A data warehouse conceptual data model

The development of an Electronic Health Record (EHR) system requires a well-defined data set and a robust data model to support complex clinical workflows, interoperability, and data quality. Many existing EHR implementations lack standardized and integrated data models, resulting in redundancy, semantic inconsistency, and limited support for secondary data use. This study aims to develop a comprehensive EHR data model based on a Minimum Data Set (MDS) that systematically represents medical service processes across emergency, outpatient, inpatient, and surgical care. The proposed approach involves the design of a conceptual, logical, and physical data model. Business processes were first analysed to identify relationships among clinical and administrative data classes, which were then transformed into a conceptual data model. The logical data model was developed through database normalization and schema definition, while the physical data model was constructed to represent the actual database structure for implementation. The results demonstrate a structured EHR data model comprising 21 interrelated data classes that reflect real-world medical service workflows. The conceptual data model establishes clear entity relationships, supporting data consistency and interoperability. The logical data model provides a normalized SQL-based schema that minimizes redundancy and enhances data integrity, while the physical data model enables efficient data storage and access. A prototype EHR system was implemented to evaluate the feasibility of the proposed data model, showing stable performance, usability, and alignment with functional requirements. This study concludes that a standardized EHR data model derived from an MDS can effectively support comprehensive clinical documentation, interoperability, and future scalability. The proposed model provides a strong foundation for developing national or institutional EHR systems and can serve as a reference for further EHR data standardization efforts.

Defining and validating metrics for assessing the understandability of entity–relationship diagrams

Fuzzy set theory has been extensively applied to extend various database models and resulted in numerous contributions, mainly with respect to the popular relational model or to some related form of it. To satisfy the need of modeling complex objects with imprecision and uncertainty, recently many researches have been concentrated on fuzzy semantic (conceptual) data models. This paper reviews fuzzy conceptual data models proposed in the literature, where fuzzy ER/EER, IFO and UML data models are mainly discussed, and reviews the applications of fuzzy conceptual data models.

Conceptual data models can change during the information system development and teamwork phases, which require constantly monitoring with synonyms detection. This study elaborates on an approach for detecting synonyms in an entity-relationship model based on mapping with ontological elements. The use of a specific data model validator (DMV) tool enables formalization of the ontology and ER models, as well as their integration with the set of reasoning rules. The reasoning rules enable mapping between formalized elements of the ontology and ER model, and the extraction of synonyms. Formalized elements and reasoning rules are processed within Prolog for the extraction of synonyms. An empirical study conducted by using university student exams demonstrates usability of the proposed approach. The results show effectiveness in extraction of synonyms in all types of conceptual data model elements.

Conceptual modeling is a learning task essential to students of computer science, software engineering and related programs. Construed as a complex task, surprisingly little is known about the actual act of conceptual modeling, and about modeling difficulties learners experience. Combining complementary modes of observation of learners’ modeling processes, we study modeling difficulties encountered while performing a data modeling task. Using the concept of cognitive breakdown, we analyze audiovisual protocols of the individual modelers’ modeling processes, recordings of their interactions with the employed modeling software tool and survey data of modelers about their perception of encountered modeling difficulties. In an exploratory study and a follow-up study, we identify eight types of modeling difficulties related to modeling entity types, generalization hierarchies, relationship types, attributes and cardinalities. The identified types of modeling difficulties contribute to a better and more complete understanding of data modeling processes intended to inform design science research on modeling assistance for data modelers at different stages of their learning and mastering of conceptual data modeling.

Agriculture extension and advisory services is a multidisciplinary discipline based on human interaction seeking to improve the livelihoods of farming communities and individuals by providing information and technologies. The training of extension staff is important as it has a bearing on their effectiveness in the office and in the field. This study sought to determine the HRD activities in agricultural extension and advisory services in the public and private sector. The study was done in 5 counties in Kenya and a total of 440 agricultural extension agents were sampled from the public and private extension service. HRD activities focused on formal and in-service training. 68 % of the respondents had attended formal education to improve their education with the majority 63.5 percent, having trained at the diploma level from certificate level while 21.1 % had undergone training at the degree level from diploma level. The main areas of specialization were Agricultural education (34.1 %), General agriculture (28.1 %) and Horticulture (11.7 %). The inclusion of non-agricultural areas of specialization such as Sustainable development and Strategic planning and management show the multidisciplinary nature of agriculture. Inservice courses attended were in the form of short courses, seminars, or workshops. These were clustered in five general areas; Crop Management, Management, Agricultural Economics, Agricultural Extension, and Animal Science. Most respondents (40.9 percent) had undergone training in Crop management which covered various crop enterprises from breeding to postharvest management. The shift of agricultural policy toward business orientation is reflected in 13.0 % the respondents specializing in Agricultural Economics. These HRD activities show commitment of agricultural extension providers to improve the competencies of their staff to deliver effective services to farmers. The wide range of formal and in-service courses attended also reflects the need to meet the management and technical requirements of a pluralistic and demand driven extension service.

