Abstract: The main objective is to design a line follower robot is to carry products in the manufacturing process in industries. In this paper, we mainly focused on the design to work the line follower efficiently with lighter weight. The line follower robot designed with 5 sensors to make the robot move in even complex paths. This paper discussed the mechanical and technical issues with the line follower robot and applications in various fields. In the working model, we used (...) black detector infrared sensors So that speed of response of the robot is high. This paper gives an brief idea about all the components used to prepare a line follower robot. (shrink)

This work has been designed to develop an a dynamic road signal based on an emergency with density. The sync signal automatically switches to detecting traffic density at the intersection. Traffic congestion is a serious problem in many large cities around the world and has become a nightmare for travelers in these cities. The conventional traffic light system is based on the concept of fixed time assigned to each side of the join that cannot be varied by varying traffic density. (...) The tie times assigned are fixed. But in an emergency, emergency timings change according to the distance and depth of the traffic. At the time the emergency vehicle is read by the receiver it will execute the management of the traffic light. These projects are infrared proximity sensors in the sightline configuration through the load to detect the traffic light density. The vehicle density is measured in several sectors based on the times assigned as a result. Every crossing of the emergency vehicle logs the data's to the cloud. This log signal would help with the destination acknowledgment. This synchronization will greatly reduce traffic jam. -/- . (shrink)

We describe a prototype ontology-driven information system (ODIS) that exploits what we call Portion of Reality (POR) representations. The system takes both sensor data and natural language text as inputs and composes on this basis logically structured POR assertions. The goal of our prototype is to represent both natural language and sensor data within a single framework that is able to support both axiomatic reasoning and computation. In addition, the framework should be capable of discovering and representing new kinds of (...) situations and thematic roles, (e.g., roles such as agent, patient and instrument), based on new compositions of existing representations. We applied our prototype in an intelligence analysis use case to test the hypothesis that a framework of this sort can produce usefully structured information from combined natural language and sensor data inputs. We further tested our hypothesis by adding an enhanced US Air Force ontology framework to our ODIS in order to (1) process a collection of sensor data, intel reports, and mission plans; (2) build composite POR representations from these data; and (3) machine analyze the fused results to infer mission threats. (shrink)

Wireless Sensors Network is a novel field shows tremendous application potential. To monitor the environmental parameters of high-tech polyhouse the Wireless Sensors Network (WSN) is developed. The heart of this ubiquitous field is the Wireless Sensor Node. Moreover, the field of microcontroller based embedded technology is innovative and more reliable. Therefore, based on an embedded technology and the RF module Zigbee a wireless senor node is designed about highly promising AVR ATmega8L microcontroller and implemented for WSN development. Recently, (...) the modern agriculturists are demanding sophisticated instrumentation for measurement and control of environmental parameters of the polyhouse. To enhance crop yield one has to provide controlled environment to the crop. The humidity is important parameter, which plays vital role on the crop yield. Therefore, a Wireless Sensors Network (WSN) is designed and implemented for monitoring of humidity of polyhouse and the results of implementation are interpreted in this paper. (shrink)

Some cognitive processes appear to have “phenomenal” properties that are directly revealed to the subject and not determined by physical properties. I suggest that the source of this appearance is the method by which our brain processes sensory information. The appearance is an illusion. Nonetheless, we are not mistaken when we judge that people sometimes fee lpain.

The antenna is considered as the primary means of absorbing electromagnetic waves in space and has its own engineering knowledge, which is very developed and extensive. In general, in order to receive the electromagnetic wave in space, the dimensions of the antenna must be in the order of the size of the input wavelength to its surface. Due to the very low dimensions of nano-sensors, nano-antennas need a very high operating frequency to be usable. The use of graphene greatly (...) helps to solve this problem. Wave propagation velocities in CNTs and GNRs can be up to 100 times slower than vacuum velocities, depending on the physical structure, temperature and energy. Accordingly, the resonant frequency of graphene-based nano-antennas can be twice as low as (nano-carbon) nano-antennas. (shrink)

Background: Smart sensors have been developed as diagnostic tools for rehabilitation to cover an increasing number of geriatric patients. They promise to enable an objective assessment of complex movement patterns. -/- Objective: This research aimed to identify and analyze the conflicting ethical values associated with smart sensors in geriatric rehabilitation and provide ethical guidance on the best use of smart sensors to all stakeholders, including technology developers, health professionals, patients, and health authorities. -/- Methods: On the basis (...) of a systematic literature search of the scientific databases PubMed and ScienceDirect, we conducted a qualitative document analysis to identify evidence-based practical implications of ethical relevance. We included 33 articles in the analysis. The practical implications were extracted inductively. Finally, we carried out an ethical analysis based on the 4 principles of biomedical ethics: autonomy, beneficence, nonmaleficence, and justice. The results are reported in categories based on these 4 principles. -/- Results: We identified 8 conflicting aims for using smart sensors. Gains in autonomy come at the cost of patient privacy. Smart sensors at home increase the independence of patients but may reduce social interactions. Independent measurements performed by patients may result in lower diagnostic accuracy. Although smart sensors could provide cost-effective and high-quality diagnostics for most patients, minorities could end up with suboptimal treatment owing to their underrepresentation in training data and studies. This could lead to algorithmic biases that would not be recognized by medical professionals when treating patients. -/- Conclusions: The application of smart sensors has the potential to improve the rehabilitation of geriatric patients in several ways. It is important that patients do not have to choose between autonomy and privacy and are well informed about the insights that can be gained from the data. Smart sensors should support and not replace interactions with medical professionals. Patients and medical professionals should be educated about the correct application and the limitations of smart sensors. Smart sensors should include an adequate representation of minorities in their training data and should be covered by health insurance to guarantee fair access. (shrink)

Multi sensor data fusion allows large scale deployments for environmental monitoring applications especially in the areas like homes, other buildings and infrastructures and industries. In such areas early fire detection is of great importance as the consequences of a fire are catastrophic. This project predicts the possibility of catching fire using a multi-sensor scheme of data fusion to enhance the performance of the early fire detection process by detecting the concentration of inflammable gases in the atmosphere and by measuring the (...) atmospheric temperature. (shrink)

Artificial Intelligence and Sensor Technologies the Future of Special Education for Students with Intellectual and Developmental Disabilities.

