this study, since the optimal point of (COM, EEV) exists at the boundary of the action domain, it inevitably has a repeating learning pattern. The repetitive stabilization pattern is examined for two cases of the discount factor of 0.5 and 0.99. When the discount factor is 0.5, it shows a shortsighted behavior to the present reward value more clearly than when it is 0.99. This kind of experimental study can be extended to find the optimum operating point when several components of an air conditioner are operating simultaneously.
Bridging Location-based Data with Mobile Practices Introducing a Framework for Mobile User-Studies

Increasingly, mobile services are using locationbased information provided by GPS sensors. Especially HCI research deals with a growing interest in how people make sense of location-based information while on the move. Mobile user-studies can help to address this black box and provide the opportunity to combine location-based data with context related content of the mobile practices being performed. In this study, we address this relationship and ask how spatial information should be visualized in order to explore mobile contexts. We conducted a qualitative study to learn about the usage and interpretation forms of spatial information and further translated these findings into a basic framework for mobile user-studies, concluding with an evaluation. Keywords-mobile user-studies; location-based services; mobility; user studies; framework.
Towards an Interaction Blueprint for Mixed Reality Experiences in GLAM Spaces: The Augmented Telegrapher at Porthcurno Museum

Emerging mixed reality (MR) technologies, such as Microsoft HoloLens, present many exciting opportunities to the heritage sector. For example, the development of immersive experiences within gallery, library, archive, and museum (GLAM) spaces. Previous work on virtual and augmented reality (AR/VR) in such spaces is often limited to meta-layers of information beyond traditional modes. However, the affordances of MR potentially offer new ways to design content beyond AR/VR that can engage users as performers upon the stage of historically resonant and artistically charged places. This work-in-progress paper examines the case of the Augmented Telegrapher under development at Porthcurno Museum. A pilot study with 30 participants examined how to situate the Augmented Telegrapher into the context of a multi-player game, with particular attention given to which interaction style is more suitable: the use of sensors and gestures to manipulate virtual objects, or a tangible user interface grounded by relevant physical objects. Experimentation reveals a statistically significant difference in time taken to complete a data entry task (d = 1.32, p < .01) and data entry errors (d = 1.24, p < .01). This highlights several challenges in the manipulation of virtual objects, most notably the difficulty of manipulating virtual objects using unnatural maps of artificial gestures to intentions. This work-in-progress paper briefly outlines future directions in response to these challenges, paving the way towards an interaction design blueprint for mixed-reality experiences in GLAM spaces.
Fast multi-pole boundary element method analysis for power frequency electric field distribution of multi-medium

To raise the low computation efficiency existed in calculation of power frequency electric field(PFEF) of the key devices in substation,a hybrid technique combining the fast multi-pole method(FMM),the boundary element method(BEM) and charge simulation method(CSM) has been proposed to solve PFEF of multi-medium problem.The calculation model for PFEF of the key devices in substation is built according to the principle of BEM and CSM.The fast algorithm is presented for multi-medium PFEF problem based on the characteristic of FMM accelerating the product between the matrix and the vector.Take the switch in 500kV substation for example and the distribution of potential field is calculated.The result shows as follow: Comparing calculation results of FMM BEM and CSM with results simulated by Integrated Engineering Software(IES),the max relative error is only 8.1%. FMM,BEM and CSM is much faster and more efficient than the traditional BEM and CSM in the computational cost and the storage of the computer on the promise of engineering error.So this method can be used in large DOF and numerous unknown parameter potential field problems.
Application of Deep Learning in Liver Pathological Image Diagnosis

Hepatopathy is a kind of disease with high incidence, so the progress in the field of liver disease research is highly valued. Medical image, as an important part of medical diagnosis, provides an important basis for doctors to make correct diagnosis. Pathological images play a significant role in clinical application because they can facilitate doctors to clearly observe the degree of lesions and make accurate judgments. As an important component of computer vision, deep learning has been paid more and more attention by researchers. The application of computer aided technology in medical image detection has become an important application of computer vision. In view of this situation, an automatic diagnosis method of liver pathological images based on deep learning method is proposed. We analyze the image features, then design and train the classification model. The final results confirmed that this method can effectively classify the pathological images of liver and has a high accuracy rate.
Design of Capacitors in SST

