Abstract: During the process of the industrialization of steel structure housing, a composite structural system with separated gravity and lateral resistant systems has been applied in engineering practices, which consists of composite frame with hinged beam-column joints, steel brace and RC shear wall. As an attempt in steel structural system area, seismic performance evaluation of the separated composite structure is important for further application in steel housing. This paper focuses on the seismic performance comparison of the separated composite structural system and traditional steel frame-shear wall system under the same inter-story drift ratio (IDR) provision limit. The same architectural layout of a high-rise building is designed as two different structural systems at the same IDR level, and finite element analysis using pushover method is carried out. Static pushover analysis implies that the separated structural system exhibits different lateral deformation mode and failure mechanism with traditional steel frame-shear wall system. Different indexes are adopted and discussed in seismic performance evaluation, including IDR, safe factor (SF), shear wall damage, etc. The performance under maximum considered earthquake (MCE) demand spectrum shows that the shear wall damage of two structural systems are similar; the separated composite structural system exhibits less plastic hinges; and the SF index value of the separated composite structural system is higher than the steel frame shear wall structural system.
Abstract: The use of a radiant cooling solution would enable to lower cooling needs which is of great interest when the demand is initially high (hot climate). But, radiant systems are not naturally compatibles with humid climates since a low-temperature surface leads to condensation risks as soon as the surface temperature is close to or lower than the dew point temperature. A radiant cooling system combined to a dehumidification system would enable to remove humidity for the space, thereby lowering the dew point temperature. The humidity removal needs to be especially effective near the cooled surface. This requirement could be fulfilled by a system using a single desiccant fluid for the removal of both excessive heat and moisture. This task aims at providing an estimation of the specification requirements of such system in terms of cooling power and dehumidification rate required to fulfill comfort issues and to prevent any condensation risk on the cool panel surface. The present paper develops a preliminary study on the specification requirements, performances and behavior of a combined dehumidifier/cooling ceiling panel for different operating conditions. This study has been carried using the TRNSYS software which allows nodal calculations of thermal systems. It consists of the dynamic modeling of heat and vapor balances of a 5m x 3m x 2.7m office space. In a first design estimation, this room is equipped with an ideal heating, cooling, humidification and dehumidification system so that the room temperature is always maintained in between 21◦C and 25◦C with a relative humidity in between 40% and 60%. The room is also equipped with a ventilation system that includes a heat recovery heat exchanger and another heat exchanger connected to a heat sink. Main results show that the system should be designed to meet a cooling power of 42W.m−2 and a desiccant rate of 45 gH2O.h−1. In a second time, a parametric study of comfort issues and system performances has been achieved on a more realistic system (that includes a chilled ceiling) under different operating conditions. It enables an estimation of an acceptable range of operating conditions. This preliminary study is intended to provide useful information for the system design.
Abstract: Reducing energy consumption and CO2 emissions are probably the greatest challenge now facing mankind. From considerations surrounding global warming and CO2 production, it has to be recognized that oil is a finite resource and the KSA like many other oil-rich countries will have to start to consider a horizon where hydro-carbons are not the dominant energy resource. The employment of hybrid ground-cooling pipes in combination with the black body solar collection and radiant night cooling systems may have the potential to displace a significant proportion of oil currently used to run conventional air conditioning plant. This paper presents an investigation into the viability of such hybrid systems with the specific aim of reducing cooling load and carbon emissions while providing all year-round thermal comfort in a typical Saudi Arabian urban housing block. Soil temperatures were measured in the city of Jeddah. A parametric study then was carried out by computational simulation software (DesignBuilder) that utilized the field measurements and predicted the cooling energy consumption of both a base case and an ideal scenario (typical block retro-fitted with insulation, solar shading, ground pipes integrated with hypocaust floor slabs/stack ventilation and radiant cooling pipes embed in floor). Initial simulation results suggest that careful ‘ecological design’ combined with hybrid radiant and ground pipe cooling techniques can displace air conditioning systems, producing significant cost and carbon savings (both capital and running) without appreciable deprivation of amenity.
