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Previous research has shown that artists employ flexible attentional strategies during offline perceptual tasks. The current study explored visual processing online, by tracking the eye movements of artists and non-artists (n=65) while they produced representational drawings of photographic stimuli. The findings revealed that it is possible to differentiate artists from non-artists on the basis of the relative amount of global-to-local saccadic eye movements they make when looking at the target stimulus while drawing, but not in a preparatory free viewing phase. Results indicated that these differences in eye movements are not specifically related to representational drawing ability, and may be a feature of artistic ability more broadly. This eye movement analysis technique may be used in future research to characterise the dynamics of attentional shifts in eye movements while artists are carrying out a range of artistic tasks.

To realize high-quality transit-time ultrasonic flow measurements, accurate and precise estimates of the transit-time difference are essential. In this study, we propose deep learning-based neural network (NN) models to measure the transit-time difference in an ultrasonic flowmeter using a linear array transducer. Three approaches to compute the transit-time difference are presented: the cross-correlation with phase zero-crossing (XCorr), fully connected NN, and recurrent neural network (RNN) with long short-term memory (LSTM). The training data for the NN were generated by simulating target time differences by utilizing the experimental data acquired in the pipe system. To evaluate the performance of the proposed methods, linear regression, the Bland–Altman plot, and the root mean squared error (RMSE) were analyzed using testing data from the experiment. The results of this study show that the RNN-based approach yielded improved performance with an accuracy of up to 94% and a 33.48% reduction in the RMSE, compared to the XCorr method. In addition to the time difference estimation, our proposed RNN-based model can replace the entire flow rate estimation process, including interpolation, velocity correction, and zero-flow calibration. This study demonstrates the feasibility of an intelligent ultrasonic flowmeter employing the RNN-based model with potential in industrial applications.

Implementing AI in all fields is a solution to the complications that can be troublesome to solve for human beings and will be the key point of the advancement of those spheres. In the marine world, specialists also encounter some problems that can be revealed through addressing AI and machine learning algorithms. One of these challenges is determining the depth of the seabed with high precision. The depth of the seabed is utterly significant in the procedure of ships at sea occupying a safe route. Thus, it is considerably crucial that the ships do not sit in shallow water. In this article, we have addressed the fuzzy c-means (FCM) clustering algorithm, which is one of the vigorous unsupervised learning methods under machine learning to solve the mentioned problems. In the case study, crowdsourced data have been trained, which are gathered from vessels that have installed sound navigation and ranging (SONAR) sensors. The data for the training were collected from ships sailing in the south part of South Korea. In the training section, we segregated the training zone into the diminutive size areas (blocks). The data assembled in blocks had been trained in FCM. As a result, we have received data separated into clusters that can be supportive to differentiate data. The results of the effort show that FCM can be implemented and obtain accurate results on crowdsourced bathymetry.

Software-Defined Networking (SDN) and Network Function Virtualization (NFV) help reduce OPEX and CAPEX as well as increase network flexibility and agility. But at the same time, operators have to cope with the increased complexity of managing virtual networks and machines, which are more dynamic and heterogeneous than before. Since this complexity is paired with strict time requirements for making management decisions, traditional mechanisms that rely on, e.g., Integer Linear Programming (ILP) models are no longer feasible. Machine learning has emerged as a possible solution to address network management problems to get near-optimal solutions in a short time. In this paper, we propose a Graph Neural Network (GNN) based algorithm to manage Virtual Network Functions (VNFs). The proposed model solves the complex VNF management prob-lem in a short time and gets near-optimal solutions.

Since the concept of Software-Defined Networking (SDN) and Network Function Virtualization (NFV) has been proposed, telcos and service providers have leveraged these concepts to provide their services more efficiently. However, as the virtual network in the data centers becomes more complex, a variety of new network management problems arise. To deal with these management problems, it is necessary to monitor and analyze resource usage and traffic load of Virtual Network Functions (VNFs) operating on the virtual network. Recently, there have been many attempts to develop technologies that enable network management without human intervention. In this paper, we specify our anomaly detection problem with scenarios involving SLA violations to satisfy the practical needs of network management. Also, we set the real-world NFV environment to generate anomalous data corresponding to each scenario and extend our approach to implementing the system for root-cause localization which identifies the exact VNF instance causing the SLA-related anomalies. We use the datasets collected from the VNFs’ service function chain scenarios implemented on OpenStack environment, and compare the accuracy of the anomaly detection models generated by various machine learning algorithms. Our experimental results show the best model has F1-measure over 95% for anomaly detection and 93% for root-cause localization.

