Artificial Intelligent and Soft Computing Methodologies

9th International Conference on Soft Computing, Artificial Intelligence and Applications (SAI 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Soft Computing. The conference looks for significant contributions to all major fields of the Artificial Intelligence, Soft Computing in theoretical and practical aspects. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.  Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to

The future society may be and most likely
1. A society without human labor
2. A society of free activities and free time
3. A company dreamed of by Heinz von Foerster, Henri Atlan and Ilya Prigogine
Part 1: Development issues of developed countries
1.1 They have already made and updated their industrial revolution, they are:
• A nano computer revolution that will boost the artificial intelligence foundation of automation and robotics (and aggravation of unemployment)
• A biotechnological and genetic revolution
• And to the revolution of the "service economy" where 65% of the active population produces 70% of national wealth (against 29% and 28% for industry and 6% and 2% for agriculture - France). These are the services that pay the most!
1.2 They have new groups - multinationals - and very active and dynamic social networks.
In this case, the future development for these already developed countries will focus on what? Or what is missing - the "almost" - to the development of today's society.
The perception - relatively widespread and fair - of a more technology-centric development - and its legal owners - than on humans feeds this ... but.
To which the question of "what" will bring about the future development of today's society becomes indeed relevant.

La coherencia y el realismo son cualidades que todo desarrollador de agentes inteligentes busca, estas cualidades no podrán ser alcanzadas sin la incorporación de emociones en los mecanismos de comportamiento de los agentes. A simple vista pareciera que las investigaciones siguen caminos erráticos, por lo que se hace pertinente determinar el estado actual de las investigaciones en el área de la incorporación y desarrollo autónomo de emociones en agentes inteligentes, para luego evaluar con propiedad si se están persiguiendo los objetivos correctamente.

In this paper, we present a complete view of an agentoriented software engineering methodology called ASEM E (for AgentSystemsEngineeringM Ethodology). Several parts of the methodology concerning different aspects of the whole development process have been already published in the past in several papers. However, our goal in this paper is to provide a global view on the methodology by providing information about the agent (and multi-agent systems) development process along with recent works concerning the tools that we have developed in order to facilitate the use of ASEM E by agent systems developers. We also provide some information on the different practical applications that we have developed by using ASEM E and which prove that ASEM E is very well suited for an easy development or real world applications.

—Satellite images are important source of information in many applications such as terrain mapping by remote sensing and GIS (Geographic Information System) applications. But information extraction by per pixel classification techniques proves to be very complex owing to the internal variability increase in land-cover units and to the weakness of spectral resolution. Image segmentation before classification was proposed as an alternative approach. Many image segmentation methods are available but most of these methods are not suitable for noisy and blurred satellite images and they require a priori knowledge. In order to overcome these obstacles, a new satellite image segmentation method is developed by combining watershed segmentation with a redundant wavelet transform. The method is applied to IKONOS images of different resolutions including noisy and blurred ones. Although the performance of the algorithm slightly changes for various complexity levels, it performs well for all types of satellite images.

Selection of an industrial robot for a specific purpose is one of the most challenging problems in modern manufacturing atmosphere. The selection decisions become more multifaceted due to continuous incorporation of advanced features and facilities as the decision makers in the manufacturing environment are to asses a wide varieties of alternatives based on a set of conflicting criteria. To assist the selection procedure various Multiple Criteria Decision Making (MCDM) approaches are available. The present investigation endeavours to mitigate and unravel the robot selection dilemma employing the newly proposed Multiplicative Model of Multiple Criteria Analysis (MMMCA) approach. MMMCA is a novel model in which all performance ratings are converted into numerical values greater than and equal to unity and converting all non-benefit rating into benefit category. Each normalized weight is used as the index of corresponding normalized ratings those are multiplied to obtain the resultant ...

