Abstract: Nowadays, Heritage Building Information Modeling (HBIM) is considered an efficient tool to represent and manage information of Cultural Heritage (CH). The basis of this tool relies on a 3D model generally obtained from a Cloud-to-BIM procedure. There are different methods to create an HBIM model that goes from manual modeling based on the point cloud to the automatic detection of shapes and the creation of objects. The selection of these methods depends on the desired Level of Development (LOD), Level of Information (LOI), Grade of Generation (GOG) as well as on the availability of commercial software. This paper presents the 3D modeling of a stone masonry chapel using Recap Pro, Revit and Dynamo interface following a three-step methodology. The first step consists of the manual modeling of simple structural (e.g., regular walls, columns, floors, wall openings, etc.) and architectural (e.g., cornices, moldings and other minor details) elements using the point cloud as reference. Then, Dynamo is used for generative modeling of complex structural elements such as vaults, infills and domes. Finally, semantic information (e.g., materials, typology, state of conservation, etc.) and pathologies are added within the HBIM model as text parameters and generic models’ families respectively. The application of this methodology allows the documentation of CH following a relatively simple to apply process that ensures adequate LOD, LOI and GOG levels. In addition, the easy implementation of the method as well as the fact of using only one BIM software with its respective plugin for the scan-to-BIM modeling process means that this methodology can be adopted by a larger number of users with intermediate knowledge and limited resources, since the BIM software used has a free student license.
Abstract: The purpose of this paper is to present a classification of Lean models which aims to capture all the concepts related to this approach and thus facilitate its implementation. This classification allows the identification of the most relevant models according to several dimensions. From this perspective, we present a review and an analysis of Lean models literature and we propose dimensions for the classification of the current proposals while respecting among others the axes of the Lean approach, the maturity of the models as well as their application domains. This classification allowed us to conclude that researchers essentially consider the Lean approach as a toolbox also they design their models to solve problems related to a specific environment. Since Lean approach is no longer intended only for the automotive sector where it was invented, but to all fields (IT, Hospital, ...), we consider that this approach requires a generic model that is capable of being implemented in all areas.
Abstract: The learning process needs to be so pervasive to impart the quality in acquiring the knowledge about a subject by making use of the advancement in the field of information and communication systems. However, pervasive learning paradigms designed so far are system automation types and they lack in factual pervasive realm. Providing factual pervasive realm requires subtle ways of teaching and learning with system intelligence. Augmentation of intelligence with pervasive learning necessitates the most efficient way of representing knowledge for the system in order to give the right learning material to the learner. This paper presents a method of representing knowledge for Pervasive Toolroom Maintenance System (PTMS) in which a learner acquires sublime knowledge about the various kinds of tools kept in the toolroom and also helps for effective maintenance of the toolroom. First, we explicate the generic model of knowledge representation for PTMS. Second, we expound the knowledge representation for specific cases of toolkits in PTMS. We have also presented the conceptual view of knowledge representation using ontology for both generic and specific cases. Third, we have devised the relations for pervasive knowledge in PTMS. Finally, events are identified in PTMS which are then linked with pervasive data of toolkits based on relation formulated. The experimental environment and case studies show the accuracy and efficient knowledge representation of toolkits in PTMS.
Abstract: The agenda of showing the scheduled time for
performing certain tasks is known as timetabling. It is widely used in
many departments such as transportation, education, and production.
Some difficulties arise to ensure all tasks happen in the time and
place allocated. Therefore, many researchers invented various
programming models to solve the scheduling problems from several
fields. However, the studies in developing the general integer
programming model for many timetabling problems are still
questionable. Meanwhile, this thesis describes about creating a
general model which solves different types of timetabling problems
by considering the basic constraints. Initially, the common basic
constraints from five different fields are selected and analyzed. A
general basic integer programming model was created and then
verified by using the medium set of data obtained randomly which is
much similar to realistic data. The mathematical software, AIMMS
with CPLEX as a solver has been used to solve the model. The model
obtained is significant in solving many timetabling problems easily
since it is modifiable to all types of scheduling problems which have
same basic constraints.
