Verifying the Correctness of UML Statechart Outpatient Clinic Based on Common Modeling Language and SMV

Unified-modelling language (UML) is a standard general purpose modelling language, which is widely, used in system design of banking, biological, plantation and healthcare. Recently, there are many systems of healthcare are modeled using behavioral diagram such as UML statechart for design purposes. However, the behavior of healthcare statechart is rarely verified to ensure it is behaving as we needed. In software engineering, a software should be verified before it is transform to the further phases. In this paper, a statechart of outpatient clinic is verified to ensuring the correctness of its design. Therefore, to achieve our objective, we have applied Common Modeling Language (CML) and SMV model checker for verification formal system modeling and specification of property of statechart outpatient clinic. The result shows that the statechart of outpatient clinic is behave as required and the statechart is allowable to transform to the next phase

The impact of social and security factors on residential site suitability by using GIS-based MCDM approach: a case study the city of Kirkuk, Iraq

Unplanned population growth, alongside unplanned development, lack of good housing and inadequate infrastructure resulted in a lot of slums and informal settlements in Iraqi cities. In 1980s there were major housing shortage in Iraq as a result of war and political instability which led to economic meltdown. Kirkuk city was one of the most affected cities by multiethnic crises as a result of employment, housing and local government members’ concentration in Kirkuk which led to political and economic migration. Suitable site selection for housing is complicated not just because it has to do with technical procedures and topography but due to environmental, social and political issues which can lead to conflict. Hence, this study seeks to discover the suitable site selection for housing using Geographical Information System (GIS), high resolution remote sensing data and multi criteria analysis (MCA)

Effect of calcium carbonate replacement on workability and mechanical strength of portland cement concrete

Abstract. The continued growth of the world construction sectors has resulted in high demand for concrete materials. The innovation of using filler as a replacement for cement is becoming a trend in order to reduce the cement consumption and provide benefit in various ways. Hence forth, 10% of cement was replaced by the calcium carbonate (CaCO3) in this study. CaCO3 is a natural material, which has a finer particles size as compared to the cement particles. This improves particle packing of concrete and give spacer effect. The concrete with CaCO3 replacement possess a higher slump, which increased the workability. The specimens were prepared in 150mm x 150mm x 150mm mould. At 28 days, the water absorbed by hardened concrete was lower for CaCO3 as microscopy analysis indicates very low porosity in CaCO3 concrete. Mechanical properties tests were conducted in 3, 7 and 28 days. The CaCO3 helps to increase the early strength, due to the accelerator effect and high rate of hydration which hardens the concrete quicker. At matured age, the concrete with the CaCO3 addition exhibits lower strength as compared with concrete without CaCO3, but still within the target strength. Keywords: Calcium carbonate, ordinary Portland cement, particle packing, concrete workability and strengt

Competitive learning in neural networks

The article presents the basic concept of competitive learning in neural networks. Provides the main machine learning learning models and applications. The analysis of the advantages and disadvantages of these models is carried out. The geometric interpretation of competitive learning is presented in terms of mathematical formulas, as well as the behavior of neurons in this model. Neural systems are described as a powerful tool and driver in the field of modern Internet technologies, in data science and big (meta) data.The article presents the basic concept of competitive learning in neural networks. Provides the main machine learning learning models and applications. The analysis of the advantages and disadvantages of these models is carried out. The geometric interpretation of competitive learning is presented in terms of mathematical formulas, as well as the behavior of neurons in this model. Neural systems are described as a powerful tool and driver in the field of modern Internet technologies, in data science and big (meta) data

Effect of microwave sintering treatment to the flank wear of titanium carbide tools in milling operations

The paper reports the research on the improvement of tool wear resistant of Titanium Carbide (TiC) cutting tool after microwave post sintering treatment. Titanium Carbide square milling insert was microwave sintered at 600°C with 15 minutes of holding time. The face milling operations were conducted to Carbon Steel S45C block (130 mm x 95 mm x 40 mm) by using both of original and microwave sintered insert at 5 different cutting speed (60, 90 , 120 , 150 and 180 m/min), constant feed rate (0.2 mm/tooth) and constant depth of cut(0.2 mm/tooth). The flank wear of the insert was measured every nearest 10th minute of complete cutting passes. The results of the experiment show that microwave post sintering treatment improves the tool resistant of the TiC insert. The flank wear of the sintered insert is lower at any machining time and all cutting speed. The research also found that the percentage of the improvement is lower at higher cutting speed compare to lower cutting speed

Development of a convolutional neural network to accurately detect land use and land cover

