Miracle-dz/UniFAR-FTUs huggingface dataset:
The Journal of Defense Software Engineering

Technology change management represents the fusion of technology innovation and process management, and is a key practice of adaptive, higher maturity organizations. Managing changes in technologies and processes are among the foremost challenges for many organizations because process stability and continual improvement are difficult to balance. Technology change management is not an isolated activity; rather it is a process that touches many of the socio-technical activities in an organization. It includes business and work processes and technical systems. Models such as the Capability Maturity Model® (CMM®) provide a vital focus for technology change management. The integration of disciplines within a single model, the CMM Integration (CMMI SM) offers a more encompassing focus to better support technology change management efforts for projects and enterprise-wide process improvement. In his article, " Structured Approaches to Managing Change " (page 4), Mark Paulk offers three perspectives that may be of value in thinking about change management: 1. internally driven change [push] vs. externally driven change [pull] 2. change directed at products and services vs. those directed at design and production processes 3. incremental vs. revolutionary change He notes that considering innovation management models can lead to significant changes in models, such as the CMM, that are widely influential in driving process improvement. Models also can influence strategic decision making by broadening and structuring executives' thinking. An objective view of the challenges that must be overcome in adopting a new technology or process can be materially aided by structuring the analysis around models. Linda Levine, in her article " Integrating Knowledge and Processes in the Learning Organization " (page 17), writes that paying attention to how people learn enables more effective change management. Learning and technology change management reinforce one another. When people are asked to change how they work, such as in adopting changes in technology or process improvement, then they are asked to learn. To be successful , learning organizations require the integration of process management, knowledge management, and technology. To better support technology change management, the CMMI integrates software and systems engineering processes that are critical to maturing organizational capabilities. CMMI serves as a more effective tool in helping to guide and assess integrated process improvement efforts. The next CMMI draft will include integrated process and product development process areas. To achieve process improvement goals, higher maturity organizations will focus organizational improvement management on critical CMMI process areas composed of practices that …
Towards personalized advertising in sponsored search

Web advertising is one of the major sources of income for numerous search engines, news sites and non-commercial publishers. Textual ads, characterized by Sponsored Search (SS) and Content Match (CM), make up a significant portion of Web advertising. In SS, with limited information about ad contents, given a query, the challenge is to place relevant ads alongside organic search results. Organic search results are ranked based on their relevance to search keyword. However, SS results are not necessarily ranked purely based on relevance due to various factors influencing the ads overall ranking such as bid phrase and displayed position. The displayed ads may not relate to a user's information need. In this paper, a study associating ads and users, referred to as personalized advertising is proposed. User profiles are used as external knowledge to establish the relationship between the users and the ads.
Predictive control with enhanced robustness for precision positioning in frictional environment

A modified predictive control strategy is developed to overcome positioning and tracking difficulties for a transmission mechanism with friction. Enhanced robustness with respect to unknown dynamics is achieved by incorporating a zero phase error tracking controller (ZPETC) and a time-delay disturbance estimation scheme. Time delay control is used to cancel disturbances and potential nonlinearities. ZPETC is included to improve the overall system bandwidth. Both realistic numerical simulations, which consider the effect of sampling, quantization, and friction, and practical experiments are performed to investigate the effectiveness of the proposed control method. Encouraging transient response and steady-state control performance were observed in the results of positioning control of a one-dimensional transmission mechanism.
Retrofit reconfigurable fault tolerant control for mechanical systems

This paper investigates a difficult problem of retrofit reconfigurable control design that retains a baseline/nominal controller and, at the same time, accommodates actuator faults and uncertain dynamics so that the overall system is stable and the control objective is met. A theoretical retrofit control architecture is developed for a class of mechanical systems. This is accomplished using minimum prior information regarding the baseline/nominal controller. A reconstruction mechanism is firstly designed to precisely estimate system uncertainties and actuator fault. Using such reconstructed value, a retrofit control signal is generated as a compensation effort, and added to the nominal controller to compensate for uncertainties and faults. It is shown that the closed-loop system resulted from the proposed retrofit controller has the same properties of the nominal closed-loop system, which consists of the certain system dynamics and the dynamics of the nominal controller. The performance of this retrofit reconfigurable control design is verified with simulation results.
Anomaly Intrusion Detection Method Based on K-Means Clustering Algorithm with Particle Swarm Optimization

