bluuebunny/crossref_metadata_2025 huggingface dataset:
Interference-Normalized Least Mean Square Algorithm: A Comparative Study
Authors: Tejasri P.N.S. , Anusha K. , Sangeet Kumar K. , Venkatesh Nukella , Yamini Devi Y.
Published: January 2023

A general least mean square interference technique is provided for effective adaptive filtering. The gradient adaptive learning rate methodology can now handle non-stationary data with the Interference normalised least mean square technique. Because of issues like duplicate talk and echo route variance, echo cancellation is made more difficult because the learning rate must be adjusted. Frequency domain echo cancelers learn at different rates, which can be altered in a novel fashion. Normalized least mean square method normalised learning rate under noise is used to calculate an optimal learning rate. This double-talk detection technique exceeds the competition while also being incredibly simple to implement. A number of least mean square (LMS)-type algorithms have been investigated in place of their recursive equivalents of IVM or TLS/DLS, which involve large calculations. As a result of these findings, we provide a consistent LMS type technique for the data least squares estimate problem. This unique approach normalizes step size and estimates the variance of the noise in a heuristic manner using the geometry of the mean squared error function, resulting in rapid convergence and robustness against environmental noise.
CNN Based Animal Repelling Device for Crop Protection
Authors: Amarendra Ch. , Rama Reddy T.
Published: January 2023

The use of modern IoT technology in agricultural regions has been the subject of much research and several attempts. This paper’s main goal is to protect the crop against animal assaults. Traditional methods apply the same level of security to all sorts of animals identified using a Passive IR sensor, and only single-stage protection is used. With the aid of Support Vector Machine and Convolution Neural Network algorithms, the photos were properly recorded and recognized, and the information was delivered to the farm owner via IoT devices. A section of the farm was used to create the project. On either side of the entry, cameras were installed to record images for processing to identify the animals, and different levels of security were applied based on the animal identification. The dB level of the reciprocating sound will fluctuate according to the animal. Different levels of protection and different forms of protection are used depending on the classification of the animals. Making noise and lighting from the opposite side sends the animal out of the farm in the first degree of protection. The collected photographs are sent to the owner at the second level. The suggested method’s accuracy may be determined by comparing it to the standard technique’s complexity, implementation cost, reciprocating time, and animal detection accuracy.
Permissions Based Android Vulnerability Detection and Classification Based on Severity Using Machine Learning
Authors: Lochanan M Aravindha , Jaysankar Rohit , Subramanian Narayanan
Published: January 2023

With the sudden upswing in digitization, usage of Android smartphones has evidently become conventional and common. Nevertheless, such extensive popularity of Android systems comes with a major trade-off between usage and security. Time and again, it has been proven that the existence of malicious applications leverage permissions given by the Android systems in order to compromise them. However, there exist certain combinations of permission sets that could potentially lead to such attacks. To address this, we propose a two-layer architecture, where each layer has an implicit handshake with a Machine Learning ensemble model, that aims at vulnerability detection as well as classification of these detected vulnerabilities into one among the three levels of severity – High Risk, Medium Risk and Low Risk. Efficiency of the proposed system has been evaluated against existing Machine Learning based models such as K-Nearest Neighbors (KNN), Decision Tree Algorithms and Multi-Layered Perceptron (MLP) on an Android Permission-Based Dataset. Results show that our proposed model outperforms the existing approaches, which has been quantitatively evaluated using accuracy and F1-score.
Visualizing Medical Flowers Details by Using Deep Neural Network
Authors: Rajesh Kumar K , Subhashini S. J.
Published: January 2023

Flowers are essential to human survival because they give food, shelter, medicine, and environmental protection. They are a variety of flowers with therapeutic properties and active substances for medical purpose. Many beneficial flower species are becoming extinct and being damaged as a result of factors such as global warming, rising population, professional secrecy, lack of government funding for research efforts, and lack of understanding about medicinal flowers. Manually identifying medicinal flowers is a time-consuming task that need the assistance of professionals. For increased value to humanity, computerized identification and categorization of medicinal flowers is required to solve this challenge. In today’s world, automated detection and categorization of medicinal flowers is a hot topic in visual processing research. The primary processes in the identification of medicinal flowers and the classification process, which measure the final accuracy of the classification system, are feature extraction and classification. This study reviews the research on image processing approaches for identifying and classifying medicinal flowers, as well as their relevance and advantages in recent years.
Design of UDS Protocol in an Automotive Electronic Control Unit
Authors: Shridhar Kuntoji Madhumati , Medam Venkatanarasimharao , Devi S.V Veena
Published: January 2023