Since the concept of Software-Defined Networking (SDN) and Network Function Virtualization (NFV) has been proposed, telcos and service providers have leveraged these concepts to provide their services more efficiently. However, as the virtual network in the data centers becomes more complex, a variety of new network management problems arise. To deal with these management problems, it is necessary to monitor and analyze resource usage and traffic load of Virtual Network Functions (VNFs) operating on the virtual network. Recently, there have been many attempts to develop technologies that enable network management without human intervention. Many of these attempts based on machine learning technologies are limited to detecting typical resource usage-related anomalies with a binary classification such as CPU/memory or traffic overload. In this paper, we specify our anomaly detection problem with scenarios involving SLA violations to satisfy the practical needs of network management. We use the datasets collected from the VNFs’ service function chain scenarios implemented on OpenStack environment, and compare the accuracy of the anomaly detection models generated by various machine learning algorithms. Our experimental results show the best model has F1-measure over 95% for anomaly detection.

Network Function Virtualization (NFV) environment can deal with dynamic changes in traffic status with appropriate deployment and scaling of Virtualized Network Function (VNF). However, determining and applying the optimal VNF deployment in consideration of the cost and Quality of Service (QoS) is a complicated and difficult task. In particular, it is necessary to predict the situation at a future point when the deployment decision is applied because it takes processing time to apply the deployment decision to the actual NFV environment. In this paper, we randomly generate service requests in Multiaccess Edge Computing (MEC) topology, then obtain optimal VNF deployment and Service Function Chaining (SFC) result from an Integer Linear Programming (ILP) solution. We use the simulation data to train a machine learning model which predicts the optimal VNF deployment at a predefined future point. The prediction model shows the accuracy over 90% compared to the ILP solution for the 5-minute future time point.

Software-Defined Networking (SDN) and Network Function Virtualization (NFV) help reduce OPEX and CAPEX as well as increase network flexibility and agility. But at the same time, operators have to cope with the increased complexity of managing virtual networks and machines, which are more dynamic and heterogeneous than before. Since this complexity is paired with strict time requirements for making management decisions, traditional mechanisms that rely on, e.g., Integer Linear Programming (ILP) models are no longer feasible. Machine learning has emerged as a possible solution to address network management problems to get near-optimal solutions in a short time. In this paper, we propose a Graph Neural Network (GNN) based algorithm to manage VNFs. The proposed model solves the complex VNF management problem in a short time and gets near-optimal solutions.

In the maritime field, interest in the utilization of multiple and various domains' data for provision of relevant, accurate and timely information ensuring the safety and security of navigation at sea has been growing. Discussion, for example, of the implementation of e-navigation, a new maritime service paradigm introduced by the International Maritime Organization, is ongoing. E-navigation enables and facilitates the on- and off-shore exchange, sharing and utilization of marine and marine-related domains' data in support of users' decision-making. For consistent exchange and sharing of marine and marine-related data in the e-navigation environment, the International Hydrographic Organization's S-100 has been adopted as the baseline of the common maritime data structure. S-100 provides common data models for consistent definition of data elements representing data contents. To that end, it supports syntactic-level data interoperability among S-100 applied e-navigation systems. However, the current S-100 does not provide methods or models for formal representation of data semantics or semantic-level harmonization of data. Therefore, current e-navigation-system efforts are focusing on the utilization of multiple domains' data at the syntactic-level. To provide relevant information for various marine activities, e-navigation systems should be able to handle various domains' data and integrate them at the syntactic-level. In this paper, we introduce a method by which multiple domains' S-100-based data can be integrated according to the characteristics of such data. Additionally, we present a method for consistent display and integration of multiple domains' S-100-based data. These methods promise to greatly facilitate S-100-based e-navigation systems' handling of multiple and various domains' data.

It is indisputable that a great deal of brand new technologies such as the internet of things, (IoT) big data, and cloud computing are conquering every aspect of our life. So, in the branch of marine technology, the mentioned technologies are also being applied to obtain more features and to automate marine-related operations as well as creating novel smart devices. As a result of this, traditional ports and ships are being replaced by smart ports and vessels. To achieve this transition, numerous applications need to be developed to make them smart. The purpose of this paper is to present a dedicated an IoT-based system for automating linkage procedures by searching for available locations via port-mounted sensors and planned ship notification. In the experimental system, we have used smartphone as an alternative to the client-side vessel of the system and created an Android app called &ldquo, Smart Ship Berthing&rdquo, instead of the charging program, for instance, NORIVIS 4, VDASH, ODYSSEY, etc. To test our proposed server-side system, we used Raspberry Pi with a combination of an ultrasonic sensor to detect the ship and modify the empty berth for anchoring. The experimental results show that the set of UR sensors have high accuracy to detect ships at the port for ship berthing and our proposed system is very amenable to implementation in the real marine environment.

