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Background Smart nursing homes (SNHs) integrate advanced technologies, including IoT, digital health, big data, AI, and cloud computing to optimise remote clinical services, monitor abnormal events, enhance decision-making, and support daily activities for older residents, ensuring overall well-being in a safe and cost-effective environment. This study developed and validated a 24-item Expectation and Acceptability of Smart Nursing Homes Questionnaire (EASNH-Q), and examined the levels of expectations and acceptability of SNHs and associated factors among older adults in China. Methods This was an exploratory sequential mixed methods study, where the qualitative case study was conducted in Hainan and Dalian, while the survey was conducted in Xi’an, Nanjing, Shenyang, and Xiamen. The validation of EASNH-Q also included exploratory and confirmatory factor analyses. Multinomial logistic regression analysis was used to estimate the determinants of expectations and acceptability of SNHs. Results The newly developed EASNH-Q uses a Likert Scale ranging from 1 (strongly disagree) to 5 (strongly agree), and underwent validation and refinement from 49 items to the final 24 items. The content validity indices for relevance, comprehensibility, and comprehensiveness were all above 0.95. The expectations and acceptability of SNHs exhibited a strong correlation (r = 0.85, p < 0.01), and good test-retest reliability for expectation (0.90) and acceptability (0.81). The highest tertile of expectations (X2=28.89, p < 0.001) and acceptability (X2=25.64, p < 0.001) towards SNHs were significantly associated with the willingness to relocate to such facilities. Older adults with self-efficacy in applying smart technologies (OR: 28.0) and those expressing a willingness to move to a nursing home (OR: 3.0) were more likely to have the highest tertile of expectations compared to those in the lowest tertile. Similarly, older adults with self-efficacy in applying smart technologies were more li

Background Smart nursing homes (SNHs) integrate advanced technologies, including IoT, digital health, big data, AI, and cloud computing to optimise remote clinical services, monitor abnormal events, enhance decision-making, and support daily activities for older residents, ensuring overall well-being in a safe and cost-effective environment. This study developed and validated a 24-item Expectation and Acceptability of Smart Nursing Homes Questionnaire (EASNH-Q), and examined the levels of expectations and acceptability of SNHs and associated factors among older adults in China. Methods This was an exploratory sequential mixed methods study, where the qualitative case study was conducted in Hainan and Dalian, while the survey was conducted in Xi’an, Nanjing, Shenyang, and Xiamen. The validation of EASNH-Q also included exploratory and confirmatory factor analyses. Multinomial logistic regression analysis was used to estimate the determinants of expectations and acceptability of SNHs. Results The newly developed EASNH-Q uses a Likert Scale ranging from 1 (strongly disagree) to 5 (strongly agree), and underwent validation and refinement from 49 items to the final 24 items. The content validity indices for relevance, comprehensibility, and comprehensiveness were all above 0.95. The expectations and acceptability of SNHs exhibited a strong correlation (r = 0.85, p < 0.01), and good test-retest reliability for expectation (0.90) and acceptability (0.81). The highest tertile of expectations (X2=28.89, p < 0.001) and acceptability (X2=25.64, p < 0.001) towards SNHs were significantly associated with the willingness to relocate to such facilities. Older adults with self-efficacy in applying smart technologies (OR: 28.0) and those expressing a willingness to move to a nursing home (OR: 3.0) were more likely to have the highest tertile of expectations compared to those in the lowest tertile. Similarly, older adults with self-efficacy in applying smart technologies were more li

Rapid transportation development may be welcomed by many, but older adults might find it difficult to keep up with their transportation uses and remain active. This study reviewed published articles on the travel behavior of older adults in Malaysia and associated transportation determinants to explore how sustainable the transportation system is for this vulnerable cohort. The authors searched four databases: PubMed, Scopus, ProQuest, and EBSCOhost. Inclusion criteria were older respondents, living in a community in Malaysia, addressing any travel behavior characteristics, and being written in English. Review papers, letters, book citations, comments, editorials, and experimental and animal studies are excluded from this study. A total of seven studies were included in this review extending from 2007 to 2020. The result showed that the transportation use of older adults has shifted from relying on public transport to driving their own vehicles to move around. According to the findings of this study, besides personal and health factors, the transport use of older adults is affected mainly by cost, public transport availability, road traffic and safety, the complexity of the transportation system, distance to public transit, availability of parking space, as well as road conditions and signage. It is concluded that an effective strategy to improve the transportation system is needed to prevent the unmet travel needs of older adults in Malaysia.

A dielectric spectroscopy method was applied to determine major fatty acids composition in vegetable oils. Dielectric constants of vegetable oils were measured in the frequency range of 5–30 MHz. After data pre-treatment, prediction models were constructed using partial least squares (PLS) regression between dielectric spectral values and the fatty acids compositions measured by gas chromatography. Generally, the root means square error of validation (RMSECV) was less than 11.23% in the prediction of individual fatty acids. The determination coefficient (R2) between predicted and measured oleic, linoleic, mono-unsaturated, and poly-unsaturated fatty acids were 0.84, 0.77, 0.84, and 0.84, respectively. These results indicated that dielectric spectroscopy coupled with PLS regression could be a promising method for predicting major fatty acid composition in vegetable oils and has the potential to be used for in-situ monitoring systems of daily consumption of dietary fatty acids.

Due to the limitations of battery life and capacity, power supply has been the bottleneck for scaling of a wireless sensor network in thousands or millions of nodes. RF energy harvester (RFEH) is a promising solution to power up sensors and wireless devices due to increasing accessibility of RF energy sources, better silicon integration of the harvester circuit and compatibility with wireless networks. One of the significant limitations of RF energy harvester is low power efficiency rectifier where the main function of the micropower rectifier is to convert RF energy into DC energy. To achieve higher power conversion energy (PCE), this paper presents a five-stage charge pump rectifier, with implementation of diode-connected MOS transistors and an auxiliary circuit to produce compensation voltage to the charge pump to achieve higher efficiency over a wide input range. This work is designed and implemented using 130nm CMOS technology and achieved a wide input power range of 15 dBm with efficiency higher than 20%; and at -21 dBm sensitivity for 1V output is achieved while driving 1 MΩ load at 920MHz.