This paper deals with the design of all “power” capacitors in two variants of a solid-state transformer (SST) described in this work. SSTs are nowadays at the center of attention mainly due to reducing the size and weight of traction transformers in railway vehicles and in power transfer, where it should be part of an energy router that could replace the distributional transformer. In the case of three-stage SST, there are three types of capacitors: in submodules of a modular multilevel converter (MMC), in the MV-DC link, and on outputs of the galvanic insulation modules (DAB). In the case of two-stage SST, there are two types of capacitors: one type is in the DC link, and another type is on the outputs of the galvanic insulation modules, similarly as in the previous case. If we choose the same voltage levels for the DAB, we will get different numbers of DAB needed for the two variants of SSTs with different capacitors and medium frequency transformers (MF Tr).
Fuze Adaptive Delay Time Control Based on Target Thickness Recognition Switch

The fuze of fixed time delay detonation of hard structure ammunition can not adapt to different thickness of the targets.To solve the problem,an self-adaptive delay time control method based on target thickness recognition switch was presented for hard structure ammunition fuze.Two signals of different thickness of the targets could be given by the target thickness recognition switch and the corresponding delay time was put out by delay control circuit.Simulation results showed that the designed device could distinguish the thickness of concrete targets at 200 mm less and 400 mm over,and adaptively control the time delay detonation point effectively.
Energy Consumption in Wireless Sensor Networks

Wireless sensor networks(WSNs) can be used to collect surrounding data by multi-hop.As sensor networks have the constrained and not rechargeable energy resource,energy efficiency is an important design issue for its topology.In this paper,the energy consumption issue under the different topology is studied.We derive the exact mathematical expression of energy consumption for the flat and clustering scheme,respectively.Then the energy consumptions of different schemes are compared.By the comparison,multi-level clustering scheme is more energy efficient in large scale networks.Simulation results demonstrate that our analysis is correct from the view of prolonging the large-scale network lifetime and achieving more power reductions.
Online human-like redundancy optimization for tele-operated anthropomorphic manipulators

Robot human-like behavior can enhance the performance of human–robot cooperation with prominently improved natural interaction. This also holds for redundant robots with an anthropomorphic kinematics. In this article, we translated human ability of managing redundancy to control a seven degrees of freedom anthropomorphic robot arm (LWR4+, KUKA, Germany) during tele-operated tasks. We implemented a nonlinear regression method—based on neural networks—between the human arm elbow swivel angle and the hand target pose to achieve an anthropomorphic arm posture during tele-operation tasks. The method was assessed in simulation and experiments were performed with virtual reality tracking tasks in a lab environment. The results showed that the robot achieves a human-like arm posture during tele-operation, and the subjects prefer to work with the biologically inspired robot. The proposed method can be applied in control of anthropomorphic robot manipulators for tele-operated collaborative tasks, such as in factories or in operating rooms.
Submodule Capacitance Voltage Balancing of Modular Multilevel Converter Based on Carrier Phase Shifted SPWM Technique

Modular multilevel converter(MMC) was a new multilevel converter suitable for VSC-HVDC.The working principle of the submodules of MMC and converter topology were introduced in this paper.Considering the new topology and its application in the field of high voltage direct current transmission system,a novel carried phase shifted sinusoidal pulse width modulation(CPS-SPWM) scheme suitable for MMC was presented.Compared with other modulation schemes,the scheme proposed had superior dynamic regulation and excellent harmonic characteristics at lower switching frequency.Voltage balancing among the submodules was a crucial problem of MMC.Based on the equipartition of energy and voltage balance,a voltage-balancing scheme of submodules was presented in this paper with the topology of MMC and modulation.This scheme can effectively ensure each submodule at the same capacitance and voltage level.The correctness and effectiveness of the proposed schemes are verified by the simulation.
Analysis of Power Decoupling Mechanism for Droop Control with Virtual Inductance in a Microgrid

Droop control is widely employed in inverter-based microgrids.The effectiveness of droop control can be significantly affected in cases of resistive line impedance because the active and reactive powers are intensively coupled.Two kinds of solutions have been proposed.One is by obtaining the inductive inverter output impedance in fundamental frequency by choosing proper control parameters.The other is by adjusting the reference voltage to inverter by subtracting a voltage drop that is synthesized by inverter output current and a virtual impedance.For the former method,the output impedance will be restricted by control parameters besides an innate shortcoming.For the later method,the feasibility and philosophy of virtual impedance is not provided,moreover,it will lead to voltage deviation.This paper investigates the defects of these two methods and proposes a droop control method by combining virtual generator and virtual inductance.Theoretical analysis and a specific scheme are provided.The effectiveness is confirmed by MATLAB simulation.
Balise System Used in High Speed or Speed-increase Line

