Miracle-dz/UniFAR-FTUs huggingface dataset:
Study on off-state hot carrier degradation and recovery of NMOSFET in SWD circuits of DRAM

We investigated threshold voltage degradation and recovery of short channel NMOS transistors in the sub wordline driver (SWD), where the source of NMOS transistors was biased with negative voltage during off-state. We found that the threshold voltage degradation occurred by the off-state hot carrier stress. The gate of NMOS transistor in sub wordline driver (SWD) in the off-state is under the subthreshold region (0<VGS<VT) due to the negative bias voltage applied to the source terminal. At this situation if a high voltage is applied to the drain, the subthreshold drain current increases due to the DIBL effect. Furthermore, hot carriers with higher energies generate interface traps near the dielectric/Si interface of the MOSFET. These hot carrier degradation caused the positive shift in the threshold voltage. Aforementioned degradation could be recovered by baking with bias. Furthermore, the time of such a recovery was shortened when the gate terminal was floating.
Multi-rate Signal Processing for Software Defined Radio (SDR) and Realize on FPGA

This article introduces the inevitability of multi-rate signal processing in the application of SDR, and then describes the hardware requirements for the realization of multi-rate signal processing in SDR, as well as its development in this stage. It mainly analyses how to realize the software part of multi-rate signal processing in FPGA, and can achieve the optimal programs and methods by comparing several kinds of different schemes on the rate of transformation. At the same time, we can get the simulation map of the 1-order CIC interpolation and the 1-order CIC extraction, respectively. And then through the analysis to the interpolation and extraction of the scores of times, we will obtain the realization of the program. Finally, download the 1-order CIC interpolation and extraction to FPGA and get the realization of multi-rate signals through authentication by the logic analyzer.
Wearable Computers in Human Perspective: The Decision Process of Innovation Acceptance with User Issues and Concerns

— Wearable computers and smart clothing started its development since the late 20 th century. Yet, it has not been widely used until the present, compared to other technological innovations that quickly gained successful diffusion. In view of this, the decision process of accepting or rejecting an innovation enumerated by Everett Rogers is reviewed to understand how target users may perceive wearable computers as an innovative technology. User-centered researches were also surveyed where user concerns and preferences with the said technology, involving cognitive, physical and social aspects that influence the individual’s decisions are extracted from. The primary goal of this study is to promote a higher rate of acceptance for wearable computers through understanding human behavior and attitude towards technological innovations while individuals go through the process of decision-making prior to utilization, and integrating the identified human issues in the design and development of wearable computers.
A Model for Cortical Rewiring Following Deafferentation and Focal Stroke

It is still unclear to what extent structural plasticity in terms of synaptic rewiring is the cause for cortical remapping after a lesion. Recent two-photon laser imaging studies demonstrate that synaptic rewiring is persistent in the adult brain and is dramatically increased following brain lesions or after a loss of sensory input (cortical deafferentation). We use a recurrent neural network model to study the time course of synaptic rewiring following a peripheral lesion. For this, we represent axonal and dendritic elements of cortical neurons to model synapse formation, pruning and synaptic rewiring. Neurons increase and decrease the number of axonal and dendritic elements in an activity-dependent fashion in order to maintain their activity in a homeostatic equilibrium. In this study we demonstrate that synaptic rewiring contributes to neuronal homeostasis during normal development as well as following lesions. We show that networks in homeostasis, which can therefore be considered as adult networks, are much less able to compensate for a loss of input. Interestingly, we found that paused stimulation of the networks are much more effective promoting reorganization than continuous stimulation. This can be explained as neurons quickly adapt to this stimulation whereas pauses prevents a saturation of the positive stimulation effect. These findings may suggest strategies for improving therapies in neurologic rehabilitation.
Mean Field Theory Applied to the HighT c Superconductivity

