Miracle-dz/UniFAR-FTUs huggingface dataset:
From Time to Space: Automatic Annotation of Unmarked Traffic Scene Based on Trajectory Data

Research on autonomous driving is requiring more affordance information from the environment, which can be efficiently used by the subject vehicle. Road layout parsing is fundamentally important to this, and has attracted deserved attention on the urban road net where traffic signs are well established. However, for the unmarked traffic scenes, like campus and residence community, the large variation on individual surroundings leads to a reduced attention on public research and a lack of both available dataset and generic methods. To explore this issue, we present a novel automatic annotation method to analyze road semantics, which regards the prior trajectories of a vehicle as multi-dimensional space series and extends the traditional time series methods to the space domain to process the data. In order to achieve this, we first propose Incremental Dynamic Space Warping (IDSW) to synchronize space series and extract statistical road feature, then a Bayesian nonparametric method based on the Hierarchical Dirichlet Process-Hidden Markov Model (HDP-HMM) is introduced to generate road semantic sections without explicitly specifying the number of class. Experiment results demonstrate the proposed method can produce road semantics in different level and annotate not only the physical road position but also the vision observations: based on the extracted road modes, the method can annotate corresponding vision image with a positive class label and a rough distance to the road intersection.
Artificial Intelligence in Politics: Establishing Ethics

Recent advances in Artificial Intelligence (AI) have produced AI tools that help political campaigns to prevail in election cycles. There have been notable early successes for campaigns using this technology, particularly in 2016 for the Trump presidential campaign and, during the Brexit referendum, the U.K. Leave Campaign. Critiques of these pioneering tools argue that they have adopted unethical practices, and that monitoring the ethical use of such tools is too complex a task, particularly when tools are the intellectual property of private corporations. This article challenges that notion and proposes a way to engage in dialectics with advanced tools of AI in governance as they go about their tasks. The proposals presented here could help electorates around the world to build up observable integrity within their election cycles and thereby increase levels of trust in the societal institutions tasked with ensuring them free, fair, and open election conditions.
Load balancing in fixed-routing optical networks with weighted ordering heuristics

In this paper we show that the adoption of a simple weighted ordering heuristic strategy to find fixed shortest path routes in a topology can improve load-balancing and, consequently, network performance. We compared our fixed routing strategies against the k-shortest paths (k-SP) fixed-alternate routing strategy for three different mesh topologies considering fixed grid networks (FGNs) and elastic optical networks (EONs). The results show that our simple fixed routing strategies can improve network performance for an optical network system, even compared with the fixed alternate routing and always using the shortest path. Results also show that such easy strategies act mainly in longer routes, increasing their probability of use and balancing the link load distribution.
Kinematic Modelling and Analysis of an Ess-board-like Robot

Considering the problem of large steering error caused by hysteresis on the passive wheel of the Essboard, a kinematic model based on coordinate transformation is proposed to improve its precision of the wheel effectively. Firstly, the holonomic constraint equation and nonholonomic constraint equation are established. The Newton iteration method is used to solve the geometric relationship between the pedal roll angle and the wheel steering angle. Then, as a verification, the virtual prototype technique(VPT) is used to obtain the measured steering angle data. Comparing with the solution of the kinematics, it is found that the average error is 0.3° and maximum error is 2.4°. After comparing with the other literature(the average error is 8.2° and the maximum error is 14.5°), it is found that the kinematic model proposed in this paper is correct and can be applied to model the motion of the Essboard. In general, this kinematic equation can be applied to the other single-track vehicles, such as motorcycle with two-wheel steering, bicycles, etc. and it has a wide application value.
Sentence Classification with Transfer Network

Sentence classification is a fundamental task in natural language processing. In this paper, clickbait detection is taken as an example to study the sentence classification with a transferring network. Clickbait are news headlines that exaggerate the facts or hide partial facts headlines. Statistics show that clickbaits are prevalent among all languages. However, previous research on clickbait detection mainly focus on English, exploiting lexical or syntactical features that are not shared by other languages. On the other hand, it would be both time-consuming and labor-intensive to annotate a clickbait dataset by humans. Recently, neural language model that represent each word by a real-valued, dense vector show that words with similar meanings across languages are close to each other in the vector space. Inspired by this, transfer learning is proposed to be applied to transfer the model on clickbait detection from a source language to other languages with very few annotations. This paper trains the source model on English corpus and transfers it to corpus in Chinese. Experimental results show that transfer learning model in this paper can achieve similar performance on the target language using less annotation, showing the effectiveness and robustness of this model.
Promoting behavior change in Rowan University students through fitness and wellness programming

