Owing to the rapid development and the evolvement of technology in the twenty-first century many domains such as agriculture, surveillance, military, healthcare and manufacturing are transforming with underlying technologies to cater to this growing demand. As a consequence the input data is becoming a vital component and strategic asset of every organization that ultimately maximizes the value of data, transferring them into meaningful information, which eventually helps in effective decisionmaking. This vast amount of vital and complex data which is also known as big data is becoming an integral part of every application domain including healthcare. Owing to the current demand and the latest trends, medical big data is growing day by day enormously, posing a variety of challenges. The big data in medical care has a considerable impact on improving the quality of healthcare, gaining insights about the patient's condition and reducing the overall cost and time of patient care, where it is a vital and successful factor for driving medical organizations to the next level. Even though big data in healthcare offer many advantages, the security and privacy of big data are becoming a tedious challenge among many other prevailing challenges, owing to the rapid demand for big data and as a result of its ever-growing endless nature. Nevertheless, as per the time being the security and privacy of medical data are overseen by many acts and regulations, where the medical big data should be protected from getting into the wrong hands, which if not endanger the lives of patients. Owing to the growing threats that target healthcare and to the further development of healthcare, the security and privacy aspect of medical big data needed to be concerned and solutions should be provided to make sure the trustworthiness of the environment. To go deeper into this topic, it's crucial to examine the critical components in the creation of security solutions for protecting medical big data from security and privacy risks. In this paper, we examine the present state of security and privacy problems in medical big data, as well as the current state of safe solution development, and propose a tiered framework for securing and preserving medical big data security and privacy.

Recent advancements in exoskeleton technology, both passive and active, are driven by the need to enhance human capabilities across various industries as well as the need to provide increased safety for the human worker. This review paper examines the sensors, actuators, mechanisms, design, and applications of passive and active exoskeletons, providing an in-depth analysis of various exoskeleton technologies. The main scope of this paper is to examine the recent developments in the exoskeleton developments and their applications in different fields and identify research opportunities in this field. The paper examines the exoskeletons used in various industries as well as research-level prototypes of both active and passive types. Further, it examines the commonly used sensors and actuators with their advantages and disadvantages applicable to different types of exoskeletons. Communication protocols used in different exoskeletons are also discussed with the challenges faced.

Abstract Purpose Learning disabilities or learning disorders are umbrella terms used for wide variety of learning problems like Dyslexia, Dyscalculia, Dysgraphia, and Dyspraxia. These disabilities are due to the neurological disorders which affects brain functions. Early diagnosis of these disabilities in kids from age 3 to 6 will help to start early medical treatments and get them back to the normal condition. Material and Method we developed a software-based Learning Disability Evaluation Kit called YALU with computer Game Modules for kids targeting their learning disabilities. These Computer game-based modules of the YALU consist of different tasks for the different age levels to identify the symptoms of the disabilities mentioned above. The children’s interaction results to each task of the game modules with the answers of the questioner about the children given by the parents will be evaluated with the threshold values given by a panel of consultant psychologist and paediatrician of the normal kids to identify the learning disabilities in kids aged 3–6 years. The result will be given to the respective parties and uploaded to the Website under the child’s name. Result YALU has been tested using 50 students in age 3–5 in three preschools. The teachers have identified Fourteen students with some learning disability symptoms. Using YALU, twelve out of fourteen students had been clearly identified. Hence, the YALU Evaluation Kit to have an accuracy 85% in diagnosing the right disability. However, the accuracy could be increased with the accurate assessments of the parents about their kids. IMPLICATIONS FOR REHABILITATION Learning disabilities are neurological disorders that affect the brain’s ability to receive, process, store, respond to and communicate information; and there are four types (Dyslexia, Dyspraxia, Dysgraphia and Dyscalculia) In this paper, we present the extracted computational techniques targeting the Dyslexia, Dyspraxia, Dysgraphia and Dyscalculia and developed a software application (YALU Learning Disability Evaluation Kit) which consists of computer game modules for the kids for evaluation their learning disabilities. The developed game modules can screen the learning disabilities and these gamification modules (YALU) consists of tasks which are based on symptoms of the said disabilities. The outcomes of each module is evaluated these learning disabilities in kids age from 3 years to 6 years by analysing children’s interactions to the each tasks, the child condition and then compare the result with the threshold values of the normal kids given by consultant psychologist and paediatrician.