Abstract: Applications of the Hausdorff space and its mappings
into tangent spaces are outlined, including their fractal dimensions
and self-similarities. The paper details this theory set up and further
describes virtualizations and atomization of manufacturing processes.
It demonstrates novel concurrency principles that will guide
manufacturing processes and resources configurations. Moreover,
varying levels of details may be produced by up folding and breaking
down of newly introduced generic models. This choice of layered
generic models for units and systems aspects along specific aspects
allows research work in parallel to other disciplines with the same
focus on all levels of detail. More credit and easier access are granted
to outside disciplines for enriching manufacturing grounds. Specific
mappings and the layers give hints for chances for interdisciplinary
outcomes and may highlight more details for interoperability
standards, as already worked on the international level. The new rules
are described, which require additional properties concerning all
involved entities for defining distributed decision cycles, again on the
base of self-similarity. All properties are further detailed and assigned
to a maturity scale, eventually displaying the smartness maturity of a
total shopfloor or a factory. The paper contributes to the intensive
ongoing discussion in the field of intelligent distributed
manufacturing and promotes solid concepts for implementations of
Cyber Physical Systems and the Internet of Things into
manufacturing industry, like industry 4.0, as discussed in German-speaking
countries.
Abstract: The development of allometric models is crucial to
accurate forest biomass/carbon stock assessment. The aim of this
study was to develop a set of biomass prediction models that will
enable the determination of total tree aboveground biomass for
savannah woodland area in Niger State, Nigeria. Based on the data
collected through biometric measurements of 1816 trees and
destructive sampling of 36 trees, five species specific and one site
specific models were developed. The sample size was distributed
equally between the five most dominant species in the study site
(Vitellaria paradoxa, Irvingia gabonensis, Parkia biglobosa,
Anogeissus leiocarpus, Pterocarpus erinaceous). Firstly, the
equations were developed for five individual species. Secondly these
five species were mixed and were used to develop an allometric
equation of mixed species. Overall, there was a strong positive
relationship between total tree biomass and the stem diameter. The
coefficient of determination (R2 values) ranging from 0.93 to 0.99 P
< 0.001 were realised for the models; with considerable low standard
error of the estimates (SEE) which confirms that the total tree above
ground biomass has a significant relationship with the dbh. F-test
values for the biomass prediction models were also significant at p
Abstract: The main purpose of this research is to construct a generic model for successful implementation of Total Quality Management (TQM) in Oil sector, and to find out the effects of this model on the organizational sustainability development (OSD) performance of Libyan oil and gas companies using the structured equation modeling (SEM) approach. The research approach covers both quantitative and qualitative methods. A questionnaire was developed in order to identify the quality factors that are seen by Libyan oil and gas companies to be critical to the success of TQM implementation. Hypotheses were developed to evaluate the impact of TQM implementation on O SD. Data analysis reveals that there is a significant positive effect of the TQM implementation on OSD. 24 quality factors are found to be critical and absolutely essential for successful TQM implementation. The results generated a structure of the TQMSD implementation framework based on the four major road map constructs (Top management commitment, employee involvement and participation, customer-driven processes, and continuous improvement culture).
Abstract: In recent years ‘technology management and policymaking’ is one of the most important problems in management science. In this field, different generations of innovation and technology management are presented which the earliest one is Innovation System (IS) approach. In a general classification, innovation systems are divided in to 4 approaches: technical, sectoral, regional, and national. There are many researches in relation to each of these approaches in different academic fields. Every approach has some benefits. If two or more approaches hybrid, their benefits would be combined. In addition, according to the sectoral structure of the governance model in Iran, in many sectors, such as information technology, the combination of three other approaches with sectoral approach is essential. Hence, in this paper, combining two IS approaches (technical and sectoral) and using system dynamics, a generic model is presented for a sample of software industry. As a complimentary point, this article is introducing a new hybrid approach called Techno-Sectoral Innovation System. This TSIS model is accomplished by Changing concepts of the ‘functions’-which came from Technological IS literature- and using them into sectoral system as measurable indicators.
