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The SPOT-MAS assay “Screening for the Presence Of Tumor by Methylation And Size” detects the five most common cancers in Vietnam by evaluating circulating tumor DNA in the blood. Here, we validated its performance in a prospective multi-center clinical trial, K-DETEK. Our analysis of 2795 participants from 14 sites across Vietnam demonstrates its ability to detect cancers in asymptomatic individuals with a positive predictive value of 60%, with 83.3% accuracy in detecting tumor location. We present a case report to support further using SPOT-MAS as a complementary method to achieve early cancer detection and provide the opportunity for early treatment.

The paper aims to investigate the impact of income diversification on commercial banks’ profitability in Vietnam. Using a panel data set of 33 Vietnamese commercial banks during the period from 2006 to 2020, the empirical analysis shows the more diverse in revenue sources, the higher banks’ financial performance. The research provides some recommendations that banks should look forward to diversifying their income, particularly income from non-traditional activities, in order to improve competitiveness, reduce risk, and raise profitability and policies that encourage banks to diversify their incomes should be enacted. This will not only be beneficial for banks but also helps to mitigate the risk for banking industry and maintain its stability. The main results are robust to a different measure of financial performance and controlling for the period of economic crisis.

Aim: This study exploited hepatocellular carcinoma (HCC)-specific circulating DNA methylation profiles to improve the accuracy of a current screening assay for HCC patients in high-risk populations. Methods: Differentially methylated regions in cell-free DNA between 58 nonmetastatic HCC and 121 high-risk patients with liver cirrhosis or chronic hepatitis were identified and used to train machine learning classifiers. Results: The model could distinguish HCC from high-risk non-HCC patients in a validation cohort, with an area under the curve of 0.84. Combining these markers with the three serum biomarkers (AFP, lectin-reactive AFP, des-γ-carboxy prothrombin) in a commercial test, μTASWako®, achieved an area under the curve of 0.87 and sensitivity of 68.8% at 95.8% specificity. Conclusion: HCC-specific circulating DNA methylation markers may be added to the available assay to improve the early detection of HCC.

The present provides molecular data for species of Habenaria diphylla (Nimmo) Dalzell, H. khasiana Hook.f. and H. rostellifera Rchb.f. collected from Binh Chau-Phuoc Buu Nature Reserve, Vietnam for the first time. Along with other DNA sequences from GenBank database, the phylogenetic trees for Habenaria species from Vietnam have been established.

Despite their promise, circulating tumor DNA (ctDNA)-based assays for multi-cancer early detection face challenges in test performance, due mostly to the limited abundance of ctDNA and its inherent variability. To address these challenges, published assays to date demanded a very high-depth sequencing, resulting in an elevated price of test. Herein, we developed a multimodal assay called SPOT-MAS (Screening for the Presence Of Tumor by Methylation And Size) to simultaneously profile methylomics, fragmentomics, copy number, and end motifs in a single workflow using targeted and shallow genome-wide sequencing (∼0.55X) of cell-free DNA. We applied SPOT-MAS to 738 nonmetastatic patients with breast, colorectal, gastric, lung and liver cancer, and 1,550 healthy controls. We then employed machine learning to extract multiple cancer and tissue-specific signatures for detecting and locating cancer. SPOT-MAS successfully detected the five cancer types with a sensitivity of 72.4% at 97.0% specificity. The sensitivities for detecting early-stage cancers were 62.3% and 73.9% for stage I and II, respectively, increasing to 88.3% for nonmetastatic stage IIIA. For tumor-of-origin, our assay achieved an accuracy of 0.7. Our study demonstrates comparable performance to other ctDNA-based assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening.

NOx emissions cause many negative impacts on the living environment. The photocatalysis of semiconductors is superior for nitric oxide (NO) degradation due to their low redox potential. In this report, we combine SnO2-x/g-C3N4 heterojunction photocatalyst toward the high selectivity into green products under visible light illumination. Results show that SnO2-x/g-C3N4 heterojunction degraded 40.8% of NO, which is 1.6 times higher than that of g-C3N4. In addition, the selectivity coefficient of SnO2-x/g-C3N4 is higher 3 times than both pure SnO2-x and g-C3N4. Furthermore, SnO2-x/g-C3N4 expresses a superior stability for NO photocatalytic-degradation after five cycles. The scavenger trapping test results, and electron spin resonance (ESR) analysis also provide more understanding of the charge transfer mechanism of materials. SnO2-x/g-C3N4 heterojunction shows a high removal efficiency of NO gas, making it an up-and-coming environmental treatment candidate.

