Digital Computer Methods Research Articles

A practitioner-centered policy roadmap for ethical computational social science in Germany, Austria, and Switzerland.

Background: Computational Social Science (CSS) utilizes large digital datasets and computational methods to study human behavior, raising ethical concerns about data privacy, informed consent, and potential misuse.Methods: This study employs a constructivist grounded theory approach, analyzing 15 in-depth interviews with CSS practitioners in Germany, Austria, and Switzerland. These countries share a European legal context regarding data privacy and hereby provide a comparable regulatory environment for examining ethical considerations.Results: Findings highlight key challenges in CSS research, including power imbalances with data providers, uncertainties around surveillance and data privacy (especially with longitudinal data), and limitations of current ethics frameworks. Researchers face tensions between established ethical principles and practical realities, often feeling disempowered and lacking support from ethics boards due to their limited CSS expertise. Regulatory ambiguity further discourages research due to fear of sanctions.Conclusions: To foster responsible CSS practices, this paper recommends establishing specialized ethics boards with CSS expertise. It also advocates for acknowledging CSS's unique nature in research policy by developing tailored data guidelines and providing legal certainty through clear guidelines. Grounding recommendations in practitioners' experiences, this study offers actionable steps to help enable ethical CSS research.

Social resilience of Pudak Sari Kelapa shop production business actors through digitalization of MSMEs in Gresik

This research is motivated by the threats that MSMEs face in the digital age and must overcome to remain relevant and sustainable. One of the major challenges comes from the large number of similar business competitors as well as the Covid-19 pandemic, which has drastically changed consumer behavior. The purpose of this research is to determine the social resilience of Pudak Sari Kelapa Shop production business actors through the digitization of MSMEs in Sukodono Village, Gresik District, Gresik Regency. This research uses a qualitative research method with a case study approach. Supported by the theory of social resilience as an analytical tool to explain the digitalization of MSMEs by Pudak Sari Kelapa Shop production business actors. The research results show that there are main aspects in the formation of social resilience of business actors, namely stability, adaptation and transformation. Digitization of MSMEs is not only a means of survival, but also a driver of sustainable business transformation. For example, the implementation of accounting transactions through digital computer methods, payment methods through Qris, and then marketing and selling products through social media and marketplaces. As well as shop renovation efforts that are strengthened by individual resilience, namely the ability to manage emergency fund reserves.

Semantic Web Practices: Infrastructural Politics and the Future of the Web

Semantic Web Practices: Infrastructural Politics and the Future of the Web

Intratumoral heterogeneity of Ki67 proliferation index outperforms conventional immunohistochemistry prognostic factors in estrogen receptor-positive HER2-negative breast cancer.

In breast cancer (BC), pathologists visually score ER, PR, HER2, and Ki67 biomarkers to assess tumor properties and predict patient outcomes. This does not systematically account for intratumoral heterogeneity (ITH) which has been reported to provide prognostic value. This study utilized digital image analysis (DIA) and computational pathology methods to investigate the prognostic value of ITH indicators in ER-positive (ER+) HER2-negative (HER2-) BC patients. Whole slide images (WSIs) of surgically excised specimens stained for ER, PR, Ki67, and HER2 from 254 patients were used. DIA with tumor tissue segmentation and detection of biomarker-positive cells was performed. The DIA-generated data were subsampled by a hexagonal grid to compute Haralick's texture indicators for ER, PR, and Ki67. Cox regression analyses were performed to assess the prognostic significance of the immunohistochemistry (IHC) and ITH indicators in the context of clinicopathologic variables. In multivariable analysis, the ITH of Ki67-positive cells, measured by Haralick's texture entropy, emerged as an independent predictor of worse BC-specific survival (BCSS) (hazard ratio (HR) = 2.64, p-value = 0.0049), along with lymph node involvement (HR = 2.26, p-value = 0.0195). Remarkably, the entropy representing the spatial disarrangement of tumor proliferation outperformed the proliferation rate per se established either by pathology reports or DIA. We conclude that the Ki67 entropy indicator enables a more comprehensive risk assessment with regard to BCSS, especially in cases with borderline Ki67 proliferation rates. The study further demonstrates the benefits of high-capacity DIA-generated data for quantifying the essentially subvisual ITH properties.

