Abstract: Breadth-First Search (BFS) is a core graph algorithm that is widely used for graph analysis. As it is frequently used in many graph applications, improving the BFS performance is essential. In this paper, we present a graph ordering method that could reorder the graph nodes to achieve better data locality, thus, improving the BFS performance. Our method is based on an observation that the sibling relationships will dominate the cache access pattern during the BFS traversal. Therefore, we propose a frequency-based model to construct the graph order. First, we optimize the graph order according to the nodes’ visit frequency. Nodes with high visit frequency will be processed in priority. Second, we try to maximize the child nodes’ overlap layer by layer. As it is proved to be NP-hard, we propose a heuristic method that could greatly reduce the preprocessing overheads.We conduct extensive experiments on 16 real-world datasets. The result shows that our method could achieve comparable performance with the state-of-the-art methods while the graph ordering overheads are only about 1/15.
Abstract: Innovation is the key element of economic development and a key factor in social processes. Technical innovations can be identified as prerequisites and causes of social change and cannot be created without the renewal of society. The study of social innovation can be characterised as one of the significant research areas of our day. The study’s aim is to identify the process of social innovation, which can be defined by input, transformation, and output factors. This approach divides the social innovation process into three parts: situation analysis, implementation, follow-up. The methods associated with each stage of the process are illustrated by the chronological line of social innovation. In this study, we have sought to present methodologies that support long- and short-term decision-making that is easy to apply, have different complementary content, and are well visualised for different user groups. When applying the methods, the reference objects are different: county, district, settlement, specific organisation. The solution proposed by the study supports the development of a methodological combination adapted to different situations. Having reviewed metric and conceptualisation issues, we wanted to develop a methodological combination along with a change management logic suitable for structured support to the generation of social innovation in the case of a locality or a specific organisation. In addition to a theoretical summary, in the second part of the study, we want to give a non-exhaustive picture of the two counties located in the north-eastern part of Hungary through specific analyses and case descriptions.
Abstract: Dimensionality reduction and feature extraction are of
crucial importance for achieving high efficiency in manipulating
the high dimensional data. Two-dimensional discriminant locality
preserving projection (2D-DLPP) and two-dimensional discriminant
supervised LPP (2D-DSLPP) are two effective two-dimensional
projection methods for dimensionality reduction and feature
extraction of face image matrices. Since 2D-DLPP and 2D-DSLPP
preserve the local structure information of the original data and
exploit the discriminant information, they usually have good
recognition performance. However, 2D-DLPP and 2D-DSLPP
only employ single-sided projection, and thus the generated low
dimensional data matrices have still many features. In this paper,
by combining the discriminant supervised LPP with the bidirectional
projection, we propose the bidirectional discriminant supervised LPP
(BDSLPP). The left and right projection matrices for BDSLPP can
be computed iteratively. Experimental results show that the proposed
BDSLPP achieves higher recognition accuracy than 2D-DLPP,
2D-DSLPP, and bidirectional discriminant LPP (BDLPP).
Abstract: Hong Hoi Formation is a Middle Triassic deep marine succession presented in outcrops throughout the Lampang Basin of northern Thailand. The primary goal of this research is to diagnose the paleoenvironment, petrographic compositions, and sedimentary sources of the Hong Hoi Formation in Ban Huat, Ngao District. The Triassic Hong Hoi Formation is chosen because the outcrops are continuous and fossils are greatly exposed and abundant. Depositional environment is reconstructed through sedimentological studies along with facies analysis. The Hong Hoi Formation is petrographically divided into two major facies, they are: sandstones with mudstone interbeds, and mudstones or shale with sandstone interbeds. Sandstone beds are lithic arenite and lithic greywacke, volcanic lithic fragments are dominated. Sedimentary structures, paleocurrent data and lithofacies arrangement indicate that the formation deposited in a part of deep marine abyssal plain environment. The sedimentological and petrographic features suggest that during the deposition the Hong Hoi Formation received sediment supply from nearby volcanic arc. This suggested that the intensive volcanic activity within the Sukhothai Arc during the Middle Triassic is the main sediment source.
