An apparatus for cooling molten material resulting from a nuclear reactor core meltdown is disclosed. The apparatus includes a basin positioned under the reactor which is protected against excessive heat by a star-like array of heat pipes whose evaporator sections are disposed above the pan and whose condenser sections are disposed in a heat sink exterior to the containment building of the reactor. Additionally, the vertical walls of the reactor vessel chamber are similarly protected by an array of heat pipes similarly arranged and provided to intercept the radient energy of the molten core material.
A fitness function is needed for a Genetic Algorithm (GA) to work, and it appears natural that the combination of objectives and constraints into a single scalar function using arithmetic operations is appropriate. One problem with this approach, however, is that accurate scalar information must be provided on the range of objectives and constraints, to avoid one of them from dominating the other. One possible solution, then, is to try to join the objectives with the constraints with internal parameters, i.e., information that belongs to the problem itself, thereby avoiding external tuning. The building of the fitness function is so complex that, using internal or external parameters, any optimal point obtained will be a function of the coefficients used to combine objectives and constraints. However, it is possible that using internal parameters will increase performance compare to external ones.
Electrolytic cells demonstrate improved performance through use of an internal brine distribution system. A brine distributor located in the interior of the cell and positioned either at the cell bottom or above the cell's electrodes has individual brine outlets for feeding electrolyte directly to each of the cell's anolyte compartments for electrolysis. By comparison with conventional brine feed systems, e.g. cell top feed, the internal brine distributor produces higher purity gas, e.g. chlorine, at reduced power consumption and higher current efficiencies.
The Gaussian process prior formulation introduced by us in this paper learns a mapping for ordinal regression task using dual sets of latent functions. In this formulation one set of latent functions are associated with data items and the other set of latent functions are associated with entities. An entity is a term introduced by us in this work to refer to the object responsible for assigning ordinal labels to data items. For example in the collaborative filtering problem an entity corresponds to a user. In our work we assume that the entities cluster, and we use latent functions to having a Gaussian process prior to model these clusters. Similarly we also assume that the data items cluster and use latent functions having a Gaussian process prior to model these clusters. We learn the parameters of these Gaussian processes in a discriminative learning framework by minimizing a loss function using an alternating minimization procedure. The purpose of introducing dual sets of latent functions is to overcome the deficiency in the predictive nature of discriminative models for ordinal regression tasks while learning from less training data unlike generative models which have a good performance even while learning from less training data. Thus we evaluate the performance of our model on two problems, collaborative filtering and image annotation, by comparing with well known baseline methods using a generative model approach so as to understand the efficacy of our model on less training data.
As the number of networked computers grows, intrusion detection is an essential component in keeping networks secure. Various approaches for intrusion detection are currently being in use with eash one has its own merits and demerits. This paper presents an improved c-fuzzy desisio tree with controllable membership characteristics for intrusion detection.The tree grows gradually by using fuzzy C-means clustering (FCM) algorithm to split the patterns in a selected node with the maximum heterogeneity into C corresponding children nodes. We use a modified fuzzy C-means algorithm with an extended distance measure to include an additional higher order tern, as defined in. We also used a hybrid model to select suitable intial points for the FCM. Experimental results have shown that our improved version performs beter resulting in an effective intrusion detection system.
A product comprising a mixture of alpha - and beta - forms of glucose as microcrystals, at least 70% of the glucose being in the form of the beta -isomer, dissolves readily in water to give approximately 60% solids solutions at ambient temperature. It is obtained by a process comprising the steps of (1) evaporating water from syrup at a pressure of less than 400 mm Hg to provide an at least 60% supersaturated solution of greater than 95% solids at a temperature of from 95 DEG to 140 DEG C.; (2) subjecting the supersaturated solution substantially instantaneously to a shear force to cause immediate nucleation of the syrup without cooling; and (3) immediately forming the nucleated but substantially uncrystallized syrup into a quiescent layer and allowing the layer to crystallize substantially isothermally to produce solid crystalline glucose.
Unsolicited commercial or bulk emails or emails containing virus currently pose a great threat to the utility of email communications. A recent solution for filtering is reputation systems that can assign a value of trust to each IP address sending email messages. By analyzing the query patterns of each participating node, reputation systems can calculate a reputation score for each queried IP address and serve as a platform for global collaborative spam filtering for all participating nodes. In this research, we explore a behavioral classification approach based on spectral sender characteristics retrieved from such global messaging patterns. Due to the large amount of bad senders, this classification task has to cope with highly imbalanced data. In order to solve this challenging problem, a novel granular support vector machine - boundary alignment algorithm (GSVM-BA) is designed. GSVM-BA looks for the optima] decision boundary by repetitively removing positive support vectors from the training dataset and rebuilding another SVM. Compared to the original SVM algorithm with cost-sensitive learning, GSVM-BA demonstrates superior performance on spam IP detection, in terms of both effectiveness and efficiency
A spectrophotometer system has an optical system for transmitting a beam from a source at select wavelengths onto a detector. A plurality of filters are positioned in a tray. A stepper mechanism indexes the tray along a path. A microcomputer controls the stepper mechanism and the optical system. The wavelength is successively changed over a range, the tray is indexed to move a select filter into the beam at a predetermined wavelength and the changing is discontinued during indexing.
Case-Based Reasoning (CBR) is a relatively new and promising technique of artificial intelligence. By CBR, every new problem is solved by adapting the solutions of the similar problems previously solved successfully. During the past few years CBR has become a very popular technique for application in knowledge-based systems for different domains because the experience has been included in solving every new problem. The intention of our research is to develop a robust and general framework which supports generation of widerange decision support systems by using different CBR approaches. Presented framework integrates two previously developed CBR shells: CaBaGe and CuBaGe.
An improved vane type rotary compressor provided with a control mechanism of a lubricating oil supply passage by which the lubricating oil supply passage is arranged to be opened during operation of the compressor, and to be closed during shut-down of the compressor for obtaining a sufficient amount of lubricating oil supply during operation and also for preventing reverse rotation during shut-down of the compressor.
In a film feeding device of a camera including a preparatory wind-up device for winding up on a supply spool, before exposure, a roll film in a film magazine loaded into the camera, and a second wind-up device for rewinding into the magazine the unexposed film wound on the supply spool, there is provided means for detecting the completion of the wind-up, by the preparatory wind-up device, of all of the film which is drawn out of the film magazine and can be wound up on the supply spool, and change-over means for blocking and releasing the operation of the second wind-up device.
