scholarly journals SpotFuzz: Fuzzing Based on Program Hot-Spots

Electronics ◽  
2021 ◽  
Vol 10 (24) ◽  
pp. 3142
Author(s):  
Haibo Pang ◽  
Jie Jian ◽  
Yan Zhuang ◽  
Yingyun Ye ◽  
Zhanbo Li
Keyword(s):  
Hot Spots ◽  
Hot Spot ◽  
Experimental Results ◽  
Test Cases ◽  
Limited Time ◽  
Very High

AFL is the most widely used coverage-guided fuzzer, which relies on rough execution information to assign seeds energy, which can lead to waste. We track the program executed by AFL and discover that the hit counts of each edge might vary greatly when using different seeds as inputs. Some seeds, which are continuously given too much energy, experience very high hit counts of several edges without new crashes or edges being explored, which results in invalid execution and waste of performance. We also define time-consuming edges and discover that they only occupy a small part of the program. In this paper, we define invalid execution edges and time-consuming edges as hot-spots and propose a fuzzing solution SpotFuzz to solve energy waste caused by the above hot-spot phenomenon. It allocates seeds with more hot-spots during execution and uses less energy to reduce energy waste. Moreover, it preferentially selects seeds with less time-consuming edges as test cases, allowing for more edges to be explored in a limited time. We implement an SpotFuzz prototype based on AFL and test it on several real programs for 600 CPU days. The experimental results show that minimizing the invalid and time-consuming execution of edges can improve the fuzzing efficiency. On average, SpotFuzz could find 42.96% more unique crashes and 14.25% more edges than AFL on GNU Binutils and tcpdump.

Evaporative Thermal Performance of Vapor Chambers Under Nonuniform Heating Conditions

2008 ◽  
Vol 130 (12) ◽  
Author(s):  
Je-Young Chang ◽  
Ravi S. Prasher ◽  
Suzana Prstic ◽  
P. Cheng ◽  
H. B. Ma
Keyword(s):  
Heat Flux ◽  
Thermal Resistance ◽  
Thermal Performance ◽  
Hot Spots ◽  
Hot Spot ◽  
Heat Fluxes ◽  
Experimental Results ◽  
Nonuniform Heating ◽  
Test Results ◽  
Uniform Heating

This paper reports the test results of vapor chambers using copper post heaters and silicon die heaters. Experiments were conducted to understand the effects of nonuniform heating conditions (hot spots) on the evaporative thermal performance of vapor chambers. In contrast to the copper post heater, which provides ideal heating, a silicon chip package was developed to replicate more realistic heat source boundary conditions of microprocessors. The vapor chambers were tested for hot spot heat fluxes as high as 746 W/cm2. The experimental results show that evaporator thermal resistance is not sensitive to nonuniform heat conditions, i.e., it is the same as in the uniform heating case. In addition, a model was developed to predict the effective thickness of a sintered-wick layer saturated with water at the evaporator. The model assumes that the pore sizes in the sintered particle wick layer are distributed nonuniformly. With an increase of heat flux, liquid in the larger size pores are dried out first, followed by drying of smaller size pores. Statistical analysis of the pore size distribution is used to calculate the fraction of the pores that remain saturated with liquid at a given heat flux condition. The model successfully predicts the experimental results of evaporative thermal resistance of vapor chambers for both uniform and nonuniform heat fluxes.

Experimental Characterization of Bonded Microcoolers for Hot Spot Removal

2005 ◽  
Author(s):  
Yan Zhang ◽  
Gehong Zeng ◽  
Christine Hoffman ◽  
Ali Shakouri ◽  
Peng Wang ◽  
...  
Keyword(s):  
Integrated Circuit ◽  
Hot Spots ◽  
Hot Spot ◽  
Experimental Results ◽  
Cooling Power ◽  
Experimental Characterization ◽  
Region Versus ◽  
Test Range ◽  
Microelectronic Devices

In this paper we describe the experimental results of Si/SiGe superlattice microcoolers, which are used to cool the target hot spot on a 65μm-thick silicon substrate. The device areas under test range from 50×50 to 150×150 μm2. We measured the cooling temperature at the hot spot region versus the current supplied to the microcooler, as well as the thermal resistance, and the cooling power density (CPD, also defined as heat flux — the flow of heat per unit area in W/cm2) of these devices. The experimental results show the maximum cooling at the hot spot region approaches 1°C for device area 150×150μm2 at 80°C, and CPD up to ∼110W/cm2 for device area 50×50×2 μm2 (two 50×50μm2 device array, as illustrated in Figure 3) at 80°C. The two-chip bonded configuration will allow the integration of spot coolers and integrated circuit chips with minimum impact on the processing of microelectronic devices. Key parameters limiting the cooling performance at the hot spots are also discussed.

