Search

An algorithm for constructing super-large semantic networks has been developed in current work. Algorithm was tested using the “Cosmos” category of the Internet encyclopedia “Wikipedia” as an example. During the implementation, a parser for the syntax analysis of Wikipedia pages was developed. A graph based on list of articles and categories was formed. On the basis of the obtained graph analysis, algorithms for finding domains of high connectivity in a graph were proposed and tested. Algorithms for constructing a domain based on the number of links and the number of articles in the current subject area is considered. The shortcomings of these algorithms are shown and explained, an algorithm is developed on their joint use. The possibility of applying a combined algorithm for obtaining the final domain is shown. The problem of instability of the received domain was discovered when starting an algorithm from two neighboring vertices related to the domain.

Due to the rising difficulty of developing complex systems a lot of research has gone into the multi‐agent paradigm over the past decades, during which a vast array of approaches for developing such systems have been proposed. Despite this fact there seems to be a gap in the MAS community between solutions that provide for expressivity and those that offer generality. It is our opinion that embedding the MAS language into a functional language we can have the best out of both worlds: we can implement the desired semantics in an abstract way, allowing us to focus on the problem domain, i.e. complex, distributed MAS. Our approach is going to be layered: (i) we start from a statically typed functional language and build an EDSL that acts as an executable specification language for single agent entities; and (ii) develop a framework for workflow‐oriented coordination on top of the previous layer and investigate its use as a means of implementing agent organizations, focusing on coordination and communication.

We describe the results of an expert system applied to the evaluation of samples of kaolin for industrial use in paper or ceramic manufacture. Different machine learning techniques—classification trees, support vector machines and Bayesian networks—were applied with the aim of evaluating and comparing their interpretability and prediction capacities. The predictive capacity of these models for the samples analyzed was highly satisfactory, both for ceramic quality and paper quality. However, Bayesian networks generally proved to be the most useful technique for our study, as this approach combines good predictive capacity with excellent interpretability of the kaolin quality structure, as it graphically represents relationships between variables and facilitates what‐if analyses.

The progress and development of information technology has opened up one form of nuclear crime, namely computer crime. The Stuxnet incident that occurred in 2010 is one example of cyber incidents related to nuclear security. The International Atomic Energy Agency (IAEA) as an international regulatory body has paid attention to computer security as outlined in one of the important elements in NSS 20 - Objective and Essentials Elements of a State’s Nuclear Security Regime. The security aspect itself is one of the aspects emphasized in Act Number 10 of 1997 concerning Nuclear Energy. Government Regulation Number 54 of 2012 concerning Nuclear Installation Safety and Security outlines a more detailed discussion of nuclear installation security, which is a more specific discussion on safety in the aspect of physical protection regulated in Regulation of the Head of the Nuclear Power Supervisory Agency Number 1 of 2009 concerning Installation Physical Protection Systems and Nuclear Materials. However, all of these regulations still do not explicitly mention computer security. This paper was prepared to provide recommendations that can be used in the preparation of regulations and guidelines related to computer security in nuclear installations. This paper was prepared using the main reference NSS 17 - Computer Security at Nuclear Facilities which was perfected by the review of Regulatory Guide 5.71 - Cyber Security Programs for Nuclear Facility, CSA N290.7-14 - Cyber Security for Nuclear Power Plants and Small Reactor Facilities, and REGDOC-2.5.2. - Design of Reactor Facilities: Nuclear Power Plants. From the results of the study, it was concluded that several things that need to be considered as required regarding computer security are the establishment of a computer security team, the preparation of a computer security plan, a graded approach to computer security, and risk assessment.

Article investigates the usage of spatial logic in the process of unmanned vehicle operation. Article examines the mode of unmanned vehicle control. Unmanned transport operation is not autonomous. Structurally it represents the control scheme which includes two operating centers, the main and peripheral ones. Main operating centre fulfills “smooth” operation and the peripheral centre performs the direct operation. Article provides systematization of transport control according to the levels of automation. The usage of spatial logic for each level of automation has been shown. Paper describes the model of information situation as a basic model during unmanned operation. The role of spatial information and geodata in unmanned operation has been specified. Article features the spatial situations in transport movement which require the usage of spatial logic. Three types of spatial situations which are used in unmanned control have been described. Paper discovers the content of spatial logic used in vehicle control. The differentiation between cognitive spatial logic and analytical spatial logic has been demonstrated.

The main goal of this paper to evaluate the performance of the proposed long short-term memory (LSTM)- basis relative humidity (RH) prediction model. Computational physics learning theory is a subfield in artificial intelligence. In this paper, we use the real observed weather data of RH from synoptic station location as an important aspect and effect in weather and climate and using machine learning approach basis on the LSTM neural network, which is a type of recurrent neural network (RNN). We use a machine learning approach to compute the relative humidity basis on the LSTM model. The LSTM is trained by using two years of climate data (from January 2008 to December 2009). LSTM is capable of forecasting complex univariate relative humidity time series with strong no-stationarity. The result shows the usefulness of LSTM and out performs traditional forecasting methods in the challenging relative humidity record problem.

Even supposing the technology is promoting little by little, many of the industrial operations are not advance till the finishing point their depreciation epoch due to either ignorant of cost and time reserves or inattention or overlooked. A scientific suggestion not only needs to highlight for the updating the system of manufacturing, but also needs to figure-out cost of loss in all aspects for non-upgrade of the facility. It can be done in the industrial management that to form Small Group Activity team to recognize such fatalities and remedies to resolve them. This paper discusses preparation of such valid proposal for a leading industry in Tamil Nadu. The case study belongs to a proposal of replacement machines as their depreciation period got over in an assembly plant of a largest and leading automobile manufacturer. The objective this research is to prepare the valid proposal to procure the equipment with necessary upgrades. The six sigma’s ECRS methodology is employed and majorly governs for this investigation. This study included the process evaluation, conceptual design, basic engineering design, computer aided design and validation, cost analysis. The effectiveness is verified and presented in this paper. The proposed machine reduced 70.27% of processing time, 39.02% of equipment cost and 70.25% cost per piece.

