• Nuclear Engineering and Technology
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• v.7 no.3
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• pp.207-211
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• 1975

The Nilsson model was used to predict energy levels of $^{53}$ Mn without taking band mixing into consideration. The results were compared with the experimental levels and the predictions with band mixing of Malik ana Scholz. In both cases, with band mixing and without band mixing, the theoretical fit to experimental results is fair only for a few low-tying levels. However, it is found that the present calculation fits rather better to experiment than the band mixing calculation as far as higher levels are concerned.

• Membrane and Water Treatment
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• v.5 no.2
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• pp.147-170
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• 2014

This paper focuses on the study of the most recent ultra-filtration techniques, based on porous polymer membranes, used for the treatment of wastewater from oil, mine and hydrometallurgical industries. The performance of porous membranes used in separation and recovery of oil and heavy metals from wastewater, was evaluated by the polymer composition and by the membrane characteristics, as it follows: hydrophobicity or hydrophilicity, porosity, carrier (composition and concentration), selectivity, fouling, durability, separation efficiency and operating conditions. The oil/water efficient separation was observed on ultra-filtration (UF) techniques, with porous membranes, whereas heavy metals recovery from wastewater was observed using porous membranes with carrier. It can be concluded, that in the ultra-filtration wastewater treatments, a hybrid system, with porous polymer membranes with or without carrier, can be used for these two applications: oil/water separation and heavy metals recovery.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.427-432
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• 2005

This paper is concerned with a simultaneous design of TSK (Takagi-Sugeno-Kang)-linguistic fuzzy models with uncertain model output and the computationally efficient representation. For this purpose, we use the fundamental idea of linguistic models introduced by Pedrycz and develop their comprehensive design framework. The design process consists of several main phases such as (a) the automatic generation of the linguistic contexts by probabilistic distribution using CDF (conditional density function) and PDF (probability density function) (b) performing context-based fuzzy clustering preserving homogeneity based on the concept of fuzzy granulation (c) augment of bias term to compensate bias error (d) combination of TSK and linguistic context in the consequent part. Finally, we contrast the performance of the enhanced models with other fuzzy models for automobile MPG predication data and coagulant dosing process in a water purification plant.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1254-1259
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• 2005

In this paper, we proposed a learning algorithm for the neuro-fuzzy modeling using a learning rule to adapt clustering. The proposed algorithm includes the data partition, assigning the rule into the process of partition, and optimizing the parameters using predetermined threshold value in self-constructing algorithm. In order to improve the clustering, the learning method of neuro-fuzzy model is extended and the learning scheme has been modified such that the learning of overall model is extended based on the error-derivative learning. The effect of the proposed method is presented using simulation compare with previous ones.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1510-1515
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• 2005

This paper is concerned with a Logic-based Fuzzy Neural Networks (LFNN) with the aid of fuzzy granulation. As the underlying design tool guiding the development of the proposed LFNN, we concentrate on the context-based fuzzy clustering which builds information granules in the form of linguistic contexts as well as OR fuzzy neuron which is logic-driven processing unit realizing the composition operations of T-norm and S-norm. The design process comprises several main phases such as (a) defining context fuzzy sets in the output space, (b) completing context-based fuzzy clustering in each context, (c) aggregating OR fuzzy neuron into linguistic models, and (c) optimizing connections linking information granules and fuzzy neurons in the input and output spaces. The experimental examples are tested through two-dimensional nonlinear function. The obtained results reveal that the proposed model yields better performance in comparison with conventional linguistic model and other approaches.

• Structural Engineering and Mechanics
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• v.21 no.4
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• pp.451-468
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• 2005

Effective beam width models are commonly used to obtain the lateral stiffness of flat plate structures. In these models, an effective beam width is defined as the width when the flexural stiffness of the beam element equals the slab stiffness. In this present study, a method to obtain effective beam widths that considers the effects of connection geometry and slab cracking is analytically proposed. The rectangularity of the vertical member for the connection geometry and the combined effects of creep and shrinkage for the slab cracking are considered. The results from the proposed method are compared with experimental results from a test structure having nine slab-column connections.

• Asian-Australasian Journal of Animal Sciences
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• v.1 no.4
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• pp.195-199
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• 1988

Two experiments were conducted to evaluate the nutritive value of a diet containing 20% alkaline hydrogen peroxide(AHP) treated aspen sawdust for ruminants. In experiment 1, sheep fed treated aspen(treated) had higher (p < 0.05) average daily gain and improved feed/gain ratio compared to animals fed untreated aspen (untreated), Apparent NDF and ADF digestibilities of treated aspen were higher (p < 0.05) than for untreated material. A similar trend was observed for DM, organic matter and cellulose digestibilities coefficients. In experiment 2, the soluble and degradable DM and crude protein (CP) fractions tended to increase with AHP treatment. Treatment also increased (p<0.05) the degradation rate of the degradable fraction. Results of these experiment indicate that AHP treatment results in a substantial improvement in the extent of utilization of aspen sawdust by ruminants.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.4
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• pp.561-573
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• 2000

Knowledge concerning the nutritional requirements and nutritional problems of fanned deer is limited. Nutritional recommendations must be based on data from domestic ruminants and fanned deer. An understanding of the biology and adaptative characteristics of wild deer is essential for sensible application of sheep and cattle nutritional principles. Nutritional requirements of deer are generally separated into five categories: energy, protein, minerals, vitamins and water. Research on deer nutrition has primarily focused on energy, protein and minerals (phosphorus and calcium). Changes in the nutritional requirements that occur with gestation, lactation, breeding and antler growth should be coordinated with seasonal changes in nutrient availability from forage plants. This paper describes aspects of current knowledge of energy, protein, minerals, vitamins and water requirements. Nutritional problems of. fanned deer are described with recommendations for prevention or control. A comparison of production efficiency of deer, lamb, beef cattle and dairy cattle is included.

• Journal of the Korean Mathematical Society
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• v.40 no.2
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• pp.225-239
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• 2003

(G, <) is an ordered group if'<'is a total order relation on G in which f < g implies that xfy < xgy for all f, g, x, y $\in$ G. We say that (G, <) is centrally ordered if (G, <) is ordered and ［G,D］ $\subseteq$ C for every convex jump C $\prec$ D in G. Equivalently, if $f^{-1}g f{\leq} g^2$ for all f, g $\in$ G with g > 1. Every order on a torsion-free locally nilpotent group is central. We prove that if every order on every two-generator subgroup of a locally soluble orderable group G is central, then G is locally nilpotent. We also provide an example of a non-nilpotent two-generator metabelian orderable group in which all orders are central.

• Construction Engineering and Management
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• v.4 no.1 s.13
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• pp.48-54
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• 2003

An automated system for scanning and characterizing unbound aggregates, called the 'Laser-based Aggregate Scanning System'(LASS), has been developed at the University of Texas at Austin. The system uses a laser profiler to acquire and analyze true three-dimensional data on aggregate particles to measure various morphological properties. Tests have demonstrated that the system can rapidly and accurately measure grain size distribution and dimensional ratios, and can objectively quantify particle shape, angularity, and texture in a size invariant manner. In its present state of development, the LASS machine is a first-generation, laboratory testing device. With additional development, this technology is expected to provide high-quality, detailed information for laboratory and on-line quality control during aggregate production.