Rechtlichen Anforderungen an automatisiertes Fahren basieren unter anderem auf dem Wiener Übereinkommen über den Straßenverkehr von 1968, das einen Rechtsrahmen für nationale Straßenverkehrsgesetze vorgibt. In Deutschland erfolgte mit Wirkung vom 21. Juni 2017 die Ergänzung der Paragraphen 1a und 1b in das Straßenverkehrsgesetz (StVG). Entsprechend dem § 1a Absatz 1 StVG ist der Betrieb eines Kraftfahrzeugs „mittels hoch- oder vollautomatisierter Fahrfunktion“ grundsätzlich zulässig, unter der Bedingung, dass die Funktion bestimmungsgemäß verwendet wird. Wegen der Bedeutsamkeit des Themas hatten sich 2015, 2018 und 2019 Arbeitskreise beim deutschen Verkehrsgerichtstag für Empfehlungen zum automatisierten Fahren ausgetauscht.
Hier wurde auch auf den bereits mehrfach von dem Juristen Prof. Dr. Dr. Hilgendorf zitierten „Aschaffenburger Fall“ von Januar 2012 hingewiesen. Dabei wurde davon ausgegangen, dass ein wegen Schlaganfall bewusstloser Fahrzeugführer durch einen aktivierten Lenkassistent in einen Ort eingefahren ist und im Anschluss zwei Menschen getötet hat. Das Fahrzeug entsprach dem Stand der Technik und Hilgendorf begrenzt in diesem konkreten Fall die Sorgfaltspfl icht des Herstellers durch den Grundsatz des erlaubten Risikos. Im Rahmen der Produktbeobachtungspflicht müssen jedoch seiner Meinung nach zukünftige Neuentwicklungen Konsequenzen aus diesem nun bekannten Verkehrsunfall ziehen. Als weiteres Beispiel wurde der tödliche Unfall in Tempe im US-Staat Arizona angesprochen, bei dem ein Uber-Testfahrzeug im selbstfahrenden autonomen Modus mit einer Fußgängerin und ihrem Fahrrad kollidierte. Es handelt sich dabei um den ersten aufgezeichneten tödlichen Fußgängerunfall mit einem selbstfahrenden Uber-Testfahrzeug. Auf der Basis von veröffentlichten Fotos des Deformierten Volvo XC90, der Unfallstelle mit den Endlagen konnte vom Verfasser eine Unfallrekonstruktion mit PC-Crash angefertigt werden. Unter Annahme einer Geschwindigkeit von 64 km/h (17,8 m/s) und einer sofort wirkenden Notbremsung 1,3 Sekunden vor Kollision mit einer Verzögerung von 6,8 m/s2 wäre der Unfall vermieden worden.
Als Basis für systematische Unfallanalysen mit künstlicher Intelligenz und Risikobewertungsmethoden (beispielsweise AcciMap, das Systems-Theoretical Accident and Process Model - STAMP und die Functional Resonance Analysis Method - FRAM) im Rahmen der Produktbeobachtung, dem Freigabeprozess und der Entwicklung von automatisierten empfiehlt sich eine flächendeckende Speicherung der Unfall-, Verkehrsfluss-, Wetter- und Fahrzeugbetriebsdaten.

