This paper introduces the basics of energy harvesters and demonstrates two specific vibratory-type energy harvesters developed at the University of Hyogo. The fabrication and evaluation results of the vibratory-type energy harvesters, which employ electrostatic and electromagnetic mechanisms, are described. The aim of developing these devices is to realize a power source for an autonomous human monitoring system. The results of harvesting from actual human activities obtained using a data logger are also described. Moreover, challenges in the power management of electronic circuitry used for energy harvesting are briefly discussed.

In this article, we propose a method to reduce the impact of primary traffic on spectrum sensing performance. In practice, the sensing performance is degraded by noise-only sample in the spectrum sensing time. Therefore, we employ a time of primary user (PU) signal arrival detector in order to remove the noise-only portion. Then, we employ equal-weight-based energy detection (EWED) to provide the detection decision. The analysis and simulation results show that there exists an optimal early time of arrival (ToA) false alarm which provides better performance compared to the use of a single EWED scheme.

A wireless emergency communication network with a fixed allocation of spectrum resources cannot meet the tremendous demand for spectrum access when a crisis occurs. It is necessary to develop an effective spectrum access scheme to improve the performance of emergency communication systems. In this paper, we study a new emergency communication system combines cognitive radio technology and an emergency communication network. Emergency users can utility resources in a general network when traffic becomes congested in an emergency network. Non-reciprocal spectrum access scheme (NRA) and reciprocal spectrum access scheme (RA) for two heterogeneous cognitive networks, namely emergency network and general network are proposed to compare with traditional spectrum access scheme (TA). User behavior with each scheme is modeled by continuous-time Markov chains. Moreover, the blocking and dropping probabilities of users in two heterogeneous cognitive networks are derived as the performance metrics. In addition, the throughput and the spectrum utilization rate of the system are evaluated. Finally, we compare the performance of three dynamic spectrum access schemes. The simulation results show that the RA scheme is an effective scheme to enhance the performance of emergency systems.

This paper presents an independent sleep scheduling protocol for energy-efficient wireless body area networks. We designed the proposed protocol based on the IEEE 802.15.6 standard that is flexible to cover various application requirements for WBAN. The target of the proposed protocol is applications that generate aperiodic and intermittent traffic. Thus, the node providing these applications wakes up only when a new event occurs. We perform the numerical analysis and the simulation to compare the IEEE 802.15.6 without and with the independent sleep scheduling protocol. The results show that the proposed protocol increases energy-efficiency in case of large data size as well as long data occurrence interval.

For a development of energy harvesting system, the fact of radio waves and ambient RF (Radio Frequency) sources, including passive devices along with novel circuits, are very closely related to mobile charging devices and energy storage system. The use of schottky diode and voltage multiplier circuits to express on the ambient RF sources surrounding the system is one way that has seen a sudden rise in use for energy harvesting. Practically speaking, the RF and ambient sources can be provided by active and passive devices such as inductors, capacitors, diode, etc. In this paper, we present a schottky based voltage multiplier circuits for mobile charging device which integrate the power generation module with radio wave generation module. We also discuss that multi-stage schematic, e.g., three-stage schottky diode based voltage multiplier circuits, for a continuing effort on energy harvesting system.

As means to control interface reactions between HfO2 and Ge(100), chemical vapor deposition (CVD) of ultrathin Ta-rich oxide using Tri (tert-butoxy) (tert-butylimido) tantalum (Ta-TTT) on chemically-cleaned Ge(100) has been conducted prior to atomic-layer controlled CVD of HfO2 using tetrakis (ethylmethylamino) hafnium (TEMA-Hf) and O3. The XPS analysis of chemical bonding features of the samples after the post deposition N2 annealing at 300 confirms the formation of TaGexOy and the suppression of the interfacial GeO2 layer growth. The energy band structure of HfO2/TaGexOy/Ge was determined by the combination of the energy bandgaps of HfO2 and TaGexOy measured from energy loss signals of O 1s photoelectrons and from optical absorption spectra and the valence band offsets at each interface measured from valence band spectra. From the capacitance-voltage (C-V) curves of Pt-gate MIS capacitors with different HfO2 thicknesses, the thickness reduction of TaGexOy with a relative dielectric constant of 9 is a key to obtain an equivalent SiO2 thickness (EOT) below 0.7 nm.