Abstract: Location-aware computing is a type of pervasive
computing that utilizes user-s location as a dominant factor for
providing urban services and application-related usages. One of the
important urban services is navigation instruction for wayfinders in a
city especially when the user is a tourist. The services which are
presented to the tourists should provide adapted location aware
instructions. In order to achieve this goal, the main challenge is to
find spatial relevant objects and location-dependent information. The
aim of this paper is the development of a reusable location-aware
model to handle spatial relevancy parameters in urban location-aware
systems. In this way we utilized ontology as an approach which could
manage spatial relevancy by defining a generic model. Our
contribution is the introduction of an ontological model based on the
directed interval algebra principles. Indeed, it is assumed that the
basic elements of our ontology are the spatial intervals for the user
and his/her related contexts. The relationships between them would
model the spatial relevancy parameters. The implementation language
for the model is OWLs, a web ontology language. The achieved
results show that our proposed location-aware model and the
application adaptation strategies provide appropriate services for the
user.
Abstract: Renewed interest in propeller propulsion on aircraft
configurations combined with higher propeller loads lead to the question how the effects of the propulsion on model support disturbances
should be accounted for. In this paper, the determination of engine power effects on support interference of sting-mounted models is
demonstrated by a measurement on a four-engine turboprop aircraft.
CFD results on a more generic model are presented in order to clarify
the possible mechanism behind engine power effects on support
interference. The engine slipstream induces a local change in angle
of sideslip at the model sting thereby influencing the sting near-field and far-field effects. Whether or not the net result of these changes
in the disturbance pattern leads to a significant engine power effect depends on the configuration of the wind tunnel model and the test
setup.
Abstract: Distant-talking voice-based HCI system suffers from
performance degradation due to mismatch between the acoustic
speech (runtime) and the acoustic model (training). Mismatch is
caused by the change in the power of the speech signal as observed at
the microphones. This change is greatly influenced by the change in
distance, affecting speech dynamics inside the room before reaching
the microphones. Moreover, as the speech signal is reflected, its
acoustical characteristic is also altered by the room properties. In
general, power mismatch due to distance is a complex problem. This
paper presents a novel approach in dealing with distance-induced
mismatch by intelligently sensing instantaneous voice power variation
and compensating model parameters. First, the distant-talking speech
signal is processed through microphone array processing, and the
corresponding distance information is extracted. Distance-sensitive
Gaussian Mixture Models (GMMs), pre-trained to capture both
speech power and room property are used to predict the optimal
distance of the speech source. Consequently, pre-computed statistic
priors corresponding to the optimal distance is selected to correct
the statistics of the generic model which was frozen during training.
Thus, model combinatorics are post-conditioned to match the power
of instantaneous speech acoustics at runtime. This results to an
improved likelihood in predicting the correct speech command at
farther distances. We experiment using real data recorded inside two
rooms. Experimental evaluation shows voice recognition performance
using our method is more robust to the change in distance compared
to the conventional approach. In our experiment, under the most
acoustically challenging environment (i.e., Room 2: 2.5 meters), our
method achieved 24.2% improvement in recognition performance
against the best-performing conventional method.
Abstract: In order to optimize annual IT spending and to reduce
the complexity of an entire system architecture, SOA trials have been
started. It is common knowledge that to design an SOA system we
have to adopt the top-down approach, but in reality silo systems are
being made, so these companies cannot reuse newly designed services,
and cannot enjoy SOA-s economic benefits. To prevent this situation,
we designed a generic SOA development process referred to as the
architecture of “mass customization."
To define the generic detail development processes, we did a case
study on an imaginary company. Through the case study, we could
define the practical development processes and found this could vastly
reduce updating development costs.