Abstract: Pre-construction is essential in achieving the success of a construction project. Due to the early involvement of project participants in the construction phase, project managers are able to plan ahead and solve issues well in advance leading to the success of the project and the satisfaction of the client. This research utilizes quantitative data derived from construction management projects in order to identify the relationship between pre-construction, construction schedule, and client satisfaction. A total of 65 construction projects and 93 clients were investigated for this research in an attempt to identify (a) the relationship between pre-construction and schedule reduction, and (b) pre-construction and client loyalty. Based on the quantitative analysis, this research was able to establish a negative correlation based on 65 construction projects between pre-construction and project schedule existed. This finding represents that the more pre-construction is performed for a certain project, the overall construction schedule decreased. Then, to determine the relationship between pre-construction and client satisfaction, Net Promoter Score (NPS) of 93 clients from the 65 projects was utilized. Pre-construction and NPS was further analyzed and a positive correlation was found between the two. This infers that clients tend to be more satisfied with projects with higher ratio of pre-construction than those projects with less pre-construction.
Abstract: Although gun barrel steels are an important variety from defense view point, available literatures are very limited. In the present work, an IF grade Ni-Cr-Mo-V high strength low alloy steel is produced in Electric Earth Furnace-ESR Route. Ingot was hot forged to desired dimension with a reduction ratio of 70-75% followed by homogenization, hardening and tempering treatment. Sample chemistry, NMIR, macro and micro structural analyses were done. Mechanical properties which include tensile, impact, and fracture toughness were studied. Ultrasonic testing was done to identify internal flaws. The existing high strength low alloy Ni-Cr-Mo-V steel shows improved properties in modified processing route and heat treatment schedule in comparison to properties noted earlier for manufacturing of gun barrels. The improvement in properties seems to withstand higher explosive loads with the same amount of steel in gun barrel application.
Abstract: In this paper, we study the Minimum Latency Broadcast
Scheduling (MLBS) problem in wireless sensor networks (WSNs).
The main issue of the MLBS problem is to compute schedules
with the minimum number of timeslots such that a base station can
broadcast data to all other sensor nodes with no collisions. Unlike
existing works that utilize the traditional omni-directional WSNs,
we target the directional WSNs where nodes can collaboratively
determine and orientate their antenna directions. We first develop
a 7-approximation algorithm, adopting directional WSNs. Our ratio
is currently the best, to the best of our knowledge. We then validate
the performance of the proposed algorithm through simulation.
Abstract: Patient satisfaction represents a crucial aspect in the evaluation of health care services. Preoperative teaching provides the patient with pertinent information concerning the surgical process and the intended surgical procedure as well as anticipated patient behavior (anxiety, fear), expected sensation, and the probable outcomes. Although patient education is part of Accreditation protocols, it is not uniform at most places. The aim of this study was to try to assess the benefit of preoperative patient education on selected post-operative outcome parameters; mainly, post-operative pain scores, requirement of additional analgesia, return to activity of daily living and overall patient satisfaction, and try to standardize few education protocols. Dependent variables were measured before and after the treatment on a study population of 302 volunteers. Educational intervention was provided by the Investigator in the preoperative period to the study group through personal counseling. An information booklet contained detailed information was also provided. Statistical Analysis was done using Chi square test, Mann Whitney u test and Fischer Exact Test on a total of 302 subjects. P value
Abstract: In this paper, we study the data collection problem in
Wireless Sensor Networks (WSNs) adopting the two interference
models: The graph model and the more realistic physical interference
model known as Signal-to-Interference-Noise-Ratio (SINR). The
main issue of the problem is to compute schedules with the minimum
number of timeslots, that is, to compute the minimum latency
schedules, such that data from every node can be collected without
any collision or interference to a sink node. While existing works
studied the problem with unit-sized and unbounded-sized message
models, we investigate the problem with the bounded-sized message
model, and introduce a constant factor approximation algorithm.