Rapid transportation development may be welcomed by many, but older adults might find it difficult to keep up with their transportation uses and remain active. This study reviewed published articles on the travel behavior of older adults in Malaysia and associated transportation determinants to explore how sustainable the transportation system is for this vulnerable cohort. The authors searched four databases: PubMed, Scopus, ProQuest, and EBSCOhost. Inclusion criteria were older respondents, living in a community in Malaysia, addressing any travel behavior characteristics, and being written in English. Review papers, letters, book citations, comments, editorials, and experimental and animal studies are excluded from this study. A total of seven studies were included in this review extending from 2007 to 2020. The result showed that the transportation use of older adults has shifted from relying on public transport to driving their own vehicles to move around. According to the findings of this study, besides personal and health factors, the transport use of older adults is affected mainly by cost, public transport availability, road traffic and safety, the complexity of the transportation system, distance to public transit, availability of parking space, as well as road conditions and signage. It is concluded that an effective strategy to improve the transportation system is needed to prevent the unmet travel needs of older adults in Malaysia.

A dielectric spectroscopy method was applied to determine major fatty acids composition in vegetable oils. Dielectric constants of vegetable oils were measured in the frequency range of 5–30 MHz. After data pre-treatment, prediction models were constructed using partial least squares (PLS) regression between dielectric spectral values and the fatty acids compositions measured by gas chromatography. Generally, the root means square error of validation (RMSECV) was less than 11.23% in the prediction of individual fatty acids. The determination coefficient (R2) between predicted and measured oleic, linoleic, mono-unsaturated, and poly-unsaturated fatty acids were 0.84, 0.77, 0.84, and 0.84, respectively. These results indicated that dielectric spectroscopy coupled with PLS regression could be a promising method for predicting major fatty acid composition in vegetable oils and has the potential to be used for in-situ monitoring systems of daily consumption of dietary fatty acids.

Due to the limitations of battery life and capacity, power supply has been the bottleneck for scaling of a wireless sensor network in thousands or millions of nodes. RF energy harvester (RFEH) is a promising solution to power up sensors and wireless devices due to increasing accessibility of RF energy sources, better silicon integration of the harvester circuit and compatibility with wireless networks. One of the significant limitations of RF energy harvester is low power efficiency rectifier where the main function of the micropower rectifier is to convert RF energy into DC energy. To achieve higher power conversion energy (PCE), this paper presents a five-stage charge pump rectifier, with implementation of diode-connected MOS transistors and an auxiliary circuit to produce compensation voltage to the charge pump to achieve higher efficiency over a wide input range. This work is designed and implemented using 130nm CMOS technology and achieved a wide input power range of 15 dBm with efficiency higher than 20%; and at -21 dBm sensitivity for 1V output is achieved while driving 1 MΩ load at 920MHz.

Background: Recent research on photon detection has led to the introduction of a silicone photomultiplier (SiPM) that operates at a low voltage and is insensitive to magnetic fields. Objective: This work aims to model a scintillation camera with a SiPM sensor and to evaluate the camera reconstructed images from gamma ray projection data. Material and Methods: The type of study in this research is experimental work and analytical. The scintillation camera, modelled from an SiPM sensor array SL4-30035, coupled with a scintillation material Caesium Iodide doped with Thallium (CsI(Tl)), is used in the experimental part. The performance of the camera was evaluated from reconstructed images by a back-projection technique of a radioactive source Caesium-137 (Cs-137). Results: The experiments conducted with a 1 µCi Cs-137 radioactive source have revealed that the bias voltage (Vbias) of the SiPM needs to be set to 27.8 V at an operating temperature between 43 °C to 44 °C. The radioactive source has to be placed within a 1 cm distance from the sensor to obtain the optimum projection data. Finally, the back-projection technique for image reconstruction with linear interpolation pre-processing has revealed that the Ram-Lak filter produces a better image contrast ratio compared to others. Conclusion: This research has successfully modelled a scintillation camera with SiPM that was able to reconstruct images with an 86.4% contrast ratio from gamma ray projection data.

Background: Recent research on photon detection has led to the introduction of a silicone photomultiplier (SiPM) that operates at a low voltage and is insensitive to magnetic fields. Objective: This work aims to model a scintillation camera with a SiPM sensor and to evaluate the camera reconstructed images from gamma ray projection data. Material and Methods: The type of study in this research is experimental work and analytical. The scintillation camera, modelled from an SiPM sensor array SL4-30035, coupled with a scintillation material Caesium Iodide doped with Thallium (CsI(Tl)), is used in the experimental part. The performance of the camera was evaluated from reconstructed images by a back-projection technique of a radioactive source Caesium-137 (Cs-137). Results: The experiments conducted with a 1 µCi Cs-137 radioactive source have revealed that the bias voltage (Vbias) of the SiPM needs to be set to 27.8 V at an operating temperature between 43 °C to 44 °C. The radioactive source has to be placed within a 1 cm distance from the sensor to obtain the optimum projection data. Finally, the back-projection technique for image reconstruction with linear interpolation pre-processing has revealed that the Ram-Lak filter produces a better image contrast ratio compared to others. Conclusion: This research has successfully modelled a scintillation camera with SiPM that was able to reconstruct images with an 86.4% contrast ratio from gamma ray projection data.

Older adults were advised to avoid social activities during the outbreak of COVID-19. Consequently, they no longer received the social and emotional support they had gained from such activities. Internet use might be a solution to remedy the situation. Therefore, this scoping review sought to map the literature on Internet use and mental health in the older population during the pandemic to examine the extent and nature of the research. A scoping review was conducted using eight databases—PubMed, Scopus, Ebscohost Medline, Ebscohost Academic Search, Ebscohost CINAHL Plus, Ebscohost Cochrane, Ebscohost Psychology and Behavioural Sciences Collection, and Ebscohost SPORTDiscus, according to PRISMA guidelines. Two pre-tested templates (quantitative and qualitative studies) were developed to extract data and perform descriptive analysis and thematic summary. A total of ten articles met the eligibility criteria. Seven out of ten studies were quantitative, while the remainder were qualitative. Five common themes were identified from all the included studies. Our review revealed that Internet use for communication purposes seems to be associated with better mental health in older adults during the COVID-19 pandemic. Directions for future research and limitations of review are also discussed.