Spatial Hotspot Analysis of Bucharest’s Urban Heat Island (UHI) Using Modis Data

2018 ◽  
Vol 18 (1) ◽  
pp. 14-22 ◽  
Author(s):  
Georgiana Grigoraș ◽  
Bogdan Urițescu
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Hot Spots ◽  
Land Surface ◽  
Hot Spot ◽  
Monitoring Network ◽  
Residential Areas ◽  
Hotspot Analysis ◽  
The City

Abstract The aim of the study is to find the relationship between the land surface temperature and air temperature and to determine the hot spots in the urban area of Bucharest, the capital of Romania. The analysis was based on images from both moderate-resolution imaging spectroradiometer (MODIS), located on both Terra and Aqua platforms, as well as on data recorded by the four automatic weather stations existing in the endowment of The National Air Quality Monitoring Network, from the summer of 2017. Correlation coefficients between land surface temperature and air temperature were higher at night (0.8-0.87) and slightly lower during the day (0.71-0.77). After the validation of satellite data with in-situ temperature measurements, the hot spots in the metropolitan area of Bucharest were identified using Getis-Ord spatial statistics analysis. It has been achieved that the “very hot” areas are grouped in the center of the city and along the main traffic streets and dense residential areas. During the day the "very hot spots” represent 33.2% of the city's surface, and during the night 31.6%. The area where the mentioned spots persist, falls into the "very hot spot" category both day and night, it represents 27.1% of the city’s surface and it is mainly represented by the city center.

The family Orthotrichaceae (Bryophyta) in flora of Russia: results of revision and biogeographical review

2018 ◽  
Vol 52 (2) ◽  
pp. 519-534 ◽  
Author(s):  
V. E. Fedosov
Keyword(s):  
Hot Spots ◽  
Latitudinal Gradient ◽  
Hot Spot ◽  
Spatial Differentiation ◽  
Taxonomic Composition ◽  
Undescribed Species ◽  
Longitudinal Gradient ◽  
Biogeographic Pattern ◽  
The Family ◽  
North Pacific Region

Recent studies on Orthotrichoid mosses in Russia are summarized genus by genus. Orthotrichum furcatum Otnyukova is synonymized with Nyholmiella obtusifolia. Orthotrichum vittii is excluded from the Russian moss flora. Description of O. dagestanicum is amended. Fifty four currently recognized species from 9 genera of the Orthotrichaceae are presently known to occur in Russia; list of species with common synonyms and brief review of distribution in Russia is presented. Numerous problematic specimens with unresolved taxonomy were omitted for future. Revealed taxonomical inconsistencies in the genera Zygodon, Ulota, Lewinskya, Nyholmiella, Orthotrichum are briefly discussed. Main regularities of spatial differentiation of the family Orthotrichaceae in Russia are considered. Recently presented novelties contribute to the certain biogeographic pattern, indicating three different centers of diversity of the family, changing along longitudinal gradient. Unlike European one, continental Asian diversity of Orthotrichaceae is still poorly known, the Siberian specimens which were previously referred to European species in most cases were found to represent other, poorly known or undescribed species. North Pacific Region houses peculiar and poorly understood hot spot of diversity of Orthotrichoid mosses. Thus, these hot spots are obligatory to be sampled in course of revisions of particular groups, since they likely comprise under-recorded cryptic- or semi-cryptic species. Latitudinal gradient also contributes to the spatial differentiation of the revealed taxonomic composition of Orthotrichaceae.

scholarly journals Family Practices and Temporality at Breakfast: Hot Spots, Convenience and Care

Sociology ◽  
2021 ◽  
pp. 003803852110155
Author(s):  
Daniela Pirani ◽  
Vicki Harman ◽  
Benedetta Cappellini
Keyword(s):  
Hot Spots ◽  
Hot Spot ◽  
Family Meals ◽  
Personal Integrity ◽  
Structured Interviews ◽  
Time Saving ◽  
Family Time ◽  
Dominant Feature ◽  
Family Practices ◽  
Cold Spots

Drawing on 34 semi-structured interviews, this study investigates the temporality of family practices taking place in the hot spot. It does so by looking at how breakfast is inserted in the economy of family time in Italy. Our data show that breakfast, contrary to other meals, allows the adoption of more individualised and asynchronous practices, hinged on the consumption of convenience products. These time-saving strategies are normalised as part of doing family. Although the existing literature suggests that convenience and care are in opposition, and consumers of convenience products can experience anxiety and a lack of personal integrity, such features were not a dominant feature of our participants’ accounts. These findings suggest that the dichotomies of hot/cold spots and care/convenience are not always experienced in opposition when embedded within family practices. Hence, this study furthers understandings of family meals, temporality and the distinction between hot and cold spots.