Internet of things (IoT) and Smart Tings has gained wide interest across various segments such as telecommunications, informatics, electronics and social science. In this paper, we propose (Aqlli va Uchuvchi Soyabon (AVUS)) a new Smart Flying Umbrella which is not only to prevent the rain it also provides a variance of services to users. However, with the use of smartphone application, Smart flying Umbrella can inform the customer about the weather status. The presence of the smart fly Umbrella has a different appearance such as giving the alarm before raining also the times of harmful sun rays with the help of the smartphone depend on the IoT environment. It is evident from the term that our purposing new smart device can substitute the older ones’ functions by flying above the human’s head and in this case, it doesn’t need any human’s assistance. This paper is going to clarify the initial form and conception of AVUS. Apart from this, the paper mainly focuses on possible device and methods which dedicated to the device in order to represent some peculiarities to follow humans and it presents feasible problems that can be faced while carrying out these functions and supports possible solutions.

In the maritime field, e-navigation, a new-paradigm information service framework that provides proper, accurate and timely information related to various marine activities at sea, has been widely discussed. For consistent exchange, sharing, and use of data among e-navigation services, the S-100 standard of the International Hydrographic Organization was adopted as the Common Maritime Data Structure. To provide proper information in the form of e-navigation services for various activities at sea, it is necessary to integrated, at the semantic level, S-100-based data that exists in several domains and is distributed both onboard and ashore. Whereas S-100, as the common data model, resolves the issue of syntactic interoperability among domains, it does not provide for semantic interoperability. In this paper, we introduce for the purposes of effective e-navigation, a multi-domain data utilization structure based on a marine knowledge base for support of the semantic representation of S-100-compliant data and their semantic interrelationships. The multiple-domain data utilization structure enables e-navigation services to access multiple-domain data and to find the e-navigation services best supporting their marine activities.

Internet of Things, Big Data, Cloud Computing and such last model technologies are taking a pace towards every part of our life. It is worth to mention that novel technologies are being directed towards obtaining more improvements in the field of Marine. Applying the IoT in particular industries makes that industry’s working process automation and creates various smart devices in the field. Also, in Marine, the process comes out identically to those industries. Namely, smart ports and smart ships substitute traditional ports and vessels. However, it should be considered that applying the technologies in the fields is not effortless. Perhaps, this process should be done pace by pace. So, building a smart ship and smart port which is expected to be the fundamental basement of shipping requires much time. To obtain it, traditional versions of the objects in the field should be alerted to smart substitutions and the processes also should be automated by dividing them into parts. In this paper, we presented a system which is dedicated to automating the mooring process of ships. The premium target of our IoT based system is finding vacant places automatically by using the sensors fixed at the port and transfer the data to the ships which are going to berth. In the experimental system, we used a smartphone instead of a ship for client-side of the system and made one Android Application that called “Smart Ship Berthing” instead of ship software. And for our proposed server-side system experiment, we utilized Raspberry Pi with Ultrasonic Sensor to detect a ship and modify empty place to berth.

Currently the International Maritime Organization (IMO) is taking the lead in developing e-navigation as an information service framework. E-navigation supports sharing, harmonization and utilization of various marine and marine-related data both shipboard and onshore. Recently, the IMO adopted the International Hydrographic Organization (IHO)'s S-100 as the basis of the Common Maritime Data Structure (CMDS) of e-navigation. Thus, the various data are to be provided to e-navigation services in formats consistent with the S-100 data model. E-navigation services, in order to provide appropriate information to users, utilize and harmonize many kinds of S-100-based data such as Electronic Navigation Chart (ENC) data, bathymetric data, tidal data, meteorology data, radar-image data, and Automatic Identification System (AIS) data. In e-navigation, data management systems dealing with S-100-based data facilitate e-navigation services' harmonization and utilization of the various S-100-based data. In this paper, we present an S-100 data management system that deals with various S-100-based data. We designed the system by generalization of the System ENC (SENC) kernel that manages S-101 ENC data. For development of a data management system that supports the management of various kinds of S-100-based data, we analyzed the characteristics of the S-100 data model and S-100-based data products. The S-100 data management system is designed to store S-100-based feature-oriented geographic data in the form of pairs.

