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Despite the adverse effects of late spring frost on the ecological and economic impact on agriculture, the management of these events are poorly investigated. Therefore, the grounded theory was used for extracting the livelihood stabilization model of orchardists on the shores of Lake Urmia against late spring frosts. The statistical population of this study in the qualitative part included 22 experts in the field of horticulture. In the quantitative study, they included all orchardists in the villages along with Lake Urmia, comprising 341 people, of which 236 were randomly selected. By carefully examining and linking the concepts and subcategories, the most important subcategories that were included six subcategories. The results of all calculated goodness-of-fit indexes (chi-square [P > 0.01], RMSEA = 0.000, NFI = 0.95, CFI = 0.91, and GFI = 0.92) showed the model provided an excellent fit for the data. Standardized regression coefficients showed that interfering factors had the greatest impact on the livelihood of orchardists against late spring frosts (β = 0.47). Also, the background factors (β = 0.43) and causal factors (β = 0.39) were found to affect the livelihood of the orchardists in encountering late spring frost. The results of multiple square correlations of dependent variables also indicated that about 41% of the livelihood variance of small-scale orchardists was explained by the predictor variables (i.e. causal conditions, background factors and interfering factors). The findings of this study can assist policymakers, planners and relevant managers while paying more attention to orchardists in the region, so as to support decisions in order to achieve sustainable development. Resumo Apesar dos efeitos adversos das geadas do final da primavera no impacto ecológico e econômico na agricultura, o manejo desses eventos é pouco investigado. Portanto, a teoria fundamentada foi utilizada para extrair o modelo de estabilização dos meios de subsistência dos pomares nas margens do Lago Urmia contra as geadas do final da primavera. A população estatística deste estudo na parte qualitativa incluiu 22 especialistas na área de horticultura. O estudo quantitativo incluiu todos os fruticultores nas aldeias junto ao Lago Urmia, compreendendo 341 pessoas, das quais 236 foram selecionadas aleatoriamente. Ao examinar cuidadosamente e vincular os conceitos e subcategorias, as subcategorias mais importantes que foram incluídas em outras 6 subcategorias. Os resultados de todos os índices de qualidade de ajuste calculados (qui-quadrado [P > 0,01], RMSEA = 0,000, NFI = 0,95, CFI = 0,91 e GFI = 0,92) mostraram que o modelo forneceu um excelente ajuste para os dados. Os coeficientes de regressão padronizados mostraram que os fatores interferentes tiveram o maior impacto sobre a subsistência dos pomares contra as geadas do final da primavera (β = 0,47). Além disso, descobriu-se que os fatores de fundo (β = 0,43) e os fatores causais (β = 0,39) afetam o sustento dos pomares ao enfrentarem geadas no final da primavera. Os resultados de múltiplas correlações quadradas de variáveis dependentes também indicaram que cerca de 41% da variância dos meios de subsistência de pequenos pomares foi explicada pelas variáveis preditoras, ou seja, condições causais, fatores de fundo e fatores interferentes. Os resultados deste estudo podem auxiliar os formuladores de políticas, planejadores e gestores relevantes, dando mais atenção aos pomares da região, de modo a apoiar as decisões a fim de alcançar o desenvolvimento sustentável.

