Case Study-Based Challenges of Quality Concrete Finishing for Architecturally Complex Structures

This paper focuses on the procedure utilized in the construction of tilt-up irregular concrete panels that are constructed on-site using concrete slabs and wooden formwork. The case study required high-quality concrete finishing. The erection and installation procedure called for a maximum panel-to-panel joint tolerance of 1.27?cm (0.5?in.), often 90° joints between panels. To meet precision requirements, the casting slabs were leveled and flattened with laser screed technology and smoothed with chemical solutions. To ensure that the final result met expectations, a mock-up model was built using different types of materials and to simulate site constraints. The architectural design is a composition of precast concrete panels like “Lego” pieces assembled similarly to a jigsaw puzzle. The unique construction process required a state-of-the-art analysis to produce the set quality. Quality conditions as set by the owner included creating a smooth concrete surface on all panels while avoiding damages and reducing equipment and material costs. The proposed methodology is described through its implementation on the case study, which is also described in this paper.     

Time jitter analysis of 1-bit sigma-delta synthesizer

This letter presents a general analysis of time jitter in sigma-delta synthesizer. One of the practical applications of 1-bit sigma-delta systems is a generation of high-resolution local oscillator (LO) signals. In order to generate LO signals, one may use a single-bit sigma-delta technique to encode sine waves. Today, direct generation of high-frequency sine wave using a clock with higher frequency, is possible. In this letter, we will analyze different LO signal generators and develop a practical way of computation to decide how to choose the best configuration under minimum degradation of signal-to-noise ratio (SNR) at the output.     

Effect of the add-back process on the free amino acid pool of potatoes

Summary The major losses in nitrogen and free amino acids (FAA) of the potato during the add-back (A-B) process were in the pre-cooking and mash-mixing steps (Fig. 1). These losses were due to leaching of nitrogen compounds into the processing water and heating.The FAA pool of the potato is composed mainly of the amides (asparagine and glutamine), aspartic and glutamic acids (approx. 53%). These amino acids were degraded substantially during the add-back process. There was also a significant loss in valine, threonine, serine, leucine, phenylalanine, and arginine, but no change in -aminobutyric acid (GABA).

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Einfluß des Add-Back Prozesses auf die freie Aminosäuremenge von Kartoffeln

Zusammenfassung Die Hauptverluste an Stickstoff und freien Aminosäuren werden bei der Kartoffel während des Add-back-Prozesses (A-B) beim Vorkochen und bei der Zerkleinerung (Abb. 1) festgestellt. Die Verluste sind durch das Auswaschen der Stickstoffverbindungen mit dem für die Herstellung erforderlichen Wasser und durch die Erhitzung bedingt. Die freien Aminosäuren der Kartoffel setzen sich im wesentlichen aus Amiden (Asparagin und Glutamin), Asparagin- und Glutaminsäuren (ca. 53%) zusammen. Die Amisnosäuren werden hauptsächlich während des Add-Back-Prozesses abgebaut. Ebenso nehmen Valin, Threonin, Serin, Leucin, Phenylalanin und Arginin im Verlauf des Prozesses signifikant ab, jedoch veränderte sich der -Aminobuttersäuregehalt (GABA) nicht.

     

Exploring similarities and differences in teamwork across diverse healthcare contexts using communication analysis

Teamwork is prevalent in many work contexts. This study explored the similarities and differences in teamwork processes across different healthcare work contexts with the aim of assessing knowledge transfer feasibility. The research approach was to aggregate team communication analyses from four healthcare contexts to uncover teamwork similarities and differences. The four healthcare contexts included two handoffs and two surgery contexts. The communication analysis segmented communication into meaningful sequences. It categorized utterances into content categories and verbal behaviors. There were a few similar content categories across the four contexts. A clear information structure emerged in the two handoff contexts. In addition, there were more dialogues and requests in the surgeries compared to more reports in the handoffs. The content similarities suggest that some knowledge is transferable among the contexts. However, the differences in communication patterns reflect fundamental differences between handoff and surgery contexts in some teamwork processes. This research demonstrated that using communication analysis can uncover similarities and differences in team cognition and teamwork processes across work contexts. This in turn can help determine what knowledge and methods pertaining to team training, procedures, and technology are transferable across the contexts.     

