bluuebunny/crossref_metadata_2025 huggingface dataset:
Fast Feature-Preserving Approach to Carpal Bone Surface Denoising
Authors: Salim Ibrahim , Hamza A. Ben
Published: July 2018

We present a geometric framework for surface denoising using graph signal processing, which is an emerging field that aims to develop new tools for processing and analyzing graph-structured data. The proposed approach is formulated as a constrained optimization problem whose objective function consists of a fidelity term specified by a noise model and a regularization term associated with prior data. Both terms are weighted by a normalized mesh Laplacian, which is defined in terms of a data-adaptive kernel similarity matrix in conjunction with matrix balancing. Minimizing the objective function reduces it to iteratively solve a sparse system of linear equations via the conjugate gradient method. Extensive experiments on noisy carpal bone surfaces demonstrate the effectiveness of our approach in comparison with existing methods. We perform both qualitative and quantitative comparisons using various evaluation metrics.
Estimation of Cough Peak Flow Using Cough Sounds
Authors: Umayahara Yasutaka , Soh Zu , Sekikawa Kiyokazu , Kawae Toshihiro , Otsuka Akira , Tsuji Toshio
Published: July 2018

Cough peak flow (CPF) is a measurement for evaluating the risk of cough dysfunction and can be measured using various devices, such as spirometers. However, complex device setup and the face mask required to be firmly attached to the mouth impose burdens on both patients and their caregivers. Therefore, this study develops a novel cough strength evaluation method using cough sounds. This paper presents an exponential model to estimate CPF from the cough peak sound pressure level (CPSL). We investigated the relationship between cough sounds and cough flows and the effects of a measurement condition of cough sound, microphone type and participant’s height and gender on CPF estimation accuracy. The results confirmed that the proposed model estimated CPF with a high accuracy. The absolute error between CPFs and estimated CPFs were significantly lower when the microphone distance from the participant’s mouth was within 30 cm than when the distance exceeded 30 cm. Analysis of the model parameters showed that the estimation accuracy was not affected by participant’s height or gender. These results indicate that the proposed model has the potential to improve the feasibility of measuring and assessing CPF.
Polymer Based Whispering Gallery Mode Humidity Sensor
Authors: Petermann Ann Britt , Hildebrandt Thomas , Morgner Uwe , Roth Bernhard Wilhelm , Meinhardt-Wollweber Merve
Published: July 2018

Whispering gallery mode (WGM) resonators are versatile high sensitivity sensors, but applications regularly suffer from elaborate and expensive manufacturing and read-out. We have realized a simple and inexpensive concept for an all-polymer WGM sensor. Here, we evaluate its performance for relative humidity measurements demonstrating a sensitivity of 47 pm/% RH. Our results show the sensor concepts’ promising potential for use in real-life applications and environments.
Self-Power Dynamic Sensor Based on Triboelectrification for Tilt of Direction and Angle
Authors: Roh Hyeonhee , Kim Inkyum , Yu Jinsoo , Kim Daewon
Published: July 2018

With the great development of the Internet of Things (IoT), the use of sensors have increased rapidly because of the importance in the connection between machines and people. A huge number of IoT sensors consume vast amounts of electrical power for stable operation and they are also used for a wide range of applications. Therefore, sensors need to operate independently, sustainably, and wirelessly to improve their capabilities. In this paper, we propose an orientation and the tilt triboelectric sensor (OT-TES) as a self-powered active sensor, which can simultaneously sense the tilting direction and angle by using the two classical principles of triboelectrification and electrostatic induction. The OT-TES device consists of a rectangular acrylic box containing polytetrafluoroethylene (PTFE) balls moved by gravity. The output voltage and current were 2 V and 20 nA, respectively, with a PTFE ball and Al electrode. The multi-channel system was adopted for measuring the degree and direction of tilt by integrating the results of measured electrical signals from the eight electrodes. This OT-TES can be attached on the equipment for drones or divers to measure their stability. As a result, this proposed device is expected to expand the field of TES, as a sensor for sky and the underwater.
Passive RFID-Based Inventory of Traffic Signs on Roads and Urban Environments
Authors: García Oya José Ramón , Martín Clemente Rubén , Hidalgo Fort Eduardo , González Carvajal Ramón , Muñoz Chavero Fernando
Published: July 2018

This paper presents a system with location functionalities for the inventory of traffic signs based on passive RFID technology. The proposed system simplifies the current video-based techniques, whose requirements regarding visibility are difficult to meet in some scenarios, such as dense urban areas. In addition, the system can be easily extended to consider any other street facilities, such as dumpsters or traffic lights. Furthermore, the system can perform the inventory process at night and at a vehicle’s usual speed, thus avoiding interfering with the normal traffic flow of the road. Moreover, the proposed system exploits the benefits of the passive RFID technologies over active RFID, which are typically employed on inventory and vehicular routing applications. Since the performance of passive RFID is not obvious for the required distance ranges on these in-motion scenarios, this paper, as its main contribution, addresses the problem in two different ways, on the one hand theoretically, presenting a radio wave propagation model at theoretical and simulation level for these scenarios; and on the other hand experimentally, comparing passive and active RFID alternatives regarding costs, power consumption, distance ranges, collision problems, and ease of reconfiguration. Finally, the performance of the proposed on-board system is experimentally validated, testing its capabilities for inventory purposes.
Supplemental Boosting and Cascaded ConvNet Based Transfer Learning Structure for Fast Traffic Sign Detection in Unknown Application Scenes
Authors: Liu Chunsheng , Li Shuang , Chang Faliang , Dong Wenhui
Published: July 2018