When students begin to learn how to program computers, the greatest difficulty does not consist in learning a programming language, even considering the various programming paradigms to which it may belong, but rather in the way of conceiving a solution algorithm for a given problem. In this paper methods for learning how to build better programs with iterative and recursive techniques are proposed. Instead of using the traditional and sequential method, following theoretical exposition and creation of algorithms, practical demonstration in a specific framework to write a program in a programming language, program execution and tests, a new approach is introduced where a set of tools, such as Python programming language, Runestone Interactive documents and Online Python tutor, is used to allow the production of enriched documents with text, images, videos, code implementation and execution windows, with the option of step by step running, showing the used data structures and their values evolution, all together in an - Interactive Electronic Document (IED). Students have the opportunity to learn and experience programming concepts in a single document, interactively, increasing learning achievement and level of satisfaction.When students begin to learn how to program computers, the greatest difficulty does not consist in learning a programming language, even considering the various programming paradigms to which it may belong, but rather in the way of conceiving a solution algorithm for a given problem. In this paper methods for learning how to build better programs with iterative and recursive techniques are proposed. Instead of using the traditional and sequential method, following theoretical exposition and creation of algorithms, practical demonstration in a specific framework to write a program in a programming language, program execution and tests, a new approach is introduced where a set of tools, such as Python programming language, Runestone Interactive documents and Online Python tutor, is used to allow the production of enriched documents with text, images, videos, code implementation and execution windows, with the option of step by step running, showing the used data structures and their values evolution, all to...

In honour to Jiři Kunovský, the paper will try to overview his work and his beloved simulation software. The Taylor–Kunovsky Simulation Language (TKSL) is software based on computations where Taylor series are used, to solve various problems by systems of equations. It deals with problems described by non-stiff and even stiff differential equations or systems of linear equations or nonlinear equations in a comparable or faster time than other known softwares. The implemented method is based on variable–step variable–order scheme. The paper will provide test problem and comparison to MATLAB software.

To enhance the security in optical image encryption system and to protect it from the attackers, this paper proposes new digital spiral phase mask based on Fresnel Transform. In this cryptosystem the Spiral Phase Mask (SPM) used is a hybrid of Fresnel Zone Plate (FZP) and Radial Hilbert Mask (RHM) which makes the key strong and enhances the security. The different keys used for encryption and decryption purposed make the system much more secure. Proposed scheme uses various structured phase mask which increases the key space also it increases the number of parameters which makes it difficult for the attackers to exactly find the key to recover the original image. We have also used different keys for encryption and decryption purpose to make the system much more secure. The strength of the proposed cryptosystem has been analyzed by simulating on MATLAB 7.9.0(R2008a). Mean Square Errors (MSE) and Peak Signal to Noise Ratio (PSNR) are calculated for the proposed algorithm. The experimental results are provided to highlight the effectiveness and sustainability of proposed cryptosystem and to prove that the cryptosystem is secure for usage.To enhance the security in optical image encryption system and to protect it from the attackers, this paper proposes new digital spiral phase mask based on Fresnel Transform. In this cryptosystem the Spiral Phase Mask (SPM) used is a hybrid of Fresnel Zone Plate (FZP) and Radial Hilbert Mask (RHM) which makes the key strong and enhances the security. The different keys used for encryption and decryption purposed make the system much more secure. Proposed scheme uses various structured phase mask which increases the key space also it increases the number of parameters which makes it difficult for the attackers to exactly find the key to recover the original image. We have also used different keys for encryption and decryption purpose to make the system much more secure. The strength of the proposed cryptosystem has been analyzed by simulating on MATLAB 7.9.0(R2008a). Mean Square Errors (MSE) and Peak Signal to Noise Ratio (PSNR) are calculated for the proposed algorithm. The experimental results are provid...

The accelerated development of new technology, particularly on mobile application has increased teacher’s responsibility as a learning facilitator. Since technology is improving, many applications keep on coming into the market to fulfill user demands. Mobile learning application is very useful in enriching the mobile learning experience of children. However, some applications fail to assist and increase children knowledge on the subject they studied. Moreover, some children are not interested in mobile applications due to issues such as poor interfaces. In this paper, some previous studies on quality attributes used to evaluate mobile learning applications were reviewed. A systematic literature review approach was employed to search previous papers and studies on usability quality attributes, particularly for mobile learning applications. The search strategy identified numerous studies on usability for mobile learning applications for children. The result showed that the top four usability quality attributes are efficiency, effectiveness; learnability and user satisfaction. The studies reviewed showed that usability evaluations were conducted during implementation phase only, and evaluation is often built as a description of the case study. This study explored the current literatures on the subject matter and stimulates further studies that will lead to improved usability and design of mobile learning applications for children.

Application of immersive Virtual Reality (VR) system has been proven to be practical and effective in offering the sense of presence and engagement for users to explore inside a virtual environment (VE) creation. However, numerous user experience problems still occur within the application design and development phase. An attempt to categorized the issues from presented studies by the researchers within the scope of papers between years of 2007 to 2017. There is no empirical evaluation conducted in this reviewing process but the aim is to bridge the gap between user experience and application system through understanding and learning from the challenges in the system itself. This can promote a more highly acceptance level of this complex technology among the users. This paper also proposes the future research directions and predicts the development trends of VR system.

With the rapid development of Internet social media, excavating the emotional tendencies of the short text information from the Internet, the acquisition of useful information has attracted the attention of researchers. At present, the commonly used can be attributed to the rule-based classification and statistical machine learning classification methods. Although micro-blog sentiment analysis has made good progress, there still exist some shortcomings such as not highly accurate enough and strong dependence from sentiment classification effect. Aiming at the characteristics of Chinese short texts, such as less information, sparse features, and diverse expressions, this paper considers expanding the original text by mining related semantic information from the reviews, forwarding and other related information. First, this paper uses Word2vec to compute word similarity to extend the feature words. And then uses an ensemble classifier composed of SVM, KNN and HMM to analyze the emotion of the short text of micro-blog. The experimental results show that the proposed method can make good use of the comment forwarding information to extend the original features. Compared with the traditional method, the accuracy, recall and F1 value obtained by this method have been improved.