Investigation of On-Chip Hot Spot Cooling Using Microchannel Heat Sink

2013 ◽  
Vol 455 ◽  
pp. 466-469
Author(s):  
Yun Chuan Wu ◽  
Shang Long Xu ◽  
Chao Wang
Keyword(s):  
Heat Flux ◽  
Heat Sink ◽  
Hot Spots ◽  
Hot Spot ◽  
High Heat ◽  
High Heat Flux ◽  
Microchannel Heat Sink ◽  
Three Dimensional Model ◽  
Spot Cooling ◽  
On Chip

With the increase of performance demands, the nonuniformity of on-chip power dissipation becomes greater, causing localized high heat flux hot spots that can degrade the processor performance and reliability. In this paper, a three-dimensional model of the copper microchannel heat sink, with hot spot heating and background heating on the back, was developed and used for numerical simulation to predict the hot spot cooling performance. The hot spot is cooled by localized cross channels. The pressure drop, thermal resistance and effects of hot spot heat flux and fluid flow velocity on the cooling of on-chip hot spots, are investigated in detail.

scholarly journals Deletion Formation Between the Two Salmonella typhimurium Flagellin Genes Encoded on the Mini F Plasmid: Escherichia coli ssb Alleles Enhance Deletion Rates and Change Hot-Spot Preference for Deletion Endpoints

Genetics ◽  
1997 ◽  
Vol 145 (3) ◽  
pp. 563-572 ◽  
Author(s):  
Takafumi Mukaihara ◽  
Masatoshi Enomoto
Keyword(s):  
Escherichia Coli ◽  
Salmonella Typhimurium ◽  
Hot Spots ◽  
Hot Spot ◽  
Direct Repeats ◽  
Replication Slippage ◽  
Detection Systems ◽  
Deletion Formation ◽  
Homologous Sequences ◽  
Deletion Detection

Deletion formation between the 5′-mostly homologous sequences and between the 3′-homeologous sequences of the two Salmonella typhimurium flagellin genes was examined using plasmid-based deletion-detection systems in various Escherichia coli genetic backgrounds. Deletions in plasmid pLC103 occur between the 5′ sequences, but not between the 3′ sequences, in both RecA-independent and RecA-dependent ways. Because the former is predominant, deletion formation in a recA background depends on the length of homologous sequences between the two genes. Deletion rates were enhanced 30- to 50-fold by the mismatch repair defects, mutS, mutL and uvrD, and 250-fold by the ssb-3 allele, but the effect of the mismatch defects was canceled by the ΔrecA allele. Rates of the deletion between the 3′ sequences in plasmid pLC107 were enhanced 17- to 130-fold by ssb alleles, but not by other alleles. For deletions in pLC107, 96% of the endpoints in the recA+ background and 88% in ΔrecA were in the two hot spots of the 60- and 33-nucleotide (nt) homologous sequences, whereas in the ssb-3 background >50% of the endpoints were in four- to 14-nt direct repeats dispersed in the entire 3′ sequences. The deletion formation between the homeologous sequences is RecA-independent but depends on the length of consecutive homologies. The mutant ssb allele lowers this dependency and results in the increase in deletion rates. Roles of mutant SSB are discussed with relation to misalignment in replication slippage.

scholarly journals Does Entrepreneurship Contribute to Innovation Performance When Considering Spatial Spillover Effects? Evidence From the Automobile Industrial Cluster in China

SAGE Open ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 215824402098299
Author(s):  
Haishi Li ◽  
Xiangyi Xu ◽  
Shuaishuai Li
Keyword(s):  
Automobile Industry ◽  
Hot Spots ◽  
Hot Spot ◽  
Empirical Support ◽  
Temporal Patterns ◽  
Spillover Effects ◽  
Industrial Clusters ◽  
Innovation Performance ◽  
Spatial Spillover ◽  
Spatio Temporal

Entrepreneurship, as one of the important factors to promote industrial innovation, is closely related to the development of the regional economy. Based on the methods of Kernel density and standard deviation ellipse, this article presents the spatio-temporal patterns of entrepreneurship and innovation performance. The article also examines the spatial spillover mechanism of entrepreneurship on innovation performance by establishing spatial Durbin models. The heterogeneous results of the spatial regression models in six clusters are also discussed. The final results show that the spatio-temporal patterns of entrepreneurship are gradually presenting three major hot spots and two secondary hot spots while the spatio-temporal patterns of innovation performance are presenting four major hot spots and a secondary hot spot; the spatial distribution of both entrepreneurship and innovation performance are changing regularly; the spillover effects of entrepreneurship and innovation performance are both significant; the spatial spillover mechanisms in six automobile industrial clusters are different. The results can provide empirical support for decision-making in the automobile industry in China in the future.