In wireless sensor networks, providing flexibility in the selection of Medium Access Control (MAC) protocols to be implemented in an operating system (OS) becomes critical to best meet the requirements of each certain application. Since OS architecture and network stack protocol overhead have an effect on a node’s ability to transmit data, analytical studies often fail to foretell the achievable throughput from an application’s perspective. In Contiki OS, there are constraints at the specific level of the network stack and due to implementation of the provided MAC layer protocol, IEEE 802.15.4 unslotted CSMA/CA, which limit node’s throughput and the available bandwidth in IEEE 802.15.4-based networks and as a result impact node’s power consumption. In this paper, a TDMA-based MAC scheme, namely, lightweight time division multiple access (L-TDMA), is developed and implemented on Contiki to achieve high throughput and low power consumption by overcoming the existing constraints on the networking stack’s implementation of MAC layer on Contiki. The L-TDMA MAC scheme’s performance is evaluated using simulation and experimental testbed to determine its effectiveness and efficiency in comparison to different versions of IEEE 802.15.4 CSMA/CA-based protocols. The results demonstrate that L-TDMA scheme can significantly enhance node’s throughput, average channel throughput, power efficiency, and prolong battery lifespan.

Older adults were advised to avoid social activities during the outbreak of COVID-19. Consequently, they no longer received the social and emotional support they had gained from such activities. Internet use might be a solution to remedy the situation. Therefore, this scoping review sought to map the literature on Internet use and mental health in the older population during the pandemic to examine the extent and nature of the research. A scoping review was conducted using eight databases—PubMed, Scopus, Ebscohost Medline, Ebscohost Academic Search, Ebscohost CINAHL Plus, Ebscohost Cochrane, Ebscohost Psychology and Behavioural Sciences Collection, and Ebscohost SPORTDiscus, according to PRISMA guidelines. Two pre-tested templates (quantitative and qualitative studies) were developed to extract data and perform descriptive analysis and thematic summary. A total of ten articles met the eligibility criteria. Seven out of ten studies were quantitative, while the remainder were qualitative. Five common themes were identified from all the included studies. Our review revealed that Internet use for communication purposes seems to be associated with better mental health in older adults during the COVID-19 pandemic. Directions for future research and limitations of review are also discussed.

In wireless sensor networks, providing flexibility in the selection of Medium Access Control (MAC) protocols to be implemented in an operating system (OS) becomes critical to best meet the requirements of each certain application. Since OS architecture and network stack protocol overhead have an effect on a node’s ability to transmit data, analytical studies often fail to foretell the achievable throughput from an application’s perspective. In Contiki OS, there are constraints at the specific level of the network stack and due to implementation of the provided MAC layer protocol, IEEE 802.15.4 unslotted CSMA/CA, which limit node’s throughput and the available bandwidth in IEEE 802.15.4-based networks and as a result impact node’s power consumption. In this paper, a TDMA-based MAC scheme, namely, lightweight time division multiple access (L-TDMA), is developed and implemented on Contiki to achieve high throughput and low power consumption by overcoming the existing constraints on the networking stack’s implementation of MAC layer on Contiki. The L-TDMA MAC scheme’s performance is evaluated using simulation and experimental testbed to determine its effectiveness and efficiency in comparison to different versions of IEEE 802.15.4 CSMA/CA-based protocols. The results demonstrate that L-TDMA scheme can significantly enhance node’s throughput, average channel throughput, power efficiency, and prolong battery lifespan.

The notion of smart cities has remained under evolution as its global implementations are challenged by numerous technological, economic, and governmental obstacles. Moreover, the synergy of the Internet of Things (IoT) and big data technologies could result in promising horizons in terms of smart city development which has not been explored yet. Thus, the current research aims to address the essence of smart cities. To this end, first, the concept of smart cities is briefly overviewed; then, their properties and specifications as well as generic architecture, compositions, and real-world implementations are addressed. Furthermore, possible challenges and opportunities in the field of smart cities are described. Numerous issues and challenges such as analytics and using big data in smart cities introduced in this study offers an enhancement in developing applications of the above-mentioned technologies. Hence, this study paves the way for future research on the issues and challenges of big data applications in smart cities.

Cardiovascular Disease (CVD) is a primary cause of heart problems such as angina and myocardial ischemia. The detection of the stage of CVD is vital for the prevention of medical complications related to the heart, as they can lead to heart muscle death (known as myocardial infarction). The electrocardiogram (ECG) reflects these cardiac condition changes as electrical signals. However, an accurate interpretation of these waveforms still calls for the expertise of an experienced cardiologist. Several algorithms have been developed to overcome issues in this area. In this study, a new scheme for myocardial ischemia detection with multi-lead long-interval ECG is proposed. This scheme involves an observation of the changes in ischemic-related ECG components (ST segment and PR segment) by way of the Choi-Williams time-frequency distribution to extract ST and PR features. These extracted features are mapped to a multi-class SVM classifier for training in the detection of unknown conditions to determine if they are normal or ischemic. The use of multi-lead ECG for classification and 1 min intervals instead of beats or frames contributes to improved detection performance. The classification process uses the data of 92 normal and 266 patients from four different databases. The proposed scheme delivered an overall result with 99.09% accuracy, 99.49% sensitivity, and 98.44% specificity. The high degree of classification accuracy for the different and unknown data sources used in this study reflects the flexibility, validity, and reliability of this proposed scheme. Additionally, this scheme can assist cardiologists in detecting signal abnormality with robustness and precision, and can even be used for home screening systems to provide rapid evaluation in emergency cases.

The notion of smart cities has remained under evolution as its global implementations are challenged by numerous technological, economic, and governmental obstacles. Moreover, the synergy of the Internet of Things (IoT) and big data technologies could result in promising horizons in terms of smart city development which has not been explored yet. Thus, the current research aims to address the essence of smart cities. To this end, first, the concept of smart cities is briefly overviewed; then, their properties and specifications as well as generic architecture, compositions, and real-world implementations are addressed. Furthermore, possible challenges and opportunities in the field of smart cities are described. Numerous issues and challenges such as analytics and using big data in smart cities introduced in this study offers an enhancement in developing applications of the above-mentioned technologies. Hence, this study paves the way for future research on the issues and challenges of big data applications in smart cities.

