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We present an L q ( L p ) -theory for the equation ∂ t α u = ϕ ( Δ ) u + f , t > 0 , x ∈ R d ; u ( 0 , ⋅ ) = u 0 . Here p , q > 1 , α ∈ ( 0 , 1 ) , ∂ t α is the Caputo fractional derivative of order α, and ϕ is a Bernstein function satisfying the following: ∃ δ 0 ∈ ( 0 , 1 ] and c > 0 such that (0.1) c ( R r ) δ 0 ≤ ϕ ( R ) ϕ ( r ) , 0 r R ∞ . We prove uniqueness and existence results in Sobolev spaces, and obtain maximal regularity results of the solution. In particular, we prove ‖ | ∂ t α u | + | u | + | ϕ ( Δ ) u | ‖ L q ( [ 0 , T ] ; L p ) ≤ N ( ‖ f ‖ L q ( [ 0 , T ] ; L p ) + ‖ u 0 ‖ B p , q ϕ , 2 − 2 / α q ) , where B p , q ϕ , 2 − 2 / α q is a modified Besov space on R d related to ϕ. Our approach is based on BMO estimate for p = q and vector-valued Calderon-Zygmund theorem for p ≠ q . The Littlewood-Paley theory is also used to treat the non-zero initial data problem. Our proofs rely on the derivative estimates of the fundamental solution, which are obtained in this article based on the probability theory.

NAND flash storage has become a standard choice in consumer electronics and is gaining popularity in enterprise systems due to its superior performance and low-power consumption. While its cost disadvantage is rapidly fading thanks to multibit cell technologies and 3-D stacking architectures, the challenge of limited endurance is still lingering and is expected to become more daunting as bits-per-cell continues to increase. In this article, we propose a novel flash translation layer (FTL) design named AxFTL (Approximate FTL) that extends the lifetime of NAND flash storage for error-tolerant applications. For error-tolerant data, AxFTL adopts shallow erase that lowers erase voltage to reduce the erase-induced wearing at the cost of an increased error rate. AxFTL manages multiple groups of blocks by error rates and allocates them according to the error tolerance of write requests. The key components of AxFTL include error tolerance-aware garbage collection and wear leveling schemes that manage the blocks with different error rates with minimal overhead. We implement AxFTL in an SSD simulator for the evaluation of the lifetime improvement and the actual allocation of the blocks. For application-level evaluation, we apply AxFTL to compressed video storage and evaluate the quality of video playback. Our experimental results show that AxFTL greatly improves the lifetime of NAND flash storage by 61% while maintaining a high structural similarity (SSIM) of 0.86 as compared to the conventional FTL.

By overlapping disk accesses with computation-intensive operations, prefetching can reduce delays in launching an application and in loading significant amounts of data while the application is running. The key to effective prefetching is making the tradeoff between the mining accuracy of selecting relevant blocks, and the time to decide those blocks. To address this problem, we propose a new prefetcher called ClusterFetch . In its learning mode, ClusterFetch detects periods of intensive disk accesses by monitoring the speed at which read requests are queued; it re-organizes these reads and locates the file opened by the application just before each such period. During subsequent runs of the same application, ClusterFetch prefetches the data associated with the opening of a “trigger” file. Our experimental results show that ClusterFetch implemented in Linux can reduce the application launch time by up to 41.3 percent and the loading time by up to 38.2 percent, while taking up less than 200 KB of main memory.

Applications face additional latency when they launch or access a disk to load data into the memory. In this paper, a user-level disk prefetching framework, called iFetcher, is introduced to hide this delay in Linux-based operating systems. This employs an inode-notification ( inotify ) application programming interface (API), which provides an efficient method of tracing operations in a Linux file system, and reports these events to applications in real time. During an initial training run, iFetcher traces the pattern with which data are read by an application. Subsequently, it searches the areas directly ahead of passages where it is requested that a lot of data are read, and locates events that can be used to trigger preloading. When the application is run again and a trigger event is reported (by the inotify API), the corresponding data are read into the page cache prior to actual demand. iFetcher has a low overhead, because disk reads are only need to be monitored during training. Furthermore, it does not require any modifications to the Linux kernel, because it runs at the user level. Five benchmark applications were run on a PC using a solid-state drive, and results demonstrated that iFetcher reduced the launch times by up to 41% and post-launch data loading times by up to 9%.

Numerous studies on forward osmosis (FO) have been conducted to understand fouling mechanisms better, especially compared to the reverse osmosis (RO) process. In this study, characteristics of concentrates from FO and RO filtrations were investigated to evaluate the rejection mechanisms of organic matter and to elucidate the effects of pressure on the active membrane side and hydrophobicity of organic compounds in the feed solution. The fluorescence excitation–emission matrix (FEEM) and a liquid chromatography-online carbon detector were employed to analyze the properties of organic matter. Secondary wastewater effluent was used to compare the concentrates. More humic-like fractions of organic matter remained in the concentrate from the FO than the RO process. In the concentrate from RO, building blocks and low-molecular weight acid were noticeable. The pressurized filtration experiments of the FO membrane revealed that operation with transmembrane pressure produced similar properties of the conce...

