The choice of agricultural crops for sowing and the planning of yields and economic results is realized in conditions of uncertainty and risk. The factors that contribute most to the uncertainty in ...achieving yields in agricultural production can be quantified using the method of fuzzyfication. The method based on the unique assessment of criteria represents an innovative approach to solving uncertainty in agricultural production. A key feature of this method is its ability to treat criteria as fuzzy scores and to allow their aggregation to make a final yield planning decision. In the paper, 15 main criteria were chosen that influence the planning of yield when sowing sage, nettle and rye. Based on economic indicators, the economic analysis does not numerically describe the impact of uncertainty, which in agricultural production can have an inestimable importance on realized yields and incomes. The method used is a suitable tool for analysis and planning in agriculture, it enables effective treatment of uncertainty and competing criteria, providing farmers with a reliable basis for making decisions about yield planning.
Aim: To assess the quality of life in patients with a malignant disease.
Research subjects and methods: Research included 105 patients with a malignant disease who were receiving stationary and daily ...treatment at the Radiotherapy and Oncology Department of the University Hospital Center, Osijek, Croatia. A questionnaire containing various demographic data and including a scale for measuring the quality of life in patients with a malignant disease – the Functional Assessment of Cancer Therapy-General (FACT-G) – was used as a research instrument.
Results: Average score on the scale was 89. Level of satisfaction with social/family relationships was significantly lower in older respondents (p = 0.027), single persons (p = 0.018) and participants with total income under HRK 3,000 (p = 0.031). Regarding family and social relationships, the patients receiving hospital day care expressed a significantly higher level of satisfaction (p = 0.001), as well as the subjects with college/university qualifications (p = 0.007). Patients with malignant disease of the head and neck expressed significantly lower levels of satisfaction on all subscales and with regard to overall health (p = 0.005).
Conclusion: Quality of life in patients with a malignant disease is satisfactory.
A spectral transform maps a function from one domain into an appropriate function in another domain where certain characteristics of the function are clearly visible. Spectral transforms have great ...importance in signal analysis, image processing, logic design, etc. The main problem with spectral transforms is their exponential computational complexity. In the case of discrete functions, spectral transform computation comes down to multiplying the transform matrix and the truth vector of the function. Most of the previously developed algorithms for spectral transforms computation are based on the fast Fourier transform algorithm, some use a compact representation of the functions (such as decision diagrams), and some use special single instruction multiple data hardware structures (such as graphics processing units). In the last years, a special type of graphics processing units with Tensor Cores has been developed for matrix multiplication. These units usually support matrix operations on limited data types and matrix dimensions. In this paper, we propose algorithms for 4-valued Reed–Muller–Fourier and Vilenkin–Chrestenson transforms on the Tensor Cores hardware. Our solution is a customization of the Cooley–Tuckey algorithm for execution on the hardware with specified limitations. Computation times of spectral transforms by the proposed algorithm are compared with computation times of the same transforms on a central processing unit by using serial and parallel algorithms, and on a standard graphics processing units. The described experiments showed that, for a large number of variables, both implementations that are executed on graphics processing units are significantly more efficient than those that are executed on central processing unit. If only implementations on graphics processing units are compared, for the functions of 14 variables, the Tensor Cores implementation of the Reed–Muller–Fourier transform is 2.03 times faster, and the implementation of the Vilenkin–Chrestenson transform is 1.5 times faster. Poorer results obtained for the Vilenkin–Chrestenson transform are due to the limited set of data types provided by the NVIDIA Turing Graphics Processing Units that were used in the experiments. Therefore, one integer spectral coefficient is represented by 4-byte values. Regardless, the proposed algorithms and the Tensor Cores architecture have proven to be a good solution for the spectral transforms calculations.
On Fixed Points of the Reed-Muller-Fourier Transform Moraga, Claudio; Stankovic, Radomir S.; Stankovic, Milena ...
2017 IEEE 47th International Symposium on Multiple-Valued Logic (ISMVL)
Conference Proceeding
The Reed-Muller-Fourier transform combines relevant aspects of the RM transform and the DFT. It constitutes a bijection in the set of p-valued functions. Some properties of the transform matrix are ...formally analyzed and its eigenvectors with eigenvalue λ = 1, which are its fixed points, are studied. Some methods to generate fixed points from known fixed points are presented and the number of fixed points for some values of p and n are given.