Quantify the Political Bias in News Edits: Experiments with Few-Shot Learners (Student Abstract)

The rapid growth of information and communication technologies in recent years, and the different forms of digital connectivity, have profoundly affected how news is generated and consumed. Digital traces and computational methods offer new opportunities to model and track the provenance of news. This project is the first study to characterize and predict how prominent news outlets make edits to news frames and their implications for geopolitical relationships and attitudes. We evaluate the feasibility of training few-shot learners on the editing patterns of articles discussing different countries, for understanding their wider implications in preserving or damaging geopolitical relationships.

Digital Melville and Computational Methods in Literary Studies

Abstract: The use of computational tools for the study of literature can facilitate new perspectives and avenues for critical work. Reflecting on the recent emergence of (and increasing hype around) large languages models such as GPT, this essay argues that the creation of "smart" data sets and corpora as new forms of literary objects requires and enables the development of computational methods and tools that can create "data stories". Smart data sets continue a humanistic tradition of textual scholarship and bibliography while also preparing text data to be "read" by machines. In telling "data stories" about Herman Melville, we bridge the gap from "numbers to meaning" in a variety of examples from Billy Budd . The essay closes with a broader reflection on reading Melville in the age of machine learning and artificial intelligence.

ZnO microrods sandwiched between layered CNF matrix: Fabrication, stress transfer, and mechanical properties

Functional metal oxide particles are often added to the polymers to prepare flexible functional polymer composites with adequate mechanical properties. ZnO and cellulose nanofibrils (CNF) outstand among these metal oxides and the polymer matrices respectively due to their various advantages. Herein, we in situ prepare ZnO microrods in the presence of CNF, which resultes in a layered composite structure. The ZnO microrods are sandwiched between the CNF layers and strongly bind to highly charged CNF, which provides a better stress transfer during mechanical activity. Digital image correction (DIC) and finite element analysis-based computational homogenization methods are used to investigate the relationship between mechanical properties and composite structure, and the stress transfer to the ZnO microrods. Full-field strain measurements in DIC reveal that the in situ ZnO microrods preparation leads to their homogenous distribution in the CNF matrix unlike other methods, which require external means such as ultrasonication. The computational homogenization technique provides a fairly good insight into the stress transfer between constituents in microstructure as well as a good prediction of macroscopic mechanical properties, which otherwise, would be challenging to be assessed by any ordinary mechanical testing in the layered composites. Finally, we also demonstrate that these composites could be used as physiological motion sensors for human health monitoring.

The computational turn in online mental health research: A systematic review

Digital trace data and computational methods are increasingly being used by researchers to study mental health phenomena (i.e. psychopathology and well-being) in social media. Computer-assisted mental health research is not simply a continuation of previous studies, but rather raises ethical, conceptual and methodological issues that are critical to behavioural science but have not yet been systematically explored. Based on a systematic review of n = 147 studies, we reveal a multidisciplinary field of research that has grown immensely since 2010, spanning the humanities, social sciences, and engineering. We find that a substantial majority of studies in our sample lack a standardized form of ethical consideration, focus on specific constructs and have a rather narrow focus on specific social media platforms. Based on our findings, we discuss how computational elements have influenced mental health research, highlight academic gaps and suggest promising directions for future studies.

PWL-Based Architecture for the Logarithmic Computation of Floating-Point Numbers

In this brief, we propose a logarithmic converter for floating-point numbers based on the piecewise linear (PWL) approximation method. The proposed method is applicable to any customized floating-point format with a mantissa length of 16–23 bits and a maximum absolute error (MAE) larger than 10−6. The logarithmic function is automatically segmented into several maximal subsections by a software-based segmentation scheme with the restriction of a predefined MAE and a fractional word length for the computing units. Then, we make a tradeoff between the piecewise number and the fractional word length. Based on the results of the segmentor, our design is coded in the Verilog hardware description language. The synthesized results show that our design consumes less area, time, and power without compromising accuracy compared to existing techniques based on the COordinate Rotation Digital Computer (CORDIC) and PWL methods.

