The fundamental frequency plays a significant part in understanding and perceiving the pitch of a sound. The pitch is a fundamental attribute employed in numerous speech-related works. For fundamental frequency extrac...The fundamental frequency plays a significant part in understanding and perceiving the pitch of a sound. The pitch is a fundamental attribute employed in numerous speech-related works. For fundamental frequency extraction, several algorithms have been developed which one to use relies on the signal’s characteristics and the surrounding noise. Thus, the algorithm’s noise resistance becomes more critical than ever for precise fundamental frequency estimation. Nonetheless, numerous state-of-the-art algorithms face struggles in achieving satisfying outcomes when confronted with speech recordings that are noisy with low signal-to-noise ratio (SNR) values. Also, most of the recent techniques utilize different frame lengths for pitch extraction. From this point of view, This research considers different frame lengths on male and female speech signals for fundamental frequency extraction. Also, analyze the frame length dependency on the speech signal analytically to understand which frame length is more suitable and effective for male and female speech signals specifically. For the validation of our idea, we have utilized the conventional autocorrelation function (ACF), and state-of-the-art method BaNa. This study puts out a potent idea that will work better for speech processing applications in noisy speech. From experimental results, the proposed idea represents which frame length is more appropriate for male and female speech signals in noisy environments.展开更多
This research project investigates the current status of water supply, sanitation, and hygiene practices in Munshiganj District, Bangladesh. Data collection involved a structured questionnaire and a reconnaissance sur...This research project investigates the current status of water supply, sanitation, and hygiene practices in Munshiganj District, Bangladesh. Data collection involved a structured questionnaire and a reconnaissance survey. Findings reveal that 30% of individuals rely on surface water (hand-tube wells, rivers, and ponds), prioritized as canal > river > pond, while 70% depend on groundwater (subterranean electric motor, deep tube-well). Drinking water is generally sufficient, with 95% reporting adequacy throughout the year. About 45% use hand tube-well water, 28% use deep tube-well water, and 11% use supply tap water for various purposes. Bathing trends include underground water through electric motor > pond > hand tube-well water > river, while for cooking, the order is underground water through electric motor > pond > hand tube-well water > river. Toilet water supply ranks as supply tap water > hand tube-well water > deep tube-well water. Although sanitation awareness is high, some lack knowledge of good hygiene practices. After defecating, handwashing methods include soap, ash, soil, or water. Children’s waste disposal varies, with some discarding it in open areas. Approximately 40% suffer from diseases like Diarrhoea due to unsafe water, primarily affecting children and elders. Training exists, but a significant portion lacks sanitation education. Dry skin or exposure to cold water may cause temporary irritation. Local government involvement in sanitation efforts is less active compared to non-governmental organizations. Results emphasize the need to enhance community awareness of safe water supplies and sanitation practices. .展开更多
The concept of community resilience in the contexts of climate change and disasters draws increasing attention and interest from practitioners and researchers in recent development discourse. This paper provides a cri...The concept of community resilience in the contexts of climate change and disasters draws increasing attention and interest from practitioners and researchers in recent development discourse. This paper provides a critical review of six selected frameworks of community resilience building operationalized in Bangladesh over the span of years. In other words, this study aims to contribute to the understanding of resilience through a systematic analysis of the dimensions and indicators of community resilience frameworks. The analysis shows that comprehensive and effective community resilience frameworks should incorporate the missing components linked to fundamental elements of good governance, economic growth, environmental sustainability, social transformation, and capacity development. The paper concludes by highlighting a few other areas of grave concern that need more appropriate attention, considering the severe threats posed by climate change and natural disasters in line with sustainable development goals. Finally, this study recommends further research regarding the effectiveness of these frameworks in different climatic and disaster contexts that can lead the concept into a new dimension of community resilience and sustainability.展开更多
