Miracle-dz/UniFAR-FTUs huggingface dataset:
Intensification of the Pre‐Meiyu Rainband in the Late 21st Century

Increased atmospheric moisture content and changing land‐ocean thermal contrasts are usually implicated in the East Asian summer rainfall response to global warming. We highlight an additional influence whereby increased meridional stationary eddy circulation downstream of the Tibetan Plateau drives a stronger moisture flux convergence over southeastern China, intensifying the early summer rainband. This effect occurs robustly across the Community Earth System Model large ensemble Representative Control Pathway 8.5 simulations, and only for its pre‐Meiyu stage (mid‐May through late June). The westerly jet impinging on the Plateau is also enhanced, suggesting an orographic influence on the westerlies as the root cause. The increased westerlies result from warmer tropical tropospheric temperatures that enhance the meridional temperature gradient at the latitudes of the Plateau. Our results highlight the potential role of the westerlies in altering the East Asian early summer monsoon rainfall in the late 21st century.
Assertion-based Verification by Using PSL

Assertion based verification is a new approach for hardware verification,which can increase the productivity and quality of verification especially for complex ASIC and SoC design.In a practical design of a digital cross connect chip which is a key device for synchronous digital hierarchy,by using ModelSim6.0 of Mentor Graphics Corp.,it embeds PSL(Property Specification Language) assertions into Verilog designs,and simulation results show that PSL can assist the check efficiently.
Task-based Example Miner for Intelligent Tutoring Systems

Intelligent tutoring systems (ITS) aim to provide customized resources or feedback on a subject (commonly known as domain in ITS) to students in real-time, emulating the behavior of an actual teacher in a classroom. This thesis designs an ITS based on an instructional strategy called example-based learning (EBL), that focuses primarily on students devoting their time and cognitive capacity to studying worked-out examples so that they can enhance their learning and apply it to similar graded problems or tasks. A task is a graded problem or question that an ITS assigns to students (e.g. task T1 in C programming domain defined as “Write an assignment instruction in C that adds 2 integers”). A worked-out example refers to a complete solution of a problem or question in the domain. Existing ITS systems such as NavEx and PADS, that use EBL to teach their domain suffer from several limitations such as (1) methods used to extract knowledge from given tasks and worked-out examples require highly trained experts and are not easily applicable or extendable to other problem domains (e.g. Math), either due to use of manual knowledge extraction methods (such as Item Objective Consistency (IOC)) or highly complex automated methods (such as syntax tree generation) (2) recommended worked-out examples are not customized for assigned tasks and therefore are ineffective in improving student success rate. This thesis proposes a new modular model for an EBL-based ITS called Example Recommendation System (ERS). ERS extracts knowledge in terms of basic learning units (LU) (e.g. scanf is a LU in the domain of C programming) from all task solutions and worked-out examples in its domain by using regular expression analysis and represents this knowledge in vector space. The prime contribution of knowledge extraction method of ERS is its extendibility to new domains without requiring highly trained experts. Experiments on two different domains show that LUs are extracted with 81% correctness for domain 1 (Programming in C) and 95% for domain 2 (Programming in Miranda). Knowledge extraction also serves as a crucial data pre-processing step for ERS, which then uses the extracted knowledge to mine its repository of worked-out examples using data mining methods such as k-nearest neighbors, in order to generate customized list
Does the inverse exchange-traded fund trading convey a bearish signal to the market?

This paper investigates whether inverse exchange-traded fund (ETF) trading can predict future negative underlying index returns. Using inverse ETF’s turnover rates and price volatilities to represent trading activities, this paper discovers that inverse ETF trading is significantly and positively related to future index returns and infers that the trading of inverse ETFs may not reflect informed pessimistic trading and cannot convey a bearish signal to the market. The trading activities in inverse ETFs do provide information about future index returns, yet what they reflect may be a lagging or less-informed bearish signal.
Impact of industrial wastewater on water and fish quality of Nile River in Kafr El-Zayat, Egypt

In Egypt, Rosetta branch of the Nile River is impacted by several industrial effluents at Kafr El-Zayat City, which potentially affect and deteriorate its quality. To study the impact of these effluents on aquatic environment of the Rosetta branch, a total of 108 water samples and 36 fish samples were collected during the spring and autumn 2010 from 9 different regions along the branch at Kafr ElZayat industrial area. Chemical analyses of water samples showed seasonal variation of pH, Pb, Cd, and NH3 values. Cu concentrations in the water were below the maximum permissible limit, however, Pb, Cd, Hg, P, NH3, and S exceeded the permissible limit. The distribution of these parameters at the area under investigations are strongly affected by the industrial effluents produced from El-Mobidat, El-Malyia and Salt and Soda companies which directly discharge industrial effluents at this area without any treatment. The presence of high levels of Pb, Hg, NH3, and S in the fish muscles were in relation to water pollution in the studied area. The bacteriological analyses showed that TBC ranged from 1.9 x103 to 5×105 cfu/ml for water and from 3×105 to 5×105 cfu/g for fish flesh. Importantly, the water and fish samples tested were positive for Salmonella and negative for E. Coli. In conclusion, the results demonstrate that the Nile River at Kafr ElZayat industrial area is heavily polluted and consequently harmful effects to the aquatic environment and to the quality of the water are established. So, treatment and safe disposal of different industrial wastes is recommended.
A Study of Noise-Robust Speech Recognition and Time-Varying Speech Features [an abstract of dissertation and a summary of dissertation review]

