Abstract: By using the two existing operators, we have defined an operator, which is an extension for them. In this paper, first the operator is introduced. Then, using this operator, the subclasses of multivalent functions are defined. These subclasses of multivalent functions are utilized in order to obtain coefficient inequalities, extreme points, and integral means inequalities for functions belonging to these classes.
Abstract: Since the mid-1970s, gated communities distributed in Latin America. They are a kind of residential development where there are privatized public spaces, and access to the area is restricted. They have specific impacts on the neighborhoods that located outside their walls such as threatening security, limiting access, and spreading social inequality. This research mainly focused on social features of gated community as; segregation, fragmentation, exclusion, specifically on sense of community and typology of gated communities. The conclusion will clarify the pros and cons of gated communities and how it could be successful or not.
Abstract: Main purpose of this study was to assess adoption level of farmers for quinoa cultivation after they had been taught through training and visit extension approach. At this time of the 21st century, population structure, climate change, food requirements and eating habits of people are changing rapidly. In this scenario, farmers must play their key role in sustainable crop development and production through adoption of new crops that may also be helpful to overcome the issue of food insecurity as well as reducing poverty in rural areas. Its cultivation in Pakistan is at the early stages and there is a need to raise awareness among farmers to grow quinoa crops. In the middle of the 2015, a training and visit extension approach was used to raise awareness and convince farmers to grow quinoa in the area. During training and visit extension program, 80 farmers were randomly selected for the training of quinoa cultivation. Later on, these farmers trained 60 more farmers living into their neighborhood. After six months, a survey was conducted with all 140 farmers to assess the impact of the training and visit program on adoption level of respondents for the quinoa crop. The survey instrument was developed with the help of literature review and other experts of the crop. Validity and reliability of the instrument were checked before complete data collection. The data were analyzed by using SPSS. Multiple regression analysis was used for interpretation of the results from the survey, which indicated that factors like information/ training, change in agronomic and plant protection practices play a key role in the adoption of quinoa cultivation by respondents. In addition, the model explains more than 50% of variation in the adoption level of respondents. It is concluded that farmers need timely information for improved knowledge of agronomic and plant protection practices to adopt cultivation of the quinoa crop in the area.
Abstract: This paper aims to present non-population search algorithms called tabu search (TS), simulated annealing (SA) and variable neighborhood search (VNS) to minimize the total cost of capacitated MRP problem in multi-stage assembly flow shop with two alternative machines. There are three main steps for the algorithm. Firstly, an initial sequence of orders is constructed by a simple due date-based dispatching rule. Secondly, the sequence of orders is repeatedly improved to reduce the total cost by applying TS, SA and VNS separately. Finally, the total cost is further reduced by optimizing the start time of each operation using the linear programming (LP) model. Parameters of the algorithm are tuned by using real data from automotive companies. The result shows that VNS significantly outperforms TS, SA and the existing algorithm.
Abstract: Conservation of historical urban patterns in the traditional neighborhoods is a part of creating integrated urban environments that are socially more sustainable. Urbanization reflects on life conditions and social, physical, economical characteristics of the society. In this regard, historical zones and traditional regions are affected by dramatic interventions on these characteristics. This article focuses on the Uch Dukkan neighborhood located in Ardabil City in Azarbaijani region of Iran, which has been up to such interventions that leaded its transformation from the past to the present. After introducing a brief inventory of the main elements of the historical zone and the neighborhood; this study explores the changes and transformations in different periods; and their impacts on the quality of the environment and its social sustainability. The survey conducted in the neighborhood as part of this research study revealed that the Uch Dukkan neighborhood and the unique architectural heritage that it possesses have become more inactive physically and functionally in a decade. This condition requires an exploration and comparison of the present and the expected transformations of the meaning of social space from the most private unit to the urban scale. From this token, it is argued that an architectural point of view that is based on space order; use and meaning of space as a social and cultural image, should not be ignored. Based on the interplay between social sustainability, collective memory, and the urban environment, study aims to make the invisible portion of ignorance clear, that ends up with a weakness in defining the collective meaning of the neighborhood as a historic urban district. It reveals that the spatial possessions of the neighborhood are valuable not only for their historical and physical characteristics, but also for their social memory that is to be remembered and constructed further.