Considering the cooperative sector capabilities in organizing rural people, primarily focusing on empowering manpower and adopting a sustainable approach to basic resources (water and soil), village-cooperative initiative has emerged as a new concept by registering and forming 4565 new cooperatives in Iran’s rural regions. The present research which was conducted in two qualitative and quantitative phases designed a new model by integrating the new village-cooperative approach along with the sustainable livelihood’s framework theory. The study sample of the qualitative phase included 32 theorists of the village-cooperative initiative. To analyze the data, the grounded theory and three-step process of open coding, axial coding and selective coding were used using MAXqda18 software. Finally, a paradigm model was designed whose most important components included causal conditions (shocks and seasonal conditions), contextual conditions (trends and governmental support), intervening conditions (control and market development), central categories (sustainable livelihoods with a village- cooperative approach), strategies (coping and adaptation) and consequences (creating jobs, establishing cooperatives, supporting smart agriculture and strengthening social capital). The statistical quantitative phase population consisted of cooperatives members in the village-cooperative initiative (N=405), being selected through Cochran's formula with proportional sampling method summing up to198 people from 5 provinces. The data collection tool was a researcher-made questionnaire whose validity and reliability were confirmed. The Bayesian structural equation modeling was used to analyze the data. The results of the research quantitative phase showed that the variables of financial capital, physical capital, social capital, coping and adaptation strategies, human capital and natural capital were the most effective variables on village-cooperative initiative members’ sustainable livelihoods, respectively. Finally, a hybrid model based on the qualitative and quantitative studies was designed and suggestions were made; for instance, the creation of suitable grounds for off-farm activities such as rural industries and ecotourism. Resumo Considerando as capacidades do setor cooperativo na organização da população rural, focando principalmente na capacitação de mão de obra e na adoção de uma abordagem sustentável para os recursos básicos (água e solo), a iniciativa de cooperativa de aldeia surgiu como um novo conceito ao registrar e formar 4.565 novas cooperativas nas regiões rurais do Irã. A presente pesquisa, que foi conduzida em duas fases qualitativas e quantitativas, projetou um novo modelo integrando a nova abordagem cooperativa de aldeia junto com a teoria da estrutura de subsistência sustentável. A amostra do estudo da fase qualitativa incluiu 32 teóricos da iniciativa vila-cooperativa. Para analisar os dados, a teoria fundamentada e o processo de três etapas de codificação aberta, codificação axial e codificação seletiva foram usados o software MAXqda18. Finalmente, um modelo de paradigma foi desenhado, cujos componentes mais importantes incluíam condições causais (choques e condições sazonais), condições contextuais (tendências e apoio governamental), condições intervenientes (controle e desenvolvimento de mercado), categorias centrais (subsistência sustentável com uma abordagem cooperativa de aldeia), estratégias (enfrentamento e adaptação) e consequências (criação de empregos, estabelecimento de cooperativas, apoio à agricultura inteligente e fortalecimento do capital social). A população da fase quantitativa estatística consistiu de cooperados na iniciativa vila-cooperativa (N = 405), sendo selecionados através da fórmula de Cochran com método de amostragem proporcional totalizando 198 pessoas de cinco províncias. A ferramenta de coleta de dados foi um questionário elaborado pelo pesquisador cuja validade e confiabilidade foram confirmadas. A modelagem de equações estruturais bayesianas foi utilizada para analisar os dados. Os resultados da fase quantitativa da pesquisa mostraram que as variáveis de capital financeiro, capital físico, capital social, estratégias de enfrentamento e adaptação, capital humano e capital natural foram as variáveis mais eficazes na subsistência sustentável dos membros da iniciativa cooperativa de aldeia, respectivamente. Finalmente, um modelo híbrido baseado nos estudos qualitativos e quantitativos foi desenhado e sugestões foram feitas; por exemplo, a criação de terrenos adequados para atividades não agrícolas, como indústrias rurais e ecoturismo.

Modern hierarchical vision transformers have added several vision-specific components in the pursuit of supervised classification performance. While these components lead to effective accuracies and attractive FLOP counts, the added complexity actually makes these transformers slower than their vanilla ViT counterparts. In this paper, we argue that this additional bulk is unnecessary. By pretraining with a strong visual pretext task (MAE), we can strip out all the bells-and-whistles from a state-of-the-art multi-stage vision transformer without losing accuracy. In the process, we create Hiera, an extremely simple hierarchical vision transformer that is more accurate than previous models while being significantly faster both at inference and during training. We evaluate Hiera on a variety of tasks for image and video recognition. Our code and models are available at https://github.com/facebookresearch/hiera., Comment: ICML 2023 Oral version. Code+Models: https://github.com/facebookresearch/hiera

Along with the global population growth, the human need for safe drinking water sources has increased. With global warming, the water challenge is perhaps the most crucial challenge for the world community. At the same time, scientific methods are one of the best tools to help humanity. Considering that in many natural phenomena, it is possible to describe them based on complex relationships, it is almost impossible to solve them analytically and mathematically. Therefore, it is necessary to use methods with the ability, accuracy, and high speed to justify nonlinear relationships. One of these methods is Artificial Intelligence (AI). This research used the Extreme Learning Machine (ELM) model and Genetic Algorithm (GA) to create a new hybrid model Genetic Extreme Learning Machine (GAELM). AI and hybrid models were used to simulate and predict the water quality parameter changes. The study area in this work was the Colorado River Basin in the United States. The desired qualitative parameters were Electrical Conductivity (EC) and Dissolved Oxygen (DO). Finally, using seven approaches, the models' performance was compared. The results showed that the best simulation related to the GAELM hybrid model in the EC parameter modeling with indices RMSE and R2 equal to 0.1304, and 0.8619, respectively. Also, the ELM model was ranked in second place in accuracy. Based on the uncertainty analysis (UA-WSM) results, the GAELM(EC) model was the most accurate, with the minimum average prediction error equal to 0.01.

Suppose that a system is subject to a sequence of shocks which occur with probability p in any period of time [Formula: see text], and suppose that [Formula: see text] and [Formula: see text] are two critical levels ([Formula: see text]). The system fails when the time interval between two consecutive shocks is less than [Formula: see text], and the time interval bigger than [Formula: see text] has no effect on the system activity. In addition, the system fails with a probability of, say, [Formula: see text], when the time interval varies between [Formula: see text] and [Formula: see text]. Therefore, this model can be regarded as an extension of discrete time version of [Formula: see text]-shock model, and such an idea can be also applied in the extension of other shock models. The present study obtains the reliability function and the probability generating function of the system’s lifetime under this model. The present study offers some properties of the system and refers to a generalization of the new model. In addition, the mean time of the system’s failure is obtained under reduced efficiency which is created when the time between two consecutive shocks varies between [Formula: see text] and [Formula: see text] for the first time.