Cardiovascular Disease (CVD) is a primary cause of heart problems such as angina and myocardial ischemia. The detection of the stage of CVD is vital for the prevention of medical complications related to the heart, as they can lead to heart muscle death (known as myocardial infarction). The electrocardiogram (ECG) reflects these cardiac condition changes as electrical signals. However, an accurate interpretation of these waveforms still calls for the expertise of an experienced cardiologist. Several algorithms have been developed to overcome issues in this area. In this study, a new scheme for myocardial ischemia detection with multi-lead long-interval ECG is proposed. This scheme involves an observation of the changes in ischemic-related ECG components (ST segment and PR segment) by way of the Choi-Williams time-frequency distribution to extract ST and PR features. These extracted features are mapped to a multi-class SVM classifier for training in the detection of unknown conditions to determine if they are normal or ischemic. The use of multi-lead ECG for classification and 1 min intervals instead of beats or frames contributes to improved detection performance. The classification process uses the data of 92 normal and 266 patients from four different databases. The proposed scheme delivered an overall result with 99.09% accuracy, 99.49% sensitivity, and 98.44% specificity. The high degree of classification accuracy for the different and unknown data sources used in this study reflects the flexibility, validity, and reliability of this proposed scheme. Additionally, this scheme can assist cardiologists in detecting signal abnormality with robustness and precision, and can even be used for home screening systems to provide rapid evaluation in emergency cases.

Introduction: Smart technologies, digital health and eHealth have been shown to enhance institutional elderly care. Because of the rapidly ageing societies, information technologies in geriatric healthcare are urgently needed. A lot of innovation in smart healthcare has occurred in the past decade, and its use in nursing care assessment, daily living activities and service management is yet to be defined. More fundamentally, the concepts, definitions and scopes of a smart nursing home are still vague. Thus, this scoping review aims to examine the extent, range (variety) and nature (characteristics) of evidence on the existing smart concepts and feasible healthcare technologies, types of medical services in nursing home settings and acceptability of a smart nursing home by the elderly people ≥60 years old, their caregivers, nursing home operators and government agencies. Methods and analysis: This scoping review will be guided by the smart technology adoption behaviours of elder consumers theoretical model (Elderadopt) by Golant and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews. First, we will conduct an internet search for nursing homes and websites and databases related to the stakeholders to retrieve the definitions, concepts and criteria of a smart nursing home (phase 1). Second, we will conduct an additional systematic electronic database search for published articles on any measures of technological feasibility and integration of medical services in nursing home settings and their acceptability by nursing home residents and caregivers (phase 2). The electronic database search will be carried out from 1999 to 30 September 2020 and limited to works published in English and Chinese languages. For phase 2, the selection of literature is further limited to residents of nursing homes aged ≥60 years old with or without medical needs but are not terminally ill or bed-bound. Qualitative data analysis wil

The capability of multiple valued logic (MVL) circuits to achieve higher storage density when compared to that of existing binary circuits is highly impressive. Recently, MVL circuits have attracted significant attention for the design of digital systems. Carbon nanotube field effect transistors (CNTFETs) have shown great promise for design of MVL based circuits, due to the fact that the scalable threshold voltage of CNTFETs can be utilized easily for the multiple voltage designs. In addition, resistive random access memory (RRAM) is also a feasible option for the design of MVL circuits, owing to its multilevel cell capability that enables the storage of multiple resistance states within a single cell. In this manuscript, a design approach for ternary combinational logic circuits while using CNTFETs and RRAM is presented. The designs of ternary half adder, ternary half subtractor, ternary full adder, and ternary full subtractor are evaluated while using Synopsis HSPICE simulation software with standard 32 nm CNTFET technology under different operating conditions, including different supply voltages, output load variation, and different operating temperatures. Finally, the proposed designs are compared with the state-of-the-art ternary designs. Based on the obtained simulation results, the proposed designs show a significant reduction in the transistor count, decreased cell area, and lower power consumption. In addition, due to the participation of RRAM, the proposed designs have advantages in terms of non-volatility.

Nursing homes integrated with smart information such as the Internet of Things, cloud computing, artificial intelligence, and digital health could improve not only the quality of care but also benefit the residents and health professionals by providing effective care and efficient medical services. However, a clear concept of a smart nursing home, the expectations and acceptability from the perspectives of the elderly people and their family members are still unclear. In addition, instruments to measure the expectations and acceptability of a smart nursing home are also lacking. The study aims to explore and determine the levels of these expectations, acceptability and the associated sociodemographic factors. This exploratory sequential mixed methods study comprises a qualitative study which will be conducted through a semi-structured interview to explore the expectations and acceptability of a smart nursing home among Chinese elderly people and their family members (Phase I). Next, a questionnaire will be developed and validated based on the results of a qualitative study in Phase I and a preceding scoping review on smart nursing homes by the same authors (Phase II). Lastly, a nationwide survey will be carried out to examine the levels of expectations and acceptability, and the associated sociodemographic factors with the different categories of expectations and acceptability (Phase III). With a better understanding of the Chinese elderly people’s expectations and acceptability of smart technologies in nursing homes, a feasible smart nursing home model that incorporates appropriate technologies, integrates needed medical services and business concepts could be formulated and tested as a solution for the rapidly ageing societies in many developed and developing countries.

The capability of multiple valued logic (MVL) circuits to achieve higher storage density when compared to that of existing binary circuits is highly impressive. Recently, MVL circuits have attracted significant attention for the design of digital systems. Carbon nanotube field effect transistors (CNTFETs) have shown great promise for design of MVL based circuits, due to the fact that the scalable threshold voltage of CNTFETs can be utilized easily for the multiple voltage designs. In addition, resistive random access memory (RRAM) is also a feasible option for the design of MVL circuits, owing to its multilevel cell capability that enables the storage of multiple resistance states within a single cell. In this manuscript, a design approach for ternary combinational logic circuits while using CNTFETs and RRAM is presented. The designs of ternary half adder, ternary half subtractor, ternary full adder, and ternary full subtractor are evaluated while using Synopsis HSPICE simulation software with standard 32 nm CNTFET technology under different operating conditions, including different supply voltages, output load variation, and different operating temperatures. Finally, the proposed designs are compared with the state-of-the-art ternary designs. Based on the obtained simulation results, the proposed designs show a significant reduction in the transistor count, decreased cell area, and lower power consumption. In addition, due to the participation of RRAM, the proposed designs have advantages in terms of non-volatility.