Minimum variance (MV) beamforming has been studied for improving the performance of a diagnostic ultrasound imaging system. However, it is not easy for the MV beamforming to be implemented in a real-time ultrasound imaging system because of the enormous amount of computation time associated with the covariance matrix inversion. In this paper, to address this problem, we propose a new fast MV beamforming method that almost optimally approximates the MV beamforming while reducing the computational complexity greatly through dimensionality reduction using principal component analysis (PCA). The principal components are estimated offline from pre-calculated conventional MV weights. Thus, the proposed method does not directly calculate the MV weights but approximates them by a linear combination of a few selected dominant principal components. The combinational weights are calculated in almost the same way as in MV beamforming, but in the transformed domain of beamformer input signal by the PCA, where the dimension of the transformed covariance matrix is identical to the number of some selected principal component vectors. Both computer simulation and experiment were carried out to verify the effectiveness of the proposed method with echo signals from simulation as well as phantom and in vivo experiments. It is confirmed that our method can reduce the dimension of the covariance matrix down to as low as 2 × 2 while maintaining the good image quality of MV beamforming.

In the maritime field, integration of information service architectures and a common data model currently are topics of considerable interest. The International Hydrographic Organization (IHO) introduced the S-100 standard for the universal hydrographic data model and publishes Geographic Information (GI) registers in order to support the wider use of, the ease of access to, and the development of S-100 based product specifications. GI registers can be used with other domains’ registers. Whereas each register might have contents for each domain or each specific type, extracting cross-domain or cross-type contents from registers is not easy. In this paper, we present three register ontologies based on the ISO 19135 register schema model, the S-100 model, and the FCD model, respectively. As each register ontology represents concept classes and their relations on different level, we also present ontology-mapping methods for enhanced interoperability of GI registers based on ISO 19100 series.

The IHO S-100 is a standard on the universal hydorgraphic data model for supporting information services that integrate various data in maritime and provide proper information for safety of vessels. The S-100 is used to develop S-10x product specifications which are standards on guideline for creation and delivery of specific data set in maritime. The product specification for feature-based data such as ENC(Electronic Navigational Chart) data includes a feature catalogue that describes characteristics of features in that feature-based data. The feature catalogue is developed by domain experts with knowledge on data of the target domain. However, it is not feasible to develop a feature catalogue according to the XML schema by manual. In the IHO TSMAD committee meeting, needs of developing technology on building feature catalogue has been discussed. Therefore, we present a feature catalogue builder that is a GUI(Graphic User Interface) system supporting domain experts to build feature catalogues in XML. The feature catalogue builder is developed to connect with the FCD(Feature Concept Dictionary) register in the IHO(International Hydrographic Organization) GI(Geographic Information) registry. Also, it supports domain experts to select proper feature items based on the relationships between register items.

In the maritime field, e-navigation, the new maritime service environment paradigm, is a topic of wide discussion. According to the e-navigation concept, the various marine and marine-related domains' data both on- and off-shore are used as resources for maritime services, the purpose of which are to facilitate communication at sea and to ensure safe navigation. To those ends, e-navigation services exchange, share, and utilize data resources created and distributed according to the data product specifications based on the e-navigation Common Maritime Data Structure (CMDS). Currently, maritime equipment and systems transfer data among themselves over ships' networks. In e- navigation, those equipment and systems' data will be utilized as useful data resources. But before that data can be used, it is necessary to create and distribute it according to the above-noted CMDS-based data product specifications. When a data product specification is developed for a specific domain, a common vocabulary for that domain is needed for consistent specification of the data elements that represent the data contents. In this paper, we present a common vocabulary set for consistent representation of the data elements of maritime equipment and systems shipboard. To build the common vocabulary set, we analyzed the digital interface standards for maritime navigation and radio- communication equipment and systems. By analysis of approved sentences for data transmission of maritime equipment and systems, we extracted candidate terms and built the common vocabulary according to the e- navigation CMDS base model.

Electronics devices are always targeted with different kind of attacks due to their activities related to data processing, data storages and data transactions. In each case, the attacker performs the attacker according to what he needs from the device. In this paper, we present various attacks types on electronics devices in particularly on crypto-module devices where we focus on side channel attacks in its form of attacks such as power analysis attack, electromagnetic attack and fault injection attack. Finally, we develop a series of countermeasures against the side-channels attacks on crypto-module devices where the result shows that they are resilient and achieve better efficient.

