Search results for: Service Oriented Integration

Authors: Adam Gorine, Faten Spondon

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Python is considered the most popular programming language and offers its own ecosystem for archiving and maintaining open-source software packages. This system is called the Python Package Index (PyPI), the repository of this programming language. Unfortunately, one-third of these software packages have vulnerabilities that allow attackers to execute code automatically when a vulnerable or malicious package is installed. This paper contributes to large-scale empirical studies investigating security issues in the Python ecosystem by evaluating package vulnerabilities. These provide a series of implications that can help the security of software ecosystems by improving the process of discovering, fixing, and managing package vulnerabilities. The vulnerable dataset is generated using the NVD, the National Vulnerability Database, and the Snyk vulnerability dataset. In addition, we evaluated 807 vulnerability reports in the NVD and 3900 publicly known security vulnerabilities in Python Package Manager (Pip) from the Snyk database from 2002 to 2022. As a result, many Python vulnerabilities appear in high severity, followed by medium severity. The most problematic areas have been improper input validation and denial of service attacks. A hybrid scanning tool that combines the three scanners, Bandit, Snyk and Dlint, which provide a clear report of the code vulnerability, is also described.

Keywords: Python vulnerabilities, Bandit, Snyk, Dlint, Python Package Index, ecosystem, static analysis, malicious attacks.

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Authors: Farzana Yasmeen, Md. Nurul Huda, Md. Enamul Haque, Michihiro Aoki, Shigeki Yamada

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Delay-Tolerant Networks (DTNs) are sparse, wireless networks where disconnections are common due to host mobility and low node density. The Message Ferrying (MF) scheme is a mobilityassisted paradigm to improve connectivity in DTN-like networks. A ferry or message ferry is a special node in the network which has a per-determined route in the deployed area and relays messages between mobile hosts (MHs) which are intermittently connected. Increased contact opportunities among mobile hosts and the ferry improve the performance of the network, both in terms of message delivery ratio and average end-end delay. However, due to the inherent mobility of mobile hosts and pre-determined periodicity of the message ferry, mobile hosts may often -miss- contact opportunities with a ferry. In this paper, we propose the combination of stationary ferry access points (FAPs) with MF routing to increase contact opportunities between mobile hosts and the MF and consequently improve the performance of the DTN. We also propose several placement models for deploying FAPs on MF routes. We evaluate the performance of the FAP placement models through comprehensive simulation. Our findings show that FAPs do improve the performance of MF-assisted DTNs and symmetric placement of FAPs outperforms other placement strategies.

Keywords: Service infrastructure, delay-tolerant network, messageferry routing, placement models.

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Authors: Jörg Linde, Ekaterina Buyko, Robert Altwasser, Udo Hahn, Reinhard Guthke

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Reverse engineering of full-genomic interaction networks based on compendia of expression data has been successfully applied for a number of model organisms. This study adapts these approaches for an important non-model organism: The major human fungal pathogen Candida albicans. During the infection process, the pathogen can adapt to a wide range of environmental niches and reversibly changes its growth form. Given the importance of these processes, it is important to know how they are regulated. This study presents a reverse engineering strategy able to infer fullgenomic interaction networks for C. albicans based on a linear regression, utilizing the sparseness criterion (LASSO). To overcome the limited amount of expression data and small number of known interactions, we utilize different prior-knowledge sources guiding the network inference to a knowledge driven solution. Since, no database of known interactions for C. albicans exists, we use a textmining system which utilizes full-text research papers to identify known regulatory interactions. By comparing with these known regulatory interactions, we find an optimal value for global modelling parameters weighting the influence of the sparseness criterion and the prior-knowledge. Furthermore, we show that soft integration of prior-knowledge additionally improves the performance. Finally, we compare the performance of our approach to state of the art network inference approaches.

Keywords: Pathogen, network inference, text-mining, Candida albicans, LASSO, mutual information, reverse engineering, linear regression, modelling.