The data collected by these sensors are transmitted to a centralized system where optimization algorithms, such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA), are applied to optimize sensor placement, data transmission, and processing efficiency. This ensures accurate, real-time pollution monitoring and data analysis, providing actionable insights for policymakers, environmental agencies, and the general public. The system's performance is evaluated through simulations and real-world experiments, demonstrating its capability to deliver reliable and timely pollution data. Future (...) work will explore the integration of machine learning techniques for predictive analytics and the expansion of the sensor network for broader coverage. (shrink)

The data collected by these sensors are transmitted to a centralized system where optimization algorithms, such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA), are applied to optimize sensor placement, data transmission, and processing efficiency. This ensures accurate, real-time pollution monitoring and data analysis, providing actionable insights for policymakers, environmental agencies, and the general public. The system's performance is evaluated through simulations and real-world experiments, demonstrating its capability to deliver reliable and timely pollution data. Future (...) work will explore the integration of machine learning techniques for predictive analytics and the expansion of the sensor network for broader coverage. (shrink)

New technologies such as smart sensors improve rehabilitation processes and thereby increase older adults’ capabilities to participate in social life, leading to direct physical and mental health benefits. Wearable smart sensors for home use have the additional advantage of monitoring day-to-day activities and thereby identifying rehabilitation progress and needs. However, identifying and selecting rehabilitation priorities is ethically challenging because physicians, therapists, and caregivers may impose their own personal values leading to paternalism. Therefore, we develop a discussion template consisting (...) of a series of adaptable questions for the patient–physician encounter based on the capability approach. The goal is to improve geriatric rehabilitation and thereby increase participation in social life and well-being. To achieve this goal, we first analyzed what is considered important for participation on basis of the capability approach, human rights, and ethics of care. Second, we conducted an ethical analysis of each of the four identified dimensions of participation: political, economic, socio-cultural, and care. To improve compliance with rehabilitation measures, health professionals must align rehabilitation measures in an open dialogue with the patient’s aspiration for participation in each dimension. A discussion template based on the capability approach allows for a proactive approach in patient information and stimulates a critical assessment of treatment alternatives while reducing the risk of imposing personal values. (shrink)

The advance of scientific approaches to life has recorded a plethora of successes as well as failures. Man being at the center of its experiment is tossed toe and fro by the result of its inquiry. Predictions are that in the nearest time, humanity might be living absolutely under the directives of Technology based on Artificial intelligence. At present, Technology based on Artificial Intelligence is quickly finding its way into various areas of life including health and social services. This spread (...) and or interplay connotes the relinquishing of health responsibilities from man to sensor technology as well as dependency on the data and result of this technology. This effort questions this unethical dependency as well as raises moral issues associated with the use of Technology base on artificial intelligence on psychiatric patient. It dabbles into medical values such as; autonomy of the patient cum consent, Kantian universal principle and its implication to implementing the universal usage of technology in mental health care services, and so on. The work of Patricia A. Arean (2016) titled Mobile Technology for Mental Health Assessment gave an in-depth analysis of the available approaches, doting advantages of sensor technology on psychiatric patient. The paper applied the analytic, descriptive and prescriptive method of philosophy to achieve its objective. To this end, it is in the view of this work imperative for the mental-medical community to consider reflectively these issues and the philosophic recommendations provided herein. (shrink)

t: Wireless Sensor Networks (WSNs) have become increasingly prevalent in various applications, ranging from environmental monitoring to smart cities. However, the limited energy resources of sensor nodes pose significant challenges in maintaining network longevity and data transmission efficiency. Duty-cycled WSNs, where sensor nodes alternate between active and sleep states to conserve energy, offer a solution to these challenges but introduce new complexities in data transmission.

Abstract—Traffic clog is a serious issue in the majority of the urban areas over the world and it has turned into a bad dream for the residents. It is brought about by postponement in flag, improper planning of traffic flagging and so on. The postponement of traffic light is hard coded and it doesn't depend on traffic. In this manner for streamlining traffic control, there is an expanding request in precise snappy programmed framework. This paper is intended to build up (...) a thickness based powerful traffic flag control. The flag timing changes naturally on detecting the traffic thickness at the junction. The microcontroller utilized in this undertaking is ARDUINO. The framework contains IR sensors (transmitter and collector) which will be mounted. It gets initiated and gets the flag as the vehicles passes near to it. (shrink)