To minimize thermal injury, the current study evaluated the real-time temperature monitoring with a proportional-integrative-derivative (PID) controller during 980-nm photothermal treatment with a radially-diffusing applicator. Both simulations and experiments demonstrated comparable thermal behaviors in temperature distribution and the degree of irreversible tissue denaturation. The PID-controlled application constantly maintained the pre-determined temperature of 353 K (steady-state error = < 1 K). Due to constant energy delivery, coagulation volumes linearly increased up to 1.04 +/- 0.02 cm(3) with irradiation time. Integration of temperature feedback with diffuser-assisted photothermal treatments can provide a feasible therapeutic modality to treat pancreatic tumors in an effective manner. (C) 2016 Optical Society of America

The growth of both IT technology and the Internet Communication has involved the development of lot of encrypted information. Among others techniques of message hiding, stenography is one them but more suspicious as no one cannot see the secret message. As we always use the MS Office, there are many ways to hide secret messages by using PowerPoint as normal file. In this paper, we propose a new technique to find a hidden message by analysing the in PowerPoint file using EnCase Transcript. The result analysis shows that Steganography technique had hidden a certain number of message which are invisible to naked eye.

Navigational information supporting services recently have become an increasingly significant global issue, particularly as trade volumes and the employment of mega ships in the maritime field have grown. However, there remain risks associated with vessel navigation; major accidents brought on by unexpected weather conditions for example, still often occur. The International Hydrographic Organization (IHO) is establishing maritime-services standards for prevention of maritime accidents and promotion of navigation safety. S-100 is the IHO standard that was adopted as a basic model supporting the exchange and integration of hydrographic information services. In order to facilitate the communication of maritime meteorological information via S-100-based navigational information services, we need to represent it according to an S-100-based data structure and formats. In this paper, we analyze certain types and characteristics of data representing maritime meteorological information and present the maritime meteorological information data model based on the S-100 General Feature Model (GFM) and its characteristics for users and data administrators.

To demonstrate the feasibility of simultaneous dual fundamental grayscale and subharmonic imaging on a modified commercial scanner.The ability to generate signals at half the insonation frequency is exclusive to ultrasound contrast agents (UCA). Thus, subharmonic imaging (SHI; transmitting at f(0) and receiving at f(0)/2) provides improved visualization of UCA within the vasculature via suppression of the surrounding tissue echoes. While this capability has proven useful in a variety of clinical applications, the SHI suppression of surrounding tissue landmarks (which are needed for sonographic navigation) also limits it use as a primary imaging modality. In this paper we present results using a commercial ultrasound scanner modified to allow imaging in both grayscale (f(0)=4.0 MHz) and SHI (f(0)=2.5 MHz, f(0)/2=1.25 MHz) modes in real time.A Logiq 9 ultrasound scanner (GE Healthcare, Milwaukee, WI) with a 4C curvilinear probe was modified to provide this capability. Four commercially available UCA (Definity, Lantheus Medical Imaging, North Billerica, MA; Optison, GE Healthcare, Princeton, NJ; SonoVue, Bracco Imaging, Milan, Italy; and Sonazoid, GE Healthcare, Oslo, Norway) were all investigated in vitro over an acoustic output range of 3.34 MPa. In vivo the subharmonic response of Sonazoid was investigated in the portal veins of four canines (open abdominal cavity) and four patients with suspected portal hypertension.In vitro, the four UCA showed an average maximum subharmonic amplitude of 44.1±5.4 dB above the noise floor with a maximum subharmonic amplitude of 48.6±1.6 dB provided by Sonazoid. The average in vivo maximum signal above the noise floor from Sonazoid was 20.8±2.3 dB in canines and 33.9±5.2 dB in humans. Subharmonic amplitude as a function of acoustic output in both groups matched the S-curve behavior of the agent observed in vitro. The dual grayscale imaging provided easier sonographic navigation, while the degree of tissue suppression in SHI mode varied greatly on a case by case basis.These results demonstrate the feasibility of dual grayscale and SHI on a modified commercial scanner. The ability to simultaneously visualize both imaging modes in real time should improve the applicability of SHI as a future primary clinical imaging modality.

In ultrasound strain and elasticity imaging, an accurate and cost-effective sub-pixel displacement estimator is required because strain/elasticity imaging quality relies on the displacement SNR, which can often be higher if more computational resources are provided. In this paper, we introduce an autocorrelation-based method to cost-effectively improve sub-pixel displacement estimation quality. To quantitatively evaluate the performance of the autocorrelation method, simulated and tissue-mimicking phantom experiments were performed. The computational cost of the autocorrelation method is also discussed. The results of our study suggest the autocorrelation method can be used for a real-time elasticity imaging system.

