Appliance Load Monitoring (ALM) is essential for energy management solutions, allowing them to obtain appliance-specific energy consumption statistics that can further be used to devise load scheduling strategies for optimal energy utilization. Fine-grained energy monitoring can be achieved by deploying smart power outlets on every device of interest; however it incurs extra hardware cost and installation complexity. Non-Intrusive Load Monitoring (NILM) is an attractive method for energy disaggregation, as it can discern devices from the aggregated data acquired from a single point of measurement. This paper provides a comprehensive overview of NILM system and its associated methods and techniques used for disaggregated energy sensing. We review the state-of-the art load signatures and disaggregation algorithms used for appliance recognition and highlight challenges and future research directions.
Colorimetric sensing, which transduces environmental changes into visible color changes, provides a simple yet powerful detection mechanism that is well-suited to the development of low-cost and low-power sensors. A new approach in colorimetric sensing exploits the structural color of photonic crystals (PCs) to create environmentally-influenced color-changeable materials. PCs are composed of periodic dielectrics or metallo-dielectric nanostructures that affect the propagation of electromagnetic waves (EM) by defining the allowed and forbidden photonic bands. Simultaneously, an amazing variety of naturally occurring biological systems exhibit iridescent color due to the presence of PC structures throughout multi-dimensional space. In particular, some kinds of the structural colors in living organisms can be reversibly changed in reaction to external stimuli. Based on the lessons learned from natural photonic structures, some specific examples of PCs-based colorimetric sensors are presented in detail to demonstrate their unprecedented potential in practical applications, such as the detections of temperature, pH, ionic species, solvents, vapor, humidity, pressure and biomolecules. The combination of the nanofabrication technique, useful design methodologies inspired by biological systems and colorimetric sensing will lead to substantial developments in low-cost, miniaturized and widely deployable optical sensors.
The Leap Motion Controller is a new device for hand gesture controlled user interfaces with declared sub-millimeter accuracy. However, up to this point its capabilities in real environments have not been analyzed. Therefore, this paper presents a first study of a Leap Motion Controller. The main focus of attention is on the evaluation of the accuracy and repeatability. For an appropriate evaluation, a novel experimental setup was developed making use of an industrial robot with a reference pen allowing a position accuracy of 0.2 mm. Thereby, a deviation between a desired 3D position and the average measured positions below 0.2 mm has been obtained for static setups and of 1.2 mm for dynamic setups. Using the conclusion of this analysis can improve the development of applications for the Leap Motion controller in the field of Human-Computer Interaction.
Microelectromechanical Systems (MEMS) technology is playing a key role in the design of the new generation of smartphones. Thanks to their reduced size, reduced power consumption, MEMS sensors can be embedded in above mobile devices for increasing their functionalities. However, MEMS cannot allow accurate autonomous location without external updates, e. g., from GPS signals, since their signals are degraded by various errors. When these sensors are fixed on the user's foot, the stance phases of the foot can easily be determined and periodic Zero velocity UPdaTes (ZUPTs) are performed to bound the position error. When the sensor is in the hand, the situation becomes much more complex. First of all, the hand motion can be decoupled from the general motion of the user. Second, the characteristics of the inertial signals can differ depending on the carrying modes. Therefore, algorithms for characterizing the gait cycle of a pedestrian using a handheld device have been developed. A classifier able to detect motion modes typical for mobile phone users has been designed and implemented. According to the detected motion mode, adaptive step detection algorithms are applied. Success of the step detection process is found to be higher than 97% in all motion modes.
Vibration analysis is an effective tool for the condition monitoring and fault diagnosis of rolling element bearings. Conventional diagnostic methods are based on the stationary assumption, thus they are not applicable to the diagnosis of bearings working under varying speed. This constraint limits the bearing diagnosis to the industrial application significantly. In order to extend the conventional diagnostic methods to speed variation cases, a tacholess envelope order analysis technique is proposed in this paper. In the proposed technique, a tacholess order tracking (TLOT) method is first introduced to extract the tachometer information from the vibration signal itself. On this basis, an envelope order spectrum (EOS) is utilized to recover the bearing characteristic frequencies in the order domain. By combining the advantages of TLOT and EOS, the proposed technique is capable of detecting bearing faults under varying speeds, even without the use of a tachometer. The effectiveness of the proposed method is demonstrated by both simulated signals and real vibration signals collected from locomotive roller bearings with faults on inner race, outer race and rollers, respectively. Analyzed results show that the proposed method could identify different bearing faults effectively and accurately under speed varying conditions.