Balise system is a very important basic system that has many advantages to be used by various kinds of lines to improve transportation efficiency and assure of safe operation. The paper describes the basic principles about the balise system, including the relationship between the size of balise and retrieved data frames of on board computer. There are several important concepts of the balise system, such as information frame format, data transmission rate and message cyclic redundancy checks. The paper introduces general methods using balise for the purpose of speed increase. At the end of the paper, we recommend some kinds of methods, which can be used in high speed or speed increase lines when the balise system is used with Cab signal and LSK train automatic control system. The methods are successfully tested on the Guangzhou Shenzhen line. The experiment proves that the LSK automatic train control system can increase or limit train speed safely and reliably after the software of LSK system is modified. The LSK system can come back to its original control mode when it passes the speed increase section. This is the first running test to automatically control train speed in combination with the intermittent signal or continuous signal on the Chinese railway. As for the fail safe function, there are two aspects in hardware and software to guarantee safety when failure occurs.
Study of machining square spindle theory and application

Based on the character that the pathways of some points on the planet are ellipses, machining square spindle is demonstrated and the error model of machining square spindle is deduced. At same time, the formula of deciding the key dimensions in designing the spindle's structure and present this spindle's structure picture are introduced. 
Index System Incubation Performance of Science and Technology Enterprise Incubator

The business incubator comes from the management model that provides environment,service for science and technology small enterprises to accelerates their growth.Incubation performance is a main evaluation criterion to choose incubator for venture investment enterprises.The paper constructs incubation performance evaluation system of science and technology business incubator,and establishes a method model to calculate weigh based on Analytical Hierarchy Process(AHP). The conclusion is that the AHP is applied well to the structure the incubation performance index system of science and technology enterprise Incubator index system based on an example.
Two Novel Methods for Wideband Source Localization in the Presence of Unknown Nonuniform Noise

In this paper, we derive the maximum-likelihood (ML) and coherent signal-subspace location estimator for wideband sources in the near field of the sensor array on the background of nonuniform white noise. By comparison of the two methods, the proposed algorithms can deal with source localization efficiently for randomly distributed sensors array. The estimation of noise covariance matrix is based on iterative procedure in ML. And a new focussing matrix is proposed in coherent signal-subspace method. Extensive simulations demonstrate that the algorithms have good performance.
Secrecy-Based Delay-Aware Computation Offloading via Mobile Edge Computing for Internet of Things

Mobile edge computing (MEC), which enables smart terminals to actively offload computation workloads to computational servers deployed at the edge of networks, has provided an efficient approach to address the intensive computation requirement in mobile Internet applications. In this paper, we investigate the delay-aware computation offloading via MEC for Internet of Things (IoT) with secrecy provisioning. Specifically, we consider a scenario where a malicious eavesdropper intentionally overhears the IoT devices’ offloaded computational data. Taking into account the secrecy outage due to the eavesdropper’s overhearing, we formulate a joint optimization of the secrecy-provisioning, computation offloading, and radio resource allocation (including time and power allocations), with the objective of minimizing the overall delay in finishing the computation requirement of the IoT device. Despite the nonconvexity of the joint optimization problem, we propose an efficient algorithm to compute the optimal computation offloading solution. By exploiting the optimal offloading decision of each IoT device, we further consider the scenario of a group of IoT devices offloading computation workloads to the edge server, and investigate how the edge server optimally selects the devices for providing the computation offloading service while subject to the limited energy budget and the time-slot budget of the edge server. We propose an efficient algorithm to find the optimal selection of the devices. We present extensive numerical results to validate the effectiveness of our proposed algorithms and show the impact of the secrecy requirement.
Flexible functional design of the torque axis in the shearer

The paper analyses the relationship of characteristics of the flexible torque axis in the shear and the main parameters, makes an analogy analysis for the case combining with the parameters of the specific torque axis, gives the functional design method which refers to the static strength as first and the torsional fatigue strength as second. By introducing the design parameters, it forms a design series and the optional method, provides the simple and practical design, and offers the reference to the standard design of the flexible torque axis.