The purpose of this study is to investigate the factors affecting the employment-oriented empowerment of rural female heads of households in Ilam. In terms of monitoring and degree of control, this is field research and in terms of method of obtaining facts and data processing, it is a survey study and in terms of data collection, it is descriptive-correlational. The statistical population of this study is 14156 rural female heads of households in Ilam. The sample size was set for 374 people using Krejcie and Morgan Table. In this study, due to having a list of the names of all women studied, a systematic sampling method was used. The data collection tool in this study was a researcher-made questionnaire whose face validity and content validity were provided through a panel of experts. The reliability of the questionnaire was also confirmed by Cronbach's alpha. The results of regression analysis showed that the variables of psychological dimension, social dimension, cultural dimension, and the technical dimension of professional competencies have the greatest impact on the empowerment of rural women and in other words, explain 52% of the changes in the empowerment variable of women.

In today’s society, achieving development and reducing regional inequalities is one of the most important challenges facing governments. The role and position of villages in the process of economic, social and political development on a local, regional and national scale and the consequences of underdevelopment of rural areas such as widespread poverty, growing inequality, rapid population growth, unemployment, migration, and urban marginalization has attracted attention to rural development, and many experts believe that the cause of urban problems in developing countries is underdevelopment of rural areas. In the current research, in order to determine the degree of development of villages in Lorestan province, various economic, social and cultural sectors were considered and their ranking based on the development level using numerical taxonomic analysis method has been done. To do this, we using the latest statistics and information related to 2016, and 101 variables in the form of 8 indicators (educational, demographic, infrastructure, economical, health, service, cultural, welfare and agricultural performance) have been evaluated. According to our results, it was observed that the distribution of facilities and services in the villages of Lorestan province is unbalanced, as out of 87 villages of Lorestan province, four villages were identified as heterogeneous areas and Bazvand village has a development coefficient of 0;765 as a most provided village in this province. The rest of the villages in Lorestan province are being deprived as semi-provided and deprived villages. In conclusion, it has been said that most of the villages in this province need proper management and planning to develop and increase facilities and services.

During the past few decades, many social factors and climate change in particular have had adverse effects on nomadic livelihoods in Iran. Drought, heat waves, floods and cold spells are impediments to a sustainable development for nomads. So far, previous adaptation strategies have not sufficiently proved effective in improving their livelihood. The present study aimed at designing a development model for organizing nomads of the Zagros region. The grounded theory methodology was applied to construct the hypothesis through inductive qualitative data. We used questionnaires, focus groups and in-depth interviews to survey the opinions of experts and managers about optimum ways to organize and develop Iranian nomadic communities. Researchers analyzed the data using open, axial and selective coding to discover the main concepts. The samples were selected through the “snowball effect sampling method” in which sampling continued until a theoretical saturation was reached. To recognize concepts and categories, line by line analysis was used in open coding. The present study revealed how various aspects of nomadic livelihood can affect managerial efforts to organize and develop nomadic life in the region. These effective aspects were categorized into three main groups: causal, interfering and background. Also, the results introduced a comprehensive adaptation strategy model based on grounded theory which covered many aspects of the nomadic livelihood. Our results suggested that this approach is more likely to ensure the sustainability of environmental resources, social justice and improvements in economic indicators.

This study was carried out to explain the development of ecotourism in the tourist villages of the Kermanshah province, using a quantitative-qualitative method. Qualitative data analysis was performed using the maxqda12 software. The statistical sample in the qualitative section was snowball and 20 experts. In the quantitative section, the stratified random sampling method with the Morgan ratio was used. The research tool was an interview with a questionnaire prepared by an investigator derived from the qualitative phase of the research and the background. Data analysis with SPSS24 and PLS2 software indicated that the study model was adequate. On the other hand, it was discovered that all the dimensions of the conceptual research model were extracted from the qualitative and literary studies of the research literature to measure the factors and had a good function in the measurement of these concepts. The multivariate determination coefficient for the main structural equation was 85.5%, indicating that the independent variables of the study included economic, social, and cultural factors, participation, attractions, management, policy formulation, and infrastructure factors. Economic, social and cultural factors, attractions, ecotourism, participatory management and policy-making infrastructures have priorities, second to seventh, respectively. The first priority focuses on anticipating changes in the development of ecotourism

In this paper, we study an (n-k+1)-out-of-n system by adopting their components to be statistically independent though nonidentically distributed. By assuming that at least m components at a fixed time have failed while the system is still working, we obtain the mixture representation of survival function for a quantity called the conditional inactivity time of failed components in the system. Moreover, this quantity for (n-k+1)-out-of-n system, in one sample with respect to k and m and in two samples, are stochastically compared.

In this paper, the life distribution behavior of a generalization of the mixed $$\delta$$-shock models in the multi-state systems is studied. In this model, the k out of interarrival times between two successive shocks with a magnitude less than $$\delta$$ have a disaster result on the system which causes a complete failure. In addition to this event, another factor called the magnitude of shock causes the failure of the system, such that if the magnitude of a shock is greater than another critical threshold $$\gamma$$, then the system fails. Such model create a multi-state system with a number of different states. The survival functions of the lifetime, the time spent by the system in a complete working state, and the total time spent by the system in partially working states are derived and the corresponding first two moments are also computed. An application in industry is analyzed to illustrate the proposed methodology. A simulation study is also presented to illustrate the behavior of the survival functions.

