Abstract: Let p be a prime and let b be an integer. MDS b-symbol codes are a direct generalization of MDS codes. The γ-constacyclic codes of length pˢ over the finite commutative chain ring Fₚm [u]/ < u² > had been classified into four distinct types, where is a nonzero element of the field Fₚm. Let C₃ be a code of Type 3. In this paper, we obtain the b-symbol distance db(C₃) of the code C₃. Using this result, necessary and sufficient conditions under which C₃ is an MDS b-symbol code are given.
Abstract: Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.
Abstract: The existing legal gap regarding thes treatment and final disposal of industrial effluents in Brazil promotes legal uncertainty. The government has not structured itself to guarantee environmental protection. The current legal system and public policies must guarantee the protection of bodies of water and an effective treatment of industrial effluents. This is because economic progress, eco-efficiency and industrial ecology are inseparable. The lack of protection for the water bodies weakens environmental protection, with abuses by companies that do not give due treatment to their effluents, or fail to present the water balance of their factories. It is considered necessary to enact a specific law on industrial effluents related to a National Industrial Effluent Policy, because it is the location of the largest Integrated Industrial Complex in the Southern Hemisphere. The regulation of this subject cannot be limited by decrees of the local Executive Branch, allowing the inspection of the industrial activity or enterprise to be affected fundamentally by environmental self-control, or by private institutions.
Abstract: Embodied Cognition (EC) as a learning paradigm is based on the idea of an inseparable link between body, mind, and environment. In recent years, the advent of theoretical learning approaches around EC theory has resulted in a number of empirical studies exploring the implementation of the theory in education. This systematic literature overview identifies the mainstream of EC research and emphasizes on the implementation of the theory across learning environments. Based on a corpus of 43 manuscripts, published between 2013 and 2017, it sets out to describe the range of topics covered under the umbrella of EC and provides a holistic view of the field. The aim of the present review is to investigate the main issues in EC research related to the various learning contexts. Particularly, the study addresses the research methods and technologies that are utilized, and it also explores the integration of body into the learning context. An important finding from the overview is the potential of the theory in different educational environments and disciplines. However, there is a lack of an explicit pedagogical framework from an educational perspective for a successful implementation in various learning contexts.
Abstract: The greatest influence we have from the world is shaped through the visual form, thus light is an inseparable element in human life. The use of daylight in visual perception and environment readability is an important issue for users. With regard to the hazards of greenhouse gas emissions from fossil fuels, and in line with the attitudes on the reduction of energy consumption, the correct use of daylight results in lower levels of energy consumed by artificial lighting, heating and cooling systems. Windows are usually the starting points for analysis and simulations to achieve visual comfort and energy optimization; therefore, attention should be paid to the orientation of buildings to minimize electrical energy and maximize the use of daylight. In this paper, by using the Design Builder Software, the effect of the orientation of an 18m2(3m*6m) room with 3m height in city of Tehran has been investigated considering the design constraint limitations. In these simulations, the dimensions of the building have been changed with one degree and the window is located on the smaller face (3m*3m) of the building with 80% ratio. The results indicate that the orientation of building has a lot to do with energy efficiency to meet high-performance architecture and planning goals and objectives.
Abstract: MDS matrices are of great significance in the design
of block ciphers and hash functions. In the present paper, we
investigate the problem of constructing MDS matrices which are
both lightweight and low-latency. We propose a new method of
constructing lightweight MDS matrices using circulant matrices
which can be implemented efficiently in hardware. Furthermore, we
provide circulant MDS matrices with as few bit XOR operations as
possible for the classical dimensions 4 × 4, 8 × 8 over the space of
linear transformations over finite field F42
. In contrast to previous
constructions of MDS matrices, our constructions have achieved
fewer XORs.
Abstract: Although English is not a second language in Iran, it has become an inseparable part of many Iranian people’s lives and is becoming more and more widespread. This high demand has caused a significant increase in the number of private English language institutes in Iran. Although English is a compulsory course in schools and universities, the majority of Iranian people are unable to communicate easily in English. This paper reviews the current state of teaching and learning English as an international language in Iran. Attitudes and motivations about learning English are reviewed. Five different aspects of using English within the country are analysed, including: English in public domain, English in Media, English in organizations/businesses, English in education, and English in private language institutes. Despite the time and money spent on English language courses in private language institutes, the majority of learners seem to forget what has been learned within months of completing their course. That is, when they are students with the support of the teacher and formal classes, they appear to make progress and use English more or less fluently. When this support is removed, their language skills either stagnant or regress. The findings of this study suggest that a dependant approach to learning is potentially one of the main reasons for English language learning problems and this is encouraged by English course books and approaches to teaching.