Payroll processing is an imperative process in an organization; it involves many tasks to ensure accurate and timely payments of the workforces’ services, and to protect organization’s reputation through effective record-keeping compliance with the government authorities’ employment legislations. Despite its important function in the organization process, studies on payroll processing is quite limited, as compared to other transaction processing systems such as sales and purchase. This paper observes the trend of articles published on payroll system that has been indexed by the Google Scholar as at February 2018. This study aims to provide insights into the characteristics of the issues related to payroll system using a bibliometric analysis. Articles that matched with the keywords [allintitle: payroll system OR systems OR application OR applications OR software] in the Google Scholar has been obtained and analyzed. After conducted the cleaning process i.e. by completing the meta-data of the articles and removing some of the irrelevant and duplicate articles, 170 articles are available for further analysis. It is found that, the number of published payroll system articles are increasing in the past five years. Most of the articles has been published as journal articles, academic dissertations and conference papers. The output of this study can help researchers to understand the landscape of the global research and issues on payroll system and establish further research directions in this field.

This paper presents modelling of both single and double-phase powder sintering processes at the macroscopic level. In particular, its constitutive formulation, numerical implementation and numerical tests are described. The macroscopic constitutive model is based on the assumption that the sintered material is a continuous medium. The parameters of the constitutive model for material under sintering are determined by simulation of sintering at the microscopic level using a micro-scale model. Numerical tests were carried out for a cylindrical specimen under hydrostatic and uniaxial pressure. Results of macroscopic analysis are compared against the microscopic model results. Moreover, numerical simulations are validated by comparison with experimental results. The simulations and preparation of the model are carried out by Abaqus FEA - a software for finite element analysis and computer-aided engineering. A mechanical model is defined by the user procedure “Vumat” which is developed by the first author in Fortran programming language. Modelling presented in the paper can be used to optimize and to better understand the process.This paper presents modelling of both single and double-phase powder sintering processes at the macroscopic level. In particular, its constitutive formulation, numerical implementation and numerical tests are described. The macroscopic constitutive model is based on the assumption that the sintered material is a continuous medium. The parameters of the constitutive model for material under sintering are determined by simulation of sintering at the microscopic level using a micro-scale model. Numerical tests were carried out for a cylindrical specimen under hydrostatic and uniaxial pressure. Results of macroscopic analysis are compared against the microscopic model results. Moreover, numerical simulations are validated by comparison with experimental results. The simulations and preparation of the model are carried out by Abaqus FEA - a software for finite element analysis and computer-aided engineering. A mechanical model is defined by the user procedure “Vumat” which is developed by the first author in F...

The aims of this paper were to describe the principles of ecosystem restoration and development of recreation sites in degraded mountain areas, with special references to East Java, Indonesia. In East Java, the mountain ecosystem has been disturbed by anthropological and natural forces, and restoration is a crucial program to repair and recover the degraded area. At the same time, tourism to mountain areas is growing significantly, and there are opportunities for integrating development of recreation tourism areas and restoration programs in degraded sites. However, considerable research shows that there are less appropriate programs, planning and practice of integrating restoration and development of tourism areas in degraded mountain areas. Numerous exotic plant species were introduced as part of the effort to repair many degraded mountain areas in East Java. There are economical motives to the introduction of exotic plants, as sh own by the abundant number of multi-purpose plant tree species. A large number of exotic plant species were also influenced by attempts to increase the beauty of recreation sites, to provide consumable fruits and vegetables and environmental education. This paper shows there are misconceptions concerning restoration and development of recreation sites in conservation forests in mountain areas in East Java. Integrating recreation tourism area development and restoration programs should be established in the perspective of sustainable development.

This paper introduces and inherit the multi-level trusted system model that solves the Trojan virus by encrypting the privacy of user data, and achieve the principle: “not to read the high priority hierarchy, not to write the hierarchy with low priority”. Thus ensuring that the low-priority data privacy leak does not affect the disclosure of high-priority data privacy. This paper inherits the multi-level trustworthy system model of Trojan horse and divides seven different risk levels. The priority level 1∼7 represent the low to high value of user data privacy, and realize seven kinds of encryption with different execution efficiency Algorithm, the higher the priority, the greater the value of user data privacy, at the expense of efficiency under the premise of choosing a more encrypted encryption algorithm to ensure data security. For enterprises, the price point is determined by the unit equipment users to decide the length of time. The higher the risk sub-group algorithm, the longer the encryption time. The model assumes that users prefer the lower priority encryption algorithm to ensure efficiency. This paper proposes a privacy cost model for each of the seven risk subgroups. Among them, the higher the privacy cost, the higher the priority of the risk sub-group, the higher the price the user needs to pay to ensure the privacy of the data. Furthermore, by introducing the existing pricing model of economics and the human traffic model proposed by this paper and fluctuating with the market demand, this paper improves the price of unit products when the market demand is low. On the other hand, when the market demand increases, the profit of the enterprise will be guaranteed under the guidance of the government by reducing the price per unit of product. Then, this paper introduces the dynamic factors of consumers’ mood and age to optimize. At the same time, seven algorithms are selected from symmetric and asymmetric encryption algorithms to define the enterprise costs at different levels. Therefore, the proposed model solves the continuous influence caused by cascading events and ensures that the disclosure of low-level data privacy of users does not affect the high-level data privacy, thus greatly improving the safety of the private information of user.

