system behavior

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Memory System Behavior of Java-Based Middleware

Memory System Behavior of Java-Based Middleware

In this paper, we present a detailed characterization of the memory system behavior of ECperf and SPECjbb using both commercial server hardware and Simics full- system simulation. We find that the memory footprint and primary working sets of these workloads are small com- pared to other commercial workloads (e.g., on-line trans- action processing), and that a large fraction of the working sets are shared between processors. We observed two key differences between ECperf and SPECjbb that highlight the importance of isolating the behavior of the middle tier. First, ECperf has a larger instruction foot- print, resulting in much higher miss rates for intermediate- size instruction caches. Second, SPECjbb’s data set size increases linearly as the benchmark scales up, while ECperf ’s remains roughly constant. This difference can lead to opposite conclusions on the design of multiproces- sor memory systems, such as the utility of moderate sized (i.e., 1 MB) shared caches in a chip multiprocessor.
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How does navigation system behavior influence human behavior?

How does navigation system behavior influence human behavior?

Navigation systems are ubiquitous tools to assist wayfinders of the mobile information society with various navigational tasks. Whenever such systems assist with self-localization and path planning, they reduce human effort for navigating. Automated navigation assistance benefits navigation performance, but research seems to show that it negatively affects attention to environment properties, spatial knowledge acquisition, and retention of spatial information. Very little is known about how to design navigation systems for pedestrian navigation that increase both navigation performance and spatial knowledge acquisition. To this end, we empirically tested participants (N = 64) using four different navigation system behaviors (between-subject design). Two cognitive processes with varying levels of automation, self-localization and allocation of attention, define navigation system behaviors: either the system automatically executes one of the processes (high level of automation), or the system leaves the decision of when and where to execute the process to the navigator (low level of automation). In two experimental phases, we applied a novel empirical framework for evaluating spatial knowledge acquisition in a real-world outdoor urban environment. First, participants followed a route assisted by a navigation system and, simultaneously, incidentally acquired spatial knowledge. Second, participants reversed the route using the spatial knowledge acquired during the assisted phase, this time without the aid of the navigation system. Results of the route-following phase did not reveal differences in navigation performance across groups using different navigation system behaviors. However, participants using systems with higher levels of automation seemed not to acquire enough spatial knowledge to reverse the route without navigation errors. Furthermore, employing novel methods to analyze mobile eye tracking data revealed distinct patterns of human gaze behavior over time and space. We thus can demonstrate how to increase spatial knowledge acquisition without harming navigation performance when using navigation systems, and how to influence human navigation behavior with varying navigation system behavior. Thus, we provide key findings for the design of intelligent automated navigation systems in real-world scenarios.
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A framework and model system to investigate linear system behavior in Escherichia coli

A framework and model system to investigate linear system behavior in Escherichia coli

guidelines for the conditions necessary that ensure lin- ear system behavior would be available. In this study, we focused on device copy number as the perturbing factor. Promoter strength is another important factor (as are RBS strength, gene length, codon usage, and product function). A library of constitutive promoters has been characterized using the cat and gfp genes [31]. By expressing cat and gfp in the manner done in that study, the model system constructed in this work can be used to investigate the effect promoter strength has on linear system behavior. Our results appear to suggest that the identity of a device’s promoter is not the only factor that impacts linearity in its RNA expression pro- file. While gfp had a promoter identical to that of cat, the former was the most nonlinear in our three-device model system (Figure 5). In fact, cat and nptII had simi- lar DTCs in our three-device model system, but yet had different promoters. Comparison of the cat DTCs in our two-device (Figure 4D) and three-device (Figure 5C) constructs also supports this premise. The cat DTC was primarily linear for both cases. The cat device in one experiment, however, had its native promoter (Fig- ure 4D), while the P L promoter was used in the other
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Analyzing System Behavior: Howthe Operating System Can Help