The International Hydrographic Organization (IHO), having recognized the data representation limitations of the S-57 standard, has presented the S-100 standard, which can support a variety of hydrographic-related digital data. In a variety of maritime areas, S-100- based data product specifications currently are being developed. For example, the S-101 Electronic Navigation Chart (ENC) represents a variety of spatial information related to navigation. Whereas S-57 ENC data is difficult to utilize because it consists only of many binary files, S-101 ENC data is much easier, particularly with its new encoding formats such as XML and GML. Therefore, S-101 ENC data needs to be converted to GML, the encoding language of information on geographical features, so that ENC spatial data can be utilized more easily and effectively in the maritime information system. In this paper, we present the mapping of the dataset structure of vector records between S-57 and S-101; additionally, we present GML methods based on the S-100 GML profile for spatial representation of S-101 ENC data.

The evolution of digital communication era includes both devices and applications running on different platforms. Specifics applications are needed for a safeguard communication ensuring protection and trust services to the users. This paper presents an authentication and session-key establishment protocol that enabling mutual authentication procedure between involved entities in the WSNs. This scheme provides specific security standards such as data integrity, message confidentiality and session key establishment to ensure security and privacy of both data and network. To illustrate the feasibility of the work to real world protocols, we simulate the session key establishment computation using Scyther tool for WiMAX protocol standards. An extensive analysis shows that the proposed scheme achieves efficiency and can be safeguard to real wireless communication applications. Finally, a performance evaluation and comparison shows that our proposed framework is lightweight and resilient to various kinds of attacks.

Data exchange over public network requires for the most part an important security mechanism enabling to both sender and receiver the property that they can mutual authenticate using different identification parameters playing the vital role of secret shared key computation. Based on the decisional Diffie-Hellman assumptions, this paper presents a cryptographic calculation of the shared secret key enabling mutual authentication and confidentiality services over public, insecure networks. This protocol is efficient than "classical" Diffe-Hellman key exchange which provides no authentication at all and suffer from man-in-the-middle attack. To attain this, we first model the scheme with mathematical concept for exponential calculation using entity parameters and finally we simulate the work by Scyther tool to verify the provability of the sameness 'shared secret value. With the standards cryptographic assumptions, the simulation result reveals that the protocol is practical and provably-secure. Thus, the proposed cryptographic protocol is awfully, straightforward, valuable, and resilient to know attacks.

Current generation of smart mobile devices can do all the things which were only possible with dedicated hardware. With 3G, 4G network they can even connect to data network anytime, anywhere as needed. However, there are limits to how much network data people are allowed, so most of smart mobile device users tend to connect to Wi-Fi network which doesn't consume their data plan. Although Wi-Fi has its economic benefits, compared to wired network, there are still many security risks such as capturing or altering of network data. There are many cases where criminals of identity theft use unauthorized Wi-Fi access point to lure people in to giving their personal information. In this paper, unauthorized Wi-Fi access point is used to simulate above case, and it is compared with case which uses authorized access point.

This paper presents an application of security protocol based-on mu-tual authentication procedure between involved entities that providing data and network security in wireless sensor environment communication. Through WSN, a user can access base station of wireless sensor networks and gets the data. This paper proposes a secure authentication protocol where involved enti-ties are mutual strongly verified before accessing the data. The proposal pro-vides secure features standards such as data integrity, mutual authentication and session key establishment. Furthermore, an extensive analysis shows that the proposed scheme possesses many advantages against popular attacks, achieves better efficiency and can be safeguard to real wireless sensor network applications.

The digital era is changing the nature of health care delivery system with the integration of Information Technology’s potential to improve the quality, safety, and efficiency of health care. Medical devices may be connected on wireless and wired networks and communicate with nearby receivers that are connected to landline networks, cellular systems or broadband facilities that provide more ubiquitous coverage of connectivity, allowing uninterrupted monitoring of patients in transit by accessing the Internet. This promise of universal connectivity allow data availability service from the high-end systems such as routers, gateways, firewalls, and web servers to the low-end systems such as smart phone, tablet, etc…Hence, security has become an essential part of today’s computing world regarding the ubiquitous nature of the entities and wireless technology evolution. This paper presents a framework for Healthcare System Communication where wireless medical devices are challenged to an identification protocol procedure which enables negotiation between wireless medical devices and specify authorization requirements that must be met before accessing the network and patients’ data. To illustrate the feasibility of the work to real world protocols, we simulate the scheme using Scyther tool by applying the IEEE-802.16-2004 PKM protocols for WiMAX protocol standards.