Legal requirements for automated driving are based, amongst others, on the Vienna Convention on Road Traffic of 1968, which provides a legal framework for national road traffic laws pretends. In Germany, paragraphs 1a and 1b were added to the Road Traffic Act (StVG) with effect from 21 June 2017. According to Section 1a, Paragraph 1 of the StVG, the operation of a motor vehicle "by means of a highly or fully automated driving function" is generally permissible, provided that the function is used as intended. Due to the importance of the topic, working groups had exchanged recommendations for automated driving at the German Traffic Court Conference in 2015, 2018 and 2019.
Here reference was also made to the "Aschaffenburg case" of January 2012, which has already been quoted several times by the lawyer Prof. Dr. Dr. Hilgendorf. This case was based on the assumption that a driver who was unconscious due to a stroke had entered a town by means of an activated steering assistant and subsequently killed two people. The vehicle was state of the art and Hilgendorf limited the manufacturer's duty of care in this specific case by the principle of permissible risk. In his opinion, however, future new developments must draw consequences from this now known traffic accident within the framework of the product monitoring obligation. As a further example, the fatal accident in Tempe in the US state of Arizona was mentioned, in which an Uber test vehicle collided with a pedestrian and her bicycle in self-propelled autonomous mode. This is the first recorded fatal pedestrian accident involving a self-propelled Uber test vehicle. On the basis of published photos of the deformed Volvo XC90, the accident site with the end positions, the author was able to make an accident reconstruction with PC-Crash. Assuming a speed of 64 km/h (17.8 m/s) and an immediately effective emergency braking 1.3 seconds before collision with a deceleration of 6.8 m/s2 the accident would have been avoided.
As a basis for systematic accident analyses and risk assessment or Artificial Intelligence methods (e.g. AcciMap, the Systems-Theoretical Accident and Process Model - STAMP and the Functional Resonance Analysis Method - FRAM) in the context of product monitoring, the release process and the development of automated ones, it is recommended that accident, traffic flow, weather and vehicle operating data be stored area-wide.

In this study, a hybrid model based on ANFIS (Adaptive Neuro-Fuzzy Inference Systems), a predictive intelligent-based technique, and TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) was implemented for sustainable supplier selection. Selection of supplier is a crucial task for companies to achieve the objectives of inbound and outbound supply chain system. This selection process may be complex due to the inclusion of diverse subjective and objective factors. There is, therefore, the need for a reliable methodology to provide higher accuracy in predictions of anticipated supplier performance, and this article makes contributions in that direction. The model was applied in the retail end of a fast-moving consumer goods (FMCG) industry to select the best possible suppliers using the sustainability criteria of the triple-bottom-line. Available data from the FMCG retail sector was fed into the TOPSIS and ANFIS model to rank the suppliers. Results indicated that th...

— Anti-lock braking systems (ABS) are safety and control devices implemented in ground vehicles that prevent the wheel lock-up during panic braking. The existing ABS controls have the ability to regulate the level of pressure to optimally maintain the wheel slip within the vehicle stability range. However, the ABS shows strong nonlinear characteristics in which the vehicles equipped with the existing controllers can still have a tendency to oversteer and become unstable. In this paper, a new intelligent robust control method based on an active force control (AFC) strategy is proposed via a rigorous simulation study. It is designed and implemented in a hybrid form by having the AFC loop associated with an iterative learning (IL) algorithm cascaded in series with a self-tuning fuzzy logic (FL)-based proportional-integral-derivative (PID) control for the effective overall performance of the proposed ABS. Both the IL and FL techniques are for the appropriate acquisition and computation of the important parameters in the controller. From the results, it is evident that the FL-PID with ILAFC scheme shows faster and better response compared to the FL-PID and FL-PID+AFC controllers in the wake of the given load and operating conditions. The incorporation of the AFC-based scheme into the ABS serves to provide an enhanced and robust performance that has the potentials to be implemented in a practical and real-time system.

In the present research paper, an attempt has
been made to design for evaluating the assessment of student
in the educational environment by using the hybrid
clustering methods. Various issues along problems are
associated with the academic performance evaluation in the
field of education. The proposed new approach known as
hybrid clustering is based on integrated techniques of
Subtractive and Fuzzy C-Means clustering methods. The
assessment of student academic performance can be considered
as a clustering problem. The clusters are formed on
the basis of the intelligence level of students. The intelligence
level wise grouping is essential for maintaining the
homogeneity of the group. Otherwise it would be difficult
to provide good educational services to the highly diverse
student population.

International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI) is an open access peer-reviewed journal that provides an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Soft Computing. The Journal looks for significant contributions to all major fields of the Artificial Intelligence, Soft Computing in theoretical and practical aspects. The aim of the Journal is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.