The paper aims to investigate the impact of Corporate Social Responsibility (CSR) practices on the financial performance of oil and gas firms in Asian countries by using a panel data set that includes 23 firms from 7 Asian countries from 2004 to 2017. The empirical results support the research hypothesis that CSR practices have a negative impact on the financial performance of oil and gas companies. This means CSR practices may impose a substantial burden on firms in the oil and gas industry. In addition, we find that different CSR practices have different sizes of impact on firm financial performance. In particular, environment practice has the biggest impact, social practice ranks second, and governance practice has the weakest impact. The main results are also confirmed by several robustness tests.

Photocatalysis has been studied and considered as a green and practical approach in addressing environmental pollution. However, factors that affect photocatalytic performance have not been systematically studied. In this work, we have presented a comprehensive roadmap for characterizing, interpreting, and reporting semiconductors' electrical and optical properties through routinely used techniques such as diffuse reflectance spectroscopy, electrochemical techniques (Mott-Schottky plots), photoluminescence, X-ray photoelectron spectroscopy, and ultraviolet photoelectron spectroscopy in the context of photocatalysis. Having precisely studied the band structure of three representative photocatalysts, we have presented and highlighted the essential information and details, which are critical and beneficial for studies of (1) band alignments, (2) redox potentials, and (3) defects. Further works with a comprehensive understanding of the band structure are desirable and hold great promise.

Aims: Early detection of colorectal cancer (CRC) provides substantially better survival rates. This study aimed to develop a blood-based screening assay named SPOT-MAS (‘screen for the presence of tumor by DNA methylation and size’) for early CRC detection with high accuracy. Methods: Plasma cell-free DNA samples from 159 patients with nonmetastatic CRC and 158 healthy controls were simultaneously analyzed for fragment length and methylation profiles. We then employed a deep neural network with fragment length and methylation signatures to build a classification model. Results: The model achieved an area under the curve of 0.989 and a sensitivity of 96.8% at 97% specificity in detecting CRC. External validation of our model showed comparable performance, with an area under the curve of 0.96. Conclusion: SPOT-MAS based on integration of cancer-specific methylation and fragmentomic signatures could provide high accuracy for early-stage CRC detection.

Vietnam has a high thalassemia burden. We collected blood samples from 5880 pregnant Vietnamese women during prenatal health checks to assess thalassemia carrier frequency using combined gap-polymerase chain reaction (gap-PCR) and targeted next-generation sequencing (NGS). Thalassemia carriers were identified with prevalence of 13.13% (772), including 7.82% (460) carriers of α-thalassemia (α-thal), 5.31% (312) carriers of β-thalassemia (β-thal), and 0.63% (37) concurrent α-/β-thal carriers. Deletional mutations (368) accounted for 80.0% of α-thal carriers, of which,

Purpose: Starting from the goal of economic development associated with environmental protection activities, this study examines the factors affecting the application of environmental accounting (EA) in manufacturing enterprises in Vietnam. Methodology: This study is conducted using a combination of qualitative research methods (review of previous theories and research papers related to the research) and a quantitative research model (testing the degree of the appropriateness of the scale and the theoretical model through Cronbach's Alpha reliability coefficient, exploratory factor analysis (EFA), multivariable regression analysis to determine the relationship between factors affecting the application environmental accounting in manufacturing enterprises in Vietnam. Results: Multivariable regression analysis shows that all factors (six factors) included in the study have an impact on the application of environmental accounting in manufacturing enterprises in Vietnam. Which stakeholder pressure has the strongest impact and financial resources have the weakest effect on the application of EA in these enterprises. Originality/Value: This study provides empirical evidence about the impact of each factor on the application of environmental accounting, thereby helping state management agencies, professional associations, and businesses in the process of developing and promulgating policies affecting these factors to promote the application of environmental accounting in Vietnamese enterprises.