The development of internet and new technology has been growing continuously, smartphone is now a necessary device that has great impact on users in various ways. Internet and smart devices have gained their success in various fields and have provided conveniences to all types of users. The flow of data is seen as a part of the internet and smart devices. Since a large amount of users rely on the internet for their own purposes, it then has become a big vulnerable target for attackers. In this paper, a design of elliptic curve cryptography-based authentication using QR Code is proposed. It mainly focuses on QR Code, as it is now widely used all over the world. However, the enhancement of the existing approaches is encouraged by the fast development of threats, which are presently encountered. The encryption process is included, and the proposed authentication protocol applies the concepts "Something you know" and "Something you have". Normally, people are not concerned about the threats behind the process of transmitting information over the internet, especially through QR Code. With this authentication process, users can ensure that they and their information are safe from online threats.

The International Hydrographic Organization (IHO) has presented a new Electronic Navigation Chart(ENC) product specification for S-101, and the paper has covered a study about display module structure. Recently, recognizing the limitations data modeling facility of S-57, IHO developed S-100 as a standard for hydrographic data. Based on S-100 standard, product specifications, including ENC, have been developed. S- 57 based ENC will be replaced by S-101 ENC after S-100 standard has been developed. Display module including S-101 ENC should be replaced, since S-57 based ENC display module have problem expressing S-101 ENC structure. For this transitional period of switching from S-57 standard based toward S-101 standard, we developed a display module that includes S-57 and S-101 standard covering both S-57 ENC data and S-101 ENC data expression.

The expansion and increasing use of ocean-weather-monitoring data is the most important factor relevant to marine-related activities as well as residential and industrial growth in coastal areas. Natural disasters occurring in or originating from the oceans are largely functions of weather conditions. This paper presents a marine weather information service system based on data from the Korea Meteorological Administration (KMA), the Korea Hydrographic and the Oceanographic Administration (KHOA), and the Korea Astronomy and Space Science Institute (KASSI). This service system can provide Automatic Identification System (AIS) information as displayed on the Electronic Navigation Chart (ENC). The system provides information such as channel markers, sunrise, sunset, low tide, high tide, and weather notifications on the ENC via the Internet and mobile devices using the user's location information or their set location. A map is provided in the tile format. To improve tile-map speed, the information is transmitted only when the user finds a new location and previous data on that client has been stored. In the future, provision of AIS information through mobile devices not only can secure the safety of the ships but also do the role of E-navigation which identifies its location in advance.

In the maritime field, e-navigation, an information-service framework for proper integration of various marine and marine-related data both shipboard and onshore, has been widely discussed. In the wake of the adoption of International Hydrographic Organization (IHO)’s S-100 as the baseline of the Common Maritime Data Structure (CMDS) for e-navigation, S100-based product specifications are being developed. The International Association of Lighthouse Authorities (IALA) is charged with the development of product specifications for its domain. In order to develop a data product specification, it is necessary to analyze the contents of the data and to define an application schema according to the S-100 data model. Aids to Navigation (AtoN) data in IALA domain constitute the typical resource of e-navigation. Thus, in this paper, we present an application schema for Aids to Navigation (AtoN) data. By analysis IALA Navguide and AtoN data provided by a regional marine office, we define an application schema on the basis of IHO S-100.

Navigation-assistance systems using feature-based geographic Electronic Navigation Chart (ENC) data are widely employed to help ensure the safety of vessels and their crews. ENC data consist of descriptions of the characteristics of features along with geographic information on them. Because they are created and delivered according to the IHO standards, they are encoded in data transfer formats such as ISO/IEC 8211; thus, they need subsequently to be converted to the data format and structures of the system that will use them. Specifically, preparatory to their effective utilization, it is necessary to store and manage ENC data sets according to their relevant characteristics. In this paper, we present a system architecture for effective management of ENC data sets. We define the system's data structures and design modules.

For real-time volumetric imaging system using 2-D arrays, control of massive ultrasound data acquired from a large number of system channels is challenging. Given a system with manageable number of channels, new methods of array configuration and beamforming are necessary to achieve the performance of utilizing the full array elements and channels. In this paper, Electric Wobbling (EW) and Elevational Synthetic Focusing (ESF) methods are proposed. Theoretical studies and simulation were performed to evaluate the quality of 3-D volume imaging methods.

