scholarly journals RF Performance of Si/SiGe MODFETs: A Simulation Study

VLSI Design ◽  
1998 ◽  
Vol 8 (1-4) ◽  
pp. 325-330
Author(s):  
S. Roy ◽  
A. Asenov ◽  
S. Babiker ◽  
J. R. Barker ◽  
S. P. Beaumont
Keyword(s):  
State Of The Art ◽  
Strong Dependence ◽  
Intrinsic Noise ◽  
Performance Potential ◽  
Figures Of Merit ◽  
Analysis Technique ◽  
Channel Velocity ◽  
The Difference ◽  
Rf Performance ◽  
Gate Region

The microwave performance potential of Si/SiGe pseudomorphic MODFETs are studied, in comparison to state of the art InGaAs pseudomorphic HEMTs. Both devices have equivalent structures corresponding to a physical HEMT used for calibration. We use an RF analysis technique based on transient Monte Carlo simulations to estimate the intrinsic noise figures, the RF figures of merit fT and fmax, and the effect of contact and gate resistances. Both devices exhibit velocity overshoot below the gate region. It is shown that the difference in noise figures and fT values can be mainly attributed to differences in device channel velocity, fmax exhibits a strong dependence on device contact resistance, eroding some of the performance advantage of the pseudomorphic HEMT.

scholarly journals Smoke recognition network based on dynamic characteristics

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142092566
Author(s):  
Dahan Wang ◽  
Sheng Luo ◽  
Li Zhao ◽  
Xiaoming Pan ◽  
Muchou Wang ◽  
...  
Keyword(s):  
Dynamic Characteristics ◽  
State Of The Art ◽  
The State ◽  
Detection Accuracy ◽  
Static Characteristics ◽  
Good Tool ◽  
Early Signal ◽  
Fuzzy Objects ◽  
The Difference ◽  
Smoke Recognition

Fire is a fierce disaster, and smoke is the early signal of fire. Since such features as chrominance, texture, and shape of smoke are very special, a lot of methods based on these features have been developed. But these static characteristics vary widely, so there are some exceptions leading to low detection accuracy. On the other side, the motion of smoke is much more discriminating than the aforementioned features, so a time-domain neural network is proposed to extract its dynamic characteristics. This smoke recognition network has these advantages:(1) extract the spatiotemporal with the 3D filters which work on dynamic and static characteristics synchronously; (2) high accuracy, 87.31% samples being classified rightly, which is the state of the art even in a chaotic environments, and the fuzzy objects for other methods, such as haze, fog, and climbing cars, are distinguished distinctly; (3) high sensitiveness, smoke being detected averagely at the 23rd frame, which is also the state of the art, which is meaningful to alarm early fire as soon as possible; and (4) it is not been based on any hypothesis, which guarantee the method compatible. Finally, a new metric, the difference between the first frame in which smoke is detected and the first frame in which smoke happens, is proposed to compare the algorithms sensitivity in videos. The experiments confirm that the dynamic characteristics are more discriminating than the aforementioned static characteristics, and smoke recognition network is a good tool to extract compound feature.

Critical Technical Issues in High Voltage SiC Power Devices

2008 ◽  
Vol 600-603 ◽  
pp. 895-900 ◽  
Author(s):  
Anant K. Agarwal ◽  
Albert A. Burk ◽  
Robert Callanan ◽  
Craig Capell ◽  
Mrinal K. Das ◽  
...  
Keyword(s):  
Threshold Voltage ◽  
Carrier Mobility ◽  
Negative Charge ◽  
State Of The Art ◽  
Power Devices ◽  
Power Mosfets ◽  
Large Numbers ◽  
Technical Issues ◽  
The Difference ◽  
Difficult Issue

In this paper, we review the state of the art of SiC switches and the technical issues which remain. Specifically, we will review the progress and remaining challenges associated with SiC power MOSFETs and BJTs. The most difficult issue when fabricating MOSFETs has been an excessive variation in threshold voltage from batch to batch. This difficulty arises due to the fact that the threshold voltage is determined by the difference between two large numbers, namely, a large fixed oxide charge and a large negative charge in the interface traps. There may also be some significant charge captured in the bulk traps in SiC and SiO2. The effect of recombination-induced stacking faults (SFs) on majority carrier mobility has been confirmed with 10 kV Merged PN Schottky (MPS) diodes and MOSFETs. The same SFs have been found to be responsible for degradation of BJTs.

scholarly journals A social trust and preference segmentation-based matrix factorization recommendation algorithm

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Wei Peng ◽  
Baogui Xin
Keyword(s):  
Matrix Factorization ◽  
Social Trust ◽  
State Of The Art ◽  
User Preference ◽  
Social Recommendation ◽  
Recommendation Algorithm ◽  
Commercial Activities ◽  
Trust Relationships ◽  
Recommendation Algorithms ◽  
The Difference