With rapid calculation speed and relatively high accuracy, the AdaBoost-based detection framework has been successfully applied in some real applications of machine vision-based intelligent systems. The main shortcoming of the AdaBoost-based detection framework is that the off-line trained detector cannot be transfer retrained to adapt to unknown application scenes. In this paper, a new transfer learning structure based on two novel methods of supplemental boosting and cascaded ConvNet is proposed to address this shortcoming. The supplemental boosting method is proposed to supplementally retrain an AdaBoost-based detector for the purpose of transferring a detector to adapt to unknown application scenes. The cascaded ConvNet is designed and attached to the end of the AdaBoost-based detector for improving the detection rate and collecting supplemental training samples. With the added supplemental training samples provided by the cascaded ConvNet, the AdaBoost-based detector can be retrained with the supplemental boosting method. The detector combined with the retrained boosted detector and cascaded ConvNet detector can achieve high accuracy and a short detection time. As a representative object detection problem in intelligent transportation systems, the traffic sign detection problem is chosen to show our method. Through experiments with the public datasets from different countries, we show that the proposed framework can quickly detect objects in unknown application scenes.
Determination of Optimal Heart Rate Variability Features Based on SVM-Recursive Feature Elimination for Cumulative Stress Monitoring Using ECG Sensor
Authors: Park Dajeong , Lee Miran , Park Sunghee E. , Seong Joon-Kyung , Youn Inchan
Published: July 2018

Routine stress monitoring in daily life can predict potentially serious health impacts. Effective stress monitoring in medical and healthcare fields is dependent upon accurate determination of stress-related features. In this study, we determined the optimal stress-related features for effective monitoring of cumulative stress. We first investigated the effects of short- and long-term stress on various heart rate variability (HRV) features using a rodent model. Subsequently, we determined an optimal HRV feature set using support vector machine-recursive feature elimination (SVM-RFE). Experimental results indicate that the HRV time domain features generally decrease under long-term stress, and the HRV frequency domain features have substantially significant differences under short-term stress. Further, an SVM classifier with a radial basis function kernel proved most accurate (93.11%) when using an optimal HRV feature set comprising the mean of R-R intervals (mRR), the standard deviation of R-R intervals (SDRR), and the coefficient of variance of R-R intervals (CVRR) as time domain features, and the normalized low frequency (nLF) and the normalized high frequency (nHF) as frequency domain features. Our findings indicate that the optimal HRV features identified in this study can effectively and efficiently detect stress. This knowledge facilitates development of in-facility and mobile healthcare system designs to support stress monitoring in daily life.
ED-FNN: A New Deep Learning Algorithm to Detect Percentage of the Gait Cycle for Powered Prostheses
Authors: Vu Huong Thi Thu , Gomez Felipe , Cherelle Pierre , Lefeber Dirk , Nowé Ann , Vanderborght Bram
Published: July 2018

Throughout the last decade, a whole new generation of powered transtibial prostheses and exoskeletons has been developed. However, these technologies are limited by a gait phase detection which controls the wearable device as a function of the activities of the wearer. Consequently, gait phase detection is considered to be of great importance, as achieving high detection accuracy will produce a more precise, stable, and safe rehabilitation device. In this paper, we propose a novel gait percent detection algorithm that can predict a full gait cycle discretised within a 1% interval. We called this algorithm an exponentially delayed fully connected neural network (ED-FNN). A dataset was obtained from seven healthy subjects that performed daily walking activities on the flat ground and a 15-degree slope. The signals were taken from only one inertial measurement unit (IMU) attached to the lower shank. The dataset was divided into training and validation datasets for every subject, and the mean square error (MSE) error between the model prediction and the real percentage of the gait was computed. An average MSE of 0.00522 was obtained for every subject in both training and validation sets, and an average MSE of 0.006 for the training set and 0.0116 for the validation set was obtained when combining all subjects’ signals together. Although our experiments were conducted in an offline setting, due to the forecasting capabilities of the ED-FNN, our system provides an opportunity to eliminate detection delays for real-time applications.
Watermarking Based on Compressive Sensing for Digital Speech Detection and Recovery †
Authors: Lu Wenhuan , Chen Zonglei , Li Ling , Cao Xiaochun , Wei Jianguo , Xiong Naixue , Li Jian , Dang Jianwu
Published: July 2018

