BACKGROUND: Photoplethysmography (PPG) is a low-cost and easy-to-implement method to measure vital signs, including heart rate (HR) and pulse rate variability (PRV) which widely used as a substitute of heart rate variability (HRV). The method is used in various wearable devices. For example, Samsung smartwatches are PPG-based open-source wristbands used in remote well-being monitoring and fitness applications. However, PPG is highly susceptible to motion artifacts and environmental noise. A validation study is required to investigate the accuracy of PPG-based wearable devices in free-living conditions. OBJECTIVE: We evaluate the accuracy of PPG signals-collected by the Samsung Gear Sport smartwatch in free-living conditions-in terms of HR and time-domain and frequency-domain HRV parameters against a medical-grade chest electrocardiogram (ECG) monitor. METHODS: We conducted 24-hours monitoring using a Samsung Gear Sport smartwatch and a Shimmer3 ECG device. The monitoring included 28 participants (14 male and 14 female), where they engaged in their daily routines. We evaluated HR and HRV parameters during the sleep and awake time. The parameters extracted from the smartwatch were compared against the ECG reference. For the comparison, we employed the Pearson correlation coefficient, Bland-Altman plot, and linear regression methods. RESULTS: We found a significantly high positive correlation between the smartwatch's and Shimmer ECG's HR, time-domain HRV, LF, and HF and a significant moderate positive correlation between the smartwatch's and shimmer ECG's LF/HF during sleep time. The mean biases of HR, time-domain HRV, and LF/HF were low, while the biases of LF and HF were moderate during sleep. The regression analysis showed low error variances of HR, AVNN, and pNN50, moderate error variances of SDNN, RMSSD, LF, and HF, and high error variances of LF/HF during sleep. During the awake time, there was a significantly high positive correlation of AVNN and a moderate positive correlation of HR, while the other parameters indicated significantly low positive correlations. RMSSD and SDNN showed low mean biases, and the other parameters had moderate mean biases. In addition, AVNN had moderate error variance while the other parameters indicated high error variances. CONCLUSION: The Samsung smartwatch provides acceptable HR, time-domain HRV, LF, and HF parameters during sleep time. In contrast, during the awake time, AVNN and HR show satisfactory accuracy, and the other HRV parameters have high errors.
Apple, Audi, Braun oder Samsung machen es vor: Gutes Design ist heute eine kritische Voraussetzung für erfolgreiche Produkte.
BACKGROUND: Fitness trackers and smart watches are frequently used to collect data in longitudinal medical studies. They allow continuous recording in real-life settings, potentially revealing previously uncaptured variabilities of biophysiological parameters and diseases. Adequate device accuracy is a prerequisite for meaningful research. OBJECTIVE: This study aims to assess the heart rate recording accuracy in two previously unvalidated devices: Fitbit Charge 4 and Samsung Galaxy Watch Active2. METHODS: Participants performed a study protocol comprising 5 resting and sedentary, 2 low-intensity, and 3 high-intensity exercise phases, lasting an average of 19 minutes 27 seconds. Participants wore two wearables simultaneously during all activities: Fitbit Charge 4 and Samsung Galaxy Watch Active2. Reference heart rate data were recorded using a medically certified Holter electrocardiogram. The data of the reference and evaluated devices were synchronized and compared at 1-second intervals. The mean, mean absolute error, mean absolute percentage error, Lin concordance correlation coefficient, Pearson correlation coefficient, and Bland-Altman plots were analyzed. RESULTS: A total of 23 healthy adults (mean age 24.2, SD 4.6 years) participated in our study. Overall, and across all activities, the Fitbit Charge 4 slightly underestimated the heart rate, whereas the Samsung Galaxy Watch Active2 overestimated it (-1.66 beats per minute [bpm]/3.84 bpm). The Fitbit Charge 4 achieved a lower mean absolute error during resting and sedentary activities (seated rest: 7.8 vs 9.4; typing: 8.1 vs 11.6; laying down [left]: 7.2 vs 9.4; laying down [back]: 6.0 vs 8.6; and walking slowly: 6.8 vs 7.7 bpm), whereas the Samsung Galaxy Watch Active2 performed better during and after low- and high-intensity activities (standing up: 12.3 vs 9.0; walking fast: 6.1 vs 5.8; stairs: 8.8 vs 6.9; squats: 15.7 vs 6.1; resting: 9.6 vs 5.6 bpm). CONCLUSIONS: Device accuracy varied with activity. Overall, both devices achieved a mean absolute percentage error of just <10%. Thus, they were considered to produce valid results based on the limits established by previous work in the field. Neither device reached sufficient accuracy during seated rest or keyboard typing. Thus, both devices may be eligible for use in respective studies; however, researchers should consider their individual study requirements.