Note: Many types of nanosensors are designed using CP nanomaterials for nanobiological applications. (Conductive surface) The oxidation of conductive polymeric materials is easily altered by redox mechanisms, and the charge transfer properties of these materials are affected by structural parameters, such as diameter and dimensions. CP materials are able to provide sensitive and rapid responses to specific biological and chemical species. Techniques such as chemical polymerization are often used to make CP nanomaterials. Manufacturing strategies can be divided into three categories: (...) hard mold synthesis, soft mold synthesis, and mold-free synthesis. The most widely used conductive polymers in nanosensors are nanomaterials made from CP due to their unique chemical and electrical properties resulting from the properties of their pie-electron nanosystem. Many modeling and functionalization technologies are being developed to control the location, distribution, amount, or structure and orientation of biological nanomolecules at the nanomaterial level. Therefore, our level of contact between biological nanomolecules and nanomaterials is of particular importance in countless applications. Covalent and non-covalent modifications are two general methods for coupling biological molecules and CP nanomaterials. Covalent functionalization is a chemical process in which a strong bond or relationship between nanomaterials and biological molecules is formed. In many cases, surface chemical modifications are required to create active groups that can bind to biomolecules. Unlike covalent functionalization, in the non-covalent method, nanomolecules can be removed without destroying the geometric and electronic structure on the surface. Nanomaterials are formed. Conclusion : The large surface-to-volume ratio in nanostructures and the high potential for signal amplification provide ideal conditions for marking and detecting biological elements in the structure of nanosensors. (shrink)

A ventilator is a device that provides cool air by moving the air in or out of the lungs, inhaling a patient who is not fit to smell, or breathing properly. In this paper, a resistive chest belt sensorbased mechanical ventilator is designed to provide the COVID-19 patient with the volume of air you need to deliver with the expansion of the patient's chest in need of more air. The resistive band sensor senses the expansion of the patient's chest and (...) controls the solenoid valve attached to the oxygen compressor. The function of the respirator is tested with the MATLAB / Simulink tool with the help of a Proportional Integral Derivative (PID) Controller and a promising result obtained. (shrink)

In this study, an automatic heat dispel system for DINGSON Biscuit Oven have been designed and simulated using Proteus program successfully. This system uses thermocouple temperature sensor to sense the oven temperature and automatically open and close the dispel system. The temperature in which the dispel open and close can be adjusted any time the operator needs to adjust it.

Optimization algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) are employed to determine the optimal aggregation and transmission schedules, taking into account factors such as network topology, node energy levels, and data urgency. The proposed approach is validated through extensive simulations, demonstrating significant improvements in energy consumption, packet delivery ratio, and overall network performance. The results suggest that the optimized aggregated packet transmission method can effectively extend the lifespan of duty-cycled WSNs while ensuring reliable data communication. Future (...) work will explore the integration of machine learning techniques for adaptive scheduling and the application of the proposed method to heterogeneous WSNs. (shrink)

Directed Diffusion (DD) uses data aggregation to suppress data overhead however there is no guarantee that paths from nearby sources join after a few hops. In this paper, an efficient data-gathering protocol (EDAP) is proposed to address this problem by using a Virtual Sink (VS) node nearby the sources, which plays the role of sink node and broadcasts local interest messages and routes gathered data toward destination. Also, multiple paths are constructed between VS and the sink node, which leads to (...) load-balancing, and increase in the lifetime of the network. Simulation results show that in EDAP a significant amount of energy can be saved and the network lifetime will be increased considerably. (shrink)

Representing the kinetic state of a patient (posture, motion, and activity) during vital sign measurement is an important part of continuous monitoring applications, especially remote monitoring applications. In contextualized vital sign representation, the measurement result is presented in conjunction with salient measurement context metadata. We present an automated annotation system for vital sign measurements that uses ontologies from the Open Biomedical Ontology Foundry (OBO Foundry) to represent the patient’s kinetic state at the time of measurement. The annotation system is applied (...) to data generated by a wearable personal status monitoring (PSM) device. We demonstrate how annotated PSM data can be queried for contextualized vital signs as well as sensor algorithm configuration parameters. (shrink)

Starting from a philosophical perspective, which states that the living structures are actually a combination between matter and information, this article presents the results on an analysis of the bipolar information-matter structure of the human organism, distinguishing three fundamental circuits for its survival, which demonstrates and supports this statement, as a base for further development of the informational model of consciousness to a general informational model of the human organism. For this, it was examined the Informational System of the Human (...) Body and its components from the perspective of the physics/information/neurosciences concepts, showing specific functions of each of them, highlighting the correspondence of these centers with brain support areas and with their projections in consciousness, which are: Center of Acquisition and Storing of Information (CASI) reflected in consciousness as memory, Center of Decision and Command (CDC) (decision), Info-Emotional Center (IES) (emotions), Maintenance Informational System (MIS) (personal status), Genetic Transmission System (GTS) (associativity/genetic transmission) and Info Genetic Generator (IGG) related by the body development and inherited behaviors. The Info Connection (IC), detected in consciousness as trust and confidence can explain the Near-Death Experiences (NDEs) and associated phenomena. This connection is antientropic and informational, because from the multitude of uncertain possibilities is selected a certain one, helping/supporting the survival and life. The human body appears therefore as a bipolar structure, connected to two poles: information and matter. It is argued that the survival, which is the main objective of the organism, is complied in three main ways, by means of: (i) the reactive operation for adaptation by attitude; (ii) the info-genetic integration of information by epigenetic processes and genetic transmission of information for species survival, both circuits (i) and (ii) being associated to the information pole; (iii) maintenance of the material body (defined as informed matter) and its functions, associated to the matter pole of the organism. It results therefore that the informational system of the human body is supported by seven informational circuits formed by the neuro-connections between the specific zones of the brain corresponding to the informational subsystems, the cognitive centers, the sensors, transducers and execution (motor/mobile) elements. The fundamental informational circuits assuring the survival are the reactive circuit, expressible by attitude, the epigenetic/genetic circuit, absorbing and codifying information to be transmitted to the next generations, and the metabolic circuit, connected to matter (matter pole). The presented analysis allows to extend the informational modeling of consciousness to an Informational Model of Consciousness and Organism, fully describing the composition/functions of the organism in terms of information/matter and neurosciences concept. (shrink)