In automotive, diagnostics is manditorily required to be performed on every ECU (Electronic Control Unit) to ensure that there is no any problem with the electronically controlled components of the vehicle. Today ECU is used in almost every vehicle as an electronic device. Recent automobiles consist of more than 80 ECU for different tasks such that every ECU or group of ECU will perform their dedicated functions. This paper explains about configuration of clock modules for microcontroller based on motor controller applications and also deals with the implementation of UDS (Unified Diagnostic Service) protocol according to the standard ISO 14229-1 which is being used by diagnostic system to communicate or to transfer the data between client & server.
A Decentralized Storage System for 3D Medical Data with Dynamic AES and AES-GCM Encryption
Authors: Aditya G , Lavanya V
Published: January 2023

The rapid digitalization of healthcare records has accelerated adoption of automated healthcare solutions. But healthcare records associated with patients can reach orders of petabytes in a few years. Therefore, to completely harness the full potential of digital healthcare technologies, scalable yet secure storage solutions are needed. Tamper-proofing medical records on decentralized storage, paired with data encryption can solve this problem. This paper proposes a working solution for this purpose using Storj as the underlying decentralized storage technology. In addition, a combination of Dynamic AES and AES-GCM is used for lossless content encryption. The viability of the proposed solution is discussed using quantitative and qualitative methods.
Efficacy of Dimensionality Reduction Techniques and 2D Features in Classification of EEG Data
Authors: Chaudhary Anuradha , Tyagi Aruna
Published: January 2023

EEG-based BCIs enable a direct path for the human brain to communicate with external devices. The main objective of BCI is to classify brain signals to control some applications of interest. EEG is a paradigm that helps to obtain the brain signals from the different states of the human brain. EEG signal feature extraction is a critical topic in brain signal processing that has attracted great attention nowadays with the emergence of large-scale data. The focus of this paper is to reduce the dimension and redundancy of raw EEG data to facilitate retrieval of selected dynamic information. Three approaches of feature extraction and dimensionality reduction viz. PCA, LDA and ICA have been implemented on EEG datasets recorded during attention and meditation state of the brain. Moreover, as massive amount of information about the relationship between time and frequency coefficients is mostly missing in EEG dataset. hence, 1D feature set has been transformed into 2D images. The efficacy of the proposed methods has been tested through the CNN classifier for the classification of EEG signals. The experimental results show that the proposed method is able to achieve an average classification accuracy of 100%.
High Performance Area Efficient Scalable In-Place Real Valued FFT
Authors: Padmavathi A , Sumalata G L
Published: January 2023

An approach for formulating an area-latency and optimized architecture for an in RFFT is outlined in this study. In this paper, modified butterfly block with an addition of re programmable clock divider for generation of variable clock has been proposed. Because of its numerous uses in traditional digital signal processing and other developing domains, efficient computing of the real-valued Fast Fourier transform (RFFT) has got attention in recent years. Scalable in-place RFFT structure for larger inputs and efficiency with high throughput which is an important scenario that leads to the increase in size of memory and accessing issues of storage memory. A butterfly block, that does the computations of butterfly unit per clock period, is typical in an in-place FFT configuration. Study suggests that the in-place FFT can significantly improve the butterfly block structures and thereby providing reduction in parameters such as area occupancy and time delay. However, by changing the structure of butterfly blocks at higher input implementations, fourier transform calculations can be made such that good efficiency is obtained. Every application has several modules that run at different speeds, that needs clock which can be programmable according to the application’s parameters. To address this, a reprogrammable clock divider was implemented, and the parameters efficiency was studied and determined to be improved timing and area to existing implementations. The proposed method is implemented using Xilinx ISE 14.7 and the area, delay of existing and implemented designs are compared.
IoT-Enabled Air Pollution Monitoring Systems: Technologies, Solutions, and Challenges
Authors: Kaur Surleen , Sharma Sandeep
Published: January 2023

Air quality is a crucial aspect of the overall health of any ecosystem. Rapidly increasing urbanization and transportation have proven detrimental to the quality of the air we breathe. Nearly two-thirds of urban air pollution is caused due to vehicular emissions. The harmful pollutants released every day into the atmosphere are deteriorating the environmental and human health. Air pollution has been closely associated with climate change as well as some serious health issues. Hence there is an urgent need for consistent, large-scale air quality monitoring and mitigation strategies. In recent years, the Internet of Things, with its wide range of technologies and some distinct attributes like connectivity, sensing, analyzing and processing capabilities, scalability, and flexibility has provided the world with a dependable option to monitor air pollution in real-time. This paper discusses the key technologies which support IoT-enabled air pollution monitoring systems, proposed solutions, and the challenges faced in the deployment of real-time pollution monitoring systems.
Wheeled Robotic Arm Using Arduino Controlled Through Bluetooth
Authors: Kumar Ayush , Shankrat Mradul , Gurung Aditya , Subhra Kundu Sankha , Gehlot Yash , Ranjan Rajeev
Published: January 2023