Abstract: In order to meet the increasing demand for housing care for Kuwaiti citizens, the government authorities in Kuwait are undertaking a series of projects in the form of new large cities, outside the current urban area. Al Mutlaa City located to the north-west of the Kuwait Metropolitan Area is one such project out of the 15 planned new cities. The city accommodates a wide variety of residential developments, employment opportunities, commercial, recreational, health care and institutional uses. This paper examines the application of comprehensive transportation demand modeling works undertaken in VISUM platform to understand the future intracity and intercity travel distribution patterns in Kuwait. The scope of models developed varied in levels of detail: strategic model update, sub-area models representing future demand of Al Mutlaa City, sub-area models built to estimate the demand in the residential neighborhoods of the city. This paper aims at offering model update framework that facilitates easy integration between sub-area models and strategic national models for unified traffic forecasts. This paper presents the transportation demand modeling results utilized in informing the planning of multi-modal transportation system for Al Mutlaa City. This paper also presents the household survey data collection efforts undertaken using GPS devices (first time in Kuwait) and notebook computer based digital survey forms for interviewing representative sample of citizens and residents. The survey results formed the basis of estimating trip generation rates and trip distribution coefficients used in the strategic base year model calibration and validation process.
Abstract: Image segmentation is the concept of splitting the images into several images. Image Segmentation algorithm is used to manipulate the process of image segmentation. The advantage of ABC is that it conducts every worldwide exploration and inhabitant exploration for iteration. Particle Swarm Optimization (PSO) and Evolutionary Particle Swarm Optimization (EPSO) encompass a number of search problems. Cleverness Artificial Bee Colony algorithm has been imposed to increase the performance of a neighborhood search. The simulation results clearly show that the presented ABC methods outperform the existing methods. The result shows that the algorithms can be used to implement the manipulator for grasping of colored objects. The efficiency of the presented method is improved a lot by comparing to other methods.
Abstract: This paper focused on application support for technical control of artillery units – PVNPG-14M, especially on interpolation issue. Artillery units of the Army of the Czech Republic, reflecting the current global security neighborhood, can be used outside the Czech Republic. The paper presents principles, evolution and calculation in the process of complete preparation. The paper presents expertise using of application of current artillery communication and information system and suggests the perspective future system. The paper also presents problems in process of complete preparing of fire especially problems in permanently information (firing table) and calculated values. The paper presents problems of current artillery communication and information system and suggests requirements of the future system.
Abstract: This paper presents a four-dimensional computational
model, k-neighborhood template A-type three-dimensional bounded
cellular acceptor (abbreviated as A-3BCA(k)), and discusses the
hierarchical properties. An A-3BCA(k) is a four-dimensional
automaton which consists of a pair of a converter and a
configuration-reader. The former converts the given four-dimensional
tape to the three- and two- dimensional configuration and
the latter determines the acceptance or nonacceptance of given
four-dimensional tape whether or not the derived two-dimensional
configuration is accepted. We mainly investigate the difference of the
accepting power based on the difference of the configuration-reader.
It is shown that the difference of the accepting power of the
configuration-reader tends to affect directly that of the A-3BCA(k)
for the case when the converter is deterministic. On the other hand,
results are not analogous for the nondeterministic case.