Acoustic energy harvesters that function in environments where sound pressure is extremely high (150 dB), such as in engine rooms of aircraft, are expected to be capable of powering wireless health monitoring systems. This paper presents the power generation performance of a lead-zirconate-titanate (PZT) acoustic energy harvester with a vibrating PZT diaphragm. The diaphragm had a diameter of 2 mm, consisting of Al (0.1 µm)/PZT (1 µm)/Pt (0.1 µm)/Ti (0.1 µm)/SiO2 (1.5 µm). The harvester generated a power of 510-14 W under a sound pressure level of 110 dB at the first resonance frequency of 6.28 kHz. It was found that the generated power was increased to 2.010-13 W using a sound-collecting Helmholtz resonator cone with a height of 60 mm. The cone provided a Helmholtz resonance at 5.8 kHz, and the generated power increased from 9.710-15 W to 7.310-13 W at this frequency. The cone was also effective in increasing the bandwidth of the energy harvester.

Automatic modulation classification (AMC) involves extracting a set of unique features from the received signal. Accuracy and uniqueness of the features along with the appropriate classification algorithm determine the overall performance of AMC systems. Accuracy of any modulation feature is usually limited by the blindness of the signal information such as carrier frequency, symbol rate etc. Most papers do not sufficiently consider these impairments and so do not directly target practical applications. The AMC system proposed herein is trained with probable input signals, and the appropriate decision tree should be chosen to achieve robust classification. Six unique features are used to classify eight analog and digital modulation schemes which are widely used by low frequency mobile emergency radios around the globe. The Proposed algorithm improves the classification performance of AMC especially for the low SNR regime.

In this paper, performances of two different virtual multiple-input multiple-output (MIMO) transmission schemes — spatial multiplexing (SM) and space-time block coding (STBC) — in a correlated wireless sensor network are analyzed. By utilizing a complex Wishart distribution, we investigate the statistical properties of a correlated virtual MIMO channel between the sensors and data collector that is used in the performance analysis of each MIMO transmission mode. Distributed sensors then transmit their data cooperatively to the data collector by choosing a proper transmission mode adaptively based on the channel conditions and spatial correlation among the sensors. Furthermore, after analyzing the energy efficiencies of SM and STBC, we propose a new energy efficient mode switching rule between SM and STBC. Finally, by analytically deriving the required transmit energy of the proposed adaptive transmission scheme, the manner in which the spatial correlation influences the energy consumption is shown. This suggests a cooperating node scheduling protocol that makes energy consumption less sensitive to the variation of the spatial correlation.

During the production of speech signals, the vowel onset point is an important event containing important information for many speech processing tasks, such as consonant-vowel unit recognition and speech end-points detection. In order to realize accurate automatic detection of vowel onset points, this paper proposes a reliable method using the energy characteristics of homomorphic filtered spectral peaks. The homomorphic filtering helps to separate the slowly varying vocal tract system characteristics from the rapidly fluctuating excitation characteristics in the cepstral domain. The distinct vocal tract shape related to vowels is obtained and the peaks in the estimated vocal tract spectrum provide accurate and stable information for VOP detection. Performance of the proposed method is compared with the existing method which uses the combination of evidence from the excitation source, spectral peaks, and modulation spectrum energies. The detection rate with different time resolutions, together with the missing rate and spurious rate, are used for comprehensive evaluation of the performance on continuous speech taken from the TIMIT database. The detection accuracy of the proposed method is 74.14% for ±10 ms resolution and it increases to 96.33% for ±40 ms resolution with 3.67% missing error and 4.14% spurious error, much better than the results obtained by the combined approach at each specified time resolution, especially the higher resolutions of ±10±30 ms. In the cases of speech corrupted by white noise, pink noise and f-16 noise, the proposed method also shows significant improvement in the performance compared with the existing method.