The detection and modeling of Land Use and Land Cover (LULC) play pivotal roles in natural resource management, environmental modeling and assessment, and ecological connectivity management. However, addressing LULCC detection and modeling constitutes a complex data-driven process. In the present study, a Convolutional Neural Network (CNN) is employed due to its great potential in image classification. The development of these tools applies the deep learning method. A methodology has been developed that classifies the set of land uses in a natural area of special protection. This study area covers the Sierra del Cando (Galicia, northwest Spain), considered by the European Union as a Site of Community Interest and integrated in the Natura 2000 Network. The results of the CNN model developed show an accuracy of 91 % on training dataset and 88 % on test dataset. In addition, the model was tested on images of the study area, both from Sentinel-2 and PNOA. Despite some confusion especially in the residential class due to the characteristics in this area, CNNs prove to be a powerful classification toolXunta de Galicia | Ref. ED481B-2023-042Agencia Estatal de Investigación | Ref. TED2021-130241A-I0

Characteristics of high potential employees: employees’ perspective

The objective of the study was to determine the major characteristics of high potential (HIPO) employees. HIPOs, as defined by Schumacher (2009), are employees who produce excellent work performance consistently. Prior research indicated various characteristics and traits portraying HIPO personalities, characters and competence but the studies only discussed the matter conceptually and in theory.Based on the data collected from 329 respondents, the overall study findings indicated that the term HIPO was made up of different competences as projected by the previous authors. It is reasonable to understand that a person with HIPO must be an individual who always want to produce results beyond expectation or at least meet with the job requirement. The findings suggest that a person with strong drive for high performance is less likely to leave, and must also have learning agility with leadership spirit. For a person with learning agility, besides having leadership spirit and drive for high performance, he/she is also highly engaged to the job and the organization. But for a person with strong leadership spirit, it is not just learning agility and drive for high performance that are important, the person also has high education level, seniority and more engaged to the organization. Nonetheless, positive relationship between leadership spirit and turnover intention will remain as a nightmare to employers. This implies that the more the person looks forward to advancement and building relationships, the more he/she intends to leave the organization

Modeling and Analyzing Cyber-Physical Systems Using Hybrid Predicate Transition Nets

Cyber-Physical Systems (CPSs) are software controlled physical devices that are being used everywhere from utility features in household devices to safety-critical features in cars, trains, aircraft, robots, smart healthcare devices. CPSs have complex hybrid behaviors combining discrete states and continuous states capturing physical laws. Developing reliable CPSs are extremely difficult. Formal modeling methods are especially useful for abstracting and understanding complex systems and detecting and preventing early system design problems. To ensure the dependability of formal models, various analysis techniques, including simulation and reachability analysis, have been proposed in recent decades. This thesis aims to provide a unified formal modeling and analysis methodology for studying CPSs. Firstly, this thesis contributes to the modeling and analysis of discrete, continuous, and hybrid systems. This work enhances modeling of discrete systems using predicate transition nets (PrTNs) by fully realizing the underlying specification through incorporating the first-order logic with set theory, improving the type system, and providing incremental model composition. This work enhances the technique of analyzing discrete systems using PrTN by improving the simulation algorithm and its efficient implementation. This work also improves the analysis of discrete systems using SPIN by providing a more accurate and complete translation method. Secondly, this work contributes to the modeling and analysis of hybrid systems by proposing an extension of PrTNs, hybrid predicate transition nets (HPrTNs). The proposed method incorporates a novel concept of token evolution, which nicely addresses the continuous state evolution and the conflicts present in other related works. This work presents a powerful simulation capability that can handle linear, non-linear dynamics, transcendental functions through differential equations. This work also provides a complementary technique for reachability analysis through the translation of HPrTN models for analysis using SpaceEx

Peat fire mapping using GIS based multi-criteria decision making: study area of Kuala Langat, Selangor / Ainon Nisa Othman … [et al.]

Peat fire is a geological disaster that causes damages to nature, human activities and environment. It is a geological phenomenon that involves a wide range of forest fire, vegetation burnt surface and smouldering fire underground. Besides that, there are other contributing factors affecting the peat fire and can lead to the forest fire disaster. In this study, GIS and MCDM Technique were used as a tool to generate the prediction of peat fire potential area map at Kuala Langat, Selangor. All the input is then being analyse in ArcGIS software. Many criteria may contribute to the peat forest fire incident such as land use, temperature, pH value, and soil type criteria. The main benefit for analysing the potential area is the possibility to prevent and predict peat fire occurrences in future other than as a precaution step to face the problems