Megan E. McHugh PROMOTING BEHAVIOR CHANGE IN ROWAN UNIVERSITY STUDENTS THROUGH FITNESS AND WELLNESS PROGRAMMING 2014-2015 Burton R. Sisco, Ed.D Master of Arts in Higher Education The purpose of this study was to investigate the impact of participation in the Rowan University Recreation Center’s 2015 RU Heart Strong incentive program, and to explore behavior change in college students as a result of fitness and wellness programming at Rowan University. Data were collected from 59 subjects who participated in a survey that assessed subjects’ physical activity levels and various psychosocial constructs such as social support, self-efficacy, and expectations in relation to the 2015 RU Heart Strong incentive program. Data analysis suggested that students who participated in the RU Heart Strong incentive program practiced behaviors to maintain a healthier lifestyle such as exercising and eating well. Data also suggested that subjects experienced minimal positive behavior change towards maintaining a healthy lifestyle as a result of their participation in the RU Heart Strong incentive program.
New parameter for modelling of hip motion at patient with coxarthritis

It is difficult to identify objective parameters for assessing the joint function when evaluating the outcome of orthopaedic procedures, especially endoprosthetic replacement. Spatial-temporal and angular parameters of gait have clinical relevance in the assessment of motor pathologies, particularly in orthopaedics. These parameters did not model the motion of the femur with respect to the pelvis. The first aim of this study is to determine a new parameter (relative hip movement parameter) for modelling the motion of the bones forming the hip joint. The spatial-temporal, angular parameters and relative movement parameters are determined by a zebris ultrasound-based motion analyser at 20 healthy subjects and at 20 patients with unilateral hip disease (Kellgren-Lawrance radiographic index 4). The second aim of this study is to compare the gait parameters of patients to those of healthy subjects. Asymmetry was observed in spatial-temporal parameters, the range of hip motion, maximum hip flexion, maximum hip extension, as well as knee motion in patients. Therefore, it was suggested that the increased motion of the opposite hip and knee was a compensatory function. The study showed that increased pelvis obliquity and flexion-extension occurred as compensation. It seems that the range of pelvis rotation was not involved, even in our patients with unilateral osteoarthritis of the hip joint. The relative hip movement parameter of patients is significantly less compared to the parameter of healthy subjects, it means the motion of the femur with respect to the pelvis is small.
Application of Insole Pressure Sensor to Assess Lower Extremity Compliance

The most serious fracture in the hip is a hip fracture. There is a large chance of death within one year, often accompanied by serious complications, which indirectly lead to death. Therefore, the importance of postoperative rehabilitation can be seen. Rehabilitation therapy for patients with lower extremity fractures is often used partial weight bearing (PWB) clinically, but the traditional method of identification the appropriate weight-bearing lower limb weight is less objective and accurate, and it is impossible to know whether the patient accurately performs the rehabilitation of partial weight bearing. Therefore, this paper proposes a wearable instant insole pressure sensing system, which can provide complete foot pressure information instantly, and know the lower limb weight, for the therapist to refer to the configuration of the patient's lower limb burden weight and the patient's regular self-testing.
A 20.5-dBm  $X$ -Band Power Amplifier With a 1.2-V Supply in 65-nm CMOS Technology

In this letter, we present an X-band power amplifier (PA) which achieves a saturated output power ( $P_{\mathrm {sat}}$ ) of 20.5 dBm under a 1.2-V supply in 65-nm CMOS. Considering the relatively low breakdown voltage of the 65-nm device, we adopted a differential configuration with a triple-well cascode in which the n-well of the cascode device was biased with a resistor. Also, the PA adopted an on-chip 1:2 transformer to provide a low output impedance at the drain, and a series RC feedback was employed to enhance the stability and the gain bandwidth (BW) as well. The measured 3-dB BW of the PA covered the whole X-band and supported an output 1-dB gain compression point (OP1dB) of 15.2 dBm. A peak power-added efficiency of 24.6% with a gain of 24.4 dB at 9 GHz was recorded. The core of the PA occupies only 0.48 mm2.
Universal Input AC Three-Phase Power Factor Correction With Adaptive Intermediate Bus Voltage to Optimize Efficiency

This paper proposes an adaptive intermediate bus voltage solution to optimize efficiency in a universal three-phase ac input (200–480 V) cascaded buck-follows-boost power factor corrected (PFC) converter with a 400-V dc output voltage. With this application and architecture, the output voltage of the boost converter needs to be higher than the peak ac input voltage to maintain PFC and regulation. The conventional approach would regulate the intermediate bus voltage to near 800-V dc; this allows for 480-V ac high line input, plus allowable overvoltage tolerance and margin for regulation, but it incurs heavy losses at low line input. This paper proposes to adaptively change the bus voltage between the boost and buck stages, based on the value of the ac input voltage, and the use of a relay to bypass the buck stage for low ac line input conditions in order to maximize efficiency. A loss analysis is included to show the significant loss savings and efficiency improvement using the proposed method. Experimental results are presented for a 5-kW silicon-carbide-based prototype. The proposed method demonstrates up to a 4.4 percentage point increase in efficiency (220-W decrease in loss) at low ac line input compared to the conventional PFC approach with an 800-V dc intermediate bus voltage.
Impedance-Based Analysis of DC-Link Voltage Dynamics in Voltage-Source Converters