A kidney transplant has become an option for many people with end-stage kidney failure. However, not all patients are likely to receive a kidney transplant. This study is conducted to identify some characteristics of patients with renal transplant indications for kidney transplantation from 26 hospitals in Hanoi. According to the research results, in 2020, Hanoi has 3,220 patients on dialysis with the average age of 54, mainly from 46-65, more males than females. More than 95% of the causes of dialysis are chronic glomerulonephritis, hypertension, and diabetes; up to 65% of the dialysis time is over 5 years, blood type O patients account for 43% and 25% of dialysis patients with hepatitis C. Out of a total of 3,220 patients, 2,400 (74%) of patients have indicated a kidney transplant with an average age of nearly 49 years, of which men (55%) are more than women (45%); dialysis time less than 5 years accounts for the highest percentage with 43%, 25% of patients with indicated kidney transplantation are HCV positive; chronic kidney failure due to chronic glomerulonephritis and hypertension, diabetes are two main groups of causes, accounting for 94% of dialysis patients who are indicated for transplant.

Purpose The purpose of this study is to carry out an empirical investigation about how the level of market concentration or competitiveness of the banking system and institutional quality are associated with bank’s financial stability. Design/methodology/approach This study uses dynamic panel data techniques on the sample of 133 developing and emerging countries over the years 2002–2020. Findings The authors document several significant findings. First, there is evidence that bank stability is positively associated with the level of market concentration. The result is in line with the concentration–stability view that banks operating in a more concentrated market tend to be more stable than those in a less concentrated market. Second, the results confirm that the quality of the institutional environment plays a critical role in improving the stability of banks in developing and emerging countries. Third, the authors find that institutional development can moderate the effect of market concentration (or competitiveness of the banking system) on bank stability. Specifically, the results show that better institutional quality enhances the positive influence of bank concentration on the bank’s financial stability in developing and emerging countries. These results are robust to different specifications with the alternative measures of bank stability and market concentration. Originality/value This study provides further understanding regarding the effects of the level of market concentration or competitiveness of the banking system and institutional quality on bank stability in 133 developing and emerging countries over the years 2002–2020.

This article presents a high fundamental frequency subterahertz (sub-THz) CMOS oscillator with a single core. The proposed structure with a capacitive load reduction circuit increases the fundamental oscillation frequency by decreasing the parasitic capacitances of the buffer transistor and inductor and minimizing the loss caused by the gate resistance of the buffer stage. To achieve high output power, the proposed oscillator combines the differential output signals through a differential-to-single (DTS) transformer. A push–push oscillator based on the high fundamental frequency oscillator is also introduced to increase the operating frequency further. The proposed oscillators are implemented in a 65-nm CMOS process. Measurements of the fundamental oscillator reveal an output power of 0.285 mW at 251 GHz, while consuming 21 mA from a 1.3-V supply voltage. The measured operating frequency of the push–push oscillator is 432 GHz.

A design for a high-output-power, high-frequency CMOS oscillator is presented in this paper. The proposed oscillator can increase the output power by coupling the signal at the source of the core transistor to the drain of the buffer transistor. In addition, the source-to-drain coupling generates an optimum negative transconductance at the desired operating frequency. A capacitive load reduction circuit is also applied to increase the fundamental oscillation frequency. Using these techniques, the fundamental and push-push oscillators were implemented using 65 nm CMOS technology. The measurement results of the fundamental and push-push oscillators showed 2.7 and -25 dBm of peak differential output power at 194 and 394 GHz, respectively. In the 200 GHz frequency band, the proposed fundamental oscillator shows the highest output power among recently reported state-of-the-art CMOS oscillators.

Moisturizers play an essential role in maintaining the integrity of the skin barrier by increasing stratum corneum hydration (SCH) and reducing transepidermal water loss (TEWL). According to dermatology and allergy guidelines, moisturizers should be applied on the skin within 3 min after bathing or showering. However, there is very little evidence supporting this recommendation. This study aimed to investigate the effectiveness of immediate and delayed moisturizing after bathing/washing on the improvement of SCH and TEWL.This was a crossover study of 60 healthy Vietnamese volunteers aged 18-25 years. In each subject, SCH and TEWL levels were measured at three areas: non-moisturized, immediate moisturizing after washing, and delayed moisturizing at 30 min after washing.In non-moisturized skin, SCH and TEWL levels were significantly different from the baseline at 60 min after washing, while significantly decreased TEWL levels were observed immediately after moisturizing. In addition, moisturized skin had significantly higher SCH and lower TEWL levels compared with non-moisturized areas at every time point (p 0.05). Interestingly, the percentage changes of SCH and TEWL levels from baseline did not differ between immediately and delayed moisturized areas.Tested moisturizer helped increase SCH and decrease TEWL; however, there was no difference in moisturizing effectiveness between immediate and delayed moisturizing in healthy skin. The recommendation of immediate application of moisturizers after bathing/washing should be reconsidered, and more studies are needed to establish a stronger recommendation.