Abstract: Installation of micro-generators based on renewable energy in power distribution system has increased in recent years, with the main renewable sources being solar and wind. Due to the intermittent nature of renewable energy sources, such micro-generators produce time-varying energy which does not correspond at certain times of the day to the peak energy consumption of end users. For this reason, the use of energy storage units next to the grid contributes to the proper leveling of the buses’ voltage level according to Brazilian energy quality standards. In this work, the effect of the addition of a photovoltaic solar generator and a store of energy in the busbar voltages of an electric system is analyzed. The consumption profile is defined as the average hourly use of appliances in a common residence, and the generation profile is defined as a function of the solar irradiation available in a locality. The power summation method is validated with analytical calculation and is used to calculate the modules and angles of the voltages in the buses of an electrical system based on the IEEE standard, at each hour of the day and with defined load and generation profiles. The results show that bus 5 presents the worst voltage level at the power consumption peaks and stabilizes at the appropriate range with the inclusion of the energy storage during the night time period. Solar generator maintains improvement of the voltage level during the period when it receives solar irradiation, having peaks of production during the 12 pm (without exceeding the appropriate maximum levels of tension).
Abstract: Natural radiations such as ultraviolet (UV) radiation sourced from sun are known to be the main causes of skin cancer, sunburn, eye damage, premature aging of skin and other skin related diseases. Its percentage of radiation reaching the earth populace and its impacts are not well known. Its variability in near-surface relating to its impacts on populace depends on some atmospheric parameters. Hence, this work was embarked on to determine the variability in near-surface UV radiation and its dependency on some atmospheric parameters at different time of the day in Offa, Nigeria. The variability was determined using the data obtained from meteorological garden, Science Laboratory Technology Department, Federal Polytechnic Offa, Nigeria. The data obtained were solar UV radiation, solar radiation, temperature, humidity and pressure at 30 minutes interval. Relationships were determined and correlations were derived using SPSS Pearson Correlation tool. The results showed a significant level of correlation with p-value of 0.01 and 0.05 levels. Thus, the results revealed some good relationships between the solar UV radiation and other atmospheric parameters with significance level less than p-value obtained. Inferentially, interdependent relationships were found to exist. Therefore, the nature of relationship obtained could be a yardstick for decision making in short term environmental planning on solar UV radiation depending of some atmospheric parameters within Offa locality.
Abstract: As world wild internet has non-stop developments, making profit by lending registered domain names emerges as a new business in recent years. Unfortunately, the larger the market scale of domain lending service becomes, the riskier that there exist malicious behaviors or malwares hiding behind parked domains will be. Also, previous work for differentiating parked domain suffers two main defects: 1) too much data-collecting effort and CPU latency needed for features engineering and 2) ineffectiveness when detecting parked domains containing external links that are usually abused by hackers, e.g., drive-by download attack. Aiming for alleviating above defects without sacrificing practical usability, this paper proposes ParkedGuard as an efficient and accurate parked domain detector. Several scripting behavioral features were analyzed, while those with special statistical significance are adopted in ParkedGuard to make feature engineering much more cost-efficient. On the other hand, finding memberships between external links and parked domains was modeled as a graph mining problem, and a coarse-to-fine strategy was elaborately designed by leverage the graphical locality such that ParkedGuard outperforms the state-of-the-art in terms of both recall and precision rates.
Abstract: With the development of HyperSpectral Imagery
(HSI) technology, the spectral resolution of HSI became denser,
which resulted in large number of spectral bands, high correlation
between neighboring, and high data redundancy. However, the
semantic interpretation is a challenging task for HSI analysis
due to the high dimensionality and the high correlation of the
different spectral bands. In fact, this work presents a dimensionality
reduction approach that allows to overcome the different issues
improving the semantic interpretation of HSI. Therefore, in order
to preserve the spatial information, the Tensor Locality Preserving
Projection (TLPP) has been applied to transform the original HSI.
In the second step, knowledge has been extracted based on the
adjacency graph to describe the different pixels. Based on the
transformation matrix using TLPP, a weighted matrix has been
constructed to rank the different spectral bands based on their
contribution score. Thus, the relevant bands have been adaptively
selected based on the weighted matrix. The performance of the
presented approach has been validated by implementing several
experiments, and the obtained results demonstrate the efficiency
of this approach compared to various existing dimensionality
reduction techniques. Also, according to the experimental results,
we can conclude that this approach can adaptively select the
relevant spectral improving the semantic interpretation of HSI.
