The protection of Polish architectural heritage in the former eastern borderlands, accomplished through the conservation and technical securing of historical structures, constitutes one of the main programmes that are implemented by the Ministry of Culture and National Heritage. Currently, many Polish historical buildings in the former eastern borderlands are in a very bad technical condition. The load-bearing systems of these elements, as well as elements of their finish, require immediate emergency securing work. The basic steps that precede conservation work are emergency structural works, which guarantee the durability and stability of the entire historical substance. The specifics and complexity of the problem of the failure of historical buildings often demands an in-depth analysis of a series of factors that are difficult to measure and which are responsible for the cause and effect relationship during the early stage of the technical evaluation of a structure. The analyses of failures of numerous historical structures, for instance that were carried out by the authors, have become the inspiration for the search for effective methods of analysis that would allow for an in-depth analysis of the causes and effects of the failures in question. The DEMATEL method (Decision Making Trial and Evaluation Laboratory) that has been presented in this work, and its fuzzy extension, has lately become one of the more popular methods used in the cause-and-effect analysis of various phenomena. The authors demonstrated how this method works on the example of the evaluation and securing of the load-bearing system of the XVII Collegiate church of the Holy Trinity in the town of Olykha in the Volhynskiy Oblast, Ukraine.

The purpose of this paper is to present and analyse the decision-making problem faced by a future house owner - selection of the optimal solution of building thermal insulation in relation to the selected criteria, both related to costs and future benefits. The problem of selecting the best solutions in the construction sector is widely discussed in the science literature. In this paper, the authors decided to solve the raised problem by using the Entropy method.

The topic of this paper is the description of the General Contractor Selection procedure using the AHP method. Another aim of this paper – within the scope of decision-making – is the determination of the potential General Contractor’s evaluation criteria and the selection of the best Bidder using the AHP method. We included the description of the conducted tender proceeding for the purpose of the procurement’s subject. As the decision-making options, we adopted four construction companies that submitted their bid. A key element of the studies was the paired comparison of all hierarchical structure elements. We estimated the local weighting coefficients and global priorities of particular decision-making options as well as analysed the vulnerabilities of the obtained results.

The present paper concerns a problem of decisive criteria and their order in formwork selection problem. As the factors affecting the choice of exact form work system have been often discussed in literature, their importance has not been distinctly formulated yet, what hampers aiding formwork selection with MCDA methods that require criteria weights (eg.: SAW, TOPS IS etc.). Therefore, author ran a survey - the decisive criteria were recognized and verified within polls send to various contractors. An analysis of survey results including criteria ordering is a subject of the present elaboration.

The problems related to construction production are multi-faceted and complex. This has promoted the search for different methods/approaches for analizing the data which supports the decision-making process in the construction industry. In the article the authors focus their attention on well-known methods and tools, and on some new approaches to solving decision-making problems. The aim of the article is to analyze the methods used to analyse data in a construction company, convey their advantages and disadvantages, and specify the degree of efficiency in the discussed area.

For the construction company, tendering is the most popular way of acquiring contracts. The decision to participate in the tender needs to be made carefully, as it affects the condition of the company and is an important aspect in its quest for success. The bid/no bid decision making is a complex process involving a number of factors. The research carried out so far has mainly concerned the identification of the various kinds of influences on contractors’ bidding decisions. The researchers, on the basis of contractors’ opinions, created rank lists in an attempt to categorize the factors. In this paper the author employs factor analysis which belongs to basic methods of multi-dimensional data analysis. The paper’s aim is first to depict an output set of observed variables, that is bid/no bid factors, in terms of a smaller set of latent variables which cannot be directly observed and then to interpret the dependencies between them.

In the paper an approach to decision making in situations with non-point-like characterisation and subjective evaluation of the actions is considered. The decision situation is represented mathematically as fuzzy multiobjective linear programming (fMOLP) model, where we apply the reduced fuzzy matrices instead of fuzzy classical numbers. The fMOLP model with reduced parameters is decomposable into the set of point-like models and the point-like models enable effective construction of an optimisation procedure – fBIP, see Wojewnik (2006ab), extending the bireference procedure by Michalowski and Szapiro (1992). The approach is applied to a fuzzy optimization problem in the area of telecommunication services.

The paper presents modification of the method dedicated to a complex area decomposition of a set of logic functions whereas the

altered method is dedicated to implement the considered logic circuits within FPGA structures. The authors attempted to reach solutions where the number of configurable logic blocks and the number of structural layer would be reasonably balanced on the basis of the minimization principle. The main advantage of the procedure when the decomposition is carried out directly on the BDD diagram is the opportunity of immediate checking whether the decomposed areas of the diagram do not exceed the resources of logic blocks incorporated into the integrated circuits that are used for implementation of the logic functions involved.