To the best known of our knowledge, our result is the first result
of the data collection problem with bounded-sized model in both
interference models.
Abstract: In the study, we present a conceptual framework for developing a scheduling system that can generate self-explanatory and easy-understanding schedules. To this end, a user interface is conceived to help planners record factors that are considered crucial in scheduling, as well as internal and external sources relating to such factors. A hybrid approach combining machine learning and constraint programming is developed to generate schedules and the corresponding factors, and accordingly display them on the user interface. Effects of the proposed system on scheduling are discussed, and it is expected that scheduling efficiency and system understandability will be improved, compared with previous scheduling systems.
Abstract: This paper gives an intuition regarding glowworm swarm optimization (GSO) technique to solve dynamic economic dispatch (DED) problems of thermal generating units. The objective of the problem is to schedule optimal power generation of dedicated thermal units over a specific time band. In this study, Glowworm swarm optimization technique enables a swarm of agents to split into subgroup, exhibit simultaneous taxis towards each other and rendezvous at multiple optima (not necessarily equal) of a given multimodal function. The feasibility of the GSO method has been tested on ten-unit-test systems where the power balance constraints, operating limits, valve point effects, and ramp rate limits are taken into account. The results obtained by the proposed technique are compared with other heuristic techniques. The results show that GSO technique is capable of producing better results.
Abstract: During aircraft maintenance scheduling, operator calculates the budget of the maintenance. Usually, this calculation includes only the costs that are directly related to the maintenance process such as cost of labor, material, and equipment. In some cases, overhead cost is also included. However, in some of those, downtime cost is neglected claiming that grounding is a natural fact of maintenance; therefore, it is not considered as part of the analytical decision-making process. Based on the normalized data, we introduce downtime cost with its monetary value and add its seasonal character. We envision that the rest of the model, which works together with the downtime cost, could be checked with the real life cases, through the review of MRO cost and airline spending in the particular and scheduled maintenance events.
Abstract: From a theoretical perspective, electric buses can be more sustainable and can be cheaper than fossil fuelled buses in city traffic. The authors have not found other studies based on actual urban public transport in Swedish winter climate. Further on, noise measurements from buses for the European market were found old. The aims of this follow-up study was therefore to test and possibly verify in a real-life environment how energy efficient and silent electric buses are, and then conclude on if electric buses are preferable to use in public transport. The Ebusco 2.0 electric bus, fitted with a 311 kWh battery pack, was used and the tests were carried out during November 2014-April 2015 in eight municipalities in the south of Sweden. Six tests took place in urban traffic and two took place in more of a rural traffic setting. The energy use for propulsion was measured via logging of the internal system in the bus and via an external charging meter. The average energy use turned out to be 8% less (0,96 kWh/km) than assumed in the earlier theoretical study. This rate allows for a 320 km range in public urban traffic. The interior of the bus was kept warm by a diesel heater (biodiesel will probably be used in a future operational traffic situation), which used 0,67 kWh/km in January. This verified that electric buses can be up to 25% cheaper when used in public transport in cities for about eight years. The noise was found to be lower, primarily during acceleration, than for buses with combustion engines in urban bus traffic. According to our surveys, most passengers and drivers appreciated the silent and comfortable ride and preferred electric buses rather than combustion engine buses. Bus operators and passenger transport executives were also positive to start using electric buses for public transport. The operators did however point out that procurement processes need to account for eventual risks regarding this new technology, along with personnel education. The study revealed that it is possible to establish a charging infrastructure for almost all studied bus lines. However, design of a charging infrastructure for each municipality requires further investigations, including electric grid capacity analysis, smart location of charging points, and tailored schedules to allow fast charging. In conclusion, electric buses proved to be a preferable alternative for all stakeholders involved in public bus transport in the studied municipalities. However, in order to electric buses to be a prominent support for sustainable development, they need to be charged either by stand-alone units or via an expansion of the electric grid, and the electricity should be made from new renewable sources.