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Authors: Ons Sassi, Wahiba Ramdane Cherif-Khettaf, Ammar Oulamara

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In this paper, we consider the vehicle routing problem with mixed fleet of conventional and heterogenous electric vehicles and time dependent charging costs, denoted VRP-HFCC, in which a set of geographically scattered customers have to be served by a mixed fleet of vehicles composed of a heterogenous fleet of Electric Vehicles (EVs), having different battery capacities and operating costs, and Conventional Vehicles (CVs). We include the possibility of charging EVs in the available charging stations during the routes in order to serve all customers. Each charging station offers charging service with a known technology of chargers and time dependent charging costs. Charging stations are also subject to operating time windows constraints. EVs are not necessarily compatible with all available charging technologies and a partial charging is allowed. Intermittent charging at the depot is also allowed provided that constraints related to the electricity grid are satisfied. The objective is to minimize the number of employed vehicles and then minimize the total travel and charging costs. In this study, we present a Mixed Integer Programming Model and develop a Charging Routing Heuristic and a Local Search Heuristic based on the Inject-Eject routine with different insertion methods. All heuristics are tested on real data instances.

Keywords: charging problem, electric vehicle, heuristics, local search, optimization, routing problem.

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Authors: Mohanad Alhabo, Li Zhang, Naveed Nawaz

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Small cell deployment in 5G networks is a promising technology to enhance the capacity and coverage. However, unplanned deployment may cause high interference levels and high number of unnecessary handovers, which in turn result in an increase in the signalling overhead. To guarantee service continuity, minimize unnecessary handovers and reduce signalling overhead in heterogeneous networks, it is essential to properly model the handover decision problem. In this paper, we model the handover decision problem using Multiple Attribute Decision Making (MADM) method, specifically Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and propose a hybrid TOPSIS method to control the handover in heterogeneous network. The proposed method adopts a hybrid weighting policy, which is a combination of entropy and standard deviation. A hybrid weighting control parameter is introduced to balance the impact of the standard deviation and entropy weighting on the network selection process and the overall performance. Our proposed method show better performance, in terms of the number of frequent handovers and the mean user throughput, compared to the existing methods.

Keywords: Handover, HetNets, interference, MADM, small cells, TOPSIS, weight.

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Authors: T.Sheela, Dr.J.Raja

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Continuously growing needs for Internet applications that transmit massive amount of data have led to the emergence of high speed network. Data transfer must take place without any congestion and hence feedback parameters must be transferred from the receiver end to the sender end so as to restrict the sending rate in order to avoid congestion. Even though TCP tries to avoid congestion by restricting the sending rate and window size, it never announces the sender about the capacity of the data to be sent and also it reduces the window size by half at the time of congestion therefore resulting in the decrease of throughput, low utilization of the bandwidth and maximum delay. In this paper, XCP protocol is used and feedback parameters are calculated based on arrival rate, service rate, traffic rate and queue size and hence the receiver informs the sender about the throughput, capacity of the data to be sent and window size adjustment, resulting in no drastic decrease in window size, better increase in sending rate because of which there is a continuous flow of data without congestion. Therefore as a result of this, there is a maximum increase in throughput, high utilization of the bandwidth and minimum delay. The result of the proposed work is presented as a graph based on throughput, delay and window size. Thus in this paper, XCP protocol is well illustrated and the various parameters are thoroughly analyzed and adequately presented.

Keywords: Bandwidth-Delay Product, Congestion Control, Congestion Window, TCP/IP

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Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: Situation-awareness, Smart home, IoT, Machine learning, Classifier.

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Authors: Oseni Taiwo Amoo, Bloodless Dzwairo

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In this paper, we extend the versatility and usefulness of GIS as a methodology for any river basin hydrologic characteristics analysis (HCA). The Gurara River basin located in North-Central Nigeria is presented in this study. It is an on-going research using spatial Digital Elevation Model (DEM) and Arc-Hydro tools to take inventory of the basin characteristics in order to predict water abstraction quantification on streamflow regime. One of the main concerns of hydrological modelling is the quantification of runoff from rainstorm events. In practice, the soil conservation service curve (SCS) method and the Conventional procedure called rational technique are still generally used these traditional hydrological lumped models convert statistical properties of rainfall in river basin to observed runoff and hydrograph. However, the models give little or no information about spatially dispersed information on rainfall and basin physical characteristics. Therefore, this paper synthesizes morphometric parameters in generating runoff. The expected results of the basin characteristics such as size, area, shape, slope of the watershed and stream distribution network analysis could be useful in estimating streamflow discharge. Water resources managers and irrigation farmers could utilize the tool for determining net return from available scarce water resources, where past data records are sparse for the aspect of land and climate.

Keywords: Hydrological characteristic, land and climate, runoff discharge, streamflow.

