Developing suggestion tools in the scope of health information systems can be a complex task, followed by a risk of not being accepted by the end users. Thus, we decide to start the implementation around the existing functionality. In this paper we present a case study showing the adaptation of e-learning medical information system extension to a set of simple suggestion tools. While some features of initial system had to be modified, the domain specific knowledge collected for the e-learning extension is used to suppress potential errors. Presented suggestion tool is based on highly configurable lists of pre-defined entities that can be easily selected, and after the verification from the medical practitioner, copied into an active visit. After four years of active use, and several iteration of update, described suggestion tools are mostly accepted among the general practitioners, especially within certain scenarios where faster medication prescription is a must.

The one of the most common problems affecting older patients is the misuse of prescribed therapies. The patients, in many cases, forget to take their therapy, use it twice or even use the wrong medication. Since all of the mentioned cases can trigger further serious health problems, and since the majority of the population in Serbia already uses mobile phones, we decided to extend our existing medical information system with a prescription service that will allow the development of mobile-device based notification system. The notification system will then help patients with medication timing and dosing issues to take their therapies more accurate and to prevent possible health complications. In this paper we present the existing mobile services offered by the medical information system Medis.NET, as well as an architectural solution for the extension of the existing software with a prescription and notification service. The architectural solution is followed by the example of an initial implementation, description of the most important use-cases and related test results. In a near future, we plan to improve the proposed solution by offering new options to the patients, easing the connection with third party services and by developing a smartphone application that can improve the complete interaction with patients.

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.

Reed-Muller expressions and their various extensions and generalizations for binary and multiple-valued logic functions are an important class of discrete function representations that are often used in practical applications. These expressions can be uniformly viewed as discrete polynomial expressions over finite fields GF(2) and GF(q) or the field of rational numbers in the case of expressions with integer-valued coefficients. The optimization of them in the number of product terms count is performed by selecting either positive or negative literals (polarities) for variables in the functions to be represented. Since there are no ways to select in advance the polarity for variables that will result in most compact expression for a given function, all possible expressions have to be generated and the simplest of them selected. This is a task computationally very demanding, the complexity of which is O(q^n \times C), where C is the time to calculate a particular polarity. Since the reduction of the first factor may lead to missing the most compact expression, the reduction of C is the single option to speed up the procedure. In this paper, we propose an approach to the solution of this problem by exploiting the notion of extended dual polarity, which provides a simple way of ordering polarities to obtain an effective way of finding the optimal one by reducing the time to move between them. The method still implies exhaustive search, but it is an optimized search, which may be expressed in very simple rules resulting in efficient implementation. Experimental results illustrate the effectiveness of the proposed method.

In this paper, we propose an approach to the reduction of sizes of multi-terminal binary decision diagrams (MTBDDs) by using the copy properties of discrete functions. The underlying principles come from copy theory of discrete signals considered previously. We propose two modifications of MTBDDs, called copy DDs (CDDs) and half copy DDs (HCDDs), using the corresponding copy operations from copy theory. Functions having different types of copy properties can be efficiently represented by the proposed Copy DDs. Examples are Walsh and Reed-Muller functions as well as different binary codes.

Discrete Walsh transform is an orthogonal transform often used in spectral methods for different applications in signal processing and logic design. FFT-like algorithms make it possible to efficiently calculate the discrete Walsh spectrum. However, for their exponential complexity, these algorithms are practically unsuitable for large functions. For this reason, a Binary Decision Diagram (BDD) based recursive method for Walsh spectrum calculation has been introduced in Clarke et al. (1993). A disadvantage of this algorithm is that the resulting Multi-Terminal Binary Decision Diagram (MTBDD) representing the Walsh spectrum for f can be large for some functions. Another disadvantage turns out if particular Walsh coefficients are to be computed separately. The algorithm always calculates the entire spectrum and, therefore, it is rather inefficient for applications where a subset of Walsh spectral coefficients, i.e., the pruned Walsh spectrum, is required. In this paper, we propose another BDD-based method for Walsh spectrum calculation adapted for application where the pruned Walsh spectrum is needed. The method takes advantage of the property that for most switching functions, the size of a BDD for f is usually quite a bit smaller than the size of the MTBDD for the Walsh spectrum. In our method, a MTBDD representing the Walsh spectrum is not: constructed. Instead, two additional fields are assigned to each node in the BDD for the processed function f. These fields are used to store the results of intermediate calculations. Pairs of spectral coefficients are calculated and stored in the fields assigned to the root node. Therefore, the calculation complexity of the proposed algorithm is proportional to the size of the BDD for f whose spectrum is calculated. Experimental results demonstrate the efficiency of the approach.