K-means clustering algorithm is an effective method that has been proved for apply to the intrusion detection system. Particle swarm optimization (PSO) algorithm which is evolutionary computation technology based on swarm intelligence has good global search ability. With the deficiency of global search ability for K-means clustering algorithm, we propose a K-means clustering algorithm based on particle swarm optimization (PSO-KM) in this paper. The proposed algorithm has overcome falling into local minima and has relatively good overall convergence. Experiments on data sets KDD CUP 99 has shown the effectiveness of the proposed method and also shows the method has higher detection rate and lower false detection rate.
Mining Techniques and Analysis of Concept Based User Profiles from Search Engine Logs

Search engine logs are emerging new type of data user profiling component of any personalization interesting opportunities for data mining. Early user profiling work on mining data mostly attempted to discover knowledge at the level of queries based on objects that users are interested in positive preferences but not the objects in negative preferences. In our paper we focus on search engine logs for patterns at the level of terms and develop many concept user profiling methods that are positive preference and negative preference. We shows that our proposed system in data mining techniques how the search engine works in query process, index process and also comparing the existing system with effective mining association
An adaptive microphone array topology for target signal extraction with humanoid robots

In this paper, an unsupervised adaptation algorithm for the microphone array topology of a humanoid robot is proposed, so that the spatial filtering performance is improved. In the given exemplary case, the target suppression (`blocking') performance of a geometrically-constrained BSS (GC-BSS) algorithm is shown to improve by the adaptation of the array topology. As a decisive feature, an online performance measure for blind source separation is introduced which provides a robust and reliable estimate of the instantaneous signal separation performance based on currently observable data. Experimental results based on simulated environments confirm the efficacy of the concept.
Bridging scales through multiscale modeling: a case study on protein kinase A

The goal of multiscale modeling in biology is to use structurally based physico-chemical models to integrate across temporal and spatial scales of biology and thereby improve mechanistic understanding of, for example, how a single mutation can alter organism-scale phenotypes. This approach may also inform therapeutic strategies or identify candidate drug targets that might otherwise have been overlooked. However, in many cases, it remains unclear how best to synthesize information obtained from various scales and analysis approaches, such as atomistic molecular models, Markov state models (MSM), subcellular network models, and whole cell models. In this paper, we use protein kinase A (PKA) activation as a case study to explore how computational methods that model different physical scales can complement each other and integrate into an improved multiscale representation of the biological mechanisms. Using measured crystal structures, we show how molecular dynamics (MD) simulations coupled with atomic-scale MSMs can provide conformations for Brownian dynamics (BD) simulations to feed transitional states and kinetic parameters into protein-scale MSMs. We discuss how milestoning can give reaction probabilities and forward-rate constants of cAMP association events by seamlessly integrating MD and BD simulation scales. These rate constants coupled with MSMs provide a robust representation of the free energy landscape, enabling access to kinetic, and thermodynamic parameters unavailable from current experimental data. These approaches have helped to illuminate the cooperative nature of PKA activation in response to distinct cAMP binding events. Collectively, this approach exemplifies a general strategy for multiscale model development that is applicable to a wide range of biological problems.
Trade Policy Disaster: Lessons from the 1930s

The recent economic crisis--with the plunge in the stock market, numerous bank failures and widespread financial distress, declining output and rising unemployment--has been reminiscent of the Great Depression. The Depression of the 1930s was marked by the spread of protectionist trade policies, which contributed to a collapse in world trade. Although policymakers today claim that they will resist the protectionist temptation, recessions are breeding grounds for economic nationalism, and countries may yet consider imposing higher trade barriers. In Trade Policy Disaster, Douglas Irwin examines what we know about trade policy during the traumatic decade of the 1930s and considers what we can learn from the policy missteps of the time. Irwin argues that the extreme protectionism of the 1930s emerged as a consequence of policymakers' reluctance to abandon the gold standard and allow their currencies to depreciate. By ruling out exchange rate changes as an adjustment mechanism, policymakers turned instead to higher tariffs and other means of restricting imports. He offers a clear and concise exposition of such topics as the effect of higher trade barriers on the implosion of world trade; the impact of the Smoot-Hawley tariff of 1930; the reasons some countries adopted draconian trade restrictions (including exchange controls and import quotas) but others did not; the effect of preferential trade arrangements and bilateral clearing agreements on the multilateral system of world trade; and lessons for avoiding future trade wars.
The economic effects of trade unions in Japan

