Reviewerly/exHarmony huggingface dataset:
TPCx-AI: First Adopter’s Experience Report

This paper provides a report based on the first TPCx-AI benchmark publication.
Benchmarking Considerations for Trustworthy and Responsible AI (Panel)

Continuing growth of Artificial Intelligence (AI) adoption across enterprises and governments around the world has fueled the demand for trustworthy AI systems and applications. The need ranges from the so-called Explainable or Interpretable AI to Responsible AI, driven by the underlying demand for increasing confidence in deploying AI as part of Enterprise IT. Both internal to organizations as well as external, customer- and user-facing use cases based on AI are increasingly being expected to meet these demands. This paper describes the need for and definitions of trustworthiness and responsibility in AI systems, summarizes currently popular AI benchmarks, and deliberates on the challenges and the opportunities for assessing and benchmarking Trustworthy and Responsible aspects of AI systems and applications.
More the Merrier: Comparative Evaluation of TPCx-AI and MLPerf Benchmarks for AI

With AI systems and solutions increasingly being deployed across many industries, measuring performance of AI workloads remains a priority in computing. TPCx-AI is a new benchmarking suite developed by TPC to address this need. It provides an alternative to MLPerf benchmarking suite that has already been adopted by many of the main players in AI. This paper compares the two benchmarks and shows pros and cons of each. We explain that the two approaches differ in scope, with TPCx-AI attempting to capture end-to-end AI process while MLPerf focuses only on the most computationally heavy AI tasks: Training and Inference. Another significant difference is scoring with TPCx-AI using a single number, while MLPerf using many scores to represent performance at a more granular level. We also present our experience with both suites and offer recommendation when to use each tool.
New Initiatives in the TPC

TPC stands for stricter standards and tougher tests in system benchmarking for over 30 years, during which technology advanced enormously. In order to stay relevant the TPC had to adapt to the advancing technology or become obsolete. Initially, the business use case of computer systems was mainly focused on online transaction processing (OLTP). Hence, the TPC developed a series of OLTP benchmarks, learning valuable lessons along the way (TPC-A, TPC-B, TPC-C and TPC-E). Then the TPC ventured into other use cases such as decision support (TPC-D, TPC-H, TPC-R, TPC-DS), web applications (TPC-App), virtualization (TCP-VMS) and data integration (TPC-DI). When the TPC realized that the old way of developing benchmarks was not sustainable, it added a new way of developing benchmark, express benchmark, which resulted in a flurry of benchmark standards (TPCx-HS, TPCx-V, TPCx-BB, TPCx-HCI, TPCx-IoT and TPCx-AI). With cloud computing becoming more and more important, the TPC made sure that new benchmarks would be able to run in the cloud. At the same time the TPC modified its pricing specification to allow for pricing of cloud based benchmarks.
Disaggregated Database Management Systems

Modern applications demand high performance and cost efficient database management systems (DBMSs). Their workloads may be diverse, ranging from online transaction processing to analytics and decision support. The cloud infrastructure enables disaggregation of monolithic DBMSs into components that facilitate software-hardware co-design. This is realized using pools of hardware resources, i.e., CPUs, GPUs, memory, FPGA, NVM, etc., connected using high-speed networks. This disaggregation trend is being adopted by cloud DBMSs because hardware re-provisioning can be achieved by simply invoking software APIs. Disaggregated DBMSs separate processing from storage, enabling each to scale elastically and independently. They may disaggregate compute usage based on functionality, e.g., compute needed for writes from compute needed for queries and compute needed for compaction. They may also use disaggregated memory, e.g., for intermediate results in a shuffle or for remote caching. The DBMS monitors the characteristics of a workload and dynamically assembles its components that are most efficient and cost effective for the workload. This paper is a summary of a panel session that discussed the capability, challenges, and opportunities of these emerging DBMSs and disaggregated hardware systems.
The Case for Quantification

Abstract This chapter sets the stage for the rest of the book by introducing notions fundamental to quantification, such as class proportions, class distributions and their estimation, dataset shift, and the various subtypes of dataset shift which are relevant to the quantification endeavour. In this chapter we also argue why using classification techniques for estimating class distributions is suboptimal, and we then discuss why learning to quantify has evolved as a task of its own, rather than remaining a by-product of classification.
Video Watermarking With Digital Signature and Fingerprinting