Title A Study of Noise-Robust Speech Recognition and Time-Varying Speech Features [an abstract of dissertation and a summary of dissertation review] Author(s) Ang, Federico Mendoza Citation 北海道大学. 博士(情報科学) 甲第12190号 Issue Date 2016-03-24 Doc URL http://hdl.handle. net/2115/61744 Rights(URL) http://creativecommons.org/licenses/by-nc-sa/2.1/jp/ Type theses (doctoral abstract and summary of review) Additional Information There are other files related to this item in HUSCAP. Check the above URL. File Information Federico_Mendoza_Ang_abstract. pdf (論文内容の要旨)
Automatised analysis of emergency calls using Natural Language Processing

The operators at SOS Alarm receives thousands of calls each day at the different emergency medical communication centres, owned by SOS Alarm, all over Sweden. A subset of these calls contain room for improvement and the operators could learn to improve from these calls. The work of finding – and analysing – these calls is however too tedious to be done by a human. This thesis presents four automatised solutions to this issue. The human factor is removed and the job of finding and analysing the calls is done by a computer. It is shown that it is possible to partly automatise the analysis, but the methods used have different strengths and weaknesses. Word frequency analysis is proven adequate at key word lookup. Similarity comparisons of various aspects of the calls are proven good at classifying calls, but less good at answering specific questions. Comparing parse trees seems promising, but the technology needs more work before it is ready to be used. The solutions presented show that it could be possible to automatise the analysis of the calls given that the right questions are asked and the results from these are used appropriately.
Introduction to Genetic Algorithms in Electromagnetics

This article is a tutorial on using genetic algorithms to optimize antenna and scattering patterns. Genetic algorithms are "global" numerical-optimization methods, patterned after the natural processes of genetic recombination and evolution. The algorithms encode each parameter into binary sequences, called a gene, and a set of genes is a chromosome. These chromosomes undergo natural selection, mating, and mutation, to arrive at the final optimal solution. After providing a detailed explanation of how a genetic algorithm works, and a listing of a MATLAB code, the article presents three examples. These examples demonstrate how to optimize antenna patterns and backscattering radar-cross-section patterns. Finally, additional details about algorithm design are given. >
A Dynamic Web Services Composition Algorithm Based on the Combination of Ant Colony Algorithm and Genetic Algorithm

Web services composition has received much interest to support business-to-business or enterprise application integration. Web services with the same functions and different QoS are increasing with the proliferation of SOA(Services Oriented Architecture). It is needed to select a best composition schema from numerous schemas in order to maximize the satisfaction and meet the QoS requirements of users. In this paper, we propose a dynamic web services composition algorithm (ACAGA_WSC) based on the combination of the ant colony algorithm and the genetic algorithm. ACAGA_WSC transforms the problem of selecting optimal execution schema for composite web service into selection of the optimal path in the weighted directed acyclic graph. The experimental results indicated the validity and efficiency of ACAGA_WSC.
CCNx Key Exchange Protocol Version 1.0

This document specifies Version 1.0 of the CCNx Key Exchange (CCNxKE) protocol. The CCNxKE protocol allows two peers to establish a shared, forward-secure key for secure and confidential communication. The protocol is designed to prevent eavesdropping, tampering, and message forgery between two peers. It is also designed to minimize the number of rounds required to establish a shared key. In the worst case, it requires two RTTs between a consumer and producer to establish a shared key. In the best case, one RTT is required before sending any application data. This document outlines how to derive the keys used to encrypt traffic for a session and shows how session information is exchanged between a consumer and producer using message encapsulation.
An Innovative Design Approach to Control over Ad Hoc Networks

In Mobile ad hoc networks (MANETs), the mobile nodes are communicating trough wireless medium. The protocol designs of MANETs are based on a traditional approach which has been found ineffective to deal congestion related problems. Hence, it is affecting properties of physical layer, the network layer and transport layer. This paper proposes a novel design approach, deviating from the traditional network design, towards enhancing the cross-layer interaction among different layers, namely physical, MAC and network. The novel approach for congestion control is to solve congestion and mobility related problems with a cross layer interaction. The significance of CLCC is that it has used two mechanisms: (i) Dynamic Transmission Power Control algorithm that predicts a link breakage if it is likely to happen, (ii) Dynamic Congestion Estimation Technique, which analyzes traffic fluctuation and categorize congestion status perfectly. The proposed protocol reduces the route breakage and network congestion, hence reduces the control overhead and latency, and increases the packet delivery ratio. Through simulation, it is shown that the proposed protocol is simple, robust and effective.
The algorithm of thread scheduling with an Improvement Accelerating Critical Section of migration strategy