In Wireless Sensor Networks (WSNs), sensor nodes consume their limited battery energy to send and receive data packets for data transmission. If some sensor nodes transmit data packets more frequently due to imbalance in the network topology or traffic flows, they experience higher energy consumption. And if the sensor nodes are not recharged, they will be turned off from the lack of battery energy which will degrade network sustainability. In order to resolve this problem, this paper proposes an Energy-aware MAC Protocol (EMP), which adaptively decides on the size of the channel polling cycle consisting of the sleep state (not to communicate with its target node) and the listening state (to awaken to receive data packets), according to the network traffic condition. Moreover, in accordance with the remaining energy state of the sensor node, the minimum size of the channel polling cycle is increased for better energy saving. For performance evaluation and comparison, we develop a Markov chain-based analytical model and an event-driven simulator. Simulation results show that a sensor node with EMP effectively reduces its energy consumption in imbalanced network condition and traffic flows, while latency somewhat increases under insufficient remaining energy. As a consequence, a holistic perspective for enhanced network sustainability can be studied in consideration of network traffic condition as well as the remaining energy states of sensor nodes.

In this paper, an energy- and traffic-balance-aware mapping algorithm from IP cores to nodes in a network is proposed for application-specific Network-on-Chip(NoC). The multi-objective optimization model is set up by considering the NoC architecture, and addressed by the proposed mapping algorithm that decomposes mapping optimization into a number of scalar subproblems simultaneously. In order to show performance of the proposed algorithm, the application specific benchmark is applied in the simulation. The experimental results demonstrate that the algorithm has advantages in energy consumption and traffic balance over other algorithms.

In many wireless sensor applications, skyline monitoring queries that continuously retrieve the skyline objects as well as the complete set of nodes that reported them play an important role. This paper presents SKYMON, a novel energy-efficient monitoring approach. The basic idea is to prune nodes that cannot yield a skyline result at the sink, as indicated by their (error bounded) prediction values, to suppress unnecessary sensor updates. Every node is associated with a prediction model, which is maintained at both the node and the sink. Sensors check sensed data against model-predicted values and transmit prediction errors to the sink. A data representation scheme is then developed to calculate an approximate view of each node's reading based on prediction errors and prediction values, which facilitates safe node pruning at the sink. We also develop a piecewise linear prediction model to maximize the benefit of making the predictions. Our proposed approach returns the exact results, while deceasing the number of queried nodes and transferred data. Extensive simulation results show that SKYMON substantially outperforms the existing TAG-based approach and MINMAX approach in terms of energy consumption.

We study the role of energy conversion in phase regulation of frequency entrainment. For an open dynamical system that interacts with its environment, energy conversion in the system is the key to a wide variety of nonlinear phenomena including frequency entrainment. In this paper, using the standard notion of energy, we study the phenomena of frequency entrainment by periodic forces in two different types of oscillations: libration and rotation. Theoretical analysis shows a relationship between phase regulation and energy conversion in the entrainment phenomena. Both of them are explained as a common phase regulation. On the other hand, no common relationship between transient behaviors and energy conversion is identified for the two different types of oscillations. For libration, the development of frequency entrainment does not depend on the energy conversion. The energy input to the oscillator affects the amplitude of libration. For the rotation, the development of frequency entrainment is governed by the amount of energy conversion. The energy input to the system directly regulates the phase of rotation, in other words, controls the entrainment phenomenon. These results suggest a different dynamical and control origin behind the two types of entrainment phenomena as the energy conversion in the systems.

In this paper, we propose an improved seam merging method for content-aware image resizing. This method merges a two-pixel-width seam element into one new pixel in image reduction and inserts a new pixel between the two pixels in image enlargement. To preserve important contents and structure, our method uses energy terms associated with importance and structure. Our method preserve the main structures by using a cartoon version of the original image when calculating the structure energy. In addition, we introduce a new energy term to suppress the distortion generated by excessive reduction or enlargement in iterated merger or insertion. Experimental results demonstrate that the proposed method can produce satisfactory results in both image reduction and enlargement.

