An efficient search mechanism for supporting partial filename queries in structured peer-to-peer overlay

Accompanying the growth of the Internet, computers throughout the world can connect to each other and exchange information, increasing the convenience and efficiency of information-based work. The advent of data-sharing applications, such as Napster and Gnutella, has made peer-to-peer (P2P) systems popular for widespread exchange of resources and voluminous information between millions of users. In recent years, research issues associated with P2P systems have been discussed widely. To resolve the file-availability problem and improve the workload, a method called the Distributed Hash Table (DHT) has been proposed. However, DHT-based systems in structured architectures cannot support efficient queries, such as a similarity query, range query, and partial-match query, due to the characteristics of the hash function. This study presents a novel scheme that supports filename partial-matches in structured P2P systems. The proposed approach supports complex queries and guarantees result quality. Experimental results demonstrate the effectiveness of the proposed approach.     

Evidence of successful river spawning by lake trout (Salvelinus namaycush) in the Lower Niagara River,Lake Ontario

Restoration of a wild-produced lake trout Salvelinus namaycush population in Lake Ontario has not been successful despite the adult population often meeting or exceeding restoration targets. Lack of high-quality spawning habitat in Lake Ontario is suggested as one impediment to recruitment of wild lake trout, although the quantity and location of spawning habitat is poorly understood. If high-quality spawning habitat is limited in Lake Ontario, lake trout may be using uncommon spawning locations such as rivers. Anecdotal angler accounts point to the Niagara River as a lake trout spawning location. To better understand the potential of the Niagara River as a spawning location, egg and juvenile fish collections were conducted 12–14 river kilometers from the mouth of the Niagara River from 2010 to 2012; and mature female lake trout with surgically implanted acoustic tags were monitored from 2015 to 2019. Genetic analyses confirmed 60% of collected eggs and 93% of collected post-hatch juvenile fish in the Niagara River were lake trout. Tagged female lake trout returned to the Niagara River over consecutive years during the spawning season. The short duration of lake trout presence in the river (mean = 56 days/year) suggests female lake trout use the Niagara River primarily for spawning. Diversity in spawning locations may provide lake trout population’s resilience against environmental variability through a portfolio effect. Improved identification of riverine spawning locations, including their overall contribution to wild recruitment, may be a useful tool for managers to restore a wild-produced population of lake trout in Lake Ontario.     

Public–Private Partnerships in the Water Sector: The Case of Desalination

Water Resources Management - Public–private partnerships (PPPs) have grown in popularity as a method to leverage private sector actors in the production of government services. With the...     

Simple systolic arrays for discrete cosine transform

in this paper, simple 1-D and 2-D systolic array for realizing the discrete cosine transform (DCT) based on the discrete Fourier transform (DFT) fo an input sequence are presented. The proposed arrays are obtained by a simple modified DFT (MDFT) and an inverse DFT (IDFT) version of the Goertzel algorithm combined with Kung's approach. The 1-D array requiresN cells, one multiplier and takesN clock cycles to produce a completeN-point DCT. The 2-D array takes N clock cycles, faster than the 1-D array, but the area complexity is larger. A continuous flow of input data is allowed and no idle time is required between the input sequences.     

Microstructural characterization of rapidly solidified nickel-base superalloys

Several Ni-Al-Mo-based eutectic superalloys were rapidly solidified using a chilled block melt spinning process. The effects of rapid solidification on the microstructure were studied using optical microscopy, transmission electron microscopy (TEM), and scanning transmission electron microscopy (STEM). Results showed, except for the alloy containing chromium, that the microstructure varied as a function of ribbon thickness from segregationless solidification at the wheel side of the ribbon to dendritic solidification at the free side. In addition, alloys with the same solidification rate showed a large variation in microstructure depending upon the solid state cooling rate. The rapidly solidified eutectic Ni-Al-Mo alloy with a small amount of rhenium and vanadium did not show any improvement on delaying or prohibiting the formation of the embrittling-NiMo phase on ageing at 1000 C. This was determined from microstructural as well as chemical analysis using STEM. Differential thermal analysis was used to obtain melting temperature,-Ni₃Al solvus, and heat of formation for the alloys.     

Combining teacher-Led and technology-assisted instruction to improve phoneme blending to read words for elementary students with disabilities

Technology-assisted instruction has potential for helping students improve their reading skills. In the current studies, PowerPoint software was used to supplement teacher-led reading instruction for elementary-aged students with disabilities who struggled with phoneme blending to read words. The effectiveness of the intervention was assessed using two multiple probe design studies across sets of words based on an onset-rime (word family) strategy. In Study 1, teacher-led instruction was paired with technology-assisted instruction for all intervention sessions for three students in first and second grade. In Study 2, teacher-led instruction occurred between baseline and technology-assisted intervention sessions for three students in third and fourth grade. During the initial instruction sessions, participants recorded their own voices onto PowerPoint slides so that their technology-assisted instruction included self-modelling. Results of both studies indicated that technology-assisted instruction can be effective for helping students learn how to blend phonemes to read words; however, performance varied and there were limitations in each study that should be addressed in future research. Relevant implications for classroom instruction are emphasized.     

Visual tracking using convolutional features with sparse coding

Artificial Intelligence Review - Visual object tracking has become one of the most active research topics in computer vision, and it has been applied in several commercial...     

Land‐use dynamic discovery based on heterogeneous mobility sources

Nowadays, cities are the most relevant type of human settlement and their population has been endlessly growing for decades. At the same time, we are witnessing an explosion of digital data that capture many different aspects and details of city life. This allows detecting human mobility patterns in urban areas with more detail than ever before. In this context, based on the fusion of mobility data from different and heterogeneous sources, such as public transport, transport‐network connectivity and Online Social Networks, this study puts forward a novel approach to uncover the actual land use of a city. Unlike previous solutions, our work avoids a time‐invariant approach and it considers the temporal factor based on the assumption that urban areas are not used by citizens all the time in the same manner. We have tested our solution in two different cities showing high accuracy rates.     

Support NNEF execution model for NNAPI

The Journal of Supercomputing - With growing applications such as image recognition, speech recognition, ADAS, and AIoT, artificial intelligence (AI) frameworks are becoming popular in various...     

Deep neural network-based fusion model for emotion recognition using visual data

The Journal of Supercomputing - In this study, we present a fusion model for emotion recognition based on visual data. The proposed model uses video information as its input and generates emotion...