Modeling COVID 19: The Value of Practice

The necessity of developing models that effectively organize data for the purpose of translating basic science to clinical care is being increasingly recognized. Reliance upon digital computational methods restricts the value of natural experience reportable by patients, often considered subjective. In the course of modeling phosphate metabolism in the context of clinical practice it has become evident that use of categories based on normality, as definition of health, is inconsistent with the experience of patients. Given the opportunity, patients can provide detailed observations upon their experience of heat as the principle component of metabolism. It seems logical that heat should also be the foundational principal component of models developed for the translation of data to clinical care. This strategy has been applied to modeling the role of ACE2 in the expression of variable phenotypes of COVID 19. Attempts to engage massive data and super-computing to the modeling of COVID 19 supported the assumption that ACE2 is a critical component causing disease. The finding is attributed to an influence, not on heat, but instead suggested bradykinin that has long been a proposed explanation for ACE inhibition on chronic cough. Our modeling would posit that the ACE system engages aldosterone and subsequent influence on heat and acid/base balance as the mediators of variance in the expression of individual phenotypes. This clarification has been useful for addressing complexity in the presentation of metabolic disorders including thyroid disease, Diabetes, bone health, sleep disorders, vascular disease and Chronic Fatigue Syndrome. It appears that the risk of developing ARDS shares a predisposition to chronic kidney disease mediated by excessive FGF23 effects, while the asymptomatic spreaders are more Klotho dependent. The vitamin D system is also complex and involved in the modulation of heat and phosphate. These and other components can be extended to understanding bone and the hematopoietic marrow niche governing immune responses and includes a role for modulation of the microbiome influences by ACE2.It is concluded that SARS-CoV-2 has helped to clarify the complexity of biology and has exposed the limitations of modeling strategies that do not include the application of case-based practice that can be described as “model-dependent realism” 1 as a means to discover the principle components of nature. The models are the valued product of the research that is mandated by the Helsinki accords when outcomes do not meet expectations. These models can facilitate the organization of all data in the appropriate translation to clinical care.1 Hawking S., Mlodinow L. The Grand Design p 39–59, Bantom Books NY, 2010

Modern aspects of determining dental color in aesthetic dentistry

One of the important factors for creating a beautiful smile is the color of the teeth, which for most people has a more important role than anatomical characteristics. The exact reproduction of the color of the tooth affects the appearance and psycho-emotional state of the patient. The purpose of this work is to review domestic and foreign literature on methods for determining the color of teeth. Methods for determining color are divided into visual, spectrophotometric, colorimetric, digital photo analysis and computer method. The most common in the practice of a dentist is visual, which is based on comparing the examined tooth with color templates. Determination of the color of teeth using scales does not give a reliable result, which is due to the small number of shades in the colors, the phenomenon of metamerism, the impossibility of converting the obtained data into digital values, etc. The hardware method for determining the color of teeth compensates for the disadvantages of the visual and has a high adaptability, which requires many interrelated factors. Due to the complexity and high cost, the devices are used mainly for research purposes. Currently, innovative methods for determining the color of teeth, based on digital and computer analysis, are being actively developed. Thus, hardware methods for determining the color of teeth significantly increase the accuracy of choosing the shade of a future aesthetic restoration or orthopedic construction, excluding subjective factors, however, they require mandatory certification. Correct color assessment and identification helps to reduce costly re-treatments and reduce warranty costs. Despite this, visual methods using scales remain in demand among practicing doctors, due to their low cost and ease of use. The accuracy of determining the color of teeth in this case depends on the professionalism of the dentist, as well as on the correctness of the photo protocol.