The structure of Austempered Ductile Iron (ADI) is depend of many factors at individual stages of casting production. There is a rich literature documenting research on the relationship between heat treatment and the resulting microstructure of cast alloy. A significant amount of research is conducted towards the use of IT tools for indications production parameters for thin-walled castings, allowing for the selection of selected process parameters in order to obtain the expected properties. At the same time, the selection of these parameters should make it possible to obtain as few defects as possible. The input parameters of the solver is chemical composition Determined by the previous system module. Target wall thickness and HB of the product determined by the user. The method used to implement the solver is the method of Particle Swarm Optimization (PSO). The developed IT tool was used to determine the parameters of heat treatment, which will ensure obtaining the expected value for hardness. In the first stage, the ADI cast iron heat treatment parameters proposed by the expert were used, in the next part of the experiment, the settings proposed by the system were used. Used of the proposed IT tool, it was possible to reduce the number of deficiencies by 3%. The use of the solver in the case of castings with a wall thickness of 25 mm and 41 mm allowed to indication of process parameters allowing to obtain minimum mechanical properties in accordance with the PN-EN 1564:2012 standard. The results obtained by the solver for the selected parameters were verified. The indicated parameters were used to conduct experimental research. The tests obtained as a result of the physical experiment are convergent with the data from the solver.

Preventive methods of plant protection used currently require a significant number of treatments throughout the season. Research results indicate a possibility of reduction of the number of treatments by halfwithout serious loss of effectiveness if the attack of pathogens has been recorded early enough. Limiting treatments to truly necessary ones means conserving chemicals, fuel and labour and consequently substantial financial savings for the farm. However, early warning requires full analysis of many factors that influence incidence, development and harmfulness of diseases, pests and weeds in relation with their impact on the yield. Such an analysis is beyond the power of the farmer alone. Appropriate models have to be used that utilize weather data and field observations in real time. At the present, due to frequent updating of the databases and sharing of the system by many users, in integrated plant protection the most efficient seem to be internet decision support systems. As of 2000 the Institute of Plant Protection in Poznań together with the Institute Soil Science and Plant Cultivation in Puławy in cooperation with the Danish Institute of Agricultural Sciences conduct a joint research project on development and implementation of an Internet Decision Support System for Integrated Plant Protection in Poland. Various modules of the system are already available on the Internet. Much like similar systems operating abroad, the Polish DSS also takes advantage of weather data utilized in disease models (the weather module). Nevertheless, an important addition to the system are strategically relevant data such as values and statistic distributions of elements of climate and potential yields (the agroclimate module), operation sheets, exploitation data and prices (the technology module) etc., which are important to the formulation and adoption of a particular line of action and risk evaluation in economic terms. When all modules are operational, the information relevant to decision making will be derived from on-line analyses based on cost calculation of different variants of plant protection applicable to the current situation.

The aim of this study is to present an exemplary cartographic visualization of fi re hydrants data consisting of a set of thematic maps containing various information related to the location of hydrants, buildings and driveways in geographic space, and relationships existing between them. Identification of these relationships requires spatial analysis, and illustrating them requires the use of appropriate cartographic presentation methods. The study was conducted on a part of the city of Poznan using data on hydrants’ location and type collected and provided by the Fire Department. Geometric data, obtained using geoprocessing algorithms, were assigned appropriate symbols, which lets differentiate them qualitatively and quantitatively. An emphasis is placed on the use of adequate visual variables and on the cartographic communication efficiency. The result of the study is a cartographic visualization in the form of series of thematic maps arranged in a logical sequence, and providing information about the secured area. The thematic layers presenting the same area were arranged in different arrangements with maintenance of the reference layers, ensuring the ease of correlation. Such a cartographic visualization provides knowledge about the spatial distribution and diversity of objects and the relationships between them. It may be an important source of knowledge both at the identification stage and at the operational stage when conducting a fire fighting action.

In the article problems related to human labor and factors affecting the increasing use of

industrial robots are discussed. Since human factors affect the production processes stability,

robots are preferred to apply. The application of robots is characterized by higher performance

and reliability comparing to human labor. The problem is how to determine the real

difference in work efficiency between human operator and robot. The aim of the study is to

develop a method that allows clearly definition of productivity growth associated with the

replacement of human labor by industrial robots. Another aim of the paper is how to model

robotized and manual operated workstation in a computer simulation software. Analysis of

the productivity and reliability of the hydraulic press workstation operated by the human

operator or an industrial robot, are presented. Simulation models have been developed taking

into account the availability and reliability of the machine, operator and robot. We apply

OEE (Overall Equipment Effectiveness) indicator to present how availability and reliability

parameters influence over performance of the workstation, in the longer time. Simplified

financial analysis is presented considering different labor costs in EU countries.