The proposed work is to design an Arduino-controlled two-wheeled Bluetooth robotic arm for control purposes. The arm mechanism works either by an outdoor user or by preset command. The medication and trade fields are the most developed field regarding the usage of this technology. The design will allow our robotic arm to exercise in four different axes (directions) with four servomotors. It can also take the objects from one place to other with the help of the geared motors and wheels attached to the holder. And jointly combines and works it with the fabric it receives. This mechanism is controlled with the help of the automation application controlled with the help of the HC-05 Bluetooth module linked to the Arduino Uno. The code is programmed to manage the working of servomotors. This design is similar to some robotic cranes, or we can turn it into a robotic crane with some adjustments. It is highly used in the manufacturing plants, Industrial sector for Automation, Agricultural and medical fields.
Mutated PSO Tuned PID Parameters for SEPIC Converter
Authors: Amarendra Ch. , Chandra Sekhar O. , Rami Reddy Ch. , Srinivasa Varma P. , Ravi Kumar D. , Parveen M. D.
Published: January 2023

Photovoltaic systems have become widely recognized as a realistic and viable source of power. The PV panel output voltage is strongly dependent on solar parameters, which is one of the most critical issues with PV systems. As a result, PV panel output cannot be directly linked to loads. To act as an interface between PV panels and loads, a SEPIC Converter is necessary. The DC-DC boost converter keeps the PV system’s output voltage constant. It transforms variable PV panel input voltage to output voltage maintained constant via output capacitors to the loads. The duty ratio affects the output voltage of a typical SEPIC converter. The output voltage will fluctuate if the input voltage changes while the duty ratio remains fixed. The duty ratio is regulated depending on the input voltage to achieve a constant output voltage. The input voltage is used to alter the duty ratio. In PV systems, PID controllers are widely utilized as SEPIC converter controllers. The PID controller parameter is tuned to enhance the controller’s operating range. SEPIC converters Kp, Kd, and Ki under various input voltage conditions. The regulated SEPIC converter serves as a link between the solar panels and the SEPIC converter’s load. A unique PID controller was used for a SEPIC converter for control to get the voltage controller in a PV system. When compared to a closed-loop SEPIC converter, the optimized PID SEPIC converter for PV systems provides the optimum performance. The simulation findings confirm that the SEPIC converter controller in a PV system is effective and trustworthy.
A Survey on IoT Based Intrusion Detection System and Its Security for Smart Homes
Authors: Keerthi J. , Bhanu Naveen Teja K. , Rama Seshu V. , Phani Sridhar A. , Kiruthika Devi B.S.
Published: January 2023

As more devices are connected to the internet to broaden their operational capabilities and pave the way for the Internet of Things, technology is advancing daily in the modern world (IOT). With their IOT connectivity, these IOT devices exchange the data they have gathered. There will be certain challenges as humanity advances into the future. Online security has emerged in order to provide or enhance security for various IoT-based devices and smart homes. Various architectures and technologies that aid in preventing or detecting these attacks are thoroughly described in this study. They include anomaly, signature, and machine learning techniques. The performance of the techniques, tools, benefits, and limitations are compared and contrasted.
Study of Linear Regression Prediction Model for American Stock Market Prediction
Authors: Chauhan Karan , Sharma Nitin
Published: January 2023

A difficult task in the financial market is to make accurate stock market predictions. This is because there are plenty of factors that affect the price of a company’s stock. Even a single bad tweet can affect the price of a stock. As a result, making an exact prediction is a difficult task. Many scientists are working to find a solution that can withstand a wide range of factors and still provide an accurate result. Supervised learning model called linear regression have produced excellent predictions in a variety of fields over the last few decades. In these studies, a model is designed to predict the stock market prediction by using linear regression. The model is evaluated by using the dataset of three best companies that is (Walmart, Tesla, and Amazon) listed on the American stock exchange called NASDAQ and the result is analyzed in terms of root mean squared error. Then the following results are compared with other machine learning models that is Random Forest and Support Vector Machine. In all cases, linear regression gives the best results.
Assessment of Radiation Density of Cell Phone Tower for Epidemiological Studies
Authors: Vijay Singh Indra , Singh Setia Maninder , Seth Bageshree , Revati N.
Published: January 2023