Abstract: This paper discusses the simulation and experimental work of small Smart Grid containing ten consumers. Smart Grid is characterized by a two-way flow of real-time information and energy. RTP (Real Time Pricing) based tariff is implemented in this work to reduce peak demand, PAR (peak to average ratio) and cost of energy consumed. In the experimental work described here, working of Smart Plug, HEC (Home Energy Controller), HAN (Home Area Network) and communication link between consumers and utility server are explained. Algorithms for Smart Plug, HEC, and utility server are presented and explained in this work. After receiving the Real Time Price for different time slots of the day, HEC interacts automatically by running an algorithm which is based on Linear Programming Problem (LPP) method to find the optimal energy consumption schedule. Algorithm made for utility server can handle more than one off-peak time period during the day. Simulation and experimental work are carried out for different cases. At the end of this work, comparison between simulation results and experimental results are presented to show the effectiveness of the minimization method adopted.
Abstract: This paper proposes a cost-effective private grid using Object-based Grid Architecture (OGA). In OGA, the data process privacy and inter communication are increased through an object- oriented concept. The limitation of the existing grid is that the user can enter or leave the grid at any time without schedule and dedicated resource. To overcome these limitations, cost-effective private grid and appropriate algorithms are proposed. In this, each system contains two platforms such as grid and local platforms. The grid manager service running in local personal computer can act as grid resource. When the system is on, it is intimated to the Monitoring and Information System (MIS) and details are maintained in Resource Object Table (ROT). The MIS is responsible to select the resource where the file or the replica should be stored. The resource storage is done within virtual single private grid nodes using random object addressing to prevent stolen attack. If any grid resource goes down, then the resource ID will be removed from the ROT, and resource recovery is efficiently managed by the replicas. This random addressing technique makes the grid storage a single storage and the user views the entire grid network as a single system.
Abstract: The cumulative costs for O&M may represent as
much as 65%-90% of the turbine's investment cost. Nowadays the
cost effectiveness concept becomes a decision-making and
technology evaluation metric. The cost of energy metric accounts for
the effect replacement cost and unscheduled maintenance cost
parameters. One key of the proposed approach is the idea of
maintaining the WTs which can be captured via use of a finite state
Markov chain. Such a model can be embedded within a probabilistic
operation and maintenance simulation reflecting the action to be
done. In this paper, an approach of estimating the cost of O&M is
presented. The finite state Markov model is used for decision
problems with number of determined periods (life cycle) to predict
the cost according to various options of maintenance.
Abstract: Mumbai, being traditionally the epicenter of India's
trade and commerce, the existing major ports such as Mumbai and
Jawaharlal Nehru Ports (JN) situated in Thane estuary are also
developing its waterfront facilities. Various developments over the
passage of decades in this region have changed the tidal flux
entering/leaving the estuary. The intake at Pir-Pau is facing the
problem of shortage of water in view of advancement of shoreline,
while jetty near Ulwe faces the problem of ship scheduling due to
existence of shallower depths between JN Port and Ulwe Bunder. In
order to solve these problems, it is inevitable to have information
about tide levels over a long duration by field measurements.