Designing accurate and efficient ConvNets for mobile devices is challenging because the design space is combinatorially large. Due to this, previous neural architecture search (NAS) methods are computationally expensive. ConvNet architecture optimality depends on factors such as input resolution and target devices. However, existing approaches are too resource demanding for case-by-case redesigns. Also, previous work focuses primarily on reducing FLOPs, but FLOP count does not always reflect actual latency. To address these, we propose a differentiable neural architecture search (DNAS) framework that uses gradient-based methods to optimize ConvNet architectures, avoiding enumerating and training individual architectures separately as in previous methods. FBNets (Facebook-Berkeley-Nets), a family of models discovered by DNAS surpass state-of-the-art models both designed manually and generated automatically. FBNet-B achieves 74.1% top-1 accuracy on ImageNet with 295M FLOPs and 23.1 ms latency on a Samsung S8 phone, 2.4x smaller and 1.5x faster than MobileNetV2-1.3 with similar accuracy. Despite higher accuracy and lower latency than MnasNet, we estimate FBNet-B's search cost is 420x smaller than MnasNet's, at only 216 GPU-hours. Searched for different resolutions and channel sizes, FBNets achieve 1.5% to 6.4% higher accuracy than MobileNetV2. The smallest FBNet achieves 50.2% accuracy and 2.9 ms latency (345 frames per second) on a Samsung S8. Over a Samsung-optimized FBNet, the iPhone-X-optimized model achieves a 1.4x speedup on an iPhone X. FBNet models are open-sourced at https://github. com/facebookresearch/mobile-vision.
Purpose Extensive research has shown that country‐of‐origin (COO) information significantly affects product evaluations and buying behavior. Yet recently, a competing perspective has emerged suggesting that COO effects have been inflated in prior research and even that the COO concept has become irrelevant. The purpose of this paper is to reconcile these two competing perspectives by examining the effects of individual brand origin perceptions. Design/methodology/approach The conceptual framework is grounded in consumers’ learning. Empirically, the authors’ hypotheses are tested using hierarchical linear modeling on a sample of 4,047 brand evaluations by 544 consumers. Findings The results provide strong evidence that product country image of the consumer's perceived brand origin strongly affects brand attitudes, and this happens regardless of the perceptions’ objective accuracy. The authors also find evidence that educating consumers about brands’ true COO can contribute to changes in brand attitudes. Practical implications It is concluded that suggestions that COO has become an irrelevant construct in international marketing may be premature. The study offers meaningful insights for managers in understanding how brands’ country associations affect brand attitudes. Originality/value This study aims to reconcile tensions in the current COO literature and does so by demonstrating that although consumer knowledge of brand origin is often mis‐calibrated, consumers’ perceptions of brand origin still matter.
OBJECTIVE: Recent evidence suggests that alcoholic fatty liver disease (AFLD) and non-alcoholic fatty liver disease (NAFLD) may differentially affect risk of cardiovascular mortality. To investigate whether early liver disease due to AFLD or NAFLD have similar or dissimilar effects on risk of early coronary artery atherosclerosis, we have investigated the associations between AFLD and NAFLD and coronary artery calcium (CAC). DESIGN: A cross-sectional study was performed in 105 328 Korean adults who attended a health check-up programme. CAC score was assessed using CT, daily alcohol intake was recorded as grams/day and liver fat by ultrasound. Logistic regression model was used to calculate ORs with 95% CIs for prevalent CAC. RESULTS: Both NAFLD and AFLD were positively associated with CAC score. After adjusting for potential confounders, multivariable-adjusted OR (95% CIs) for CAC >0 comparing NAFLD and AFLD to the reference (absence of both excessive alcohol use and fatty liver disease) were 1.10 (95% CI 1.05 to 1.16) and 1.20 (95% CI 1.11 to 1.30), respectively. In post hoc analysis, OR (95% CI) for detectable CAC comparing AFLD to NAFLD was 1.09 (95% CI 1.01 to 1.17). Associations of NAFLD and AFLD with CAC scores were similar in both non-obese and obese individuals without significant interaction by obesity (p for interaction=0.088). After adjusting for homeostasis model assessment of insulin resistance and high-sensitivity C reactive protein, the associations between fatty liver disease and CAC scores remained statistically significant. CONCLUSION: In this large sample of young and middle-aged individuals, early liver disease due to NAFLD and AFLD were both significantly associated with the presence of coronary artery calcification.