Metadata provides the information that describes, explains, or makes it easier to retrieve, use, or manage information resources. In the marine field, a metadata model is defined and used for exchange, retrieval, integration, and usage of data, such as hydrographic data. The S-100 of the International Hydrographic Organization (IHO), recently introduced new paradigm for integration and usage of various data on marine safety and the marine environment, also includes a metadata model defined in uniformed modeling language (UML). This model, consisting of entities that describe the main concepts and conceptual structures of metadata, provides for syntactic interoperability between systems. However, semantic heterogeneities as well as difficulties encountered in automatic semantic-based processing remain yet. For the purposes of enhancing semantic interoperability between systems on the S-100-based infrastructure, we herein introduce a new metadata ontology. Analyzing metadata elements in the S-100 metadata model, we removed the syntactic and semantic redundancies of the metadata elements. After conceptualizing and generalizing the metadata elements, we defined ontology elements free of syntactic or semantic redundancy. Additionally, we improved the previous ontology by UML-to-OWL conversion.

Volumetric ultrasound imaging has been primarily used as a clinical tool to diagnose cardiac dysfunction. However, the modality still suffers from system complexity due to a large number of receive channels for volumetric reconstruction. The aim of the study was to numerically assess a cross-shaped sparse array with a dynamic transmit focusing method to reduce the system complexity and to compensate for the image quality of unfocused volumetric imaging. Analytical simulations with two-way point spread functions demonstrated that the cross-shaped sparse array entailed up to an 84% increase in side-lobes (up to 32 dB), thus leading to significant degradation of the point spread function in the diagonal plane. A dynamic transmit focusing method was able to vividly overcome the image degradation by transmitting more beams with tilting angles. This also yielded a comparable image sensitivity (65 dB) to that of the full array when 31 × 31 tilted waves were used. The proposed cross-shaped sparse array with the dynamic transit focusing method can be used to enhance the frame rate as well as the image quality for unfocused ultrasound imaging.

Photoacoustic signals, detected by a transducer array, need to be beamformed for subsequent use in a limited view angle tomography such as B-scan imaging. In the presence of the light scattering or phase aberration, the spatial resolution and contrast in the photoacoustic images are degraded. Phase aberration due to tissues with inhomogeneous acoustic speeds is a major source for image degradation. However, a constant speed of sound (e.g., 1540 m/s) is typically assumed in photoacoustic imaging. Such an assumption can affect the quality of photoacoustic image since changes in sound velocity cause significant phase errors in beamforming. An adaptive weighting method such as coherence factor (CF) technique can improve the ultrasound and photoacoustic image quality significantly. In addition, photoacoustic images can be further improved by applying adaptive beamforming techniques developed for ultrasound imaging. In this study, an adaptive photoacoustic image reconstruction technique that combines an adaptive weighting factor (CF) and an adaptive apodization called minimum variance method (MV) is introduced. Although MV method calculates the optimal apodization weighting factors which minimize the variance of the beamformed signal, it can lead to unexpected weighting factors since it is data dependant. In this case, CF weighting can help to avoid this problem by weighting the output from the MV method based on signal coherence. Simulations were performed to analyze the spatial resolution using a point targets and to demonstrate improvement in phase aberration correction. Numerical studies demonstrated the superior performance of MV adaptive method combined with CF weighting.

Ultrasonography constructs pictures of areas inside the body needs in diagnosis by bouncing ultrasound off internal tissues or organs. In constructing an ultrasonographic image, the weakness of bounding signals induces noises and detailed differences of brightness, so that having a difficulty in detecting and diagnosing with the naked eyes in the analysis of ultrasonogram. Especially, the difficulty is extended when diagnosing muscle areas by using ultrasonographic images in the musculoskeletal test. In this paper, we propose a novel image processing method that computationally extracts a muscle area from an ultrasonographic image to assist in diagnosis. An ultrasonographic image consists of areas corresponding to various tissues and internal organs. The proposed method, based on features of intensity distribution, morphology and size of each area, extracts areas of the fascia, the subcutaneous fat and other internal organs, and then extracts a muscle area enclosed by areas of the fascia. In the extraction of areas of the fascia, a series of image processing methods such as histogram stretching, multiple operation, binarization and area connection by labeling is applied. A muscle area is extracted by using features on relative position and morphology of areas for the fascia and muscle areas. The performance evaluation using real ultrasonographic images and specialistspsila analysis show that the proposed method is able to extract target areas being approximate to real muscle areas.