A Novel Coordinate Rotation Digital Computer Method for Energy and Latency Saving by Trigonometric Operations Spatial Locality Principle

In this work, we propose an approximate and energy-efficient CORDIC method, based on a trigonometric function spatial locality principle derived from benchmarks profiling. Successive sine/cosine computation requests cover more than 50% when the absolute phase difference is at most ten degrees. Consequently, this property suggests an optimized circuit implementation, both iterative or a succession of microrotation modules, where the last CORDIC requires fewer iterations, reducing the latency and the total energy budget at the same precision of two separate and independent instances. Thus, this simple design strategy allows significant area and energy dissipation in general-purpose VLSI architectures, but it introduces also dramatically optimizations in applicationspecific embedded systems used in the area of signal processing and radio frequency communication. In this contribution, we introduce a method, the hardware overhead and the energy budget per single cycle. Simulation results show the total energy saving in considered benchmarks is 40% in pipelined and iterative general purposes CORDIC. Furthermore, our application-specific systems (fast Fourier transform and digital oscillators for radiofrequency down conversions) show remarkable cycle savings when the successive sine/cosine computation requests are more than 70%. Finally, in this work, we extend the proposed approach to whichever phase difference less than 26.56° , as a variable for the second CORDIC number of angle rotations.

Distant reading as a strategy of an exact study of bibliography

In recent times marked by the offensive and largescale advancement of computer technol-ogy numerous libraries, scientific and educational centers in the world are creating their own extensive databases of literary and bibliographic texts. Facing such databases the close reading method designed to work with specific texts would seem to lose its meaning. The Italian sociolo-gist and literary critic Franco Moretti became the main critic of the close reading. He presented his ideas in the book «Distant Reading». This book can be viewed as a program to update the methodology of studying world literature. Moretti believes that the world literature should be studied not by looking at the details, but by examining it from a long distance: studying hudreds and thousands of texts. He suggest to use the Digital Humanities (DH) methods, i.e. to ap-ply digital (computer) methods in the humanities. To show the reasons for the survival of certain types of texts, Moretti compares literary processes with biological ones and draws an anology between natural selection and reader selection. Moretti’s predecessor, who first used quantitative methods in literary studies and saw common ground between literary and biological processes, was the author of the fundamental monograph “Methodology of an exact study of literature” B. I. Yarkho (18891942).Moretti’s book “Distant Reading” shatters stereotypes of the bibliographic environment. It is directed no to the study of close (slow) reading, but to the study of the entire world docmentary flow. This approach opens the way to the use of quantitative methods in the study of world bibliography. A new research strategy “exact study of bibliography” will be formed as part of digital and automated text processing.

A computer assisted automatic grenade throw training system with simple digital cameras

Grenade throwing is a routine military training and testing subject among many armies of the world. However, the conventional manual measurement mode has many defects: poor efficiency, large training field needing and important data losing. So how to utilize simple device and simple method framework to replace the actual test procedure becomes an interesting issue. In this paper, we present a real-time computer assisted grenade throwing training system by simple digital camera and low-cost computational methods. In this system, firstly, the marked grenade is extracted from the camera video frames; Secondly, a linked list is generated to store the grenade pixel coordinate; Thirdly, after a transformation from image space to real space, the instantaneous velocity of throwing (initial speed) can be computed; Lastly, a virtual 3D scene is established to demonstrate the training activity. By using this system, an overall throwing result data (distance, height, throwing angle, throwing speed and ballistic trajectory) can be obtained. The most significant novelty of our application is achieving a real-time computer assisted grenade throwing training system by simple and low-cost computational methods. In addition, we proposed a specialized self-adapted color enhancement method in the system. This computation strategy may provide some enlightenments for other research work. From the test data of several hurlers, it can be seen that the effectiveness and the accuracy of this training system are favorable. This system may provide technical support for the modern military throwing training and may change the traditional manual measuring mode for grenade throwing.

