Search results for: Ziba Hamidi

Authors: Zh. Saffari, A. Naeimi, M. S. Ekrami-Kakhki, F. Hamidi

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Fe3O4 is one of the important magnetic oxides with spinel structure; it has exhibited unique electric and magnetic properties based on the electron transfer between Fe2+ and Fe3+ in the octahedral sites. Fe3O4 has received considerable attention in various areas such as cancer therapy, drug targeting, enzyme immobilization catalysis, magnetic cell separation, magnetic refrigeration systems and super-paramagnetic materials Fe3O4–TiO2 nanostructures were synthesized by simple, effective and new co-precipitation method assisted by ultrasonic reaction at room temperatures with organic surfactant. The effect of various parameters such as temperature, time, and power on the size and morphology of the product was investigated. Alternating gradient force magnetometer shows that Fe3O4 nanoparticles exhibit super-paramagnetic behaviour at room temperature. For preparation of nanocomposite, 1 g of TiO2 nanostructures were dispersed in 100 mL of ethanol. 0.25 g of Fe(NO3)2 and 2 mL of octanoic acid was added to the solution as a surfactant. Then, NaOH solution (1.5 M) was slowly added into the solution until the pH of the mixture was 7–8. After complete precipitation, the solution placed under the ultrasonic irradiation for 30 min. The product was centrifuged, washed with distilled water and dried in an oven at 100 °C for 3 h. The resulting red powder was calcinated at 800 °C for 3 h to remove any organic residue. The photocatalytic behaviour of Fe3O4–TiO2 nanoparticles was evaluated using the degradation of a Methyl Violet (MV) aqueous solution under ultraviolet light irradiation. As time increased, more and more MV was adsorbed on the nanoparticles catalyst, until the absorption peak vanish. The MV concentration decreased rapidly with increasing UV-irradiation time

Keywords: magnetic, methyl violet, nanocomposite, photocatalytic

Procedia PDF Downloads 233

Authors: Ahmad Hamidi Mohamed, Jamaluddin Othman, Mashitah Suid, Mohd Zaim Mohd Shukri

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Floods are considered an annual natural disaster in Kelantan. However, the record-setting flood of 2014 was a 'tsunami-like disaster'. A study has been conducted with the objectives to assess the economic impact of the flood to the resident of Dabong area in Kelantan Darul Naim, Malaysia. This area was selected due to the severity during the flood. The impacts of flood on local people were done by conducting structured interviews with the use of questionnaires. The questionnaire was intended to acquire information on losses faced by Dabong residence. Questionnaires covered various areas of inconveniences suffered with respect to health effects, including illnesses suffered, their intensities, duration and their associated costs. Loss of productivity and quality of life was also assessed. Inquiries were made to Government agencies to obtain relevant statistical data regarding the loss due to the flood tragedy. The data collected by giving formal request to the governmental agencies and formal meetings were done. From the study a staggering amount of losses were calculated. This figure comes from losses of property, Farmers/Agriculture, Traders/Business, Health, Insurance and Governmental losses. Flood brings hardship to the people of Dabong and these losses of home will cause inconveniences to the society. The huge amount of economic loss extracted from this study shows that federal and state government of Kelantan need to find out the cause of the major flood in 2014. Fast and effective measures have to be planned and implemented in flood prone area to prevent same tragedy happens in the future.