A digital watermark, which is embedded in an image sequence or video frames as the form of a binary string or visual logo, is a small size of visible data. Thus, the quality of embedded videos is often slashed due to the watermarking. Comparative video watermarking is a highly innovative method that was designed to unravel this issue. In this chapter, the authors make use of singular value decomposition (SVD) and discrete wavelet transform (DWT) for video watermarking; the authors employed inverse transform (IDWT) to extract the video watermark. The digital signature is also utilised to increase the authenticity of watermarks and verify any changes. The authors combine this approach with digital fingerprinting as well as to get the improved results. Throughout the designed attacks, the merits of the new watermarking paradigm such as robustness, convergence, and stability are attained with security and authenticity by calculating the metrics such as MSE, PSNR, entropy, SSIM, etc.
A New Efficient Crypto-Watermarking Method for Medical Images Security Based on Encrypted EPR Embedding in Its DICOM Imaging

Digitalization of media has exploded in recent years. It has resulted in the rise of private data hacking, which has been increased by the growth of the data exchange system, i.e., the Internet, as well as the simple access to storage media. New approaches, such as watermarking in (C. Iwendi et al., 2020; D. Datta et al, 2021; Randhir Kumar et al,2021), are being used to combat these hackers. The application of image watermarking technologies to medical images, as proposed in (Nazari, M., et al, 2021; Thanki, R, 2021; Manoj K., 2020), is the focus of this research. In this chapter, we propose a new robust blind crypto-watermarking solution for medical imaging or DICOM file (Digital Imaging and Communications in Medicine) security based on masking (or hide) electronic patient information (patient name, patient ID, patient age...) in its medical imaging, then, erases them from the tag of the DICOM. Before being included into medical imaging, DICOM patient information, or EPR, is encrypted using a modified AES (Advanced Encryption Standard) encryption technique. The image is broken into 8x8 pixel chunks. In each block, we use the 2D-LWT (Lifting wavelet transform), 2D-DCT (discrete cosine transforms), and SVD (singular value decomposition) to insert one bit of the encrypted watermark into the hybrid transform domain. Various attacks, such as noise, filtering, scaling, and compression, are used to test the method. According to the obtained results the watermark (EPR) is imperceptible in the imaging, and the suggested technique has passed the attacks test with success.
Novel Fast Improved 3D S-Box-Based Cryptography Algorithm for Protecting DICOM Images

Data encryption is one of the security solutions used to protect secret data. The use of image encryption techniques in DICOM (digital imaging and communications in medicine) data to secure it in unprotected networks or storage is the focus of this chapter. Therefore, based on the improvement of a 3D (three dimension) s-box proposed previously, the authors provide a novel efficient images encryption method for medical imaging. The technique also encrypts the DICOM tags and Jpeg compressed DICOM imaging because 512-bit-based blocks of data are processed. A function named encrypt_block() is used for the diffusion and confusion. This function processes a block with subblocks each of 8-bit. For each subblock it uses the s-box for data transformation. The cryptanalysis of the proposed encryption system shows its strength and security. The runtime and the speed of the algorithm demonstrate its low time complexity, which makes it suitable for much electronics hardware, especially embedded systems.
On the issue of cultural (African) specifics of "responsible artificial intelligence"

The article deals with the problems associated with the socio-cultural specifics of the development of practical principles of "responsible artificial intelligence (AI)". At present, much attention of researchers is attracted by the African continent, stereotypes about which were associated with backwardness and underdevelopment. Currently, African countries, while effectively building their economic strategies, are also using AI technologies. The concept of Umeå University professor Virginia Dignum, which she outlined in one of the sections of the book “Responsible AI in Africa. Problems and Opportunities” (Springer, 2023). The main logic of Professor Dignum's theory is that all the consequences of using AI technology do not depend on AI, but on the socio-cultural characteristics of the socio-techno-anthropological environment in which these technologies are applied. Using Ubuntu philosophy as an example, Virginia Dignum shows how the sociocultural philosophical aspects of "non-Western" philosophy can be applied to the creation of new socioethical principles that emphasize the cultural diversity of modern AI ethics. The position of Virginia Dignum's theory on the sociocultural specifics of the ethics of "responsible AI" seems to be important, which, in our opinion, can be adapted for various sociocultural spaces that, to one degree or another, do not coincide with the Anglo-American paradigm of economic civilization.
Effective Moving Object Detection Using Background Subtraction in Stationary Wavelet Domain