Preface Introduction Union and Social-Economic Background Attitudes of Non-Union Members Towards Unions Union Voice, and The Effect Satisfaction and Separation Motive The Effect of Unions on Wages The Effect of Unions and Employee Voice on Wages and Working Conditions: Their Endogeneity Problem The Effect of Voices on Working Conditions and Their Economic Interpretations Based on Enterprise Unionism The Effect of Union Voices and Productivity The Effect of Trade Unions on Labour Shares and Industrial Relations Concluding Remarks Index
Operation Level Safety Analysis for Object Oriented Software Design Using SFMEA

Recent trends have indicated the increased use of object oriented technology not only for the design and development of traditional softare but also for safety critical software. There has been an ongoing effort for the application of traditional well documiented and well tested hardware safety and reliability analysis techniques to software. Software Failure Modes and Effects Analysis (SFMEA) is one such technique that has been adopted from its hardware counter part Failure Modes and Effects Analysis (FMEA). Despite differences in operational failure modes between hardware and software, the recent research has shown the usefulness of the technique in software development process. This paper aims to: (i) highlight the application of SFMEA in object oriented design process and (ii) use the results of analysis obtained from previous step at implementation phase for improving robustness of the code.
Statechart Verification with iState

This paper is the longer version of the extended abstract with the same name published in FM 06. We describe in detail the algorithm to generate verification conditions from statechart structures implemented in the iState tool. This approach also suggests us a novel method to define a version of predicate semantics for statecharts analogous to how we assign predicate semantics to programming languages.
Agent-Based Artificial Chinese Stock Market and Nonlinear Characteristic Analysis

In Consideration of the characteristics of the Chinese stock market, we modeled the formation of Agent's price expectations, with the policy introduced as a factor into the model. We categorized traders as rational traders and noise traders, and constructed a model of noise traders. We also consider the characteristics of the Chinese stock market when we built dividend model. With these models, we simulated the Chinese stock market. Then we compared the characteristics of the real stock market and of an artificial stock market and found the real stock market and the artificial stock market are of the same primary nonlinear characteristics-fractal and chaos. This research is of great significance in capturing the critical factors which characteristics the evolving rules and the chaos dynamics of the Chinese stock market.
Youth Unemployment in Europe and the United States

This paper focuses particularly on youth unemployment, why we should be concerned about it, why it is increasing again, how the present difficulties of young people entering the labour market differ from those of the past and what useful lessons have been learned that may guide future policy. We focus on Europe and USA, but introduce evidence from other countries where appropriate. Our analysis of the UK NCDS birth cohort data provides evidence supporting the notion that early adulthood unemployment creates long lasting scars which affect labour market outcomes much later in life. Our chosen variables are weekly wages and happiness. Our results show significant effects at age 50 from early adulthood unemployment. These affects are stronger than more recent unemployment experiences.
Interleukin-8 Is Activated in Patients with Chronic Liver Diseases and Associated with Hepatic Macrophage Accumulation in Human Liver Fibrosis

Background Interleukin-8 (IL-8, CXCL8) is a potent chemoattractant for neutrophils and contributes to acute liver inflammation. Much less is known about IL-8 in chronic liver diseases (CLD), but elevated levels were reported from alcoholic and hepatitis C-related CLD. We investigated the regulation of IL-8, its receptors CXCR1 and CXCR2 and possible IL-8 responding cells in CLD patients. Methodology Serum IL-8 levels were measured in CLD patients (n = 200) and healthy controls (n = 141). Intrahepatic IL-8, CXCR1 and CXCR2 gene expression was quantified from liver samples (n = 41), alongside immunohistochemical neutrophil (MPO) and macrophage (CD68) stainings. CXCR1 and CXCR2 expression was analyzed on purified monocytes from patients (n = 111) and controls (n = 31). In vitro analyses explored IL-8 secretion by different leukocyte subsets. Principal Findings IL-8 serum levels were significantly increased in CLD patients, especially in end-stage cirrhosis. Interestingly, patients with cholestatic diseases exhibited highest IL-8 serum concentrations. IL-8 correlated with liver function, inflammatory cytokines and non-invasive fibrosis markers. Intrahepatically, IL-8 and CXCR1 expression were strongly up-regulated. However, intrahepatic IL-8 could only be associated to neutrophil infiltration in patients with primary biliary cirrhosis (PBC). In non-cholestatic cirrhosis, increased IL-8 and CXCR1 levels were associated with hepatic macrophage accumulation. In line, CXCR1, but not CXCR2 or CXCR3, expression was increased on circulating monocytes from cirrhotic patients. Moreover, monocyte-derived macrophages from CLD patients, especially the non-classical CD16+ subtype, displayed enhanced IL-8 secretion in vitro. Conclusions IL-8 is strongly activated in CLD, thus likely contributing to hepatic inflammation. Our study suggests a novel role of IL-8 for recruitment and activation of hepatic macrophages via CXCR1 in human liver cirrhosis.
Managing Complexity in the Piranha Server-Class Processor Design