However, field measurement is a tedious and costly affair;
application of artificial intelligence was used to predict water levels
by training the network for the measured tide data for one lunar tidal
cycle. The application of two layered feed forward Artificial Neural
Network (ANN) with back-propagation training algorithms such as
Gradient Descent (GD) and Levenberg-Marquardt (LM) was used to
predict the yearly tide levels at waterfront structures namely at Ulwe
Bunder and Pir-Pau. The tide data collected at Apollo Bunder, Ulwe,
and Vashi for a period of lunar tidal cycle (2013) was used to train,
validate and test the neural networks. These trained networks having
high co-relation coefficients (R= 0.998) were used to predict the tide
at Ulwe, and Vashi for its verification with the measured tide for the
year 2000 & 2013. The results indicate that the predicted tide levels
by ANN give reasonably accurate estimation of tide. Hence, the
trained network is used to predict the yearly tide data (2015) for
Ulwe. Subsequently, the yearly tide data (2015) at Pir-Pau was
predicted by using the neural network which was trained with the
help of measured tide data (2000) of Apollo and Pir-Pau. The analysis of measured data and study reveals that: The
measured tidal data at Pir-Pau, Vashi and Ulwe indicate that there is
maximum amplification of tide by about 10-20 cm with a phase lag
of 10-20 minutes with reference to the tide at Apollo Bunder
(Mumbai). LM training algorithm is faster than GD and with increase
in number of neurons in hidden layer and the performance of the
network increases. The predicted tide levels by ANN at Pir-Pau and
Ulwe provides valuable information about the occurrence of high and
low water levels to plan the operation of pumping at Pir-Pau and
improve ship schedule at Ulwe.
Abstract: Concurrent planning of project scheduling and
material ordering has been increasingly addressed within last decades
as an approach to improve the project execution costs. Therefore, we
have taken the problem into consideration in this paper, aiming to
maximize schedules quality robustness, in addition to minimize the
relevant costs. In this regard, a bi-objective mathematical model is
developed to formulate the problem. Moreover, it is possible to
utilize the all-unit discount for materials purchasing. The problem is
then solved by the E-constraint method, and the Pareto front is
obtained for a variety of robustness values. The applicability and
efficiency of the proposed model is tested by different numerical
instances, finally.
Abstract: The present research aimed at studying the awareness
and attitudes of teachers towards inclusive education. The sample
consisted of 60 teachers, teaching in the primary section (1st – 4th) of
regular schools affiliated to the SSC board in Mumbai. Sample was
selected by Multi-stage cluster sampling technique. A semi-structured
self-constructed interview schedule and a self-constructed attitude
scale was used to study the awareness of teachers about disability and
Inclusive education, and their attitudes towards inclusive education
respectively. Themes were extracted from the interview data and
quantitative data was analyzed using SPSS package. Results revealed
that teachers had some amount of awareness but an inadequate
amount of information on disabilities and inclusive education.
Disability to most (37) teachers meant “an inability to do something”.
The difference between disability and handicap was stated by most as
former being cognitive while handicap being physical in nature. With
regard to Inclusive education, a large number (46) stated that they
were unaware of the term and did not know what it meant. Majority
(52) of them perceived maximum challenges for themselves in an
inclusive set up, and emphasized on the role of teacher training
courses in the area of providing knowledge (49) and training in
teaching methodology (53). Although, 83.3% of teachers held a
moderately positive attitude towards inclusive education, a large
percentage (61.6%) of participants felt that being in inclusive set up
would be very challenging for both children with special needs and
without special needs. Though, most (49) of the teachers stated that
children with special needs should be educated in regular classroom
but they further clarified that only those should be in a regular
classroom who have physical impairments of mild or moderate
degree.
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: Round addition differential fault analysis using
operation skipping for lightweight block ciphers with on-the-fly key
scheduling is presented. For 64-bit KLEIN, it is shown that only a pair
of correct and faulty ciphertexts can be used to derive the secret master
key. For PRESENT, one correct ciphertext and two faulty ciphertexts
are required to reconstruct the secret key. Furthermore, secret key
extraction is demonstrated for the LBlock Feistel-type lightweight
block cipher.
Abstract: Cancer is still one of the serious diseases threatening
the lives of human beings. How to have an early diagnosis and
effective treatment for tumors is a very important issue. The animal
carcinoma model can provide a simulation tool for the studies of
pathogenesis, biological characteristics, and therapeutic effects.
Recently, drug delivery systems have been rapidly developed to
effectively improve the therapeutic effects. Liposome plays an
increasingly important role in clinical diagnosis and therapy for
delivering a pharmaceutic or contrast agent to the targeted sites.
