Miracle-dz/UniFAR-FTUs huggingface dataset:
A PM Pole With Axial Varied Width for Vibration Mitigation in PM Brush DC Motors

This paper presents a PM pole with varied width in the axial direction for vibration mitigation in permanent magnet brush dc motors, which is proposed to decrease the deformation caused by radial pulsating force and bending moment together. First, the air gap flux density distribution and radial force density distribution are derived in detail. After two types of vibration modes and their reasons as pulsating force and bending moment are analyzed, the difficulty in vibration mitigation is pointed out. By investigating the change rule of the pulsating force and bending moment with PM pole width, a type of PM pole with varied width in the axial direction is proposed. Its principle of deformation reduction is presented, and the optimized pole shape is derived. A three-dimensional finite-element method is used to calculate the magnetic field, Maxwell force, modal analysis, and deformation of motors. In order to verify the effectiveness of the proposed method, the vibration of the proposed motor is compared with the other three types of traditional motors, including skewing slot or skewing pole. Finally, experimental results of two types of motors are compared to validate the proposed technique.
Enhanced Machine Learning Feature Selection Algorithm for Cardiac Arrhythmia in a Personal Healthcare Application

In this paper, we propose a personal healthcare system to diagnosis, monitor, identify ectopic heartbeats and provide services for heart diseases patients. The proposed system includes three subsystems, (1) the Electrocardiograph signal acquisition device, (2) the mobile device with APP software for signal processing and communication, and (3) Web service for feature extraction, selection and heartbeat classification based on the support vector machine. The proposed system can identify 16 kinds of heartbeats and it can be used in daily life.
Interest-based Modeling Based on Group Wisdom and Its Application in Recommendation Algorithms

The existing related work fails to capture the shortcomings of the user's real interest when using resource features for user interest modeling. This paper proposes a user intelligence modeling method based on group intelligence. Taking into account several user behaviors including browsing and evaluation, we use group intelligence and representation learning technology to model users' interes, in order to improving the performance of personalized recommendation. In the experiment, this paper takes the film recommendation task as an example to verify the effectiveness of the proposed method on real data. The experimental results show that compared with the traditional project-based user interest modeling method, the group intelligence-based user interest modeling method can more accurately describe the user's interest and obtain better recommendation effect.
A New Timing Steganography Algorithm in Real-Time Transmission Devices

Network steganography is the practice of concealing information in a carrier, the challenges in steganography arises due to abnormalities created because of carrier modification, which comes when embedding binaries, making it detectable by either statistical analysis or some sophisticated algorithm, and often the methods are not reliable. This paper presents a new approach by using time interval of successive transmission and if the interval is numerically a member of a set of a key, represents bit one else bit zero. To scramble the message before hiding, I first encrypt using XOR cipher and bitwise shifting, and by applying the concept of dynamical key generation, reinforce resistivity against cryptanalysis. Furthermore, to mystify security system from monitoring a channel, the concept of discreet mathematical relationship is use for security enhancement, by applying many sets of devices for transmission; these devices must adhere to the generated time interval. The experiment conducted at application layer in OSI network model using applications like, WhatsApp, WeChat, and cell phone time of calls, the result showed that it is extremely difficult to differentiate between normal transmission and the one carrying hidden message and the method is reliable. Keywords-information hiding; steganography; information security; cryptography; network security
Efficient Classification of Application Characteristics by Using Hardware Performance Counters with Data Mining

Hardware performance counters in processors are mainly used for low level performance analysis and application tuning by monitoring performance-related hardware events. With the advent of processors with more cores than existing multicore processors and additional high-bandwidth memory, research on the performance analysis of new systems has received increasing attention from the high-performance computing community. Analyzing application characteristics and system features in a new system is essential for computational scientists and engineers who are eager to obtain the best performance of their scientific applications. However, these processors, increased core counts and high-performance resources, make it difficult to understand the correlation between performance-related hardware events. In this paper, we propose a method to simply and quickly classify application characteristics by using a data mining tool without understanding the correlation between hardware events. When we applied the proposed method to NAS Parallel Benchmarks (NPB), the application characteristics were the same as the authorized NPB categories. We show the effectiveness of the proposed scheme in a case study on analyzing the degree of interference between application characteristics.
Workspace and Singularity Analysis of Five Bar Planar Parallel Manipulator