In this paper, a novel imperceptible, fragile and blind watermark scheme is proposed for speech tampering detection and self-recovery. The embedded watermark data for content recovery is calculated from the original discrete cosine transform (DCT) coefficients of host speech. The watermark information is shared in a frames-group instead of stored in one frame. The scheme trades off between the data waste problem and the tampering coincidence problem. When a part of a watermarked speech signal is tampered with, one can accurately localize the tampered area, the watermark data in the area without any modification still can be extracted. Then, a compressive sensing technique is employed to retrieve the coefficients by exploiting the sparseness in the DCT domain. The smaller the tampered the area, the better quality of the recovered signal is. Experimental results show that the watermarked signal is imperceptible, and the recovered signal is intelligible for high tampering rates of up to 47.6%. A deep learning-based enhancement method is also proposed and implemented to increase the SNR of recovered speech signal.
Cooperative Dynamic Game-Based Optimal Power Control in Wireless Sensor Network Powered by RF Energy
Authors: Wang Manxi , Xu Haitao , Zhou Xianwei
Published: July 2018

This paper focuses on optimal power control in wireless sensor networks powered by RF energy, under the simultaneous wireless information and power transfer (SWIFT) protocol, where the information and power can be transmitted at the same time. We aim to maximize the utility for each sensor through the optimal power control, considering the influences of both the SINR and the harvested energy. The utility maximization problem is formulated as a cooperative dynamic game of a given time duration. All the sensors cooperate together to control their transmission power to maximize the utility and agree to act cooperatively so that a team optimum can be achieved. As a result, a feedback Nash equilibrium solution for each sensor is given based on the dynamic programming theory. Simulation results verify the effectiveness of the proposed approach, by comparing the grand coalition solutions with the non-cooperative solutions.
A Multi-Server Two-Factor Authentication Scheme with Un-Traceability Using Elliptic Curve Cryptography
Authors: Xu Guosheng , Qiu Shuming , Ahmad Haseeb , Xu Guoai , Guo Yanhui , Zhang Miao , Xu Hong
Published: July 2018

To provide secure communication, the authentication-and-key-agreement scheme plays a vital role in multi-server environments, Internet of Things (IoT), wireless sensor networks (WSNs), etc. This scheme enables users and servers to negotiate for a common session initiation key. Our proposal first analyzes Amin et al.’s authentication scheme based on RSA and proves that it cannot provide perfect forward secrecy and user un-traceability, and is susceptible to offline password guessing attack and key-compromise user impersonation attack. Secondly, we provide that Srinivas et al.’s multi-server authentication scheme is not secured against offline password guessing attack and key-compromise user impersonation attack, and is unable to ensure user un-traceability. To remedy such limitations and improve computational efficiency, we present a multi-server two-factor authentication scheme using elliptic curve cryptography (ECC). Subsequently, employing heuristic analysis and Burrows–Abadi–Needham logic (BAN-Logic) proof, it is proven that the presented scheme provides security against all known attacks, and in particular provides user un-traceability and perfect forward security. Finally, appropriate comparisons with prevalent works demonstrate the robustness and feasibility of the presented solution in multi-server environments.
A Flexible Capacitive Pressure Sensor Based on Ionic Liquid
Authors: Yang Xiaofeng , Wang Yishou , Qing Xinlin
Published: July 2018

A flexible microfluidic super-capacitive pressure sensor is developed to measure the surface pressure of a complex structure. The innovative sensor contains a filter paper filled with ionic liquid, and coated with two indium tin oxide polyethylene terephthalate (ITO-PET) films on the top and bottom, respectively. When external pressure is applied on the top ITO-PET film of the sensor mounted on the surface of an aircraft, the capacitance between the two ITO-PET films will change because of the deformation of the top ITO-PET film. The external pressure will be determined based on the change of the capacitance. Compared to the traditional pressure sensor, the developed sensor provides a high sensitivity of up to 178.5 nF/KPa and rapid dynamic responses for pressure measurement. Meanwhile, experiments are also conducted to study the influence of the thickness of the sensing film, sensing area, temperature, and humidity.
Intensity Demodulated Refractive Index Sensor Based on Front-Tapered Single-Mode-Multimode-Single-Mode Fiber Structure
Authors: Kang Jing , Yang Jiuru , Zhang Xudong , Liu Chunyu , Wang Lu
Published: July 2018

A novel intensity demodulated refractive index (RI) sensor is theoretically and experimentally demonstrated based on the front-tapered single-mode-multimode-single-mode (FT-SMS) fiber structure. The front taper is fabricated in a section of multimode fiber by flame-heated drawing technique. The intensity feature in the taper area is analyzed through the beam propagation method and the comprehensive tests are then conducted in terms of RI and temperature. The experimental results show that, in FT-SMS, the relative sensitivity is −342.815 dB/RIU in the range of 1.33~1.37. The corresponding resolution reaches 2.92 × 10−5 RIU, which is more than four times higher than that in wavelength demodulation. The temperature sensitivity is 0.307 dB/°C and the measurement error from cross-sensitivity is less than 2 × 10−4. In addition, fabricated RI sensor presents high stability in terms of wavelength (±0.045 nm) and intensity (±0.386 dB) within 2 h of continuous operation.
Detection of Broken Strands of Transmission Line Conductors Using Fiber Bragg Grating Sensors
Authors: Zhao Long , Huang Xinbo , Jia Jianyuan , Zhu Yongcan , Cao Wen
Published: July 2018

