Corporate Payout Policy in Japan

This paper examines cash dividends and share repurchases in Japan - discerning between keiretsu and non-keiretsu groupings of firms - during the period 1990 to 2008, a period of extensive Japanese corporate governance reform. As in the United States, share repurchases in Japan have grown strikingly across firm groupings even relative to cash dividends which have also increased. Unlike in the United States, cash dividends remain the dominant form of payout across the groupings of firms in Japan. Despite extensive corporate governance reform, the keiretsu grouping of firms exhibits a comparative reticence to alter its corporate payout policy. In particular, it remains the case that keiretsu firms disburse relatively large amounts of cash, they rely relatively heavily on cash dividends rather than share repurchases, they exhibit a greater tendency to discontinue cash dividend payouts, their payouts are relatively sensitive to earnings and these payouts respond relatively rapidly with respect to earnings. In addition, the cash dividend payouts in keiretsu firms have been relatively concentrated, while these payouts from non-keiretsu firms concentrate increasingly over time. The findings also suggest that larger firms in Japan are more likely to payout and if they decide to do so they tend to payout more. As the level of concentration of ownership in Japanese firms increases the amount of cash dividends disbursed decreases. Privatized firms are more likely to pay cash dividends and if they decide to do so and they are not keiretsu affiliated they tend to payout more.Payout policy, dividends, share repurchases, corporate governance

Transforming Patient Check-in/Registration with a Fast Healthcare Interoperability Resources (FHIR) Integrated QR Code System and Mobile App

The aim of the project is to examine the implementation of universal quick response (QR) codes issued by health insurance providers for patient identification within electronic health records (EHR). The integration of QR codes into EHR using Fast Healthcare Interoperability Resources Application Programming Interface (FHIR API) can help standardize the identification process, making it more efficient and reducing medical errors. These improvements can lead to a reduction in waiting time, improved patient satisfaction and coordination of care. The paper will provide insights on the possibility for widespread adoption of QR codes for patient identification in healthcare and its impact on the overall quality of patient care. The paper will compare current methods of patient identification with the new approach of using universal QR codes, outline the objectives, project timeline, and deliverables. The findings of this project will be important not only for patients but for healthcare providers, health insurance providers, and policymakers

Building Accurate Low Latency ASR for Streaming Voice Search

Automatic Speech Recognition (ASR) plays a crucial role in voice-based applications. For applications requiring real-time feedback like Voice Search, streaming capability becomes vital. While LSTM/RNN and CTC based ASR systems are commonly employed for low-latency streaming applications, they often exhibit lower accuracy compared to state-of-the-art models due to a lack of future audio frames. In this work, we focus on developing accurate LSTM, attention, and CTC based streaming ASR models for large-scale Hinglish (a blend of Hindi and English) Voice Search. We investigate various modifications in vanilla LSTM training which enhance the system's accuracy while preserving its streaming capabilities. We also address the critical requirement of end-of-speech (EOS) detection in streaming applications. We present a simple training and inference strategy for end-to-end CTC models that enables joint ASR and EOS detection. The evaluation of our model on Flipkart's Voice Search, which handles substantial traffic of approximately 6 million queries per day, demonstrates significant performance gains over the vanilla LSTM-CTC model. Our model achieves a word error rate (WER) of 3.69% without EOS and 4.78% with EOS while also reducing the search latency by approximately ~1300 ms (equivalent to 46.64% reduction) when compared to an independent voice activity detection (VAD) model.Comment: Accepted at ACL 2023 Industry Trac

An Efficient Approach to Privacy Preserving Association Rule Mining

The vulnerabilities associated with large databases is increasing with the passage of time and sharing of data over a network becomes a critical issue for every organization. When we talk about data mining approaches,there has been a tremendous success. But when we see the other side of the coin, it has put the databases and its sensitive information on the verge of being modified or altered by unwanted sources. The major problem is still out in there in the middle and we need to create a balance between the data mining results with the appropriate time management to hide the data. The main focus should be on how we can keep our sensitive data private and the sensitive information could not be revealed through data mining techniques with ease. In this thesis, we focus on hiding the sensitive data with a much faster pace as compared to hiding counter algorithm