Purpose This paper seeks to introduce a six‐sigma based methodology for the SCM domain which was developed and has been used in Samsung. Design/methodology/approach The paper provides a detailed description of how and why a six‐sigma‐based methodology for the SCM domain was developed in Samsung and presents a real industry case to illustrate the usage of the methodology. Findings In Samsung, the effort and investment in synthesizing SCM and six sigma, and developing a unique six‐sigma‐based methodology to improve its SCM operation, have turned out to be fruitful. The Black Belt program has produced highly qualified and talented SCM specialists, who are currently training the methodology to members in their organizations and leading SCM projects. SCM projects are being prepared and conducted in a more disciplined way and their outcomes are continuously monitored and shared through the company's repository. Research limitations/implications To generalize its usefulness, the methodology needs to be applied to the SCM projects of those companies whose organizational and cultural contexts are different from those of Samsung. In addition, the overview of an illustrative SCM project presented in the paper is brief due to space limitations. Practical implications Today, SCM is increasingly recognized as a strategic way to innovate a company's business operation. This paper shows that a methodology such as Samsung's SCM six sigma can be the key to conducting SCM projects in a more disciplined way and for fruitful outcomes. Originality/value The paper introduces a unique six‐sigma‐based methodology for the SCM domain which has been developed and applied in a leading global manufacturing, financial, and services conglomerate. This methodology could be adapted by other companies for their SCM projects to increase the likelihood of project success.
Academic achievement is one of the major subjects in the educational researches.Academic achievement is defined as the outcomes of the education. Preventingstudents from failure is related with identifying the factors affecting the achievement.By defining the important factors affecting the students’ achievement, failure can beunder controlled [Ozguven, 1974]. Education is a complex process and many factorsdirectly or indirectly may affect achievement. Besides, it is difficult to properly definethe major factors influencing students' achievement. Although researchers haveidentified several factors affecting the student achievement, there are still somearguments about them. Some researchers attribute the student’s achievement to theschool; others indicate that the school makes little impact on academic outcome. Otherresearchers say that the effective teacher is the only one who can play the main role interms of student progress. All the factors such as teacher, school context, classroomcontext and the community around the school contribute or impact student’sachievement somehow [Harris, 1999]. In all these thoughts, we can see that there arethree common factors affecting the students’ achievement. Factors related withteachers, students and lastly environment. All these factors are affective on thestudents’ grade more or less. In our research, we handle the students’ perspective andsearch for the factors affecting the students’ achievement i n their demographic itemssuch as age, sex, and their academic background such as high school type, grade,University Entrance score, their families’ social and economic status, income, housing,computer knowledge skills and social behaviors and mannerism. The aim of this studyis to find out what kinds of factors have effects on students’ exam success among thestudents at School of Transportation and Logistics by using the path analysis.
This study tried to investigate the reason concerning the purchase decision of smartphone. The variables that is used are brand image and product price of Samsung smartphone. The descriptive quantitative research methods with a non purposive sampling was implemented by involving two independent variables Brand Image, and Product Price and one dependent variable Purchase Decision, The result showed that customer not just only influenced by the product but also the price as well. The researcher suggests to add another factor for increasing the value of R square.