Abstract: Hole Vacuum theory is based on discontinuous spacetime that contains vacuum holes. Vacuum holes can explain gravitation, some laws of quantum mechanics and allow teleportation of matter. All massive bodies emit a flux of holes which curve the spacetime; if we increase the concentration of holes, it leads to length contraction and time dilation because the holes do not have the properties of extension and duration. In the limited case when space consists of holes only, the distance between every two points is equal to zero and time stops - outside of the Universe, the extension and duration properties do not exist. For this reason, the vacuum hole is the only particle in physics capable of describing gravitation using its own properties only. All microscopic particles must 'jump' continually and 'vibrate' due to the appearance of holes (impassable microscopic 'walls' in space), and it is the cause of the quantum behavior. Vacuum holes can explain the entanglement, non-locality, wave properties of matter, tunneling, uncertainty principle and so on. Particles do not have trajectories because spacetime is discontinuous and has impassable microscopic 'walls' due to the simple mechanical motion is impossible at small scale distances; it is impossible to 'trace' a straight line in the discontinuous spacetime because it contains the impassable holes. Spacetime 'boils' continually due to the appearance of the vacuum holes. For teleportation to be possible, we must send a body outside of the Universe by enveloping it with a closed surface consisting of vacuum holes. Since a material body cannot exist outside of the Universe, it reappears instantaneously in a random point of the Universe. Since a body disappears in one volume and reappears in another random volume without traversing the physical space between them, such a transportation method can be called teleportation (or Hole Teleportation). It is shown that Hole Teleportation does not violate causality and special relativity due to its random nature and other properties. Although Hole Teleportation has a random nature, it can be used for colonization of extrasolar planets by the help of the method called 'random jumps': after a large number of random teleportation jumps, there is a probability that the spaceship may appear near a habitable planet. We can create vacuum holes experimentally using the method proposed by Descartes: we must remove a body from the vessel without permitting another body to occupy this volume.
Abstract: In wireless sensor networks, locality and positioning information can be captured using Global Positioning System (GPS). This message can be congregated initially from spot to identify the system. Users can retrieve information of interest from a wireless sensor network (WSN) by injecting queries and gathering results from the mobile sink nodes. Routing is the progression of choosing optimal path in a mobile network. Intermediate node employs permutation of device nodes into teams and generating cluster heads that gather the data from entity cluster’s node and encourage the collective data to base station. WSNs are widely used for gathering data. Since sensors are power-constrained devices, it is quite vital for them to reduce the power utilization. A tree-based data fusion clustering routing algorithm (TBDFC) is used to reduce energy consumption in wireless device networks. Here, the nodes in a tree use the cluster formation, whereas the elevation of the tree is decided based on the distance of the member nodes to the cluster-head. Network simulation shows that this scheme improves the power utilization by the nodes, and thus considerably improves the lifetime.
Abstract: Treating data based on its location in memory has received much attention in recent years due to its different properties, which offer important aspects for cache utilization. Stack data and non-stack data may interfere with each other’s locality in the data cache. One of the important aspects of stack data is that it has high spatial and temporal locality. In this work, we simulate non-unified cache design that split data cache into stack and non-stack caches in order to maintain stack data and non-stack data separate in different caches. We observe that the overall hit rate of non-unified cache design is sensitive to the size of non-stack cache. Then, we investigate the appropriate size and associativity for stack cache to achieve high hit ratio especially when over 99% of accesses are directed to stack cache. The result shows that on average more than 99% of stack cache accuracy is achieved by using 2KB of capacity and 1-way associativity. Further, we analyze the improvement in hit rate when adding small, fixed, size of stack cache at level1 to unified cache architecture. The result shows that the overall hit rate of unified cache design with adding 1KB of stack cache is improved by approximately, on average, 3.9% for Rijndael benchmark. The stack cache is simulated by using SimpleScalar toolset.
Abstract: Large scale computing infrastructures have been widely
developed with the core objective of providing a suitable platform
for high-performance and high-throughput computing. These systems
are designed to support resource-intensive and complex applications,
which can be found in many scientific and industrial areas. Currently,
large scale data-intensive applications are hindered by the high
latencies that result from the access to vastly distributed data.
Recent works have suggested that improving data locality is key to
move towards exascale infrastructures efficiently, as solutions to this
problem aim to reduce the bandwidth consumed in data transfers, and
the overheads that arise from them. There are several techniques that
attempt to move computations closer to the data. In this survey we
analyse the different mechanisms that have been proposed to provide
data locality for large scale high-performance and high-throughput
systems. This survey intends to assist scientific computing community
in understanding the various technical aspects and strategies that
have been reported in recent literature regarding data locality. As a
result, we present an overview of locality-oriented techniques, which
are grouped in four main categories: application development, task
scheduling, in-memory computing and storage platforms. Finally, the
authors include a discussion on future research lines and synergies
among the former techniques.
