A High-Performance Vehicle Detection Algorithm for Wireless Sensor Parking Systems

Cardiorespiratory or aerobic exercise immediately after practice of an upper-extremity motor skill task can facilitate skill consolidation, as demonstrated by enhanced performances at 24 h and 7-day retention tests. The purpose of this study was to examine the effect of acute cardiorespiratory exercise on motor skill consolidation when skill practice involved low and high levels of contextual interference introduced through repetitive and interleaved practice schedules, respectively. Forty-eight young healthy adults were allocated to one of four groups who performed either repetitive or interleaved practice of a pinch grip motor sequence task, followed by either a period of seated rest or a bout of high-intensity interval cycling. At pre- and post-practice and 24 h and 7-day retention tests, we assessed motor skill performance and β-band (15–35 Hz) intermuscular coherence using surface electromyography (EMG) collected from the abductor pollicis brevis and first dorsal interosseous. At the 7-day retention test, off-line consolidation was enhanced in the cardiorespiratory exercise relative to the rest group, but only among individuals who performed interleaved motor skill practice (p = 0.02). Similarly, at the 7-day retention test, β-band intermuscular coherence increased to a greater extent in the exercise group than in the rest group for those who performed interleaved practice (p = 0.02). Under the present experimental conditions, cardiorespiratory exercise preferentially supported motor skill consolidation and change in intermuscular coherence when motor skill practice involved higher rather than lower levels of contextual interference.

Selectively retrieving episodic information from a cue often induces interference from related episodes. To promote successful retrieval of the target episode, such interference is resolved by inhibition, causing retrieval-induced forgetting of the related but irrelevant information. Passively studying the episodic information again (reexposure) does not show this effect. This study examined the hypothesis that brain oscillations in the theta band (5-9 Hz) reflect the dynamics of interference in selective memory retrieval, analyzing EEG data from 24 healthy human subjects (21 women, 3 men). High versus low levels of interference were investigated by comparing the effects of selective retrieval with the effects of reexposure of material, with the former, but not the latter, inducing interference. Moreover, we analyzed repeated cycles of selective retrieval and reexposure, assuming that interference is reduced by inhibition across retrieval cycles, but not across reexposure cycles. We found greater theta band activity in selective retrieval than in reexposure, and a reduction in theta amplitude from the first to the second cycle of retrieval predicting the amount of retrieval-induced forgetting; the sources of theta amplitude reduction across retrieval cycles were located in the anterior cingulate cortex. No difference in theta activity was found across repeated cycles of reexposure. The results suggest that higher levels of interference in episodic memory are indexed by more theta band activity, and that successful interference resolution via inhibition causes a reduction in theta amplitude. Thus, theta band activity can serve as a neural marker of the dynamics of interference in selective episodic retrieval.

A wireless pressure sensor node design method and realization is put forward aiming at problems of dynamic pressure test in the hermetic cavity or cabin, such as high wiring difficulty and influence on air flow field. Dynamic gauge pressure signal is transmitted by a wireless sensor node in consideration of temperature affection factors. The sensor node is mainly composed of gauge and atmospheric pressure, temperature sensor, signal acquisition and modulation module, wireless RF module, data memory, lithium battery. On the basis of the above, the prototype is developed. The effectiveness and reliability of the wireless pressure sensor node are verified in means of sea trial test.

Fatigue is one of the most prevalent and significant symptoms experienced by breast cancer patients. This study aimed to investigate potential population heterogeneity in fatigue symptoms of the patients using the innovative non-normal mixture modeling. A sample of 197 breast cancer patients completed the brief fatigue inventory and other measures on cancer symptoms. Non-normal factor mixture models were analyzed and compared using the normal, t, skew-normal, and skew-t distributions. Selection of the number of latent classes was based on the Bayesian information criterion (BIC). The identified classes were validated by comparing their demographic profiles, clinical characteristics, and cancer symptoms using a stepwise distal outcome approach. The observed fatigue items displayed slight skewness but evident negative kurtosis. Factor mixture models using the normal distribution pointed to a 3-class solution. The t distribution mixture models showed the lowest BIC for the 2-class model. The restored class (52.5 %) exhibited moderate severity (item mean = 2.8-3.2) and low interference (item mean = 1.1-1.9). The exhausted class (47.5 %) displayed high levels of fatigue severity and interference (item mean = 5.8-6.6). Compared to the restored class, the exhausted class reported significantly higher perceived stress, anxiety, depression, pain, sleep disturbance, and lower quality of life. The non-normal factor mixture models suggest two distinct subgroups of patients on their fatigue symptoms. The presence of the exhausted class with exacerbated symptoms calls for a proactive assessment of the symptoms and development of tailored interventions for this subgroup.