Faithfull detection of non-utilized spectrum hole in available channel is a crucial issue for cognitive radio network. Choosing the best available channel for a secondary user transmission includes settling on decision of accessible choices of free frequency spectrum based on multiple objectives. Thus channel judgment can be demonstrated as several objective decision making (MODM) problem. An ultimate goal of this exploration is to define and execute a technique for multiple objective optimizations of multiple alternative of channel decision in Adhoc cognitive radio network. After a coarse review of an articles related to the multiple objective decision making within a process of channel selection, Multiple Objective Optimization on the basis of the Ratio Analysis (MOORA) technique is taken into consideration. Some important objectives values of non-utilized spectrum collected by a fusion center are proposed as objectives for consideration in the decision of alternatives. MOORA method are applied to a matrix of replies of each channel alternatives to channel objectives which results in set ratios. Among the set of obtained dimensionless ratios, all the channel alternatives are ranked in descending order. In MOORA, channel choices with moderate objectives can top in ranking order, which is hardly conceivable with linearly weighted objectives of the different channel by using different decision making technique.

This study investigates learners’ processing of English unaccusative verbs in the inchoative frame ( The door opened; Oil is spilling). Previous approaches explained L2 difficulty with the inchoative construction in terms of learners’ L1 and their perception of discourse or semantic factors hypothesized to be responsible for common overpassivization errors ( The door was opened). The purpose of the present study is to complement the extant inventory by proposing an additional factor instrumental in L2 processing. It is hypothesized that L2 use of unaccusative verbs is contingent on learners’ familiarity with formulaic expressions exemplifying the inchoative construction. The study focuses on the entrenchment of frequent phrases like My jaw dropped in Czech and Polish learners. In a lexical decision task, their reaction times for frequent expressions were found to be faster and fewer mistakes were made than in the case of non-formulaic counterparts ( My hair dropped).

We all face a wide array of different choices every day of our lives. Asst. Prof. Miłosz Kadziński explains how artificial intelligence could be used to help us make decisions.

Supply Chain Management (SCM) is a very important part of the industrial world, especially in the manufacturing sector. The development of the business world affects the complexity of the supply chain due to the lack of logistics infrastructure, quality of materials and components, and much more. Supply chain disruption risk mapping needs to be done due to high uncertainty, which is overcome by implementing a decision support system. Based on the background of the problem, supply chain disruption mapping uses the help of the Six Sigma method, which consists of 5 stages: Define, Measure, Analyze, Improve, and Control (DMAIC). The measurement of disturbance also uses the Failure Mode and Effect Analysis (FMEA) approach to prioritize risk. Risks that have a high assessment and cause failure need to be prioritized for improvement. This study aims to map supply chain disruptions in the current manufacturing industry based on the barriers, resistances, and causes detected for making a decision support system prototype. By implementing a decision support system in the supply chain process, it is

The difficulty of innovation risk assessment makes it necessary to use a multi-criteria analysis.

Innovative projects are related to unstructured problems and the uncertainty, therefore,

the use of fuzzy logic in the innovation risk assessment is analyzed. This paper proposes

a method of determining the weights of criteria in order to innovation risk assessment. The

weights are determined by 5 general criteria and 14 detailed criteria of innovation risk assessment.

The proposed method is an extension of the fuzzy AHP method. The extension

consists in taking into consideration the group decision-making approach with experts’ psychological

conditions. The groups of experts have been chosen based on an elaborated form.

The form makes it possible to characterize the persons within the scope of different psychological

conditions. The proposed method provides objective and rational decision-making.

The paper presents also a comparison of results with the fuzzy AHP method without the

group decision making. The weights obtained by the proposed method are more diversified

and bring out the most important criteria.

Open pit mining of rock minerals and the affected areas requiring further development are a serious challenge for shaping the positive image of the mining industry among the public. The direction and method of post-mining land reclamation are important for this image, which should take into account various factors describing the mining area, including social preferences. The article presents an example solution – fuzzy system (FSDR) – which supports the selection of the direction of reclamation of post-mining areas created after the termination of operations of open pit gravel and sand natural aggregate mines. The article presents selected factors determining the selection of the direction and possible reclamation variants as input and output data of the fuzzy system. The rules base of the developed system, as well as the mechanisms of inference and defuzzification, were also characterized. The application of the developed system is presented on selected examples.