Abstract: This paper looks at healing performances as
ethnographic expressions of local knowledge and culture embedded
within the Malay psyche and gemeinschaft. As society develops and
progresses, these healing performances are caught within conflicting
trajectories which become compounded by the contestations of
tradition, religious concerns, locality and modernity. As
exemplifications of the Malay ethos, these performances practice
common rituals, cater to the innate needs of the practitioners and
serve the targeted, closed, local community. This paper traces the
ethnographic methods in documenting these practices as rituals of
healing in a post-modern world. It delineates the ethnographic
concepts used to analyze these rituals, and to semiotically read the
varied binarial oppositions and juxtapositions. The paper concludes
by highlighting the reconciliatory processes involved in maintaining
these ritual performances as exemplifications of the Malay ethos
playing an important role in the re-aligning, re-balancing and healing
of the Malay community’s psyche.
Abstract: Myoelectric control system is the fundamental
component of modern prostheses, which uses the myoelectric signals
from an individual’s muscles to control the prosthesis movements.
The surface electromyogram signal (sEMG) being noninvasive has
been used as an input to prostheses controllers for many years.
Recent technological advances has led to the development of
implantable myoelectric sensors which enable the internal
myoelectric signal (MES) to be used as input to these prostheses
controllers. The intramuscular measurement can provide focal
recordings from deep muscles of the forearm and independent signals
relatively free of crosstalk thus allowing for more independent
control sites. However, little work has been done to compare the two
inputs. In this paper we have compared the classification accuracy of
six pattern recognition based myoelectric controllers which use
surface myoelectric signals recorded using untargeted (symmetric)
surface electrode arrays to the same controllers with multichannel
intramuscular myolectric signals from targeted intramuscular
electrodes as inputs. There was no significant enhancement in the
classification accuracy as a result of using the intramuscular EMG
measurement technique when compared to the results acquired using
the surface EMG measurement technique. Impressive classification
accuracy (99%) could be achieved by optimally selecting only five
channels of surface EMG.
Abstract: Recent research in neural networks science and
neuroscience for modeling complex time series data and statistical
learning has focused mostly on learning from high input space and
signals. Local linear models are a strong choice for modeling local
nonlinearity in data series. Locally weighted projection regression is
a flexible and powerful algorithm for nonlinear approximation in
high dimensional signal spaces. In this paper, different learning
scenario of one and two dimensional data series with different
distributions are investigated for simulation and further noise is
inputted to data distribution for making different disordered
distribution in time series data and for evaluation of algorithm in
locality prediction of nonlinearity. Then, the performance of this
algorithm is simulated and also when the distribution of data is high
or when the number of data is less the sensitivity of this approach to
data distribution and influence of important parameter of local
validity in this algorithm with different data distribution is explained.
Abstract: The lactic acid bacteria (LAB) were isolated from
10 samples of fermented foods (Sa-tor-dong and Bodo) in South
locality of Thailand. The 23 isolates of lactic acid bacteria were
selected, which were exhibited a clear zone and growth on MRS
agar supplemented with CaCO3. All of lactic acid bacteria were
tested on morphological and biochemical. The result showed that
all isolates were Gram’s positive, non-spore forming but only
10 isolates displayed catalase negative. The 10 isolates including
BD1 .1, BD 1.2, BD 2.1, BD2.2, BD 2.3, BD 3.1, BD 4.1, BD 5.2,
ST 4.1 and ST 5.2 were selected for inhibition activity
determination. Only 2 strains (ST 4.1 and BD 2.3) showed
inhibition zone on agar, when using Escherichia coli sp. as target
strain. The ST 4.1 showed highest inhibition zone on agar, which
was selected for probiotic property testing. The ST4.1 isolate
could grow in MRS broth containing a high concentration of
sodium chloride 6%, bile salts 7%, pH 4-10 and vary temperature
at 15-45°C.
Abstract: The Salman Farsi dam project is constructed on the Ghareh Agahaj River about 140km south of Shiraz city in the Zagros Mountains of southwestern Iran. This tectonic province of south-western Iran is characterized by a simple folded sedimentary sequence. The dam foundation rocks compose of the Asmari Formation of Oligo-miocene and generally comprise of a variety of karstified carbonate rocks varying from strong to weak rocks. Most of the rocks exposed at the dam site show a primary porosity due to incomplete diagenetic recrystallization and compaction. In addition to these primary dispositions to weathering, layering conditions (frequency and orientation of bedding) and the subvertical tectonic discontinuities channeled preferably the infiltrating by deep-sited hydrothermal solutions. Consequently the porosity results to be enlarged by dissolution and the rocks are expected to be karstified and to develop cavities in correspondence of bedding, major joint planes and fault zones. This kind of karsts is named hypogenic karsts which associated to the ascendant warm solutions. Field observations indicate strong karstification and vuggy intercalations especially in the middle part of the Asmari succession. The biggest karst in the dam axis which identified by speleological investigations is Golshany Cave with volume of about 150,000 m3. The tendency of the Asmari limestone for strong dissolution can alert about the seepage from the reservoir and area of the dam locality.