Currently safety is one of the primary concerns in the transmission of images due to increasing the use of images within the industrial applications. So it’s necessary to secure the image facts from unauthorized individuals. There are various strategies are investigated to secure the facts. In that encryption is certainly one of maximum distinguished method. This paper gives a sophisticated Rijndael (AES) algorithm to shield the facts from unauthorized humans. Here Exponential Key Change (EKE) concept is also introduced to exchange the key between client and server. The things are exchange in a network among client and server through a simple protocol is known as Trivial File Transfer Protocol (TFTP). This protocol is used mainly in embedded servers to transfer the data and also provide protection to the data if protection capabilities are integrated. In this paper, implementing a GUI environment for image encryption and decryption. All these experiments carried out on Linux environment the usage of Open CV-Python script.

Electronic Commerce (EC) platform which is widely known as E-Marketplace handles millions of transactions over the internet. While individual users of E-Marketplace frequently interact with a shorter supply chain, Business-to-Business (B2B) users, on the other hand, manage multiple interactions with multiple layers of partners such as manufacturers or suppliers. This complexity, however, introduces problems of information overload where the users only require pertinent information based on their interests. Although recommender systems (RSs) are widely used in resolving such problems, the current RSs in the literature are still suffering several limitations, such as overspecialised recommendation, and scalability issues. Moreover, there is an urgency to introduce manufacturing companies or suppliers to online business buyers within to trade with the shortest paths between the users. This paper presents a conceptual idea of the B2B recommendation model to present potentially useful products to virtual manufacturers or suppliers to business users. The concept highlighted the effectiveness of social network information for the recommender to alleviate the current issues of RSs to support the complexity introduced in the B2B environment.Electronic Commerce (EC) platform which is widely known as E-Marketplace handles millions of transactions over the internet. While individual users of E-Marketplace frequently interact with a shorter supply chain, Business-to-Business (B2B) users, on the other hand, manage multiple interactions with multiple layers of partners such as manufacturers or suppliers. This complexity, however, introduces problems of information overload where the users only require pertinent information based on their interests. Although recommender systems (RSs) are widely used in resolving such problems, the current RSs in the literature are still suffering several limitations, such as overspecialised recommendation, and scalability issues. Moreover, there is an urgency to introduce manufacturing companies or suppliers to online business buyers within to trade with the shortest paths between the users. This paper presents a conceptual idea of the B2B recommendation model to present potentially useful products to virtual manuf...

The shortage of IP addresses and the scalability of routing systems [1] are challenges for the Internet. The idea of dividing existing IP addresses between identities and locations is one of the important research directions. This paper proposed a new decimal network architecture based on IPv9 [11], and decimal network IP address from E.164 principle of traditional telecommunication network, the IP address level, which helps to achieve separation and identification and location of IP address, IP address form a multilayer network structure, routing scalability problem in remission at the same time, to solve the problem of IPv4 address depletion. On the basis of IPv9, a new decimal network architecture is proposed, and the IP address of the decimal network draws on the E.164 principle of the traditional telecommunication network, and the IP addresses are hierarchically divided, which helps to realize the identification and location separation of IP addresses, the formation of multi-layer IP address network structure, while easing the scalability of the routing system to find a way out of IPv4 address exhausted. In addition to modifying DNS [10] simply and adding the function of digital domain, a DDNS [12] is formed. At the same time, a gateway device is added, that is, IPV9 gateway. The original backbone network and user network are unchanged.The shortage of IP addresses and the scalability of routing systems [1] are challenges for the Internet. The idea of dividing existing IP addresses between identities and locations is one of the important research directions. This paper proposed a new decimal network architecture based on IPv9 [11], and decimal network IP address from E.164 principle of traditional telecommunication network, the IP address level, which helps to achieve separation and identification and location of IP address, IP address form a multilayer network structure, routing scalability problem in remission at the same time, to solve the problem of IPv4 address depletion. On the basis of IPv9, a new decimal network architecture is proposed, and the IP address of the decimal network draws on the E.164 principle of the traditional telecommunication network, and the IP addresses are hierarchically divided, which helps to realize the identification and location separation of IP addresses, the formation of multi-layer IP address network ...

One of the most dangerous waste in the world are the End-of-Life tires (EOLT). They are waste that does not practically decompose in nature. Because of this their sound treatment is needed for environment protection. Pyrolysis process is one of the possible methods for such a treatment. Globally, around 23% of all EOLT are processed through pyrolysis, whereas in the Republic of Bulgaria only 5% are processed by pyrolysis. It is clear that for Bulgaria this method still has a good potential for usage, development and further research. The pyrolysis process, used for EOLT treatment, usually is 3D and non-stationary. Thus it is very complicated for modeling and studying.Following [3] an adequate mathematical model of the heat transfer during the pyrolysis process used for the treatment of the End-of-Life tires (EOLT) has been presented in our previous paper [1]. There a numerical algorithm in MATLAB for solving the respective mathematical initial and boundary value problems has been also developed. Some results for the temperature field for several characteristic periods of operation of pyrolysis station are presented and commented in this paper [1]. In our next paper [2] we have examined the influence of the heating upon the heat transfer during the pyrolysis process used for EOLT treatment.This paper deals with studying the influence of the heater position upon the heat transfer during EOLT treatment by pyrolysis process. The results for temperature fields, temperature isolines and gradients at some specific moments of time and for two different initial heating functions are graphically presented and commented. Results from this modeling can be used in the real pyrolysis stations for more precise displacement of heathers and measurement devices and for designing of automated management of the process.

Data analysis is an important issue for companies as it provides deep business insights thus facilitating their performance. Usually enterprise applications and platforms for Big Data processing live in the Java ecosystem. Therefore it is important to investigate how Java-based platforms for data analytics and machine learning work and the functionality they provide. The paper analyzes the most widely used machine learning libraries in the Java world - Deeplearning4j and Spark MLlib. Using data lakes is a common practice for storing large amount of data for data analytic tasks. Hadoop has proved to be the common choice for building data lakes. The paper will review Hadoop ecosystem components, their advantages and potential problems concerning machine learning tasks.