BACKGROUND: Overt and subclinical hypothyroidism are associated with higher levels of serum creatinine and with increased risk of chronic kidney disease (CKD). The prospective association between thyroid hormones and kidney function in euthyroid individuals,however, is largely unexplored. METHODS: We conducted a prospective cohort study in 104 633 South Korean men and women who were free of CKD and proteinuria at baseline and had normal thyroid hormone levels and no history of thyroid disease or cancer. At each annual or biennial follow-up visit, thyroid-stimulating hormone (TSH), free triiodothyronine (FT3) and free thyroxin (FT4) levels were measured by radioimmunoassay. The study outcome was incident CKD, defined as an estimated glomerular filtration rate (eGFR)<60 ml/min/1.73 m2 based on the Chronic Kidney Disease Epidemiology Collaboration creatinine equation. RESULTS: After a median follow-up of 3.5 years, 1032 participants developed incident CKD.There was a positive association between high-normal levels of TSH and increased risk of incident CKD. In fully-adjusted models including baseline eGFR, the hazard ratio comparing the highest vs the lowest quintiles of TSH was 1.26 [95% confidence interval (CI) 1.02 to 1.55; P for linear trend=0.03]. In spline models, FT3 levels below 3 pg/ml were also associated with increased risk of incident CKD. There was no association between FT4 levels and CKD. CONCLUSIONS: In a large cohort of euthyroid men and women, high levels of TSH and low levels of FT3, even within the normal range, were modestly associated with an increased risk of incident CKD.
Abstract: This article contributes to the small but growing geographic literature on the internationalization of retailing by exploring the strategic localization of transnational retailers. While it has long been recognized that firms in many different sectors localize their activities to meet the requirements of different national and local markets, the imperative is particularly strong for retail transnational corporations (TNCs) because of the extremely high territorial embeddedness of their activities. This embeddedness can be seen through the ways in which retailers seek to establish and maintain extensive store networks, adapt their offerings to various cultures of consumption, and manage the proliferation of connections to the local supply base. We illustrate these conceptual arguments through a case study of the Samsung‐Tesco joint venture in South Korea, profiling three particular aspects of Samsung‐Tesco's strategic localization: the localization of products, the localization of sourcing, and the localization of staffing and strategic decision making. In conclusion, we argue that the strategic localization of transnational retailers needs to be conceptualized as a dynamic that evolves over time after initial inward investment and that localization should be seen as a two‐way dynamic that has the potential to have a wider impact on the parent corporation.
Of late, deep neural networks have become ubiquitous in mobile applications. As mobile devices generally require immediate response while maintaining user privacy, the demand for on-device machine learning technology is on the increase. Nevertheless, mobile devices suffer from restricted hardware resources, whereas deep neural networks involve considerable computation and communication. Therefore, the implementation of a neural-network specialized hardware accelerator, generally called neural processing unit (NPU), has started to gain attention for the mobile application processor (AP). However, NPUs for commercial mobile AP face two challenges that are difficult to realize simultaneously: execution of a wide range of applications and efficient performance.In this paper, we propose a flexible but efficient NPU architecture for a Samsung flagship mobile system-on-chip (SoC). To implement an efficient NPU, we design an energy-efficient inner-product engine that utilizes the input feature map sparsity. We propose a re-configurable MAC array to enhance the flexibility of the proposed NPU, dynamic internal memory port assignment to maximize on-chip memory bandwidth utilization, and efficient architecture to support mixed-precision arithmetic. We implement the proposed NPU using the Samsung 5nm library. Our silicon measurement experiments demonstrate that the proposed NPU achieves 290.7 FPS and 13.6 TOPS/W, when executing an 8-bit quantized Inception-v3 model [1] with a single NPU core. In addition, we analyze the proposed zero-skipping architecture in detail. Finally, we present the findings and lessons learned when implementing the commercial mobile NPU and interesting avenues for future work.
Penelitian ini bertujuan untuk mengetahui pengaruh citra merek, harga dan promosi terhadap keputusan pembelian Handphone Samsung di Yogyakarta. Metode pengambilan sampelnya mengunakan Convenience Sampling, dengan jumlah responden 65 orang. Metode analisis data yang digunakan dalam penelitian ini adalah metode analisis regresi linear berganda. Berdasarkan hasil uji t dapat diketahui bahwa variabel promosi berpengaruh secara signifikan terhadap keputusan pembelian, sedangkan variabel citra merek dan harga tidak berpengaruh secara signifikan terhadap keputusan pembelian Kata Kunci : Citra Merek, Harga, Promosi dan Keputusan Pembelian
SLIM is a set of methodologies and scheduling applications for managing cycle time in semiconductor manufacturing. SLIM includes methodology for calculating target cycle times and target WIP levels for individual manufacturing steps, heuristic algorithms for factory floor scheduling, and optimization-based capacity analysis. Between 1996 and 1999, Samsung Electronics Corp., Ltd., implemented SLIM in all its semiconductor manufacturing facilities. It reduced manufacturing cycle times to fabricate dynamic random access memory devices from more than 80 days to less than 30. Considering the decline of selling prices for dynamic random access memory devices, SLIM enabled Samsung to capture an additional $1 billion in sales revenue compared to the revenue it would have realized had cycle times not been reduced.