Investigation of Composite Materials Using Digital Volume Correlation

Composites are growing at a rapid pace for its use in industry such as automobiles because of its high strength to weight ratio and better damage tolerance than traditional materials. The composite structure is non-homogenous and anisotropic. The mechanical behavior of the microstructure is complex under loading. The traditional measurement technique such as strain gauge and extensometer provide limited information. Therefore, to understand the internal structure under loading conditions, there is a need for full field internal displacement and strain field. Digital Volume Correlation (DVC) is a measurement technique which generates a 3D displacement and strain field for the sample under loading. Fused filament fabrication (FFF) and hybrid braided composites has limited research to understand the microstructure behavior non-destructively. Therefore, thesis will explore the application of DVC on FFF and Hybrid braided composites under tensile loading

End-to-End Speech to Intent Prediction to improve E-commerce Customer Support Voicebot in Hindi and English

Automation of on-call customer support relies heavily on accurate and efficient speech-to-intent (S2I) systems. Building such systems using multi-component pipelines can pose various challenges because they require large annotated datasets, have higher latency, and have complex deployment. These pipelines are also prone to compounding errors. To overcome these challenges, we discuss an end-to-end (E2E) S2I model for customer support voicebot task in a bilingual setting. We show how we can solve E2E intent classification by leveraging a pre-trained automatic speech recognition (ASR) model with slight modification and fine-tuning on small annotated datasets. Experimental results show that our best E2E model outperforms a conventional pipeline by a relative ~27% on the F1 score.Comment: Accepted at EMNLP 2022 Industry Trac

The Emerging Epidemic of Obesity, Diabetes, and the Metabolic Syndrome in China

China is one of the fastest developing countries in the world. Rapid economic progress has resulted in changes to both diet and physical activity. New found prosperity, increased urban migration, and the adoption of sedentary lifestyles by an aging Chinese population have resulted in a dramatic shift in disease burden—from infectious to chronic. Modern Chinese find themselves increasingly afflicted with the same noncommunicable chronic diseases typical of industrialized nations. Today, cardiovascular disease is the number one cause of both morbidity and mortality, affecting both rural and urban Chinese. The rising incidence of cardiovascular disease has been fueled by an epidemic of cardiometabolic risk factors. While hypertension and smoking have received considerable spotlight, little attention has been given to obesity, diabetes, and metabolic syndrome. Their increasing prevalence is the focus of this paper

Cash dividends and investor protection in Asia

We study the importance of investor rights in payout policy determination in Asia, using a sample of up to 52,778 firm years. The listed Asian firms located in relatively high investor protection, common law countries, have a greater tendency to payout and, if they do so, they tend to pay out more. We also examine the importance of distinctive creditor and minority shareholder rights in respect to payout policy determination. In our study of a variety of payout events (decisions to pay out, to initiate or omit payout and to markedly increase or decrease payout), we show that this set of payout events is principally determined by competing creditor and minority shareholder rights, rather than managerial sought reputation related effects, to diminish the cost of capital. Our findings indicate that creditors exert significant and far reaching influence over corporate payout policy decision-making, however, the importance of the agency costs of equity predominates

Corporate Payout Policy in Japan

Abstract This paper examines cash dividends and share repurchases in Japan -discerning between keiretsu and non-keiretsu groupings of firms -during the period 1990 to 2008, a period of extensive Japanese corporate governance reform. As in the United States, share repurchases in Japan have grown strikingly across firm groupings even relative to cash dividends which have also increased. Unlike in the United States, cash dividends remain the dominant form of payout across the groupings of firms in Japan. Despite extensive corporate governance reform, the keiretsu grouping of firms exhibits a comparative reticence to alter its corporate payout policy. In particular, it remains the case that keiretsu firms disburse relatively large amounts of cash, they rely relatively heavily on cash dividends rather than share repurchases, they exhibit a greater tendency to discontinue cash dividend payouts, their payouts are relatively sensitive to earnings and these payouts respond relatively rapidly with respect to earnings. In addition, the cash dividend payouts in keiretsu firms have been relatively concentrated, while these payouts from non-keiretsu firms concentrate increasingly over time. The findings also suggest that larger firms in Japan are more likely to payout and if they decide to do so they tend to payout more. As the level of concentration of ownership in Japanese firms increases the amount of cash dividends disbursed decreases. Privatized firms are more likely to pay cash dividends and if they decide to do so and they are not keiretsu affiliated they tend to payout more

iTimer - Count On Your Time

In current lifestyle people tend to waste a lot of time in doing unnecessary activities like watching movies, playing video games, window shopping, etc. Many a times they are not aware of the cumulative time they spend wastefully. They can use their time constructively if they were informed about it through a mobile app. In our project we aim to develop an app which helps in monitoring the amount of time spent in such activities at various locations and inform the user about the same through visual display on Google maps. This app displays the summary of the locations visited during the day along with timestamps for better analyzing of data