Nursing homes integrated with smart information such as the Internet of Things, cloud computing, artificial intelligence, and digital health could improve not only the quality of care but also benefit the residents and health professionals by providing effective care and efficient medical services. However, a clear concept of a smart nursing home, the expectations and acceptability from the perspectives of the elderly people and their family members are still unclear. In addition, instruments to measure the expectations and acceptability of a smart nursing home are also lacking. The study aims to explore and determine the levels of these expectations, acceptability and the associated sociodemographic factors. This exploratory sequential mixed methods study comprises a qualitative study which will be conducted through a semi-structured interview to explore the expectations and acceptability of a smart nursing home among Chinese elderly people and their family members (Phase I). Next, a questionnaire will be developed and validated based on the results of a qualitative study in Phase I and a preceding scoping review on smart nursing homes by the same authors (Phase II). Lastly, a nationwide survey will be carried out to examine the levels of expectations and acceptability, and the associated sociodemographic factors with the different categories of expectations and acceptability (Phase III). With a better understanding of the Chinese elderly people’s expectations and acceptability of smart technologies in nursing homes, a feasible smart nursing home model that incorporates appropriate technologies, integrates needed medical services and business concepts could be formulated and tested as a solution for the rapidly ageing societies in many developed and developing countries.

Introduction: Smart technologies, digital health and eHealth have been shown to enhance institutional elderly care. Because of the rapidly ageing societies, information technologies in geriatric healthcare are urgently needed. A lot of innovation in smart healthcare has occurred in the past decade, and its use in nursing care assessment, daily living activities and service management is yet to be defined. More fundamentally, the concepts, definitions and scopes of a smart nursing home are still vague. Thus, this scoping review aims to examine the extent, range (variety) and nature (characteristics) of evidence on the existing smart concepts and feasible healthcare technologies, types of medical services in nursing home settings and acceptability of a smart nursing home by the elderly people ≥60 years old, their caregivers, nursing home operators and government agencies. Methods and analysis: This scoping review will be guided by the smart technology adoption behaviours of elder consumers theoretical model (Elderadopt) by Golant and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews. First, we will conduct an internet search for nursing homes and websites and databases related to the stakeholders to retrieve the definitions, concepts and criteria of a smart nursing home (phase 1). Second, we will conduct an additional systematic electronic database search for published articles on any measures of technological feasibility and integration of medical services in nursing home settings and their acceptability by nursing home residents and caregivers (phase 2). The electronic database search will be carried out from 1999 to 30 September 2020 and limited to works published in English and Chinese languages. For phase 2, the selection of literature is further limited to residents of nursing homes aged ≥60 years old with or without medical needs but are not terminally ill or bed-bound. Qualitative data analysis wil

With the continuous downscaling of semiconductor processes, the growing power density and thermal issues in multicore processors become more and more challenging, thus reliable dynamic thermal management (DTM) is required to prevent severe challenges in system performance. The accuracy of the thermal profile, delivered to the DTM manager, plays a critical role in the efficiency and reliability of DTM, different sources of noise and variations in deep submicron (DSM) technologies severely affecting the thermal data that can lead to significant degradation of DTM performance. In this article, we propose a novel fault-tolerance scheme exploiting approximate computing to mitigate the DSM effects on DTM efficiency. Approximate computing in hardware design can lead to significant gains in energy efficiency, area, and performance. To exploit this opportunity, there is a need for design abstractions that can systematically incorporate approximation in hardware design which is the main contribution of our work. Our proposed scheme achieves 11.20% lower power consumption, 6.59% smaller area, and 12% reduction in the number of wires, while increasing DTM efficiency by 5.24%.

Error control schemes became a necessity in network-on-chip (NoC) to improve reliability as the on-chip interconnect errors increase with the continuous shrinking of geometry. Accordingly, many researchers are trying to present multi-bit error correction coding schemes that perform a high error correction capability with the simplest design possible to minimize area and power consumption. A recent work, Multi-bit Error Correcting Coding with Reduced Link Bandwidth (MECCRLB), showed a huge reduction in area and power consumption compared to a well-known scheme, namely, Hamming product code (HPC) with Type-II HARQ. Moreover, the authors showed that the proposed scheme can correct 11 random errors which is considered a high number of errors to be corrected by any scheme used in NoC. The high correction capability with moderate number of check bits along with the reduction in power and area requires further investigation in the accuracy of the reliability model. In this paper, reliability analysis is performed by modeling the residual error probability Presidual which represents the probability of decoder error or failure. New model to estimate Presidual of MECCRLB is derived, validated against simulation, and compared to HPC to assess the capability of MECCRLB. The results show that HPC outperforms MECCRLB from reliability perspective. The former corrects all single and double errors, and fails in 5.18% cases of the triple errors, whereas the latter is found to correct all single errors but fails in 32.5% of double errors and 38.97% of triple errors.

Error control schemes became a necessity in network-on-chip (NoC) to improve reliability as the on-chip interconnect errors increase with the continuous shrinking of geometry. Accordingly, many researchers are trying to present multi-bit error correction coding schemes that perform a high error correction capability with the simplest design possible to minimize area and power consumption. A recent work, Multi-bit Error Correcting Coding with Reduced Link Bandwidth (MECCRLB), showed a huge reduction in area and power consumption compared to a well-known scheme, namely, Hamming product code (HPC) with Type-II HARQ. Moreover, the authors showed that the proposed scheme can correct 11 random errors which is considered a high number of errors to be corrected by any scheme used in NoC. The high correction capability with moderate number of check bits along with the reduction in power and area requires further investigation in the accuracy of the reliability model. In this paper, reliability analysis is performed by modeling the residual error probability Presidual which represents the probability of decoder error or failure. New model to estimate Presidual of MECCRLB is derived, validated against simulation, and compared to HPC to assess the capability of MECCRLB. The results show that HPC outperforms MECCRLB from reliability perspective. The former corrects all single and double errors, and fails in 5.18% cases of the triple errors, whereas the latter is found to correct all single errors but fails in 32.5% of double errors and 38.97% of triple errors.