In this study, a Best First Search (BFS) Based Intelligent PID Tuning Method is proposed for a mobile robot path tracking problem. BFS is an informed search strategy in Artificial Intelligence (AI). It has been used in many areas of intelligent systems. Here, it is used to search values of both ultimate period and ultimate gain of Ziegler-Nichols (ZN) PID Tuning Method. So, using these ultimate period and gain, PID parameters can be c from tables of ZN method. The performance measure in this problem is described as minimizing total error during any specified trajectory tracking. Thus the proposed method does not depend on the system model. It only needs error information during the tracking control. So, this method can be used to tune PID parameters of any tracking controller for a system with unknown system dynamics. The proposed method is tested with simulations in MATLAB during trajectory tracking of a mobile robot. In addition, it is compared with classical PID and conventional PID tuning methods including Ziegler-Nichols method, Tyreus-Luyben method, and Shinskey method.

Keywords: Intelligent PID tuning, best first search, autonomous mobile robot, mobile robot path tracking problem, computed torque PID control, dynamic model, Ziegler-Nichols, Tyreus-Luyben, Shinskey.

This article introduces and compares software development methodologies. This information will help you recognize which methodologies may be best suited for use in various situations. The target audience is all personnel involved in software development for the DoD. No attempt has been made to cover methodologies that are most applicable to smaller projects that can be accomplished by five or fewer software engineers. You may learn about several of these in [10]. Since the intended readers should consider government software standards in their use of methodologies, background on these standards is included.

Expert and intelligent systems try to simulate intelligent human experts in solving complex real-world problems. The domain of problems varies from engineering and industry to medicine and education. In most situations, the system is required to take decisions based on multiple inputs, but the search space is usually very huge so that it will be very hard to use the traditional algorithms to take a decision; at this point, the metaheuristic algorithms can be used as an alternative tool to find near-optimal solutions. Thus, inventing new metaheuristic techniques and enhancing the current algorithms is necessary. In this paper, we introduced an enhanced variant of the Flower Pollination Algorithm (FPA). We hybridized the standard FPA with the Clonal Selection Algorithm (CSA) and tested the new algorithm by applying it to 23 optimization benchmark problems. The proposed algorithm is compared with five famous optimization algorithms, namely, Simulated Annealing, Genetic Algorithm, Flower Pollination Algorithm, Bat Algorithm, and Firefly Algorithm. The results show that the proposed algorithm is able to find more accurate solutions than the standard FPA and the other four techniques. The superiority of the proposed algorithm nominates it for being a part of intelligent and expert systems.

For a long time, one of my dreams was to describe the nature of uncertainty axiomatically, and it looks like I've finally done it in my co∼eventum mechanics! Now it remains for me to explain to everyone the co∼eventum mechanics in the most approachable way. This is what I'm trying to do in this work. The co∼eventum mechanics is another name for the co∼event theory, i.e., for the theory of experience and chance which I axiomatized in 2016 [1, 2]. In my opinion, this name best reflects the co∼event-based idea of the new dual theory of uncertainty, which combines the probability theory as a theory of chance, with its dual half, the believability theory as a theory of experience. In addition, I like this new name indicates a direct connection between the co∼event theory and quantum mechanics, which is intended for the physical explanation and description of the conict between quantum observers and quantum observations [4]. Since my theory of uncertainty satises the Kolmogorov axioms of probability theory, to explain this co∼eventum mechanics I will use a way analogous to the already tested one, which explains the theory of probability as a theory of chance describing the results of a random experiment. The simplest example of a random experiment in probability theory is the " tossing a coin ". Therefore, I decided to use this the simplest random experiment itself, as well as the two its analogies: the " "flipping a coin " and the " spinning a coin " to explain the co∼eventum mechanics, which describes the results of a combined experienced random experiment. I would like to resort to the usual for the probability theory " coin-based " analogy to explain (and first of all for myself) the logic of the co∼eventum mechanics as a logic of experience and chance. Of course, this analogy one may seem strange if not crazy. But I did not come up with a better way of tying the explanations of the logic of the co∼eventum mechanics to the coin-based explanations that are commonly used in probability theory to explain at least for myself the logic of the chance through a simple visual " coin-based " model that clarifies what occurs as a result of a combined experienced random experiment in which the experience of observer faces the chance of observation. I hope this analogy can be useful not only for me in understanding the co∼eventum mechanics.