Abstract: Scarce resources are the inseparable part of organization life. This fact that only small number of the employees can have these resources such as promotion, raise, and recognition can cause competition among employees, which create competitive climate. As well as any other competition, small number wins the reward, and a great number loses, one of the possible emotional reactions to this loss is negative emotions like malicious envy. In this case, the envious person may try to harm the envied person by reducing the prosocial behavior. Prosocial behavior is a behavior that aimed to benefit others. The main propose of this action is to maintain and increase well-being and well-fare of others. Therefore, one of the easiest ways for harming envied one is to suppress prosocial behavior. Prosocial behavior has positive and important implication for organizational efficiency. Our results supported our model and suggested that competitive climate has a significant effect on increasing workplace envy and on the other hand envy has significant negative impact on prosocial behavior. Our result also indicated that envy is the mediator in the relation between competitive climate and prosocial behavior. Organizational competitive climate can cause employees respond envy with negative emotion and hostile and damaging behavior toward envied person. Competition can lead employees to look out for proof of their self-worthiness; and, furthermore, they measure their self-worth, value and respect by the superiority that they gain in competitions. As a result, loss in competitions can harm employee’s self-definition and they try to protect themselves by devaluating envied other and being ‘less friendly’ to them. Some employees may find it inappropriate to engage in the harming behavior, but they may believe there is nothing against withholding the prosocial behavior.
Abstract: In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset.
Abstract: The McEliece cryptosystem is an asymmetric type of
cryptography based on error correction code. The classical McEliece
used irreducible binary Goppa code which considered unbreakable
until now especially with parameter [1024, 524, and 101], but it is
suffering from large public key matrix which leads to be difficult to
be used practically. In this work Irreducible and Separable Goppa
codes have been introduced. The Irreducible and Separable Goppa
codes used are with flexible parameters and dynamic error vectors. A
Comparison between Separable and Irreducible Goppa code in
McEliece Cryptosystem has been done. For encryption stage, to get
better result for comparison, two types of testing have been chosen;
in the first one the random message is constant while the parameters
of Goppa code have been changed. But for the second test, the
parameters of Goppa code are constant (m=8 and t=10) while the
random message have been changed. The results show that the time
needed to calculate parity check matrix in separable are higher than
the one for irreducible McEliece cryptosystem, which is considered
expected results due to calculate extra parity check matrix in
decryption process for g2(z) in separable type, and the time needed to
execute error locator in decryption stage in separable type is better
than the time needed to calculate it in irreducible type. The proposed
implementation has been done by Visual studio C#.
Abstract: In this paper, we present a quantum statistical
mechanical formulation from our recently analytical expressions for
partial-wave transition matrix of a three-particle system. We report
the quantum reactive cross sections for three-body scattering
processes 1+(2,3)→1+(2,3) as well as recombination
1+(2,3)→1+(3,1) between one atom and a weakly-bound dimer. The
analytical expressions of three-particle transition matrices and their
corresponding cross-sections were obtained from the threedimensional
Faddeev equations subjected to the rank-two non-local
separable potentials of the generalized Yamaguchi form. The
equilibrium quantum statistical mechanical properties such partition
function and equation of state as well as non-equilibrium quantum
statistical properties such as transport cross-sections and their
corresponding transport collision integrals were formulated
analytically. This leads to obtain the transport properties, such as
viscosity and diffusion coefficient of a moderate dense gas.
Abstract: The notion of power and gender domination is one of
the inseparable aspects of themes in postmodern literature. The
reason of its importance has been discussed frequently since the rise
of Michel Foucault and his insight into the circulation of power and
the transgression of forces. Language and society operate as the basic
grounds for the study, as all human beings are bound to the set of
rules and norms which shape them in the acceptable way in the
macrocosm. How different genders in different positions behave and
show reactions to the provocation of social forces and superiority of
one another is of great interest to writers and literary critics. Mamet’s
works are noticeable for their controversial but timely themes which
illustrate human conflicts with the society and greed for power. Many
critics like Christopher Bigsby and Harold Bloom have discussed
Mamet and his ideas in recent years. This paper is the study of
Oleanna, Mamet’s masterpiece about the teacher-student relationship
and the circulation of power between a man and woman. He shows
the very breakable boundaries in the domination of a gender and the
downfall of speech as the consequence of transgression and freedom.
The failure of the language the teacher uses and the abuse of his own
words by a student who seeks superiority and knowledge are the
main subjects of the discussion. Supported by the ideas of Foucault,
the language Mamet uses to present his characters becomes the
fundamental premise in this study. As a result, language becomes
both the means of achievement and downfall.
Abstract: This paper presents a Gaussian process model-based
short-term electric load forecasting. The Gaussian process model is
a nonparametric model and the output of the model has Gaussian
distribution with mean and variance. The multiple Gaussian process
models as every hour ahead predictors are used to forecast future
electric load demands up to 24 hours ahead in accordance with the
direct forecasting approach. The separable least-squares approach that
combines the linear least-squares method and genetic algorithm is
applied to train these Gaussian process models. Simulation results
are shown to demonstrate the effectiveness of the proposed electric
load forecasting.
Abstract: A game using electro-oculography (EOG) as control signal was introduced in this study. Various EOG signals are generated by eye movements. Even though EOG is a quite complex type of signal, distinct and separable EOG signals could be classified from horizontal and vertical, left and right eye movements. Proper signal processing was incorporated since EOG signal has very small amplitude in the order of micro volts and contains noises influenced by external conditions. Locations of the electrodes were set to be above and below as well as left and right positions of the eyes. Four control signals of up, down, left and right were generated. A microcontroller processed signals in order to simulate a DDR game. A LCD display showed arrows falling down with four different head directions. This game may be used as eye exercise for visual concentration and acuity. Our proposed EOG control signal can be utilized in many other applications of human machine interfaces such as wheelchair, computer keyboard and home automation.