One method for preventing the spread of the coronavirus and other contagious diseases is through social distancing. Therefore, creating a tool to measure and quickly discover the precise distance is necessary. In order to prevent physical contact between individuals, this study aimed to detects individuals’ physical distance, through an inaugurated battery-powered device that monitors physical distance through wireless technology. Specifically, in public or crowded areas, to lessen the spread of the virus. This study focuses on detecting people’s physical distance in (...) the region of interest utilizing an Ultrasonic and VL53L0X sensors and determining the significant difference between the two sensors in monitoring physical distance. This study employs an applied experimental research design. The efficiency of both sensors in measuring physical distance was evaluated through analysis. The Ultrasonic and VL53L0X sensors underwent 15 tests. Furthermore, the researchers effectuated a t-test to determine the significant difference between the two sensors. Data gathered revealed that the sensors’ combined mean in terms of measuring physical distance indicates that the ultrasonic sensor performed better than VL53L0X, measuring 134.7 cm, notwithstanding 99.8 cm for the VL53L0X sensor. Complementary to this, the results of the t-test show that the VL53L0X sensor and Ultrasonic sensor have a significant difference in terms of distance precision. (shrink)

This paper shows the smart walking stick based on ultrasonic sensors and Arduino for outwardly debilitated individuals. There are roughly 37 million individuals over the globe who are visually impaired as indicated by the World Health Organization. Individuals with visual inabilities are regularly subjected to outer help which can be given by people, trained dogs, or electronic gadgets as supportive networks for basic assistance. Thus, this played as the motivation to develop a smart cane white stick to survive these (...) restrictions which includes ultrasonic sensors at particular positions to the stick that gave data about nature to the client by initiating the signal sound and vibrations. We proposed minimal effort and light weight framework structured with micro controller that processes signal and alerts the visually impaired person over any obstacle, water or dark areas through beeping sounds or vibrations. The system comprises of obstacle and moisture detection sensors for process of receiving, processing and sending signals to the alarm system which finally alerts the user for prompt action. The system was designed, programmed using Java language and tried for exactness by the visually impaired. Our gadget can recognize obstacle inside the separation of around 2m from the client. (shrink)

Wireless Sensor Networks (WSNs) have become increasingly prevalent in various applications, ranging from environmental monitoring to smart cities. However, the limited energy resources of sensor nodes pose significant challenges in maintaining network longevity and data transmission efficiency. Duty-cycled WSNs, where sensor nodes alternate between active and sleep states to conserve energy, offer a solution to these challenges but introduce new complexities in data transmission. This paper presents an optimized approach to aggregated packet transmission in duty-cycled WSNs, utilizing advanced optimization techniques (...) to enhance energy efficiency, reduce latency, and improve network throughput. By aggregating data packets from multiple nodes before transmission, the proposed method minimizes the number of transmissions, thereby conserving energy. Optimization algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) are employed to determine the optimal aggregation and transmission schedules, taking into account factors such as network topology, node energy levels, and data urgency. T. (shrink)

Cameras, microphones, and other sensors continue to proliferate in the world around us. I offer a new metaphor for conceptualizing these technologies: they are _digital wormholes_, transmitting representations of human persons between disparate points in space–time. We frequently cannot tell when they are operational, what kinds of data they are collecting, where the data may reappear in the future, and how the data can be used against us. The wormhole metaphor makes the mysteriousness of digital sensors salient: digital (...) sensors have brought us to a strange place. If humans are to be capable of making sensible decisions while under observation by digital sensors, we must improve the epistemic position of potential sensor subjects. (shrink)

Abstract: Smoke detectors are critical devices for early fire detection and life-saving interventions. This research paper explores the application of Artificial Neural Networks (ANNs) in smoke detection systems. The study aims to develop a robust and accurate smoke detection model using ANNs. Surprisingly, the results indicate a 100% accuracy rate, suggesting promising potential for ANNs in enhancing smoke detection technology. However, this paper acknowledges the need for a comprehensive evaluation beyond accuracy. It discusses potential challenges, such as overfitting, dataset size, (...) and class imbalance, and presents strategies employed to address these issues. Additionally, the paper emphasizes the importance of alternative evaluation metrics, including precision, recall, and F1-score, to assess the model's performance comprehensively. Detailed information regarding the model architecture, data preprocessing, and hyperparameter tuning is provided to enhance the reproducibility of the research. The study also discusses ethical considerations and the implications of false positives and false negatives in smoke detection applications. While achieving 100% accuracy is a notable accomplishment, this paper calls for cautious interpretation and further validation in real-world settings. It concludes by highlighting areas for future research and improvement in smoke detection technology, emphasizing the need for practical deployment and the reduction of false alarms. (shrink)