Human-Computer Expression is gaining momentum as a computer-interaction technique. In speech based search engines and assistants such as Siri, Google Chrome and Cortana, there has been a recent upsurge. Chatbots replace some of the tasks human workers have traditionally filled, such as remote customer service agents and educators. Effectiveness of chatbots continue to increase right from initial stage of rule-based chatbots. The purpose of this paper is to help researchers to find the research gap for future upgradation of chatbots. This paper presents a survey on the techniques used to design Chatbots and a comparison is made between different design techniques from nine carefully selected papers according to the main methods adopted.

IN HERE IS PROOF THAT THE AETHERS THEMSELVES ARE CHANGING AND BECOMING PURPLISH CIRCUITRY.  FOR THE ULTIMATE AI PROGRAM.  THEN THERE’S THE WORLDWIDE PURPLISH TIDAL WAVE IN THE ATMOSPHERE.  A BIG BIG CHANGE IS COMING.  IT IS VISIBLE TO EARTHLINGS.

left a reason for downloading OUR SHADOW SELVES The recognition that we live in a holographic reality, which we can alter, once we recognized it and become aware of it.  CORRECT!!!!!

3rd International Conference on Advances in Artificial Intelligence Techniques (ArIT 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and its advances. The Conference looks for significant contributions to all major fields of the Artificial Intelligence in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.

This paper has examined propagations and deliberations of AI in Sri Lankan software industry. A survey has been carried out for gathering the information. Even though software industry is a rapidly growing sector in Sri Lanka, it is lagging behind in terms of using AI technologies with compared to other countries in the world. According to the survey, this is due to the lack of popularity, knowledge, experts, requirements and sponsorship for the AI related software projects. Sri Lankan software industry has the required maturity to adopt with AI technologies and they have already made their foot print on potential markets where they could find advanced AI research and development projects in different domains. However, Sri Lankan software industry has not been able to achieve the required momentum, stability and the confidence on research and development projects in AI. Large-scale companies must increase their attention on AI technologies and the required knowledge and work force should be supplied through the Sri Lankan education system. Professional organizations, research groups, academics and the industry experts got a huge role to be played jointly to overcome the barriers in order to introduce AI technologies to the Sri Lankan software industry.

De nouvelles crypto-monnaies émergent quotidiennement, offrant des alternatives aux formes traditionnelles de paiement et permettant de nouveaux moyens d’échange tels que l’argentliquide. Ces devises couvrent Bitcoin, Litecoin et Etherium. En moins d’une décennie, le bitcoin est passé d’une curiosité obscure à un nom familier. Ces derniers temps, le bitcoin a  augmenté – avec des hauts et des bas – de quelques cents par pièce à plus de 4 000 $. Entre-temps, des centaines d’autres crypto-monnaies – égalant bitcoin en valeur marchande – ont émergé (graphique 1, panneau de gauche).      Bien que  le bitcoin ou ses sœurs semblent peu susceptibles de remplacer les monnaies souveraines, ils ont démontré la viabilité de la blockchain sous-jacente ou de la technologie du grand livre distribué (DLT).
Les investisseurs en capital-risque et les institutions financières investissent  massivement dans des projets DLT qui cherchent à fournir de nouveaux services financierset à fournir les anciens plus efficacement. Les blogueurs, les banquiers centraux et les universitaires prédisent des implications transformatrices ou perturbatrices pour les paiements, les banques et le système financier en général.

Many teachers and students in Nigerian institutions of learning find teaching and learning a herculean task and very boring because of the obsolete methods of teaching and learning in this sector of the Nigerian economy. New innovative and IT-driven approach will be used in this research to help improve the quality of teaching and learning in Nigerian schools. This research will try to find a solution to this problem, where both students and teachers will enjoy teaching and learning respectively in an environment where effective teaching and learning is the target objective.