Giving Birth and Returning to Work: The Impact of Work–Family Conflict on Women's Health After Childbirth

Channel assignment is an efficient method to increase the network capacity of multi-radio mesh networks by using orthogonal channels for otherwise interfering transmissions in the network. With the massive increase of commercial and personal WLAN deployments in urban areas, co-located networks may cause a performance degradation if operated on the same wireless channels. Thus, in order to fully exploit the benefits of spectral diversity, channel assignment needs to become aware of external interference. In this paper, we propose EICA, a distributed algorithm for external interference-aware channel assignment. We show how EICA is capable to detect co-located sources of interference with spectrum sensing using commodity IEEE 802.11 radios of the network nodes. Thus, no additional hardware is required. Based on the channel conditions, the algorithm favors the lesser congested channels for the channel assignment. We evaluate EICA in a large-scale testbed with 126 multi-radio network nodes in different scenarios with increasing levels of interference. The testbed study shows that EICA can significantly increase the network capacity in scenarios with high levels of external interference.

Present-day digital data transmission systems should provide a high accuracy for information transmission, maintaining, at the same time, the maximal rate. The systems that apply spectral-effective signal modulation methods enabling to reasonably use the selected section of the frequency spectrum. The orthogonal frequency-division multiplexing (OFDM) is among spectral-effective. This kind of modulation uses its own signal constellation at each subcarrier when transmitting information. The system noise immunity generally depends on the signal point arrangement of a signal constellation. At low noise and interference levels, the signal point arrangement increases, which leads to an increase in the information rate. As the noise and interference level increases, the signal point arrangement decreases, which leads to the transmission rate decrease. In the digital information transmission systems, particularly interesting are asymmetric signal constellations, applying which enable generally improve the system operation quality. Therefore, studying signal constellations is a vital problem nowadays. In this paper, we address the structure and the operation principle of a generator for signal constellations, implemented in the NI LabVIEW software. Using such a generator enables to create signal constellations with an extended configuration, which provides a possibility to investigate the system noise immunity by applying symmetric and asymmetric diagrams (maps).

This paper proposes a generalized model and methods for fast-convolution (FC)-based waveform generation and processing with specific applications to fifth generation new radio (5G-NR). Following the progress of 5G-NR standardization in 3rd generation partnership project (3GPP), the main focus is on subband-filtered cyclic prefix (CP) orthogonal frequency-division multiplexing (OFDM) processing with specific emphasis on spectrally well localized transmitter processing. Subband filtering is able to suppress the interference leakage between adjacent subbands, thus supporting different numerologies for so-called bandwidth parts as well as asynchronous multiple access. The proposed generalized FC scheme effectively combines overlapped block processing with time- and frequency-domain windowing to provide highly selective subband filtering with very low intrinsic interference level. Jointly optimized multi-window designs with different allocation sizes and design parameters are compared in terms of interference levels and implementation complexity. The proposed methods are shown to clearly outperform the existing state-of-the-art windowing and filtering-based methods.

Proposed wireless sensor node is a highly flexible and programmable system on chip (PSoC) architecture along with integrated RF radio chip, which can be adapted to any IEEE 802.15.4 standard based protocol, working at the band of 2.4GHz.This can be accompanied by the RF antenna matched with the interface circuit for various kinds of sensors and peripherals to form a wireless sensor node.This can be very well used to form a wireless sensor network in different domains.This proposed methodology can be used for specific application for improving the WSN stability and performance.This article will mainly present the design of wireless sensor nodes based on PSoC and CyFi radio chip, including the application specific antenna and hardware design for the system on chip for the sensor node and the simple introduction of the application domain.The proposed nodes are used with a special antenna and application based protocol for communication.This design has a better power handling and performing capacity.Further, we have implemented this for the wireless sensor node as well.