Abstract: Medical digital images usually have low resolution because of nature of their acquisition. Therefore, this paper focuses on zooming these images to obtain better level of information, required for the purpose of medical diagnosis. For this purpose, a strategy for selecting pixels in zooming operation is proposed. It is based on the principle of analog clock and utilizes a combination of point and neighborhood image processing. In this approach, the hour hand of clock covers the portion of image to be processed. For alignment, the center of clock points at middle pixel of the selected portion of image. The minute hand is longer in length, and is used to gain information about pixels of the surrounding area. This area is called neighborhood pixels region. This information is used to zoom the selected portion of the image. The proposed algorithm is implemented and its performance is evaluated for many medical images obtained from various sources such as X-ray, Computerized Tomography (CT) scan and Magnetic Resonance Imaging (MRI). However, for illustration and simplicity, the results obtained from a CT scanned image of head is presented. The performance of algorithm is evaluated in comparison to various traditional algorithms in terms of Peak signal-to-noise ratio (PSNR), maximum error, SSIM index, mutual information and processing time. From the results, the proposed algorithm is found to give better performance than traditional algorithms.
Abstract: Climate change remains a challenging matter for the human and the built environment in the 21st century, where the need to consider adaptation to climate change in the development process is paramount. However, there remains a lack of information regarding how we should prepare responses to this issue, such as through developing organized and sophisticated tools enabling the adaptation process. This study aims to build a systematic framework approach to investigate the potentials that Neighborhood Sustainability Assessment tools (NSA) might offer in enabling both the analysis of the emerging adaptive capacity to climate change. The analysis of the framework presented in this paper aims to discuss this issue in three main phases. The first part attempts to link sustainability and climate change, in the context of adaptive capacity. It is argued that in deciding to promote sustainability in the context of climate change, both the resilience and vulnerability processes become central. However, there is still a gap in the current literature regarding how the sustainable development process can respond to climate change. As well as how the resilience of practical strategies might be evaluated. It is suggested that the integration of the sustainability assessment processes with both the resilience thinking process, and vulnerability might provide important components for addressing the adaptive capacity to climate change. A critical review of existing literature is presented illustrating the current lack of work in this field, integrating these three concepts in the context of addressing the adaptive capacity to climate change. The second part aims to identify the most appropriate scale at which to address the built environment for the climate change adaptation. It is suggested that the neighborhood scale can be considered as more suitable than either the building or urban scales. It then presents the example of NSAs, and discusses the need to explore their potential role in promoting the adaptive capacity to climate change. The third part of the framework presents a comparison among three example NSAs, BREEAM Communities, LEED-ND, and CASBEE-UD. These three tools have been selected as the most developed and comprehensive assessment tools that are currently available for the neighborhood scale. This study concludes that NSAs are likely to present the basis for an organized framework to address the practical process for analyzing and yet promoting Adaptive Capacity to Climate Change. It is further argued that vulnerability (exposure & sensitivity) and resilience (Interdependence & Recovery) form essential aspects to be addressed in the future assessment of NSA’s capability to adapt to both short and long term climate change impacts. Finally, it is acknowledged that further work is now required to understand impact assessment in terms of the range of physical sectors (Water, Energy, Transportation, Building, Land Use and Ecosystems), Actor and stakeholder engagement as well as a detailed evaluation of the NSA indicators, together with a barriers diagnosis process.
Abstract: In this paper, we present a pedestrian detection descriptor called Fused Structure and Texture (FST) features based on the combination of the local phase information with the texture features. Since the phase of the signal conveys more structural information than the magnitude, the phase congruency concept is used to capture the structural features. On the other hand, the Center-Symmetric Local Binary Pattern (CSLBP) approach is used to capture the texture information of the image. The dimension less quantity of the phase congruency and the robustness of the CSLBP operator on the flat images, as well as the blur and illumination changes, lead the proposed descriptor to be more robust and less sensitive to the light variations. The proposed descriptor can be formed by extracting the phase congruency and the CSLBP values of each pixel of the image with respect to its neighborhood. The histogram of the oriented phase and the histogram of the CSLBP values for the local regions in the image are computed and concatenated to construct the FST descriptor. Several experiments were conducted on INRIA and the low resolution DaimlerChrysler datasets to evaluate the detection performance of the pedestrian detection system that is based on the FST descriptor. A linear Support Vector Machine (SVM) is used to train the pedestrian classifier. These experiments showed that the proposed FST descriptor has better detection performance over a set of state of the art feature extraction methodologies.