In this paper the state of art study is being done to create awareness and evaluate the level of surface power density emitted from base transceiver (BTS) at different horizontal distances and frequencies, in Navi Mumbai region. A NARDA SRM-3006 kit was used to measure the maximum surface power density in broadband region. The highest power level was found within 40–50m from the tower, ≈ 427.00 mW/m2 (frequency band 26.00MHz to 3.00 GHz). This power level was more than the limit of exposure level recommended by International Commission on Non-Ionizing Radiation Protection (ICNIRP). However, the distance from the BTS Antenna more than 50m and at same frequency, the observed exposure levels were below the ICNIRP limit but more than the limit values, recommended by some countries (≤ 1mW/m2) and researchers. The power density ∼ 24.3 mW/m2 (maximum peak) was found at 350m distance from the tower. The power dependencies algorithm on frequency has been verified and it is observed that power level reduced by ∼ 40% to ∼96% , by reducing the frequency from 2000.00MHz to 500.00 MHz, respectively at fixed distance from the BTS. The results of this study informed that the surface power density levels significantly varied with distance, direction, characteristics impedance of medium and frequency. Therefore, these facts need to be incorporated for determining the public health guideline regarding cell phone towers. Now, this study can further be utilized in future for auditing the power density radiated from BTS for epidemiological studies.
An Intelligent Flood Automation System Using IoT and Machine Learning
Authors: Verma Bhumika , Yudheksha GK  , Sanjana Reddy P , Maheswari.R  , Parvathi.R  , Vignesh U
Published: January 2023

Floods are one of the most common and well-known natural calamities that create havoc, causing damage to one’s life and economy while adversely affecting the environment. This Research focuses on receiving emergency notifications whenever the situation is critical and also being able to predict the flood in time by automatically measuring the riverbed water level periodically. In this work, the objective is to measure the level using ultrasonic sensors and process the acquired data using ESP8266, where the information will be transferred to ThingSpeak IoT cloud which uses HTTP Protocol over Local Area Network thus enabling it to graphically monitor the world. It checks whether it is not exceeding the threshold limit and when it reaches beyond the limit the system should be able to alert individuals through Telegram and web cloud application, and when the system predicts a flood in the following timeline. Here the Servo Motor acts as a dam gate i.e., it opens when the flood is alerted and closes back once it reaches below the threshold value. For prediction, various machine-learning algorithms such as Random Forest, Support Vector Machine, KNN, Decision Tree, and Logistic Regression were implemented. Due to its high accuracy of about 95%, the logistic regression model was considered suitable for predicting the changes and detecting various possibilities.
Deep Neural Network Inference via Edge Computing: On-Demand Accelerating
Authors: Singh Mahesh K. , Karthik M. , Ramesh P. , Rama Naidu G.
Published: January 2023

Deep Neural Networks (DNN) are a vital technology for allowing Artificial Intelligence applications in the 5G future, and they’ve gotten a lot of press. Complex DNN-based activities are difficult to run on mobile devices. Edge computing was introduced in this research as a solution to these problems. Edge makes use of two design features: DNN partitioning and DNN right-sizing. The training technique provides information about the training. Preserving Edge is a very dynamic filtering approach for video images. Filters for edge preservation are vital tools for the many tasks involved in image processing and transformation. Nonlinear algorithms calculated the filtered grey value according to the contents of a certain neighborhood. Only for the average pixels evaluated with the same grey values are these taken on the basis of the list of neighborhood pixels. While one of their common features is the conservation of the rim, each edge preserving filter is characterized by its own individual algorithm.
A Hybrid Approach to Food Delivery for the Health Management System
Authors: Vignesh U. , Mukherjee Atrim
Published: January 2023

Rapid Industrialization and advancements in technology have had a heavy toll on the food industry. Cases of obesity, diabetes type 2, and other lifestyle-related non-communicable diseases are on the rise in the current population. To prevent further deterioration of human health, it is required to devise an effective diet regimen, one in which the attrition is lesser. A software-based approach has an edge over other conventional methods in getting people to shape. But in a software-based approach, the responsibility of creating the diet gets shouldered on the person making him more likely to quit the program. Therefore, a better approach would be a union of the software-based approach and the food delivery system. The food delivery component plays an important part in delivering the food from the nearest available vendor to the person saving the person’s time and effort. Besides, it is also important that the person has the flexibility to change the food being delivered without undermining the nutritional standard set by the dietitian. Therefore, the elements like “saving time and effort” and “flexibility” play an important part in reducing attrition among the participants.
The Power Quality Improvement in Distribution System for Unbalanced and Faulty Conditions by Using MMC-DSTATCOM
Authors: Ramakrishna E. , Bharath Kumar M. , Jaya Krishna G. , Sujatha P.
Published: January 2023

This study examines the performance of a modular multi level converter with a half bridge sub-module (HBSM)-based seven level distribution static synchronous compensator (MMC-DSTATCOM) in low voltage micro grids under unbalanced and flawed system conditions. For MMC- DSTATCOM, the phase angle control algorithm served as the outside control and the phase shift carrier PWM served as the interior control with capacitor balanced control. The effectiveness of MMC-DSTATCOM is investigated in MATLAB/Simulink for a number of simulations, including reactive power compensation, unbalanced, and defective grid scenarios.
Analysis of Autism Recognition from a Preliminary Symptom
Authors: Ravi Chandana D. , Joseph Sneha M. , Gamini Sridevi
Published: January 2023