Abstract: A case study of the generation scheduling optimization
of the multi-hydroplants on the Yuan River Basin in China is reported
in this paper. Concerning the uncertainty of the inflows, the
long/mid-term generation scheduling (LMTGS) problem is solved by
a stochastic model in which the inflows are considered as stochastic
variables. For the short-term generation scheduling (STGS) problem, a
constraint violation priority is defined in case not all constraints are
satisfied. Provided the stage-wise separable condition and low
dimensions, the hydroplant-based operational region schedules
(HBORS) problem is solved by dynamic programming (DP). The
coordination of LMTGS and STGS is presented as well. The
feasibility and the effectiveness of the models and solution methods
are verified by the numerical results.
Abstract: Petroglyphs, stone sculptures, burial mounds, and
other memorial religious structures are ancient artifacts which find
reflection in contemporary world culture, including the culture of
Kazakhstan. In this article, the problem of the influence of ancient
artifacts on contemporary culture is researched, using as an example
Kazakhstan-s sculpture and painting. The practice of creating
petroglyphs, stone sculptures, and memorial religious structures was
closely connected to all fields of human existence, which fostered the
formation of and became an inseparable part of a traditional
worldview. The ancient roots of Saka-Sythian and Turkic nomadic
culture have been studied, and integrated into the foundations of the
contemporary art of Kazakhstan. The study of the ancient cultural
heritage of Kazakhstan by contemporary artists, sculptors and
architects, as well as the influence of European art and cultures on the
art of Kazakhstan are furthering the development of a new national
art.
Abstract: Integrins are a large family of multidomain α/β cell
signaling receptors. Some integrins contain an additional inserted I
domain, whose earliest expression appears to be with the chordates,
since they are observed in the urochordates Ciona intestinalis (vase
tunicate) and Halocynthia roretzi (sea pineapple), but not in integrins
of earlier diverging species. The domain-s presence is viewed as a
hallmark of integrins of higher metazoans, however in vertebrates,
there are clearly three structurally-different classes: integrins without
I domains, and two groups of integrins with I domains but separable
by the presence or absence of an additional αC helix. For example,
the αI domains in collagen-binding integrins from Osteichthyes
(bony fish) and all higher vertebrates contain the specific αC helix,
whereas the αI domains in non-collagen binding integrins from
vertebrates and the αI domains from earlier diverging urochordate
integrins, i.e. tunicates, do not. Unfortunately, within the early
chordates, there is an evolutionary gap due to extinctions between the
tunicates and cartilaginous fish. This, coupled with a knowledge gap
due to the lack of complete genomic data from surviving species,
means that the origin of collagen-binding αC-containing αI domains
remains unknown. Here, we analyzed two available genomes from
Callorhinchus milii (ghost shark/elephant shark; Chondrichthyes –
cartilaginous fish) and Petromyzon marinus (sea lamprey;
Agnathostomata), and several available Expression Sequence Tags
from two Chondrichthyes species: Raja erinacea (little skate) and
Squalus acanthias (dogfish shark); and Eptatretus burgeri (inshore
hagfish; Agnathostomata), which evolutionary reside between the
urochordates and osteichthyes. In P. marinus, we observed several
fragments coding for the αC-containing αI domain, allowing us to
shed more light on the evolution of the collagen-binding integrins.
Abstract: We consider power system expansion planning under
uncertainty. In our approach, integer programming and stochastic
programming provide a basic framework. We develop a multistage
stochastic programming model in which some of the variables are
restricted to integer values. By utilizing the special property of the
problem, called block separable recourse, the problem is transformed
into a two-stage stochastic program with recourse. The electric power
capacity expansion problem is reformulated as the problem with first
stage integer variables and continuous second stage variables. The
L-shaped algorithm to solve the problem is proposed.
Abstract: Soft topological spaces are considered as mathematical tools for dealing with uncertainties, and a fuzzy topological space is a special case of the soft topological space. The purpose of this paper is to study soft topological spaces. We introduce some new concepts in soft topological spaces such as soft first-countable spaces, soft second-countable spaces and soft separable spaces, and some basic properties of these concepts are explored.
Abstract: In this paper, a new face recognition method based on
PCA (principal Component Analysis), LDA (Linear Discriminant
Analysis) and neural networks is proposed. This method consists of
four steps: i) Preprocessing, ii) Dimension reduction using PCA, iii)
feature extraction using LDA and iv) classification using neural
network. Combination of PCA and LDA is used for improving the
capability of LDA when a few samples of images are available and
neural classifier is used to reduce number misclassification caused by
not-linearly separable classes. The proposed method was tested on
Yale face database. Experimental results on this database
demonstrated the effectiveness of the proposed method for face
recognition with less misclassification in comparison with previous
methods.