Food waste accounts for a substantial portion of the organic waste generated at an increasing rate worldwide. Organic waste, including food waste, is largely subjected to landfill disposal, incineration, and anaerobic digestion; however, more sustainable methods are needed for treating it. Treatment of organic waste using black soldier fly (Hermetia illucens) larvae is an environmentally safe and cost-efficient method that has been attracting increasing attention worldwide. Black soldier fly decomposes various types of organic waste and converts them into high-value biomasses such as oils and proteins. This review introduces the trends in research related to the treatment of organic waste by black soldier fly (Hermetia illucens) larvae (BSFL) and their bioconversion efficiencies in Asian countries. Perspectives on the growth of BSFL during waste treatment operation and optimal rearing conditions are provided. The trends in studies related to the application of BSFL as biofuel and animal feed are also discussed. Such use of BSFL would be beneficial in Asia, especially in countries where the technology for processing organic waste is not readily available. This review may provide further directions of investigations including culture techniques for industrial scale applications of BSFL in food waste treatment and resource production in Asian countries.

Numerous advantages of forward osmosis (FO) include operation at low or no hydraulic pressure, high rejection of a wide range of contaminants, and low irreversible fouling. The FO has been investigated to reduce effluent discharge in wastewater reclamation. The application of wastewater effluent as a feed stream to FO yields fouling on the active layer of the FO membrane. Fouling was examined using two compounds (i.e., alginate and humic acid) with distinguished hydrophobic properties. The repeated filtration and surface wash were applied and flux decline and reversibility of physical cleaning were evaluated. In addition, the characteristics of fouling cakes and concentrates were also analyzed. The foulants showed different behaviors in flux decline. The thick cake layer of alginate was obvious and the cake enhanced concentration polarization was also observed. The recovery results along with the FTIR spectra and FE-SEM images proved that the surface cleaning was not effective to detach foulants, especially for alginate fouling. The osmotic backwash showed greater flux recovery for alginate fouling than humic acid fouling, which indicated that restoring membrane pores or disturbing cake layers by osmotic backwash might be successful for the foulants for strong interactions between foulants and foulants. The concentrates were mostly composed of humic substances and low-molecular weight neutrals. The differences in the relative portions of the major components were occurred in the concentrates implying that the organic properties of the feed water and also interactions of foulants and membranes should be evaluated prior to determination of disposal options for concentrates.

Active storage devices further improve their performance by executing “intelligence functions,” such as prefetching and data deduplication, in addition to handling the usual I/O requests they receive. Significant research has been carried out to develop effective intelligence functions for the active storage devices. However, laborious and time-consuming efforts are usually required to set up a suitable experimental platform to evaluate each new intelligence function. Moreover, it is difficult to make such prototypes available to other researchers and users to gain valuable experience and feedback. To overcome these difficulties, we propose $\tt {IOLab}$ , a virtual machine (VM)-based platform for evaluating intelligence functions of active storage devices. The VM-based structure of $\tt {IOLab}$ enables the evaluation of new (and existing) intelligence functions for different types of OSes and active storage devices with little additional effort. $\tt {IOLab}$ also supports real-time execution of intelligence functions, providing users opportunities to experience latest intelligence functions without waiting for their deployment in commercial products. Using a set of interesting case studies, we demonstrate the utility of $\tt {IOLab}$ with negligible performance overhead except for the VM’s virtualization overhead.

Application launch performance is of great importance to system platform developers and vendors as it greatly affects the degree of users’ satisfaction. The single most effective way to improve application launch performance is to replace a hard disk drive (HDD) with a solid state drive (SSD), which has recently become affordable and popular. A natural question is then whether or not to replace the traditional HDD-aware application launchers with a new SSD-aware optimizer. We address this question by analyzing the inefficiency of the HDD-aware application launchers on SSDs and then proposing a new SSD-aware application prefetching scheme, called the Fast Application STarter (FAST). The key idea of FAST is to overlap the computation (CPU) time with the SSD access (I/O) time during an application launch. FAST is composed of a set of user-level components and system debugging tools provided by Linux OS (operating system). Hence, FAST can be easily deployed in any recent Linux versions without kernel recompilation. We implement FAST on a desktop PC with an SSD running Linux 2.6.32 OS and evaluate it by launching a set of widely-used applications, demonstrating an average of 28% reduction of application launch time as compared to PC without a prefetcher.

Application loading times can be reduced by prefetching disk blocks into the buffer cache. Existing prefetching schemes for general workloads suffer from significant overheads and low accuracy. ClusterFetch is a lightweight prefetcher that identifies continuous sequences of I/O requests and identifies the files that trigger them. The next time that the same files are opened, the corresponding disk blocks are prefetched. In experiments, ClusterFetch reduced the launch time, by which we refer to the latency that first occurs when a program runs, by 15.2 to 30.9%, and loading times, meaning the delays that are incurred while additional data is loaded from the disk during program execution, by 15.9%.

Using an optimised application prefetcher to accelerate the application launch on solid-state drives (SSDs) by exploiting the SSD parallelism is proposed. The proposed prefetcher was implemented on the Linux OS and achieved a 37% reduction of prefetcher execution time, which corresponds to an 18% reduction of application launch time.

A simple tactile imaging system for detecting possible breast lumps is proposed. The breast cancer detection system (BCDS) consists of a palm-sized, portable, wireless scanning probe with a nine-force sensor array, a web camera, and a PC program to display the location and stiffness of hard breast lesions based on tactile pressure profiles. The results of performance evaluation tests using various breast phantoms demonstrated that palpable abnormalities larger than 5 mm located at depths less than 25 mm can be detected accurately. It is expected that this low-priced BCDS will extensively benefit all adults and ubiquitous healthcare services who apply regular breast self-examination by providing remote magnified palpation with enhanced tactile sensitivity.