The conjunction of wireless computing, ubiquitous Internet access, and the miniaturisation of sensors have opened the door for technological applications that can monitor health and well-being outside of formal healthcare systems. The health-related Internet of Things (H-IoT) increasingly plays a key role in health management by providing real-time tele-monitoring of patients, testing of treatments, actuation of medical devices, and fitness and well-being monitoring. Given its numerous applications and proposed benefits, adoption by medical and social care institutions and consumers may (...) be rapid. However, a host of ethical concerns are also raised that must be addressed. The inherent sensitivity of health-related data being generated and latent risks of Internet-enabled devices pose serious challenges. Users, already in a vulnerable position as patients, face a seemingly impossible task to retain control over their data due to the scale, scope and complexity of systems that create, aggregate, and analyse personal health data. In response, the H-IoT must be designed to be technologically robust and scientifically reliable, while also remaining ethically responsible, trustworthy, and respectful of user rights and interests. To assist developers of the H-IoT, this paper describes nine principles and nine guidelines for ethical design of H-IoT devices and data protocols. (shrink)

In this paper, we report on an experiment with The Walking Dead (TWD), which is a narrative-driven adventure game with morally charged decisions set in a post-apocalyptic world filled with zombies. This study aimed to identify physiological markers of moral decisions and non-moral decisions using infrared thermal imaging (ITI). ITI is a non-invasive tool used to capture thermal variations due to blood flow in specific body regions that might be caused by sympathetic activity. Results show that moral decisions seem (...) to elicit a significant decrease in temperature in the chin region 20 seconds after participants are presented with a moral decision. However, given the small sample involved, and the lack of significance in other regions, future studies might be needed to confirm the results obtained in this work. (shrink)

Man has built tools to extend his visual experience in order to explore reality beyond his sensory capacity, for example microscopes, telescopes, high shutter speed and infrared cameras. However he has yet to build a tool to fully explore visual realms beyond his ordinary cognitive faculties. With the development of computing, comes the possibility of building a tool to explore the virtual forms/spaces of images that are ordinarily inaccessible to the mind. This article identifies how cognition is ordinarily limited (...) and posits a way of going beyond those limits, by defining a computational model of how those virtual forms/spaces might be created. This definition is based on brief but repeated empirical experiences of ‘higher order’ manifestations. (shrink)

Analysis of grip force signals tailored to hand and finger movement evolution and changes in grip force control during task execution provide unprecedented functional insight into somatosensory cognition. Somatosensory cognition is a basis of our ability to manipulate, move, and transform objects of the physical world around us, to recognize them on the basis of touch alone, and to grasp them with the right amount of force for lifting and manipulating them. Recent technology has permitted the wireless monitoring of grip (...) force signals recorded from biosensors in the palm of the human hand to track and trace human grip forces deployed in cognitive tasks executed under conditions of variable sensory (visual, auditory) input. Non-invasive multi-finger grip force sensor technology can be exploited to explore functional interactions between somatosensory brain mechanisms and motor control, in particular during learning a cognitive task where the planning and strategic execution of hand movements is essential. Sensorial and cognitive processes underlying manual skills and/or hand-specific (dominant versus non-dominant hand) behaviors can be studied in a variety of contexts by probing selected measurement loci in the fingers and palm of the human hand. Thousands of sensor data recorded from multiple spatial locations can be approached statistically to breathe functional sense into the forces measured under specific task constraints. Grip force patterns in individual performance profiling may reveal the evolution of grip force control as a direct result of cognitive changes during task learning. Grip forces can be functionally mapped to from-global-to-local coding principles in brain networks governing somatosensory processes for motor control in cognitive tasks leading to a specific task expertise or skill. Under the light of a comprehensive overview of recent discoveries into the functional significance of human grip force variations, perspectives for future studies in cognition, in particular the cognitive control of strategic and task relevant hand movements in complex real-world precision task, are pointed out. (shrink)

The measurement of light and colour has always been a peripheral science. Light became a 'disciplined' quantity over the period of a century, but the specialist communities that measured it did not. The quantification of visible light (photometry), colour (colorimetry), and radiant intensity (radiometry) involved distinct communities of physicists, psychologists, technicians and engineers. -/- This chapter of _Science in the Shadows_ examines how the measurement of non-visible light became the domain of post Second World War military engineers and classified development (...) programmes. (shrink)

Plastic waste is a significant environmental problem for almost all countries; therefore, protecting the environment from the problem is crucial. The most sensible solution to these problems is substituting the natural aggregates with substantial plastic waste in various building materials. This study aimed to optimise the mixed design ratio of cement brick containing plastic waste as aggregate replacement. Plastic cement brick mixtures were prepared by the incorporation of four different types of plastic waste such as polyethylene terephthalate (PET), high-density polyethylene, (...) low-density polyethylene and polypropylene into cement bricks with different cement contents (150, 300 and 450 g) and plastic replacement percentages (0, 3 and 6%). Compressive strength and water absorption of the plastic cement bricks were analysed using a statistical model through the response surface methodology. It revealed the optimum cement brick mixed design is C3-1% PET with the compressive strength of 27.50 MPa and water absorption of 1.16%. The optimised plastic cement brick also satisfied the general ASTM C62-17 requirements for building bricks despite the higher porosity observed by the scanning electron microscopy. The results from Fourier transform infrared spectroscopy analysis also showed that the addition of the plastic waste into cement brick was unlikely to modify the chemical compound within the cement brick mixtures. Thus, the proposed mathematical model can predict the required hardened properties of plastic cement bricks and could lead to greater utilisation of plastic waste in building materials. (shrink)

