Journal of NCBAE

A healthcare model to predict skin cancer using deep extreme machine learning

2022-06-27T13:08:01+00:00

In the modern world, skin diseases are the leading cause of death in humans. Malignant skin growths most commonly develop on areas of the body that are exposed to sunlight, but they can appear anywhere on the body. In the early stages, most skin tumors are treatable. Early and rapid detection of skin diseases can save a patient's life. Innovation makes it possible to detect skin diseases at an early stage. A biopsy is a formal technique for detecting malignant growths on the skin [1]. After the skin cells are removed, the example is sent to different research centers for testing. The interaction is difficult and time-consuming, and we have developed a framework for spotting skin malignant growths with SVM for the early detection of skin cancers. Patients benefit more from this. Diagnoses are made using image processing strategies and support vector machines (SVMs). Various pre-handling procedures for clamor evacuation and picture improvement are performed on the coloscopy picture of skin disease. A thresholding procedure is then used to divide the picture. The GLCM method should be used to separate a few highlights in the image. The classifier uses these elements as inputs. The data is then classified using SVM. A harmful or harmless image is classified

Context Aware Win-Win Situation For Automatic Negotiation In Intelligent Agents

2022-06-22T12:39:26+00:00

Negotiation is an important human activity in almost every matter of daily life to reach an agreement. Several automated negotiation support systems have been developed to help ease the negotiation process in human-to-human or human-to-agent negotiation. The major drawback of available systems is that they mainly focus on an agent to agent communication, which may not be suitable in an environment where humans make decisions, particularly in multi-literal negotiations. This research paper aims to present a Context-Aware Win-Win Situation for Automatic Negotiation (CAWSAN) for mutual negotiation between human and intelligent agents. Proposed system will be used for automated negotiations using a win-win strategy where preference elicitation will be performed by human negotiator while offer generation and offer evaluation will be handled by autonomous agent. In negotiation, a win-win strategy is a kind of compromise/cooperation where any negotiator generates an offer which is more acceptable for his/her counterpart by compromising claims on one matter to get extra benefit on other issues. A heuristic computational model is proposed in this research to simulate win-win strategy. The proposed computational model will employ a novel linear algorithm to estimate the preferences of other participants by using hill climbing approach to search the space of possible tradeoffs that are more acceptable by other negotiators.

An IoMT enabled smart healthcare model to monitor elderly people using Explainable Artificial Intelligence (EAI)

2022-06-28T09:58:13+00:00

Disease forecast and control via several healthcare gadgets and services have recently recognized a lot of attention, especially with the fast transition to an ageing people and increased attention in healthcare. In this age of advanced technology, advances in the Internet of Medical Things (IoMT), wearable sensors, and telecommunication technologies have made human life smarter, enabling smart healthcare services. The Internet of Things (IoT) can revolutionize the healthcare sector. By utilizing Wireless Body Sensor Networks (WBSNs) and Implantable Medical Devices based IoMT, smart healthcare systems (SHSs) are delivering quick and effective disease medication. This paper describes an IoMT-based intelligent healthcare model that uses explainable artificial intelligence (EAI) to keep track of the health of elderly people. EAI can be used to overcome the explainability and reliability limitations of Machine Learning (ML) and Deep Learning (DL) models, resulting in more accurate results.

Working Memory Model for Multi-party Interaction Using Audiovisual Perception

2022-06-22T11:24:57+00:00

Human mind integrates visual and natural language information simultaneously and perform context switching between different tasks and they also have ability to learn from environment. Interactive systems having cognitive capabilities can learn and acquire knowledge within dynamic environment. Their responses in environment are more human like as compare to the static conversational agents. These systems have limitations to perform multi-party interaction on the basis of cognitive constructs with audiovisual stimuli. Therefore, there is a need to design a working memory model that will serve as an executive control for the required cognitive processing of multisensory modalities perceived within the context of multiparty interaction. This agent will be capable to perform fusion of data collected from different sensors. This may allow the underlying agent to act more humanly due to its subjective nature of selection of context and attention of the afore-mentioned percepts. Such agent that has multiparty capabilities can be applied as an effective conversational agent in any multi-party environment.

Female labor force participation and women empowerment in KPK, Pakistan according to 21st century

2022-06-29T13:27:33+00:00

This essay's goal is to shed light on the variables that affect married women's decisions to enter the workforce in KPK, Pakistan. This empirical study on the PDHS for the years 2017–18 uses binary logistic regression (1973 sample size). The findings show that while women's age and place of residence have a positive but slight impact on empowerment, women's education, occupation, wealth index, and husband's education all have a positive and statistically significant impact. A socioeconomic policy can be created for a developing area like KPK, Pakistan, on the basis of this research. On the basis of this research, a development policy can be created to improve human resource development for a developing and traditional economy like Pakistan, with a particular focus on gender issues. Researchers, decision-makers, and social scientists can all benefit from the conclusions of this work since it will raise the bar for social welfare and equity.