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Authors: Saleh Alumaran, Giampaolo Bella, Feng Chen

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The study of organisations’ information security cultures has attracted scholars as well as healthcare services industry to research the topic and find appropriate tools and approaches to develop a positive culture. The vast majority of studies in Saudi national health services are on the use of technology to protect and secure health services information. On the other hand, there is a lack of research on the role and impact of an organisation’s cultural dimensions on information security. This research investigated and analysed the role and impact of cultural dimensions on information security in Saudi Arabia health service. Hypotheses were tested and two surveys were carried out in order to collect data and information from three major hospitals in Saudi Arabia (SA). The first survey identified the main cultural-dimension problems in SA health services and developed an initial information security culture framework model. The second survey evaluated and tested the developed framework model to test its usefulness, reliability and applicability. The model is based on human behaviour theory, where the individual’s attitude is the key element of the individual’s intention to behave as well as of his or her actual behaviour. The research identified a set of cultural and sub-cultural dimensions in SA health information security and services.

Keywords: Behaviour theory, Culture dimensions, Electronic health records, Information security.

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Authors: Natalia Polkanova, Sergey Kazakov

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In the second decade of the XXI century the role of tourism destination attractiveness is becoming increasingly important for destination management. Competition in tourism market moves from ordinary service quality to provision of unforgettable emotional experience for tourists. The main purpose of the present study is to identify the perception of the tourism destinations based on the number of factors related to its tourist attractiveness. The content analysis method was used to analyze the on-line tourist feedback data immensely available in Social Media and in travel related sites. The collected data made it possible to procure the information which is necessary to understand the perceived attractiveness of the destinations and key destination appeal factors that are important for Russian leisure travelers. Results of the present study demonstrate key attractiveness factors or destination ‘properties’ that were unveiled as the most important for Russian leisure tourists. The study targeted five main Spanish tourism destinations that initially were determined by in-depth interview with a number of Russian nationals who had visited Spain at least once. The research results can be useful for Spanish Tourism Organization Representation office in Russia as well as for the other national tourism organizations in order to promote their respective destinations for Russian travelers focusing on main attractiveness factors identified in this study.

Keywords: Tourism destination, destination attractiveness, destination competitiveness, content analysis, unstructured image.

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Authors: Mohsen Soori, Fooad Karimi Ghaleh Jough

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The integration of Artificial Intelligence (AI) techniques in the optimization of steel moment frame structures represents a transformative approach to enhance the design, analysis, and performance of these critical engineering systems. The review encompasses a wide spectrum of AI methods, including machine learning algorithms, evolutionary algorithms, neural networks, and optimization techniques, applied to address various challenges in the field. The synthesis of research findings highlights the interdisciplinary nature of AI applications in structural engineering, emphasizing the synergy between domain expertise and advanced computational methodologies. This synthesis aims to serve as a valuable resource for researchers, practitioners, and policymakers seeking a comprehensive understanding of the state-of-the-art in AI-driven optimization for steel moment frame structures. The paper commences with an overview of the fundamental principles governing steel moment frame structures and identifies the key optimization objectives, such as efficiency of structures. Subsequently, it delves into the application of AI in the conceptual design phase, where algorithms aid in generating innovative structural configurations and optimizing material utilization. The review also explores the use of AI for real-time structural health monitoring and predictive maintenance, contributing to the long-term sustainability and reliability of steel moment frame structures. Furthermore, the paper investigates how AI-driven algorithms facilitate the calibration of structural models, enabling accurate prediction of dynamic responses and seismic performance. Thus, by reviewing and analyzing the recent achievements in applications artificial intelligent in optimization of steel moment frame structures, the process of designing, analysis, and performance of the structures can be analyzed and modified.

Keywords: Artificial Intelligent, optimization process, steel moment frame, structural engineering.

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Authors: Marialuisa Gennari, Giancarlo Tamanza, Ilaria Montanari