In this paper, an altitude control system is designed to increase the positioning accuracy of a mini-UAV on the z-axis of the inertial system and to improve conventional altitude control systems relying only on GPS, barometer or laser sensors which may have significant errors in certain flight conditions. The main objective of the mini-UAV is to monitor and detect a Corona Discharge that usually occurs on high voltage powerlines which implies a very good infrastructure in terms of on-board equipment because of the danger which occur when UAV flies quite close to the powerlines and into an intense electromagnetic field. To design the altitude controller for the longitudinal dynamics a control structure method, based on successively closed loops with different types of classic controllers was used. We concluded that the command structures with speed constraint was necessary to implement a speed device that automatically maintains a constant speed. Thus, the speed device is trying to maintain a constant speed using the throttle control. After modelling the longitudinal dynamics, numerical simulations were performed in MATLAB, Simulink and the obtained results confirmed a good performance of the proposed control strategy flight altitude control based on the automated speed device.In this paper, an altitude control system is designed to increase the positioning accuracy of a mini-UAV on the z-axis of the inertial system and to improve conventional altitude control systems relying only on GPS, barometer or laser sensors which may have significant errors in certain flight conditions. The main objective of the mini-UAV is to monitor and detect a Corona Discharge that usually occurs on high voltage powerlines which implies a very good infrastructure in terms of on-board equipment because of the danger which occur when UAV flies quite close to the powerlines and into an intense electromagnetic field. To design the altitude controller for the longitudinal dynamics a control structure method, based on successively closed loops with different types of classic controllers was used. We concluded that the command structures with speed constraint was necessary to implement a speed device that automatically maintains a constant speed. Thus, the speed device is trying to maintain a constant spee...

Augmented Reality (AR) has become an essential technology in various sectors. Nowadays, despite the popularity of AR for product promotion and media campaign, the use of printed media, such as books and cards, is still common. In fact, AR T-shirts is one of the innovations of clothing companies to promote their products. This paper was focused on the development of AR applications on T-Shirt that as a method to improve the product and to know the extent of how AR application can survive under various lighting conditions. The model used in developing the AR application was Waterfall Process Model. Lux meter was used to find out how far the camera can detect images on the T-shirt, in which it revealed that through the effect of light intensity, AR application on T-shirt could survive 10.8 lux or above. At light intensity of 10.8 lux, the camera experienced difficulty in tracking picture on the T-shirt. From the test using Lux meter, the result was that AR application could survive from twilight to sunlight. However, this study still requires further research such as the implementation of smartphones, media expert trials, and user testing to cooperate with related industries.Augmented Reality (AR) has become an essential technology in various sectors. Nowadays, despite the popularity of AR for product promotion and media campaign, the use of printed media, such as books and cards, is still common. In fact, AR T-shirts is one of the innovations of clothing companies to promote their products. This paper was focused on the development of AR applications on T-Shirt that as a method to improve the product and to know the extent of how AR application can survive under various lighting conditions. The model used in developing the AR application was Waterfall Process Model. Lux meter was used to find out how far the camera can detect images on the T-shirt, in which it revealed that through the effect of light intensity, AR application on T-shirt could survive 10.8 lux or above. At light intensity of 10.8 lux, the camera experienced difficulty in tracking picture on the T-shirt. From the test using Lux meter, the result was that AR application could survive from twilight to sunlight....

Climbing robot has been an area of interest since the demand of inspection of pipeline, nuclear power plant, and various big structure is growing up rapidly. This paper represents the development of a bio-inspired modular robot which mimics inchworm locomotion during climbing. In the present paper, the climbing motion is achieved only on a flat vertical plane by magnetic adhesion principle. The robot is modelled as a 4-link planar mechanism with three revolute joints actuated by DC servo motors. Sinusoidal gait pattern is used to approximate the motion of an inchworm. The dynamics of the robot is presented by using ADAMS/MATLAB co-simulation methodology. The simulation result gives the maximum value of joint torque during one complete cycle of motion. This torque value is used for the selection of servo motor specifications required to build the prototype.

While the prediction of spatial distribution of potential landslide occurrences is a primary interest in landslide hazard mitigation, it remains a challenging task. To overcome the scarceness of complete, sufficiently detailed geomorphological attributes and environmental conditions, various machine-learning techniques are increasingly applied to effectively map landslide susceptibility for large regions. Nevertheless, limited review papers are devoted to this field, particularly on the various domain specific applications of machine learning techniques. Available literature often report relatively good predictive performance, however, papers discussing the limitations of each approaches are quite uncommon. The foremost aim of this paper is to narrow these gaps in literature and to review up-to-date machine learning and ensemble learning techniques applied in landslide susceptibility mapping. It provides new readers an introductory understanding on the subject matter and researchers a contemporary review ...

In today’s society, with the rapid development and extensive application of the information technology of the network central station and the integrated information system technology, information plays an important role in the military communication, mastering the information right to the competition Important role, how to protect one’s own security, smooth access to and transmission of information, and to maximize the elimination of interference has become an important issue at home and abroad. QPSK modulation and its improved QPSK modulation as the mainstream signal modulation, the most widely used. In this paper, the principle of QPSK and QDPSK modulation and demodulation are introduced in this paper. Then, how to interfere with QPSK modulation signal is analyzed, and the interference of QPSK modulation signal is simulated by Matlab scripting program, which can be used in the next step. And to study the next step of anti-jamming measures provided the basis and preparatory work.

This research paper aims to propose a hybrid of ant colony optimization (ACO) and k-nearest neighbor (KNN) algorithms as feature selections for selecting and choosing relevant features from customer review datasets. Information gain (IG), genetic algorithm (GA), and rough set attribute reduction (RSAR) were used as baseline algorithms in a performance comparison with the proposed algorithm. This paper will also discuss the significance test, which was used to evaluate the performance differences between the ACO-KNN, IG-GA, and IG-RSAR algorithms. This study evaluated the performance of the ACO-KNN algorithm using precision, recall, and F-score, which were validated using the parametric statistical significance tests. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. In ...