Transmission lines are affected by Aeolian vibration, which causes strands to break and eventually causes an entire line to break. In this paper, a method for monitoring strand breaking based on modal identification is proposed. First, the natural frequency variation of a conductor caused by strand breakage is analyzed, and a modal experiment of the LGJ-95/15 conductor is conducted. The measurement results show that the natural frequencies of the conductor decrease with an increasing number of broken strands. Next, a monitoring system incorporating a fiber Bragg grating (FBG)-based accelerometer is designed in detail. The FBG sensor is mounted on the conductor to measure the vibration signal. A wind speed sensor is used to measure the wind speed signal and is installed on the tower. An analyzer is also installed on the tower to calculate the natural frequencies, and the data are sent to the monitoring center via 3G. Finally, a monitoring system is tested on a 110 kV experimental transmission line, and the short-time Fourier transform (STFT) method and stochastic subspace identification (SSI) method are used to identify the natural frequencies of the conductor vibration. The experimental results show that SSI analysis provides a higher precision than does STFT and can extract the natural frequency under various wind speeds as an effective basis for discriminating between broken strands.
A Fluorescent Biosensors for Detection Vital Body Fluids’ Agents
Authors: Nawrot Witold , Drzozga Kamila , Baluta Sylwia , Cabaj Joanna , Malecha Karol
Published: July 2018

The clinical applications of sensing tools (i.e., biosensors) for the monitoring of physiologically important analytes are very common. Nowadays, the biosensors are being increasingly used to detect physiologically important analytes in real biological samples (i.e., blood, plasma, urine, and saliva). This review focuses on biosensors that can be applied to continuous, time-resolved measurements with fluorescence. The material presents the fluorescent biosensors for the detection of neurotransmitters, hormones, and other human metabolites as glucose, lactate or uric acid. The construction of microfluidic devices based on fluorescence uses a variety of materials, fluorescent dyes, types of detectors, excitation sources, optical filters, and geometrical systems. Due to their small size, these devices can perform a full analysis. Microfluidics-based technologies have shown promising applications in several of the main laboratory techniques, including blood chemistries, immunoassays, nucleic-acid amplification tests. Of the all technologies that are used to manufacture microfluidic systems, the LTCC technique seems to be an interesting alternative. It allows easy integration of electronic and microfluidic components on a single ceramic substrate. Moreover, the LTCC material is biologically and chemically inert, and is resistant to high temperature and pressure. The combination of all these features makes the LTCC technology particularly useful for implementation of fluorescence-based detection in the ceramic microfluidic systems.
Adaptive Windowing Framework for Surface Electromyogram-Based Pattern Recognition System for Transradial Amputees
Authors: Al-Timemy Ali H. , Bugmann Guido , Escudero Javier
Published: July 2018

Electromyogram (EMG)-based Pattern Recognition (PR) systems for upper-limb prosthesis control provide promising ways to enable an intuitive control of the prostheses with multiple degrees of freedom and fast reaction times. However, the lack of robustness of the PR systems may limit their usability. In this paper, a novel adaptive time windowing framework is proposed to enhance the performance of the PR systems by focusing on their windowing and classification steps. The proposed framework estimates the output probabilities of each class and outputs a movement only if a decision with a probability above a certain threshold is achieved. Otherwise (i.e., all probability values are below the threshold), the window size of the EMG signal increases. We demonstrate our framework utilizing EMG datasets collected from nine transradial amputees who performed nine movement classes with Time Domain Power Spectral Descriptors (TD-PSD), Wavelet and Time Domain (TD) feature extraction (FE) methods and a Linear Discriminant Analysis (LDA) classifier. Nonetheless, the concept can be applied to other types of features and classifiers. In addition, the proposed framework is validated with different movement and EMG channel combinations. The results indicate that the proposed framework works well with different FE methods and movement/channel combinations with classification error rates of approximately 13% with TD-PSD FE. Thus, we expect our proposed framework to be a straightforward, yet important, step towards the improvement of the control methods for upper-limb prostheses.
Channel Characteristic Aware Privacy Protection Mechanism in WBAN
Authors: Zhang Puning , Ma Jie
Published: July 2018