Abstract: The purpose of this research is to study sport and
exercise behavior of students in Suan Sunandha Rajabhat University
in September of 2012. The sample group used in this research was a
group of regular students in undergraduate school enrolled in faculty
of science and technology. This sample group consisted of 1,858
students. The research tool used to collect result was the checklist.
The data was calculated by statistical percentage. From the research,
it was discovered that most students did exercise in previous month.
71.6% of students exercised by running. 61.1% of students exercised
in their neighborhood. 60.4% of students exercised in order to keep
fit. 60.2% of students agreed that the result from this research can be
educational and inspirational for students in campus in terms of living
healthily by exercise.
Abstract: Scripts are one of the basic text resources to understand
broadcasting contents. Topic modeling is the method to get the
summary of the broadcasting contents from its scripts. Generally,
scripts represent contents descriptively with directions and speeches,
and provide scene segments that can be seen as semantic units.
Therefore, a script can be topic modeled by treating a scene segment
as a document. Because scene segments consist of speeches mainly,
however, relatively small co-occurrences among words in the scene
segments are observed. This causes inevitably the bad quality of
topics by statistical learning method. To tackle this problem, we
propose a method to improve topic quality with additional word
co-occurrence information obtained using scene similarities. The
main idea of improving topic quality is that the information that
two or more texts are topically related can be useful to learn high
quality of topics. In addition, more accurate topical representations
lead to get information more accurate whether two texts are related
or not. In this paper, we regard two scene segments are related
if their topical similarity is high enough. We also consider that
words are co-occurred if they are in topically related scene segments
together. By iteratively inferring topics and determining semantically
neighborhood scene segments, we draw a topic space represents
broadcasting contents well. In the experiments, we showed the
proposed method generates a higher quality of topics from Korean
drama scripts than the baselines.
Abstract: This article presents the main results of a numerical
investigation on the uncertainty of dynamic response of structures
with statistically correlated random damping Gamma distributed. A
computational method based on a Linear Statistical Model (LSM) is
implemented to predict second order statistics for the response of a
typical industrial building structure. The significance of random
damping with correlated parameters and its implications on the
sensitivity of structural peak response in the neighborhood of a
resonant frequency are discussed in light of considerable ranges of
damping uncertainties and correlation coefficients. The results are
compared to those generated using Monte Carlo simulation
techniques. The numerical results obtained show the importance of
damping uncertainty and statistical correlation of damping
coefficients when obtaining accurate probabilistic estimates of
dynamic response of structures. Furthermore, the effectiveness of the
LSM model to efficiently predict uncertainty propagation for
structural dynamic problems with correlated damping parameters is
demonstrated.
Abstract: This paper addresses minimizing the makespan of the
distributed permutation flow shop scheduling problem. In this
problem, there are several parallel identical factories or flowshops
each with series of similar machines. Each job should be allocated to
one of the factories and all of the operations of the jobs should be
performed in the allocated factory. This problem has recently gained
attention and due to NP-Hard nature of the problem, metaheuristic
algorithms have been proposed to tackle it. Majority of the proposed
algorithms require large computational time which is the main
drawback. In this study, a general variable neighborhood search
algorithm (GVNS) is proposed where several time-saving schemes
have been incorporated into it. Also, the GVNS uses the sophisticated
method to change the shaking procedure or perturbation depending
on the progress of the incumbent solution to prevent stagnation of the
search. The performance of the proposed algorithm is compared to
the state-of-the-art algorithms based on standard benchmark
instances.
Abstract: Currently, green rating systems are mainly utilized for
correctly sizing mechanical and electrical systems, which have short
lifetime expectancies. In these systems, passive solar and bio-climatic
architecture, which have long lifetime expectancies, are neglected.
