Miracle-dz/UniFAR-FTUs huggingface dataset:
How Smartphone Accelerometers Reveal Aggressive Driving Behavior?—The Key is the Representation

Aggressive driving behavior is one of the leading causes of road accidents worldwide. One way to ameliorate this situation is to collect and analyze driving patterns with the intention of promoting driving awareness, a task that has been called driving analytics (DA). DA employing the driver’s smartphone has attracted attention from the community given its good capabilities to capture, via its integrated sensors, data that could be exploited to infer driving style. Most works in the related literature have represented this sensor information either as statistical scores or in raw format that are later fed into threshold-based heuristics or machine learning (ML) approaches. Based on the hypothesis that better data representations do exist, in this paper, we propose a second-order representation, based on the bag-of-words’ strategy, to model accelerometer timestamps associated with aggressive driving maneuvers. We evaluate this representation in two scenarios and three data sets against the best reported work in each of them. In the first scenario, we classify accelerometer samples as either belonging to aggressive or safe driving style. In the second scenario, we approach a multi-class problem, where we are now interested in identifying the exact aggressive maneuver that the accelerometer sample represents. The results show that this novel representation outperforms both state-of-the-art works with 6% and 15% in F-measure for each scenario, respectively. To further investigate the strength of our representation, we make a comparison against similar second-order strategies that have also proved to be successful. Overall, this analysis suggests that this representation constitutes an attractive method for driving behavior classification, boosting discriminative performance of ML approaches.
Discrete-Time Terminal Sliding-Mode Tracking Control With Alleviated Chattering

A tracking controller design problem for the discrete-time uncertain systems is investigated in this paper. A discrete-time terminal sliding-mode tracking controller is designed to achieve high-performance tracking with alleviated chattering phenomenon. A novel reaching-law is proposed which reduces the bandwidth of the quasi-sliding-mode domain and suppresses the chattering. Furthermore, the reaching process and the bound of the tracking error are analyzed in detail. Finally, comparative experimental results are presented to illustrate the effectiveness and advantages of the proposed strategy.
A Novel Spoke-Type PM Motor With Auxiliary Salient Poles for Low Torque Pulsation

This paper proposes a novel spoke-type permanent-magnet (PM) motor with auxiliary salient poles (ASPs). With these ASPs, unequal ASPs and shifted ASPs in the circumferential direction can be realized and combined to reduce the torque pulsation, while their functions are different. Unequal ASPs are employed to eliminate the second-order torque pulsation. Nevertheless, the shifted ASPs are selected to reduce the first-order torque pulsation. Additionally, the relationship between the unequal angle or shifted angle of the ASPs and the order of the torque pulsation is revealed. Furthermore, the revealed principle of the torque pulsation reduction can be extended to other slot–pole combinations. Finally, a prototype is manufactured for experiments to evaluate the low torque pulsation spoke-type PM motor. Through theoretical analysis and experimental testing, it is verified that the proposed motor offers low torque pulsation and that the revealed principle for torque pulsation reduction of different orders is feasible and effective.
The Effects of Da’wah Approach through Multimedia Students of Sultan Zainal Abidin University (UniSZA)

The use of multimedia in life is a very important thing in life, especially university students. Some can not live without a lot of multimedia that alters the lifestyle. Various things are derived from the use of multimedia, such as viewing videos, listening to music, reading articles and so on from multiple platforms. However, multimedia facilities can also invite various things that are not good if it is wrong to use them. UniSZA students prefer to enjoy multimedia through Facebook platforms rather than conventional platforms. Hence, da'wah in the present time has a huge challenge among university students. Without proper approach, da'wah by using multimedia has no significant effect. The research method used in this study is quantitative, test the effectiveness of da'wah approach through text, image, and video and through the facebook platform as intermediary among university students. The purpose of this study is to determine the effectiveness of da'wah approaches that are favoured by university students. A total of 250 UniSZA students are used as a sample using facebook in their lives. The data analysis method used is Structure Equation Model (SEM) using Amos-SEM software. The findings show that the facebook platform has a significant impact on the student's interest in da'wah approach through multimedia. Videos, pictures and texts have a significant impact on the Facebook platform. The results of this study can be used as a reference by Muslim practitioners both individuals and institutions who want to carry out da'wah through multimedia that has a positive impact.
MEASURING THE PERFORMANCE OF BIG DATA ANALYTICS PROCESS

