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This study examines the correlation between Competitive Intelligence (competitive intelligence) maturity levels and organisational decision-making styles in software industry firms. For this purpose, we followed the competitive intelligence maturity model established by Zuquetto and Beltrame [(2012). Modelo de maturidade em inteligência competitiva. Global Manager Acadêmica, 1(2), 1–19] and the Organisational Decision-Making Perception Scale (ODMPS) model proposed by Nascimento and Gomide Jr [(2014). Tomada de decisão organizacional. In Novas medidas do comportamento organizacional: ferramentas de diagnóstico e de gestão, M. M. M. Siqueira (ed.), pp. 298–306. Porto Alegre: Artmed] was used to assess organisational decision-making styles. A quantitative study was carried out using a closed-ended questionnaire and a Likert scale, targeting managers of software companies. It is worth noting that technical abbreviations were clarified when first used. In addition, the language used in the study was objective, value-neutral and free of ornamental or figurative language. The structure of the study was clear and concise, with logical causality between each statement. The text followed scientifical guidelines for structure, terminology and footnoting. The results show that a significant number of companies have an intermediate level of competitive intelligence maturity and that the systematic approach to decision-making is ubiquitous. Hence, the Spearman Rank Correlation Coefficient (i.e. Spearman’s rho) indicates a positive correlation between competitive intelligence maturity and systematic decision-making in software companies. So, this research helps to understand the relationship between competitive intelligence and organisational decision-making in software companies. According to the findings, organisations with higher levels of competitive intelligence maturity are more likely to adopt a systematic decision-making style. This is noteworthy because systematic decision-making can lead to improved organisational outcomes. The research has implications for academics and practitioners alike. It provides new insights into the relationship between competitive intelligence and organisational decision-making. For practitioners, the findings suggest that investing in competitive intelligence and adopting a methodical approach to decision-making can improve organisational performance. The relationship between competitive intelligence maturity level and organisational decision-making styles in different industries should be explored in further research.

With the increasing role of computing devices, facilitating natural human computer interaction (HCI) will have a positive impact on their usage and acceptance as a whole. For long time, research on HCI has been restricted to techniques based on the use of keyboard, mouse, etc. Recently, this paradigm has changed. Techniques such as vision, sound, speech recognition allow for much richer form of interaction between the user and machine. The emphasis is to provide a natural form of interface for interaction. Gestures are one of the natural forms of interaction between humans. As gesture commands are found to be natural for humans, the development of gesture control systems for controlling devices have become a popular research topic in recent years. Researchers have proposed different gesture recognition systems which act as an interface for controlling the applications. One of the drawbacks of present gesture recognition systems is application dependence which makes it difficult to transfer one gesture control interface into different applications. This paper focuses on designing a vision-based hand gesture recognition system which is adaptive to different applications thus making the gesture recognition systems to be application adaptive. The designed system comprises different processing steps like detection, segmentation, tracking, recognition, etc. For making the system as application-adaptive, different quantitative and qualitative parameters have been taken into consideration. The quantitative parameters include gesture recognition rate, features extracted and root mean square error of the system while the qualitative parameters include intuitiveness, accuracy, stress/comfort, computational efficiency, user's tolerance, and real-time performance related to the proposed system. These parameters have a vital impact on the performance of the proposed application adaptive hand gesture recognition system.

The effective and efficient management of buildings necessitates, amongst other aspects, the ability to interrogate reliable data relating to condition, cost implications of that condition and the spend options available and appropriate. Most buildings have been subject to one or more surveys and data from these is often available to the building owner, manager or user. The form and value of such data is, however, variable in the extreme and is, not least, relevant mainly to the organization or person who commissioned that particular survey.

This paper introduces a quantitative model for the repair and maintenance of buildings/properties. It is based on a coded system of observing, assessing, recording and appraising the condition of those elements of a building which would most influence the costs of repairing or maintaining elements of, or the whole of, buildings.

Background information and criteria for the development of this model is detailed in this paper and also, the model matrix system defining the step-by-step calculation process of cost of repair and maintenance has been reported.

A detailed report on a case-study (application of the model) consisting of the data collection and cost analysis of a property is also provided. The case-study includes a comparison between the predicted cost of repair and the real cost of repair (cost after completion of repair work) concerning a residential dwelling.