Computer applications in non-traditional areas have put requirements on conceptual data modeling. Some conceptual data models, being the tool of design databases, have been proposed. However, information in real-world applications is often vague or ambiguous. Currently, less research has been done in modeling imprecision and uncertainty in conceptual data models and the design of databases with imprecision and uncertainty. In this chapter, a different level of fuzziness based on fuzzy set and possibility distribution theory will be introduced into the IFO data model and the corresponding graphical representations will be given. The IFO data model is then extended to a fuzzy IFO data model, denoted IF2O. In particular, we provide the approach to mapping an IF2O model to a fuzzy relational database schema.

6 - Normalization

Effort and cost estimation is crucial in software management. Estimation of software size plays a key role in the estimation. Line of Code (LOC) is still a commonly used software size measure. Despite the fact that software sizing is well recognized as an important problem for more than two decades, there is still much problem in existing methods. Conceptual data model is widely used in the requirements analysis for information systems. It is also not difficult to construct conceptual data models in the early stage of developing information systems. Much characteristic of an information system is actually reflected from its conceptual data model. We explore into the use of conceptual data model for estimating LOC. This paper proposes a novel method for estimating LOC for an information system from its conceptual data model through the use of multiple linear regression model. We have validated the method through collecting samples from both the industry and open-source systems.

This lecture is supposed to be a mini–review of the recent results obtained by the Dubna-MainzTubingen Collaboration, see Refs. [1, 2, 3]. The research is aiming to study the semileptonic, rare and radiative decays of the Λb-baryon by using the covariant quark model previously developed by us. The decay Λb → Λ l+l− (l = e, μ, τ) is a rare b − s favor-changing neutral current process that in the Standard Model proceeds through electroweak loop (penguin andW−box) diagrams. This decay can be considered to be a welcome complement to the well–analyzed rare meson decays B → K(∗) l+l−, Bs → φ l+l− etc. to study the short– and long–distance dynamics of rare decays induced by the transition b → s l+l−. However, the study of baryon decays is of more interest because the Λb baryon has spin one half compare with zero spin of the B−meson. Therefore, the matrix element of the baryon decay possesses more rich helicity structure. For the first time, the CDF Collaboration has reported on the measurement of the Λb → Λ+μ+μ− total branching ratio: B(Λb → Λ+μ+μ−) = (1.73± 0.42± 0.55) · 10−6 [4]. Recently, the LHCb Collaboration [5] has measured the differential branching fraction of this decay as a function of the square of the dimuon invariant mass. Integrating the differential branching fraction gives a branching fraction of B(Λb → Λ+μ+μ−) = (0.96±0.16±0.13±0.21)·10−6. Here, the uncertainties are statistical, systematic and due to the normalisation mode, Λb → ΛJ/ψ, respectively. The physics of heavy baryon decays appears to have entered a new era with these experimental results. There have been a number of theoretical papers on the rare Λb → Λ baryon decays involving the one-photon mode Λb → Λγ and the dilepton modes Λb → Λ l+l− (l = e, μ, τ). They use the same set of (penguin) operators or their non–Standard Model extensions to describe the short distance dynamics but differ in their use of theoretical models to calculate the nonperturbative transition matrix element 〈Λ|Oi |Λb〉. We use the covariant constituent quark model (for short: covariant quark model) as dynamical input to calculate the nonperturbative transition matrix elements. In the covariant quark model the current–induced transitions between baryons are calculated from two–loop Feynman diagrams with free quark propagators in which the divergent high energy behavior of the loop integrations is tempered by Gaussian vertex functions. Quark confinement has incorporated in an effective way, first, by introducing the scale integration in the space of α-parameters, and, second, by cutting this scale integration on the upper limit which corresponds to an infrared

A data base design aid, SYDADA, is introduced. Input to SYDADA is a requirements specification, expressed in a language called SYSDOC. A SYSDOC specification consists of two main parts: a conceptual data model and a transaction description. The conceptual data model is a high level, implementation independent data description. The transaction description is expressed in a very high level language which uses the conceptual data model. SYDADA analyzes the requirements specification by modelling the specified system. In the system model the conceptual data model is the data base, and the transactions specified can be executed using this data base. The most important result of the analysis is a set of statistics showing how, and how frequently, the various parts of the conceptual data model are used. We have shown how these statistics can be used as a basis for logical data base design.