The efficiency of transportation system depends on many factors, such as traffic congestion, vehicle accidents and road conditions. To improve the reliability, productivity and safety of the system, many researchers propose to use a wireless sensor network (WSN) as a solution. A WSN usually consists of many tiny sensor nodes for sensing, data processing and communication. In this study, we present the development of a small-sized, low-power and lightweight wireless sensor node. It is equipped with a 3-axes accelerometer, an altimeter sensor, humidity sensor, temperature sensor, 315 MHz RF transceiver module and a typical coin-sized lithium battery (3.0 V, 220 mAh). The entire sensor node fits within a 28 × 20 × 8 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> volume and is only 7 grams (not including the antenna). An 8-bit MCU is included in the RF transceiver module to control sensor node operation. It collects and transmits sensors data in real time to the RF repeater with bit rate 24 kbps. During continuous operation, the sensor node consumes less than 3 mA current. Thus for a 220 mAh battery, the wireless sensor node can continue operating for more than 75 hours.

Over the last few years, IoT devices have multiplied their number and functionality. These devices are located all over the world and batteries are their main source of energy. In this paper the usage of wireless LoRaWAN sensor node in smart Internet of Things applications was analyzed. The study focuses on the reduction of power consumption from wireless LoRaWAN sensor nodes. An analysis of the energy consumption of the various components of the architecture of the wireless sensor nodes is performed. An energy model of the energy consumed by the sensor nodes is presented and analyzed. The result of the analysis provides an accurate identification of the main energy consumers, the magnitude of their consumption and an in-depth understanding of the key mechanisms that need to be applied to improve energy efficiency in wireless sensor nodes. The emphasis is on the presented energy efficient protocol. Three action scenarios from the sensor nodes are presented, outlining the main guidelines and strategies for improving the efficiency of the wireless nodes. In addition, the research results reveal the magnitude of energy savings that can be achieved by implementing the improved duty cycle mechanisms in wireless sensor nodes.

A multi-Mobile Agent and optimal itinerary planning-based data aggregation in Wireless Sensor Networks

Wireless sensor node is an autonomous and compact device that has capability to monitor a variety of real-world phenomena. It is designed composed of sensing device, embedded processor, communication module, and power equipment. Wireless sensor node is part of wireless sensor network where hundred or thousand sensor node can be deployed. Over the past decade Wireless Sensor Networks (WSNs) have emerged as one of the computing platforms of note within the electronics community. In prediction, there will be more than 127 million wireless sensor nodes deployed worldwide by 2014. We have surveyed 100 currently available wireless sensor network node platforms have been developed and produced not only by the research institutions, the universities but also some companies in last ten years. In this paper, we present a review of 27 different wireless sensor node platforms. We review these devices under a number of different parameters, and we highlight the key advantages of each node platform according to dimension and power consumption. We also discuss the characteristics and trend of development and deployment a wireless sensor node technology.

In order to solve the problems that ever wireless sensor nodes' energy consumption is high and solar-powered wireless nodes are greatly influenced by the weather and the system is not stable, comprehensive utilization of solar energy power supply technology, sensor technology and wireless communication technology, this paper designs a new type of wireless sensor nodes, which is powered by solar energy. The wireless sensor nodes which is supplied by solar energy, solving the problem of the energy consumption of sensor nodes effectively. After tested, it has simple operation, high reliability and it can satisfy the requirement of environmental parameter acquisition and monitoring work.

Pervasive computing is an environment consisting set of sensor nodes with the characteristics of perception, computation and communication capabilities. Wireless sensor nodes are deployed in various pervasive computing applications to observe the happenings in the surroundings. Data gathered from such wireless sensor nodes are utilized for critical decision making in context-aware environment. The Frequent incorrect data sampling, missing values, untrustworthy data, misbehavior and selfishness of nodes are common in pervasive applications since they are deployed in unfriendly and harsh environment. Moreover, the increasing number of sensor node fabricator leads to interoperability problems in context aware pervasive applications because they are represented in different formats and processed using different techniques. In this paper, we propose an ontology based trust framework for sensor driven pervasive environment for evaluating node and data trustworthiness which suffers from heterogeneity and interoperability problems. The proposed approach is capable of handling all types of nodes in pervasive environment and heterogeneous data generated from harsh and unfriendly environments of context aware pervasive applications. The proposed method comprises of semantic sensor data model and an ontology which is written in OWL language and implemented in protege. The proposed ontology is validated against use case and used for finding the trustworthiness of different sensor nodes and its data using a generic TRUST ontology.