Deep learning and image processing are two areas of great interest to academics and industry professionals alike. The areas of application of these two disciplines range widely, encompassing fields such as medicine, robotics, and security and surveillance. The aim of this book, 'Deep Learning for Image Processing Applications', is to offer concepts from these two areas in the same platform, and the book brings together the shared ideas of professionals from academia and research about problems and solutions relating to the multifaceted aspects of the two disciplines. The first chapter provides an introduction to deep learning, and serves as the basis for much of what follows in the subsequent chapters, which cover subjects including: the application of deep neural networks for image classification; hand gesture recognition in robotics; deep learning techniques for image retrieval; disease detection using deep learning techniques; and the comparative analysis of deep data and big data. The book will be of interest to all those whose work involves the use of deep learning and image processing techniques

We provide first steps toward building a software agent/robot with compassionate intelligence.  We approach this goal with an example software agent, EM-2.  We also give a generalized software requirements guide for anyone wishing to pursue other means of building compassionate intelligence into an AI system.

Abstract
There is no gain-saying that in the near future, our world, as it is known today will experience dramatic change, improvement, efficient means of doing things and loss of jobs in terms of work displacements. This has been the case since 1946 when the automobile industry improved their production by the use of automatic devices and controls – a term referred to as automation. Most experts, at the time, raised concern about these machines replacing factory workers. Rather than augment workers, and improve productivity, this process was misunderstood. But as we approach the latter part of the year 2020, a new paradigm shift seems to have occurred regarding the role of automation and AI in the future of work. This is what this paper will seek to address.

Keywords: Artificial Intelligence, Automation, Machine learning, Employment, Displacement

The construction industry is witnessing a rapid rise in tall building projects due to an anticipated urban population explosion. However, this building typology has been subject to time overruns and total abandonment due to an underestimation of the project duration. Consequently, this paper presents the development of a model to predict the construction duration of tall building projects. In developing the model, a suite of machine learning algorithms was adopted including Multi-Linear Regression Analysis (MLRA), k-Nearest Neighbors (KNN), Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Ensemble Methods. Thus, twelve models were developed in the process, and the most efficient model was selected. The procedure described in this study presents researchers and practitioners with a strategy to enhance the time performance of tall building projects through the adoption of modern digital technologies such as machine learning. The proposed model was based on an ensemble method using ANN as the combiner, with a Correlation Coefficient (R 2) of 0.69, Root Mean Squared Error (RMSE) of 301.72, and Mean Absolute Percentage Error (MAPE) of 18%.

Neuron Structure:
The spikes travelling along the axon of the pre-synaptic neuron trigger the release of neurotransmitter substances at the synapse.
The neurotransmitters cause excitation or inhibition in the dendrite of the post-synaptic neuron.
The integration of the excitatory and inhibitory signals may produce spikes in the post-synaptic neuron.
The contribution of the signals depends on the strength of the synaptic connection.

As the name specifies “HOSTEL MANAGEMENT SYSTEM” is software developed for managing various activities in the hostel. For the past few years the number of educational institutions is increasing rapidly. Thereby the number of hostels is also increasing for the accommodation of the students studying in this institution. And hence there is a lot of strain on the person who are running the hostel and software’s are not usually used in this context. This particular project deals with the problems on managing a hostel and avoids the problems which occur when carried manually.
Identification of the drawbacks of the existing system leads to the development of computerized hostel management system for Catholic University College of Ghana that will be compatible to the existing system with the system which is more users friendly and more GUI oriented. We can improve the efficiency of the system, thus overcome the drawbacks of the existing hostel management system. Less human error, Strength and strain of manual labor can be reduced, High security, Data redundancy can be avoided to some extent, Data consistency, Easy to handle, Easy data updating, Easy record keeping, Backup data can be easily generated.