Advances of information and communication technologies in medical areas have led to the emergence of wireless body area network (WBAN). The high accessibility of media in WBAN can easily lead to the malicious tapping or tampering attacks, which may steal privacy data or inject wrong data. However, existing privacy protection mechanisms in WBAN depend on the third-party key management system and have a complex key exchange process. To enhance user privacy at a low cost and with high flexibility, a channel characteristic aware privacy protection mechanism is proposed for WBAN. In the proposed mechanism, the similarity of RSS is measured to authenticate nodes. The key extraction technique can reduce the cost of the key distribution process. Due to the half duplex communication mode of sensors, the biased random sequences are extracted from the RSS of sensor nodes and coordinator. To reduce the inconsistency, we propose the n-dimension quantification and fuzzy extraction, which can quickly encrypt the transmission information and effectively identify malicious nodes. Simulation results show that the proposed mechanism can effectively protect user privacy against tampering and eavesdropping attacks.
Active Potentiometry for Dissolved Oxygen Monitoring with Platinum Electrodes
Authors: Zimmermann Peter , Weltin Andreas , Urban Gerald A. , Kieninger Jochen
Published: July 2018

Potentiometric oxygen monitoring using platinum as the electrode material was enabled by the combination of conventional potentiometry with active prepolarization protocols, what we call active potentiometry. The obtained logarithmic transfer function is well-suited for the measurement of dissolved oxygen in biomedical applications, as the physiological oxygen concentration typically varies over several decades. We describe the application of active potentiometry in phosphate buffered salt solution at different pH and ion strength. Sensitivity was in the range of 60 mV/dec oxygen concentration; the transfer function deviated from logarithmic behavior for smaller oxygen concentration and higher ion strength of the electrolyte. Long-term stability was demonstrated for 60 h. Based on these measurement results and additional cyclic voltammetry investigations a model is discussed to explain the potential forming mechanism. The described method of active potentiometry is applicable to many different potentiometric sensors possibly enhancing sensitivity or selectivity for a specific parameter.
Fast Visual Tracking Based on Convolutional Networks
Authors: Huang Ren-Jie , Tsao Chun-Yu , Kuo Yi-Pin , Lai Yi-Chung , Liu Chi Chung , Tu Zhe-Wei , Wang Jung-Hua , Chang Chung-Cheng
Published: July 2018

Recently, an upsurge of deep learning has provided a new direction for the field of computer vision and visual tracking. However, expensive offline training time and the large number of images required by deep learning have greatly hindered progress. This paper aims to further improve the computational performance of CNT which is reported to deliver 5 fps performance in visual tracking, we propose a method called Fast-CNT which differs from CNT in three aspects: firstly, an adaptive k value (rather than a constant 100) is determined for an input video; secondly, background filters used in CNT are omitted in this work to save computation time without affecting performance; thirdly, SURF feature points are used in conjunction with the particle filter to address the drift problem in CNT. Extensive experimental results on land and undersea video sequences show that Fast-CNT outperforms CNT by 2~10 times in terms of computational efficiency.
Adaptive Robust Unscented Kalman Filter via Fading Factor and Maximum Correntropy Criterion
Authors: Deng Zhihong , Yin Lijian , Huo Baoyu , Xia Yuanqing
Published: July 2018

In most practical applications, the tracking process needs to update the data constantly. However, outliers may occur frequently in the process of sensors’ data collection and sending, which affects the performance of the system state estimate. In order to suppress the impact of observation outliers in the process of target tracking, a novel filtering algorithm, namely a robust adaptive unscented Kalman filter, is proposed. The cost function of the proposed filtering algorithm is derived based on fading factor and maximum correntropy criterion. In this paper, the derivations of cost function and fading factor are given in detail, which enables the proposed algorithm to be robust. Finally, the simulation results show that the presented algorithm has good performance, and it improves the robustness of a general unscented Kalman filter and solves the problem of outliers in system.
Intelligent Multimodal Framework for Human Assistive Robotics Based on Computer Vision Algorithms
Authors: Ivorra Eugenio , Ortega Mario , Catalán José M. , Ezquerro Santiago , Lledó Luis Daniel , Garcia-Aracil Nicolás , Alcañiz Mariano
Published: July 2018

Assistive technologies help all persons with disabilities to improve their accessibility in all aspects of their life. The AIDE European project contributes to the improvement of current assistive technologies by developing and testing a modular and adaptive multimodal interface customizable to the individual needs of people with disabilities. This paper describes the computer vision algorithms part of the multimodal interface developed inside the AIDE European project. The main contribution of this computer vision part is the integration with the robotic system and with the other sensory systems (electrooculography (EOG) and electroencephalography (EEG)). The technical achievements solved herein are the algorithm for the selection of objects using the gaze, and especially the state-of-the-art algorithm for the efficient detection and pose estimation of textureless objects. These algorithms were tested in real conditions, and were thoroughly evaluated both qualitatively and quantitatively. The experimental results of the object selection algorithm were excellent (object selection over 90%) in less than 12 s. The detection and pose estimation algorithms evaluated using the LINEMOD database were similar to the state-of-the-art method, and were the most computationally efficient.
Training Models and Practices in Sociology
Authors: Serpa Sandro , Ferreira Carlos Miguel
Published: July 2018