Autism is a category of beginning sign of deficiency in early phase of life and difficult to detecting, particularly in small children. This is for the reason that the autism symptoms are depend on the reaction of children to their cognitive function. On the other hand, if autism is not distinguished and delighted among the age of 2–5 years. The treatment next to a later on next phase, it becomes more complicated. Furthermore, a lot of parents are not capable to articulate each and every one of the symptoms, that children is familiarity. In this article, planned a method for indicating the probable symptom starting the beginning indication through with the preceding extended expression patient report to identify the appropriate autism category. Here the proposed method applies equally the used machine learning algorithm as well as confabulation speculation to get ready a medium which assist for receiving each category of relations for producing the rules. The clarity is used to calculate the frequencies of occurrence on a couple of provisional objects. Hence it is used for coupling of symptoms to forecast the subsequently the most feasible and convinced symptom for appropriate identification of autism. By using this method, it can identify both the ordinary and uncommon type of autism. For observing the autism identification contrivance uses a lesser amount of reminiscence for its implementation. It is quicker for the reason that single instance database admittance as compare by using the Apriority algorithm.
Microstrip Antenna for 5G Millimetre-Wave Applications
Authors: Surya Jyothi M. , Sai Prasanna S. , Prasad K L V , Kumar Sanjeev
Published: January 2023

In this paper, a single element antenna is presented for 5G millimeter wave (mm Wave) applications and using single element can be made for MIMO, array of antenna. The bandwidth value of the presented antenna is 11.1 GHz (from 25.1 GHz to 36.2 GHz) and overall size is only 11.5 × 12.5 mm2. It shows that very good candidate for 5G applications. Future wireless communications services require high data rates as technology is progressing. Multi-input multi-output (MIMO) technology for emerging and future wireless communications systems is seen as a fundamental requirement. Technologies like data rate improvements, transmission speed, channel capacity and throughput increase the performance of wireless communication systems substantially. On the side of the transmitter and the receiver, MIMO antennas are several. The design of effective MIMO antennas with a high rate of data and large capacity presents various obstacles.
Kinematic Analysis and Modeling of the Gait by Parameterization of Body Trajectories of a Quadruped Robot
Authors: Kumar Singh Prashant , Kumar Jitendra
Published: January 2023

Kinematic analysis of legged robotic systems is our focus of study in this paper. The detailed forward and inverse kinematic analysis of the quadruped robots using the geometric method has been discussed in this paper. DH convention is used to assign frames to the link of a quadruped robot. The gait of the quadruped robot under study depends upon many things like type of motion, mobility constraint, terrain structure, etc. The configuration of a quadruped robot for one complete gait cycle is shown with the help of a stick diagram. Time variations of kinematic quantities like joint angles and angular velocity of the knee and hip have been studied. In the future, we have a plan to generate the optimal gait of a quadruped robot on uneven terrain.
Dengue Disease Forecasting: Current Outbreak and Diagnostic Model’s Analysis
Authors: Kaur Supreet , Sharma Sandeep
Published: January 2023

The global burden of infectious Dengue disease remains a tricky bomb as its explosion is no longer restricted to tropical/subtropical regions anymore, also the absence of a globally approved vaccine is still there. Continuous research is done to devise systems that could timely predict, diagnose, and treat patients to effectively lessen the yearly Dengue death toll worldwide which resulted in a regular escalation of research in this area. This paper aims to perform a quick effective review of studies done till December 2020, emphasizing forecasting of Dengue epidemiology covering a range of factors such as diagnostics, surveillance, and prognosis prediction so that the intended reader can get an overall scheme of the current research progress well as obstacles regarding Dengue infection. This study points out numerous predictive approaches to Dengue investigation and several open issues which require further investigation eg: human mobility, mosquito breeding sensory reporting, diagnosis of dengue warning stages which may lead to a more accurate and detailed dengue patient prediction and care model. This paper has a good blend of papers encompassing various research directions both traditional and innovative in Dengue epidemiology which are further sub grouped according to their proposed approach and objectives to enhance understanding.
Social Robots in Care Facilities: Reflections on Current Research and the Potential of Ethical Visions
Authors: Remmers Peter , Fischer Nele
Published: January 2023

Research and development of robots for health and elder care is guided by political, economic and technological visions that imagine social robots as a way to address the future care crisis caused by demographic change. Within that vision, robots were originally imagined as substitutes or assistants for care givers, thereby increasing efficiency and mitigating the lack of personnel. On a practical level, however, this overarching image of robots doing genuine care is neither technologically feasible nor aligned with practices of good care. But although this image is more or less abandoned in professional discourse, the expectation that the use of robots will somehow address the care crisis remains. This discrepancy creates special problems for embedded ethicists. We present findings from interviews and workshops with care workers that question the vision of robots as a technological solution for a societal challenge. In conclusion, this development seems to severely limit social human-robot interaction to a merely instrumental role.
Two Issues with the Empathy-Based Argument Against Robot-Physicians
Authors: Malbois Elodie
Published: January 2023