We propose an effective transverse Ising model (TIM) as a means to treat both metallic and hightemperature superconductivity. The model is inspired by features which are present in the GorterCasimir two-fluid model of superconductivity, but it encompasses also the formalism used to treat the phase transitions in hydrogen-bonded ferroelectrics. We treat the model in the random-phase approximation, and as a consequence, the superconducting state reveals a structure of a gas of elementary excitations where the energy gap appears in a quite natural way.
Pedestrian motion classification on omnidirectional treadmill

In this paper, the direction integrated pedestrian motion classification method on the omnidirectional treadmill is proposed based on a navigation algorithm. The virtual reality technology is widely applied to a military training in recent years since previous drill conducted outside is relatively cost and time inefficient. Among several roles in training system, motion recognition including direction determination is essential, but the classification result by a classifier only becomes a problem. In order to improve the classification accuracy, navigational error is obtained using an EKF-ZUPT algorithm, and the direction is estimated from the corrected position by previous states. Aside from the determined direction, features are extracted, and the learning and collection steps are conducted. The final recognition results are acquired from the combination of direction and a classifier. The experimental results show that motion classification accuracy of the proposed algorithm has over 90%.
Network intrusion detection and prevention middlebox management in SDN

In traditional networks, it is difficult to manage the distributed detection and prevention nodes of IDS and IPS due to the laborious manual deployment and independent configuration. Software defined networking (SDN) provides a flexible approach to control the underlying network infrastructures efficiently. However, the OpenFlow flow table is too simple to provide complex functions with the match-action style processing. To support more functionalities, in this paper, we propose a middlebox management architecture with SDN - OpenMiddlebox, by extending OpenFlow to support middleboxes with ClickOS virtual machines (VM), so that programmable middleboxes could be deployed and managed in switches with fast booted ClickOS VMs flexibly. We then design automatic deployment and update schemes of network intrusion detection and prevention middleboxes with the centralized controller. The evaluation results show that OpenMiddlebox could manage the distributed middleboxes efficiently and is scalable to large networks, and the centralized control also improves the network intrusion detection and prevention accuracy.
Stable emergent agent distributions under sensing and travel delays

In order for a team of cooperating agents to achieve a group goal (such as searching for targets, monitoring an environment, etc.) those agents must be able to share information and achieve some level of coordination. Since realistic methods of communication between agents have limited range and speed, the agents¿ decision-making strategies must operate with incomplete and outdated information. Moreover, in many situations the agents must travel to particular locations in order to perform various tasks, and so there will also be a delay between any particular decision and its effect. In this paper we develop an asynchronous framework that models the behavior of a group of agents that is spatially distributed across a predefined area of interest. We derive general conditions under which the group is guaranteed to converge to a specific distribution within the environment without any form of central control and despite unknown but bounded delays in sensing and travel. The achieved distribution is optimal in the sense that the proportion of agents allocated over each area matches the relative importance of that area. Finally, based on the derived conditions, we design a cooperative control scheme for a multi-agent surveillance problem. Via Monte Carlo simulations we show how sensing and travel delays and the degree of cooperation between agents affect the rate at which they achieve the desired coverage of the region under surveillance.
An Information-Theoretic Security Evaluation of a Class of Randomized Encryption Schemes

Randomized encryption techniques, where randomness is used for security enhancement, are considered. We focus on the case where the encrypted data experiences noise, e.g., is transmitted over a noisy channel, within the encoding-encryption paradigm, where the data is first encoded for error correction, before being encrypted for security. We assume that the ciphertext is subject to a corruption equivalent to its transmission through a binary symmetric channel with known probability of error. The enhanced security is based on a dedicated wire-tap channel coding that introduces extra randomness, combined with that of the communication channel noise. The encryption is based on a block-by-block modulo 2 addition between an encoded message vector and a pseudorandom vector. The goal is to enhance the protection of the secret key employed in the encryption algorithm. Security evaluations of the model are performed employing an information-theoretic approach. Assuming both a passive and an active attacker, we show that there is a threshold before which the wire-tap encoder guarantees an information-theoretic security (during which the equivocation of the secret key is increased), and after which the uncertainty reduces, entering a regime in which a computational security analysis is needed for estimating the complexity resistance against the secret key recovery.
Cognitive Science Approach to Shogi Playing Processes (1) ——Some Results on Memory Experiments