Credit/debit cards are a ubiquitous form of payment at present. They offer a number of advantages over cash, including convenience, security, and fraud protection. In contrast, the inherent vulnerabilities of credit/debit cards and transaction methods have led many payment institutions to focus on strengthening the security of these electronic payment methods. Also, the increasing number of electronic payment transactions around the world have led to a corresponding increase in the amount of money lost due to fraud and cybercrime. This loss of money has a significant impact on businesses and consumers, and it necessitates the development of rigid and robust security designs for securing underlying electronic transaction methods. In this regard, this research introduces a novel geolocation-based multi-factor authentication method for improving the security of electronic payment transactions, especially ATM transactions. The proposed method leverages geolocation to verify the user's identity and prevent fraudulent transactions. In addition, this research also proposes a novel design approach for further controlling the ownership of transactions in a convenient way (e.g., allowing users to deactivate/reactivate authentication at any time, block the card in case it is stolen or lost, and set up a withdrawal limit). Overall, this approach does not require any major modifications to the existing banking infrastructure, which would be an ideal solution for securing ATM transactions around the world.

In this paper, a comprehensive review of the wireless body area network is provided. A review of the WBAN architectures, standard network topologies, and WBAN communication protocols is discussed in detail. Also, the security requirements of WBAN, security threats and types of attacks, and authentications used in WBAN are discussed. The paper also includes very detailed coverage of antenna types, antenna designs, and flexible antennas used in WBAN with some design considerations and comparisons. Some new energy harvesting technologies, materials used for energy harvesting, and energy management are also discussed. Energy harvesting and power management is an ever-growing area of research. Despite the fact that there are many nanogenerator-based energy harvesting methods, the demand for more efficient energy harvesting mechanisms is ever-increasing. The paper has an extensive discussion of energy harvesting and power management methods. Subsequently, some reviews of recent developments in wearable sensors and novel materials for developing wearable sensors are discussed. Finally, the application areas of WBAN are discussed

The Internet of Things (IoT) is a vast concept spreading rapidly throughout the world today. Due to their inherent nature, IoT devices are more vulnerable to attacks than other cyber infrastructure. In a typical IoT system, four different types of layers can be identified. Those layers can be specified as the application layer, data processing (software) layer, network layer, and sensing (physical) layer. According to this architecture, each layer operates under different technologies. Thus, various challenges and vulnerabilities related to security have emerged and exist. Thereby extant and forthcoming IoT applications must comply with standard cyber security guides and regulations to guarantee safety; otherwise, they would jeopardize the lives of people using these IoT applications resulting in chaos. To achieve this, IoT applications can create environments with end-to-end security by adding security measures and the required adjustment, guaranteeing safety and privacy. By bearing this in mind, this research reviews the different types of security challenges, such as access control attacks and physical security attacks found in each of the four layers of the IoT architecture, along with what countermeasures can be taken to mitigate these attacks. As the main objective of this research is to examine underlying security challenges in the standard IoT architecture, we examine and categorize IoT vulnerabilities and outline methods used to ensure such IoT systems safety. Further, we also present the future directions in terms of security and privacy of IoT as well.

The rapid growth of Information and Communication Technology (ICT) in the 21st century has resulted in the emergence of a novel technological paradigm; known as the Internet of Things, or IoT. The IoT, which is at the heart of today's smart infrastructure, aids in the creation of a ubiquitous network of things by simplifying interconnection between smart digital devices and enabling Machine to Machine (M2M) communication. As of now, there are numerous examples of IoT use cases available, assisting every person in this world towards making their lives easier and more convenient. With the latest advancement of IoT in variety of cyber-attacks that targets these pervasive IoT environments, which can even lead to jeopardizing the lives of peoples; that are involving with it. In general, this IoT can be considered as every digital object that is connected to the Internet for intercommunication. Hence in this regard in order to analyse cyber threats that come through the Internet, here we are doing an experimental evaluation to analyse the requests, received to exploit the opened Secure Shell (SSH) connection service of an IoT device, which in our case a Raspberry Pi devices, which connected to the Internet for more than six consecutive days. By opening the SSH service on Raspberry Pi, it acts as a Honeypot device where we can log and retrieve all login attempt requests received to the SSH service opened. Inspired by evaluating the IoT security attacks that target objects in the pervasive IoT environment, after retrieving all the login requests that made through the open SSH connection we then provide a comprehensive analysis along with our observations about the origin of the requests and the focus areas of intruders; in this study.