With the ever increasing of internet applications and social networking sites, people nowadays can easily express their feelings towards any products and services. These online reviews act as an important source for further analysis and improved decision making. These reviews are mostly unstructured by nature and thus, need processing like sentiment analysis and classification to provide a meaningful information for future uses. In text analysis tasks, the appropriate selection of words/features will have a huge impact on the effectiveness of the classifier. Thus, this paper explores the effect of the pre-processing strategies in the sentiment analysis of online movie reviews. In this paper, supervised machine learning method was used to classify the reviews. The support vector machine (SVM) with linear and non-linear kernel has been considered as classifier for the classification of the reviews. The performance of the classifier is critically examined based on the results of precision, recall, f-measure,...

The availability, integrity and confidentiality of information are fundamental to the long-term survival of any organization. Information security is a complex issue that must be holistically approached, combining assets that support corporate systems, in an extended network of business partners, vendors, customers and other stakeholders. This paper addresses the conception and implementation of information security systems, conform the ISO/IEC 27000 set of standards, using the model-driven approach. The process begins with the conception of a domain level model (computation independent model) based on information security vocabulary present in the ISO/IEC 27001 standard. Based on this model, after embedding in the model mandatory rules for attaining ISO/IEC 27001 conformance, a platform independent model is derived. Finally, a platform specific model serves the base for testing the compliance of information security systems with the ISO/IEC 27000 set of standards.The availability, integrity and confidentiality of information are fundamental to the long-term survival of any organization. Information security is a complex issue that must be holistically approached, combining assets that support corporate systems, in an extended network of business partners, vendors, customers and other stakeholders. This paper addresses the conception and implementation of information security systems, conform the ISO/IEC 27000 set of standards, using the model-driven approach. The process begins with the conception of a domain level model (computation independent model) based on information security vocabulary present in the ISO/IEC 27001 standard. Based on this model, after embedding in the model mandatory rules for attaining ISO/IEC 27001 conformance, a platform independent model is derived. Finally, a platform specific model serves the base for testing the compliance of information security systems with the ISO/IEC 27000 set of standards.

The blindness of fuzzing test is the main reason for its inefficiency in practical vulnerability discovery. In this paper, we proposed a static analysis assisted and vulnerability-oriented fuzzing testing technology. Through the static analysis, the suspect vulnerable code areas can be located roughly. And combined with dynamics update based on the fuzzing feedback, the vulnerable code areas can be further accurately located. By applying the distances to the located vulnerable code areas as one of metrics of the evolutionary fuzzing test, the vulnerability-oriented test cases are generated. The results in the experiment showed that the method proposed in this paper could effectually improve the vulnerability discovering efficiency of fuzzing test.

Nowadays, designers are more concern with the issue of engagement and informal learning at museum and gallery sites. This has made studies to focus more on the use of Mobile Augmented Reality (MAR) at museum and gallery sites. However, most of the MAR applications for museum visitors are largely tailored to normal hearing visitors while the hearing-impaired (HI) visitors are not supported. The hearing impaired (HI) community account for over 5% of the world’s populace which is about 360 million people. Thus, this paper explores the design elements of mobile augmented reality for engaging hearing impaired visitors at the museum site. The findings of this paper argues that there are eleven major elements of engagement of MAR needed for the design of an efficient museum MAR app for hearing impaired visitors. These eleven elements include Aesthetics, Curiosity, Usability, Interaction, Motivation, Satisfaction, Self-Efficacy, Perceived Control, Enjoyment, Focused Attention and Interest. This study pointed out that for an efficient and engaged MAR app for the HI community especially HI visitors to museum sites, these eleven elements are critical. This finding will help MAR designers and developers on how to design an efficient and engaged MAR app for the HI community at large and museum HI visitors specifically.Nowadays, designers are more concern with the issue of engagement and informal learning at museum and gallery sites. This has made studies to focus more on the use of Mobile Augmented Reality (MAR) at museum and gallery sites. However, most of the MAR applications for museum visitors are largely tailored to normal hearing visitors while the hearing-impaired (HI) visitors are not supported. The hearing impaired (HI) community account for over 5% of the world’s populace which is about 360 million people. Thus, this paper explores the design elements of mobile augmented reality for engaging hearing impaired visitors at the museum site. The findings of this paper argues that there are eleven major elements of engagement of MAR needed for the design of an efficient museum MAR app for hearing impaired visitors. These eleven elements include Aesthetics, Curiosity, Usability, Interaction, Motivation, Satisfaction, Self-Efficacy, Perceived Control, Enjoyment, Focused Attention and Interest. This study pointed out ...

Mathematical modeling of the heat transfer during the pyrolysis process used for the treatment of the End-of-Lifetires (EOLT) is presented in this paper. The pyrolysis process is 3D and non-stationary and because of this it is very complicated for modeling and studying. To simplify the modeling here a hierarchy of 2D models for the temperature which describe the non-stationary heat transfer in such a pyrolysis station is created. An algorithm for solving the model equations, based on MATLAB software is developed. The results for the temperature for some characteristic periods of operation of pyrolysis station are presented and commented in the paper. The results from this modeling can be used in the real pyrolysis station for more precise displacement of measurement devices and for designing of automated management of the process.

Integration of computerized system in healthcare management help in smoothening the documentation of patient records, highly accesses of knowledge and clinical practices guideline, and advice on decision making. Exploit the advancement of artificial intelligent such as fuzzy logic and rule-based reasoning may improve the management of emergency department in terms of uncertainty condition and medical practices adherence towards clinical guideline. This paper presenting details of the emergency department flow for acute asthma severity identification with the embedding of acute asthma severity identification expert system (AASIES). Currently, AASIES is still in preliminary stage of system validation. However, the implementation of AASIES in asthma bay management is hope can reduce the usage of paper for manual documentation and be a pioneer for the development of a more complex decision support system to smoothen the ED management and more systematic.