The development of social robots in medicine is an important area of development in robotics. It is possible that in the future, robots will become able to (partly) replace physicians. Several authors think robots ought not to replace physicians because they cannot be empathic, and empathy is necessary for good are. In this paper, I show that although widely accepted, this argument rests on two questionable assumptions. The first one is that because empathy is highly beneficial to care, it is necessary for good care. The second is that because empathy is necessary for good care performed by humans, it is also necessary for good care performed by robots. I discuss these two assumptions and show that the empathy-based argument against the use of social robots in medicine is not as convincing as we might have originally thought. I conclude that we need to explore further what good care is and the role that empathy plays in it.
The Significance of the Sense of Touch for the Use of Social Robots in Care Settings
Authors: Apostolova Iva
Published: January 2023

There are two main goals I set out to achieve here. On the one hand, I intend to delve deeper into the exploration of the sense of touch, which has been largely ignored by philosophers, including empirically minded ones. And on the other hand, albeit not decisively conclusive, my claim is that there are important boundaries of the implementation of social robots in a care setting such as long-term care facilities based on interactive limitations. The limitations in the interactions between human subjects (both care recipients and care givers) and social robots are most visible where touch is involved, hence my preoccupation with it.
Creativity and AI: A Response to Boden
Authors: Botha Catherine F.
Published: January 2023

Are creativity and artificial intelligence contradictions in terms? Margaret Boden argues that a creative product is one that is “surprising” as a result of the combination, exploration, or transformation involved in producing it. Boden uses examples of artificial intelligence systems that fit all of these criteria, but then argues that “real” creativity involves autonomy, intentionality, valuation, emotion, and consciousness. I analyse Boden’s position and argue that her argument is problematic as a result of the anthropocentrism implicit in the bifurcated definition she sets up. Contrary to Boden, I propose that we need not jealously guard creativity as an ability that is exclusively held by humans. I suggest we rather reject the anthropocentric conception of agenthood as problematic within our understandings of creativity. In my view, it is possible to grant (some) non-human agents entry into the realm of creativity, without undermining the value of the artifacts and ideas created, and without undermining the worth and dignity of our humanness
Trusting Workers: Information and Sociability in the Digital Age
Authors: Martino Valeria
Published: January 2023

In this research paper, we will consider the nature of our interactions with autonomous robot, with the aim to determine whether information about their nature (as well as information about the way in which robots proceed or, more generally, act in accordance with goals) should be shared among the people involved. We will consider the differences between sharing information and having common knowledge, which seem to be two separate concepts. Indeed, this could have a great impact on a key feature we recognize relevant in our interactions, namely sociability. This theoretical framework becomes even more relevant if it is applied to a specific case, such as work. Work itself is traditionally meant as a field for the promotion of sociability and trust in other people. The differences which could be promoted by new kinds of works and interactions will be also taken into consideration.
Can We Have Cultural Robotics Without Emotions?
Authors: Candiotto Laura , Mansouri Masoumeh
Published: January 2023

As robots begin to operate in environments hitherto only occupied by humans, it has become common to introduce social and cultural thinking into robotics research. Starting from the conceptualisation of culture as an emergent property of participatory processes of sense-making, in this paper we argue that cultural robotics cannot be achieved without emotions. To defend this thesis, we will first justify our working concepts, then provide our argument along with clarificatory examples. We also point to limitations of the current state-of-the-art in realising an “emotional robot” required in cultural robotics, and finally, set out a roadmap for robotics research into emotion and culture.
Incommensurability, Incomparability, and Robotic Choices
Authors: Laitinen Arto , Sahlgren Otto
Published: January 2023

Some comparisons yield puzzling results. In the puzzling cases, neither item is determinately better than the other, but they are not exactly equal either, as improving one of them just slightly still does not make it determinately better than the other. What does this kind of incommensurability or incomparability mean for robots? We discuss especially Ruth Chang’s views, arguing for four claims. First, we defend her view that despite appearances to the contrary, formal incomparability does not follow – comparison of “apples” and “oranges” is not impossible. Second, rational value-assessment turns out to be very complicated in virtue of the non-linear relations between descriptive and evaluative features. These complications pose considerable challenges to robots, whatever views about incommensurability are adopted. Ruth Chang’s theory introduces a fourth value relation “being on a par”, and we argue, thirdly, that (unlike its rivals) it will pose a considerable extra challenge for robots, as it is a non-transitive relation (unlike equality or betterness). Fourthly, we argue that exercise of normative powers – Chang’s suggestion for hard choices in contexts of parity – is not available in the case of (fully autonomous) robots.
Robotics for Human Creativity: Ethical Issues
Authors: Quick Oliver Santiago , Nørskov Sladjana
Published: January 2023