Derandomized graph products

Berman and Schnitger gave a randomized reduction from approximating MAX-SNP problems within constant factors arbitrarily close to 1 to approximating clique within a factor ofn (for some ). This reduction was further studied by Blum, who gave it the namerandomized graph products. We show that this reduction can be made deterministic (derandomized), using random walks on expander graphs. The main technical contribution of this paper is in proving a lower bound for the probability that all steps of a random walk stay within a specified set of vertices of a graph. (Previous work was mainly concerned with upper bounds for this probability.) This lower bound extends also to the case where different sets of vertices are specified for different time steps of the walk.     

Agent decision-making in open mixed networks

Computer systems increasingly carry out tasks in mixed networks, that is in group settings in which they interact both with other computer systems and with people. Participants in these heterogeneous human-computer groups vary in their capabilities, goals, and strategies; they may cooperate, collaborate, or compete. The presence of people in mixed networks raises challenges for the design and the evaluation of decision-making strategies for computer agents. This paper describes several new decision-making models that represent, learn and adapt to various social attributes that influence people's decision-making and presents a novel approach to evaluating such models. It identifies a range of social attributes in an open-network setting that influence people's decision-making and thus affect the performance of computer-agent strategies, and establishes the importance of learning and adaptation to the success of such strategies. The settings vary in the capabilities, goals, and strategies that people bring into their interactions. The studies deploy a configurable system called Colored Trails (CT) that generates a family of games. CT is an abstract, conceptually simple but highly versatile game in which players negotiate and exchange resources to enable them to achieve their individual or group goals. It provides a realistic analogue to multi-agent task domains, while not requiring extensive domain modeling. It is less abstract than payoff matrices, and people exhibit less strategic and more helpful behavior in CT than in the identical payoff matrix decision-making context. By not requiring extensive domain modeling, CT enables agent researchers to focus their attention on strategy design, and it provides an environment in which the influence of social factors can be better isolated and studied.     

Automatic boosting of cross-product coverage using Bayesian networks

Closing the feedback loop from coverage data to the stimuli generator is one of the main challenges in the verification process. Typically, verification engineers with deep domain knowledge manually prepare a set of stimuli generation directives for that purpose. Bayesian networks based CDG (coverage directed generation) systems have been successfully used to assist the process by automatically closing this feedback loop. However, constructing these CDG systems requires manual effort and a certain amount of domain knowledge from a machine learning specialist. We propose a new method that boosts coverage in the early stages of the verification process with minimal effort, namely a fully automatic construction of a CDG system that requires no domain knowledge. Experimental results on a real-life cross-product coverage model demonstrate the efficiency of the proposed method.     

Using a pseudo-stochastic approach for multiple-parts scheduling on an unreliable machine

In this paper we follow previous “pseudo-stochastic” approaches that solve stochastic control problems by using deterministic optimal control methods. In a similar manner to the certainty equivalence principle, the suggested model maximizes a given profit function of the expected system outcome. However, unlike the certainty equivalence principle, we model the expected influences of all future events (including those that are expected beyond the planning horizon), as encapsulated by their density functions and not only by their mean values. The model is applied to the optimal scheduling of multiple part-types on a single machine that is subject to random failures and repairs. The objective of the scheduler is to maximize the profit function of the produced multiple-part mix. A numerical study is performed to evaluate the suggested pseudo-stochastic solutions under various conditions. These solutions are compared to a profit upper bound of the stochastic optimal control solutions.     

Distributed Multi-Level Recovery in Main-Memory Databases

In this paper we present recovery techniques for distributed main-memory databases, specifically for client-server and shared-disk architectures. We present a recovery scheme for client-server architectures which is based on shipping log records to the server, and two recovery schemes for shared-disk architectures—one based on page shipping, and the other based on broadcasting of the log of updates. The schemes offer different tradeoffs, based on factors such as update rates.Our techniques are extensions to a distributed-memory setting of a centralized recovery scheme for main-memory databases, which has been implemented in the Dalì main-memory database system. Our centralized as well as distributed-memory recovery schemes have several attractive features—they support an explicit multi-level recovery abstraction for high concurrency, reduce disk I/O by writing only redo log records to disk during normal processing, and use per-transaction redo and undo logs to reduce contention on the system log. Further, the techniques use a fuzzy checkpointing scheme that writes only dirty pages to disk, yet minimally interferes with normal processing—all but one of our recovery schemes do not require updaters to even acquire a latch before updating a page. Our log shipping/broadcasting schemes also support concurrent updates to the same page at different sites.