In this paper, we have analyzed the guiding problem by dielectric waveguide with defects composed of dielectric circular cylinders array and deformed rhombic dielectric structure embedded in the middle layer and investigated the influence of energy flow for defect area by using the propagation constants at the guided area. From the numerical results, it is shown that we can obtain the confinement efficiency by rhombic dielectric structure compared with the deformed rhombic dielectric structure for both TE and TM modes.

In this paper, we present Greedy Routing for Maximum Lifetime (GRMax) [1],[2] which can use the limited energy available to nodes in a Wireless Sensor Network (WSN) in order to delay the dropping of packets, thus extend the network lifetime. We define network lifetime as the time period until a source node starts to drop packets because it has no more paths to the destination [3]. We introduce the new concept of Network Connectivity Aiming (NCA) node. The primary goal of NCA nodes is to maintain network connectivity and avoid network partition. To evaluate GRMax, we compare its performance with Geographic and Energy Aware Routing (GEAR) [4], which is an energy efficient geographic routing protocol and Greedy Perimeter Stateless Routing (GPSR) [5], which is a milestone among geographic routing protocol. We evaluate and compare the performance of GPSR, GEAR, and GRMax using OPNET Modeler version 15. The results show that GRMax performs better than GEAR and GPSR with respect to the number of successfully delivered packets and the time period before the nodes begin to drop packets. Moreover, with GRMax, there are fewer dead nodes in the system and less energy is required to deliver packets to destination node (sink).

We investigate a design strategy for subthreshold circuits focusing on energy-consumption minimization and yield maximization under process variations. The design strategy is based on the following findings related to the operation of low-power CMOS circuits: (1) The minimum operation voltage (VDDmin) of a circuit is dominated by flip-flops (FFs), and VDDmin of an FF can be improved by upsizing a few key transistors, (2) VDDmin of an FF is stochastically modeled by a log-normal distribution, (3) VDDmin of a large circuit can be efficiently estimated by using the above model, which eliminates extensive Monte Carlo simulations, and (4) improving VDDmin may substantially contribute to decreasing energy consumption. The effectiveness of the proposed design strategy has been verified through circuit simulations on various circuits, which clearly show the design tradeoff between voltage scaling and transistor sizing.

We propose a family of algorithms for efficiently merging on contemporary GPUs, so that each algorithm requires O(m log (+1)) element comparisons, where m and n are the sizes of the input sequences with m ≤ n. According to the lower bounds for merging all proposed algorithms are asymptotically optimal regarding the number of necessary comparisons. First we introduce a parallely structured algorithm that splits a merging problem of size 2l into 2i subproblems of size 2l-i, for some arbitrary i with (0 ≤ i ≤ l). This algorithm represents a merger for i=l but it is rather inefficient in this case. The efficiency is boosted by moving to a two stage approach where the splitting process stops at some predetermined level and transfers control to several parallely operating block-mergers. We formally prove the asymptotic optimality of the splitting process and show that for symmetrically sized inputs our approach delivers up to 4 times faster runtimes than the thrust::merge function that is part of the Thrust library. For assessing the value of our merging technique in the context of sorting we construct and evaluate a MergeSort on top of it. In the context of our benchmarking the resulting MergeSort clearly outperforms the MergeSort implementation provided by the Thrust library as well as Cederman's GPU optimized variant of QuickSort.

We observe that the state-of-the-art power-saving mechanisms (PSM) for IEEE 802.16e is neither optimal in terms of delay nor in terms of energy consumption. We propose a new PSM which achieves the optimality in terms of the average buffering delay without increasing energy consumption. In order to do so, we derive a formula which relates the average buffering delay to sleep intervals. Simulation results show that our scheme surpasses the BTE algorithm (used by the current IEEE 802.16e Mobile Stations) by 56.75–76% and the PSID algorithm by 8.52–24.39% in terms of the delay-energy consumption product.