Abstract: Worldwide, about two-thirds of industrial and domestic wastewater effluent is discharged without treatment, which can cause contamination and eutrophication of the water. In particular, for Mediterranean countries, irrigation with treated wastewater would mitigate the water stress and support the agricultural sector. Changing global weather patterns will make the situation worse, due to increased susceptibility to drought, which can cause major environmental, social, and economic problems. The study was carried out in open field in an intensive agricultural area of the Apulian region in Southern Italy where freshwater resources are often scarce. As well as providing a water resource, irrigation with treated wastewater represents a significant source of nutrients for soil–plant systems. However, the use of wastewater might have further effects on soil. This study thus investigated the long-term impact of irrigation with reclaimed agro-industrial wastewater on the chemical characteristics of the soil. Two crops (processing tomato and broccoli) were cultivated in succession in Stornarella (Foggia) over four years from 2012 to 2016 using two types of irrigation water: groundwater and tertiary treated agro-industrial wastewater that had undergone an activated sludge process, sedimentation filtration, and UV radiation. Chemical analyses were performed on the irrigation waters and soil samples. The treated wastewater was characterised by high levels of several chemical parameters including TSS, EC, COD, BOD5, Na+, Ca2+, Mg2+, NH4-N, PO4-P, K+, SAR and CaCO3, as compared with the groundwater. However, despite these higher levels, the mean content of several chemical parameters in the soil did not show relevant differences between the irrigation treatments, in terms of the chemical features of the soil.
Abstract: Introduction: The process to build a better safety
culture, methods of error analysis, and preventive measures, starts
with an understanding of the effects when human factors engineering
refer to remote microscopic diagnosis in surgery and specially in
organ transplantation for the remote evaluation of the grafts. It has
been estimated that even in well-organized transplant systems an
average of 8% to 14% of the grafts (G) that arrive at the recipient
hospitals may be considered as diseased, injured, damaged or
improper for transplantation. Digital microscopy adds information on
a microscopic level about the grafts in Organ Transplant (OT), and
may lead to a change in their management. Such a method will
reduce the possibility that a diseased G, will arrive at the recipient
hospital for implantation. Aim: Ergonomics of Digital Microscopy
(DM) based on virtual slides, on Telemedicine Systems (TS) for
Tele-Pathological (TPE) evaluation of the grafts (G) in organ
transplantation (OT). Material and Methods: By experimental
simulation, the ergonomics of DM for microscopic TPE of Renal
Graft (RG), Liver Graft (LG) and Pancreatic Graft (PG) tissues is
analyzed. In fact, this corresponded to the ergonomics of digital
microscopy for TPE in OT by applying Virtual Slide (VS) system for
graft tissue image capture, for remote diagnoses of possible
microscopic inflammatory and/or neoplastic lesions. Experimentation
included: a. Development of an OTE-TS similar Experimental
Telemedicine System (Exp.-TS), b. Simulation of the integration of
TS with the VS based microscopic TPE of RG, LG and PG applying
DM. Simulation of the DM based TPE was performed by 2
specialists on a total of 238 human Renal Graft (RG), 172 Liver Graft
(LG) and 108 Pancreatic Graft (PG) tissues digital microscopic
images for inflammatory and neoplastic lesions on four electronic
spaces of the four used TS. Results: Statistical analysis of specialist‘s
answers about the ability to diagnose accurately the diseased RG, LG
and PG tissues on the electronic space among four TS (A,B,C,D)
showed that DM on TS for TPE in OT is elaborated perfectly on the
ES of a Desktop, followed by the ES of the applied Exp.-TS. Tablet
and Mobile-Phone ES seem significantly risky for the application of
DM in OT (p
Abstract: Voting algorithms are extensively used to make
decisions in fault tolerant systems where each redundant module
gives inconsistent outputs. Popular voting algorithms include
majority voting, weighted voting, and inexact majority voters. Each
of these techniques suffers from scenarios where agreements do not
exist for the given voter inputs. This has been successfully overcome
in literature using fuzzy theory. Our previous work concentrated on a
neuro-fuzzy algorithm where training using the neuro system
substantially improved the prediction result of the voting system.
Weight training of Neural Network is sub-optimal. This study
proposes to optimize the weights of the Neural Network using
Artificial Bee Colony algorithm. Experimental results show the
proposed system improves the decision making of the voting
algorithms.
Abstract: The main aim of the presented experiments is to
improve behaviour of sandwich structures under dynamic loading,
such as crash or explosion. This paper describes experimental
investigation on the response of new advanced materials to low and
high velocity load. Blast wave energy absorbers were designed using
two types of porous lightweight raw particle materials based on
expanded glass and ceramics with dimensions of 0.5-1 mm,
combined with polymeric binder. The effect of binder amount on the
static and dynamic properties of designed materials was observed.
Prism shaped specimens were prepared and loaded to obtain physicomechanical
parameters – bulk density, compressive and flexural
strength under quasistatic load, the dynamic response was determined
using Split Hopkinson Pressure bar apparatus. Numerical
investigation of the material behaviour in sandwich structure was
performed using implicit/explicit solver LS-Dyna. As the last step,
the developed material was used as the interlayer of blast resistant
litter bin, and it´s functionality was verified by real field blast tests.
Abstract: The building sector is responsible, in many
industrialized countries, for about 40% of the total energy
requirements, so it seems necessary to devote some efforts in this
area in order to achieve a significant reduction of energy
consumption and of greenhouse gases emissions.