The Internet of Things, often known as IoT, is an innovative technology that connects digital devices all around us, allowing Machine to Machine (M2M) communication between digital devices all over the world, owing to the technological advancements in the 21 st century.Due to the convenience, connectivity, and affordability, this IoT is being served in various domains including healthcare where it brings exceptional benefits to improve patient care, uplifting medical resources to the next level.As of now, the IoT is served in various aspects of healthcare making many of the medical processes much easier as opposed to the earlier times.One of the most important aspects that this IoT can be used is, managing various aspects of healthcare during global pandemics, as pandemics can bring an immense strain on healthcare resources.As there is no proper study is done with regards to the proper use of IoT for managing pandemics, in this regard, through our study we aim to provide a comprehensive analysis of various use cases of IoT towards managing pandemics especially in terms of COVID-19 owing to what we are currently going through, along with key challenges and future directions.In this regard, we are proposing a contextual framework synthesizing the current literature and resources, which can be adopted when managing global pandemics like COVID-19 at the national and global levels.

. Information has become an integral in both individuals and the business and a large amount of digital information in new types is being generated every moment from different data capturing devices. As today we are living in an on-demand on-command world, the data analytics is playing an increasingly critical role for making full use of it in most of the business organizations. Different forms of analytics can be found, but they don't provide the best perspective or provide the right information. To turn a company into a profitable operation, top management relies heavily on decisions, which are in turn based on the type of knowledge available. Hence, we are going to introduce a new AI based BI Framework which can be used by different businesses, industries and service providing companies for predictions and to get the prescriptive decisions. In this paper, we are going to introduce a Business Intelligence tool for the AI based BI framework to analyse the big data set and to extract the required data and create a predictive model for making the prescriptive decisions for the business. This BI tool is sophisticated, user-friendly, cost-effective and comprehensive data-driven business intelligence tool for efficient prediction, and it can be used to analyse the big data sets of the industry. The BI tool must be trained using a data set of the same industry before it is used with the large data set. The tool first extracts the data set, transform the extracted data set to the required format and then it is loaded to the BI tool to select the suitable algorithm. The tool has a set of pre-defined algorithms and the loaded data set is analysed using these algorithms and get the percentage of accuracy in each algorithm we introduced with the tool. Then the end-users will be able to select the suitable algorithm for the data set and then it can be used with the big data set of the similar industry. The AI based BI framework provides the facility for many cross industries and businesses. In this work, we focused on the Telco Industry and we implemented our novel Business Intelligence tool for that industry. Because they are facing problems in finding hidden patterns in their large chunk of data which may have a big impact on their decision-making process. Most telecommunication companies are suffering from churn (customer leaving the service) of their customers day by day due to high competition within the competitor telco companies. This churning will badly effect to the huge financial losses and survival of such companies. The experiment result showed more than 90% accuracy of selecting the right churn customers and the tool helped to make the prescriptive decisions to the top management to minimize churning.

The Internet of Things, often known as IoT, is an innovative technology that connects digital devices all around us, allowing Machine to Machine (M2M) communication between digital devices all over the world. Due to the convenience, connectivity, and affordability, this IoT is being served in various domains including healthcare where it brings exceptional benefits to improve patient care, uplifting medical resources to the next level. Some of these examples include surveillance networks, healthcare delivery technologies, and smart thermal detection. As of now, the IoT is served in various aspects of healthcare making many of the medical processes much easier as opposed to the earlier times. One of the most important aspects that this IoT can be used is, managing various aspects of healthcare during global pandemics, as pandemics can bring an immense strain on healthcare resources, during the pandemic. As there is no proper study is done with regards to the proper use of IoT for managing pandemics, in this regard, through our study we aim to review various use cases of IoT towards managing pandemics especially in terms of COVID-19; owing to what we are currently going through. In this regard, we are proposing a conceptual framework synthesizing the current literature and resources, which can be adopted when managing global pandemics to accelerate the battle pace with these deadly pandemics and focusing on what the entire world is currently going through where almost more than four (04) million people are diminished of this COVID-19 pandemic.