Graph Neural Networks (GNNs) have recently emerged as a robust framework for graph-structured data. They have been applied to many problems such as knowledge graph analysis, social networks recommendation, and even Covid19 detection and vaccine developments. However, unlike other deep neural networks such as Feed Forward Neural Networks (FFNNs), few analyses such as verification and property inferences exist, potentially due to dynamic behaviors of GNNs, which can take arbitrary graphs as input, whereas FFNNs which only take fixed size numerical vectors as inputs. This paper proposes an approach to analyze GNNs by converting them into FFNNs and reusing existing FFNNs analyses. We discuss various designs to ensure the scalability and accuracy of the conversions. We illustrate our method on a study case of node classification. We believe that our approach opens new research directions for understanding and analyzing GNNs., Comment: Accepted to ICSE 2022, NIER track

A novel clustering technique based on the projection onto convex set (POCS) method, called POCS-based clustering algorithm, is proposed in this paper. The proposed POCS-based clustering algorithm exploits a parallel projection method of POCS to find appropriate cluster prototypes in the feature space. The algorithm considers each data point as a convex set and projects the cluster prototypes parallelly to the member data points. The projections are convexly combined to minimize the objective function for data clustering purpose. The performance of the proposed POCS-based clustering algorithm is verified through experiments on various synthetic datasets. The experimental results show that the proposed POCS-based clustering algorithm is competitive and efficient in terms of clustering error and execution speed when compared with other conventional clustering methods including Fuzzy C-Means (FCM) and K-means clustering algorithms., Comment: 6 pages, 4 figures, IWIS 2022

To demonstrate the prevalence of maternal mosaic monosomy X (MMXO) in a cohort of pregnant women in Vietnam. All 105,594 singleton pregnant women undergoing noninvasive prenatal screening (NIPS) between January 2019 and February 2021 in Vietnam were analyzed by measuring discordance between size- and count-based z-scores for chromosome X (ChrX) to identify suspected cases of MMXO and validated by fluorescence in situ hybridization (FISH) on maternal blood. We identified 295 (0.279%) suspected MMXO cases. After FISH analysis, MMXO was confirmed in 125 cases (42.37%), revealing the MMXO prevalence of 0.118% (95% CI: 0.097–0.139%) in this cohort. We found a relatively high prevalence of MMXO in Vietnamese pregnant women and demonstrated a strong influence of MMXO on the ChrX z-score using a count-based method, resulting in false positives. The size-based method is not sensitive to MMXO and therefore achieves higher PPV.

Photocatalysis has been studied and considered as a green and effective approach in addressing environmental pollution. However, factors that affect photocatalytic performance have not been systematically studied. In this work, we have presented a comprehensive roadmap for characterizing, interpreting, and reporting semiconductors' electrical and optical properties through routinely used techniques such as diffuse reflectance spectroscopy (DRS), electrochemical techniques (Mott-Schottky plots), photoluminescence (PL), X-ray photoelectron spectroscopy (XPS ), and ultraviolet photoelectron spectroscopy (UPS) in the context of photocatalysis. Having deeply and precisely studied the band structure of three representative photocatalysts, we have presented and highlighted essential information and details, which are critical and beneficial for studies of (1) band alignments, (2) redox potentials, and (3) defects. Further works with a comprehensive understanding of band structure are desirable and hold great promise.

This paper presents a high-speed ASIC implementation of the tanh activation function (AF) for artificial neural network. The proposed architecture for tanh AF is designed using a highspeed cascade Coordinate Rotation DIgital Computer (CORDIC) to implement hyperbolic and division functions. CORDIC processing is accelerated by fixing the angle of rotation and removing parameters related to the direction of rotation. The proposed architecture was coded in Verilog hardware description language and synthesized by Synopsys Design Compiler using a 90-nm CMOS standard cell library. The implementation results show an improved area-delay product compared to the existing architectures.