Urban rating systems consider buildings and services in addition to
neighborhoods and public transportation as integral parts of the built
environment. The main goal of this study was to develop a more
consistent point allocation system for urban building standards by
using six different lifetime shearing layers: Site, Structure, Skin,
Services, Space, and Stuff, each reflecting distinct environmental
damages. This shearing-layer concept was applied to internationally
well-known rating systems: Leadership in Energy and Environmental
Design (LEED) for Neighborhood Development, BRE
Environmental Assessment Method (BREEAM) for Communities
and Comprehensive Assessment System for Building Environmental
Efficiency (CASBEE) for Urban Development. The results showed
that LEED for Neighborhood Development and BREEAM for
Communities focused on long-lifetime-expectancy building designs,
whereas CASBEE for Urban Development gave equal importance to
the Building and Service Layers. Moreover, although this rating
system was applied using a building-scale assessment, “Urban Area +
Buildings” focuses on a short-lifetime-expectancy system design,
neglecting to improve the architectural design by considering bioclimatic
and passive solar aspects.
Abstract: The lifetime of a wireless sensor network can be
effectively increased by using scheduling operations. Once the
sensors are randomly deployed, the task at hand is to find the largest
number of disjoint sets of sensors such that every sensor set provides
complete coverage of the target area. At any instant, only one of these
disjoint sets is switched on, while all other are switched off. This
paper proposes a heuristic search method to find the maximum
number of disjoint sets that completely cover the region. A
population of randomly initialized members is made to explore the
solution space. A set of heuristics has been applied to guide the
members to a possible solution in their neighborhood. The heuristics
escalate the convergence of the algorithm. The best solution explored
by the population is recorded and is continuously updated. The
proposed algorithm has been tested for applications which require
sensing of multiple target points, referred to as point coverage
applications. Results show that the proposed algorithm outclasses the
existing algorithms. It always finds the optimum solution, and that
too by making fewer number of fitness function evaluations than the
existing approaches.
Abstract: Artificial neural networks have gained a lot of interest
as empirical models for their powerful representational capacity,
multi input and output mapping characteristics. In fact, most feedforward
networks with nonlinear nodal functions have been proved to
be universal approximates. In this paper, we propose a new
supervised method for color image classification based on selforganizing
feature maps (SOFM). This algorithm is based on
competitive learning. The method partitions the input space using
self-organizing feature maps to introduce the concept of local
neighborhoods. Our image classification system entered into RGB
image. Experiments with simulated data showed that separability of
classes increased when increasing training time. In additional, the
result shows proposed algorithms are effective for color image
classification.
Abstract: This work sets out to debate the tensions involved in
the processes of contamination and self-purification in the urban
space, particularly in the streams that run through the Buenos Aires
metropolitan area. For much of their course, those streams are piped;
their waters do not come into contact with the outdoors until they
have reached deeply impoverished urban areas with high levels of
environmental contamination. These are peripheral zones that, until
thirty years ago, were marshlands and fields. They are now densely
populated areas largely lacking in urban infrastructure.
The Cárcova neighborhood, where this project is underway, is in
the José León Suárez section of General San Martín county, Buenos
Aires province. A stretch of José León Suarez canal crosses the
neighborhood. Starting upstream, this canal carries pollutants due to
the sewage and industrial waste released into it. Further downstream,
in the neighborhood, domestic drainage is poured into the stream. In
this paper, we formulate a hypothesis diametrical to the one that
holds that these neighborhoods are the primary source of
contamination, suggesting instead that in the stretch of the canal that
runs through the neighborhood the stream’s waters are actually
cleaned and the sediments accumulate pollutants. Indeed, the
stretches of water that runs through these neighborhoods act as water
processing plants for the metropolis.
This project has studied the different organic-load polluting
contributions to the water in a certain stretch of the canal, the
reduction of that load over the course of the canal, and the
incorporation of pollutants into the sediments. We have found that
the surface water has considerable ability to self-purify, mostly due to
processes of sedimentation and adsorption. The polluting load is
accumulated in the sediments where that load stabilizes slowly by
means of anaerobic processes. In this study, we also investigated the
risks of sediment management and the use of the processes studied
here in controlled conditions as tools of environmental restoration.