Moving object detection is a fundamental task on smart CCTV systems, as it provides a focal point for further investigation. In this study, an algorithm for moving object detection in video, which is thresholded using a stationary wavelet transform (SWT), is developed. In the detection steps, the authors perform a background subtraction algorithm; the obtained results are decomposed using discrete stationary wavelet transform 2D, and the coefficients are thresholded using Birge-Massart strategy. This leads to an efficient calculation method and system compared to existing traffic estimation methods.
Reflection and Construction on the Operation Mode of Medical Data Management Platforms in the Context of the COVID-19 Pandemic

With the development of modern health technology, every aspect of people's clothing, food, housing, and transportation is affected by information data. Doctors can use information data to assist in daily decision-making, enabling patients to enjoy better medical services. With the promulgation of the government's policy on medical treatment in different places, patients need medical institutions to be connected nationwide for subsequent medical insurance reimbursement. This chapter aims to analyze and provide development suggestions for the current EHR system in China through data structure and blockchain technology. This study provides comprehensive processing of patients' health data, promotes the healthy development of the whole medical information-sharing platform, improves the level of medical information data in the entire medical industry, and makes deeper exploitation of medical information.
The Secret Sauce to Blockchain Technology

Today, blockchain technology has become the verdict for almost all sectors including Healthcare. Blockchain technology confides in a distributed and decentralized ledger model. Axiomatically blockchain is more protected and robust as compared to the centralized models which are at present used in various systems. In simple words, blockchain technology is a distributed and immutable record of digital events which is shared from point to point between various participants. This chapter portrays key aspects of blockchain technologies, its characteristic features, and frameworks. Authors have presented the conceptual framework for electronic health record management using consortium blockchain.
Development of EHR Using Blockchain Technology

Electronic health records (EHRs) are the most effective method to store and share patient's data among different hospitals which a patient visits in the over the course of time. Data of the patient's medical history needs to be shared among the various healthcare providers for a better understanding of the patient's progress and to carry on with the treatment. The traditional methodology for storing patient's data poses threat to data integrity, security, reliability, provider and patient trust, interoperability among clients and easy accessibility of personal data. With the advent of blockchain technology and its application in the healthcare sector, it ensures immutability, user data protection and information accessibility to share data in a distributed storage for the verified parties. Blockchain technology provides us with the benefit of storing this data without the possibility of modification in a decentralized manner.
Enhancing the Role of Audit as an Effective Governance Mechanism via Digital Transformation

This paper aims to examine the digital transformation process of audit practices in Malaysia, and to examine how it could improve the role of audit as a governance mechanism. This study applied qualitative research methodology by conducting in-depth semi-structured interviews with six experts in the auditing field. The discussions were made in the following themes: 1) Overview of digital transformation in the audit practices in Malaysia; 2) Digital technologies as tool to improve the role of audit as a governance mechanism; 3) Challenges in the digital transformation of audit practices. The findings of this research mainly indicate that the digital transformation of audit practices in Malaysia is still in its infancy. Through this research, the audit practitioners can be informed of the potential of digital transformation to enhance the role of audit as a governance mechanism and its respective challenges. Therefore, necessary actions to accelerate the digital transformation process can be carried out by the audit industry in Malaysia.
A Study of Data Sources for Accessibility and Reuse Practices among Agricultural Researchers in Tanzania

This paper reports a study that investigated how agricultural researchers use and reuse other researchers’ data in Tanzania. This research used a survey method to investigate the factors influencing researchers in this use/reuse. Findings indicated that more than 80% of researchers use and reuse data accessed from different sources. Several factors influence the majority of researchers (more than 70%) to use and reuse data. The results of this study may attract the attention of agricultural researchers elsewhere to agricultural data use and reuse practices.
Optimization in the Flow of Scientific Newspapers

The evolutions that occurred in the past decades have provoked variations in the market as well as academic and research. Given this scenario, the research explored in this article was aimed to analyze the contribution of the management of PMBOK methods for the optimization of Scientific Editorial Flow. The methodology used presented a quantitative approach, of descriptive character based on a survey, made available on social networks and Facebook groups, through the google forms platform. The sample is given by Snowball, this type of sampling enables the researcher to study specific groups and is difficult to reach. The analysis was by descriptive statistics, using the Likert scale, as well as the weighted average and fashion responses. It was identified that the Critical Success Factors of a Project that can contribute to the optimization of the editorial flow of a Scientific Periodical are efficient communication, empowerment, change management, client involvement, supplier involvement and conflict management.
Risk and Return Analysis of Crypto Currencies in India