In this paper, we present multiple bit error correction coding scheme based on extended Hamming product code combined with type II HARQ using shared resources for on chip interconnect. The shared resources reduce the hardware complexity of the encoder and decoder compared to the existing three stages iterative decoding method for on chip interconnects. The proposed method of decoding achieves 20% and 28% reduction in area and power consumption respectively, with only small increase in decoder delay compared to the existing three stage iterative decoding scheme for multiple bit error correction. The proposed code also achieves excellent improvement in residual flit error rate and up to 58% of total power consumption compared to the other error control schemes. The low complexity and excellent residual flit error rate make the proposed code suitable for on chip interconnection links.

In this paper, we present multiple bit error correction coding scheme based on extended Hamming product code combined with type II HARQ using shared resources for on chip interconnect. The shared resources reduce the hardware complexity of the encoder and decoder compared to the existing three stages iterative decoding method for on chip interconnects. The proposed method of decoding achieves 20% and 28% reduction in area and power consumption respectively, with only small increase in decoder delay compared to the existing three stage iterative decoding scheme for multiple bit error correction. The proposed code also achieves excellent improvement in residual flit error rate and up to 58% of total power consumption compared to the other error control schemes. The low complexity and excellent residual flit error rate make the proposed code suitable for on chip interconnection links.

With the continuous downscaling of semiconductor processes, the growing power density and thermal issues in multicore processors become more and more challenging, thus reliable dynamic thermal management (DTM) is required to prevent severe challenges in system performance. The accuracy of the thermal profile, delivered to the DTM manager, plays a critical role in the efficiency and reliability of DTM, different sources of noise and variations in deep submicron (DSM) technologies severely affecting the thermal data that can lead to significant degradation of DTM performance. In this article, we propose a novel fault-tolerance scheme exploiting approximate computing to mitigate the DSM effects on DTM efficiency. Approximate computing in hardware design can lead to significant gains in energy efficiency, area, and performance. To exploit this opportunity, there is a need for design abstractions that can systematically incorporate approximation in hardware design which is the main contribution of our work. Our proposed scheme achieves 11.20% lower power consumption, 6.59% smaller area, and 12% reduction in the number of wires, while increasing DTM efficiency by 5.24%.

PUTRAFLEX is structured with an underpinning philosophy of producing Future-Proof PUTRA Graduates through a curriculum that is flexible in nature, promotes the convergence of disciplines, and offers diverse study paths. Accordingly, PUTRAFLEX contains the concepts and guidelines for its implementation at UPM.

The importance of wireless sensor networks in structural health monitoring is unceasingly growing, because of the increasing demand for both safety and security in the cities. The speedy growth of wireless technologies has considerably developed the progress of structural monitoring systems with the combination of wireless sensor network technology. Wireless sensor network–based structural health monitoring system introduces a novel technology with compelling advantages in comparison to traditional wired system, which has the benefits of reducing installation and maintenance costs of structural health monitoring systems. However, structural health monitoring has brought an additional complex challenges in network design to wireless sensor networks. This article presents a contemporary review of collective experience the researchers have gained from the application of wireless sensor networks for structural health monitoring. Technologies of wired and wireless sensor systems are investigated along with wireless sensor node architecture, functionality, communication technologies, and its popular operating systems. Then, comprehensive summaries for the state-of-the-art academic and commercial wireless platform technologies used in laboratory testbeds and field test deployments for structural health monitoring applications are reviewed and tabulated. Following that, classification taxonomy of the key challenges associated with wireless sensor networks for structural health monitoring to assist the researchers in understanding the obstacles and the suitability of implementing wireless technology for structural health monitoring applications are deeply discussed with available research efforts in order to overcome these challenges. Finally, open research issues in wireless sensor networks for structural health monitoring are explored.

In the presence of deep submicron noise, providing reliable and energy-efficient network on-chip operation is becoming a challenging objective. In this study, the authors propose a hybrid automatic repeat request (HARQ)-based coding scheme that simultaneously reduces the crosstalk induced bus delay and provides multi-bit error protection while achieving high-energy savings. This is achieved by calculating two-dimensional parities and duplicating all the bits, which provide single error correction and six errors detection. The error correction reduces the performance degradation caused by retransmissions, which when combined with voltage swing reduction, due to its high error detection, high-energy savings are achieved. The results show that the proposed scheme reduces the energy consumption up to 51.7% as compared with other schemes while achieving the target link reliability level. Also, it shows improved network performance as compared with ARQ-based scheme and close to forward error correction-based schemes.

In this paper, we reported the detection of lard using tapered optical fiber integrated with graphene quantum dot (GQD). Two different sensors were fabricated and tested, one coated with GQD only as sensing element, the other was coated with gold (Au)-GQD to be tested with lard concentration ranging from 20% till 100%. The GQD coated sensor obtained a sensitivity of 0.034/a.u.% at fluorescence emission peak 652 nm. Meanwhile the Au-GQD sensor, obtained higher sensitivity at 0.042/a.u.% with peak fluorescence emission at 680 nm. The proposed sensor shows a great potential of using sensor in detection of lard for future advancement of food technology.

When a person gets old, there are many changes that occur in the aspect of biomechanical features such as bones, joints and muscles which can affect their mobility and strength including reduction in vision and hearing abilities. Thus, this condition will expose them to risk of injuries and accidents. Based on previous studies, toilet and bathroom are identified as the common place where injuries and accidents occur involving older persons. Therefore, in order to create safe and suitable environment for older persons, modifications to products, systems and environments for their daily use should be taken into consideration. Environmental modifications and assistive technology (AT) can compensate for limitations in functional capabilities and thus promoting the well-being and independence of the elderly. In this study, the initial approach is through qualitative methods which was Focus Group Discussion (FGD). Information related to issues and problems, causing factors and suggestions for improvement will be used as an important indicator in the development of relevant systems in this study.