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Adapted Utilitarian Judo: The Adaptation of a Traditional Martial Art as a Program for the Improvement of the Quality of Life in Older Adult Populations
Authors: DelCastillo-Andrés Óscar , Toronjo-Hornillo Luis , Toronjo-Urquiza María Teresa , Cachón Zagalaz Javier , Campos-Mesa María del Carmen
Published: July 2018

This article reports on the Adapted Utilitarian Judo project. The use of the foundations and technical elements of traditional Judo, adapted and contextualised to the requirements of the older adult population, orienting the activity toward the field of health and the improvement of the quality of life of the older adult. Its mission is to facilitate maintaining and improving the functionality and autonomy of this population, with respect to the performance of the basic and instrumental activities of daily life. At the same it seeks to achieve this while maintaining the essence of the values that are inherent to the practice of Judo as a traditional martial art. It is argued that Judo, once adapted to focus on a utilitarian function, not only allows to actively influence aspects such as maintaining the physical qualities of the elderly but also fosters other key elements for active and healthy ageing by participating in an ongoing group activity, such as socialisation and self-esteem. More specifically, the paper presents how adapted Judo represents an innovation in the treatment of a risk factor associated with aging: the active prevention of falls. We conclude that Adapted Utilitarian Judo (JUA) is both a timely and relevant as a social and educational tool of great value, responds to propos called for by the international scientific community for programs aimed at improving the health and quality of life of the older adult population, especially in Europe, that is ageing at a fast pace.
The Determinants and Outcomes of Absence Behavior: A Systematic Literature Review
Authors: Čikeš Vedrana , Maškarin Ribarić Helga , Črnjar Kristina
Published: July 2018

This research aims to identify and analyze the frequency of the researched determinants and outcomes of absenteeism and thus create an extensive pool of knowledge that can be used for further research. A systematic review, based on Tranfield, Denyer, and Smart’s guidelines of 2003, was used. An electronic search of the Scopus database led to the inclusion of 388 peer-reviewed research articles. Finally, 100 top-quality articles were analyzed using content analysis. This article provides several starting points for practitioners and researchers when investigating absenteeism and its potential determinants and outcomes. It also shows that there is an evident imbalance between empirical research dealing with determinants and research dealing with absenteeism outcomes. Employee attitudes stand out among the most repetitive absenteeism causes, while turnover, organizational health, and loss of productivity are some of the most researched absenteeism outcomes. Most research takes place in the manufacturing industries, followed by hospitals and other public service organizations, banks, and insurance companies. This systematic literature review is the first known attempt of this kind of review of the causes and consequences of absence behavior. It covers a wide range of literature published from 1969 until today and includes more than 150 different absenteeism determinants and outcomes.
Validity of Session Rating Perceived Exertion Method for Quantifying Internal Training Load during High-Intensity Functional Training
Authors: Tibana Ramires , De Sousa Nuno , Cunha Gabriel , Prestes Jonato , Fett Carlos , Gabbett Tim , Voltarelli Fabrício
Published: July 2018

The aim of this study was to validate the quantification of internal training load (session rating perceived exertion, sRPE) and the effect of recall timing of sRPE during high-intensity functional training (HIFT) sessions. Thirteen male HIFT practitioners (age 27.2 ± 33 years, height 177.1 ± 4.0 cm, body mass 81.1 ± 9.0 kg) were monitored during two common HIFT training sessions: Fight Gone Bad (FGB) and Fran. The Edwards summated heart-rate-zone method was used as a reference measure of internal training load. The session-RPE rating was obtained using the CR-10 scale modified by Foster. The training load calculated by the Edwards-TRIMP index was significantly higher (p < 0.05) during the FGB (77.7 ± 4.9) than the Fran (19.8 ± 8.4) workout. There was a strong correlation (p < 0.05) between the Edwards-TRIMP index and the training load calculated by the sRPE in all time frames (0, 10, 20, and 30 min post-exercise). The RPE and sRPE measured at 30 min post-exercise time frame was significant lower than 0, 10, and 20 min post-exercise for both workouts. The session-RPE method is an easy and valid tool to evaluate internal training load for high intensity functional training practitioners.
Smart Villages: Comprehensive Review of Initiatives and Practices
Authors: Zavratnik Veronika , Kos Andrej , Stojmenova Duh Emilija
Published: July 2018

Over recent decades, people’s (rural and urban) communities are facing numerous social and economic changes and challenges. Some of those challenges have been increasingly addressed through the lenses of technological developments and digitalization. In this paper, we have made a review of already existing practices while focusing on the existing implementations of the Smart Village concept and the importance of digital transformation for rural areas. We give special attention to EU policies that we are using as an already existing framework for understanding our own forthcoming examples. We have shown the parallels between the findings and insights from different regions and made an evaluation of presented practices. Our main argument stems from our own previous experiences and experiences of other research approaches, and is grounded on the argument that rural areas are not uniform, and that smart rural development has to be applied in combination with place-based approach. We present the cases of Slovenian pilot practices and support our argument by proposing the FabVillage concept.
Agro-Forest Management and Soil Degradation in Mediterranean Environments: Towards a Strategy for Sustainable Land Use in Vineyard and Olive Cropland
Authors: Marchi Maurizio , Ferrara Carlotta , Biasi Rita , Salvia Rosanna , Salvati Luca
Published: July 2018