Urban agriculture can provide food security that is essential to sustainable development goals. Citizen education plays a vital role in urban agriculture formation. The present study examined the effectiveness of urban agriculture education courses in the three levels of the Kirkpatrick model and estimated a structural equation model to obtain the direct effects of the studied factors. This study consisted of citizens (N = 80) who participated in the urban agricultural education courses in flowering centers of the 2nd district of Tehran, Iran. According to the results, 55, 46.25 and 48.75% of the respondents evaluated the education courses as “good” in the reaction, learning, and behavior levels, respectively. In addition, 58% of participants believed these courses had a great impact on their understanding of urban agriculture. Attending education courses was well explained by the three levels of the Kirkpatrick model (P 0.05], RMSEA = 0.02, SRMR = 0.065, NFI = 0.91, CFI = 0.92, and GFI = 0.90) showed the model provided an excellent fit for the data. There is limited information about urban agriculture among the citizens. According to the results the training courses can increase the citizen’s knowledge on urban agriculture which improve food security and urban environmental management.

Qualitative analysis of water resources is one of the most widely used topics in water resources research today. Researchers use various analysis methods of water parameters to achieve the desired goals in this field. This research uses artificial intelligence (AI), learning machine (LM), data mining, and mathematical techniques to simulate water behavior and estimate its parametric changes. The proposed model used in this study was a Self-adaptive Extreme learning machine (SAELM) to estimate hydrogeological parameters of the Meghan wetland located in Markazi province in Iran. In addition, SAELM simulation results were compared to Least square support vector machine (LSSVM), Multiple linear regression (MLR), and Adaptive Neuro-fuzzy inference system (ANFIS) models. The simulated parameters were Electrical Conductivity (EC), Total Dissolved Solids (TDS), Groundwater Level (GWL), and salinity. This information was related to sampling for 175 months in the study area. Finally, after simulation operation, four models were introduced as superior models. Mentioned exceptional models were SAELM in GWL modeling, SAELM in modeling the EC, MLR in salinity simulation, and LSSVM in the simulation of TDS parameters. Moreover, by five approaches, the models' performance was evaluated. Suggested strategies were performance evaluation by statistical indicators, Wilson score method uncertainty analysis (WSMUA), response & correlation plots, discrepancy ratio charts, and distribution error diagrams. Based on statistical indicators, the SAELMGWL model was the most accurate model with RMSE, MAPE, and R2 indices equal to 0.1496, 0.0043, and 0.9933, respectively. The ANFIS model had the worst results in simulation.

Empowering or gaining power is considered as a process through which villagers get capability to form and organize themselves in order to increase their self-confidence, ask for their right to choose freely and independently, being able to control the resources, cope with and eliminate poverty. Accordingly, the present study (a descriptive and non-experimental study) aimed to design a capability model for villagers in Zanjan province in order to achieve self-efficiency and assess the model through structural equations modeling. The main components of the intended model were compared through post-event technique, and the variables of self-sufficiency in villagers were validated by using descriptive-correlational design and structural equations modeling. Furthermore, statistical population included all villagers living in Zanjan province among which 384 ones were selected as the sample population through stratified random sampling with proportional allocation through distributing researcher-made questionnaire among villagers in the province. The data related to descriptive and inferential statistics sections were respectively analyzed by SPSS 25 and AMOS 24 softwares. Based on the results of structural equations, financial connector and condition were determined as the most effective latent variables on capability as a mediator dependent variable. Finally, the highest effect on self-sufficiency was observed in capability.

We introduce Patch Aligned Contrastive Learning (PACL), a modified compatibility function for CLIP's contrastive loss, intending to train an alignment between the patch tokens of the vision encoder and the CLS token of the text encoder. With such an alignment, a model can identify regions of an image corresponding to a given text input, and therefore transfer seamlessly to the task of open vocabulary semantic segmentation without requiring any segmentation annotations during training. Using pre-trained CLIP encoders with PACL, we are able to set the state-of-the-art on the task of open vocabulary zero-shot segmentation on 4 different segmentation benchmarks: Pascal VOC, Pascal Context, COCO Stuff and ADE20K. Furthermore, we show that PACL is also applicable to image-level predictions and when used with a CLIP backbone, provides a general improvement in zero-shot classification accuracy compared to CLIP, across a suite of 12 image classification datasets.

In natural resource management, different stakeholders and actors can be involved as major components. These can include the social network of users benefiting from natural resources. Therefore, the need for an evaluation of the human community that comes into relation with natural resources and social relations is inevitable. The present study aimed to portray current scopes of management in the Zagros forests based on social monitoring and estimations of relationships between local actors. The research uses a method of social network analysis as an efficient tool for evaluating these relationships. Links were found between information exchange and participation in the social network of local actors, and, accordingly, the quantitative and mathematical indicators of network analysis were evaluated among all actors in the Zagros forests. The level of cohesion and social capital in the social network of local stakeholders in this region were estimated as “weak” to “moderate,” and the sustainability of the network was “moderate.” Based on the Quadratic Assignment Procedure (QAP index), a high coefficient was obtained in describing the level of correlation between the two networks of information exchange and participation among the actors in the region. The results can be used in line with principled policies in managing forest resources of the Zagros region for planning, decision-making, and sustainability. Based on the results, there is potential for an increase in social control in the target groups and adherence to local traditions in the sustainable management of forest resources among actors. This can be achieved by strengthening social trust. The scientific contribution of this research mainly fills gaps in the current knowledge of Iran’s administrative bodies which are responsible for sending and receiving information about forest management. The focus is largely descriptive and each organization is given attributes to its values of in-degree and out-degree centrality.