This paper discusses organizational and HRI research on the topic of creativity in order to draw attention to some underexplored ethical dimensions of both fields. Through an examination of the relationship between emotional labor, the affect-creativity link, and social robots aimed at augmenting human creative outputs or skills, we argue that researchers working with creativity ought to engage in ethical reflection on how their research results might impact practice ab initio—rather than forgoing such reflection or doing so only after the fact. Furthermore, we suggest that creativity researchers working with social robots or the affect-creativity link not only have a normative responsibility to engage with the potential ethical implications of the applications of their research results, but that by doing so from the start they will be positioned to exert some influence over how these results might be employed.
Ethical Planning with Multiple Temporal Values
Authors: Parker Timothy , Grandi Umberto , Lorini Emiliano , Clodic Aurélie , Alami Rachid
Published: January 2023

This paper describes an approach to ethical planning in robotics that combines classical planning, Linear Temporal Logic and lexicographically ordered value sets. We also discuss the features and limitations of the model, with particular attention to its philosophical implications.
Robotic Co-Evolution or K.O. of Robo-Evolution – Quo Vadis, Digital Humanism?
Authors: Funk Michael , Frauenberger Christopher , Reichl Peter
Published: January 2023

Social Robotics is one of the most innovative fields in robotics research. However, the current struggle for an adequate definition of “social robots” leads, a.o., to different interpretations for the status of this innovativeness. With respect to the recently emerging idea of a Digital Humanism, these controversies are of importance since the co-creation of social relations between humans and robots directly affects the concept of human-computer co-evolution; and thus the very core of (digital) humanism. Therefore, in this paper we reconstruct important related discourse threads of Robophilosophy conference contributions since 2014 with a particular focus on understanding humanity. Based on this, we confront these systematic scientific insights with the Vienna Manifesto on Digital Humanism and reveal its shortcomings in providing a consistent as well as robust conceptual basis for its own humanistic claims (which we nevertheless support from a more general perspective). By emphasizing inconsistencies in the manifesto, we argue that any kind of humanism, and especially the digital one, requires a careful and methodically reflected conceptual basis in order to not end up fueling systemic problems that the manifesto itself accuses for having made the system failing.
How We Respond to Robots and Whether It Matters Morally
Authors: Gorr Miriam
Published: January 2023

In the growing literature on the moral status of robots, authors such as Danaher, Coeckelbergh, and Sparrow have developed novel conceptions of moral status. In contrast to the standard emphasis on capacities, their accounts of moral status focus on human responses to robots. This paper provides both an analysis and critique of their accounts. First, it is argued that that all three authors endorse a response-dependence (RD) account of moral status. Second, it will be shown that these accounts suffer from three major problems. The conclusion is that an RD account is unsuitable to explain moral status and faces more problems than the capacity-based approach.
Sociomorphing and an Actor-Network Approach to Social Robotics
Authors: Bisconti Piercosma , Possati Luca
Published: January 2023

Most of human-robot interaction (HRI) research relies on an implicit assumption that seems to drive experimental work in interaction studies: the more anthropomorphism we can reach in robots, the more effective the robot will be in “being social.” The notion of “sociomorphing” was developed in order to challenge the assumption of ubiquitous anthropomorphizing. This paper aims to explore the notion of sociomorphing by analysing the possibilities offered by actor-network theory (ANT). We claim that ANT is a valid framework to re-think the conceptual couple anthropomorphizing / sociomorphing and answer the following question: What kind of negotiation process and social practices can be developed in HRI, given the notion of sociomorph interactional networks?
Dual Aspect Presence: Intercorporeality for Thee But Not for Me
Authors: Zebrowski Robin
Published: January 2023

There is a puzzle around presence, the feeling of being present with other beings, as it relates to certain kinds of technologies. When I am on a Zoom or Skype call (for example), there are a range of ways in which I am always aware that I am not present with others, from conceptual-level understandings that I cannot make eye contact because of camera-placement, to phenomenological facts about experiences of co-presence. On the other side, when I am interacting with some social robots (for example), I may feel as if I am in the presence of a real being, even if I know exactly how those appearances come about on an engineering or programming level. Each side of the problem is explored somewhat on its own terms in various disciplines, but taken together, we can see that these two issues are foundationally related and jointly are oddly paradoxical. By bringing these puzzles about presence into juxtaposition, we can start to see how much more troublesome and unclear the individual pieces actually are. This paper explores approaches to making sense of this problem, including intercorporeality and sociomorphing, and relates them to concepts in presence and telepresence research in trying to resolve the puzzle.
Persons, Things or Otherwise: The Place of Social Robots in Social Institutions
Authors: Gunkel David J.
Published: January 2023