This paper presents an analysis of workspace and singularity of a five-bar planar parallel manipulator with revolute joints. The traditional approach of kinematic analysis is not suitable for parallel manipulator. Therefore, the inverse kinematic approach is used for the workspace analysis. A simplified equation for tracing the boundary of the workspace is presented. Practically, the manipulator stops or fails to operate after traveling certain distance within the workspace due to the occurrence of singularity, therefore singularity must be avoided for a smooth operation of manipulator. In the present paper, the mathematical conditions for the three kinds of singularity of five-bar planar parallel manipulator are derived, which is based on Jacobian matrices and represent the corresponding singularity configuration. The results are useful to the design, manufacturing and control of a five-bar planar parallel manipulator. This kind of analysis is very important while designing the industrial robotic manipulator.
Study of Extended SM scheme over Generalized α — µ fading channel

In this paper, performance of Extended Spatial Modulation (ESM) scheme for multi input multi output systems over uncorrelated flat fading α - µ channel have been evaluated using simulation and studied. The existing sub-optimal threshold detection method with lesser complexity is implemented at the receiver. The effects of varying the transmitter diversity, spectral efficiency and receiver diversity on the bit error rate (BER) performance have also been discussed. The comparative study of spectral efficiency ESM with spatial modulation SM has also been presented.
Sub-Pixel Defect Detection for Super Large LCD Images Using Quadrant Gradient Operator

This paper proposes an automatic sub-pixel component defect detection algorithm to locate the flaws of liquid crystal display (LCD) using super large images. To ensure detection accuracy, a line scan camera is used to capture the images of an LCD with more than 200 million pixels. Therefore, a tiny sub-pixel component of an LCD is mapped into many pixels in an image. The quadrant gradient operator is proposed to adjust gradient direction dynamically in different quadrants. Our method can directly detect sub-pixel component defects without extra operation to deal with edges. To detect defects efficiently and automatically, related parameters are estimated using a small random sampled sub-image. The projection method estimates the spaces between sub-pixel components, based on which the sample size and the defect area threshold can be estimated. Theoretical analysis and experimental results show that the proposed algorithm can accurately detect sub-pixel component defects in linear complexity O($n$).
Extraction Micro-Doppler Feature of Precession Targets in Orthogonal Frequence Division Multiplexing-Linear Frequence Modulation Multiple Input Multiple Output Radar

The micro-Doppler feature of ballistic targets is a hot spot in current research. The problem that the single-base radar can’t accurately obtain the target micro-motion parameters due to the shielding effects in radar observation angle. This paper puts forward a method to introduce Orthogonal Frequence Division Multiplexing-Linear Frequence Modulation(OFDMLFM) signal into Multiple Input Multiple Output(MIMO) radar. Firstly, the mathematical model of the cone-cylinder ballistic target’s precession in MIMO radar is constructed, and then the micro-Doppler effect of the target when the radar radiates OFDM-LFM signal is analyzed. On this basis, using Hough transform to extract the parameters of the time-frequency curve, by solving multiple nonlinear equations to obtain the estimated value of the target precession angle, micro-motion angle velocity, target height,and finally verify the effectiveness of the algorithm through simulation experiments.
Speech Directed Face Composite Tool

Forensic composite is an artistic technique used in the identification, apprehension, or conviction of wanted persons. Face Composite is traditionally the most commonly known discipline of forensic art. Facial sketches are particularly valuable when eyewitnesses' or victim's descriptions are the only form of evidence available. For a very accurate forensic sketch to be developed the forensic sketch artists typically require a few years of training to become proficient in drawing sketches. Unfortunately, this process is inefficient and does not leverage all available resources, in particular, the extensive mugshot databases maintained by law enforcement agencies. We address this problem by developing a software tool that prepares a face composite based on the oral narration of the eyewitness through speech and image processing techniques. Where forensic sketch artists typically require a few years of training to become proficient in drawing sketches, here only a few hours of training are typically required before the user can start using composite-generation software. Successful techniques for automatically matching facial sketches to mugshots will also improve the effectiveness of facial sketches and allow for a faster apprehension of such suspects. We present experimental results using a database that is created which gives the software tool, the capability of generating 720 male and 720 female face composites. The created face composite can also be compared to the face composites that are already stored in a mugshot database.
Prediction and Detection of Malicious Insiders' Motivation Based on Sentiment Profile on Webpages and Emails

Recent high profile data breaches have highlighted the importance of insider threat detection research for cyber security. Anomaly based insider detection approaches are generally associated with high false positives; thus, there has been increased focus on including prediction of user psychology and attack motivations. However, data relating to psychological profile and personality trait of employees are challenging to collect, and do not generally adequately capture attack motivations such as disgruntlement (e.g. towards certain behavior). Therefore, in this paper, we demonstrate how one can build a user psychological profile based on the sentiment analysis of their network browsing and email content. We then evaluate our approach using real-world datasets, and the findings suggest that our approach can proactively and accurately detect malicious insiders with extreme or negative emotional tendencies. This is the first work to build user profile and predict insider threats using sentiment analysis of their browsing and email content.
An Aggregate Computing Approach to Self-Stabilizing Leader Election