Spam emails pose a threat to individuals. The proliferation of spam emails daily has rendered traditional machine learning and deep learning methods for screening them ineffective and inefficient. In our research, we ...Spam emails pose a threat to individuals. The proliferation of spam emails daily has rendered traditional machine learning and deep learning methods for screening them ineffective and inefficient. In our research, we employ deep neural networks like RNN, LSTM, and GRU, incorporating attention mechanisms such as Bahdanua, scaled dot product (SDP), and Luong scaled dot product self-attention for spam email filtering. We evaluate our approach on various datasets, including Trec spam, Enron spam emails, SMS spam collections, and the Ling spam dataset, which constitutes a substantial custom dataset. All these datasets are publicly available. For the Enron dataset, we attain an accuracy of 99.97% using LSTM with SDP self-attention. Our custom dataset exhibits the highest accuracy of 99.01% when employing GRU with SDP self-attention. The SMS spam collection dataset yields a peak accuracy of 99.61% with LSTM and SDP attention. Using the GRU (Gated Recurrent Unit) alongside Luong and SDP (Structured Self-Attention) attention mechanisms, the peak accuracy of 99.89% in the Ling spam dataset. For the Trec spam dataset, the most accurate results are achieved using Luong attention LSTM, with an accuracy rate of 99.01%. Our performance analyses consistently indicate that employing the scaled dot product attention mechanism in conjunction with gated recurrent neural networks (GRU) delivers the most effective results. In summary, our research underscores the efficacy of employing advanced deep learning techniques and attention mechanisms for spam email filtering, with remarkable accuracy across multiple datasets. This approach presents a promising solution to the ever-growing problem of spam emails.展开更多
Blockchain has proven to be an emerging technology in the digital world, changing the way everyone thinks about data security and bringing efficiency to several industries. It has already been applied to a wide range ...Blockchain has proven to be an emerging technology in the digital world, changing the way everyone thinks about data security and bringing efficiency to several industries. It has already been applied to a wide range of applications, from financial services and supply chain management to voting systems and identity verification. An organization must verify its candidates before selecting them. Choosing an unqualified candidate can ruin an organization’s reputation. In this paper, a blockchain-based academic certificate authentication system will be used to ensure authenticity and make the assertion of the decentralized system secure. However, the system will generate, authenticate and make corrections on academic certificates. Ultimately, some blockchain-based authentication systems already exist, they can’t correct any errors that occur during generation. A blockchain-based certificate authentication system was built using blockchain technology. Where admin could generate, authenticate and correct the certificate if necessary. The admin can also check how many times a certificate has been modified. Other users can only check the authenticity of the certificates. We’re using two blockchains to enable corrections. Blockchain technology can successfully implement a certificate authentication system. This system will eliminate doubts about the authenticity of certificates, provide fast responses, and ensure reliable and secure storage. The proposed system will help in many ways, such as providing a user-friendly university admission, and smooth job hiring process, etc. In conclusion, our proposed system can permanently eradicate certificate forgeries and create and promote trust in society.展开更多
Zirconia toughened alumina (ZTA) ceramics are very promising materials for structural and biomedical applications due to their high hardness, fracture toughness, strength, corrosion and abrasion resistance and excelle...Zirconia toughened alumina (ZTA) ceramics are very promising materials for structural and biomedical applications due to their high hardness, fracture toughness, strength, corrosion and abrasion resistance and excellent biocompatibility. The effect of unstabilized ZrO<sub>2</sub> on the density, fracture toughness, microhardness, flexural strength and microstructure of some Zirconia-toughened alumina (ZTA) samples was investigated in this work. The volume percentage of unstabilized ZrO<sub>2</sub> was varied from 0% - 20% whereas sintering time and sintering temperature were kept constant at 2 hours and 1580°C. The samples were fabricated from nanometer-sized (<em>α</em>-Al<sub>2</sub>O<sub>3</sub>: 150 nm, monoclinic ZrO<sub>2</sub>: 30 - 60 nm) powder raw materials by the conventional mechanical mixing process. Using a small amount of sintering aid (0.2 wt% MgO) almost 99.2% of theoretical density, 8.54 MPam<sup>?</sup> fracture toughness, 17.35 GPa Vickers microhardness and 495.67 MPa flexural strength were found. It was observed that the maximum flexural strength and fracture toughness was obtained for 10 vol% monoclinic ZrO<sub>2</sub> but maximum Vickers microhardness was achieved for 5 vol% ZrO<sub>2</sub> although the maximum density was found for 20 vol% ZrO<sub>2</sub>. It is assumed that this was happened due to addition of denser component, phase transformation of monoclinic ZrO<sub>2</sub> and the changes of grain size of α-Al<sub>2</sub>O<sub>3</sub> and ZrO<sub>2</sub>.展开更多