Keywords: economic impact, flood tragedy, Malaysia, property losses

Procedia PDF Downloads 239

Authors: Mohammed Ahmed, Ziba Nazarlou

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Mild steels have a limited alloying content which makes them vulnerable to excessive corrosion rates in the harsh medium. To overcome this issue, some protective coatings are used to prevent corrosion on the steel surface. The use of specialized coatings, mainly organic coatings (such as epoxies, polyurethanes, and acrylics) and inorganic coatings (such as Polysiloxanes) is the most common method of mitigating corrosion of carbon steel. Incorporating the benefits of organic and inorganic hybrid (OIH) compounds for the designing of hybrid protective coatings is still challenging for industrial applications. There are advantages of inorganic coatings have, but purely inorganic siloxane-based coatings are difficult to use on industrial applications unless they are used at extremely low thicknesses (< 1-2 microns). Hence, most industrial applications try to have a combination of Polysiloxanes with organic compounds.  A hybrid coating possesses an organic section, which transports flexibility and impact resistance, and an inorganic section, which usually helps in the decreasing of porosity and increasing thermal stability and hardness. A number of polymers including polyethylene glycol and polyvinyl pyrrolidone have been reported to inhibit the corrosion mild steel in acidic media. However, reports on the effect of polyethylene oxide (PEO) or its blends on corrosion inhibition of metals is very scarce. Different composition of OIH coatings was synthesized by using silica sol-gel, epoxy, and PEO. The effect of different coating types on the corrosion behavior of carbon steel in harsh solution has been studied by weight loss and electrochemical measurements using Gamry 1000 Interface Potentiostat. Coating structures were investigated by SEM. İt revealed a considerable reduction in corrosion rate for coated sample. Based on these results, OIH coating prepared by epoxy-silica sol gel-PEO and epoxy-silica sol-gel exhibit had a %99.5 and %98 reduction of (Corrosion rate) CR compares to baseline. Cathodic Tafel constant (βc) shows that coatings change both Tafel constants but had more effect on the cathodic process. The evolution of the Potentiostatic scan with time displays stability in potential, some of them in a high value while the other in a low value which can be attributed to the formation of an oxide film covering substrate surface. The coated samples with the group of epoxy coating have a lower potential along with the time test, while the silica group shows higher in potential with respect to time.

Keywords: electrostatic, hybrid coating, corrosion tests, silica sol gel

Procedia PDF Downloads 90

Authors: Zahra Hamidi

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Promoting cycling, as an affordable environmentally friendly mode of transport to replace private car use has been central to sustainable transport policies. Cycling is faster than walking and combined with public transport has the potential to extend the opportunities that people can access. In other words, cycling, besides direct positive health impacts, can improve people mobility and ultimately their quality of life. Transport literature well supports the close relationship between mobility, quality of life, and, well being. At the same time inequity in the distribution of access and mobility has been associated with the key aspects of injustice and social exclusion. The pattern of social exclusion and inequality in access are also often related to population characteristics such as age, gender, income, health, and ethnic background. Therefore, while investing in transport infrastructure it is important to consider the equity of provided access for different population groups. This paper proposes a method to evaluate the equity of cycling in a city from Rawls egalitarian perspective. Since this perspective is concerned with the difference between individuals and social groups, this method combines accessibility measures and Theil index of inequality that allows capturing the inequalities ‘within’ and ‘between’ groups. The paper specifically focuses on two population characteristics as gender and ethnic background. Following Rawls equity principles, this paper measures accessibility by bikes to a selection of urban activities that can be linked to the concept of the social primary goods. Moreover, as growing number of cities around the world have launched bike-sharing systems (BSS) this paper incorporates both private and public bikes networks in the estimation of accessibility levels. Additionally, the typology of bike lanes (separated from or shared with roads), the presence of a bike sharing system in the network, as well as bike facilities (e.g. parking racks) have been included in the developed accessibility measures. Application of this proposed method to a real case study, the city of Malmö, Sweden, shows its effectiveness and efficiency. Although the accessibility levels were estimated only based on gender and ethnic background characteristics of the population, the author suggests that the analysis can be applied to other contexts and further developed using other properties, such as age, income, or health.