Suppose that a system is subject to independent random shocks over discrete time periods, with the shocks occurring each period with a probability of p, and suppose that k1 and k2 (1≤k1

In this paper, the mixed δ-shock models for the multi-state systems is generalized to a model for which the system switches to a lower partially working state as soon as the occurrence of each inte...

While deep neural networks have achieved remarkable success in various computer vision tasks, they often fail to generalize to new domains and subtle variations of input images. Several defenses have been proposed to improve the robustness against these variations. However, current defenses can only withstand the specific attack used in training, and the models often remain vulnerable to other input variations. Moreover, these methods often degrade performance of the model on clean images and do not generalize to out-of-domain samples. In this paper we present Generative Adversarial Training, an approach to simultaneously improve the model's generalization to the test set and out-of-domain samples as well as its robustness to unseen adversarial attacks. Instead of altering a low-level pre-defined aspect of images, we generate a spectrum of low-level, mid-level and high-level changes using generative models with a disentangled latent space. Adversarial training with these examples enable the model to withstand a wide range of attacks by observing a variety of input alterations during training. We show that our approach not only improves performance of the model on clean images and out-of-domain samples but also makes it robust against unforeseen attacks and outperforms prior work. We validate effectiveness of our method by demonstrating results on various tasks such as classification, segmentation and object detection., Comment: ICCV 2021. arXiv admin note: substantial text overlap with arXiv:1911.09058

The present study aimed to design a model to reduce agricultural work injury among orchardists in Ilam Province, Iran. This was a qualitative research study that used grounded theory to analyze data. The study included 25 specialists, managers, and experts of horticulture in Ilam Province who were selected through purposive sampling. Field observations and interviews in the form of focus groups were used for collecting data. The results were extracted from the research data through the coding process (open, axial, and selective) in the form of concepts, subcategories, and categories using MAXqda12. The paradigm model included causal, contextual and intervening conditions, strategy, and consequences. The results indicated that several causal conditions can affect work injury in agriculture. These were identified as vulnerability level, personal characteristics of orchardists, subsistence level, general health, climatic conditions, and academic qualifications. Contextual conditions also included categories like trends, occupational safety and health principles, infrastructure, government support, and government incentives. Meanwhile, intervening conditions were identified as structural, educational-research factors, economic criteria, regulation and development of marketing horticultural and greenhouse products, type of exploitation system, and orchardists��� motivation. Finally, reducing agricultural work injuries among orchardists involved the multi-faceted identification of various aspects of production and education, along with technical, operational, executive, and supervisory management strategies. Reducing the number of agricultural work injuries among orchardists would lead to regional, economic, individual, and social benefits. The results helped researchers to identify what areas to address and mitigate safety issues of horticultural activities in Ilam.

Point clouds provide a compact and efficient representation of 3D shapes. While deep neural networks have achieved impressive results on point cloud learning tasks, they require massive amounts of manually labeled data, which can be costly and time-consuming to collect. In this paper, we leverage 3D self-supervision for learning downstream tasks on point clouds with fewer labels. A point cloud can be rotated in infinitely many ways, which provides a rich label-free source for self-supervision. We consider the auxiliary task of predicting rotations that in turn leads to useful features for other tasks such as shape classification and 3D keypoint prediction. Using experiments on ShapeNet and ModelNet, we demonstrate that our approach outperforms the state-of-the-art. Moreover, features learned by our model are complementary to other self-supervised methods and combining them leads to further performance improvement., Comment: 3DV 2020

Shock models and multi-state systems have both been studied in the reliability literature. Suppose a system experiences shocks that occur randomly and their occurrence causes a change in the system...

In this paper, a comprehensive scheme is proposed for online monitoring of voltage stability using the Weighted Least Square Support Vector Machine (WLS-SVM) that the effect of overcurrent protection for transmission lines is factored in. The operation of protection systems, due to their nonlinear effect on the system graph, changes the linear and nonlinear equations of the system which cannot be solved by conventional methods. To prevent the maloperation of the overcurrent protection system, coordination between Directional Overcurrent Relays (DOCRs) has been done by linear programming to reach the globally optimum values for DOCR settings. As a result, WLS-SVM is used by implementing collected data from Phasor Measurement Units (PMUs). In addition to solving linear equations instead of quadratic equations, WLS-SVM solves the problems of noise sensitivity and lack of sparseness of the solutions. Also, Principal Component Analysis (PCA) has been used for the dimensionality reduction of the input vector applied to WLS-SVM in this work to make it suitable for real-time applications. Moreover, the measurement errors between measurements obtained from PMUs and the reference values have been taken into account. Then, real-time power system stability monitoring is performed by predicting a voltage stability assessment index using WLS-SVM to evaluate the voltage stability status in a real-time manner. Results of the proposed method regarding efficiency demonstrate high accuracy and better performance in comparison with other approaches. The simulation of the presented approach is carried out on the IEEE 39-bus and IEEE 118-bus systems.