Today in most sectors like ICT, Apparel and BPO, as the common practice employees are working as teams in projects. Selecting the right team for the right project in these industries is vital for the projects to make it a success since these industries have a high impact on the economy. In present this is mostly done with the experience of Higher Management. But with the churning of the employees' knowledge transferring process has been really complex since knowledge is not stored anywhere and also training a new candidate takes great amount of time and effort. People Clues is a business intelligence tool which selects the best team for a given project by analyzing their past experience, Educational Qualifications and Past Performances. People Clues has been built on the concept of Team Dynamics. User can provide Project details as the input and by analyzing human resource characteristics system will generate the best team for the relevant project. Mainly three algorithms have been used for the prediction while giving the chance of selecting the preferred algorithm to the user. In this paper we present a desktop and a web application that facilitates the task of automating dynamic team generation depending on the optimality or feasibility based on different knowledge areas such as team dynamics, predictive modeling, business intelligence, data mining and team characteristics.

In nature of the transmission medium the broadcast, Wireless sensor networks are vulnerable to security attacks.The nodes are placed in a hostile or dangerous environment where they are not tangibly safe in the MANETs.In many application, the data obtained from the sensing nodes need a false, or malicious node could intercept private information or could send false messages to nodes in the network.Among the major attacks Eavesdropping, Spoof Attack, Denial of Service, Wormhole attack, Sinkhole attack, Sybil attack, Selective Forwarding attack, Passive information gathering, Node capturing, and False or malicious node, Hello flood attack are common.In this paper, authors have proposed and implemented an efficient light weighted authentication secure routing protocol on top of an AODV.The focused area of the proposed routing protocol is increasing the network security of the MANET.Additionally, the paper evaluates the implemented protocol using NS2 simulator in different networks with SecAODV.

Road traffic accidents (RTAs) pose a public health and development challenge and greatly affect the human capital development of every nation. Main causes for a significant percentage of RTAs are recklessness, fatigue or stress, inexperienced driving and driving under the influence of alcohol. Reputed automobile companies and authorities have established standards and/or proactive/reactive solutions over the years to overcome this problem but the rates continue to grow each year. Software solutions that focus on preventing RTAs are difficult to be found in economy class automobiles that are used by the majority of consumers. The limited number of successful applications are either bound to a certain brand/model and/or focus on a specific task. SmartV is smart phone based vigilance monitoring system that focuses on the majority of factors contributing to RTAs. These include DUI (driving under the influence of alcohol), health issues and vehicle defects. The mobile application communicates with a heart rate monitor and a Bluetooth OBDII Adapter. These will continuously monitor the heart rate of the driver and the status of the vehicle respectively. During the course of the drive, the system monitors the behavior of the vehicle for existence of dangerous driving patterns that are defined in Visual Detection of DWI Motorists[8] a study conducted by U.S.A. N.H.T.S.A. The final product is a versatile, non-intrusive, flexible and most importantly an affordable mobile application that captures the vehicle's behavior, the health level of the driver and the status of the vehicle. Real environment operation of SmartV has yielded significant results proving itself to be a successful and an affordable Vigilance Monitoring System for the future.

Traceability systems have become a dominant component within the production and marketing companies as they can efficiently control the supply chain, minimize the risks of the production process, and help to enhance the consumer/customer reliability on products. Moreover, such systems can be used to meet the requirements of government rules and regulations about safety of the products. The potential of traceability systems to reap multifaceted benefits have been identified by many research works for many years but the apparent anomaly that these business industries do not still feel traceability systems as a catalyst for financial gains inhibits the practical deployment of tractability systems. Moreover, most of such systems could be traced the characteristics of one process or one location. But today, to get the cost benefits, final product may be a collection of intermediate sub products, produced and process in different locations. Efficient system of tracing such types of supply chain and processes are still a challenging issue.This paper we first review the currently available traceability systems and analyze the effectiveness, limitations practical problems of implementation. Most of these systems are less cost effectiveness, lack of accuracy and also lack of technological knowledge of the staff. We focus on a supply chain which has several sub processes and then we focus on the limitations and problems and introduce a traceability system by combination of horizontal and vertical traceability systems. Further, we are going to implement our system with a sales and marketing company business model. Our system mainly addresses the cost effectiveness, accuracy, user friendliness, preciseness and security. Further more, we have planned to implement this system in three phases.