In multi-core processors,the heterogeneous multi-core processors are more practical than homogeneous multi-core because they have asymmetric cores.Therefore,the multi-thread scheduling among them becomes a hot research topic.In this paper, an Improvement Accelerating Critical Section algorithm is proposed for the improvement of the Accelerating Critical Section algorithm. The algorithm tracks the execution of threads on the cores that contain the critical section and changes the priority factor of threads . It use the priority factor to guide the threads’dynamic migration between the high-performance core and the low-performance cores.The algorithm can accelerate the excution of the critical section and effectively solve the threads block problem on high-performance core that the Accelerating Critical Section causes.This paper use the Simics to simulate heterogeneous multi-core processors system and the inputs are 12 loads with intensive critical sections. The experimental results show that compared to the Accelerating Critical Section algorithm and the Simple Algorithm ,the algorithm this paper proposes has better performance.
4D geomechanical simulations for field development planning

3D and 4D geomechanical can be time-consuming to build and calibrate. However, once such a model is built, it is relative straightforward to use this model for various field development and management applications. In so doing, the return on the initial investment of time and effort in the creation of a 4D geomechanical model can be substantial. I present a case study where a 4D geomechanical model of a deepwater turbidite field under water flood is used to: Assessment of wellbore stability for drilling inclined infill wells after a stuck pipe event Calculation of maximum allowable injection pressures during hydraulic stimulation to avoid out-of-zone growth of stimulated fractures, and evaluation of risk of fault re-activation during a range of production scenarios for pressure support in order to establish safe operational limits for pressure support. Model building uses seismic inversion volumes to constrain a geological facies model, followed by upscaling to a reservoir simulation model and history matching. Similarly, a 3D geomechanical property model is built to the seafloor. The calibration of the pre-production stress state of the geomechanical model comprises of matching the results of 3D finite element stress field calculations to 1D wellbore models. The calibration uses a novel method of linking tectonic strain terms in poro-elastic equations in the 1D and 3D models. Production and injection processes are the computed using a fully coupled finite element based geomechanical flow simulator, solving multi-phase (black-oil) fluid flow and geomechanics equations simultaneously on the same computational mesh. The computational mesh is optimized for geomechanical predictions of wellbore and fault stability.
Multi-objective mapping of full-mission simulators on heterogeneous distributed multi-processor systems

Full-mission simulators (FMSs) are considered the most critical simulation tool belonging to the flight simulator family. FMSs include a faithful reproduction of fighter aircraft. They are used by armed forces for design, training, and investigation purposes. Due to the criticality of their timing constraints and the high computation cost of the whole simulation, FMSs need to run in a high-performance computing system. Heterogeneous distributed systems are among the leading computing platforms and can guarantee a significant increase in performance by providing a large number of parallel powerful execution resources. One of the most persistent challenges raised by these platforms is the difficulty of finding an optimal mapping of n tasks on m processing elements. The mapping problem is considered a variant of the quadratic assignment problem, in which an exhaustive search cannot be performed. The mapping problem is an NP-hard problem and solving it requires the use of meta-heuristics, and it becomes more challenging when one has to optimize more than one objective with respect to the timing constraints. Multi-objective evolutionary algorithms have proven their efficiency when tackling this problem. Most of the existent works deal with the task mapping by considering either a single objective or homogeneous architectures. Therefore, the main contribution of this paper is a framework based on the model-driven design paradigm allowing us to map a set of intercommunicating real-time tasks making up the FMS model onto the heterogeneous distributed multi-processor system model. We propose a multi-objective approach based on the well-known optimization algorithm “Non-dominated Sorting Genetic Algorithm-II” satisfying the tight timing constraints of the simulation and minimizing makespan, communication cost, and memory consumption simultaneously.
Content-Based Interactive Emotional Image Retrieval