Paddy cultivation of rice requires substantial physical strength, perseverance and manual labor. During the manual harvesting of paddy rice in Iran, laborers are exposed to several work-related physical risks. Paddy cultivation has been reported as one of the most important causes of nonfatal occupational injuries and accidents among farmers. With the aim of identifying which parts of the musculoskeletal structure are mostly affected as a result of working on paddy rice fields, the present study aimed to investigate the potential risk factors for musculoskeletal problems in paddy field workers in Mazandaran Province, Iran.A cross-sectional, analytical study was conducted among paddy field workers via multistage sampling in 2019. Prior to the interviews based on the Nordic Musculoskeletal Questionnaire, the participants were briefed about the objectives of the research and their consent was obtained for voluntary participation. Through interviews, data were collected on demographics, agricultural utilization systems, use of paddy tractors, frequency of tiller and tractor use, injuries sustained during the daytime, and outcomes of injuries by paddy field working. Responses were obtained from 384 workers using structured interviews. The respondents were asked to describe problems and pain in their neck, shoulders, elbows, wrists and hands, upper back, hip and lower back. Logistic regression models were used to identify potential risk factors for musculoskeletal problems in specific body regions.The most commonly reported ailments were back pain (Disorders in certain body regions could be explained by specific individual and work-related factors. While the prevalence of work-related injury was high, mostly due to ignorance and disregard for personal convenience of the workers, the findings call for improvements in mechanization and division of labor time and force. Another highlight is that social worth is not given sufficiently to the health of paddy field workers. These should be worked on in future research to find ways of allocating machinery and worth to the workers.

Background: Carpal tunnel syndrome (CTS) is the most prevalent form of peripheral neuropathy. There are various treatments for carpal tunnel. Objectives: In this study, we evaluated the effect of electroacupuncture and exercise on pinch and grip strength and wrist range of motion in patients with mild to moderate CTS. Methods: Sixty patients with carpal tunnel syndrome were evaluated in this study, only five of whom were male. In this study, patients were divided into three groups. The control group consisted of 20 patients who only used splints in the second group, in addition to splints, special exercises were administered, and the third group, electroacupuncture, and brace were prescribed for 12 sessions of 40- minute duration. study time was 6 weeks. The parameters of pinch force, grip force, ROM (flexion and extension) were evaluated at baseline and after the treatment. Results: In this study, 55 women and 5 men with an average age of 49.23 ± 8.96 were enrolled. At the final follow up, significant improvements in all parameters were found in third groups (P < 0.05), except flexion of the wrist in the control group (P = 0.098). Our findings indicate that exercise therapy had more effect on ROM of flexion than acupuncture and acupuncture had more effect on pinching than exercise therapy but the effect sizes were weak. Also, the efficacy of splint alone was less than intervention groups in all parameters. Conclusions: Results of this study demonstrated that adding exercise or acupuncture to nocturnal splinting, the functional improvement is more in patients with mild to moderate carpal tunnel syndrome and these interventions could be adopted in the management of these patients.

We propose a novel neural architecture for representing 3D surfaces, which harnesses two complementary shape representations: (i) an explicit representation via an atlas, i.e., embeddings of 2D domains into 3D; (ii) an implicit-function representation, i.e., a scalar function over the 3D volume, with its levels denoting surfaces. We make these two representations synergistic by introducing novel consistency losses that ensure that the surface created from the atlas aligns with the level-set of the implicit function. Our hybrid architecture outputs results which are superior to the output of the two equivalent single-representation networks, yielding smoother explicit surfaces with more accurate normals, and a more accurate implicit occupancy function. Additionally, our surface reconstruction step can directly leverage the explicit atlas-based representation. This process is computationally efficient, and can be directly used by differentiable rasterizers, enabling training our hybrid representation with image-based losses.

We aim to build image generation models that generalize to new domains from few examples. To this end, we first investigate the generalization properties of classic image generators, and discover that autoencoders generalize extremely well to new domains, even when trained on highly constrained data. We leverage this insight to produce a robust, unsupervised few-shot image generation algorithm, and introduce a novel training procedure based on recovering an image from data augmentations. Our Augmentation-Interpolative AutoEncoders synthesize realistic images of novel objects from only a few reference images, and outperform both prior interpolative models and supervised few-shot image generators. Our procedure is simple and lightweight, generalizes broadly, and requires no category labels or other supervision during training.