Big data analysis is a hot topic in the IT field now. Spark is a high-reliability and high-performance distributed parallel computing framework for big data sets. K-means algorithm is one of the classical partition methods in clustering algorithm. In this paper, we study the k-means clustering algorithm on Spark. Firstly, the principle of the algorithm is analyzed, and then the clustering analysis is carried out on the supermarket customers through the experiment to find out the different shopping patterns. At the same time, this paper proposes the parallelization of k-means algorithm and the distributed computing framework of Spark, and gives the concrete design scheme and implementation scheme. This paper uses the two-year sales data of a supermarket to validate the proposed clustering algorithm and achieve the goal of subdividing customers, and then analyze the clustering results to help enterprises to take different marketing strategies for different customer groups to improve sales performance.

The paper discusses two methods of design of power optimized FSMs. Both methods use clock gating techniques. The main objective of the research was to write a program capable of generating automatic hardware description of finite-state machines in VHDL and testbenches to help power analysis. The creation of relevant output files is detailed step by step. The program was tested using the LGSynth91 FSM benchmark package. An analysis of the generated circuits shows that the second method presented in this paper leads to significant reduction of power consumption.

The vision of Internet of Things (IoT) is about interconnectivity between sensors, actuators, people and processes. IoT exploits connectivity between physical objects like fridges, cars, utilities, buildings and cities for enhancing the lives of people through automation and data analytics. However, this sudden increase in connected heterogeneous IoT devices takes a huge toll on the existing Internet infrastructure and introduces new challenges for researchers to embark upon. This paper highlights the effects of heterogeneity challenges on connectivity, interoperability, management in greater details. It also surveys some of the existing solutions adopted in the core network to solve the challenges of massive IoT deployment. The paper finally concludes that IoT architecture and network infrastructure needs to be reengineered ground-up, so that IoT solutions can be safely and efficiently deployed.

To protect the privacy of sensitive data, an encrypted and decrypted file system based on USBKey and hardware code is designed and implemented in this paper. This system uses USBKey and hardware code to authenticate a user. We use random key to encrypt file with symmetric encryption algorithm and USBKey to encrypt random key with asymmetric encryption algorithm. At the same time, we use the MD5 algorithm to calculate the hash of file to verify its integrity. Experiment results show that large files can be encrypted and decrypted in a very short time. The system has high efficiency and ensures the security of documents.To protect the privacy of sensitive data, an encrypted and decrypted file system based on USBKey and hardware code is designed and implemented in this paper. This system uses USBKey and hardware code to authenticate a user. We use random key to encrypt file with symmetric encryption algorithm and USBKey to encrypt random key with asymmetric encryption algorithm. At the same time, we use the MD5 algorithm to calculate the hash of file to verify its integrity. Experiment results show that large files can be encrypted and decrypted in a very short time. The system has high efficiency and ensures the security of documents.

As the vibration of running vehicle mainly comes from road and influence vehicle ride performance. So the road roughness power spectral density simulation has great significance to analyze automobile suspension vibration system parameters and evaluate ride comfort. Firstly, this paper based on the mathematical model of road roughness power spectral density, established the integral white noise road random method. Then in the MATLAB/Simulink environment, according to the research method of automobile suspension frame from simple two degree of freedom single-wheel vehicle model to complex multiple degrees of freedom vehicle model, this paper built the simple single incentive input simulation model. Finally the spectrum matrix was used to build whole vehicle incentive input simulation model. This simulation method based on reliable and accurate mathematical theory and can be applied to the random road simulation of any specified spectral which provides pavement incentive model and foundation to vehicle ride ...

Large portion of numbers team organization in the IBS construction sector is known are being fragmented. That is contributed from a segregation of construction activity thus create team working in virtually. Virtual team are the nature when teams are working in distributed area, across culture and time. Therefore, teams can be respond to the task without relocating to the site project and settle down a problem through information and communication technology (ICT). The emergence of virtual team are carry out by advancements in communication technologies as a medium to improve project team communication in project delivery process on IBS construction. Based on literature review from previous study and data collected from interviewing, this paper aim to identified communication challenges among project team members according to current project development practices in IBS construction project. Hence, in attempt to develop effective communication through the advantages of virtual team approach for IBS construction project. In order to ensure the data is gathered comprehensively and accurately, the data was collected from project managers by using semi structured interview method. It was found that virtual team approach could be enable competitive challenges on complexity in the construction project management process.Large portion of numbers team organization in the IBS construction sector is known are being fragmented. That is contributed from a segregation of construction activity thus create team working in virtually. Virtual team are the nature when teams are working in distributed area, across culture and time. Therefore, teams can be respond to the task without relocating to the site project and settle down a problem through information and communication technology (ICT). The emergence of virtual team are carry out by advancements in communication technologies as a medium to improve project team communication in project delivery process on IBS construction. Based on literature review from previous study and data collected from interviewing, this paper aim to identified communication challenges among project team members according to current project development practices in IBS construction project. Hence, in attempt to develop effective communication through the advantages of virtual team approach for IBS constr...

This paper presents the concept and the modern advances in personalized medicine that rely on technology and review the existing tools for early detection of breast cancer. The breast cancer types and distribution worldwide is discussed. It is spent time to explain the importance of identifying the normality and to specify the main classes in breast cancer, benign or malignant. The main purpose of the paper is to propose a conceptual model for early detection of breast cancer based on machine learning for processing and analysis of medical big dataand further knowledge discovery for personalized treatment. The proposed conceptual model is realized by using Naive Bayes classifier. The software is written in python programming language and for the experiments the Wisconsin breast cancer database is used. Finally, the experimental results are presented and discussed.