The paper presents a study aiming at providing a design
methodology able to identify the best configuration of the system
building/plant, from a technical, economic and environmentally point
of view.
Normally, the classical approach involves a building's energy
loads analysis under steady state conditions, and subsequent selection
of measures aimed at improving the energy performance, based on
previous experience made by architects and engineers in the design
team. Instead, the proposed approach uses a sequence of two wellknown
scientifically validated calculation methods (TRNSYS and
RETScreen), that allow quite a detailed feasibility analysis.
To assess the validity of the calculation model, an existing,
historical building in Central Italy, that will be the object of
restoration and preservative redevelopment, was selected as a casestudy.
The building is made of a basement and three floors, with a
total floor area of about 3,000 square meters.
The first step has been the determination of the heating and
cooling energy loads of the building in a dynamic regime by means,
which allows simulating the real energy needs of the building in
function of its use. Traditional methodologies, based as they are on
steady-state conditions, cannot faithfully reproduce the effects of
varying climatic conditions and of inertial properties of the structure.
With this model is possible to obtain quite accurate and reliable
results that allow identifying effective combinations building-HVAC
system.
The second step has consisted of using output data obtained as
input to the calculation model, which enables to compare different
system configurations from the energy, environmental and financial
point of view, with an analysis of investment, and operation and
maintenance costs, so allowing determining the economic benefit of
possible interventions.
The classical methodology often leads to the choice of
conventional plant systems, while our calculation model provides a
financial-economic assessment for innovative energy systems and
low environmental impact.
Computational analysis can help in the design phase, particularly
in the case of complex structures with centralized plant systems, by
comparing the data returned by the calculation model for different
design options.
Abstract: In this paper, an analysis of some model order
reduction techniques is presented. A new hybrid algorithm for model
order reduction of linear time invariant systems is compared with the
conventional techniques namely Balanced Truncation, Hankel Norm
reduction and Dominant Pole Algorithm (DPA). The proposed hybrid
algorithm is known as Clustering Dominant Pole Algorithm (CDPA),
is able to compute the full set of dominant poles and its cluster center
efficiently. The dominant poles of a transfer function are specific
eigenvalues of the state space matrix of the corresponding dynamical
system. The effectiveness of this novel technique is shown through
the simulation results.
Abstract: The author presented a method for model order reduction of large-scale time-invariant systems in time domain. In this approach, two modified Hankel matrices are suggested for getting reduced order models. The proposed method is simple, efficient and retains stability feature of the original high order system. The viability of the method is illustrated through the examples taken from literature.
Abstract: In today's world, success of most systems depend on the use of new technologies and information technology (IT) which aimed to increase efficiency and satisfaction of users. One of the most important systems that use information technology to deliver services is the education system. But for educational services in the form of E-learning systems, hardware and software equipment should be containing high quality, which requires substantial investment. Because the vast majority of educational establishments can not invest in this area so the best way for them is reducing the costs and providing the E-learning services by using cloud computing. But according to the novelty of the cloud technology, it can create challenges and concerns that the most noted among them are security issues. Security concerns about cloud-based E-learning products are critical and security measures essential to protect valuable data of users from security vulnerabilities in products. Thus, the success of these products happened if customers meet security requirements then can overcome security threats. In this paper tried to explore cloud computing and its positive impact on E- learning and put main focus to identify security issues that related to cloud-based E-learning efforts which have been improve security and provide solutions in management challenges.
Abstract: This paper presents comparison among methods of
determination of the characteristic polynomial coefficients. First, the
resultant systems from the methods are compared based on frequency
criteria such as the closed loop bandwidth, gain and phase margins.
Then the step responses of the resultant systems are compared on the
basis of the transient behavior criteria including overshoot, rise time,
settling time and error (via IAE, ITAE, ISE and ITSE integral
indices). Also relative stability of the systems is compared together.
Finally the best choices in regards to the above diverse criteria are
presented.
Abstract: this paper presents an auto-regressive network called the Auto-Regressive Multi-Context Recurrent Neural Network (ARMCRN), which forecasts the daily peak load for two large power plant systems. The auto-regressive network is a combination of both recurrent and non-recurrent networks. Weather component variables are the key elements in forecasting because any change in these variables affects the demand of energy load. So the AR-MCRN is used to learn the relationship between past, previous, and future exogenous and endogenous variables. Experimental results show that using the change in weather components and the change that occurred in past load as inputs to the AR-MCRN, rather than the basic weather parameters and past load itself as inputs to the same network, produce higher accuracy of predicted load. Experimental results also show that using exogenous and endogenous variables as inputs is better than using only the exogenous variables as inputs to the network.