This selective review explores biologically inspired learning as a model for intelligent robot control and sensing technology on the basis of specific examples. Hebbian synaptic learning is discussed as a functionally relevant model for machine learning and intelligence, as explained on the basis of examples from the highly plastic biological neural networks of invertebrates and vertebrates. Its potential for adaptive learning and control without supervision, the generation of functional complexity, and control architectures based on self-organization is brought forward. Learning without (...) prior knowledge based on excitatory and inhibitory neural mechanisms accounts for the process through which survival-relevant or task-relevant representations are either reinforced or suppressed. The basic mechanisms of unsupervised biological learning drive synaptic plasticity and adaptation for behavioral success in living brains with different levels of complexity. The insights collected here point toward the Hebbian model as a choice solution for “intelligent” robotics and sensor systems. Keywords: Hebbian learning; synaptic plasticity; neural networks; self-organization; brain; reinforcement; sensory processing; robot control . (shrink)

Primitive awareness leading to consciousness can be explained as a manifestation of internal forces between charge and mass. These internal forces, related to the weak and strong forces, balance the external forces of gravity-inertia and electricity-magnetism and thereby accommodate outside influences by adjusting the internal structure of material from which we are composed. Such accommodation is the physical implementation of a model of the external physical world and qualifies as Vitiello's double held inside ourselves. We experience this accommodation as the (...) conscious experience in front of our noses. Neural pulse traffic is interpreted as unconscious signal processing activity happening between this internal accommodation and our external interface of sensors and actuators. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;}. (shrink)

Deep learning algorithms are rapidly changing the way in which audiovisual media can be produced. Synthetic audiovisual media generated with deep learning—often subsumed colloquially under the label “deepfakes”—have a number of impressive characteristics; they are increasingly trivial to produce, and can be indistinguishable from real sounds and images recorded with a sensor. Much attention has been dedicated to ethical concerns raised by this technological development. Here, I focus instead on a set of issues related to the notion of synthetic audiovisual (...) media, its place within a broader taxonomy of audiovisual media, and how deep learning techniques differ from more traditional approaches to media synthesis. After reviewing important etiological features of deep learning pipelines for media manipulation and generation, I argue that “deepfakes” and related synthetic media produced with such pipelines do not merely offer incremental improvements over previous methods, but challenge traditional taxonomical distinctions, and pave the way for genuinely novel kinds of audiovisual media. (shrink)

Note: In general, in order to receive the electromagnetic wave in the space, the dimensions of the antenna must be in the order of the wavelength of the input to its surface. Due to the very small dimensions of nano sensors, nano antennas need to have a very high working frequency to be usable. -/- The use of graphene helps to solve this problem to a great extent. The speed of propagation of waves in CNTs and GNRs can be (...) 100 times lower than its speed in vacuum, and this is related to the physical structure, temperature and energy. Based on this, the resonance frequency of graphene-based nano-antennas can be two orders of magnitude lower than nano-antennas based on nano-carbon materials. It has been mathematically and theoretically proven that a quasi-metallic carbon nanotube can emit terahertz radiation when a time-varying voltage is applied to its sides. One of the most important parameters of any nano antenna is the current distribution on it. This characteristic determines the radiation pattern, radiation resistance and reactance and many important characteristics of the antenna. Despite the possibilities of making nanotubes with a length of several centimeters, it is possible to make electrical conductors with a length-to-width ratio of the order of 10^7. has it. At first glance, nanotube antennas give us the impression that they are similar to Dipole antennas designed in small dimensions. (shrink)

The chapter deals with the notion of phenomenal realness, which was first systematically explored by Albert Michotte. Phenomenal realness refers to the impression that a perceptual object is perceived to have an autonomous existence in our mind-independent world. Perceptual psychology provides an abundance of phenomena, ranging from amodal completion to picture perception, that indicate that phenomenal realness is an independent perceptual attribute that can be conferred to perceptual objects in different degrees. The chapter outlines a theoretical framework that appears particularly (...) well-suited for dealing with corresponding phenomena. According to this framework, perception can be understood as a triggering of conceptual forms by sensor inputs. It is argued that the attribute of phenomenal realness is based on specific types of internal evaluation functions which deal with the segregation of causes conceived as ‘external’ from those conceived as ‘internal’. These evaluation functions integrate different internal sources of ‘knowledge’ about the potential causes for the activation of conceptual forms and provide markers by which conceptual forms can be tagged as ‘external world objects’. (shrink)

This paper attempts to answer a central question in unsupervised learning: what does it mean to “make sense” of a sensory sequence? In our formalization, making sense involves constructing a symbolic causal theory that both explains the sensory sequence and also satisfies a set of unity conditions. The unity conditions insist that the constituents of the causal theory – objects, properties, and laws – must be integrated into a coherent whole. On our account, making sense of sensory input is a (...) type of program synthesis, but it is unsupervised program synthesis. Our second contribution is a computer implementation, the Apperception Engine, that was designed to satisfy the above requirements. Our system is able to produce interpretable human-readable causal theories from very small amounts of data, because of the strong inductive bias provided by the unity conditions. A causal theory produced by our system is able to predict future sensor readings, as well as retrodict earlier readings, and impute (fill in the blanks of) missing sensory readings, in any combination. In fact, it is able to do all three tasks simultaneously. We tested the engine in a diverse variety of domains, including cellular automata, rhythms and simple nursery tunes, multi-modal binding problems, occlusion tasks, and sequence induction intelligence tests. In each domain, we test our engine's ability to predict future sensor values, retrodict earlier sensor values, and impute missing sensory data. The Apperception Engine performs well in all these domains, significantly out-performing neural net baselines. We note in particular that in the sequence induction intelligence tests, our system achieved human-level performance. This is notable because our system is not a bespoke system designed specifically to solve intelligence tests, but a general-purpose system that was designed to make sense of any sensory sequence. (shrink)