In this paper, we reported the detection of lard using tapered optical fiber integrated with graphene quantum dot (GQD). Two different sensors were fabricated and tested, one coated with GQD only as sensing element, the other was coated with gold (Au)-GQD to be tested with lard concentration ranging from 20% till 100%. The GQD coated sensor obtained a sensitivity of 0.034/a.u.% at fluorescence emission peak 652 nm. Meanwhile the Au-GQD sensor, obtained higher sensitivity at 0.042/a.u.% with peak fluorescence emission at 680 nm. The proposed sensor shows a great potential of using sensor in detection of lard for future advancement of food technology.

In the presence of deep submicron noise, providing reliable and energy-efficient network on-chip operation is becoming a challenging objective. In this study, the authors propose a hybrid automatic repeat request (HARQ)-based coding scheme that simultaneously reduces the crosstalk induced bus delay and provides multi-bit error protection while achieving high-energy savings. This is achieved by calculating two-dimensional parities and duplicating all the bits, which provide single error correction and six errors detection. The error correction reduces the performance degradation caused by retransmissions, which when combined with voltage swing reduction, due to its high error detection, high-energy savings are achieved. The results show that the proposed scheme reduces the energy consumption up to 51.7% as compared with other schemes while achieving the target link reliability level. Also, it shows improved network performance as compared with ARQ-based scheme and close to forward error correction-based schemes.

When a person gets old, there are many changes that occur in the aspect of biomechanical features such as bones, joints and muscles which can affect their mobility and strength including reduction in vision and hearing abilities. Thus, this condition will expose them to risk of injuries and accidents. Based on previous studies, toilet and bathroom are identified as the common place where injuries and accidents occur involving older persons. Therefore, in order to create safe and suitable environment for older persons, modifications to products, systems and environments for their daily use should be taken into consideration. Environmental modifications and assistive technology (AT) can compensate for limitations in functional capabilities and thus promoting the well-being and independence of the elderly. In this study, the initial approach is through qualitative methods which was Focus Group Discussion (FGD). Information related to issues and problems, causing factors and suggestions for improvement will be used as an important indicator in the development of relevant systems in this study.

The importance of wireless sensor networks in structural health monitoring is unceasingly growing, because of the increasing demand for both safety and security in the cities. The speedy growth of wireless technologies has considerably developed the progress of structural monitoring systems with the combination of wireless sensor network technology. Wireless sensor network–based structural health monitoring system introduces a novel technology with compelling advantages in comparison to traditional wired system, which has the benefits of reducing installation and maintenance costs of structural health monitoring systems. However, structural health monitoring has brought an additional complex challenges in network design to wireless sensor networks. This article presents a contemporary review of collective experience the researchers have gained from the application of wireless sensor networks for structural health monitoring. Technologies of wired and wireless sensor systems are investigated along with wireless sensor node architecture, functionality, communication technologies, and its popular operating systems. Then, comprehensive summaries for the state-of-the-art academic and commercial wireless platform technologies used in laboratory testbeds and field test deployments for structural health monitoring applications are reviewed and tabulated. Following that, classification taxonomy of the key challenges associated with wireless sensor networks for structural health monitoring to assist the researchers in understanding the obstacles and the suitability of implementing wireless technology for structural health monitoring applications are deeply discussed with available research efforts in order to overcome these challenges. Finally, open research issues in wireless sensor networks for structural health monitoring are explored.

Low Power Wide Area Networks technology is considered as a new technology which enables a long-range communication where it targets the low power applications. There are many available solutions for Low Power Wide Area Networks technology in the market which among them are LoRa from Semtech and NB-IoT from 3GPP. This paper provides a review of the performances evaluation for Low Power Wide Area Networks Technology. It is shown that the parameters of PHY layer such as frequency, bandwidth, transmit power, spreading factor and code rate able to affect the performances of Low Power Wide Area Networks. Meanwhile, the received signal strength indicator and number of successful received packets data are the common performance parameter studied. In addition, the performance also conducted in the various location either in line-of-sight or not such as outdoor, indoor and underground.

Area-delay curve is an effective technique to compare and select the appropriate library at different target delay constraint. However, generating area-delay curve requires time-consuming synthesis processes. This paper presents a fast area estimation model to allow the designer to select the optimal library for designing area-optimized circuit. The model predicts the area-delay curves for a target circuit based on reduced number of synthesis performed at different frequencies. As compared to the general linear search method, the proposed model with 5 synthesis points results 16.5X-18.6X runtime reduction with average error of 2.74%~5.74% in different height libraries implementation. This shows that the proposed model is beneficial for area optimal library selection at the early stage of design.

Deep submicron technologies continue to develop according to Moore’s law allowing hundreds of processing elements and memory modules to be integrated on a single chip forming multi/many-processor systems-on-chip (MPSoCs). Network on chip (NoC) arose as an interconnection for this large number of processing modules. However, the aggressive scaling of transistors makes NoC more vulnerable to both permanent and transient faults. Permanent faults persistently affect the circuit functionality from the time of their occurrence. The router represents the heart of the NoC. Thus, this research focuses on tolerating permanent faults in the router’s input buffer component, particularly the virtual channel state fields. These fields track packets from the moment they enter the input component until they leave to the next router. The hardware redundancy approach is used to tolerate the faults in these fields due to their crucial role in managing the router operation. A built-in self-test logic is integrated into the input port to periodically detect permanent faults without interrupting router operation. These approaches make the NoC router more reliable than the unprotected NoC router with a maximum of 17% and 16% area and power overheads, respectively. In addition, the hardware redundancy approach preserves the network performance in the presence of a single fault by avoiding the virtual channel closure.

Deep submicron technologies continue to develop according to Moore’s law allowing hundreds of processing elements and memory modules to be integrated on a single chip forming multi/many-processor systems-on-chip (MPSoCs). Network on chip (NoC) arose as an interconnection for this large number of processing modules. However, the aggressive scaling of transistors makes NoC more vulnerable to both permanent and transient faults. Permanent faults persistently affect the circuit functionality from the time of their occurrence. The router represents the heart of the NoC. Thus, this research focuses on tolerating permanent faults in the router’s input buffer component, particularly the virtual channel state fields. These fields track packets from the moment they enter the input component until they leave to the next router. The hardware redundancy approach is used to tolerate the faults in these fields due to their crucial role in managing the router operation. A built-in self-test logic is integrated into the input port to periodically detect permanent faults without interrupting router operation. These approaches make the NoC router more reliable than the unprotected NoC router with a maximum of 17% and 16% area and power overheads, respectively. In addition, the hardware redundancy approach preserves the network performance in the presence of a single fault by avoiding the virtual channel closure.