人間の問題解決の認知過程については数多くの研究が行われてきた. ゲームおよびゲーム理論は昔 から人間の問題解決行動の研究において重要な役割を演じてきた. 認知研究の題材にゲームを用いる ことの利点は,ゲームが良定義問題で対戦による評価が容易なことである. チェスで最もよく知られ た認知実験は局面の記憶に関するもので De Grootによって行われた. この研究を継いだ Simonと Chaseはチャンクという概念を用いてエキスパートの認知能力を説明した. チャンクは一種の情報の かたまりで,チェスでいうとチェス盤上の典型的な駒の配置パターンのかたまりをチャンクと呼んで いる. 彼らは強いプレイヤは弱いプレイヤよりも広い配置パターンをチャンクとして記憶しているこ とを示した. 将棋の認知研究の第 1歩として,我々はまずチェスで行われた認知実験を追試してみる ことにした. チェスと将棋には認識の点からいくつかの違いがあるので,この追試実験を一度は実施 することが必要だと考えた. 本論文では将棋を対象とした時間無制限と時間制限の記憶実験を行った. 強いプレイヤが弱いプレイヤより成績が良いこと,すなわち広い配置パターンをチャンクとして記憶 しているというチェスとほぼ同様の結果が得られた.
Individual relationship education program as a prevention method for intimate partner violence

ABSTRACT Intimate partner violence (IPV) can have detrimental effects on the lives of partners and children. The authors examined the effectiveness of a relationship education program, titled Within My Reach (WMR), to prevent IPV in a naturalistic nonrandomized adult sample. The sample included participants who endorsed no physical violence in their relationship and no to very low controlling behaviors at pretest. At 6-month follow-up the participants in the WMR group reported statistically significant fewer controlling behaviors than the comparison group (d = .45). Although there were no statistically significant differences between the WMR and comparison group in physical violence at 6-month follow-up, the findings were in still favor of the WMR group (d = .15).
Development of nonlinear filter bank system for real-time beautification of facial video using GPGPU

A nonlinear filter bank named as an ∈-filter bank is implemented for real-time processing of video in order to make the skin in human faces look beautified. General-purpose computing on graphics processing units (GPGPU) is utilized for this real-time implementation. GPGPU has quite high computational power, and the facial beautification system using the ∈-filter bank is efficiently implemented in real time, although the amount of the computation of this system is large. A new language is developed to design and edit the ∈-filter bank, which enables this system to be edited conveniently by trial and error, reflecting the user's request concerning the smoothness of skin. Skin detection is also applied to limit the area to be processed within the face area, so that the other areas than the face, such as hair and background, are not influenced by the system. Experimental results verify its high performance.
Influence Discovery in Semantic Networks: An Initial Approach

Assessing the influence between concepts, which include people, physical objects, as well as theoretical ideas, plays a crucial role in understanding and discovering knowledge. Despite the huge amount of literature on knowledge discovery in semantic networks, there has been little attempt to fully classify and investigate the influence, which also includes causality, of a semantic entity on another one as dynamical entities. In this paper we will introduce an approach to discover and assess influence among nodes in a semantic network, with the aim to provide a tool to identify its type and direction. Even though this is still being developed, the preliminary evaluation shows promising and interesting results.
Learning Formulation and Transformation Rules for Multilingual Named Entities

This paper investigates three multilingual named entity corpora, including named people, named locations and named organizations. Frequency-based approaches with and without dictionary are proposed to extract formulation rules of named entities for individual languages, and transformation rules for mapping among languages. We consider the issues of abbreviation and compound keyword at a distance. Keywords specify not only the types of named entities, but also tell out which parts of a named entity should be meaning-translated and which part should be phoneme-transliterated. An application of the results on cross language information retrieval is also shown.
A lattice coding based non-orthogonal multiple access scheme