Leader election is one of the core coordination problems of distributed systems, and has been addressed in many different ways suitable for different classes of systems. It is unclear, however, whether existing methods will be effective for resilient device coordination in open, complex, networked distributed systems like smart cities, tactical networks, personal networks and the Internet of Things (IoT). Aggregate computing provides a layered approach to developing such systems, in which resilience is provided by a layer comprising a set of adaptive algorithms whose compositions have been shown to cover a large class of coordination activities. In this paper, we show how a feedback interconnection of these basis set algorithms can perform distributed leader election resilient to device topology and position changes. We also characterize a key design parameter that defines some important performance attributes: Too large a value impairs resilience to loss of existing leaders, while too small a value leads to multiple leaders. We characterize the smallest value of this parameter for which the only stationary points have single leaders, and demonstrate resilience of this algorithm through simulations.
MILP Model for Reliability Optimization In Active Distribution Networks

This paper presents a Mixed Integer Linear Programming (MILP) model for optimal allocation of Automatic Switching Devices (ASDs) and Distributed Generation (DG) in distribution networks. The model’s formulation considers the application of ASDs for protection and post-fault restoration purposes, as well as the role of DG units in the restoration process. From the reliability perspective, System Average Interruption Frequency Index (SAIFI) is used as a metric index for obtaining an optimal placement of ASDs and DG units. Decoupling the optimal allocation problems of ASDs and DG units does not provide an optimal solution, since both are inherently interdependent with system reliability. Hence, the simultaneous allocation of ASDs and DG units is considered in this work. A Goal Programming approach is used to establish the optimal trade-off between the placement of ASDs and DG units, and the improvement on SAIFI. In other words, the developed model aims to i) minimize the number of interrupted consumers due to protection operation; ii) maximize the number of consumers restored by automatic network reconfiguration, and iii) minimize costs associated with the allocation of ASDs and DG units. Restoration is ensured by a set of linear power flow equations. The model’s solutions are obtained from a Branch and Bound-based technique, and results are presented using the IEEE 123-bus system.
An Optimal Resource Allocation Algorithm Based on Sum Rate Maximization for Uplink SCMA system

An optimal resource allocation algorithm based on sum rate maximization for uplink Sparse Code Multiple Access (SCMA) is proposed in this paper. The goal of the algorithm is to solve the problem of resource allocation based on maximizing system and rate in the uplink SCMA system. Firstly, based on the inter-user interference model in the system, an optimal subcarrier allocation algorithm is proposed to solve the subcarrier allocation problem. Then, based on the subcarrier allocation scheme, the optimization problem for maximizing the system sum rate is reduced to a convex optimization problem. A power allocation scheme is obtained by solving the convex optimization problem. Finally, the subcarrier allocation optimization algorithm and the power distribution solution are combined and iteratively optimized. Simulation results demonstrate that the proposed optimization algorithm can effectively increase the total capacity of the uplink SCMA system.
The Influence of Corporate Reputation on Consumer Brand Loyalty in Caused-Related Marketing

"Buy a bottle of water and donate a penny" is a marketing campaign by Nongfu Spring. We collectively refer to similar activities as cause-related marketing (CRM). First of all, through the research of previous scholars, a new research model on brand loyalty is established. For further research, the first step is to verify the relationship between emotional reputation, cognitive reputation and consumer trust and brand loyalty. What is more important is to examine the intermediary role of consumer trust. This paper mainly examines how corporate reputation influences consumer brand loyalty. The application of Wen’s intermediary effect test model mediates the mediating role of consumer trust. The results reveal a positive mediating effect of consumer trust between emotional reputation and brand loyalty. However, when testing the cognition reputation, the result is negative.
An 8-Bit High Speed Successive Approximation Analog-to-Digital Converter

In this paper, an 8-Bit 51 MS/s SAR-ADC in 180 nm CMOS Process is designed. This SAR-ADC utilizes a high-speed clocked-comparator to improve the comparing speed. The converter adopts an improved DAC structure to eliminate the negative influence brought by the large unit capacitance (16fF) that limits the speed of SAR-ADC. The simulation results show that the SNDR of the ADC is 44.3 dB, the SFDR is 51.6dB, and the ENOB is 7.07dB at 25 MHz input signal frequency and 51MHz sample clock frequency. The total power dissipation of this converter is 0.61mW, and the FOM is 89fj/conv with a 1.8V supply. Based on the large capacitance under standard process, the design in this paper doubles the speed compared to the original structure with only one more register and 0.05mW more power consumption.
Algorithm Recognizing Nonlinear-Load-Current States and Having Dynamic Iteration Step Size