Liposome can be absorbed and excreted by the human body, and is
well known that no harm to the human body. This study aimed to
compare the therapeutic effects between encapsulated (doxorubicin
liposomal, Lipodox) and un-encapsulated (doxorubicin, Dox)
anti-tumor drugs using magnetic resonance imaging (MRI).
Twenty-four New Zealand rabbits implanted with VX2 carcinoma at
left thighs were classified into three groups: control group (untreated),
Dox-treated group, and LipoDox-treated group, 8 rabbits for each
group. MRI scans were performed three days after tumor implantation.
A 1.5T GE Signa HDxt whole body MRI scanner with a high
resolution knee coil was used in this study. After a 3-plane localizer
scan was performed, three-dimensional (3D) fast spin echo (FSE)
T2-weighted Images (T2WI) was used for tumor volumetric
quantification. Afterwards, two-dimensional (2D) spoiled gradient
recalled echo (SPGR) dynamic contrast-enhanced (DCE) MRI was
used for tumor perfusion evaluation. DCE-MRI was designed to
acquire four baseline images, followed by contrast agent Gd-DOTA
injection through the ear vein of rabbit. A series of 32 images were
acquired to observe the signals change over time in the tumor and
muscle. The MRI scanning was scheduled on a weekly basis for a
period of four weeks to observe the tumor progression longitudinally.
The Dox and LipoDox treatments were prescribed 3 times in the first
week immediately after the first MRI scan; i.e. 3 days after VX2 tumor
implantation. ImageJ was used to quantitate tumor volume and time
course signal enhancement on DCE images. The changes of tumor size
showed that the growth of VX2 tumors was effectively inhibited for
both LipoDox-treated and Dox-treated groups. Furthermore, the tumor
volume of LipoDox-treated group was significantly lower than that of
Dox-treated group, which implies that LipoDox has better therapeutic effect than Dox. The signal intensity of LipoDox-treated group is
significantly lower than that of the other two groups, which implies
that targeted therapeutic drug remained in the tumor tissue. This study
provides a radiation-free and non-invasive MRI method for
therapeutic monitoring of targeted liposome on an animal tumor
model.
Abstract: Scheduled waste management is very important in
environmental and health aspects. In delivering services, highway
industry has been indirectly involved in producing scheduled wastes.
This paper aims to define the scheduled waste, to provide a
conceptual framework of the scheduled waste management in
highway industry, to highlight the effect of improper management of
scheduled waste and to encourage future researchers to identify and
share the present practice of scheduled waste management in their
country. The understanding on effective management of scheduled
waste will help the operators of highway industry, the academicians,
future researchers, and encourage a friendly environment around the
world. The study on scheduled waste management in highway
industry is very crucial as highway transverse and run along
kilometers crossing the various type of environment, residential and
schools. Using Environmental Quality (Scheduled Waste)
Regulations 2005 as a guide, this conceptual paper highlight several
scheduled wastes produced by highway industry in Malaysia and
provide a conceptual framework of scheduled waste management that
focused on the highway industry. Understanding on scheduled waste
management is vital in order to preserve the environment. Besides
that, the waste substances are hazardous to human being. Many
diseases have been associated with the improper management of
schedule waste such as cancer, throat irritation and respiration
problem.
Abstract: This paper evaluates the accrual based scheduling for
cloud in single and multi-resource system. Numerous organizations
benefit from Cloud computing by hosting their applications. The
cloud model provides needed access to computing with potentially
unlimited resources. Scheduling is tasks and resources mapping to a
certain optimal goal principle. Scheduling, schedules tasks to virtual
machines in accordance with adaptable time, in sequence under
transaction logic constraints. A good scheduling algorithm improves
CPU use, turnaround time, and throughput. In this paper, three realtime
cloud services scheduling algorithm for single resources and
multiple resources are investigated. Experimental results show
Resource matching algorithm performance to be superior for both
single and multi-resource scheduling when compared to benefit first
scheduling, Migration, Checkpoint algorithms.