Landscape fragmentation typical of the Mediterranean region is the result of long-term settlement history and continuous socioeconomic interactions among countries. In complex agro-ecosystems of the Mediterranean basin, formulation of practical guidelines aimed at counteract soil and land degradation, water depletion, rural area depopulation, and the loss of agricultural knowledge is imperative. Based on a multidisciplinary, integrated approach, the present contribution discusses the role of traditional agricultural systems in ecosystem services provision, considering together economic sustainability and the medium-term ecological benefits. A permanent monitoring of rural areas specialized in traditional crop production such as olive and vine may support optimal selection of cultivars finely adapted to a warm climate. A competitive agricultural system may consider human well-being, social equity, and conservation of natural resources, to ensure a high level of services for current and future generations. Recovery and conservation of agricultural resources provide positive externalities and social benefits at both local and regional levels. Understanding the multiple use and functions of tree crop landscapes will contribute to improve food security, land quality, and the provision of related ecosystem services.
Transforming Cape Vert Informal Settlements
Authors: Amado Miguel , Poggi Francesca , Martins Adriana , Vieira Nuno , Amado Antonio Ribeiro
Published: July 2018

The lack of land ownership databases in developing countries has influenced inhabitants of these countries to occupy public lands. This situation has resulted in areas of informal housing, commerce, and agriculture, ultimately creating new informal settlements, which are becoming a serious problem in developing countries. These informal settlements contain inhabitants settled on public land without any infrastructure and against the landowner’s wishes. This process results in uncontrolled land occupation that promotes new informal areas without any proper urban utilities, positioned in risky areas, where the minimum requirements for healthy living are not being met. In some cases, this incentivizes an informal economy. Building a cadastral map in informal settlement areas is fundamental to supporting the future transformation of illegal areas, and in regulating the occupation of new subdivisions and new expansion areas. In this paper, we present a methodology developed to support the management of informal settlement areas. The method we used has the potential for replication so that it can be adapted to multiple types of informal settlements, as can the model used to register the land tenure. The model was developed using a series of qualitative and quantitative data that determine the identification and classification of buildings, along with a physical and functional description. A Geographic Information System, an initial survey of existing land titles of possession, and public proposals to develop new expansion areas were used to develop the model. A case study is presented where the land management model was implemented in Chã da Caldeiras in Ilha do Fogo, which is an informal settlement in Cape Verde. The proposal created using the results was accepted by the population and local authorities.
A Global Expected Risk Analysis of Fatalities, Injuries, and Damages by Natural Disasters
Authors: Shen Guoqiang , Zhou Long , Wu Yao , Cai Zhiming
Published: July 2018

Natural disasters are hazardous geophysical, meteorological, hydrological, climatological, and/or biological events that disturb human and natural environments, causing injuries, casualties, property damages, and business interruptions. Sound analysis is required regarding the effective hazard preparedness for, response to, mitigation of, and recovery from natural disasters. This research proposes an expected risk analysis model of world natural disasters recorded for 1900–2015 in the Emergency Disaster Database compiled by the Centre for Research on the Epidemiology of Disaster. The model produces consistent estimates of country-level risks in terms of human casualty and economic loss. The expected risks, along with their standard deviations, and ranks for world 208 countries, are analyzed with highlights for the top 10, 20 and 30 countries. Normalized expected risks by country population density and per capita gross domestic product (GDP) are also analyzed to further understand the relationships between risks and socio-economic measures. The results show that the model is a reasonably effective alternative to the existing risk analysis methods, based on the high correlations between the observed and estimated total risks. While riskier countries with higher expected risks and standard deviations are found in all continents, some developing countries such as China, India, Bangladesh, and Brazil, or developed countries, such as the United States, Japan, and Germany, are the hot-spots of global natural disasters. The model can be used as a new alternative approach to conduct country-level risk assessments or risk analyses of fatality, injured, affected, and damage—especially for countries’ governments to make sound disaster preparation, and mitigation decisions, sustainable policies, or plans regarding natural disasters.
Characterizing the Influences of Economic Development, Energy Consumption, Urbanization, Industrialization, and Vehicles Amount on PM2.5 Concentrations of China
Authors: Zhao Haoran , Guo Sen , Zhao Huiru
Published: July 2018