Prediction of the moderator temperature field in a heavy water reactor based on a cellular neural network

Reactors with heavy water coolants and moderators have been used extensively in today's power industry. Monitoring of the moderator condition plays an important role in ensuring normal operation of a power plant. A cellular neural network, the architecture of which has been adapted for hardware implementation, is proposed for use in a system for prediction of the heavy water moderator temperature. A reactor model composed in accordance with the CANDU Darlington heavy water reactor design was used to form the training sample collection and to control correct operation of the neural network structure. The sample components for the adjustment and configuration of the network topology include key parameters that characterize the energy generation process in the core. The paper considers the feasibility of the temperature prediction only for the calandria's central cross-section. To solve this problem, the cellular neural network architecture has been designed, and major parts of the digital computational element and methods for their implementation based on an FPLD have also been developed. The method is described for organizing an optical coupling between individual neural modules within the network, which enables not only the restructuring of the topology in the training process, but also the assignment of priorities for the propagation of the information signals of neurons depending on the activity in a situation analysis at the neural network structure inlet. Asynchronous activation of cells was used based on an oscillating fractal network, the basis for which was a modified ring oscillator. The efficiency of training the proposed architecture using stochastic diffusion search algorithms is evaluated. A comparative analysis of the model behavior and the results of the neural network operation have shown that the use of the neural network approach is effective in safety systems of power plants.

Frequency Convolution for Implementing Window Functions in Spectral Analysis

Windowing is a common method to reduce spectral leakage in Fourier analysis. Based on the principle that time domain multiplication corresponds to frequency domain convolution, this paper suggests frequency convolution to implement windowing functions by FIR filter structure. The proposed digital filter has full compatibility for variable length of window and is capable of implementing the three most popular windows, viz. Hanning, Hamming and Blackman. Numerical simulation indicates that the method consumes $$78\,\%$$78% less area, $$11\,\%$$11% higher throughput rate than the CORDIC-based (co-ordinate rotation digital computer) method, and achieves $$33\,\%$$33% lower quantization error for fixed point than the time domain multiplication method. Furthermore, an example of stretch processing in HF radar is shown to reduce the $$99\,\%$$99% computational complexity because of the segmental frequency points windowing.

Development of dus standard for taro [Colocasia esculentavar.antiquirom(L.) Schott.] using digital morphometrics

The leaves, tubers and other morpho-culinary characters of nine taro [Colocasia esculenta var. antiquirom (L) Schott.] cultivars were considered for development of distinct, uniform and stable (DUS) standards using digital morphometrics and computational methods besides taking help from prototypes of hand-held digital field guides and various robotic systems to bring them under IPR-related regimes. Out of 48 morphoculinary characters studied maximum were polymorphic in nature. Some cultivars possessed unique stable characters helpful for their identification. The study revealed that DUS descriptors using digital morphometrics can be used effectively for identification and grouping of taro germplasm.

Turan M Itil.