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Identity development in adolescence is characterized by many risks and challenges, and becomes even more complex by the situation of migration and deafness. In particular, the condition of the second generation of migrant adolescents involves the comparison between the family context in which everybody speaks a language and deals with a specific culture (usually parents’ and relatives’ original culture), the social context (school, peer groups, sports groups), where a foreign language is spoken and a new culture is faced, and finally in the context of the “deaf” world. It is a dialectic involving unsolved differences that have to be treated in a discontinuous process, which will give complex outcomes and chances depending on the process of elaboration of the themes of growth and development, culture and deafness. This paper aims to underline the problems and opportunities for each issue which immigrant deaf adolescents must deal with. In particular, it will highlight the importance of a multifactorial approach for the analysis of personal resources (both intra-psychic and relational); the level of integration of the family of origin in the migration context; the elaboration of the migration event, and finally, the tractability of the condition of deafness. Some psycho-educational support objectives will be also highlighted for the identity development of deaf immigrant adolescents, with particular emphasis on the construction of the adolescents’ useful abilities to decode complex emotions, to develop self-esteem and to get critical thoughts about the inevitable attempts to build their identity. Remarkably, and of importance, the construction of flexible settings which support adolescents in a supple, “decentralized” way in order to avoid the regressive defenses that do not allow for the development of an authentic self.

Keywords: Immigrant deaf adolescents, identity development, personal and social challenges, psycho-educational support.

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Authors: Kyoung-jae Kim

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Recommender systems are usually regarded as an important marketing tool in the e-commerce. They use important information about users to facilitate accurate recommendation. The information includes user context such as location, time and interest for personalization of mobile users. We can easily collect information about location and time because mobile devices communicate with the base station of the service provider. However, information about user interest can-t be easily collected because user interest can not be captured automatically without user-s approval process. User interest usually represented as a need. In this study, we classify needs into two types according to prior research. This study investigates the usefulness of data mining techniques for classifying user need type for recommendation systems. We employ several data mining techniques including artificial neural networks, decision trees, case-based reasoning, and multivariate discriminant analysis. Experimental results show that CHAID algorithm outperforms other models for classifying user need type. This study performs McNemar test to examine the statistical significance of the differences of classification results. The results of McNemar test also show that CHAID performs better than the other models with statistical significance.

Keywords: Customer need type, Data mining techniques, Recommender system, Personalization, Mobile user.

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Authors: Roman Graf, Sergiu Gordea, Heather M. Ryan

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This paper presents an approach for easy creation and classification of institutional risk profiles supporting endangerment analysis of file formats. The main contribution of this work is the employment of data mining techniques to support set up of the most important risk factors. Subsequently, risk profiles employ risk factors classifier and associated configurations to support digital preservation experts with a semi-automatic estimation of endangerment group for file format risk profiles. Our goal is to make use of an expert knowledge base, accuired through a digital preservation survey in order to detect preservation risks for a particular institution. Another contribution is support for visualisation of risk factors for a requried dimension for analysis. Using the naive Bayes method, the decision support system recommends to an expert the matching risk profile group for the previously selected institutional risk profile. The proposed methods improve the visibility of risk factor values and the quality of a digital preservation process. The presented approach is designed to facilitate decision making for the preservation of digital content in libraries and archives using domain expert knowledge and values of file format risk profiles. To facilitate decision-making, the aggregated information about the risk factors is presented as a multidimensional vector. The goal is to visualise particular dimensions of this vector for analysis by an expert and to define its profile group. The sample risk profile calculation and the visualisation of some risk factor dimensions is presented in the evaluation section.

Keywords: linked open data, information integration, digital libraries, data mining.

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Authors: Sawarni Hasibuan, Juliza Hidayati

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Competitiveness and sustainability issues not only put pressure on big companies, but also small and medium enterprises (SMEs). SMEs Batik Bogor is one of the local culture-based creative industries in Bogor city which is also dealing with the issue of sustainability. The purpose of this research is to develop framework of sustainability at SMEs Batik Indonesia case of SMEs Batik Bogor by integrating innovation of cleaner production in its supply chain. The approach used is desk study, field survey, in-depth interviews, and benchmarking best practices of SMEs sustainability. In-depth interviews involve stakeholders to identify the needs and standards of sustainability of SMEs Batik. Data analysis was done by benchmarking method, Multi Dimension Scaling (MDS) method, and Strength, Weakness, Opportunity, Threat (SWOT) analysis. The results recommend the framework of sustainability for SMEs Batik in Indonesia. The sustainability status of SMEs Batik Bogor is classified as Moderate Sustainable. Factors that support the sustainability of SMEs Batik Bogor such is a strong commitment of top management in adopting cleaner production innovation and creativity approach. Successful cleaner production innovations are implemented primarily in the substitution of dye materials from toxic to non-toxic, reducing the intensity of non-renewable energy use, as well as the reuse and recycle of solid waste. “Mosaic Batik” is one of the innovations of solid waste utilization of batik waste produced by company R&D center that gives benefit to three pillars of sustainability, that is financial benefit, environmental benefit, and social benefit. The sustainability of SMEs Batik Bogor cannot be separated from the support of Bogor City Government which proactively facilitates the promotion of sustainable innovation produced by SMEs Batik Bogor.