ARTICLE INFO SolidCAM is a popular add-in of SolidWorks. SolidCAM is the manufacturing suite for Keywords: easiest, fastest, most efficient computer numerical control (CNC) simulation and prog-CAM amming facility that can be done directly inside SolidWorks. It provides a seamless si-SolidCAM iMachining ngle window integration and full associativity with the SolidWorks model. SolidCAM CNC iMachining is a real breakthrough in CNC milling tool path technology. The iMachining Simulation technology uses a intelligent, patented algorithms for specific operations to optimize G-code the tool path, reduce machining time, tool wear etc. A great variety of machining operations on different stock objects for producing various products can be easily defined *Corresponding author: by using this suite which results in increased flexibility. The simulation process makes nazma.kuet@yahoo.com it possible to observe the operations in real time conditions and makes the g-code flaw-(Sultana, N.) less for physical operation. In this paper, SolidCAM iMachining is studied and the detailed procedures of the machining process of a spur gear from stock material is descry-bed step by step by using SolidCAM 2014 2D iMachining technology. After the steps are defined the whole process is simulated in various modes. Finally the G-codes are automatically generated for the practical use in CNC machine. SolidCAM helps understand the concept, operation and importance of using CAM software in modern day manufacturing industries. Moreover by using SolidCAM the steps of operation, parameter details can be set in a way to save time, cost, tool lives etc.

DATA STRUCTURES AND ALGORITHMS - STUDENT VERSION
UNIVERSITY OF TOURISM TECHNOLOGY AND BUSINESS STUDIES(UTB) – DEPARTMENT OF BUSINESS INFORMATION TECHNOLOGY
  “Just-in-time-erudition, learning by case in point, and Learning by doing and  Demonstrating.”

Artificial intelligence (AI) research and regulation seek to balance the benefits of innovation against any potential harms and disruption. However, one unintended consequence of the recent surge in AI research is the potential re-orientation of AI technologies to facilitate criminal acts, term in this article AI-Crime (AIC). AIC is theoretically feasible thanks to published experiments in automating fraud targeted at social media users, as well as demonstrations of AI-driven manipulation of simulated markets. However, because AIC is still a relatively young and inherently interdisciplinary area—spanning socio-legal studies to formal science—there is little certainty of what an AIC future might look like. This article offers the first systematic, interdisciplinary literature analysis of the foreseeable threats of AIC, providing ethicists, policy-makers, and law enforcement organisations with a synthesis of the current problems, and a possible solution space.

International Journal of Computer Science, Engineering and Applications (IJCSEA) is an open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer science, Engineering and Applications. The journal is devoted to the publication of high quality papers on theoretical and practical aspects of computer science, Engineering and Applications.

It is often thought that consciousness has a qualitative dimension that cannot be tracked by science. Recently, however, some philosophers have argued that this worry stems not from an elusive feature of the mind, but from the special nature of the concepts used to describe conscious states. Marc Champagne draws on the neglected branch of philosophy of signs or semiotics to develop a new take on this strategy. 

The term “semiotics” was introduced by John Locke in the modern period – its etymology is ancient Greek, and its theoretical underpinnings are medieval. Charles Sanders Peirce made major advances in semiotics, so he can act as a pipeline for these forgotten ideas. Most philosophers know Peirce as the founder of American pragmatism, but few know that he also coined the term “qualia,” which is meant to capture the intrinsic feel of an experience. Since pragmatic verification and qualia are now seen as conflicting commitments, Champagne endeavors to understand how Peirce could (or thought he could) have it both ways. The key, he suggests, is to understand how humans can insert distinctions between features that are always bound.

Recent attempts to take qualities seriously have resulted in versions of panpsychism, but Champagne outlines a more plausible way to achieve this. So, while semiotics has until now been the least known branch of philosophy ending in –ics, his book shows how a better understanding of that branch can move one of the liveliest debates in philosophy forward.

3rd International Conference on Artificial Intelligence and Machine Learning (CAIML 2022) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and Machine Learning. The Conference looks for significant contributions to all major fields of the Artificial Intelligence,
Machine Learning in theoretical and practical aspects.

The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.