文摘The fundamental frequency plays a significant part in understanding and perceiving the pitch of a sound. The pitch is a fundamental attribute employed in numerous speech-related works. For fundamental frequency extraction, several algorithms have been developed which one to use relies on the signal’s characteristics and the surrounding noise. Thus, the algorithm’s noise resistance becomes more critical than ever for precise fundamental frequency estimation. Nonetheless, numerous state-of-the-art algorithms face struggles in achieving satisfying outcomes when confronted with speech recordings that are noisy with low signal-to-noise ratio (SNR) values. Also, most of the recent techniques utilize different frame lengths for pitch extraction. From this point of view, This research considers different frame lengths on male and female speech signals for fundamental frequency extraction. Also, analyze the frame length dependency on the speech signal analytically to understand which frame length is more suitable and effective for male and female speech signals specifically. For the validation of our idea, we have utilized the conventional autocorrelation function (ACF), and state-of-the-art method BaNa. This study puts out a potent idea that will work better for speech processing applications in noisy speech. From experimental results, the proposed idea represents which frame length is more appropriate for male and female speech signals in noisy environments.
文摘This research project investigates the current status of water supply, sanitation, and hygiene practices in Munshiganj District, Bangladesh. Data collection involved a structured questionnaire and a reconnaissance survey. Findings reveal that 30% of individuals rely on surface water (hand-tube wells, rivers, and ponds), prioritized as canal > river > pond, while 70% depend on groundwater (subterranean electric motor, deep tube-well). Drinking water is generally sufficient, with 95% reporting adequacy throughout the year. About 45% use hand tube-well water, 28% use deep tube-well water, and 11% use supply tap water for various purposes. Bathing trends include underground water through electric motor > pond > hand tube-well water > river, while for cooking, the order is underground water through electric motor > pond > hand tube-well water > river. Toilet water supply ranks as supply tap water > hand tube-well water > deep tube-well water. Although sanitation awareness is high, some lack knowledge of good hygiene practices. After defecating, handwashing methods include soap, ash, soil, or water. Children’s waste disposal varies, with some discarding it in open areas. Approximately 40% suffer from diseases like Diarrhoea due to unsafe water, primarily affecting children and elders. Training exists, but a significant portion lacks sanitation education. Dry skin or exposure to cold water may cause temporary irritation. Local government involvement in sanitation efforts is less active compared to non-governmental organizations. Results emphasize the need to enhance community awareness of safe water supplies and sanitation practices. .
文摘The concept of community resilience in the contexts of climate change and disasters draws increasing attention and interest from practitioners and researchers in recent development discourse. This paper provides a critical review of six selected frameworks of community resilience building operationalized in Bangladesh over the span of years. In other words, this study aims to contribute to the understanding of resilience through a systematic analysis of the dimensions and indicators of community resilience frameworks. The analysis shows that comprehensive and effective community resilience frameworks should incorporate the missing components linked to fundamental elements of good governance, economic growth, environmental sustainability, social transformation, and capacity development. The paper concludes by highlighting a few other areas of grave concern that need more appropriate attention, considering the severe threats posed by climate change and natural disasters in line with sustainable development goals. Finally, this study recommends further research regarding the effectiveness of these frameworks in different climatic and disaster contexts that can lead the concept into a new dimension of community resilience and sustainability.