The term Cryptocurrency, also referred to as crypto-currency or crypto, is the currency that is digital in nature and traded virtually in a secure manner. Although there is no regulatory body to monitor the issue or regulation of the digital asserts, they have been making the news of late and have captured the hearts of the investors. In recent days, Crypto currencies are the major players in the Coin Market. Today everyone investing in Crypto currencies and they analyses that the Crypto market is efficient or not. This study is based on the Crypto Currencies Market. In this study we used Descriptive statistics, Correlation Matrix test and GARCH Model for the period of 1st Jan, 2015 to 31st Dec, 2021. The study concludes that Crypto currencies in India are highly volatile and traders can able to forecast both Risk and Return in future.
Acceptance and Adoption of Care Robots Among Elderly: A Critical Review of the Ethnographic Production

The progressive aging of Western societies and the challenges this poses for health and care systems has encouraged different types of technology to emerge as realistic solutions for the care of the elderly. Among these, robotic technologies, especially anthropomorphic ones, are becoming increasingly relevant in the care of the elderly. Regarding the acceptance of these technologies, in addition to the classical models of acceptance (TAM, MPT, HMSAM, UTAUT) there is a current of studies that proposes to study in depth the interactions between robots and humans (HRI studies) and in this field the ethnographic method is revealed as an optimal tool for a dense knowledge of the imaginaries and representations of technology, and therefore the elements that underlie its acceptance. Under this premise, the aim of the present work is to map the networks of meanings that operate in the processes of acceptance and adoption of robotic technology oriented to the care of the elderly. For this purpose, an exploratory review has been carried out, analyzing those ethnographic studies that address such processes. The resulting categories are framed within the main debates in HRI studies. The conclusions provide the reader with the deep keys to the acceptance by the elderly of robotic technologies of care.
Construction and analysis of knowledge graphs for multi‐source heterogeneous data of soil pollution

Abstract The decommissioning and overall relocation of urban industrial enterprises have generated a large number of decommissioned contaminated sites, and the leftover soil pollution is gradually becoming a major problem that restricts urban green development and damages human health. Deep mining and efficient management of site soil pollution information through digitization and informatization are needed to solve these problems more accurately and efficiently. Knowledge mapping for visual analysis of relevant pathways is a forward‐looking approach in soil contamination management that does not require complex testing instruments, thus saving research manpower, time and cost. Data associated with contaminated sites come from a wide range of sources and have different structures. Through the natural language processing technology of computer, suitable methods such as entity recognition, relationship recognition and knowledge fusion are selected to extract various types of information from contaminated sites and establish semantic networks for fast targeting of soil contamination sources, thus providing a more convenient solution. In this paper, we propose a knowledge graph construction method for multi‐source heterogeneous data of contaminated sites, find sulphide contamination sources through visual analysis of knowledge graph and explore the application prospects of natural language processing techniques such as knowledge graph in contaminated site management.
Strategy Implementation in a Developing Country Multinational (Etisalat): A Factor-Analytic Investigation

The study aims to explore the factors that may have a significant impact on Etisalat’s strategy implementation in the telecommunications sector. To do so, quantitative method approach was applied through a survey questionnaire that distributed and addressed to the employees of Etisalat. A combination of exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) was used to achieve the study’s objective. Based on an empirical exercise, success factors in the technology strategy implementation are identified, which are planning factors; organizational factors; managerial factors; and individual factors. It provides significant policy implications for Etisalat’s successful implementation of its strategy in the UAE telecommunications market. For example, for successful implementation of strategies, managers must understand the factors required. Successful implementation of Strategy can also help an organization mitigate resistance to change and improve its competitiveness.
Noisy stabilizer formalism

Despite the exponential overhead to describe general multi-qubit quantum states and processes, efficient methods for certain state families and operations have been developed and utilised. The stabilizer formalism and the Gottesman-Knill theorem, where pure stabilizer or graph states are manipulated by Clifford operations and Pauli measurements, are prominent examples, and these states play a major role in many applications in quantum technologies. Here we develop a noisy stabilizer formalism, i.e., a method that allows one not only to efficiently describe and follow pure states under Clifford operations and Pauli measurements but also Pauli noise processes acting on such stabilizer states, including uncorrelated and correlated dephasing and single- or multi-qubit depolarizing noise. The method scales linearly in the number of qubits of the initial state, but exponentially in the size of the target state. Thus, whenever a noisy stabilizer state is manipulated by means of local Pauli measurements such that a multipartite entangled state of a few qubits is generated, one can efficiently describe the resulting state.