This paper uses a paradox inherent in any solution to the Hard Problem of Consciousness to argue for God’s existence. The paper assumes we are “thought machines”, reading the state of a relevant physical medium and then outputting corresponding thoughts. However, the existence of such a thought machine is impossible, since it needs an infinite number of point-representing sensors to map the physical world to conscious thought. This paper shows that these sensors cannot exist, and thus thought cannot (...) come solely from our physical world. The only possible explanation is something outside, argued to be God. (shrink)

The body is a highly complex, coordinated system engaged in coping with many environmental problems. It can be considered as some sort of opportunity or obstacle, with which internal processing must deal. Internal processing must take into account the possibilities and limitations of the particular body. In other words, even if the body is not involved in the realization of some cognitive explicit task, it is not a neutral factor of our understanding of why a system solves a task in (...) one way or another. Therefore, when conducting research on embodiment and the body’s cognitive system we should not neglect internal, cognitive processing. I appeal to Goldman’s research on embodied cognition to sketch the broader framework for internal processing in embodied cognition. I believe that even if we don’t accept Goldman’s approach as the viable proposal for embodied cognition in general, it’s a quite natural starting point for our analysis. Goldman (2012; 2014, and with de Vignemont 2009) argue for the essential role of the bodily formats or bodily codes (respectively: B-formats and B-codes) in embodied cognition. B-codes are here described as the processing of regions or sub-regions of the central nervous system. They are primarily employed for body control or monitoring, and reused for cognitive tasks. Beyond doubt, this conception provides an excellent starting point for analyzing the internal (mostly neural) processing in cases of embodied cognition. At the end of this paper, I will argue that the embodiment of cognition needs a conceptual twist. Following Keijzer’s (2015) interest in the evolution of the nervous system, and the minimal forms of cognition, I argue that in investigating embodied cognition, we should investigate the role played by cognitive processing for specific kinds of organisms, meaning organisms with a body of a particular morphology (size, shape, kinds, and distribution of sensors and effectors). Doing that, I refer to some conceptual and empirical considerations. I will also try to show that research on embodied cognition is still not sufficiently anchored in evolutionary and comparative studies on cognition, nor on the nervous system and body morphology. Bigger reliance on these kinds of studies, will make it make possible to gain a deeper understanding of internal processing in embodied cognition. (shrink)

To enable microbial colonisation of the gut mucosa, the intestinal immune system must not only react to danger signals but also recognize cues that indicate safety. Safety recognition, paradoxically, is mediated by the same environmental sensors that are involved in signalling danger. Indeed, in addition to their well established role in inducing inflammation in response to stress signals, pattern recognition receptors (PRRs) and a variety of metabolic sensors also promote gut-microbiota symbiosis by responding to "microbial symbiosis factors", "resolution-associated (...) molecular patterns", markers of energy extraction and other signals indicating the absence of pathogenic infection and tissue damage. Here we focus on how the paradoxical role of immune receptors and other environmental sensors define the microbiota signature of the individual. (shrink)

This article identifies and examines a tension in mental health researchers’ growing enthusiasm for the use of computational tools powered by advances in artificial intelligence and machine learning (AI/ML). Although there is increasing recognition of the value of participatory methods in science generally and in mental health research specifically, many AI/ML approaches, fueled by an ever-growing number of sensors collecting multimodal data, risk further distancing participants from research processes and rendering them as mere vectors or collections of data points. (...) The imperatives of the “participatory turn” in mental health research may be at odds with the (often unquestioned) assumptions and data collection methods of AI/ML approaches. This article aims to show why this is a problem and how it might be addressed. (shrink)

We argue that a command and control system can undermine a commander’s moral agency if it causes him/her to process information in a purely syntactic manner, or if it precludes him/her from ascertaining the truth of that information. Our case is based on the resemblance between a commander’s circumstances and the protagonist in Searle’s Chinese Room, together with a careful reading of Aristotle’s notions of ‘compulsory’ and ‘ignorance’. We further substantiate our case by considering the Vincennes Incident, when the crew (...) of a warship mistakenly shot down a civilian airliner. To support a combat commander’s moral agency, designers should strive for systems that help commanders and command teams to think and manipulate information at the level of meaning. ‘Down conversions’ of information from meaning to symbols must be adequately recovered by ‘up conversions’, and commanders must be able to check that their sensors are working and are being used correctly. Meanwhile ethicists should establish a mechanism that tracks the potential moral implications of choices in a system’s design and intended operation. Finally we highlight a gap in normative ethics, in that we have ways to deny moral agency, but not to affirm it. (shrink)

Knill, Kersten, & Mamassian (Chapter 6) provide an interesting discussion of how the Bayesian formulation can be used to help investigate human vision. In their view, computational theories can be based on an ideal observer that uses Bayesian inference to make optimal use of available information. Four factors are important here: the image information used, the output structures estimated, the priors assumed (i.e., knowledge about the structure of the world), and the likelihood function used (i.e., knowledge about the projection of (...) the world onto the sensors). Knill & Kersten argue that such a framework not only helps analyze a perceptual task, but can also help investigators to define it. Two examples are provided (the interpretation of surface contour and the perception of moving shadows) to show how this approach can be used in practice. As the authors admit, most (if not all) perceptual processes are ill-suited to a "strong" Bayesian approach based on a single consistent model of the world. Instead, they argue for a "weak" variant that assumes Bayesian inference to be carried out in modules of more limited scope. But how weak is "weak"? Are such approaches suitable for only a few relatively low-level tasks, or can they be applied more generally? Could a weak Bayesian approach, for example, explain how we would recognize the return of Elvis Presley? The formal modelling of human perception To help get a fix on things, it is useful to examine the fate of an earlier attempt to formalize human perception: the application of information theory. It was once hoped that this theory—a close cousin of the Bayesian formulation—would provide a way to uncover information-handling laws that were largely independent of physical implementation. In this approach, the human nervous system was assumed to have.. (shrink)