Decision diagrams (DD) are a widely used data structure for discrete
functions representation. The major problem in DD-based applications is the
DD size minimization (reduction of the number of ...nodes), because their size
is dependent on the variables order. Genetic algorithms are often used in
different optimization problems including the DD size optimization. In this
paper, we apply the genetic algorithm to minimize the size of both Binary
Decision Diagrams (BDDs) and Functional Decision Diagrams (FDDs). In both
cases, in the proposed algorithm, a Bottom-Up Partially Matched Crossover
(BU-PMX) is used as the crossover operator. In the case of BDDs, mutation is
done in the standard way by variables exchanging. In the case of FDDs, the
mutation by changing the polarity of variables is additionally used.
Experimental results of optimization of the BDDs and FDDs of the set of
benchmark functions are also presented.
nema
Decision diagrams (DDs) are a data structure that allows compact representation of discrete functions. The efficient construction of DDs in terms of space and time is often considered problem. A ...particular problem is that during the construction of a DD, a large number of temporary nodes are created. We address this problem in the case when the functions are specified in the PLA format. A common practice is to construct a DD by recursively processing all the cubes in PLA specification. The DD representing a subfunction defined by a single cube is merged with the DD for the subfunction defined by all the previously processed cubes. We proposed a method of reordering and partitioning the set of cubes in PLA specification that results in the reduction of both space and time complexities of the construction of DDs. First, we arrange cubes by their suffices. Then we partition the set of cubes, construct DDs for the subfunctions representing each partition separately, and merge them into a final DD. The reordering and partitioning ensures that these intermediary decision diagrams never exceed a certain size which is controlled by the size of the partitions. In this way, the number of operations on the nodes during the merging decision diagrams is reduced. This reduction results in a decrease both in the number of temporary nodes and construction time. The proposed method is used for the construction of DDs for the set of standard benchmark functions. The experiments show that the total number of created nodes is reduced on average by 34.65 percent, while the construction time is decreased by 48.6 percent.
The paper presents a method for reversible synthesis of Boolean functions based on the properties of theis Walsh-Hadamard spectra. To realize a function, each part of the reversible cascade is ...specified by an examination if certain appropriately defined conditions are satisfied by pairs of the Walsh-Hadamard spectral coefficients. The function to be realized is represented by a Binary Decision Diagram (BDD) and the Walsh-Hadamard spectrum is computed over this BDD. Experimental results show that the proposed method outperforms existing similar methods in terms of both the number of lines and gates.
Transformation of BDD into Heterogeneous MDD with Minimal Cost STOJKOVIC, Suzana; STANKOVIC, Milena; STANKOVIC, Radomir S.
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences,
2009, Letnik:
E92.A, Številka:
10
Journal Article
Recenzirano
Decision diagrams (DDs) are data structures commonly used for representation of discrete functions with large number of variables. Binary DDs (BDDs) are used for representation and manipulation with ...Boolean functions. Complexity of a BDD is usually measured by its size, that is defined as the number of non-terminal nodes in the BDD. Minimization of the sizes of DDs is a problem greatly considered in literature and many related algorithms (exact and heuristic) have been proposed. However, there are many functions for which BDDs when minimized are still large and can have even an exponential size in the number of variables. An approach to derive compact decision diagram representations for such functions is transformation of BDDs into Multi-valued DDs (MDDs) and Heterogeneous MDDs (HMDDs). Complexity of MDDs and HMDDs is measured by the cost which is a generalization of the notion of the size by taking into account complexity of nodes in MDDs and HMDDs. This paper presents a method for transformation of BDD into HMDD with minimal cost. The proposed method reduces the time for determination of the type of nodes in HMDDs by introducing a matrix expressing dependency (interconnections) among nodes at different levels. Comparing to other methods for conversion of BDDs into HMDDs, the method reduces the number of traverses of a BDD necessary for collecting enough information to construct an equivalent HMDD. For an experimental verification of its efficiency, the method is applied to construction of HMDDs for some benchmark functions and their arithmetic and Walsh spectra.
Incompletely specified logic functions are often met in computer science and engineering and their compact representations are a subject of a wide research interest. In this paper, we present a ...method for determining an assignment of unspecified function values that will produce compact decision diagrams. The method is based on the analysis of Walsh and Vilenkin-Chrestenson spectral coefficients for binary and multiple-valued functions, respectively, and the operation of spectral translation of logic functions. Spectral transforms are used to identify the linear function with strongest correlation with the initial function and assign the unspecified values as well as to specify the spectral translation that will result in a compact decision diagram.
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