The speeding-up of economic development and industrialization processes in China have brought about serious atmospheric pollution issues, especially in terms of particulate matter harmful to health. However, impact mechanisms of socio-economic forces on PM2.5 (the particle matter with diameter less than 2.5 μm) have rarely been further investigated. This paper selected GDP (gross domestic product) per capita, energy consumption, urbanization process, industrialization structure, and the amount of possession of civil vehicles as the significant factors, and researched the relationship between these factors and PM2.5 concentrations from 1998 to 2016, employing auto-regressive distributed lag (ARDL) methodology and environmental Kuznets curve (EKC) theory. Empirical results illustrated that a long-term equilibrium nexus exists among these variables. Granger causality results indicate that bi-directional causality exist between PM2.5 concentrations and GDP per capita, the squared component of GDP per capita, energy consumption and urbanization process. An inverse U-shape nexus exists between PM2.5 concentrations and GDP per capita. When the real GDP per capita reaches 5942.44 dollars, PM2.5 concentrations achieve the peak. Results indicate that Chinese governments should explore a novel pathway to resolve the close relationship between socio-economic factors and PM2.5, such as accelerating the adjustment of economic development mode, converting the critical industrial development driving forces, and adjusting the economic structure.
A Periodic Caching Strategy Solution for the Smart City in Information-Centric Internet of Things
Authors: Naeem Muhammad Ali , Ali Rashid , Kim Byung-Seo , Nor Shahrudin Awang , Hassan Suhaidi
Published: July 2018

Named Data Networking is an evolving network model of the Information-centric networking (ICN) paradigm which provides Named-based data contents. In-network caching is the responsible for dissemination of these contents in a scalable and cost-efficient way. Due to the rapid expansion of Internet of Things (IoT) traffic, ICN is envisioned to be an appropriate architecture to maintain the IoT networks. In fact, ICN offers unique naming, multicast communications and, most beneficially, in-network caching that minimizes the response latency and server load. IoT environment involves a study of ICN caching policies in terms of content placement strategies. This paper addressed the caching strategies with the aim to recognize which caching strategy is the most suitable for IoT networks. Simulation results show the impact of different IoT ICN-based caching strategies, out of these; periodic caching is the most appropriate strategy for IoT environments in terms of stretch that results in decreasing the retrieval latency and improves the cache-hit ratio.
Conserving Tropical Forests: Can Sustainable Livelihoods Outperform Artisanal or Informal Mining?
Authors: Fisher Joshua , Arora Poonam , Rhee Sophia
Published: July 2018

The viability of conservation efforts, including protected areas and buffer zones, depends on finding ways to make those strategies more attractive and viable for local populations. This paper presents a pilot study utilizing a rapid rural appraisal of livelihoods in the buffer zone of Tambopata National Reserve in Madre de Dios, Peru, threatened by illegal gold mining and logging. We evaluated three predominant economic activities—artisanal gold mining, Brazil nut harvesting, and fish farming—in terms of potential economic returns. The main research question we ask is whether the latter two potentially sustainable land uses can match or exceed the returns from mining. Contrary to popular belief, we find that enhancing value creation at product origin could make existing forest-friendly livelihoods as or more lucrative than extractive ones. This has implications on local conservation policy encouraging implementable strategies incentivizing sustainable livelihoods in tandem with, and in support of, conservation goals.
Identifying Economic Growth Convergence Clubs and Their Influencing Factors in China
Authors: Li Feng , Li Guangdong , Qin Weishan , Qin Jing , Ma Haitao
Published: July 2018

Balanced and coordinated economic development across regions is a critical goal of regional economic development and new-type urbanization in China. However, few studies have examined economic growth convergence clubs at the county level. To extend the research on convergence clubs, this research applies a log t convergence test and a dynamic spatial ordered probit model (DSOP) to endogenously identify economic growth convergence clubs in counties and to examine the influence of initial states and structures on club convergence probability. The study sample covers 2286 counties of China from 1992 to 2010. The results show significant convergence club patterns at the county levels, resulting in the gradual formation of six convergence clubs. The DSOP estimation results show that per capita fixed assets, population density, and industrialization have promoted convergence club formation to varying degrees.
Laboratory Evaluation of Hot Asphalt Concrete Properties with Cuban Recycled Concrete Aggregates
Authors: Acosta Alvarez Debora , Alonso Aenlle Anadelys , Tenza-Abril Antonio José
Published: July 2018

Recycled Aggregates (RA) from construction and demolition waste (CDW) are a technically viable alternative to manufacture of asphalt concrete (AC). The main objective of this work is to evaluate the properties of hot asphalt mixtures that have been manufactured with different sources of CDW (material from concrete test specimens, material from the demolition of sidewalks and waste from prefabrication plants) from Cuba. Dense asphalt mixtures were manufactured with a maximum aggregate size of 19 mm, partially replacing (40%) the natural aggregate fraction measured between 5 mm and 10 mm with three types of RA from Cuba. Marshall specimens were manufactured to determine the main properties of the AC in terms of density, voids, stability and deformation. Additionally, the stiffness modulus of the AC was evaluated at 7 °C, 25 °C and 50 °C. The results corroborate the potential for using these sources of CDW from Cuba as a RA in asphalt concrete, thereby contributing an important environmental and economic benefit.