Intelligent Data Collaboration in Heterogeneous-device IoT Platforms

The merging boundaries between edge computing and deep learning are forging a new blueprint for the Internet of Things (IoT). However, the low-quality of data in many IoT platforms, especially those composed of heterogeneous devices, is hindering the development of high-quality applications for those platforms. The solution presented in this article is intelligent data collaboration, i.e., the concept of deep learning providing IoT with the ability to adaptively collaborate to accomplish a task. Here, we outline the concept of intelligent data collaboration in detail and present a mathematical model in general form. To demonstrate one possible case where intelligent data collaboration would be useful, we prepared an implementation called adaptive data cleaning (ADC), designed to filter noisy data out of temperature readings in an IoT base station network. ADC primarily consists of a denoising autoencoder LSTM for predictions and a four-level data processing mechanism to perform the filtering. Comparisons between ADC and a maximum slop method show ADC with the lowest false error and the best filtering rates.

Keystroke Dynamics-Based Authentication Using Unique Keypad

Authentication methods using personal identification number (PIN) and unlock patterns are widely used in smartphone user authentication. However, these authentication methods are vulnerable to shoulder-surfing attacks, and PIN authentication, in particular, is poor in terms of security because PINs are short in length with just four to six digits. A wide range of research is currently underway to examine various biometric authentication methods, for example, using the user’s face, fingerprint, or iris information. However, such authentication methods provide PIN-based authentication as a type of backup authentication to prepare for when the maximum set number of authentication failures is exceeded during the authentication process such that the security of biometric authentication equates to the security of PIN-based authentication. In order to overcome this limitation, research has been conducted on keystroke dynamics-based authentication, where users are classified by analyzing their typing patterns while they are entering their PIN. As a result, a wide range of methods for improving the ability to distinguish the normal user from abnormal ones have been proposed, using the typing patterns captured during the user’s PIN input. In this paper, we propose unique keypads that are assigned to and used by only normal users of smartphones to improve the user classification performance capabilities of existing keypads. The proposed keypads are formed by randomly generated numbers based on the Mersenne Twister algorithm. In an attempt to demonstrate the superior classification performance of the proposed unique keypad compared to existing keypads, all tests except for the keypad type were conducted under the same conditions in earlier work, including collection-related features and feature selection methods. Our experimental results show that when the filtering rates are 10%, 20%, 30%, 40%, and 50%, the corresponding equal error rates (EERs) for the proposed keypads are improved by 4.15%, 3.11%, 2.77%, 3.37% and 3.53% on average compared to the classification performance outcomes in earlier work.

Alteration of Feeding and Filtering Rates of Two Species of Marine Copepods Exposed to Different pH Levels

Impacts of different pH levels on different species of marine copepods, Calanoida copepod Schmackeria poplesia and Cyclopoida copepod Oithona similis were evaluated, and the alteration of key physiological processes of feeding and filtering were comparatively studies under controlled lab conditions. The optimal pH for O.similis and S.poplesia was 9.0 and 8.0 respectively, and they performed differently when exposed to different pH levels. For S. poplesia., the feeding and filtering rates increased steadily with the increment of pH at the range of 6.0~8.0, and reached the peak at pH 8.0. However, the rates decreased when pH was above 9.0. O.similis seemed more adaptive to the change of pH, and the increment was found in feeding and filtering rates at a range of 6.0~8.0. The maximus appeared at pH 9.0. compared to the other pH levels, the acidifying level of pH 6.0 presented the most obviously inhibition on feeding and filtering. Results in the present study would shed light on establishing the optimum culturing conditions for the cultivation of marine copepod.

Experimental research on filtering fibers in a cyclone–porous barrier system

Properties of filtering materials used as porous barriers in air cleaners of motor vehicles have been analyzed in the paper. Relations that determine the filter life have been analyzed and the coefficient of dust absorption km of the filtering material has been determined. Methodology of research has been presented of a study air filter element made of filtering fiber used as a second filtering stage downstream of a single continuous cyclone. The results of the investigations into the characteristics of efficiency, accuracy and drag of the filtering fiber for different filtering rates have been discussed. Dust absorption coefficients km have been determined. Changes in the granulometric composition of dust downstream of the investigated filtering element have been presented. Benefits resulting from the application of a two-stage air filtering method have been indicated.

Are Private Markets and Filtering a Viable Source of Low-Income Housing? Estimates from a “Repeat Income” Model

While filtering has long been considered the primary mechanism by which markets supply low-income housing, direct estimates of that process have been absent. This has contributed to doubts about the viability of markets and to misplaced policy. I fill this gap by estimating a “repeat income” model using 1985–2011 panel data. Real annual filtering rates are faster for rental housing (2.5 percent) than owner-occupied (0.5 percent), vary inversely with the income elasticity of demand and house price inflation, and are sensitive to tenure transitions as homes age. For most locations, filtering is robust which lends support for housing voucher programs. (JEL R21, R31, R38)

Experimental research of intake air filtering fibers in motor vehicle engines

Properties of filtering materials used as porous barriers in filter elements of motor vehicle air cleaners have been analyzed. Criteria of fiber and paper selection for the filter elements have been presented. A relation showing the filter life and a coefficient of dust absorption km of filtering materials have been presented. A methodology of research of the fiber filter element characteristics has been developed. Results of investigations of the characteristics of efficiency, filtering accuracy and drag of the filtering fiber operating at different filtering rates have been presented. The coefficients of dust absorption km of the filtering fiber have been determined. Changes in the granulometric properties of dust in the airflow downstream of the filtering fiber and paper have been presented.

Zebra mussel (Dreissena polymorpha) selective filtration promoted toxic Microcystis blooms in Saginaw Bay (Lake Huron) and Lake Erie

Microcystis aeruginosa, a planktonic colonial cyanobacterium, was not abundant in the 2-year period before zebra mussel (Dreissena polymorpha) establishment in Saginaw Bay (Lake Huron) but became abundant in three of five summers subsequent of mussel establishment. Using novel methods, we determined clearance, capture, and assimilation rates for zebra mussels feeding on natural and laboratory M. aeruginosa strains offered alone or in combination with other algae. Results were consistent with the hypothesis that zebra mussels promoted blooms of toxic M. aeruginosa in Saginaw Bay, western Lake Erie, and other lakes through selective rejection in pseudofeces. Mussels exhibited high feeding rates similar to those seen for a highly desirable food alga (Cryptomonas) with both large ( >53 µm) and small (<53 µm) colonies of a nontoxic and a toxic laboratory strain of M. aeruginosa known to cause blockage of feeding in zooplankton. In experiments with naturally occurring toxic M. aeruginosa from Saginaw Bay and Lake Erie and a toxic isolate from Lake Erie, mussels exhibited lowered or normal filtering rates with rejection of M. aeruginosa in pseudofeces. Selective rejection depended on "unpalatable" toxic strains of M. aeruginosa occurring as large colonies that could be rejected efficiently while small desirable algae were ingested.