AbstractA recommendation can inspire potential demands of users and make e-commerce platforms more intelligent and is essential for e-commerce enterprises’ sustainable development. The traditional social recommendation algorithm ignores the following fact: the preferences of users with trust relationships are not necessarily similar, and the consideration of user preference similarity should be limited to specific areas. To solve these problems mentioned above, we propose a social trust and preference segmentation-based matrix factorization (SPMF) recommendation algorithm. Experimental results based on the Ciao and Epinions datasets show that the accuracy of the SPMF algorithm is significantly superior to that of some state-of-the-art recommendation algorithms. The SPMF algorithm is a better recommendation algorithm based on distinguishing the difference of trust relations and preference domain, which can support commercial activities such as product marketing.

scholarly journals RBP: a website fingerprinting obfuscation method against intelligent fingerprinting attacks

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Tao Luo ◽  
LiangMin Wang ◽  
ShangNan Yin ◽  
Hao Shentu ◽  
Hui Zhao
Keyword(s):  
Data Security ◽  
Arrival Time ◽  
State Of The Art ◽  
Web Security ◽  
Security And Privacy ◽  
Low Delay ◽  
Defense Technology ◽  
The Difference ◽  
Bandwidth Overhead ◽  
Traffic Analysis Attack

AbstractEdge computing has developed rapidly in recent years due to its advantages of low bandwidth overhead and low delay, but it also brings challenges in data security and privacy. Website fingerprinting (WF) is a passive traffic analysis attack that threatens website privacy which poses a great threat to user’s privacy and web security. It collects network packets generated while a user accesses website, and then uses a series of techniques to discover patterns of network packets to infer the type of website user accesses. Many anonymous networks such as Tor can meet the need of hide identity from users in network activities, but they are also threatened by WF attacks. In this paper, we propose a website fingerprinting obfuscation method against intelligent fingerprinting attacks, called Random Bidirectional Padding (RBP). It is a novel website fingerprinting defense technology based on time sampling and random bidirectional packets padding, which can covert the real packets distribution to destroy the Inter-Arrival Time (IAT) features in the traffic sequence and increase the difference between the datasets with random bidirectional virtual packets padding. We evaluate the defense against state-of-the-art website fingerprinting attacks in real scenarios, and show its effectiveness.

scholarly journals Improving Lidar Windshear Detection Efficiency by Removal of “Gentle Ramps”

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1539
Author(s):  
Kai Kwong Hon ◽  
Pak Wai Chan
Keyword(s):  
Detection Efficiency ◽  
State Of The Art ◽  
Detection Algorithm ◽  
Doppler Lidar ◽  
Hit Rate ◽  
Glide Path ◽  
The World ◽  
Alerting System ◽  
The Difference ◽  
Hong Kong International Airport

The Doppler Lidar windshear alerting system at the Hong Kong International Airport (HKIA), the first of its kind in the world, has been in operation since 2006. This paper reports on an enhancement to the automatic windshear detection algorithm at HKIA, which aims at filtering out alerts associated with smoother headwind changes spread over longer distances along the aircraft glide path (called “gentle ramps”) which may nonetheless exceed the well-established alerting threshold. Real-time statistics are examined over a 46-month study period between March 2016 and December 2019, covering a total of 2,017,440 min and over 1500 quality-controlled pilot reports of windshear (PIREP). The “gentle ramp removal” (GRR) function is able to effectively cut down the alert duration over the 5 major runway corridors, inclusive of both landing and take-off, which together account for over 98% of the PIREP received at HKIA during the study period. In all 5 runway corridors this is achieved with a proportionately smaller decrease—even with no changes in 2 cases—in the hit rate, highlighting the efficiency of the GRR function. The difference in statistical behaviour across the runway corridors also echo literature findings about the differences in length scale of wind disturbances at different locations within HKIA. This study serves as a unique documentation of the state-of-the-art in operational Lidar windshear detection and can provide useful reference to airports and aviation meteorologists around the world.

scholarly journals PENGARUH LATIHAN KNEE TUCK JUMP DAN LATIHAN HALF SQUAT JUMP TERHADAP KEMAMPUAN SMASH KEDENG DALAM PERMAINAN SEPAKTAKRAW

2020 ◽  
Vol 11 (3) ◽  
pp. 117
Author(s):  
Heriansyah Heriansyah ◽  
Suhartiwi Suhartiwi
Keyword(s):  
Data Analysis ◽  
Random Sampling ◽  
Male Students ◽  
Squat Jump ◽  
Significance Level ◽  
Jump Training ◽  
Analysis Technique ◽  
Significant Difference ◽  
Experiment Method ◽  
The Difference

This study aims to determine the extent of the difference in effect between knee tuck jump and half squat jump training on the ability to smash kedeng in sepaktakraw games. By using the field experiment method. The population used is male students of Southeast Sulawesi SMANKO with a sample of 60 people taken by Proposive random sampling. The data analysis technique used is the t-test at 95% significance level. The results showed that; (1) There is a significant effect of knee tuck jump training on the ability to smash kedeng in sepaktakraw games on Southeast Sulawesi SMANKO students, proven to = 13,446> tt = 2,045. There is a significant effect of half squat jump training on the ability of the Kedeng smash in sepaktakraw games on Southeast Sulawesi SMANKO students, proven to = 10.478> tt = 2.045. There is a significant difference in effect between training on the ability to smash kedeng in sepaktakraw games on Southeast Sulawesi SMANKO students, proven, to = 9,970> tt = 2,000.