Abstract: Order reduction of linear-time invariant systems employing two methods; one using the advantages of Routh approximation and other by an evolutionary technique is presented in this paper. In Routh approximation method the denominator of the reduced order model is obtained using Routh approximation while the numerator of the reduced order model is determined using the indirect approach of retaining the time moments and/or Markov parameters of original system. By this method the reduced order model guarantees stability if the original high order model is stable. In the second method Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical examples.
Abstract: The Ant Colony Optimization (ACO) is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It has recently attracted a lot of attention and has been successfully applied to a number of different optimization problems. Due to the importance of the feature selection problem and the potential of ACO, this paper presents a novel method that utilizes the ACO algorithm to implement a feature subset search procedure. Initial results obtained using the classification of speech segments are very promising.
Abstract: The authors present an optimization algorithm for order reduction and its application for the determination of the relative mapping errors of linear time invariant dynamic systems by the simplified models. These relative mapping errors are expressed by means of the relative integral square error criterion, which are determined for both unit step and impulse inputs. The reduction algorithm is based on minimization of the integral square error by particle swarm optimization technique pertaining to a unit step input. The algorithm is simple and computer oriented. It is shown that the algorithm has several advantages, e.g. the reduced order models retain the steady-state value and stability of the original system. Two numerical examples are solved to illustrate the superiority of the algorithm over some existing methods.
Abstract: Feature selection is an important step in many pattern
classification problems. It is applied to select a subset of features,
from a much larger set, such that the selected subset is sufficient to
perform the classification task. Due to its importance, the problem of
feature selection has been investigated by many researchers. In this
paper, a novel feature subset search procedure that utilizes the Ant
Colony Optimization (ACO) is presented. The ACO is a
metaheuristic inspired by the behavior of real ants in their search for
the shortest paths to food sources. It looks for optimal solutions by
considering both local heuristics and previous knowledge. When
applied to two different classification problems, the proposed
algorithm achieved very promising results.
Abstract: Legionella pneumophila is involved in more than 95%
cases of severe atypical pneumonia. Infection is mainly by
inhalation the indoor aerosols through the water-coolant systems.
Because some Legionella strains may be viable but not culturable,
therefore, Taq polymerase, DNA amplification and semi-nested-PCR
were carried out to detect Legionella-specific 16S-rDNA sequence.
For this purpose, 1.5 litter of water samples from 77 water-coolant
system were collected from four different hospitals, two nursing
homes and one student hostel in Kerman city of Iran, each in a brand
new plastic bottle during summer season of 2006 (from April to
August). The samples were filtered in the sterile condition through
the Millipore Membrane Filter. DNA was extracted from membrane
and used for PCR to detect Legionella spp. The PCR product was
then subjected to semi-nested PCR for detection of L. pneumophila.
Out of 77 water samples that were tested by PCR, 30 (39%) were
positive for most species of Legionella. However, L. pneumophila
was detected from 14 (18.2%) water samples by semi-nested PCR.
From the above results it can be concluded that water coolant
systems of different hospitals and nursing homes in Kerman city of
Iran are highly contaminated with L. pneumophila spp. and pose
serious concern. So, we recommend avoiding such type of coolant
system in the hospitals and nursing homes.
Abstract: Herein, we report the different types of surface morphology due to the interaction between the pure protein Insulin (INS) and catanionic surfactant mixture of Sodium Dodecyl Sulfate (SDS) and Cetyl Trimethyl Ammonium Bromide (CTAB) at air/water interface obtained by the Langmuir-Blodgett (LB) technique. We characterized the aggregations by Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM) and Fourier transform infrared spectroscopy (FTIR) in LB films. We found that the INS adsorption increased in presence of catanionic surfactant at air/water interface. The presence of small amount of surfactant induces two-stage growth kinetics due to the pure protein absorption and protein-catanionic surface micelle interaction. The protein remains in native state in presence of small amount of surfactant mixture. Smaller amount of surfactant mixture with INS is producing surface micelle type structure. This may be considered for drug delivery system. On the other hand, INS becomes unfolded and fibrillated in presence of higher amount of surfactant mixture. In both the cases, the protein was successfully immobilized on a glass substrate by the LB technique. These results may find applications in the fundamental science of the physical chemistry of surfactant systems, as well as in the preparation of drug-delivery system.
Abstract: In this paper a unified approach via block-pulse functions (BPFs) or shifted Legendre polynomials (SLPs) is presented to solve the linear-quadratic-Gaussian (LQG) control problem. Also a recursive algorithm is proposed to solve the above problem via BPFs. By using the elegant operational properties of orthogonal functions (BPFs or SLPs) these computationally attractive algorithms are developed. To demonstrate the validity of the proposed approaches a numerical example is included.