Estimating fundamental matrices is a classic problem in computer vision. Traditional methods rely heavily on the correctness of estimated key-point correspondences, which can be noisy and unreliable. As a result, it is difficult for these methods to handle image pairs with large occlusion or significantly different camera poses. In this paper, we propose novel neural network architectures to estimate fundamental matrices in an end-to-end manner without relying on point correspondences. New modules and layers are introduced in order to preserve mathematical properties of the fundamental matrix as a homogeneous rank-2 matrix with seven degrees of freedom. We analyze performance of the proposed models using various metrics on the KITTI dataset, and show that they achieve competitive performance with traditional methods without the need for extracting correspondences.

In this paper, the life behavior of a shock model is studied, when the external shocks occur according to a binomial process whose interarrival times between successive shocks follow a geometric distribution. The system transits into a lower partially working state upon the occurrence of each interarrival time between two successive shocks less than a critical threshold, say δ . The system fails when k out of interarrival times between two successive shocks are less than δ , or the magnitude of the shock is larger than the other critical level, say γ . Such a model creates a multi-state system having a number of different states. The probability mass functions of system’s life time, the time spent by the system in a perfectly functioning state, and the total time spent by the system in partially working states are derived for the proposed model. The corresponding probability generating functions are also derived. The case of Markov shock occurrences is also studied. To illustrate the model studied in this paper, some numerical examples are also considered. Finally, an application in insurance is also provided.

Since the advent of online real estate database companies like Zillow, Trulia and Redfin, the problem of automatic estimation of market values for houses has received considerable attention. Several real estate websites provide such estimates using a proprietary formula. Although these estimates are often close to the actual sale prices, in some cases they are highly inaccurate. One of the key factors that affects the value of a house is its interior and exterior appearance, which is not considered in calculating automatic value estimates. In this paper, we evaluate the impact of visual characteristics of a house on its market value. Using deep convolutional neural networks on a large dataset of photos of home interiors and exteriors, we develop a method for estimating the luxury level of real estate photos. We also develop a novel framework for automated value assessment using the above photos in addition to home characteristics including size, offered price and number of bedrooms. Finally, by applying our proposed method for price estimation to a new dataset of real estate photos and metadata, we show that it outperforms Zillow's estimates.

OBJECTIVE: The aims of this study were to assess the incidence, risk factors and complications of falls in the hemodialysis (HD) population. MATERIAL and METHODS: Using a prospective study design, chronic HD patients aged ≥50 years were recruited. The baseline characteristics and laboratory markers of all study participants were recorded. Participants were followed prospectively for 12 weeks. Patients were questioned thrice weekly about fall incidents. RESULTS: A total of 34 patients (mean age 69.1 year) participated in this study. A total of 16 falls occurred in nine (26%) patients over 12 weeks of follow-up with an incidence rate of 1.30 falls/patientyear. By applying univariate logistic regression analysis, previous fall history (odds ratio 10.5, P-value= 0.008), high parathyroid hormone level (odds ratio 1.032, P-value= 0.016) and impaired balance (odds ratio 9.00, P-value= 0.01) were identified as significant risk factors for falls. CONCLUSION: We concluded that high parathyroid hormone levels might be an important predictor of falling in HD patients in addition to impaired balance and previous fall history. As such, parathyroid hormone is a crucial factor to target for future intervention strategies aimed at reducing the fall incidence in the HD population. KEy wORDS: Accidental falls, Renal dialysis, Parathyroid hormone, Balance, Risk factors

Sustainable development and the definition of indicators to assess progress towards sustainability have become a high priority in scientific research. The purpose of this study was two-fold: first, to determine agricultural sustainability criteria; second, to determine optimum partnership models for agricultural sustainability. This study was conducted in Ilam Province of Iran. The populations of the research were 30 farmers, who were interviewed to determine the sustainable agricultural development criteria. A discussion of the nine criteria was developed. Through an interview we were able to determine how they perceived the relative importance of these criteria. A questionnaire was developed based on analytical hierarchy process (AHP). Each question consisted of a pair-wise comparison of two criteria. Therefore, the nine criteria and four alternatives resulted in a total of 72 questions. First the respondents were asked to indicate the relative importance of the two criteria with respect to the overall goal. Finally, the farmers were asked to indicate the relative importance of the two alternatives (partnership models) with respect to each criterion. The results indicated thatreducing farmers migration, sharing with agricultural engineer, land consolidation, increasing farmers awareness, crop rotation, using less amount of chemical fertilizer, using less amount of chemical pesticide, fertilizer recommendation and allocation efficiency are the most important criteria for sustainable agriculture in Iran. A sensitivity analysis was carried out to determine the critical factors that affected the priority of alternatives. Also, results of application of AHP indicated that private and cooperative partnership models are the most useful partnership models in the agricultural sustainability. The results of this study demonstrated that the private partnership model for agricultural sustainability is imperative. Key words: AHP, partnership, Iran, sustainable agricultural development.

In this paper, a parallel system consisting of a finite number of identical components with independent lifetimes having a common distribution function is considered, when the failure time of the system is restricted to a finite interval (double regularly checking). Under these conditions, the mean past lifetime (MPL) of the system is presented and some of its properties are derived. It is shown that the underlying distribution function can be recovered from the proposed MPL. Then, a consistent estimator for MPL is presented and some of its properties are studied. This estimator also could be used for the single monitoring case or ordinary MPL. Finally, some properties of the MPL of a parallel system with nonidentical components are discussed.