This paper addresses the stability issues caused by the dc-link voltage control of grid-connected voltage-source converters. An analytical impedance model is developed first for capturing the interactions between the dc-link voltage control and ac current control of converters, which enables to identify different stability impacts of the dc-link voltage control in the rectifier and inverter operation modes of converters. The impedance model is further transformed from the <inline-formula><tex-math notation="LaTeX">$dq$</tex-math></inline-formula>-frame to the <inline-formula><tex-math notation="LaTeX">$\alpha \beta $</tex-math></inline-formula>-frame, which allows characterizing the frequency-coupling effects of the dc-link voltage control dynamics. The impedance-based analysis reveals that the dc-link voltage control may cause low-frequency oscillations in the rectifier mode and high-frequency oscillations in the inverter mode. Case studies on the rectifier and inverter operation modes are presented, and subsequently validated by using time-domain simulations and experimental tests. The close correlations between the measured results and theoretical analysis demonstrate the effectiveness of the impedance model and stability analysis.
Harnessing the Power of the General Public for Crowdsourced Business Intelligence: A Survey

Crowdsourced business intelligence (CrowdBI), which leverages the crowdsourced user-generated data to extract useful knowledge about business and create marketing intelligence to excel in the business environment, has become a surging research topic in recent years. Compared with the traditional business intelligence that is based on the firm-owned data and survey data, CrowdBI faces numerous unique issues, such as customer behavior analysis, brand tracking, and product improvement, demand forecasting and trend analysis, competitive intelligence, business popularity analysis and site recommendation, and urban commercial analysis. This paper first characterizes the concept model and unique features and presents a generic framework for CrowdBI. It also investigates novel application areas as well as the key challenges and techniques of CrowdBI. Furthermore, we make discussions about the future research directions of CrowdBI.
Dictionary Representation of Deep Features for Occlusion-Robust Face Recognition

Deep learning has achieved exciting results in face recognition; however, the accuracy is still unsatisfying for occluded faces. To improve the robustness for occluded faces, this paper proposes a novel deep dictionary representation-based classification scheme, where a convolutional neural network is employed as the feature extractor and followed by a dictionary to linearly code the extracted deep features. The dictionary is composed by a gallery part consisting of the deep features of the training samples and an auxiliary part consisting of the mapping vectors acquired from the subjects either inside or outside the training set and associated with the occlusion patterns of the testing face samples. A squared Euclidean norm is used to regularize the coding coefficients. The proposed scheme is computationally efficient and is robust to large contiguous occlusion. In addition, the proposed scheme is generic for both the occluded and non-occluded face images and works with a single training sample per subject. The extensive experimental evaluations demonstrate the superior performance of the proposed approach over other state-of-the-art algorithms.
On the Implementation of Frequency Response Estimation Method of Electric Drives

Identification of a frequency response function of a plant is an important stage in a tuning process of a servo drive control system. This article presents a design and implementation method of a frequency response function estimation. A proposed solution is based on an empirical method, when a series of injection signals with various frequencies are used. Then, the frequency response function is estimated using the Fourier transformation of an input and an output signal of the plant. There is proposed a separation of the estimation process between a human machine interface and a servo controller to reduce the servo controller loading. In this case, the servo controller generates the injection signal, collects and sends the data to human machine interface which realizes mathematical functions of the frequency response estimation. The designed method could identify any desired frequency response function using corresponding injected and collected signals. It was successfully used for experimentally identification of as a resonance plant such as a LCL filter of active front end.
P2AM: An Anti-Profiling Framework for Online Healthcare Applications

Users who wish to receive data analytics from an online service are often forced to share their data with service providers (SPs)in order to receive accurate analysis. In some cases, e.g. healthcare, users data cannot be shared because of containing sensitive information and users wish to gain these analytics without exposing their data to SPs. In this work, we propose Profile Perturbation Analytics Mediator framework employing perturbed Mediator Accounts where each profile is randomly perturbed and then exposed as synthetic user profiles to SPs' back-end for training analytic models. Once the model is trained, it is used in the client side to perform analytics on users original profiles. We refer to such randomized perturbations as anti-profiling and define quantitative measurements for evaluating their performance with regards to user privacy gain and utility loss. We introduce Random Partial Profile Perturbation as an example anti-profiling mechanism to be used in P2AM framework and evaluate its performance in two healthcare applications.
DF -FS based path planning algorithm with sparse waypoints in unstructured terrain