scholarly journals An Experimental Analysis of Model Compression Techniques for Object Detection

2020 ◽  
Author(s):  
Andrey De Aguiar Salvi ◽  
Rodrigo Coelho Barros
Keyword(s):  
Object Detection ◽  
Experimental Analysis ◽  
State Of The Art ◽  
Neural Architecture ◽  
Model Compression ◽  
Processing Power ◽  
Benchmark Datasets ◽  
The Difference ◽  
And Performance ◽  
Consumption Constraints

Recent research on Convolutional Neural Networks focuses on how to create models with a reduced number of parameters and a smaller storage size while keeping the model’s ability to perform its task, allowing the use of the best CNN for automating tasks in limited devices, with reduced processing power, memory, or energy consumption constraints. There are many different approaches in the literature: removing parameters, reduction of the floating-point precision, creating smaller models that mimic larger models, neural architecture search (NAS), etc. With all those possibilities, it is challenging to say which approach provides a better trade-off between model reduction and performance, due to the difference between the approaches, their respective models, the benchmark datasets, or variations in training details. Therefore, this article contributes to the literature by comparing three state-of-the-art model compression approaches to reduce a well-known convolutional approach for object detection, namely YOLOv3. Our experimental analysis shows that it is possible to create a reduced version of YOLOv3 with 90% fewer parameters and still outperform the original model by pruning parameters. We also create models that require only 0.43% of the original model’s inference effort.

Effects Of Gettering On Device Characteristics

1996 ◽  
Vol 442 ◽  
Author(s):  
Mitsuhiro Horikawa ◽  
Akihiko Yaoita ◽  
Tsuyoshi Nagata ◽  
Tomohisa Kitano
Keyword(s):  
Heat Treatment ◽  
State Of The Art ◽  
Annealing Process ◽  
Clean Room ◽  
Data Retention ◽  
Effective Technique ◽  
Slow Cooling ◽  
Metal Impurities ◽  
The Difference ◽  
Metallic Impurities

AbstractEffective methods of gettering metallic impurities were proposed. To achieve effective gettering, an annealing process to induce gettering was modified taking fundamental gettering steps and the difference in the gettering mechanism into account. As the concentration of heavy metal is below solubility in a state-of-the-art clean room, a combination of segregation type gettering and slow cooling heat treatment is an effective technique to remove metal impurities from the device active region. Using this technique, DRAM device characteristics such as leakage current and data retention time can be improved.

scholarly journals A Multiscale Chaotic Feature Extraction Method for Speaker Recognition

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Jiang Lin ◽  
Yi Yumei ◽  
Zhang Maosheng ◽  
Chen Defeng ◽  
Wang Chao ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Speaker Recognition ◽  
Extraction Method ◽  
State Of The Art ◽  
Recognition System ◽  
Nonlinear Dynamic Model ◽  
Feature Extraction Method ◽  
Analysis Technique ◽  
Recognition Systems ◽  
Environment Noise

In speaker recognition systems, feature extraction is a challenging task under environment noise conditions. To improve the robustness of the feature, we proposed a multiscale chaotic feature for speaker recognition. We use a multiresolution analysis technique to capture more finer information on different speakers in the frequency domain. Then, we extracted the speech chaotic characteristics based on the nonlinear dynamic model, which helps to improve the discrimination of features. Finally, we use a GMM-UBM model to develop a speaker recognition system. Our experimental results verified its good performance. Under clean speech and noise speech conditions, the ERR value of our method is reduced by 13.94% and 26.5% compared with the state-of-the-art method, respectively.

A Historical Overview of Design Analyses and Experimental Observations of Ratcheting Phenomenon

2020 ◽  
Author(s):  
Jean Macedo ◽  
Stéphane Chapuliot ◽  
Jean-Michel Bergheau ◽  
Eric Feulvarch ◽  
Olivier Ancelet ◽  
...  
Keyword(s):  
Cyclic Loading ◽  
State Of The Art ◽  
Constitutive Models ◽  
Experimental Tests ◽  
Design Codes ◽  
Historical Overview ◽  
Design Rules ◽  
Current Article ◽  
The Difference ◽  
Design Analyses

Abstract In order to investigate the ratcheting behavior and to determine new design rules, some experimental tests were conducted in many countries in the last decades. In France, some tests were carried out under mechanical or thermal cyclic loading to examine this risk. The first section of the current article is addressed to the state of the art concerning the ratcheting effects. The difference between Local and Global Ratcheting is clarified. The second section is dedicated to the experimental observations of ratcheting. The following section describes the constitutive models which are able to simulate material/structural ratcheting responses. The models presented are Linear Kinematic, Armstrong-Frederick, Chaboche, Ohno-Wang and Chen-Jiao-Kim. Finally, the ratcheting rules in design codes are exposed. Both simple and complex rules are presented.

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