With the continuous development of network technology and the rapid spread of the Internet, computer networks have been around the world every corner. However, the network attacks frequently occur. The ARP protocol vulnerability is one of the most common vulnerabilities in the TCP / IP four-layer architecture. The network protocol vulnerabilities can lead to the intrusion and attack of the information system, and disable or disable the normal defense function of the system [1]. At present, ARP spoofing Trojans spread widely in the LAN, the network security to run a huge hidden danger, is the primary threat to LAN security. In this paper, the author summarizes the research status and the key technologies involved in ARP protocol, analyzes the formation mechanism of ARP protocol vulnerability, and analyzes the feasibility of the attack technique. Based on the summary of the common defensive methods, the advantages and disadvantages of each defense method. At the same time, the current defense method is improved, and the advantage of the improved defense algorithm is given. At the end of this paper, the appropriate test method is selected and the test environment is set up. Experiment and test are carried out for each proposed improved defense algorithm.With the continuous development of network technology and the rapid spread of the Internet, computer networks have been around the world every corner. However, the network attacks frequently occur. The ARP protocol vulnerability is one of the most common vulnerabilities in the TCP / IP four-layer architecture. The network protocol vulnerabilities can lead to the intrusion and attack of the information system, and disable or disable the normal defense function of the system [1]. At present, ARP spoofing Trojans spread widely in the LAN, the network security to run a huge hidden danger, is the primary threat to LAN security. In this paper, the author summarizes the research status and the key technologies involved in ARP protocol, analyzes the formation mechanism of ARP protocol vulnerability, and analyzes the feasibility of the attack technique. Based on the summary of the common defensive methods, the advantages and disadvantages of each defense method. At the same time, the current defense method is impr...

Spectrum prediction technology is an effective way to solve the problems of processing latency, spectrum access, spectrum collision and energy consumption in cognitive radio networks. Spectral prediction technology is divided into three categories according to its nature, namely, spectral prediction method based on regression analysis, spectrum prediction method based on Markov model and spectrum prediction method based on machine learning. By analyzing and comparing the three kinds of prediction models, the author hopes to provide some reference for the later researchers. In this paper, the development situation, practical application and existent problems of three kinds of forecasting models are analyzed and summarized. On this basis, this paper discusses the development trend of the next step.

The aim of this paper is a comparison of the existing classification algorithms with different parameters, and selection those ones, which allows solving the problem of primary diagnosis of cervical intraepithelial neoplasia (CIN), as it characterizes the condition of the body in the precancerous stage. The paper describes a feature selection process, as well as selection of the best models for a multiclass classification. © 2017 Author(s).

This paper presents an image classification algorithm based on spatial sparse coding model and random forest. Firstly, SIFT feature extraction of the image; and then use the sparse encoding theory to generate visual vocabulary based on SIFT features, and using the visual vocabulary of SIFT features into a sparse vector; through the combination of regional integration and spatial sparse vector, the sparse vector gets a fixed dimension is used to represent the image; at last random forest classifier for image sparse vectors for training and testing, using the experimental data set for standard test Caltech-101 and Scene-15. The experimental results show that the proposed algorithm can effectively represent the features of the image and improve the classification accuracy. In this paper, we propose an innovative image recognition algorithm based on image segmentation, sparse coding and multi instance learning. This algorithm introduces the concept of multi instance learning, the image as a multi instance bag...

The paper deals with a follow-up research on intelligent tutoring systems that were studied in authors’ previous papers from the point of view of describing their advantages. In this paper, the authors make use of the fuzzy logic expert system, which assesses student’s knowledge, and integrate it into the intelligent tutoring system called Barborka. The goal is to create an even more personal student’s study plan, which is tailored both to student’s sensory/learning preferences and the level of knowledge of the given subject.

The development of computers and artificial intelligence theory allow their application in the field of education. Intelligent tutoring systems reflect student learning styles and adapt the curriculum according to their individual needs. The building of intelligent tutoring systems requires not only the creation of suitable software, but especially the search and application of the rules enabling ICT to individually adapt the curriculum. The main idea of this paper is to attempt to specify the rules for dividing the students to systematically working students and more practically or pragmatically inclined students. The paper shows that monitoring the work of students in e-learning environment, analysis of various approaches to educational materials and correspondence assignments show different results for the defined groups of students.

Traditional supervised classifiers neglect a large amount of data which not have sufficient follow-up information, only work with labeled data. Consequently, the small sample size limits the advancement of design appropriate classifier. In this paper, a transductive learning method which combined with the filtering strategy in transductive framework and progressive labeling strategy is addressed. The progressive labeling strategy does not need to consider the distribution of labeled samples to evaluate the distribution of unlabeled samples, can effective solve the problem of evaluate the proportion of positive and negative samples in work set. Our experiment result demonstrate that the proposed technique have great potential in cancer prediction based on gene expression.Traditional supervised classifiers neglect a large amount of data which not have sufficient follow-up information, only work with labeled data. Consequently, the small sample size limits the advancement of design appropriate classifier. In this paper, a transductive learning method which combined with the filtering strategy in transductive framework and progressive labeling strategy is addressed. The progressive labeling strategy does not need to consider the distribution of labeled samples to evaluate the distribution of unlabeled samples, can effective solve the problem of evaluate the proportion of positive and negative samples in work set. Our experiment result demonstrate that the proposed technique have great potential in cancer prediction based on gene expression.

This paper studied on the store-space assignment based on logistic AGV in E-commerce goods to person picking pattern, and established the store-space assignment model based on the lowest picking cost, and design for store-space assignment algorithm after the cluster analysis based on similarity coefficient. And then through the example analysis, compared the picking cost between store-space assignment algorithm this paper design and according to item number and storage according to ABC classification allocation, and verified the effectiveness of the design of the store-space assignment algorithm.

This paper compares the performances of four rank-based weighting assessment techniques, Rank Sum (RS), Rank Reciprocal (RR), Rank Exponent (RE), and Rank Order Centroid (ROC) on five identified e-learning criteria to select the best weights method. A total of 35 experts in a public university in Malaysia were asked to rank the criteria and to evaluate five e-learning approaches which include blended learning, flipped classroom, ICT supported face to face learning, synchronous learning, and asynchronous learning. The best ranked criteria weights are defined as weights that have the least total absolute differences with the geometric mean of all weights, were then used to select the most suitable e-learning approach by using TOPSIS method. The results show that RR weights are the best, while flipped classroom approach implementation is the most suitable approach. This paper has developed a decision framework to aid decision makers (DMs) in choosing the most suitable weighting method for solving MCDM problems.