Lard adulteration in processed foods is a major public concern as it involves religion and health. Most lard discriminating works require huge lab-based equipment and complex sample preparation. The objective of the present work was to assess the feasibility of dielectric spectroscopy as a method for classification of fats from different animal sources, in particular, lard. The dielectric spectra of each animal fat were measured in the radio frequency of 100 Hz – 100 kHz at 45°C to 55°C. The fatty acid composition of each fat was studied by using data from gas chromatography mass spectrometry (GCMS) to explain the dielectric behaviour of each fat. The principal component analysis (PCA) and artificial neural network (ANN) were used to classify different animal fats based on their dielectric spectra. It was found that lard showed the highest dielectric constant spectra among other animal fats, and was mainly affected by the composition of C16 and C18 fatty acids. PCA classification plot showed clear performance in classifying different animal fats. Finally, ANN classification showed different animal fats were classified into their respective groups effectively at high accuracy of 85%. Dielectric spectroscopy, in combination with quantitative analysis, was concluded to provide rapid method to discriminate lard from other animal fats.

Lard adulteration in processed foods is a major public concern as it involves religion and health. Most lard discriminating works require huge lab-based equipment and complex sample preparation. The objective of the present work was to assess the feasibility of dielectric spectroscopy as a method for classification of fats from different animal sources, in particular, lard. The dielectric spectra of each animal fat were measured in the radio frequency of 100 Hz – 100 kHz at 45°C to 55°C. The fatty acid composition of each fat was studied by using data from gas chromatography mass spectrometry (GCMS) to explain the dielectric behaviour of each fat. The principal component analysis (PCA) and artificial neural network (ANN) were used to classify different animal fats based on their dielectric spectra. It was found that lard showed the highest dielectric constant spectra among other animal fats, and was mainly affected by the composition of C16 and C18 fatty acids. PCA classification plot showed clear performance in classifying different animal fats. Finally, ANN classification showed different animal fats were classified into their respective groups effectively at high accuracy of 85%. Dielectric spectroscopy, in combination with quantitative analysis, was concluded to provide rapid method to discriminate lard from other animal fats.

PUTRAFLEX is structured with an underpinning philosophy of producing Future-Proof PUTRA Graduates through a curriculum that is flexible in nature, promotes the convergence of disciplines, and offers diverse study paths. Accordingly, PUTRAFLEX contains the concepts and guidelines for its implementation at UPM.

Low Power Wide Area Networks technology is considered as a new technology which enables a long-range communication where it targets the low power applications. There are many available solutions for Low Power Wide Area Networks technology in the market which among them are LoRa from Semtech and NB-IoT from 3GPP. This paper provides a review of the performances evaluation for Low Power Wide Area Networks Technology. It is shown that the parameters of PHY layer such as frequency, bandwidth, transmit power, spreading factor and code rate able to affect the performances of Low Power Wide Area Networks. Meanwhile, the received signal strength indicator and number of successful received packets data are the common performance parameter studied. In addition, the performance also conducted in the various location either in line-of-sight or not such as outdoor, indoor and underground.

Area-delay curve is an effective technique to compare and select the appropriate library at different target delay constraint. However, generating area-delay curve requires time-consuming synthesis processes. This paper presents a fast area estimation model to allow the designer to select the optimal library for designing area-optimized circuit. The model predicts the area-delay curves for a target circuit based on reduced number of synthesis performed at different frequencies. As compared to the general linear search method, the proposed model with 5 synthesis points results 16.5X-18.6X runtime reduction with average error of 2.74%~5.74% in different height libraries implementation. This shows that the proposed model is beneficial for area optimal library selection at the early stage of design.

Repeated use of frying oil has been proven hazardous due to the degradation process that changes the quality of the oil. In this study, an interdigitated electrode (IDE) sensor was designed to evaluate palm olein degradation during deep fat frying at several frying intervals by measuring the changes in the oil‘s electrical properties. The frying experiment was carried out in batches. In total, 150 batches (150 g batch-1) of French fries were fried over five days. Oil samples were collected (150 mL) after every five frying cycles. The impedance values were measured at 35°C and 45°C using the IDE sensor connected to aninductance (L), capacitance (C), and resistance (R) LCR meter with five frequency levels (100 Hz, 1 kHz, 10 kHz, 20 kHz, and 100 kHz). The total polar compounds (TPC) of each oil sample were measured with a Testo 270 frying oil tester, while the viscosity was measured with a viscometer. The impedance values were found to be significantly different at 35°C and 45°C as well as at different frequency levels (p < 0.0001). For individual frequency analysis, the regression equation obtained the best results at 35°C (with RMSE of 1.21%) and 1.33 mPa.s for TPC and viscosity, respectively. The results indicated that the designed IDE sensor has good potential as a simple and inexpensive method for monitoring palm olein degradation during deep fat frying.

Repeated use of frying oil has been proven hazardous due to the degradation process that changes the quality of the oil. In this study, an interdigitated electrode (IDE) sensor was designed to evaluate palm olein degradation during deep fat frying at several frying intervals by measuring the changes in the oil‘s electrical properties. The frying experiment was carried out in batches. In total, 150 batches (150 g batch-1) of French fries were fried over five days. Oil samples were collected (150 mL) after every five frying cycles. The impedance values were measured at 35°C and 45°C using the IDE sensor connected to aninductance (L), capacitance (C), and resistance (R) LCR meter with five frequency levels (100 Hz, 1 kHz, 10 kHz, 20 kHz, and 100 kHz). The total polar compounds (TPC) of each oil sample were measured with a Testo 270 frying oil tester, while the viscosity was measured with a viscometer. The impedance values were found to be significantly different at 35°C and 45°C as well as at different frequency levels (p < 0.0001). For individual frequency analysis, the regression equation obtained the best results at 35°C (with RMSE of 1.21%) and 1.33 mPa.s for TPC and viscosity, respectively. The results indicated that the designed IDE sensor has good potential as a simple and inexpensive method for monitoring palm olein degradation during deep fat frying.