An active power filter is a feasible solution to compensate harmonics, and harmonic currents detection is one of its key aspects. In order to explore a harmonic currents detection method with both high steady-state detection accuracy and short dynamic response time, two nonlinear load current (NLC) states, a steady and a change state, should be recognized accurately. Thus, a method should be researched for recognizing NLC states accurately. This paper derived a direct computational method, and a simple and an optimal iteration algorithm, for computing NLC average value. The direct computational method can be employed to compute its average value accurately when NLC is in steady states. Although the optimal iteration algorithm is more complex than the direct computational method, it provides an idea of recognizing NLC states. From this idea, an algorithm was presented for recognizing NLC states based on the optimal iteration algorithm. In this algorithm, a dynamic iteration step size (ISS) was introduced, and thus an algorithm was proposed for recognizing NLC states accurately based on the dynamic ISS. Finally, accuracy of the proposed algorithm is confirmed by simulation and experiment results.
Fraction of Connections Among Friends of Friends as a New Metric for Network Analysis

Network generation models try to mimic real world networks. Basic models of network generation like Random and Preferential Attachment result in networks without communities and having clustering coefficients less than that of real networks. We have proposed an alternative model to generate network having high clustering coefficient as well as community structure. We have included two new features in our model to achieve this. They are: $i$) to allow a person to make friends in iterations and ii) to make a particular fraction (say f) of links among friends of friends and rest among others. By preferring the connections among friends of friends, the clustering coefficient increases. By varying the fraction f, we can generate network with desired clustering coefficient. The proposed model has certain interesting properties. it generates community structure where number of communities and their interconnectedness can also be controlled by varying f. Finally, network size, and fraction $f$ are deciding the value of clustering coefficient of the network and responsible for having communities.
Normalized Log Twicing Function for DC Coefficients Scaling in LAB Color Space

The brightness of hand held captured images using cameras or camcorders usually differ in the color of the actual scene. These images suffer from the poor contrast values and are having non uniform illumination. There is always a scope to improve the contrast and illustration outward show of the true color metaphors. This piece mainly focuses on the contrast enhancement methods using DC coefficient scaling in the DCT domain. The performance of the conventional DC coefficient scaling is compared in different color spaces as YCbCR and LAB. Based on comparison, it is proposed to scale the DC coefficient in the CIE-Lab color space. Our prime contribution is to propose a novel mapping function by merging the log transformation and the standard Twicing function. The mapped function is then normalized using optimum constants to achieve better visual appearance. The contrast of only L components of LAB space is enhanced, but chrominance information terms are kept preserved. This provides the improved entropy of the enhanced images. The performance is compared using statistical parameters as SNR, entropy and standard deviation difference. The method are trialling on true color image of different environments.
Optimal Power Allocation Using PSO in Cooperative Wireless Networks

In recent years, cooperative communication based on wireless communication networks have attracted significant attentions because of their intrinsic capability of suitability of working in an adverse environment where multiple interferer which causes fading are also present. Mobile wireless communication has experienced an unprecedented growth in data traffic for which communication using cooperative networks has attracted much interest where relay transmission gives better performance as compared to direct transmission. The system performance improves for multi relay model where minimizing the problem of relay selection with limited transmit power a major challenge to deal with. In the proposed work, an AF relaying based cooperative wireless network is considered in which communication takes place from source to destination via various relay nodes. The concern of optimal power allocation is resolved by using the proposed Particle Swarm Optimization (PSO) technique. The proposed algorithm using the PSO optimization technique is used in cooperative communication network scenario and communication process is simulated using MATLAB software. The results obtained are compared with other previous works.
Comparison with HTTP and MQTT In Internet of Things (IoT)

Internet of Things (IoT) can be defined as a physical object which are connected over internet or an embedded system which consists of electronics, software, sensors, and connectivity module like modem or Wi-Fi which enable the device to connect over internet so that data can be exchanged and will be able to control the embedded device from anywhere over internet. IoT devices helps to connect all sensors which help to monitor and control electronic or mechanical systems. IoT system are very useful in industries where humans are unable to enter like a radiation room etc. Nowadays IoT systems are used in government sectors for security and in-home security and home automation [4]. But still it's not common as the cost of IoT devices is high and the modularity is less. To make the device modular we need to find a best way of communication protocol so that the latency of the communication will be less. This paper presents the comparison of best to protocol and which is the best protocol which we need to use to reduce the latency and make the device modular and able to control remotely.