Keywords: Cleaner production innovation, creativity, SMEs Batik, sustainability supply chain.

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Authors: David Halley, Tyra Oseng-Rees, Luca Pagano, Juan A Ferriz-Papi

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Recycled glass material is made from 100% recycled bottle glass and consumes less energy than re-melt technology. It also uses no additives in the manufacturing process allowing the recycled glass material, in principal, to go back to the recycling stream after end-of-use, contributing to the circular economy with a low ecological impact. The aim of this paper is to investigate the procedure for testing the recycled glass material for impact resistance, so it can be applied to pavements and other surfaces which are at risk of impact during service. A review of different impact test procedures for construction materials was undertaken, comparing methodologies and international standards applied to other materials such as natural stone, ceramics and glass. A drop weight impact testing machine was designed and manufactured in-house to perform these tests. As a case study, samples of the recycled glass material were manufactured with two different thicknesses and tested. The impact energy was calculated theoretically, obtaining results with 5 and 10 J. The results on the material were subsequently discussed. Improvements on the procedure can be made using high speed video technology to calculate velocity just before and immediately after the impact to know the absorbed energy. The initial results obtained in this procedure were positive although repeatability needs to be developed to obtain a correlation of results and finally be able to validate the procedure. The experiment with samples showed the practicality of this procedure and application to the recycled glass material impact testing although further research needs to be developed.

Keywords: Construction materials, drop weight impact, impact testing, recycled glass.

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Authors: M. Israil Hossain, T. P. Tiwari, Ashrafuzzaman Gulandaz, Nusrat Jahan

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Two-wheel tractor (power tiller) is a common tillage tool in Bangladesh agriculture for easy access in fragmented land with affordable price of small farmers. Traditional maize sheller needs to be carried from place to place by hooking with two-wheel tractor (2WT) and set up again for shelling operation which takes longer time for preparation of maize shelling. The mobile maize sheller eliminates the transportation problem and can start shelling operation instantly any place as it is attached together with 2WT. It is counterclockwise rotating cylinder, axial flow type sheller, and grain separated with a frictional force between spike tooth and concave. The maize sheller is attached with nuts and bolts in front of the engine base of 2WT. The operating power of the sheller comes from the fly wheel of the engine of the tractor through ‘V” belt pulley arrangement. The average shelling capacity of the mobile sheller is 2.0 t/hr, broken kernel 2.2%, and shelling efficiency 97%. The average maize shelling cost is Tk. 0.22/kg and traditional custom hire rate is Tk.1.0/kg, respectively (1 US$=Tk.78.0). The service provider of the 2WT can transport the mobile maize sheller long distance in operator’s seating position. The manufacturers started the fabrication of mobile maize sheller. This mobile maize sheller is also compatible for the other countries where 2WT is available for farming operation.

Keywords: Cost effective, mobile maize sheller, maize shelling capacity, small farmers, two-wheel tractor.

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Authors: Supachai Tangwongsan, Sathaporn Kassuvan

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The purpose of this research is to develop a security model for voice eavesdropping protection over digital networks. The proposed model provides an encryption scheme and a personal secret key exchange between communicating parties, a so-called voice data transformation system, resulting in a real-privacy conversation. The operation of this system comprises two main steps as follows: The first one is the personal secret key exchange for using the keys in the data encryption process during conversation. The key owner could freely make his/her choice in key selection, so it is recommended that one should exchange a different key for a different conversational party, and record the key for each case into the memory provided in the client device. The next step is to set and record another personal option of encryption, either taking all frames or just partial frames, so-called the figure of 1:M. Using different personal secret keys and different sets of 1:M to different parties without the intervention of the service operator, would result in posing quite a big problem for any eavesdroppers who attempt to discover the key used during the conversation, especially in a short period of time. Thus, it is quite safe and effective to protect the case of voice eavesdropping. The results of the implementation indicate that the system can perform its function accurately as designed. In this regard, the proposed system is suitable for effective use in voice eavesdropping protection over digital networks, without any requirements to change presently existing network systems, mobile phone network and VoIP, for instance.

Keywords: Computer Security, Encryption, Key Exchange, Security Model, Voice Eavesdropping.