Form understanding is a challenging problem which aims to recognize semantic entities from the input document and their hierarchical relations. Previous approaches face significant difficulty dealing with the complexity of the task, thus treat these objectives separately. To this end, we present a novel deep neural network to jointly perform both entity detection and link prediction in an end-to-end fashion. Our model extends the Multi-stage Attentional U-Net architecture with the Part-Intensity Fields and Part-Association Fields for link prediction, enriching the spatial information flow with the additional supervision from entity linking. We demonstrate the effectiveness of the model on the Form Understanding in Noisy Scanned Documents (FUNSD) dataset, where our method substantially outperforms the original model and state-of-the-art baselines in both Entity Labeling and Entity Linking task., Comment: Accepted to ICPR 2020

The waste classification has become a crucial mission for sustaining worldwide economic growth and preserving the environment. Using deep learning to sort solid waste automatically is necessary since it could minimize the time taken to categorize a large amount of rubbish manually and health risks created by working with polluted waste. In this study, we take advantage of several Convolutional Neural Networks such as VGG, Resnet, Efficientnet, etc. to solve this problem. The test accuracies achieved by training Resnet101, EfficientNet-B0, and EfficientNet-B1 on the dataset of 6640 images are 92.43%, 90.02%, and 91.53% respectively. We also build an ensemble model on the base of these three models, which attains an accuracy of 94.11%. The dataset is from the Trashnet dataset of Stanford and images collected on the Internet. This approach can be potentially applied to real-life environmental problems.

International audience; In the present paper, the Layer by Layer (LbL) method using beta-lactoglobulin and sodium alginate was performed to individually encapsulateSaccharomyces cerevisiaecells in microorganized shells in order to protect them against stresses during dehydration. Higher survival (similar to 1 log) for encapsulated yeast cells was effectively observed after air dehydration at 45 degrees C. For the first time, the potentiality of Synchrotron-Fourier Transform InfraRed microspectroscopy (S-FTIR) was used at the single-cell level in order to analyze the contribution of the biochemical composition of non-encapsulated vs. encapsulated cells in response to dehydration. The microspectroscopy measurements clearly differentiated between non-encapsulated and encapsulated yeast cells in the amide band region. In the spectral region specific to lipids, the S-FTIR results indicated probably the decrease in membrane fluidity of yeast after dehydration without significant distinction between the two samples. These data suggested minor apparent chemical changes in cell attributable to the LbL system upon dehydration. More insights are expected regarding the lower mortality among encapsulated cells. Indeed the hypothesis that the biopolymeric layers could induce less damage in cell by affecting the transfer kinetics during dehydration-rehydration cycle, should be verified in further work.

International audience; Fluidized bed drying is a dehydration process often applied to microorganisms and used for food particles stabilization. Despite its common use in yeast production, this process can lead to cell death depending on the strain and the growth conditions. During fermentation, yeasts undergo nutritional stressful environments according to media composition. In order to face these conditions, yeasts are able to synthesize protective molecules, e.g. glutathione (tripeptide, an antioxidant) and trehalose (disaccharide, a cell desiccation protector). However, the role of these two molecules during fluidized bed drying is still not well known. This work aimed to investigate if total glutathione (GSHt) and trehalose (TRE) accumulation leads to the creation of more resistant and stable yeast cells. The effect of GSHt accumulation after relatively nutrient richer cultivation on cell resistance to mild stress (45 degrees C-90 min) was obvious. This growing condition also improved the stabilization and performance of cells after rehydration. On the other hand, the highest amount of TRE stored by yeasts cultivated in nutrient poorer media led to cells being more resistant to severe stress (60 degrees C-60 min). This strategy could be used for the development of new bioprocesses focusing on improving the performance and resistance of cells after fluidized bed drying.

International audience; We report herein an efficient synthesis of news naphtalimide-based fluorescent derivatives functionalized with an a,(3-unsaturated carbonyl group. Probes were synthesized from reaction of an amino-naphtalimide precursor with maleic anhydride. Photophysical study of fluorescent probes and cells labelling were performed, and showed that the reactive derivatives exhibit rich turn on fluorescence properties in presence of different biological thiol (Glutathione and Cysteine) making these systems a very promising way for thiol bioimaging.

This letter presents a novel subterahertz CMOS signal source with high output power. The proposed oscillators are mutually injected to align their frequencies and phases through a transformer that couples the gate and drain signals between the adjacent cores. The proposed architecture is implemented using the 65-nm CMOS technology. The measured peak output power is −2.5 dBm at 417 GHz while dissipating 108 mW. The proposed signal source shows the highest dc-to-RF efficiency (0.5%) and a wide tuning range (5.1%) among state-of-the-art signal sources above 400 GHz.