Abstract: Nowadays, the mathematical/statistical applications
are developed with more complexity and accuracy. However, these
precisions and complexities have brought as result that applications
need more computational power in order to be executed faster. In this
sense, the multicore environments are playing an important role to
improve and to optimize the execution time of these applications.
These environments allow us the inclusion of more parallelism inside
the node. However, to take advantage of this parallelism is not an
easy task, because we have to deal with some problems such as: cores
communications, data locality, memory sizes (cache and RAM),
synchronizations, data dependencies on the model, etc. These issues
are becoming more important when we wish to improve the
application’s performance and scalability. Hence, this paper describes
an optimization method developed for Systemic Model of Banking
Originated Losses (SYMBOL) tool developed by the European
Commission, which is based on analyzing the application's weakness
in order to exploit the advantages of the multicore. All these
improvements are done in an automatic and transparent manner with
the aim of improving the performance metrics of our tool. Finally,
experimental evaluations show the effectiveness of our new
optimized version, in which we have achieved a considerable
improvement on the execution time. The time has been reduced
around 96% for the best case tested, between the original serial
version and the automatic parallel version.
Abstract: Uniqueness and distinctiveness of localities (referred to as genius loci or sense of place) are important to ensure people-s identification with their locality. Existing frameworks reveals that the affective dimension of environments is rarely mentioned or explored and limited public participation was used in constructing the frameworks. This research argues that the complexity of sense of place would be recognised and appropriate planning guidelines formulated by exploring and integrating the affective dimension of a site. Aims of the research therefore are to (i) explore relational dimensions between people and a natural rural landscape, (ii) to implement a participatory approach to obtain insight into different relational dimensions, and (ii) to concretise socio-affective relational dimensions into site planning guidelines. A qualitative, interdisciplinary research approach was followed and conducted on the farm Kromdraai, Vredefort Dome World Heritage Site. In essence the first phase of the study reveals various affective responses and projections of personal meanings. The findings in phase 1 informed the second phase, to involve people from various disciplines and different involvement with the area to make visual presentations of appropriate planning and design of the site in order to capture meanings of the interactions between people and their environment. Final site planning and design guidelines were formulated, based on these. This research contributed to provide planners with new possibilities of exploring the dimensions between people and places as well as to develop appropriate methods for participation to obtain insight into the underlying meanings of sites.
Abstract: The African Great Lakes Region refers to the zone
around lakes Victoria, Tanganyika, Albert, Edward, Kivu, and
Malawi. The main source of electricity in this region is hydropower
whose systems are generally characterized by relatively weak,
isolated power schemes, poor maintenance and technical deficiencies
with limited electricity infrastructures. Most of the hydro sources are
rain fed, and as such there is normally a deficiency of water during
the dry seasons and extended droughts. In such calamities fossil fuels
sources, in particular petroleum products and natural gas, are
normally used to rescue the situation but apart from them being nonrenewable,
they also release huge amount of green house gases to our
environment which in turn accelerates the global warming that has at
present reached an amazing stage. Wind power is ample, renewable,
widely distributed, clean, and free energy source that does not
consume or pollute water. Wind generated electricity is one of the
most practical and commercially viable option for grid quality and
utility scale electricity production. However, the main shortcoming
associated with electric wind power generation is fluctuation in its
output both in space and time. Before making a decision to establish
a wind park at a site, the wind speed features there should therefore
be known thoroughly as well as local demand or transmission
capacity. The main objective of this paper is to utilise monthly
average wind speed data collected from one prospective site within
the African Great Lakes Region to demonstrate that the available
wind power there is high enough to generate electricity. The mean
monthly values were calculated from records gathered on hourly
basis for a period of 5 years (2001 to 2005) from a site in Tanzania.
The documentations that were collected at a height of 2 m were
projected to a height of 50 m which is the standard hub height of
wind turbines. The overall monthly average wind speed was found to
be 12.11 m/s whereas June to November was established to be the
windy season as the wind speed during the session is above the
overall monthly wind speed. The available wind power density
corresponding to the overall mean monthly wind speed was evaluated
to be 1072 W/m2, a potential that is worthwhile harvesting for the
purpose of electric generation.