One of the important opportunities/challenges of social robots is deciding whether these artifacts are and can be treated as things that we (human beings) can use and even abuse as we decide and see fit? Whether they would, due to their specific social circumstances and interpersonal contexts, require some level of personification and even the extension of some aspects of moral or legal personality? Or whether these technological innovations go further and challenge the very categories of person and thing, inviting us to rethink one of the fundamental organizing principles of our social ontology? This workshop is designed to address these questions. We have assembled a team of researchers from across the globe and from different disciplines, who can bring to this conversation a wide range of viewpoints and methods of investigation. The objective of the effort is not to advance one, definitive solution but to map the range of possible answers and critically evaluate their significance.
Legal Personhood for Artificial Intelligence: Can and Should It Be Conferred?
Authors: Tunç Aybike
Published: January 2023

It is a fact that today artificial intelligence is at an indispensable point for human life. Even though robots have a history of only 100 years in human life, it is not possible to imagine a life without robots with artificial intelligence technology when considering the great conveniences provided by them while performing our routines in our daily lives. This indispensable technology is of course used in legal relations, as well as in every field. Since Gaius, it has been accepted that law concerns persons, or things or actions. For this reason, legal systems need to determine the legal status of artificial intelligence and decide whether a new notion of personhood is needed for this technology. Therefore, this article aims to answer the questions whether it is possible to confer a new kind of personhood to artificial intelligence, as well as whether there is a legal need for it.
Challenges for the Inclusion of Robots in Social Institutions
Authors: Sætra Henrik Skaug
Published: January 2023

According to a typical definition, a social institution is “a complex of positions, roles, norms and values lodged in particular types of social structures and organising relatively stable patterns of human activity with respect to fundamental problems in producing life-sustaining resources, in reproducing individuals, and in sustaining viable societal structures within a given environment.” References to humans and life aside, this provides several important questions, in which I focus on two: First, can robots hold significant positions or have roles? Second, are they subject to norms and values, and do they take part in the social construction of the same? After answering these questions partially in the affirmative, I examine the requirements that must be met before robots can be perceived as fully in social institutions. If these requirements are met, I argue that social robots can indeed be in social institutions conducive to meeting fundamental needs and sustaining viable societal structures. Finally, I argue that meeting the most important requirements rely on design choices that can potentially be made with existing technologies. Meeting the requirements would potentially allow social robots a different social standing, but designers and regulators also have good reasons not to design—or allow robots to be designed—in such ways.
ELSI of the Avatar Symbiotic Society
Authors: Kukita Minao , Kanda Takayuki , Shimpo Fumio , Kato Takayuki , Ishiguro Hiroshi
Published: January 2023

We are currently promoting a project to develop (physical or virtual) avatar technology and to create a society where everyone can engage in various activities as they wish, beyond physical constraints, by using avatars. We are particularly concerned with enriching our communications, interactions, and relationships through avatars. However, this aim cannot be achieved by technology alone. We have to consider the ELSI (ethical, legal and social issues) concerning avatars as well. In this workshop, the speakers will introduce some of our technologies and then raise ethical and legal questions concerning avatars. Then we would like to discuss these issues with all the participants.
Legal Issues Concerning Cybernetic Avatars
Authors: Shimpo Fumio
Published: January 2023

The purpose of this paper is to examine the legal implications of cybernetic avatars (CA), which will be used in our daily life as remotely operated and autonomous robots. Such legal aspects consider the research, development, and use of ‘cyber-physical systems (CPS)’, which combine ‘cyber’ and ‘physical’ elements, and are referred to as the ‘avatar law’. The legal issues regarding CA need to be considered from the same perspective not only in Japan but also internationally.
Looking for an Obscenity Standard in the Cybernetic Avatar World
Authors: Kato Takayuki
Published: January 2023

This paper examines what legal norms would be appropriate in the world of the metaverse in which avatars operate. Specifically, it analyses the obscenity regulations of Japan and the US and evaluates whether or not rule formation in the world of the metaverse can be possible while referring to peculiarities of the metaverse world. The rules are divided into two dimensions: legal norms and compliance. This article concerns the former.
Is There a Need for Critical Robotics Research?
Authors: Ljungblad Sara , Ni Bhroin Niamh , Serholt Sofia , Samuelsson Gamboa Mafalda
Published: January 2023

What research questions and approaches are currently missing in the field of human-robot interaction research? We discuss humanistic and critical dimensions of critical robotics – an initiative created to investigate a possible paradigm shift in the field of robotics research. Robotic solutions are increasingly presented as a potentially desirable and emerging technologies in different social domains and institutions. At the same time, both this vision and the reality of robots in society pose a great deal of challenges. We provide some background to the critical robotics movement and present examples of research that takes a critical robotics perspective.