This thesis describes the extension of the coordination chemistry of triazacyclohexanes to new copper complexes and to new ligands with similar coordination geometry, i.e. the orthoamides 13-alkyl-1,5,9-triazatricyclo[7.3.1.05,13 ]-tridecanes (RTATC) and unsymmetrically substituted triazacyclohexanes. By treatment of the literature known [TATC]+ cation with Li, Na, or K alkylating reagents several new RTATC (R = Ph, Bz, CH2SiMe3, 4-Bu-PhCH2) have been prepared and characterized. With these and the previously known ligands HTATC and MeTATC complexes of Cr(III), Fe(III), Cu(II), and Zn(II) have been made and their properties have been compared with those of the analogous 1,3,5-trialkyl-1,3,5-triazacyclohexane (R3TAC) complexes. It shows that the structural, chemical, and physical properties of the RTATC complexes are quite similar to those of the R3TAC complexes. [(R3TAC)Cu(PPh3)]BF4 complexes with R = iPr, Bz, Cy, and (S)-PhMeCH have been prepared and characterized. The Cu(I) complexes are diamagnetic and therefore ideal for NMR spectroscopical analysis. The η3-coordination of the ligand can be deduced from the discrimination of the endoand exo-protons of the TACring, which are in fast exchange in the free ligand. From the form of the ring signals a more symmetrical η3-coordination for the Pr3TAC complex and a slightly distorted η3-coordination for the Bz3TAC complex can be expected. This could be verified by x-ray crystal structures of both complexes. A new Cu(II) complex was found when excess Me3TAC was reacted with CuCl2: (Me3TAC)2CuCl2. The unusual coordination geometry leads to a slow reduction to Cu(I). A crystal structure of the reduction product revealed an unusual [Cu2Cl4] 2−. It shows the first Cu-Cu cuprophilic interaction in an anion which must be stronger than the electrostatic repulsion within the dianion. Synthesis of triazacyclohexanes with a mixture of two amines in a suitable solvent such as ethanol or exploitation of equilibria between R3TAC and R ′NH2 above 100 ◦C yields mixtures of unsymmetrically substituted R2R′TAC which could be separated by various methods below 100◦C. The pure and dry unsymmetrical R2R′TAC are stable at room temperature and even at higher temperatures for short periods and can best be identified by their very characteristic 13C NMR signals for the ring carbon atoms. This way a couple of examples for basically three different types of unsymmetrically substituted R2R′TAC could be prepared: simple R2R′TAC with small hydrocarbon substituents (Me2BzTAC, Me2OctTAC), R2(R′X)TAC with a substituent bearing a functional group (Me2(EtOH)TAC, Me2(EtCN)TAC), and two triazacyclohexanes linked by a short bridge R2TAC-R’-R2TAC (Me2TAC-CH2PhCH2Me2TAC), Bu2TAC-CH2PhCH2Bu2TAC).

In the past few years, object–oriented (O–O) conceptual data modeling has emerged as an alternative to the traditional technique of entity–relationship modeling. O–O modeling is based on the premise that the resulting models are easier to use and understand. However, most claims of O–O modeling superiority are not empirically verified. Previous studies in this area have focused on a database modeler’s ability to create conceptual data models from a written description, but the concept of understanding a completed data model by a database designer has not been investigated. Thus, this study explores a database designer’s ability to understand an O–O conceptual data model – the Object Modeling Technique (OMT) – compared to an E–R model – the extended–entity– relationship model (EER). The OMT and EER conceptual data modeling techniques are compared using three modeling performance criteria: (1) model understanding; (2) time to understand; and (3) perceived ease–of–use. Results of this study indicate that the only difference between the two techniques is in the time to understand – OMT is significantly faster for both simple and complex problems.

This paper presents an incremental approach for modeling fatigue crack growth with history effects. This approach is being developed at LMT since 2003, in collaboration with several industrial partners, mainly with Snecma, the SAFRAN Group, EDF and AREVA, and the SNCF. The first part of this paper presents the context, objectives and key assumptions on which the model is based. The second part presents some examples of applications of the model, fatigue crack growth under Mode I conditions, with variable amplitude loading; non-isothermal situations; crack growth under coupled environmental and fatigue loading conditions; extension of the model to non-proportional mixed mode loading conditions and to short cracks. The last part presents the ongoing work, the possible developments and the scientific challenges that remain to be overcome.

The cosmic stories : beginning, evolution, and present days of the universe