Some defenders of so-called `artificial intelligence' believe that machines can understand language. In particular, Søgaard has argued in his "Understanding models understanding language" (2022) for a thesis of this sort. His idea is that (1) where there is semantics there is also understanding and (2) machines are not only capable of what he calls `inferential semantics', but even that they can (with the help of inputs from sensors) `learn' referential semantics. We show that he goes wrong because he pays (...) insufficient attention to the difference between language as used by humans and the sequences of inert symbols which arise when language is stored on hard drives or in books in libraries. (shrink)

Detecting quality in large unstructured datasets requires capacities far beyond the limits of human perception and communicability and, as a result, there is an emerging trend towards increasingly complex analytic solutions in data science to cope with this problem. This new trend towards analytic complexity represents a severe challenge for the principle of parsimony (Occam’s razor) in science. This review article combines insight from various domains such as physics, computational science, data engineering, and cognitive science to review the specific properties (...) of big data. Problems for detecting data quality without losing the principle of parsimony are then highlighted on the basis of specific examples. Computational building block approaches for data clustering can help to deal with large unstructured datasets in minimized computation time, and meaning can be extracted rapidly from large sets of unstructured image or video data parsimoniously through relatively simple unsupervised machine learning algorithms. Why we still massively lack in expertise for exploiting big data wisely to extract relevant information for specific tasks, recognize patterns and generate new information, or simply store and further process large amounts of sensor data is then reviewed, and examples illustrating why we need subjective views and pragmatic methods to analyze big data contents are brought forward. The review concludes on how cultural differences between East and West are likely to affect the course of big data analytics, and the development of increasingly autonomous artificial intelligence (AI) aimed at coping with the big data deluge in the near future. Keywords: big data; non-dimensionality; applied data science; paradigm shift; artificial intelligence; principle of parsimony (Occam’s razor) . (shrink)

: Driver drowsiness is a significant factor contributing to road accidents, resulting in severe injuries and fatalities. This study presents an optimized approach for detecting driver drowsiness using machine learning techniques. The proposed system utilizes real-time data to analyze driver behavior and physiological signals to identify signs of fatigue. Various machine learning algorithms, including Support Vector Machines (SVM), Convolutional Neural Networks (CNN), and Random Forest, are explored for their efficacy in detecting drowsiness. The system incorporates an optimization technique—such as Genetic (...) Algorithms (GA) or Particle Swarm Optimization (PSO)—to enhance the accuracy and response time of the detection process. The integration of optimization methods ensures that the model adapts to various driving conditions and individual differences, providing a more reliable and robust detection mechanism. Data from multiple sources, including camera feeds and wearable sensors, are used to train and validate the models, ensuring a comprehensive understanding of drowsiness indicators. (shrink)

Driver drowsiness is a significant factor contributing to road accidents, resulting in severe injuries and fatalities. This study presents an optimized approach for detecting driver drowsiness using machine learning techniques. The proposed system utilizes real-time data to analyze driver behavior and physiological signals to identify signs of fatigue. Various machine learning algorithms, including Support Vector Machines (SVM), Convolutional Neural Networks (CNN), and Random Forest, are explored for their efficacy in detecting drowsiness. The system incorporates an optimization technique—such as Genetic Algorithms (...) (GA) or Particle Swarm Optimization (PSO)—to enhance the accuracy and response time of the detection process. The integration of optimization methods ensures that the model adapts to various driving conditions and individual differences, providing a more reliable and robust detection mechanism. Data from multiple sources, including camera feeds and wearable sensors, are used to train and validate the models, ensuring a comprehensive understanding of drowsiness indicators. (shrink)

Introduction: The objective of this investigation is to analyse the informational circuits of the brain connections with the body from neurologic and neuroscience point of view, on the basis of the concepts of information promoted by the Informational Model of Consciousness. Analysis: Distinguishing between the virtual and matter-related information promoted by the Informational Model of Consciousness, the main specific features of consciousness are analyzed from the informational perspective, showing that the informational architecture of consciousness consists in seven groups of specific (...) activities, defined as cognitive centres, each of them with specific distinct tasks, but correlated each other: centre of acquisition and storing of information (memory), centre of decision and command (decision), centre of the emotional states (emotions), centre of the body maintenance (power and health), centre of the genetic elaboration/transmission (reproduction) and the info-genetic generator, inherited from the parents (predispositions, talents and skills). A special centre, dedicated to the connectivity with some extra-power properties of the mind is also introduced, assuring an intimate supra-sensitive detection of the world to explain the associated phenomena of the near-death experiences. Result: The activity of all these centres should be supported neurologically by the brain neuro-connectivity to the body and to external and internal info-signals. On the basis of the informational analysis, the neuro-connections of the brain regions associated to the main characteristics of the cognitive centres are highlighted, showing the anatomic and neuro-functional relation between the distinct components of the brain and the specific operating body regions. These connections describe in terms of information the brain-body neuro-activities as informational specific circuits, composed by the info-operational subsystems managed by the brain, and sensors, transducer and execution elements. Conclusion: The components and connections mind-body stipulated by the Informational Model of Consciousness are supported by the neurologic/neuroscience evidence. (shrink)