Traceability systems have become a dominant management information system within the production and marketing companies as they can efficiently control the supply chain, by minimizing the risks of the production process, and helping to enhance the consumer/customer reliability on products. There may have some limitations of using available traceability systems with small and medium scale industries as there may have design-reality gap of such systems.In this paper, we first analyzed effectiveness, limitations and practical problems of the available traceability systems for supply chain management. Design gap between real system and proposed model, high cost, accuracy and lack of technically qualified staff are some main problems of such systems. Then we introduced a novel system, "Total Traceability System", to overcome such limitations and problems by minimizing the gap between design and on-the ground reality (minimize the design reality gap).Further, we are going to implement our system with a sales and marketing company business model. Our system mainly addresses the cost effectiveness, accuracy, user friendliness, preciseness and security. Furthermore, we have planned to implement this system in three phases.

The explosive growth of the network, end-host performances and their heterogeneities have resulted ever changing advancement and complexity of distributed computing environments. The users in such environment have not been provided a satisfactory service when they access the required objects. In this paper we focus on adaptive WWW content delivery, which is the most ubiquitous and popular way of information dissemination, primarily in the form of Web-server, Web-browser interaction. In these applications, we address controlling the quality of delivery and time of access tradeoff of the WWW contents. We implement this as a httpa protocol, which is an adaptive transcoding methodology for embedded images in Web pages, according to available channel bandwidth and other accessibility parameters at the client side. Compared to the conventional form of server side adaptive content delivery proposed in the literature, we propose a hybrid form of adaptation: client side progressive parameter estimation and server side transcoding of images, which is more scalable and flexible. Through experimental results we verify the performance of httpa

Distributed systems are some of the most successful structures ever designed for computer users with their undisputed benefits. However, this structure has also introduced several side-effects, most notably unanticipated runtime events and reconfiguration burdens imposed by environmental changes. In this paper, we discuss a model that enables an object to adapt itself in order to provide the required service by adaptively shifting into the optimal replication strategy. The strategy selection can be done according to environmental conditions in order to address unanticipated events and unpredictable hazards in distributed systems. Therefore, designing an adaptable replication scheme could have a major impact with the growing requirements to support distributed computing to overcome their rapidly growing complexity and to enable their further developments

Caching has long been used in most fields of the computer systems to enhance the scalability of the objects, improve the performance and reduce the access latency. A significant effort has been made to introduce cache-coherent algorithms for maintaining the consistency of such data objects in cache by keeping a higher freshness of the data. Updating the cache objects considering the access behavior and user preferences is one of an attractive solutions to maintain the consistency. In this paper, we define quality of data (QoD) metric to evaluate the amount of freshness that is necessary to satisfy the user requirements. We then focus on the update scheduling method that analyzes the access behavior of the cache objects and predicts the time interval for updating the cache. Here, we introduce the "average update interval method" that uses the most recent time between access values, to predict the time interval. Using our proposed algorithm, the user can not only access the preference view but also he can get the maximum QoD of the objects. Moreover we performed extensive experiments using web log data and simulation data. Then the results could conclude that the cache objects are maintaining more than 70% of consistency with the original objects.

New applications are being introduced for different areas such as commercial, education, and medical etc. A significant effort has been made in developing some of these applications considering the adaptability to the dynamically changing network and hosts' environments. In client-server applications, this adaptability is very important to enhance the reliability of the system and maintain the consistency of the objects. We describe a framework that can detect the changes in performance of the execution environment, and provide strategies in order to adapt such changes. Using these access strategies the client objects can access the server objects efficiently in a dynamically changing environment. We do not only consider the dynamic changes of the network characteristics but also consider the end-hosts performances before changing to the optimal strategy. Therefore the client objects can achieve the maximum usefulness of the environment. Here, we introduce three access strategies, namely client migration, direct access, and lazy access to impart an adaptive behavior to the client objects in the distributed environment. Advancing from the conventional static access models we propose algorithms to select the best-suited access strategy for the dynamic environment. Moreover the proposed model is to be implemented to the "juice" distributed object-oriented environment.