Big data analytics (BDA) in a process perspective has major benefits towards a better outcome, thereby satisfied customers and evidence-based practices. The aim of BDA is to examine and analyze raw data and to derive and extract actionable insights from it. BDA involves data and tools for processing and analyzing, and the process which data is handled and managed. BDA process is the end-to-end process which consists of phases named as data acquisition, data preparation (integration and preprocessing), data analysis, visualizations and interpretation. The performance of big data analytics is not merely dependent on having quality data input, but also on performance of the process which the data goes through from acquisition to visualization and interpretation. Measuring the process performance has the benefit of identifying problems and launching corrective actions before these problems deteriorate. The aim of this paper is to present the evaluation for BDA process performance. In view of that, the study identifies the measures, metrics, and indicators for each phase of the BDA process. A subject-matter expert review and a pilot study were conducted, and the results obtained were reported in this paper.
Embedding social inclusiveness and appropriateness in engineering assessment of green infrastructure to enhance urban resilience

ABSTRACT Urban resilience emerges not only from ‘what’ is done in relation to critical infrastructure systems, but in the ‘how’ of their conception, co-creation and integration into complex socio-ecological-technical systems. For green infrastructure, where ownership and agency may be distributed amongst organisations and diverse communities, inclusiveness and appropriateness require embedding in engineering assessments of green infrastructure and resilience. Through consideration of past, present and future engineering and resilience assessments – from monetising, through greening, to humanising – this paper examines the ways in which GI may be or has already contributed to enhancing urban resilience and types of assessment and indicators that have been or could be used. We suggest that enhancing visibility of the ‘whos’ (individuals, communities) is crucial to fully diversifying assessments. We also suggest some ideas for additional indicators and assert that co-production of future indicators needs to be undertaken with appropriate professionals (e.g. social impact assessment professionals).
Aerodynamic Model Identification of a Quadrotor Subjected to Rotor Failures in the High-Speed Flight Regime

This letter presents a high-fidelity aerodynamic model of a quadrotor in the high-speed flight, with the normal configuration, or subjected to rotor failures. A novel experimental setup, data processing, and model identification procedure are developed. The main idea is that by first establishing the thrust and torque model from static wind tunnel tests as the benchmark of the aerodynamic model, and then identifying the in-plane forces, pitch and roll moments of each rotor from the free flight data obtained in a large-scale open-jet wind tunnel. The validation results show a decent model performance in predicting forces/moments, lateral forces effects, and the quadrotor trimming curve, by comparing with the benchmark model.
An Energy-Efficient Timetable Optimization Approach in a Bi-DirectionUrban Rail Transit Line: A Mixed-Integer Linear Programming Model

The quick growth of energy consumption in urban rail transit has drawn much attention due to the pressure of both operational cost and environmental responsibilities. In this paper, the timetable is optimized with respect to the system cost of urban rail transit, which pays more attention to energy consumption. Firstly, we propose a Mixed-Integer Non-Linear Programming (MINLP) model including the non-linear objective and constraints. The objective and constraints are linearized for an easier process of solution. Then, a Mixed-Integer Linear Programming (MILP) model is employed, which is solved using the commercial solver Gurobi. Furthermore, from the viewpoint of system cost, we present an alternative objective to optimize the total operational cost. Real Automatic Fare Collection (AFC) data from the Changping Line of Beijing urban rail transit is applied to validate the model in the case study. The results show that the designed timetable could achieve about a 35% energy reduction compared with the maximum energy consumption and a 6.6% cost saving compared with the maximum system cost.
Analysis of the Current Electric Battery Models for Electric Vehicle Simulation

Electric vehicles (EVs) are a promising technology to reduce emissions, but its development enormously depends on the technology used in batteries. Nowadays, batteries based on lithium-ion (Li-Ion) seems to be the most suitable for traction, especially nickel-manganese-cobalt (NMC) and nickel-cobalt-aluminum (NCA). An appropriate model of these batteries is fundamental for the simulation of several processes inside an EV, such as the state of charge (SoC) estimation, capacity and power fade analysis, lifetime calculus, or for developing control and optimization strategies. There are different models in the current literature, among which the electric equivalent circuits stand out, being the most appropriate model when performing real-time simulations. However, impedance models for battery diagnosis are considered very attractive. In this context, this paper compares and contrasts the different electrical equivalent circuit models, impedance models, and runtime models for battery-based EV applications, addressing their characteristics, advantages, disadvantages, and usual applications in the field of electromobility. In this sense, this paper serves as a reference for the scientific community focused on the development of control and optimization strategies in the field of electric vehicles, since it facilitates the choice of the model that best suits the needs required.
Euphemistic Strategies Used by Iranian EFL Learners: Death and Lying in Focus