Analyzing System Behavior: Howthe Operating System Can Help

Instrumenting applications at operating system level has been well investigated. On Win- dows operating systems, the major comprehensive analysis tool at operating system level is perfmon [RS05]. Perfmon queries built-in Windows performance counters and generates diagrams that help system administrators to identify bottlenecks in the operating system. Performance counters have to be queried by a Windows API, restricting the frequency of the requests. For example, it is impossible to trace every context switch, because the con- text switch counter might already have changed while the result of a query is transfered to the monitoring thread.
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Validating the System Behavior of Large-Scale Networked Computers

Validating the System Behavior of Large-Scale Networked Computers

 Overlays compete with IP-layer to control routing decisions – ISPs & overlays are unaware of decisions made by the other layer – Multiple overlay networks co-exist and make indepen[r]

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System Behavior Analysis by Machine Learning

System Behavior Analysis by Machine Learning

Windows Error Reporting System[XHF + 09] Web server performance metric[BSP + 08] Console logs with source code[DB08] 3 Conclusion. 4 References.[r]

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System Behavior and Causal Loop Diagrams

System Behavior and Causal Loop Diagrams

To start to consider system structure, you first generalize from the specific events associated with your problem to considering patterns of behavior that character- ize the situation. Usually this requires that you investigate how one or more variables of interest change over time. (In a business setting, variables of in- terest might be such things as cost, sales, revenue, profit, market share, and so forth.) That is, what patterns of behavior do these variables display. The systems approach gains much of its power as a problem solving method from the fact that similar patterns of behavior show up in a variety of different situations, and the underlying system structures that cause these characteristic patterns are known. Thus, once you have identified a pattern of behavior that is a problem, you can look for the system structure that is know to cause that pattern. By finding and modifying this system structure, you have the possibility of permanently eliminating the problem pattern of behavior.
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Review on Behavior of Outrigger System in High Rise Building

Review on Behavior of Outrigger System in High Rise Building

In July 2015, Abdul karimmulla and Srinivas B.N.presented a research containing comparative study on behavior of the outrigger in regular and irregular structure. In this paper the researcher gave a brief introduction of the conventional and virtual concept of outrigger system. The conventional outrigger is connected to braced frame or shear wall directly at the core but not necessary to column to locate at outer edges of the building. Virtual outrigger is connecting core and perimeter system is eliminated directly and belt truss is used with strong diaphragm. Virtual outrigger couldn’t compete the conventional outriggers under acute conditions of lateral loading. That’s why the scope for the virtual outrigger is limited to regions of less severe winds and earthquakes.
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Modeling the Behavior of the Stock Market with an Artificial Immune System

Modeling the Behavior of the Stock Market with an Artificial Immune System

Negative selection (NS) was first used in AIS for recognizing “self” and “not self”, with this type of learning the algorithm only uses examples of one-type of object such as in positive-only learning. NS comes from the Thymus which is an organ responsible for generating the T-Cells which circulate the body looking for invading antigens. The thymus continually creates T-cells which are first held in the thymus and tested to see if they are activated by any of the “self”, which would mean that they recognize and react to “self”, if they do than they are destroyed, otherwise released into the body as they will only be activated by “non-self” pathogens. A T-cell is activated if its degree of similarity is sufficiently close to an antigen and this degree of similarity is determined by an affinity measure. This type of learning can be very ineffective for supervised learning as the “non- self” space can be quite large and require a massive number of T-cells to accurately map it. Also by ignoring counter examples and only training on one type of data a large amount of useful information is ignored. To improve upon the principle of NS, the algorithm implemented in this study, which will be more thoroughly introduced in the next section, is referred to as clonal selection-based AIS where training is conducted with both negative and positive exemplars. The algorithm learns and builds a memory of negative and positive exemplars and later uses this experience to classify new antigens which enter the system or, representing, new, unlabelled examples to which the algorithm is exposed.
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Crowdroid: Behavior-Based Malware Detection System for Android