文摘Spam emails pose a threat to individuals. The proliferation of spam emails daily has rendered traditional machine learning and deep learning methods for screening them ineffective and inefficient. In our research, we employ deep neural networks like RNN, LSTM, and GRU, incorporating attention mechanisms such as Bahdanua, scaled dot product (SDP), and Luong scaled dot product self-attention for spam email filtering. We evaluate our approach on various datasets, including Trec spam, Enron spam emails, SMS spam collections, and the Ling spam dataset, which constitutes a substantial custom dataset. All these datasets are publicly available. For the Enron dataset, we attain an accuracy of 99.97% using LSTM with SDP self-attention. Our custom dataset exhibits the highest accuracy of 99.01% when employing GRU with SDP self-attention. The SMS spam collection dataset yields a peak accuracy of 99.61% with LSTM and SDP attention. Using the GRU (Gated Recurrent Unit) alongside Luong and SDP (Structured Self-Attention) attention mechanisms, the peak accuracy of 99.89% in the Ling spam dataset. For the Trec spam dataset, the most accurate results are achieved using Luong attention LSTM, with an accuracy rate of 99.01%. Our performance analyses consistently indicate that employing the scaled dot product attention mechanism in conjunction with gated recurrent neural networks (GRU) delivers the most effective results. In summary, our research underscores the efficacy of employing advanced deep learning techniques and attention mechanisms for spam email filtering, with remarkable accuracy across multiple datasets. This approach presents a promising solution to the ever-growing problem of spam emails.
文摘Blockchain has proven to be an emerging technology in the digital world, changing the way everyone thinks about data security and bringing efficiency to several industries. It has already been applied to a wide range of applications, from financial services and supply chain management to voting systems and identity verification. An organization must verify its candidates before selecting them. Choosing an unqualified candidate can ruin an organization’s reputation. In this paper, a blockchain-based academic certificate authentication system will be used to ensure authenticity and make the assertion of the decentralized system secure. However, the system will generate, authenticate and make corrections on academic certificates. Ultimately, some blockchain-based authentication systems already exist, they can’t correct any errors that occur during generation. A blockchain-based certificate authentication system was built using blockchain technology. Where admin could generate, authenticate and correct the certificate if necessary. The admin can also check how many times a certificate has been modified. Other users can only check the authenticity of the certificates. We’re using two blockchains to enable corrections. Blockchain technology can successfully implement a certificate authentication system. This system will eliminate doubts about the authenticity of certificates, provide fast responses, and ensure reliable and secure storage. The proposed system will help in many ways, such as providing a user-friendly university admission, and smooth job hiring process, etc. In conclusion, our proposed system can permanently eradicate certificate forgeries and create and promote trust in society.
文摘Zirconia toughened alumina (ZTA) ceramics are very promising materials for structural and biomedical applications due to their high hardness, fracture toughness, strength, corrosion and abrasion resistance and excellent biocompatibility. The effect of unstabilized ZrO<sub>2</sub> on the density, fracture toughness, microhardness, flexural strength and microstructure of some Zirconia-toughened alumina (ZTA) samples was investigated in this work. The volume percentage of unstabilized ZrO<sub>2</sub> was varied from 0% - 20% whereas sintering time and sintering temperature were kept constant at 2 hours and 1580°C. The samples were fabricated from nanometer-sized (<em>α</em>-Al<sub>2</sub>O<sub>3</sub>: 150 nm, monoclinic ZrO<sub>2</sub>: 30 - 60 nm) powder raw materials by the conventional mechanical mixing process. Using a small amount of sintering aid (0.2 wt% MgO) almost 99.2% of theoretical density, 8.54 MPam<sup>?</sup> fracture toughness, 17.35 GPa Vickers microhardness and 495.67 MPa flexural strength were found. It was observed that the maximum flexural strength and fracture toughness was obtained for 10 vol% monoclinic ZrO<sub>2</sub> but maximum Vickers microhardness was achieved for 5 vol% ZrO<sub>2</sub> although the maximum density was found for 20 vol% ZrO<sub>2</sub>. It is assumed that this was happened due to addition of denser component, phase transformation of monoclinic ZrO<sub>2</sub> and the changes of grain size of α-Al<sub>2</sub>O<sub>3</sub> and ZrO<sub>2</sub>.