Non-orthogonal multiple access (NOMA) employing nested lattice codes is investigated in a downlink transmission scenario. The fundamental idea is the multiple access scheme via Compute-and-Forward framework, which produces an equivalent MIMO channel such that multiuser detection can be performed. Approaches including the successive lattice decoding of linear functions of transmitted messages by cancelling decoded equations and ML detection are investigated. Power allocation as a precoding scheme as well as an allocation strategy are proposed to deal with channel fadings and to enhance system throughput.
Bacterial Communities in the Rhizosphere of Amilaceous Maize (Zea mays L.) as Assessed by Pyrosequencing

Maize (Zea mays L.) is the staple diet of the native peasants in the Quechua region of the Peruvian Andes who continue growing it in small plots called chacras following ancestral traditions. The abundance and structure of bacterial communities associated with the roots of amilaceous maize has not been studied in Andean chacras. Accordingly, the main objective of this study was to describe the rhizospheric bacterial diversity of amilaceous maize grown either in the presence or the absence of bur clover cultivated in soils from the Quechua maize belt. Three 16S rRNA gene libraries, one corresponding to sequences of bacteria from bulk soil of a chacra maintained under fallow conditions, the second from the rhizosphere of maize-cultivated soils, and the third prepared from rhizospheric soil of maize cultivated in intercropping with bur clover were examined using pyrosequencing tags spanning the V4 and V5 hypervariable regions of the gene. A total of 26031 sequences were found that grouped into 5955 distinct operational taxonomic units which distributed in 309 genera. The numbers of OTUs in the libraries from the maize-cultivated soils were significantly higher than those found in the libraries from bulk soil. One hundred ninety seven genera were found in the bulk soil library and 234 and 203 were in those from the maize and maize/bur clover-cultivated soils. Sixteen out of the 309 genera had a relative abundance higher than 0.5% and the were (in decreasing order of abundance) Gp4, Gp6, Flavobacterium, Subdivision3 genera incertae sedis of the Verrucomicrobia phylum, Gemmatimonas, Dechloromonas, Ohtaekwangia, Rhodoferax, Gaiella, Opitutus, Gp7, Spartobacteria genera incertae sedis, Terrimonas, Gp5, Steroidobacter and Parcubacteria genera incertae sedis. Genera Gp4 and Gp6 of the Acidobacteria, Gemmatimonas and Rhodoferax were the most abundant in bulk soil, whereas Flavobacterium, Dechloromonas and Ohtaekwangia were the main genera in the rhizosphere of maize intercropped with bur clover, and Gp4, Subdivision3 genera incertae sedis of phylum Verrucomicrobia, Gp6 and Rhodoferax were the main genera in the rhizosphere of maize plants. Taken together, our results suggest that bur clover produces specific changes in rhizospheric bacterial diversity of amilaceous maize plants.
Transmission Scheduling in Wireless Networks with SINR Constraints

Despite all the work being done so far in scheduling for wireless networks, the transmission scheduling problem with specific constraints is not yet fully understood and explored. In this work, we find the minimum number of time-slots (or channels) required in any given network and the corresponding transmitting powers, such that all communication requests are being processed correctly, while fulfilling specific constraints that comply with the Quality of Service (QoS) requirements for successful transmissions. More specifically, in this paper, we formulate the optimization problem as a Mixed Integer Program (MIP) and solve the mathematical formulation by a Branch-and-Bound algorithm. Our computational study shows that our methodology is capable of solving exactly networks of varying size but can also provide a near optimal heuristic solution for the hardest instances. The results can be used as bounds for the study of distributed algorithms that aim for the optimal scheduling and power assignment without information about the whole network. Numerical examples are provided to illustrate the validity of our proposed methodology.
Scalable Analytics for IaaS Cloud Availability