Euphemism is a communicative strategy used to frame a polite or less offensive language and to save people’s public face in communication. This study investigated the euphemistic strategies used by Persian speakers in situations associated with death and lying. Warren’s model of euphemism was drawn on as the analytic model guiding the study. To conduct the study, 60 male and female university students were randomly selected. The data were gathered through copies of an open-ended questionnaire and then analyzed. It was found that “figurative expression”, “implication”, “overstatement”, “understatement”, and “particularization” were the most frequently used euphemistic strategies among the participants in the contexts of death and lying. The study also revealed that there was no relationship between gender and the choice of euphemistic strategies. The findings implied that euphemistic strategies might reflect cultural and religious values.
Pengukuran Keberhasilan E-Learning dengan Mengadopsi Model Delone & Mclean

Investment resources, time and cost in the implementation of information systems are not small, making measuring the success of information systems becomes very important to do. Meanwhile, the university as an educational institution today has been rampant to implement e-learning as an information system that provides added value for students. A University in North Jakarta has implemented e-learning integrated with information portal of students and lecturers since 2009. But until now has not been measured the success of the information system. So this research is done with one of the goals to measure the success of e-learning adopted by the University. In addition, this research would like to test the success model of DeLone and McLean's updated information system (2003) in the case of e-learning. The analysis was performed using SEM with the help of Lisrel 8.7 which tested 7 hypotheses. From this research found that DeLone and McLean model can not be used to explain the cause of success of e-learning system that its use is required, but need further research to get better level of generalization.
A comparison of linear and mosaic diagrams for set visualization

Linear diagrams have been shown to compare favourably to better known forms of set visualization, such as Venn and Euler diagrams, in supporting non-interactive assessment of set relationships. Recent studies that compared several variants of linear diagrams have demonstrated that users perform best at tasks involving identification of intersections, disjointness and subsets when using a horizontally drawn linear diagram with thin lines representing sets and employing vertical lines as guide lines. The essential visual task the user needs to perform in order to interpret this kind of diagram is vertical alignment of parallel lines and detection of overlaps. Space-filling mosaic diagrams which support this same visual task have been used in other applications, such as the visualization of schedules of activities, where they have been shown to be superior to linear Gantt charts. In this article, we present an experimental comparison of linear and mosaic diagrams for visualization of set relationships, in terms of accuracy, time-to-answer and subjective ratings of perceived task difficulty. The findings show that the two visualizations are largely similar with respect to these measures, suggesting that the choice of one or the other may be solely guided by other visual design considerations. Mosaic diagrams might be more suitable, for instance, in cases where miniature diagrams representing overviews of relations in different collections of sets are required, such as in small-multiples displays.
Some Aspects of UWB Signal Interference

Some problems of UWB signal interference are considered without making conventional simplifying assumptions. The possibility of applying impulse response and other dynamic characteristics to vector electromagnetic problems is discussed. We formulate a general superposition principle applicable to electromagnetic fields and give a generalized description of the interference field and its polarization state, suitable for the analysis of any signals, including UWB signals.
Inkjet Printing of Paper-Based Wideband and High Gain Antennas

This thesis represents a major contribution to wideband and high gain inkjetprinted antennas on paper. This work includes the complete characterization of the inkjet printing process for passive microwave devices on paper substrate as well as several ultra-wideband and high gain antenna designs. The characterization work includes the electrical characterization of the permittivity and loss tangent for paper substrate through 10 GHz, ink conductivity data for variable sintering conditions, and minimum feature sizes obtainable by today’s current inkjet processes for metallic nanoparticles. For the first time ever, inkjet-printed antennas are demonstrated that operate over the entire UWB band and demonstrate gains up to 8dB. This work also presents the first fractal-based inkjet-printed antennas with enhanced bandwidth and reduced production costs, and a novel slow wave log periodic dipole array which shows minimizations of 20% in width over conventional log periodic antennas.
PERAN GCG DAN STRUKTUR KEPEMILIKAN DALAM MENDETEKSI MANAJEMEN LABA MELALUI DISCRETIONARY REVENUE