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Authors: Wilailuk Meepracha

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The results of the study on the project evaluation to  develop the competencies, capabilities, and skills in repairing  computers of people in Jompluak Local Municipality, Bang Khonthi  District, Samut Songkram Province showed that the overall result  was good (4.33). When considering on each aspect, it was found that  the highest one was on process evaluation (4.60) followed by product  evaluation (4.50) and the least one was on feeding factor (3.97).  When considering in details, it was found that: 1) the context aspect  was high (4.23) with the highest item on the arrangement of the  training situation (4.67) followed by the appropriateness of the target  (4.30) and the least aspect was on the project cooperation (3.73). 2)  The evaluation of average overall primary factor or feeding factor  showed high value (4.23) while the highest aspect was on the  capability of the trainers (4.47) followed by the suitable venue (4.33)  while the least aspect was on the insufficient budget (3.47). 3) The  average result of process evaluation was very high (4.60). The  highest aspect was on the follow-op supervision (4.70) followed by  responsibility of each project staffs (4.50) while the least aspect was  on the present situation and the problems of the community (4.40). 4)  The overall result of the product evaluation was very high (4.50). The  highest aspect was on the diversity of the activities and the  community integration (4.67) followed by project target achievement  (4.63) while the least aspect was on continuation and regularity of the  activities (4.33). The trainees reported high satisfaction on the project  management at very high level (43.33%) while 40% reported high  level and 16.67% reported moderate level. Suggestions for the project  were on the additional number of the computer sets (37.78%)  followed by longer training period especially on computer skills  (43.48%).

 

Keywords: Project evaluation, competency development, the capability on computer repairing and computer skills.

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Authors: E. Ramaraj, A. Padmapriya

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In large Internet backbones, Service Providers typically have to explicitly manage the traffic flows in order to optimize the use of network resources. This process is often referred to as Traffic Engineering (TE). Common objectives of traffic engineering include balance traffic distribution across the network and avoiding congestion hot spots. Raj P H and SVK Raja designed the Bayesian network approach to identify congestion hors pots in MPLS. In this approach for every node in the network the Conditional Probability Distribution (CPD) is specified. Based on the CPD the congestion hot spots are identified. Then the traffic can be distributed so that no link in the network is either over utilized or under utilized. Although the Bayesian network approach has been implemented in operational networks, it has a number of well known scaling issues. This paper proposes a new approach, which we call the Pragati (means Progress) Node Popularity (PNP) approach to identify the congestion hot spots with the network topology alone. In the new Pragati Node Popularity approach, IP routing runs natively over the physical topology rather than depending on the CPD of each node as in Bayesian network. We first illustrate our approach with a simple network, then present a formal analysis of the Pragati Node Popularity approach. Our PNP approach shows that for any given network of Bayesian approach, it exactly identifies the same result with minimum efforts. We further extend the result to a more generic one: for any network topology and even though the network is loopy. A theoretical insight of our result is that the optimal routing is always shortest path routing with respect to some considerations of hot spots in the networks.

Keywords: Conditional Probability Distribution, Congestion hotspots, Operational Networks, Traffic Engineering.

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Authors: G. Tamanza, A. Bossoni

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84 deaf students (from primary school to college) and their families participated in this inclusion project in cooperation with numerous institutions in northern Italy (Brescia-Lombardy). Participants were either congenitally deaf or their deafness was related to other pathologies. This research promoted the integration of deaf students as they pass from primary school to high school to college. Learning methods and processes were studied that focused on encour­aging individual autonomy and socialization. The research team and its collaborators included school teachers, speech ther­apists, psychologists and home tutors, as well as teaching assistants, child neuropsychiatrists and other external authorities involved with deaf persons social inclusion programs. Deaf children and their families were supported, in terms of inclusion, and were made aware of the research team that focused on the Bisogni Educativi Speciali (BES or Special Educational Needs) (L.170/2010 - DM 5669/2011). This project included a diagnostic and evaluative phase as well as an operational one. Results demonstrated that deaf children were highly satisfied and confident; academic performance improved and collaboration in school increased. Deaf children felt that they had access to high school and college. Empowerment for the families of deaf children in terms of networking among local services that deal with the deaf also improved while family satisfaction also improved. We found that teachers and those who gave support to deaf children increased their professional skills. Achieving autonomy, instrumental, communicative and relational abilities were also found to be crucial. Project success was determined by temporal continuity, clear theoretical methodology, strong alliance for the project direction and a resilient team response.