Real-time systems are used in many critical domains such as automotive, avionics and nuclear, therefore their temporal behavior needs to be checked rigorously. Many scheduling theory-based analysis tests have been proposed to validate the design of real-time systems. Since each given test is based on a set of assumptions, only the constrained system which satisfies these assumptions can be reliably verified by such a test. These assumptions do not depend on any design language but their interpretation does. Currently, these assumptions are often drowned in scientific paper discussions and expressed in natural languages. In this paper, we aim to make possible to define formally assumptions by real-time systems analysts without being expert of design languages. Indeed, we propose a domain specific language named IRL (Identification Rule Language). We show the benefit of such a language to capitalize efforts. That is, IRL allows to define analysis supports to help the timing verification community to share its knowledge and enables systems designers to use this knowledge easily.

Saving energy is one of the biggest concerns nowadays in order to deal with lacking fossil fuel and climate change. One possible approach is using the Home Energy Management System (HEMS) to monitor and manage the electrical usage at residential user. One useful feature of HEMS is the capability of detecting and identifying electrical appliances in order to assign these appliances to join many saving energy programs such as Time-Of-Use or Demand Response. In this paper, we propose an appliance classification approach based on K-Nearest Neighbors (KNN) technique. KNN is extensively used classification algorithm owing to its simplicity, ease of implementation and effectiveness. The inputs we used to calculate the Euclidean distance in KNN are the root mean square (RMS) of voltage, current and the active power of appliance. We also implement a HEMS prototype includes many smart plug-in devices and a MQTT server. The appliance classification results show that our KNN classifier can be a suitable approach for appliance classification feature of HEMS.

In this paper we test the sustainability of U.S. public debt for the period 1916–2012 by analyzing how the primary surplus to gross domestic product (GDP) responds to changes in the debt to GDP ratio in a time‐varying parameter model. Further, we determine the stationarity property of the debt/GDP ratio while accommodating possible breaks in the data caused by wars and economic crisis under both the null and alternative hypotheses of an endogenous unit root test. The results show that the U.S. public debt was sustainable until 2005 when the primary surplus to GDP reacted negatively to the debt/income ratio. This is further exacerbated during the global financial crisis when primary surpluses continued to fall with increased debt, thus jeopardizing the sustainability of fiscal policy. While the stationarity test shows that the U.S. fiscal debt/GDP ratio is sustainable, it fails to highlight the risk that its debt policy has been becoming unsustainable in recent years.

This paper presents a push-push coupled stack oscillator that achieves a high output power level at terahertz (THz) wave frequency. The proposed stack oscillator core adopts a frequency selective negative resistance topology to improve negative transconductance at the fundamental frequency and a transformer connected between gate and drain terminals of cross pair transistors to minimize the power loss at the second harmonic frequency. Next, the phases and the oscillation frequencies between the oscillator cores are locked by employing an inductor of frequency selective negative resistance topology. The proposed topology was implemented in a 65-nm bulk CMOS technology. The highest measured output power is &minus, 0.8 dBm at 353.2 GHz while dissipating 205 mW from a 2.8 V supply voltage.

Herein, the fast and simple formation of triangular silver nanoparticles (T-Ag NPs) was systematically studied by a chemical reduction process with the assistance of light irradiation. The effects of sodium borohydride (NaBH4) concentration, pH medium, and light source irradiation are investigated via the localized surface plasmon resonances (LSPRs) detection of silver nanoparticles (Ag NPs). Results indicated that pH and light source are the two primary factors for the morphology of Ag NPs while NaBH4 plays an important role to control the formation rate of T-Ag NPs. Moreover, the photoreduction time for synthesis of T-Ag NPs is 180 min, and this method can be easily synthesized in any laboratory.

Identification of in-home electrical appliances is an important task for the home energy management system in order to surveillance and control the home electrical usage. In this paper, we propose a Smart Plug device prototype that can that can recognize the type of electric appliances according to the measured voltage, current and power factor. Our device includes two modules. The power interface with the appliance is based on the voltage and current sensors connected to the Arduino Uno. The processing module uses the machine learning approaches such as neural network or K Nearest Neighborhood (KNN) to recognize the electrical appliances plugged into in real time. All of the recognized in-home appliances datasets then can be uploaded to the home energy management system for further applications. For instance, the system gives a warning message to the user when the appliance has an unusual power factor or an outlier in power consumption. This warning is sent via email or mobile phone. Compare to other commercial smart plug devices, our device has more functionalities at a low price.