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Explores the connection between knowledge management (KM) and process innovation (PI). Although these are popular themes in the literature on management innovation, there is not much discussions of these issues. On the one hand, KM has been treated as a managerial fad that is mainly focused on knowledge generation, dissemination, and utilization. Moreover, the advocates of KM seem to be concerned with building knowledge management systems (KMS). On the other hand, PI is regarded as an efficiency‐oriented process redesign and re‐engineering (or BPR), which seems to be nothing to do with KM. However, the case study of Samsung SDI shows that in the real world KM is deeply linked with PI. For illustrating the KM strategy of Samsung SDI, uses the term “PI‐based KM”. Sheds light on two points: the features of process knowledge can be studied in the sense that knowledge associated with process is dubbed “process knowledge”; and socio‐cultural features of KM should be illustrated in terms of knowledge transformation path in the information space.
To determine overall detection rates of lung cancer by low-dose CT (LDCT) screening and to compare histopathologic and imaging differences of detected cancers between high- and low-risk groups, this study included 6,406 asymptomatic Korean adults with >or=45 yr of age who underwent LDCT for lung cancer screening. All were classified into high- (>or=20 pack-year smoking; 3,353) and low-risk (3,053; <20 pack-yr smoking and non-smokers) groups. We compared CT findings of detected cancers and detection rates between high- and low-risk. At initial CT, 35% (2,255 of 6,406) had at least one or more non-calcified nodule. Lung cancer detection rates were 0.36% (23 of 6,406). Twenty-one non-small cell lung cancers appeared as solid (n=14) or ground-glass opacity (GGO) (n=7) nodules. Cancer likelihood was higher in GGO nodules than in solid nodules (p<0.01). Fifteen of 23 cancers occurred in high-risk group and 8 in low-risk group (p=0.215). Therefore, LDCT screening help detect early stage of lung cancer in asymptomatic Korean population with detection rate of 0.36% on a population basis and may be useful for discovering early lung cancer in low-risk group as well as in high-risk group.
The Samsung Exynos family of cores are highperformance “big” processors developed at the Samsung Austin Research & Design Center (SARC) starting in late 2011. This paper discusses selected aspects of the microarchitecture of these cores - specifically perceptron-based branch prediction, Spectre v2 security enhancements, micro-operation cache algorithms, prefetcher advancements, and memory latency optimizations. Each micro-architecture item evolved over time, both as part of continuous yearly improvement, and in reaction to changing mobile workloads.
Preface. Chapter 1. Sony and Samsung: Portraits of Two Global Competitors. Part 1: Strategic Analysis. Chapter 2. Prince and Pauper in the Analog World. Chapter 3. Digital Dream Kids and the Digital Sashimi Shop. Chapter 4. New Kids on the Block. Chapter 5. Wannabe Globals. Part 2: Organizational Process and Leadership. Chapter 6. Same Silos but Different Outcomes. Chapter 7. From Founders to Professionals Managers. Chapter 8. The Future of Sony and Samsung Electronics. Endnotes. Glossary. Index.
This study aims to analyze the effect of Product Quality and Price on Purchase Decisions and their impact on Repurchase on Samsung smartphone consumers in the city of Jakarta. The population in this study are consumers who have purchased and used Samsung smartphone products located in the city of Jakarta. The number of samples used is based on the number of indicators multiplied by 5 to obtain 180 respondents. The research data was obtained through a survey conducted using a questionnaire and data analysis using Partial Least Square (PLS) version 3.0. The results showed that product quality and price had a positive and significant effect on purchasing decisions, product quality had no effect on repurchases, prices had a positive and significant effect on repurchases, and purchase decisions were not able to mediate the relationship between product quality and repurchase, but were able to mediate relationship between Price and Repurchase.