Keywords: Autonomy, inclusion, skills, well-being.

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Authors: Jenny Paola Forero Pachón, Sonia Cristina Gamboa Sarmiento, Luis Carlos Gómez Flórez

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The Colombian government has defined an e-government strategy to take advantage of Information Technologies (IT) in order to contribute to the building of a more efficient, transparent and participative State that provides better services to citizens and businesses. In this regard, the Justice sector is one of the government sectors where IT has generated more expectation considering that the country has a judicial processes backlog. This situation has led to the search for alternative forms of access to justice that speed up the process while providing a low cost for citizens. To this end, the Colombian government has authorized the use of Alternative Dispute Resolution methods (ADR), a remedy where disputes can be resolved more quickly compared to judicial processes while facilitating greater communication between the parties, without recourse to judicial authority. One of these methods is conciliation, which includes a special modality that takes advantage of IT for the development of itself known as virtual conciliation. With this option the conciliation is supported by information systems, applications or platforms and communications are provided through it. This paper evaluates the level of maturity in how the service of virtual conciliation is under the framework of this strategy. This evaluation is carried out considering Shahkooh's 5-phase model for e-government. As a result, it is evident that in the context of conciliation, maturity does not reach the necessary level in the model so that it can be considered as virtual conciliation; therefore, it is necessary to define strategies to maximize the potential of IT in this context.

Keywords: Alternative dispute resolution, e-government, evaluation of maturity, Shahkooh model, virtual conciliation.

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Authors: S. Imbin, S. Dullah, H. Asrah, P. S. Kumar, M. E. Rahman, M. A. Mannan

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Service life of existing reinforced concrete (RC) structures in coastal towns of Sabah has been affected very much. Concrete crack, spalling of concrete cover and reinforcement rusting of RC buildings are seen even within 5 years of construction in Sabah. Hence, in this study a new mix design of concrete grout was developed using locally available materials and investigated under two curing conditions and workability, compressive strength, Accelerated Mortar Bar Test (AMBT), water absorption, volume of permeable voids (VPV), Sorptivity and 90-days salt ponding test were conducted. The compressive strength of concrete grout at the age 90 days was found to be 44.49 N/mm2 under water curing. It was observed that the percentage of mortar bar length change was below 1% for developed concrete grout. The water absorption of the concrete grout was in between the range of 0.88 % to 3.60 % under two different curing up to the age 90 days. It was also observed that the VPV of concrete was in the range of 0 % to 9.75 and 2.44% to 13.05% under water curing and site curing respectively. It was found that the Sorptivity of the concrete grout under water curing at the age of 28 days is 0.211mm/√min and at the age 90 day are 0.067 mm/√min. The chloride content decreased greatly, 90% after a depth of 15 mm. It was noticed that the site cured samples showed higher chloride contents near surface compared to water cured samples. This investigation suggested that the developed mix design of concrete grout using locally available construction materials can be used for crack repairing of existing RC structures in Sabah.

Keywords: Concrete grout, Salt ponding, Sorptivity, Water absorption.

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

Abstract:

The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: Big data, bus headway prediction, machine learning, public transportation.

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Authors: Faizal A. Samman, Thomas Hollstein, Manfred Glesner

Abstract:

This paper presents design trade-off and performance impacts of the amount of pipeline phase of control path signals in a wormhole-switched network-on-chip (NoC). The numbers of the pipeline phase of the control path vary between two- and one-cycle pipeline phase. The control paths consist of the routing request paths for output selection and the arbitration paths for input selection. Data communications between on-chip routers are implemented synchronously and for quality of service, the inter-router data transports are controlled by using a link-level congestion control to avoid lose of data because of an overflow. The trade-off between the area (logic cell area) and the performance (bandwidth gain) of two proposed NoC router microarchitectures are presented in this paper. The performance evaluation is made by using a traffic scenario with different number of workloads under 2D mesh NoC topology using a static routing algorithm. By using a 130-nm CMOS standard-cell technology, our NoC routers can be clocked at 1 GHz, resulting in a high speed network link and high router bandwidth capacity of about 320 Gbit/s. Based on our experiments, the amount of control path pipeline stages gives more significant impact on the NoC performance than the impact on the logic area of the NoC router.