Architecture Analysis and Design Language (AADL) is a standard in avionics system design. However, the communication patterns provided by AADL are not sufficient to the current context of Real-Time Embedded System (RTES) in which some multi-periodic communication patterns may occur. We propose an extension of a precedence model between tasks of different periods (multiperiodic communication). This relies on the Semaphore Precedence Constraint (SPC) model that is inspired from the concept of Semaphore, and more specifically on the m-n producer/consumer paradigm. We reinforce the SPC semantics by allowing cycles in the SPC precedence graph. We also present another viewpoint on the periodicity of tasks system using SPC based on a graph apart from the encoding technique presented in the SPC seminal work. An implementation of SPC in AADL and its associated analysis tool are also provided to study the temporal behaviour of systems using SPC.

Purpose: The purpose of this paper is to promote the integration of sustainable development concepts and conceptual models in engineering research, and therefore, to enhance sustainability of research models. Particularly, the concepts are integrated with an integrated theoretical model of knowledge management and DMAIC (Define-Measure-Analysis-Improve-Control) process. Methodology: Based on literature, the key concepts of sustainable development, knowledge management, Ontology and DMAIC methodology have been reviewed. A theoretical combination of knowledge management, ontology engineering, and DMAIC methodology is to aim at accumulating and reusing a potential economic resource, knowledge resource. An analysis of sustainable aspects of a proposed model is presented. Important findings: As literature expressed that knowledge created by every step of a DMAIC process can be accumulated and reused by using Ontology in a conceptual model. Furthermore, sustainable aspects of the model such as economy, environment and society are identified. Conclusion: DMAIC knowledge is a potential economic resource that should be shared and reused using Ontology engineering in order to archive sustainable development of DMAIC process. Theoretical integration of seven sustainable measures with activities of knowledge management is possible and realizable.

Sustainable development of a process depends on a harmonious association of three sustainable pillars: Economy, Society, and Environment. Yet, in case of DMAIC (Define-Measure-Analyze-Improve-Control) process, the combination is challenged by inefficient management of knowledge resource in the process. The potential economy resource is not preserved and renewed, and therefore influents on sustainability of the process. In this article, the authors present and discuss sustainable aspects of a knowledge management model for DMAIC in which knowledge resource is accumulated and reused efficiently. In particular, the key concepts of sustainable development are reviewed, a process of knowledge management based on Ontology Engineering is presented, and sustainable criterial and measures for the proposed model are applied. The authors find that preserving and renewing knowledge is an indispensable process of sustainable development of DMAIC process.

DMAIC (Define, Measure, Analyze, Improve, and Control) is an important process used to enhance quality of processes basing on knowledge. However, it is difficult to access DMAIC knowledge. Conventional approaches meet a problem arising from structuring and reusing DMAIC knowledge. The main reason is that DMAIC knowledge is not represented and organized systematically. In this article, we overcome the problem basing on a conceptual model that is a combination of DMAIC process, knowledge management, and Ontology engineering. The main idea of our model is to utilizing Ontologies to represent knowledge generated by each of DMAIC phases. We build five different knowledge bases for storing all knowledge of DMAIC phases with the support of necessary tools and appropriate techniques in Information Technology area. Consequently, these knowledge bases provide knowledge available to experts, managers, and web users during or after DMAIC execution in order to share and reuse existing knowledge.

Sustainable development of a process depends on a harmonious association of three sustainable pillars: Economy, Society, and Environment. Yet, in case of DMAIC (Define-Measure-Analyze-Improve-Control) process, the combination is challenged by inefficient management of knowledge resource in the process. The potential economy resource is not preserved and renewed, and therefore influents on sustainability of the process. In this article, the authors present and discuss sustainable aspects of a knowledge management model for DMAIC in which knowledge resource is accumulated and reused efficiently. In particular, the key concepts of sustainable development are reviewed, a process of knowledge management based on Ontology Engineering is presented, and sustainable criterial and measures for the proposed model are applied. The authors find that preserving and renewing knowledge is an indispensable process of sustainable development of DMAIC process.