Crowdroid: Behavior-Based Malware Detection System for Android

We have chosen a simple 2-means clustering algorithm to distinguish between benign applications and their correspon- dent malware version. The results have been encouraging, although we need to address some open issues. First, the system would always separate the system call data vectors in two clusters even if there is no malware on it. The cluster mapping would change drastically whenever a malicious exe- cution vector enters into the dataset. These issue requires some manual check or further automatic analysis. Second, one could intentionally submit incorrect data to the system leaving the dataset corrupt. One next step is to authenti- cate the submitting application so we can ensure that no- body is directly sending wrong data to the system. Regard- ing the communication mechanism between the Crowdroid client and our server, it is made using the FTP protocol in this first version, without focusing on protecting the privacy of transferred data. If an attacker sniffs and manipulates the traffic in the communication process, it can lead to misclas- sification errors. In order to avoid this, we are introducing encryption mechanisms to provide integrity of data and au- thenticity of the sender. We have to take into account that applying this technique in the mobile device, it might have an extra overhead in the processor, resulting in a fast battery drain.
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The Effects of a School Wide Positive Behavior Support System

The Effects of a School Wide Positive Behavior Support System

Having safe supportive schools is crucial to the advancement of academic and social success. Due to the culture of violence in society, many schools make violence prevention and conflict resolution part of learning. The increase in aggressive and delinquent behavior in schools throughout the country has reached critical proportions (Safran & Oswald, 2003). In 2007, the NCES reported that 74% of public schools recorded one or more violent incidents of crime; 16% recorded one or more serious violent incidents; 44% recorded one or more thefts, and 68% recorded one or more other incidents (NCES, 2007). As a result, schools established policies to increase discipline and control by adopting “get tough” practices (Simonsen, Sugai, & Negron, 2008). Violent and disruptive behaviors become more destructive over time, destroy the school environment, and lower the quality of life for students and teachers (Walker, Cheney, Stage, & Blum, 2005).
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Study on Coalmine Safety Behavior Control System Model and its Manager Behavior Choice

Study on Coalmine Safety Behavior Control System Model and its Manager Behavior Choice

As we all know, the characteristic of coal production determines there are full of potentially dangerous in coal production process. In order to prevent possible accidents or reduce their harmful degree to an acceptable level, it is needed to remove the factors that might conduce to seri- ous injury or loss of life by implementing various safety management measures, such as managing the essential factors that influence miner to do unsafe behavior. How- ever, as one composition of coalmine safety management, behavior management is more important to physical management, because miner’s behavior is a more active ingredient in the coal production process, and the miner’s unsafe behavior is the primary and direct factors leading
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Human Behavior centered Museum Guided Tour System

Human Behavior centered Museum Guided Tour System

Why do we have so many unsuitable user interfaces? Some user interface designs focus on human-centered and display design, but rarely focus on human behavior, also called “human action.” One command, or target, can be accomplished using various methods, or actions under different types of situations and environments, but some interface designers restrict themselves in a limited hardware design, like keyboard and mouse. They does not notice that there are still a lot of types of human behavior can be considered as an “interface”.

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Clarification of Tritium Behavior in Pb Li Blanket System

Clarification of Tritium Behavior in Pb Li Blanket System

Properties related with tritium inventory and recovery in the Pb­Li liquid blanket were summarized here, when the eutectic alloy was applied to a tritium breeder in fusion reactor. The solubility and diffusivity of hydrogen isotopes in Pb­Li were summarized and compared among previous data. The differences among previous solubility data were experimentally explained based on the Li activity changes in the Pb­Li alloy system and interactions with wall materials. Isotope effects of solubility and diffusivity for H and D in the Pb ­ Li eutectic alloy were determined. The decrease of tritium permeation through Er 2 O 3 coating on
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Interactive system by observation and analysis of behavior for children with autism

Interactive system by observation and analysis of behavior for children with autism

The project that we carry out, called Autism Project, is in partnership with the psychi- atric service for children with autism of La Rochelle hospital. Our objective is to imple- ment a software and hardware system that could help the children with autism during the rehabilitation process. It consists in establishing a multimode and multimedia dialogue between the assisted child and the system. The role of such a system is to provide to the children the personalized activities in the form of educational games. During a session, the system collects by various devices (camera, touch screen, mouse, keyboard. . . ) the child reactions, in order to understand her/his behavior and response to it, in real time, by adequate actions considering the expert’s directives.
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Management system of personality corelated with organizational behavior