In the field experiments performed in 1999–2001 the profitability of late blight control in accordance with three decision support systems: NegFry, Simphyt and Stephan with routine fungicide program was compared. Potato protection carried out according to the recommendations of the decision support systems guaranteed higher profitability of late blight control than when potato was protected routinely. The highest profitability was recorded for susceptible variety Bekas protected according to NegFr.

As the most recent video coding standard, High Efficiency Video Coding (HEVC) adopts various novel techniques, including a quad-tree based coding unit (CU) structure and additional angular modes used for intra encoding. These new techniques achieve a notable improvement in coding efficiency at the penalty of significant computational complexity increase. Thus, a fast HEVC coding algorithm is highly desirable. In this paper, we propose a fast intra CU decision algorithm for HEVC to reduce the coding complexity, mainly based on a key-point detection. A CU block is considered to have multiple gradients and is early split if corner points are detected inside the block. On the other hand, a CU block without corner points is treated to be terminated when its RD cost is also small according to statistics of the previous frames. The proposed fast algorithm achieves over 62% encoding time reduction with 3.66%, 2.82%, and 2.53% BD-Rate loss for Y, U, and V components, averagely. The experimental results show that the proposed method is efficient to fast decide CU size in HEVC intra coding, even though only static parameters are applied to all test sequences.

A significant part of the knowledge used in the production processes is represented with natural language. Yet, the use of that knowledge

in computer-assisted decision-making requires the application of appropriate formal and development tools. An interesting possibility is

created by the use of an ontology that is understandable both for humans and for the computer. This paper presents a proposal for

structuring the information about the foundry processes, based on the definition of ontology adapted to the physical structure of the

ongoing technological operations that make up the process of producing castings.

The computational intelligence tool has major contribution to analyse the properties of materials without much experimentation. The B4C particles are used to improve the quality of the strength of materials. With respect to the percentage of these particles used in the micro and nano, composites may fix the mechanical properties. The different combinations of input parameters determine the characteristics of raw materials. The load, content of B4C particles with 0%, 2%, 4%, 6%, 8% and 10% will determine the wear behaviour like CoF, wear rate etc. The properties of materials like stress, strain, % of elongation and impact energy are studied. The temperature based CoF and wear rate is analysed. The temperature may vary between 30°C, 100°C and 200°C. In addition, the CoF and wear rate of materials are predicted with respect to load, weight % of B4C and nano hexagonal boron nitride %. The intelligent tools like Neural Networks (BPNN, RBNN, FL and Decision tree) are applied to analyse these characteristics of micro / nano composites with the inclusion of B4C particles and nano hBN % without physically conducting the experiments in the Lab. The material properties will be classified with respect to the range of input parameters using the computational model.

A concern about the current state of relations between industry and the environment is

often neglected. However, it is important to underline that industry and sustainability are

not mutually exclusive. There are many industrial processes to blame when analyzing the

negative impact on current socio-ecological environment. The emerging question is whether

companies nowadays are ready to face challenges in the name of sustainability, the future

of the planet and generations to come. In addition, an assessment of industrial processes

may be very time-consuming and costly in financial terms. This fact allows developing sustainability

assessment approach and its measures for keeping track on to evaluate scale of

environmental, social and economic changes. The goal of the paper is to develop a multicriteria

decision-making approach for sustainability assessment of renewable energy technology.

A sustainability assessment approach combines life cycle-based methods integrated with

multi-criteria decision-making method based on analytical hierarchy process. The resulting

assessment method allows finding a compromise between industry and the environment and

identify potential intervention points for further research. As a result of decision-making

process, string ribbon technology was considered as the most sustainable. The applicability

of the proposed method is assessed based on photovoltaic panels.

The specificity of tool provisioning is conditioned using tooling, the quantity of which

exceeds the nomenclature of the manufactured goods considerably. Therefore, for modern

enterprises, first-priority issues are harmonizing the processes of tool provisioning systems,

increasing the level of the reaction of this system to changes, obtaining operational control

over the production system, and, thus, improving the efficiency of the production process.

In this paper, a mathematical model of decision-making based on determining the optimal

strategy for the process flow was proposed to improve the efficiency of the information

system for quality management of tool provisioning. It is suggested to use the sustainable

development factor of information system for quality management of tool provisioning to

make decisions about the path of the tooling process, which considers the requirements of

international standards for management systems (ISO 9001, ISO 45001, etc.). This model

is based on the application of graph optimization theory, fuzzy logic, and Markov chains.

The use of this model is universal and will increase the validity of operational management

decisions, increase productivity, reduce resource dependency, and, therefore, reduce the

costs of tool provisioning, which directly affects the cost of production and competitiveness

of the enterprise as a whole.