A high output power and high fundamental frequency CMOS oscillator is presented in this paper. To increase output power, the source inductor at the core transistor is coupled with the drain inductor at the buffer transistor through a transformer. A capacitive load reduction circuit (CLRC) is also used to increase the fundamental oscillation frequency. The proposed single-core fundamental oscillator is implemented using 65 nm CMOS technology. The measurement results show a fundamental frequency of 194 GHz and maximum differential output power of 1.85 mW.

In this paper, we focus on RTES (real-time embedded systems) designs expressed in AADL (Architecture and Analysis Design Language) and we propose a model-based approach to improve the way that designers check and analyze the performance of their system designs by capitalizing the analysis process. Our approach is based on proposing customized repositories of models using formal AADL-compliant query and constraint languages in order to orient designers to choose the most suitable analysis models and tests. Furthermore, this work is also dedicated to research teams to share their researches and prototypes, in order to enhance the (re-)usability of the real-time performance analysis tests.

The millimeter-wave imaging approach is a promising candidate to satisfy the unmet needs of real-time biomedical imaging, such as resolution, focal area, and cost. As a part of the endeavor to make millimeter-wave imaging more feasible, this paper presents a CMOS oscillator generating a high output power at the millimeter-wave frequency range, with a high fundamental oscillation frequency. The proposed oscillator adopts a frequency-selective negative resistance topology to improve the negative transconductance and to increase the fundamental frequency of oscillation. The proposed oscillator was implemented in a 65 nm bulk CMOS process. The measured highest output power is &ndash, 2.2 dBm at 190 GHz while dissipating 100 mW from a 2.8 V supply voltage.

DHT (Distributed Hash Table) such as CHORD or PARTRY facilitates information searching in scalable systems. Two popular DHT-based approaches for range or multi-attribute search are to rely on attribute-value tree and a combination of attributes and values. However, tradeoff between a load balancing mechanism and query efficiency is a challenging task for such information searching systems. In this paper, we propose improved algorithms for a system called DSMAV in which information resources are distributed fairly among nodes and found based on multi-attribute queries in a small number of hop counts. Our system creates identifiers from resource names, each of which is a combination of attribute-value pairs (AV pairs). In order to overcome problem of load imbalance among nodes because of frequent appearance of AV pairs in many resource names, we control the quantity of information resources distributed to a node based on load capacity of each node. Moreover, periodical updating processes on a node enable our load balancing mechanism to be maintained accurately. As a result, our improvement evaluated by simulated results depicts a good degree of load balance as well as query efficiency.

Knowledge is considered as a resource that contributes an important role in the success of Six Sigma DMAIC methodology. However, knowledge resides brain of the individuals and exists in various forms and different places. This rise the problem of how to collect and share DMAIC knowledge everywhere all time. In this paper, we introduce a proposed Knowledge Portal named KPD that had been designed as a tool to manage DMAIC knowledge. Through the deployment of the Knowledge Portal, this paper aims at investigating its impacts on DMAIC execution based on experiments and appreciation of experts who are working in the areas of quality management and information technology. The results of the survey reveal that KPD benefits DMAIC deployment and impacts positively on the success of DMAIC through its knowledge management process.

DHT-based P2P networks such as Chord, CAN, Pastry, etc can achieve exact query with characteristic of scalability, efficiency and fault-tolerate. However, in the case of complex queries such as range query or multiple-attribute query, pure DHT is not efficient since a lot of query messages must be sent. In this paper we focus our intentions on multiple-attribute query on DHT-based P2P network systems. Conventional researches meet a problem arising from the load unbalance among nodes due to the appearance of common attribute/value pairs (AV pairs) in content names (i.e. AV pairs those appear in a lot of content names). We propose a hierarchical key generation approach for storing and querying multiple-attribute contents. The main idea of our proposed system is to limit the number of information contents distributed by one key to a node by the use of sub-keys created from multiple common AV pairs. Sub-keys, by which the total number of information contents in the system are already distributed is not over N MAX , will be used as distribution keys to distribute information contents. Furthermore, our system keeps the mapping between sub-keys created from two common AV pairs and distribution keys created from two more common AV pairs to reduce query cost. Our system can achieve both efficiency and a good degree of load balancing even when the distribution of AV pairs in content names is skewed. Our simulation result shows the efficiency of our solution in respects of lookup time and the degree of load balancing.