With increased computing power, electronic storage capacity, and the rapid development of the Internet, the potential for large digital image libraries is now growing at an astonishing pace. Providing efficient access to images, however, is not an easy task. To overcome this difficulty, content-based image retrieval(CBIR) was thus proposed as a solution. In CBIR, images would be indexed by their own visual content, instead of being manually annotated by text-based keyword s. In this framework, many research studies have been performed, and many commercial and academic CBIR systems, widely applied in multimedia databases, digital libraries, medical image management, public security department and satellite image management, have been developed in the past few years. Most CBIR systems, however, answer users' query by similarity match based on multi-dimensional physical image features. Because of human subjectivity, different persons or the same person under different circumstances may perceive the same visual content differently. To address the difficulties arising from human subjectivity, we propose a content-based interactive emotional image retrieval approach. Through interactive evolution computation, human intuition and emotion is integrated into the evolution process to realize on-line retrieval by human-computer interaction. To deal with the problem that the user may tend to be tired arising from that the user has to evaluate a large number of individuals when the evolution time is too long, neural networks are used for off-line learning to alleviate human fatigue. Based on image content, an emotional image retrieval system has been realized. The experimental results demonstrate the effectiveness of our approach.
Online Consumers’ Responses to Deal Popularity as an Extrinsic Cue

ABSTRACT Deal popularity indicates the popularity of a product or service within a specific deal duration and is being used by many e-tailers in their websites/apps. While deal popularity is receiving increasing attention by academics and practitioners alike, its effect as an extrinsic cue remains under-researched. Using an experimental design, this study investigates the effect of deal popularity on expected service quality in an e-tailing environment. It is found that deal popularity influences service quality expectations for credence services, but not experience services. High deal popularity positively influences consumers’ intention to purchase and willingness to recommend credence services. E-tailers of services need to pay attention to deal popularity displayed for credence services and leverage on the positive effect it has on consumers.
Multi-objective Group Decision Making for Job Shop Scheduling Problem

To solve the problem of job-shop scheduling with multi-objective group constraints,it presents a scheduling algorithm combing the fuzzy decision-making method and the preferential assignment heuristic scheduling algorithm.The weight coefficients of multi-objective group are firstly determined by analysis hierarchy process,the processing machine tools used in each procedures of parts are determined by using the fuzzy decision-making method.Based on above analysis,it gives the order of parts to be processed on the same machine tool with the preferential assignment heuristic scheduling problem.The results show that the method is effective.
Modelling of masonry walls rendered with auxetic foam layers against vehicular impacts

Masonry walls allow easy intrusion of the impacting vehicles into the impacted buildings. The cause of the damage due to vehicular impacts in masonry walls is the generation of tensile stresses due to “Poisson’s effect”. Auxetic foams, due to their negative Poisson’s ratio, can eliminate these tensile stresses. In this study, masonry walls with and without Auxetic foam renders subject to lateral impact were analysed using an explicit finite element method incorporating shell elements. Masonry was considered as a homogenised continuum with distinct directional properties. The Poisson’s ratio of the Auxetic layers was considered as -0.2 and -0.9. The impact scenario was simulated using applied velocities. The results show that Auxetic layer reduced stresses in the masonry wall. The detailed deformation and failure results of the numerical examples encourage the potential for developing Auxetic composite render material, and methods of design and application to masonry walls to mitigate vehicular intrusions.
Prediction Based on the Acquisition of Sina Weibo Data and Users’ Forwarding Behavior

Microblogging, also known as Weibo, has currently become the prevalent social networking platform, and its function of disseminating information has been increasingly recognized and valued. One of the main approaches of information communication on Weibo is forwarding activities among users. Therefore, the key interests have focused on the microblogs that are easily recognized and forwarded. Through predicting the possibility of a micro-blog being forwarded among users, it is able to effectively improve the efficiency of information spreading on the Weibo platform. On the basis of Sina Weibo data, this paper intends to study 13 features of Sina Weibo including user and content, so as to conduct machine learning, to establish a feature analysis model, to identify key influence factors on Weibo forwarding, to study the combination of feature attributes for the first time, to explore the correlation among features, then to predict the probability of a micro-blog being forwarded by users. Meanwhile, concerning different features held by different data, different machine learning algorithms are applied in model training, in order to identify the algorithm with the highest prediction accuracy.
Dictionary of Pure and Applied Physics

Compiled by Louis de Vries and W. E. Clason Essex: Elsevier Publishing Co. Ltd. Volume I. 1963. German-English. Pp. 367. Price 55s. Volume II. 1964. English-German. Pp. 341. Price 55s. This is a quite unusually good dictionary. It is simple to use, clear and comprehensive. (I checked it against a scientific article and stopped when I found 'Molekiilion' as a separate entry.)
Performance Metric of Z Source CHB Multilevel Inverter FED IM for Selective Harmonic Elimination and THD Reduction

This paper focuses on a Z source cascaded multilevel inverter which is designed to minimize harmonics in the output voltage. A balanced dc-link peak voltage can be achieved. The power generation module is built by PV panels which are connected to Z-Source Cascade H-bridge inverter. Cascaded multilevel inverter can achieve the distributed maximum power point tracking to increase the system efficiency and achieve high voltage/high power grid tie without a transformer. This paper analyzes the different PWM switching scheme and the operating states of a ZSI module and comparison is made with different PWM and total harmonic distortion of various PWM schemes.