Keywords: accessibility, cycling, equity, gender

Procedia PDF Downloads 376

Authors: Homeira Asadi Kavan, Seyed Nasrollah Sajjadi, Mehrzade Hamidi, Hossein Rajabi, Mahdi Bigdely

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Positioning strategies of a sports brand can create a unique impression in the minds of the fans, sponsors, and other stakeholders. In order to influence potential customer's perception in an effective and positive way, a brands positioning strategy must be unique, credible, and relevant. Many sports clubs in Iran have been struggling to implement and achieve brand positioning accomplishments, due to different reasons such as lack of experience, scarcity of experts in the sports branding, and lack of related researches in this field. This study will provide a comprehensive theoretical framework and action plan for sport managers and marketers to design and implement effective brand positioning and to enable them to be distinguishable from competing brands and sports clubs. The study instrument is interviews with sports marketing and brand experts who have been working in this industry for a minimum of 20 years. Qualitative data analysis was performed using Atlast.ti text mining software version 7 and Open, axial and selective coding were employed to uncover and systematically analyze important and complex phenomena and elements. The findings show 199 effective elements in positioning strategies in Iran Professional Soccer League. These elements are categorized into 23 concepts and sub-categories as follows: Structural prerequisites, Strategic management prerequisites, Commercial prerequisites, Major external prerequisites, Brand personality, Club symbols, Emotional aspects, Event aspects, Fans’ strategies, Marketing information strategies, Marketing management strategies, Empowerment strategies, Executive management strategies, League context, Fans’ background, Market context, Club’s organizational context, Support context, Major contexts, Political-Legal elements, Economic factors, Social factors, and Technological factors. Eventually, the study model was developed by 6 main dimensions of Causal prerequisites, Axial Phenomenon (brand position), Strategies, Context Factors, Interfering Factors, and Consequences. Based on the findings, practical recommendations and strategies are suggested that can help club managers and marketers in developing and improving their respective sport clubs, brand positioning, and activities.

Keywords: brand positioning, soccer club, sport marketing, Iran professional soccer league, brand strategy

Procedia PDF Downloads 106

Authors: Shayan Mohajer Hamidi

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Federated learning has emerged as a promising approach for distributed model training while preserving data privacy. However, the challenges of communication overhead, limited network resources, and slow convergence hinder its widespread adoption. On the other hand, knowledge distillation has shown great potential in compressing large models into smaller ones without significant loss in performance. In this paper, we propose an innovative framework that combines federated learning and knowledge distillation to address these challenges and enhance the efficiency of distributed learning. Our approach, called Federated Knowledge Distillation (FKD), enables multiple clients in a federated learning setting to collaboratively distill knowledge from a teacher model. By leveraging the collaborative nature of federated learning, FKD aims to improve model compression while maintaining privacy. The proposed framework utilizes a coded teacher model that acts as a reference for distilling knowledge to the client models. To demonstrate the effectiveness of FKD, we conduct extensive experiments on various datasets and models. We compare FKD with baseline federated learning methods and standalone knowledge distillation techniques. The results show that FKD achieves superior model compression, faster convergence, and improved performance compared to traditional federated learning approaches. Furthermore, FKD effectively preserves privacy by ensuring that sensitive data remains on the client devices and only distilled knowledge is shared during the training process. In our experiments, we explore different knowledge transfer methods within the FKD framework, including Fine-Tuning (FT), FitNet, Correlation Congruence (CC), Similarity-Preserving (SP), and Relational Knowledge Distillation (RKD). We analyze the impact of these methods on model compression and convergence speed, shedding light on the trade-offs between size reduction and performance. Moreover, we address the challenges of communication efficiency and network resource utilization in federated learning by leveraging the knowledge distillation process. FKD reduces the amount of data transmitted across the network, minimizing communication overhead and improving resource utilization. This makes FKD particularly suitable for resource-constrained environments such as edge computing and IoT devices. The proposed FKD framework opens up new avenues for collaborative and privacy-preserving distributed learning. By combining the strengths of federated learning and knowledge distillation, it offers an efficient solution for model compression and convergence speed enhancement. Future research can explore further extensions and optimizations of FKD, as well as its applications in domains such as healthcare, finance, and smart cities, where privacy and distributed learning are of paramount importance.

Keywords: federated learning, knowledge distillation, knowledge transfer, deep learning

Procedia PDF Downloads 43

Authors: Shayan Mohajer Hamidi

Abstract:

Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

Procedia PDF Downloads 46