High-end microprocessor designs have recently been incorporating increasingly advanced features, such as larger issue width and speculative out-of-order execution, which are targeted at further extracting instruction-level parallelism from programs. The added design complexity introduced by such mechanisms has led to an alarming increase in design cost and time-to-market for next generation designs. Although these mechanisms have improved performance of some applications, many important commercial workloads, such as online transaction processing, have not benefited significantly from them. In response to these trends, the Piranha project set out to address commercial workload performance requirements while managing overall project complexity. In this paper, we discuss the Piranha architecture and the project's novel design methodology, which together enabled the design to be brought to the point of a physical prototype by a team of less than 20 people working for little over a year.
On the nature of argument schemes

Since the 1980s, computer science, especially artificial intelligence (AI) has developed formal models of many aspects of argumentation that since the work of Toulmin and Perelman were thought of as belonging to informal logic. Doug Walton is one of the argumentation theorists who has recognised the relevance of this body of work for argumentation theory. One of the concepts on which recent work in AI has shed more light is that of argument schemes (sometimes also called ‘argumentation schemes’), which features prominently in Walton’s work. A study of argument schemes from the perspective of AI is therefore very appropriate for this volume in honour of his work. More precisely, the aim of this paper is to use insights from AI to propose an understanding of the nature of argument schemes as a means to evaluate arguments, and to compare this understanding with Walton’s own account of argument schemes. Walton regards argument schemes as essentially dialogical devices, determining dialectical obligations and burdens of proof. Using this account, a procedure for evaluating arguments should take the form of a set of dialogue rules. I shall instead argue that argument schemes are essentially logical constructs, so that a procedure for evaluating arguments primarily takes the form of a logic. More specifically, I shall argue that most argument schemes are defeasible inference rules and that their critical questions are pointers to counterarguments, so that the logic governing the use of argument schemes should be a logic for nonmonotonic, or defeasible reasoning. The dialogical role of argument schemes can then be modelled by embedding such a logic in a system for dialogue, so that in the end argument evaluation with argument schemes is a combination of logical and dialogical aspects. However, after having developed this account, I shall also argue that not all argument schemes naturally fit the format of defeasible inference rules and that there is an often overlooked distinction between two types of argument schemes. One type fits the model of defeasible inference rules, i.e., elements of a reasoning method, but another type can better be seen as a reasoning method in itself. To model reasoning with such argument schemes, an account is needed of how reasoning methods can be combined, and I shall argue that this goes beyond the usual nonmonotonic logics and dialogue systems.
Exploiting Inherent Parallelisms for Accelerating Linear Hough Transform

Accelerating Hough transform in hardware has been of interest due its popularity in real-time capable image processing applications. In most existing linear Hough transform architectures, an m times medge map is serially read for processing, resulting in a total computation time of at least m2 cycles. In this paper, we propose a novel parallel Hough transform computation method called the Additive Hough transform (AHT), wherein the image is divided using a k times k grid to reduce the total computation time by a factor of k2. We have also proposed an efficient implementation of the AHT consisting of a look-up table (LUT) and two-operand adder arrays for every angle. Techniques to condense the LUT size have also been proposed to further reduce area utilization by as much as 50%. Our investigations based on employing an 8 times 8 grid shows a 1000 times speedup compared to existing architectures for a range of image sizes. Area-time trade-off analysis has been presented to demonstrate that the area-time product of the proposed AHT-based implementation is at least 43% lower than other implementations reported in the literature. We have also included and characterized a hierarchical addition step in order to generate a global accumulation space equivalent to that of the conventional HT. It is shown that the proposed implementation with the hierarchical addition step remains superior to other methods in terms of both performance and area-time product metrics. Finally, we show that the proposed solution is equally efficient when applied on rectangular images.