Management system of personality corelated with organizational behavior

Abstract: The organization is a system of interrelated activities, made up of individuals - employees. They, the employees as members of a labor organization should endeavor to establish a balance between personal needs and desires from one side and those needs of the organization from the other side. Sometimes this balance is easily accomplished, but sometimes it is impossible. Today, in these turbulent social change falling into opposite-directed chaos, personal, individual and organizational. It is required modifying the basic needs in the system of an individual to continue, that will result in an open organizational behavior. This behavior represents a set of personal goals, competencies, beliefs and values. The best predictor of future behavior is a previous behavior of the person. It is a key link which linked expectations of person with its actions in specific situations. Expectations are basic to start some action, competence which incorporates the knowledge and skills leads to superior performance. The system of personality composed of subsystems generate synergy through self - concept in which the changes in any subsystem affect others.
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Statewide System Change in Positive Behavior Support

Statewide System Change in Positive Behavior Support

Interventions, Volume 2, pp. 208–253 for brief de- scriptions of several efforts) are important to note as they pertain to system change (i.e., with the in- dividual school as the system). In their work Sugai and colleagues (2000) provided guidance, noting that ‘‘without a systems approach, identification of practices is limited, adoptions are incomplete, and attention to school initiatives to address discipline is episodic and short term’’ (p. 136). That work builds upon previous efforts (e.g., O’Neill et al., 1997) that provide a ‘‘continuum of positive be- havior support that emphasizes a systems approach, preventive perspective, and specialized interven- tions’’ (p. 136). This model is helpful for assessing which needs to address when seeking to produce meaningful and widespread change throughout a system. Additional efforts in system change within schools, such as that described by Knoster, Villa, and Thousand (2000), highlight the importance of ‘‘a comprehensive approach that attends to both the how and why of the process of change’’ (p. 95). Although such efforts represent important initia- tives focused on meaningful change in school set- tings, they do not provide a model sufficient to ad- dress the needs for system change in positive be- havior support in a statewide MR/DD system. In
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Asymptotic behavior of a system of linear fractional difference equations

Asymptotic behavior of a system of linear fractional difference equations

has been investigated in [9]. Here we will obtain more precise results for the special case of system (1.1) by using the monotonicity properties of the map in (1.1). We will give some basic results on the equilibrium points and their stability and prove some asymptotic results for the unique equilibrium point of (1.1).

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Coordination of mobile robot system with 
		behavior based architecture

Coordination of mobile robot system with behavior based architecture

Indoor mobile robots are becoming reliable enough in navigation tasks to consider working with teams of robots. The use of multiple robots is often suggested to have several gains over single robot systems (Burgard et al. 2005). First, cooperating robots have the prospective to accomplish a single task faster than a single robot. A system of collaborative robots that jointly schedule a meeting which outperformed several single robot systems designed to accomplish the same task. Furthermore, multiple robots can localize themselves more efficiently if they exchange information about their position whenever they sense each other. Finally, using several cheap robots introduces redundancy and therefore can be expected to be more fault-tolerant than having only one powerful and expensive robot (Egerstedt, 2014), (Montano and Suarez, 2013) and (Quinonez et al. 2013).
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Bookstore Readers’ Behavior Acquisition System Based on Iot

Bookstore Readers’ Behavior Acquisition System Based on Iot

In this paper, the development of the bookstore reader behavior perception system mainly by the book shelves’ perception nodes, coordinator nodes, routing nodes and background systems [6]. The book shelves’ perception nodes is responsible for collecting the situation of book and can communicate with the reader's mobile phone, it also can sent the information to the coordinator node. After reader read the book, it can sent the information of which books the reader have read a moment ago. Coordinator node is responsible for transmitting the information, including the data sent by the sensing node and the commands issued by the background system. At the same time, the wireless network can be searched and the network area can be expanded to make the more aware nodes join the network. The routing node is responsible for establishing and starting the ZigBee wireless network , it’s also could transmission of wireless signals, management of wireless network nodes, storage of wireless network node information, the routing also bear the responsibility of communication with the background system, upload the data fromother nodes to the background system, and translate the background system’s command to the perceptual nodes; the background system is responsible for the network configuration of the wireless network and the analysis of the data collected by the sensing nodes. The whole system as shown in Fig 1:
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