Cholinesterases are important biological targets responsible for regulation of cholinergic transmission, and their inhibitors are used for the treatment of Alzheimer's disease. To design new cholinesterase inhibitors, of different structure-based design strategies was followed, including the modification of compounds from a previously developed library and a fragment-based design approach. This led to the selection of heterodimeric structures as potential inhibitors. Synthesis and biological evaluation of selected candidates confirmed that the designed compounds were acetylcholinesterase inhibitors with IC50 values in the mid-nanomolar to low micromolar range, and some of them were also butyrylcholinesterase inhibitors.
Wireless sensor networks (WSNs) can be quickly and randomly deployed in any harsh and unattended environment and only authorized users are allowed to access reliable sensor nodes in WSNs with the aid of gateways (GWNs). Secure authentication models among the users, the sensor nodes and GWN are important research issues for ensuring communication security and data privacy in WSNs. In 2013, Xue et al. proposed a temporal-credential-based mutual authentication and key agreement scheme for WSNs. However, in this paper, we point out that Xue et al.'s scheme cannot resist stolen-verifier, insider, off-line password guessing, smart card lost problem and many logged-in users' attacks and these security weaknesses make the scheme inapplicable to practical WSN applications. To tackle these problems, we suggest a simple countermeasure to prevent proposed attacks while the other merits of Xue et al.'s authentication scheme are left unchanged.
The high cost of what have historically been sophisticated research-related sensors and tools has limited their adoption to a relatively small group of well-funded researchers. This paper provides a methodology for applying an open-source approach to design and development of a colorimeter. A 3-D printable, open-source colorimeter utilizing only open-source hardware and software solutions and readily available discrete components is discussed and its performance compared to a commercial portable colorimeter. Performance is evaluated with commercial vials prepared for the closed reflux chemical oxygen demand (COD) method. This approach reduced the cost of reliable closed reflux COD by two orders of magnitude making it an economic alternative for the vast majority of potential users. The open-source colorimeter demonstrated good reproducibility and serves as a platform for further development and derivation of the design for other, similar purposes such as nephelometry. This approach promises unprecedented access to sophisticated instrumentation based on low-cost sensors by those most in need of it, under-developed and developing world laboratories.
Facial expressions are widely used in the behavioral interpretation of emotions, cognitive science, and social interactions. In this paper, we present a novel method for fully automatic facial expression recognition in facial image sequences. As the facial expression evolves over time facial landmarks are automatically tracked in consecutive video frames, using displacements based on elastic bunch graph matching displacement estimation. Feature vectors from individual landmarks, as well as pairs of landmarks tracking results are extracted, and normalized, with respect to the first frame in the sequence. The prototypical expression sequence for each class of facial expression is formed, by taking the median of the landmark tracking results from the training facial expression sequences. Multi-class AdaBoost with dynamic time warping similarity distance between the feature vector of input facial expression and prototypical facial expression, is used as a weak classifier to select the subset of discriminative feature vectors. Finally, two methods for facial expression recognition are presented, either by using multi-class AdaBoost with dynamic time warping, or by using support vector machine on the boosted feature vectors. The results on the Cohn-Kanade (CK+) facial expression database show a recognition accuracy of 95.17% and 97.35% using multi-class AdaBoost and support vector machines, respectively.
In this preliminary study, the silver nanoparticle (Ag NP)-based dressing, Acticoat(TM) Flex 3, has been applied to a 3D fibroblast cell culture in vitro and to a real partial thickness burn patient. The in vitro results show that Ag NPs greatly reduce mitochondrial activity, while cellular staining techniques show that nuclear integrity is maintained, with no signs of cell death. For the first time, transmission electron microscopy (TEM) and inductively coupled plasma mass spectrometry (ICP-MS) analyses were carried out on skin biopsies taken from a single patient during treatment. The results show that Ag NPs are released as aggregates and are localized in the cytoplasm of fibroblasts. No signs of cell death were observed, and the nanoparticles had different distributions within the cells of the upper and lower dermis. Depth profiles of the Ag concentrations were determined along the skin biopsies. In the healed sample, most of the silver remained in the surface layers, whereas in the unhealed sample, the silver penetrated more deeply. The Ag concentrations in the cell cultures were also determined. Clinical observations and experimental data collected here are consistent with previously published articles and support the safety of Ag NP-based dressing in wound treatment.