The Monte Carlo method is a versatile simulation algorithm to model the propagation of photons inside the biological tissues. It has been applied to the reconstruction of the fluorescence molecular tomography (FMT). However, such method suffers from low computational efficiency, and the time consumption is not desirable. One way to solve this problem is to introduce a priori knowledge which will facilitate iterative convergence. We presented an in vivo simulation environment for fluorescence molecular tomography (ISEFMT) using the Monte Carlo method to simulate the photon distribution of fluorescent objects and their sectional view in any direction quantitatively. A series of simulation experiments were carried out on different phantoms each with two fluorescent volumes to investigate the relationship among fluorescence intensity distribution and the excitation photon number, the locations and sizes of the fluorescence volumes, and the anisotropy coefficient. A significant principle was discovered, that along the direction of the excitation light, the fluorescent volume near the excitation point will provide shelter effect so that the energy of the fluorescent volume farther away from the excitation point is relatively lower. Through quantitative analysis, it was discovered that both the photon energy distribution on every cross section and the fluorescence intensity distributed in the two volumes exhibit exponential relationships. The two maximum positions in this distribution correspond to the centers of fluorescent volumes. Finally, we also explored the effect of the phantom coefficients on the exponential rule, and found out that the exponential rule still exists, only the coefficient of the exponential rule changed. Such results can be utilized in locating the positions of multiple fluorescent volumes in complicated FMT reconstruction involving multiple fluorescent volumes. Thus, a priori knowledge can be generalized, which would accelerate the reconstruction of FMT and even other images.

Angiogenesis is a natural process of new vessel formation from existing ones. The formation of blood vessels in tumors is an interactive process between tumor, endothelial and stromal cells in order to create a network for oxygen and nutrients supply. The chicken embryo chorioallantoic membrane (CAM) model is widely used as an in vivo model to study the vascular effects of angiogenesis modulating agents. The aim of this paper, is to break the blood vessel for quantification.

In an article added recently to the Stanford Encyclopedia of Philosophy, Eran Tal notes that “there is little consensus among philosophers as to how to define measurement, what sorts of things are measurable, or which conditions make measurement possible” [1]

The meaning and scope of measurement have been discussed frequently within physical metrology, by David Hand [2], René Dybkaer [3], Rod White [4], Eran Tal [5], Luca Mari et al. [6], Giovanni Rossi [7], Eran Tal [8], and Luca Mari et al. [9], among others. The same issues have also been examined within the social sciences [10], in particular in education [11, 12], psychology [13–15], and sociology [16, 17].

Defining measurement involves identifying its essential characteristics, and specifying the traits that distinguish it from similar activities that ought not to be construed as measurement. Delineating its scope involves determining the classes of properties whose values are measurable.

None of the logical, terminological, historical, or customary-use considerations that might give preeminence to a particular definition of measurement seem to be decisive, for otherwise a consensus about it would have formed already.

For example, a recent survey of its membership, conducted by the ISO/REMCO committee on reference materials, revealed that the metrological community represented in this committee is just about evenly split on whether the assignment of value to qualitative (nominal, or categorical) properties should, or should not be called "measurement."

Defining the meaning of measurement, and circumscribing its scope, therefore involve arbitrary choices, which concern matters of taste, matters of precedence, and matters of convenience. This contribution discusses these choices, and advocates for an inclusive and broad understanding of measurement.

The inhomogeneous light lattice structure administers to decrease product weight, to enhance structure adaptability, and to enrich the functionality. In order to improve the efficiency of structure modeling, a hybrid method is proposed by combining feature tree creation with user-defined feature (UDF) under CAD. This process is done during the design phase instead of the manufacturing phase. Firstly, a parameter model of lattice cell unit should be established by analyzing the key parameters which affect unit's size and shape, whereafter a UDF model is correspondingly generated. Then set UDF models with different parameters based on reference datum which are computed and inserted according to the component's structure. Comparing with homogeneous lattice structure created by Magics, the result shows that the modeling process can be completed during the design stage and inhomogeneous lattice structure leads to improve the efficiency of structural light-weighting.