This study investigated the effects of workshop and lecture methods on pastoralists' learning in Ilam Province, west of Iran. A quasi-experimental research method and non-equivalent control group design was used. Sixty pastoralists participated in this study. An open-ended questionnaire was used as the instrument of the study and found to have content validity and inter-rater reliability. Findings of the study showed a significant difference between effectiveness of lecture and workshop through pre- and post-tests. In general, the workshop method was proven to be more effective in improving pastoralists' learning with regard to preservation, renovation, and utilization of rangelands due to better decision making about their rangeland management practices. Most importantly, the workshop method also seemed to have established the behavioral mapping of these factors to a greater degree for participants.

In the present article, we consider a parallel system consisting of n identical components, such that the lifetimes of components are independent and have a common distribution function F. It is assumed that the total number of failures of the components at time t 1 is m and at time t 2 (t 1

In this paper, we present a multi-user resource allocation framework using fragmented-spectrum synchronous OFDM-CDMA modulation over a frequency-selective fading channel. In particular, given pre-existing communications in the spectrum where the system is operating, a channel sensing and estimation method is used to obtain information of subcarrier availability. Given this information, some real-valued multi-level orthogonal codes, which are orthogonal codes with values of $\{\pm1,\pm2,\pm3,\pm4, ... \}$, are provided for emerging new users, i.e., cognitive radio users. Additionally, we have obtained a closed form expression for bit error rate of cognitive radio receivers in terms of detection probability of primary users, CR users' sensing time and CR users' signal to noise ratio. Moreover, simulation results obtained in this paper indicate the precision with which the analytical results have been obtained in modeling the aforementioned system., Comment: 6 pages and 3 figures

In this paper, we propose a novel generative model named Stacked Generative Adversarial Networks (SGAN), which is trained to invert the hierarchical representations of a bottom-up discriminative network. Our model consists of a top-down stack of GANs, each learned to generate lower-level representations conditioned on higher-level representations. A representation discriminator is introduced at each feature hierarchy to encourage the representation manifold of the generator to align with that of the bottom-up discriminative network, leveraging the powerful discriminative representations to guide the generative model. In addition, we introduce a conditional loss that encourages the use of conditional information from the layer above, and a novel entropy loss that maximizes a variational lower bound on the conditional entropy of generator outputs. We first train each stack independently, and then train the whole model end-to-end. Unlike the original GAN that uses a single noise vector to represent all the variations, our SGAN decomposes variations into multiple levels and gradually resolves uncertainties in the top-down generative process. Based on visual inspection, Inception scores and visual Turing test, we demonstrate that SGAN is able to generate images of much higher quality than GANs without stacking., Comment: CVPR 2017, camera-ready version

In Cognitive Radio (CR), in order to avoid interference in the Primary Users (PU), some subcarriers need to be deactivated. In systems based on Multicarrier Code Division Multiple Access (MC-CDMA), this causes losing orthogonality among different spreading codes, leading to poor Bit Error Rate (BER) performance. The performance of such system can be improved by using Generalized Hadamard Codes (GHC) instead of conventional Hadamard codes which avoids the loss of orthogonality. This is due to the fact that unlike conventional Hadamard codes, GHC are conjectured to exist for any arbitrary length. In this paper, we propose using a novel spreading code, namely, GHC for synchronous MC-CDMA in CR networks. The new spreading codes help the CR systems maintaining the data rate while improving the performance by eliminating the orthogonality loss. Finally, the performance of the MCCDMA system using GHC is evaluated and it is shown that the proposed system outperform the system with conventional Hadamard codes.

Formulas presented for the calculation of ∑ j=1 n jk (n, k ∈ N do not have a closed form; they are in the form of recursive or complex formulas. Here an attempt is made to present a simple formula in which it is only necessary to compute the numerical coefficients in a recursive form, and the coefficients in turn follow a simple pattern (almost similar to Pascal's Triangle). Although the pattern for calculating numerical coefficients based on forming a table is easy, non-recursive formulas are presented to determine the numerical coefficients.

This study aims to reduce energy consumption by application of geothermal heat pumps in residential buildings and reduction of Greenhouse Gases (GHGs) emissions under Clean Development Mechanism (CDM) project. In this approach, the required thermal load of a typical four-floor 12-units residential building located in Tehran city has been considered and calculated separately based on the actual operational data. According to the thermal properties of soil and the annual average temperature of the area, the appropriate geothermal heat pump system has been taken into consideration. Subsequently, three scenarios based on transaction of Certified Emission Reductions (CERs) as Primary, Secondary and Unilateral types of CDM projects were created considering the primary costs of purchase and installment of geothermal heat pump system and its electricity consumption. Technical, economical and environmental feasibility study of this project has been assessed through using Proform software in three different scenarios based on global carbon credit market. The results show that in the optimum scenario in case of replacing the boiler system with vertical geothermal heat pump system in the residential building, could conserve 67,000 GJ of natural gas during the project implementation period and 3,759 tons of COR2R equivalent emissions would be reduced. Results demonstrate also the favorable economic and environmental impacts that can be achieved by CDM.