scholarly journals Prediction of Hourly Effect of Land Use on Crime

2018 ◽  
Vol 8 (1) ◽  
pp. 16 ◽  
Author(s):  
Irina Matijosaitiene ◽  
Peng Zhao ◽  
Sylvain Jaume ◽  
Joseph Gilkey Jr
Keyword(s):  
Machine Learning ◽  
Land Use ◽  
Logistic Regression ◽  
Hot Spots ◽  
Urban Areas ◽  
Prediction Models ◽  
Hot Spot ◽  
Time Range ◽  
Land Uses ◽  
Police Departments

Predicting the exact urban places where crime is most likely to occur is one of the greatest interests for Police Departments. Therefore, the goal of the research presented in this paper is to identify specific urban areas where a crime could happen in Manhattan, NY for every hour of a day. The outputs from this research are the following: (i) predicted land uses that generates the top three most committed crimes in Manhattan, by using machine learning (random forest and logistic regression), (ii) identifying the exact hours when most of the assaults are committed, together with hot spots during these hours, by applying time series and hot spot analysis, (iii) built hourly prediction models for assaults based on the land use, by deploying logistic regression. Assault, as a physical attack on someone, according to criminal law, is identified as the third most committed crime in Manhattan. Land use (residential, commercial, recreational, mixed use etc.) is assigned to every area or lot in Manhattan, determining the actual use or activities within each particular lot. While plotting assaults on the map for every hour, this investigation has identified that the hot spots where assaults occur were ‘moving’ and not confined to specific lots within Manhattan. This raises a number of questions: Why are hot spots of assaults not static in an urban environment? What makes them ‘move’—is it a particular urban pattern? Is the ‘movement’ of hot spots related to human activities during the day and night? Answering these questions helps to build the initial frame for assault prediction within every hour of a day. Knowing a specific land use vulnerability to assault during each exact hour can assist the police departments to allocate forces during those hours in risky areas. For the analysis, the study is using two datasets: a crime dataset with geographical locations of crime, date and time, and a geographic dataset about land uses with land use codes for every lot, each obtained from open databases. The study joins two datasets based on the spatial location and classifies data into 24 classes, based on the time range when the assault occurred. Machine learning methods reveal the effect of land uses on larceny, harassment and assault, the three most committed crimes in Manhattan. Finally, logistic regression provides hourly prediction models and unveils the type of land use where assaults could occur during each hour for both day and night.

scholarly journals Research of Personalized Recommendation Technology Based on Knowledge Graphs

2021 ◽  
Vol 11 (15) ◽  
pp. 7104
Author(s):  
Xu Yang ◽  
Ziyi Huan ◽  
Yisong Zhai ◽  
Ting Lin
Keyword(s):  
Neural Network ◽  
Hot Spot ◽  
Experimental Results ◽  
Graph Representation ◽  
Personalized Recommendation ◽  
Knowledge Graph ◽  
Learning Technology ◽  
Data Set ◽  
Model Based ◽  
Knowledge Graphs

Nowadays, personalized recommendation based on knowledge graphs has become a hot spot for researchers due to its good recommendation effect. In this paper, we researched personalized recommendation based on knowledge graphs. First of all, we study the knowledge graphs’ construction method and complete the construction of the movie knowledge graphs. Furthermore, we use Neo4j graph database to store the movie data and vividly display it. Then, the classical translation model TransE algorithm in knowledge graph representation learning technology is studied in this paper, and we improved the algorithm through a cross-training method by using the information of the neighboring feature structures of the entities in the knowledge graph. Furthermore, the negative sampling process of TransE algorithm is improved. The experimental results show that the improved TransE model can more accurately vectorize entities and relations. Finally, this paper constructs a recommendation model by combining knowledge graphs with ranking learning and neural network. We propose the Bayesian personalized recommendation model based on knowledge graphs (KG-BPR) and the neural network recommendation model based on knowledge graphs(KG-NN). The semantic information of entities and relations in knowledge graphs is embedded into vector space by using improved TransE method, and we compare the results. The item entity vectors containing external knowledge information are integrated into the BPR model and neural network, respectively, which make up for the lack of knowledge information of the item itself. Finally, the experimental analysis is carried out on MovieLens-1M data set. The experimental results show that the two recommendation models proposed in this paper can effectively improve the accuracy, recall, F1 value and MAP value of recommendation.

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