In a large Infrastructure-as-a-Service (IaaS) cloud, component failures are quite common. Such failures may lead to occasional system downtime and eventual violation of Service Level Agreements (SLAs) on the cloud service availability. The availability analysis of the underlying infrastructure is useful to the service provider to design a system capable of providing a defined SLA, as well as to evaluate the capabilities of an existing one. This paper presents a scalable, stochastic model-driven approach to quantify the availability of a large-scale IaaS cloud, where failures are typically dealt with through migration of physical machines among three pools: hot (running), warm (turned on, but not ready), and cold (turned off). Since monolithic models do not scale for large systems, we use an interacting Markov chain based approach to demonstrate the reduction in the complexity of analysis and the solution time. The three pools are modeled by interacting sub-models. Dependencies among them are resolved using fixed-point iteration, for which existence of a solution is proved. The analytic-numeric solutions obtained from the proposed approach and from the monolithic model are compared. We show that the errors introduced by interacting sub-models are insignificant and that our approach can handle very large size IaaS clouds. The simulative solution is also considered for the proposed model, and solution time of the methods are compared.
Interruptability Prediction Using Motion Detection

People are subjected to a multitude of interruptions. This paper introduces an approach to predict a person’s presence and interruptability in an office-like environment. To determine these two states we record data as audio, motion detection, and the time of the day representing a person’s context. We show that motion detection data outperforms audio data both in presence and interruptability prediction.
Właściwości psychometryczne kwestionariusza do diagnozy osobowości typu D (DS14) szacowane na podstawie badania pacjentów z przebytym zawałem serca

Wstep. W ostatnich latach rozne czynniki psychologiczne rozwazano jako czynniki ryzyka choroby wiencowej. Wyniki badan wskazują, ze osobowośc typu D wiąze sie z zaburzeniami depresyjnymi, izolacją spoleczną, wyzszą liczbą powtornych zawalow oraz wiekszą śmiertelnością. Narzedzie do badania osobowości typu D stworzono na podstawie danych uzyskanych w populacji belgijskich pacjentow kardiologicznych, natomiast nie ma wystarczających danych na temat trafności stosowania tego narzedzia w populacjach innych narodowości. Celem niniejszej pracy jest dostosowanie testu badającego osobowośc typu D do wymagan Polskiej populacji pacjentow po pierwszym zawale serca. Material i metody. Piecdziesieciu pacjentow 4 tygodnie do 6 miesiecy po pierwszym zawale serca przebadano za pomocą baterii testow psychologicznych. Wyniki. Potwierdzono zarowno dwuczynnikową strukture skali, jak i wewnetrzną spojnośc skali Negatywna Emocjonalnośc (α = 83) oraz Zahamowanie Spoleczne (α = 63). Ponadto potwierdzono konstrukcje testu za pomocą innych skal badających podobne czynniki. Wnioski. Badania autorow wskazują na to, ze kwestionariusz do badania osobowości typu D (DS14) mozna stosowac u polskich pacjentow z chorobą wiencową.
Rapid reduction of Arctic perennial sea ice

The extent of Arctic perennial sea ice, the year‐round ice cover, was significantly reduced between March 2005 and March 2007 by 1.08 × 106 km2, a 23% loss from 4.69 × 106 km2 to 3.61 × 106 km2, as observed by the QuikSCAT/SeaWinds satellite scatterometer (QSCAT). Moreover, the buoy‐based Drift‐Age Model (DM) provided long‐term trends in Arctic sea‐ice age since the 1950s. Perennial‐ice extent loss in March within the DM domain was noticeable after the 1960s, and the loss became more rapid in the 2000s when QSCAT observations were available to verify the model results. QSCAT data also revealed mechanisms contributing to the perennial‐ice extent loss: ice compression toward the western Arctic, ice loading into the Transpolar Drift (TD) together with an acceleration of the TD carrying excessive ice out of Fram Strait, and ice export to Baffin Bay. Dynamic and thermodynamic effects appear to be combining to expedite the loss of perennial sea ice.