This study aims to examine the role of good corporate governance (GCG) and the ownership structure in the control of management incentives to perform earnings management. GCG in this study measured using indices issued by GCG agencies in Indonesia, Indonesian Institute for Corporate Directorship (IICD). Ownership structure under test consists of managerial ownership, institutional ownership, and foreign ownership. Earnings management measured by discretionary revenue models of Stuben (2010). Samples were analyzed are a manufacturing company study period of 2009 to 2012. Testing the hypothesis is done by using multiple linear regression method. The test results showed that the GCG proven to reduce earnings management. However, all of the ownership structure in this study is not proven negative effect on earnings management. Implications of this research are expected to contribute as additional information for practitioners, academics and policy makers related to the implementation of good corporate governance and ownership structure and its impact on earnings management incentive measures
A Survey on Internet of Things and Cloud Computing for Healthcare

The fast development of the Internet of Things (IoT) technology in recent years has supported connections of numerous smart things along with sensors and established seamless data exchange between them, so it leads to a stringy requirement for data analysis and data storage platform such as cloud computing and fog computing. Healthcare is one of the application domains in IoT that draws enormous interest from industry, the research community, and the public sector. The development of IoT and cloud computing is improving patient safety, staff satisfaction, and operational efficiency in the medical industry. This survey is conducted to analyze the latest IoT components, applications, and market trends of IoT in healthcare, as well as study current development in IoT and cloud computing-based healthcare applications since 2015. We also consider how promising technologies such as cloud computing, ambient assisted living, big data, and wearables are being applied in the healthcare industry and discover various IoT, e-health regulations and policies worldwide to determine how they assist the sustainable development of IoT and cloud computing in the healthcare industry. Moreover, an in-depth review of IoT privacy and security issues, including potential threats, attack types, and security setups from a healthcare viewpoint is conducted. Finally, this paper analyzes previous well-known security models to deal with security risks and provides trends, highlighted opportunities, and challenges for the IoT-based healthcare future development.
A Fault-Tolerant Wideband Amplifier Based on Distributed Amplification Topology

The failure of the transistor could make an amplifier useless, bringing the wireless system to a sudden halt. Therefore, an amplifier which can handle this type of fault without introducing additional components is highly demanded in industrial applications. For this purpose, a distributed amplification topology is proposed in this paper. The robustness of the proposed structure was theoretically verified by analyzing the ideal models of the amplifier under normal and failed modes. The possibility for further performance enhancement using tunable components is also theoretically investigated. For validation, a wideband amplifier which covers a bandwidth from 0.75 to 2.4 GHz is designed, fabricated, and measured. To verify the robustness, the cases with one and two field effect transistors (FETs) failed are evaluated. For the case with one failed FET, the implemented amplifier maintained a comparable performance over the operating frequency band. For the case with two failed FETs, the same bandwidth can be maintained with the unavoidable minor degradation in gain and gain flatness. The unique fault-tolerant property of the proposed topology is demonstrated. As a beneficial supplement to the proposed fault-tolerant architecture, the proposed optimization approach is applied to achieve a better tradeoff among return loss, gain, and gain flatness.
Deep Multi-Scale Convolutional LSTM Network for Travel Demand and Origin-Destination Predictions

Advancements in sensing and the Internet of Things (IoT) technologies generate a huge amount of data. Mobility on demand (MoD) service benefits from the availability of big data in the intelligent transportation system. Given the future travel demand or origin–destination (OD) flows prediction, service providers can pre-allocate unoccupied vehicles to the customers’ origins of service to reduce waiting time. Traditional approaches on future travel demand and the OD flows predictions rely on statistical or machine learning methods. Inspired by deep learning techniques for image and video processing, through regarding localized travel demands as image pixels, a novel deep learning model called multi-scale convolutional long short-term memory network (MultiConvLSTM) is developed in this paper. Rather than using the traditional OD matrix which may lead to loss of geographical information, we propose a new data structure, called OD tensor to represent OD flows, and a manipulation method, called OD tensor permutation and matricization, is introduced to handle the high dimensionality features of OD tensor. MultiConvLSTM considers both temporal and spatial correlations to predict the future travel demand and OD flows. Experiments on real-world New York taxi data of around 400 million records are performed. Our results show that the MultiConvLSTM achieves the highest accuracy in both one-step and multiple-step predictions and it outperforms the existing methods for travel demand and OD flow predictions.
Distributed SECONDO: an extensible highly available and scalable database management system

This paper describes a novel method to couple a standalone database management system (DBMS) with a highly scalable key-value store. The system employs Apache Cassandra as data storage and the extensible DBMS Secondo as a query processing engine. The resulting system is highly scalable and can handle failing systems. All the data models and functions implemented in Secondo can be used in a scalable way without changing the implementation. Many aspects of the distribution are hidden from the user. Existing sequential queries can be easily converted into parallel ones.