In 1929 Hans Berger, a German sanitarium psychiatrist, recorded the brain's continuing electrical rhythms from the intact scalp of his daughter and a laboratory assistant. He described changes in response to eye-opening, arithmetic tests, sleep, and such drugs as morphine, cocaine and chloroform. Soon thereafter, the treatments of insulin coma, induced seizures, and lobotomy were introduced for the severe psychiatric ill. Each altered the EEG rhythms galvanizing psychiatrists who studied the effects on the EEG to understand how these treatments worked. When chlorpromazine and imipramine were introduced to the clinic, Turan Itil was among the first to study their effects on the EEG. At the CINP meeting in Rome in 1958, our independent reports were so similar that each could have used the other's slides and data. In 1964 he came to St Louis to establish the Neurophysiology Laboratory at the Missouri Institute of Psychiatry using newly developed digital computer methods to measure EEG changes. Reliable quantitative methods were used to predict the clinical applications of putative psychoactive drugs, to separate clinically active from inactive substances, and to suggest dosage ranges. In 1972 he was asked to profile GB-94 (mianserin), a new agent developed by Organon scientists. He found the EEG patterns in human volunteers and patients to be identical to those of imipramine. His report conflicted with the predictions made by the Organon pharmacologists in their animal models. Based on Turan's prediction, clinical trials did show clinical antidepressant activity and mianserin was successfully marketed as Tolvon, verifying the usefulness of the pharmaco-EEG prediction model. Were the EEG effects of psychoactive substances in animals predictive of their effects in man? Pharmacologists opined that the EEG changes induced by drugs in animal trials were dissociated from behavior, and not predictive of human drug effects, challenging the nascent pharmaco-EEG science. By1966 presentations at the CINP in Washington showed that EEG and behavior were associated in humans, and that EEG studies of potential psychoactive medicines could be used to predict human applications. This critical determination established pharmaco-EEG as a human science. Throughout his life Turan was at the heart of this science. He described the effects of natural and synthetic hormones, psychostimulants, and cognitive enhancers. In his later years he established outpatient clinics assessing dementia by EEG and computerized neuropsychological tests. He was a founder of the International Pharmaco-EEG Group (IPEG), an active scientific member of ACNP and CINP and numerous other EEG and psychopharmacology societies (Itil 1998, 2011). Werner Herrmann in Berlin, Bernd Saletu in Vienna, Masami Saito in Osaka, and Sevket Akpinar in Ankara, each a leader in pharmaco-EEG science, were his students. Turan was a consultant and lead scientist on projects of the World Health Organization. Turan Itil was born in Bursa, Turkey, on 12 August 1924. He received the MD degree from Istanbul University in 1948 and moved to the University of Tubingen in Germany for training in neurology. In 1953 he joined the faculty at the University of Erlangen, with EEG and psychopharmacology the center of his research. After a decade in St Louis, he moved to New York Medical College and established the HZI Research Center Laboratory in Tarrytown, New York. He was a vibrant, enthusiastic, and warm-hearted man. He played intensely, and enjoyed ping-pong, billiards, and roulette. He supported friends and colleagues enthusiastically. He adjusted to the American culture but on retirement he returned to his family in Turkey. He died at his country home on 29 April 2014 at the age of 89. He and his wife Ellen had two children, Kurt and Yasmin. He leaves an extended family in Turkey and New York, friends and students around the world, and a unique body of psychopharmacology science.

Fabricating Complexity - A Performance Based Methodology through Parametric Optimization

This paper discusses the integration of advanced computational design and digital fabrication methods through the project Light-Vault, which addresses the development and execution of complex designs resulting in a performance based approach through optimization. The project shows the development of a vault which is made through an assemblage of customized multiple components, which are parametrically controlled and evaluated with respect to light and weight. Due to influence of multiple fitness parameters a genetic algorithm is created and new methodology is developed for the evolution of the form. Algorithms are developed to ensure design thinking and fabrication procedures are simultaneously developed in a non-linear, parallel performance based process. This logical approach investigates the various possibilities and optimizes the development and fabrication of ruled surfaces in the interior volume of the component using digital methods and translation of the form into reality using industrial robots for fabrication. In parallel, the project explores the potential of robotic technology and introduces innovations of personalized robotic tools, in generating quick shaping volumes through this process. The developed methodology is tested in creating multiple units of the vault which are analyzed against various evaluation criteria. This cumulative cohesive process between advanced digital and physical computation methods is translated through a full-scale built pavilion.

Data point weighting in pharmacokinetic analysis: intravenous paracetamol in man.

Compartmental analysis of plasma paracetamol concentrations following intravenous injection of 12 mg kg-1 in aqueous solution to normal subjects was performed using analogue and digital computer methods. Using a "simplex" non-linear optimization procedure, the pharmacokinetic parameters were found to be influenced considerably by the choice of the weighting factors (W1) attributed to individual data points. The plasma half-life of paracetamol varied by up to a seven-fold with the weighting factors selected. However, the predicted mean steady-state plasma concentrations were shown to be relatively little affected by the different weighting factors.