For autonomous navigation in unstructured terrain, it's difficult to plan the path with traditional algorithms based on searching guidance waypoints such as ARA* and Field D* as a result of the poor positioning signal and the environmental uncertainty especially when dense waypoints are not given. Because of irregular road boundaries, there are also problems for path planning based road detection methods. To solve these problems, the depth first forward search (DF-FS) based path planning algorithm which combines forward searching along the road and model-based prediction is proposed. DF-FS based planner takes road boundary constraint, road direction and heading of vehicle as the basis of path planning, while using model prediction optimizes planned path to improve navigation stability. The experiment results show that in unstructured terrain with sparse waypoints or even without waypoints in the one-way road, the autonomous navigation can be guaranteed effectively. Meanwhile the proposed algorithm has a strong robustness to the uncertainty of positioning and environmental perception, so it is suitable for autonomous navigation in rough terrain.
A new proof of an inequality between two secrecy exponents

Hayashi and Matsumoto gave two lower bounds for the secrecy exponent for wiretap channels in 2011 and 2016. They proved that the latter exponent function is greater than or equal to the former one for any positive rate, input distribution and conditional probability of wiretapper’s channel. In this paper, we give a new and simple proof of the inequality between the two exponent functions. To prove the inequality we use non-negativity of Kullback-Leibler distance together with a lemma that was introduced by Arimoto to derive a computation algorithm for error and correct decoding probability exponent for discrete memoryless channels.
Evaluation of the Bolted Joints Fault of Aircraft Structure with Flexible Analytic Wavelet Transform

Bolted joints as a universal connecting are widely used in engineering especially in aircraft structure. While, being one of the most common failure components in aircraft structure, bolted joints failure forms are kind of difference and the most common failure form is bolt looseness, which is difficult to be observed directly, and it usually leads to destructive accidents. In this paper, the state of bolted joints is evaluated with the active method, which used lead zirconate titanate (PZT) sensors to create surface waves and to monitor their responses. Then using a flexible analytic wavelet transform (FAWT), FFT and DWT, the experimental data was analyzed and compared to detect the faults. All the results showed that FAWT is more suitable for the experiment of bolted joints.
Polymer Tandem solar cell: An overview

Solar cell has gained Wide Attention in the last decade or so due to the fact that solar cell has the potential to tap the worlds current energy demand of 15TW besides this solar cell is renewable and cleaner source of energy unlike fossil fuel . The primary problem currently with the solar cell is that it has relatively low efficiency and expensive installation and very long energy payback time. Lot of research and development is going on to make solar cells affordable recently polymer solar cell gained wide attention worldwide as it belongs to the category of direct band gap semiconductors which helps in decreasing the thinness of photo-voltaic up to a level of few micrometer also the polymer solar cell has an inherit advantage of flexibility, very low thickness but has incorporated with an disadvantage of low efficiency which is around 11% but tandem solar cell which is comprised of two layers of different active material which enables the cell to cover broad spectrum and overall increase in efficiency. Tandem solar cell has a huge potential due to utilization of energy extracted from two active layers in a single solar cell that’s the reason there is noticeable addition in the performance, efficiency and other parameters of the solar cell. This article tends to provide an overview how tandem solar cell works, the polymer material that is being used in tandem solar cell which is divided into two categories high energy band gap polymers and low energy band gap polymers then discussing different types and use of interconnecting layer in polymer tandem solar cell.
Optimal Grip planning for Biped Climbing Robots

Grips from the original point to the destination are indispensable for biped climbing robots moving in truss environments. In this paper, we present a novel optimal grip planning method to generate the grip sequence. Based on the prior knowledge of transition operational regions obtained in the global path planning procedure [1], we first analyze the relationship between moving distance and the number of climbing steps. We then set up a grip optimization model to minimize the total climbing steps, guaranteeing that the transition grips are assigned in the transition operational regions and all grips satisfy the robot kinematics. Lastly, grip sequences are generated by a grip interpreter. Simulations are conducted with our self-developed biped climbing robot (Climbot), to verify the effectiveness and efficiency of the proposed methodology. Results show that our method is capable of planning a sequence of grips up to 30 footsteps in 0.2 seconds, running on a common desktop computer.
Cancer Classification of Gene Expression Data using Machine Learning Models

The World Cancer Report described cancer as a global problem because it affects the whole greater population. It was projected by that cancer incidence will increase to 20 million new cases by 2025 [2]. There are several known published literatures on cancer classification techniques with varying models and implementations. This paper presents the existing technology of microarray gene expression and classify the cancer genes using machine learning algorithms. A logical design was presented using supervised classification and gene selection model. This model can improve the process and method of identifying and classifying cancer disease using gene expression data.