Keywords: Network-on-Chip, Synchronous Parallel Pipeline, Router Architecture, Wormhole Switching

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Authors: Kasra Majbouri Yazdi, Adel Majbouri Yazdi, Saeid Khodayi, Jingyu Hou, Wanlei Zhou, Saeed Saedy

Abstract:

Fake news and false information are big challenges of all types of media, especially social media. There is a lot of false information, fake likes, views and duplicated accounts as big social networks such as Facebook and Twitter admitted. Most information appearing on social media is doubtful and in some cases misleading. They need to be detected as soon as possible to avoid a negative impact on society. The dimensions of the fake news datasets are growing rapidly, so to obtain a better result of detecting false information with less computation time and complexity, the dimensions need to be reduced. One of the best techniques of reducing data size is using feature selection method. The aim of this technique is to choose a feature subset from the original set to improve the classification performance. In this paper, a feature selection method is proposed with the integration of K-means clustering and Support Vector Machine (SVM) approaches which work in four steps. First, the similarities between all features are calculated. Then, features are divided into several clusters. Next, the final feature set is selected from all clusters, and finally, fake news is classified based on the final feature subset using the SVM method. The proposed method was evaluated by comparing its performance with other state-of-the-art methods on several specific benchmark datasets and the outcome showed a better classification of false information for our work. The detection performance was improved in two aspects. On the one hand, the detection runtime process decreased, and on the other hand, the classification accuracy increased because of the elimination of redundant features and the reduction of datasets dimensions.

Keywords: Fake news detection, feature selection, support vector machine, K-means clustering, machine learning, social media.

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Authors: L. Edirisinghe, Zhihong Jin, A. W. Wijeratne, R. Mudunkotuwa

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The virtual container yard is an effective solution to the container inventory imbalance problem which is a global issue. It causes substantial cost to carriers, which inadvertently adds to the prices of consumer goods. The virtual container yard is rooted in the fundamentals of container interchange between carriers. If carriers opt to interchange their excess containers with those who are deficit, a substantial part of the empty reposition cost could be eliminated. Unlike in other types of ships, cargo cannot be directly loaded to a container ship. Slots and containers are supplementary components; thus, without containers, a carrier cannot ship cargo if the containers are not available and vice versa. Few decades ago, carriers recognized slot (the unit of space in a container ship) interchange as a viable solution for the imbalance of shipping space. Carriers interchange slots among them and it also increases the advantage of scale of economies in container shipping. Some of these service agreements between mega carriers have provisions to interchange containers too. However, the interchange mechanism is still not popular among carriers for containers. This is the paradox that prevails in the liner shipping industry. At present, carriers reposition their excess empty containers to areas where they are in demand. This research applied factor analysis statistical method. The paper reveals that five major components may influence the virtual container yard namely organisation, practice and culture, legal and environment, international nature, and marketing. There are 12 variables that may impact the virtual container yard, and these are explained in the paper.

Keywords: Virtual container yard, imbalance, management, inventory.

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Authors: Kari Björn, Mikael Soini

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Higher Education system reforms, especially Finnish system of Universities of Applied Sciences in 2014 are discussed. The new steering model is based on major legislative changes, output-oriented funding and open information. The governmental steering reform, especially the financial model and the resulting institutional level responses, such as a curriculum reforms are discussed, focusing especially in engineering programs. The paper is motivated by management need to establish objective steering-related performance indicators and to apply them consistently across all educational programs. The close relationship to governmental steering and funding model imply that internally derived indicators can be directly applied. Metropolia University of Applied Sciences (MUAS) as a case institution is briefly introduced, focusing on engineering education in Information and Communications Technology (ICT), and its related programs. The reform forced consolidation of previously separate smaller programs into fewer units of student application. New curriculum ICT students have a common first year before they apply for a Major. A framework of parallel and longitudinal comparisons is introduced and used across Majors in two campuses. The new externally introduced performance criteria are applied internally on ICT Majors using data ex-ante and ex-post of program merger.  A comparative performance of the Majors after completion of joint first year is established, focusing on previously omitted Majors for completeness of analysis. Some new research questions resulting from transfer of Majors between campuses and quota setting are discussed. Practical orientation identifies best practices to share or targets needing most attention for improvement. This level of analysis is directly applicable at student group and teaching team level, where corrective actions are possible, when identified. The analysis is quantitative and the nature of the corrective actions are not discussed. Causal relationships and factor analysis are omitted, because campuses, their staff and various pedagogical implementation details contain still too many undetermined factors for our limited data. Such qualitative analysis is left for further research. Further study must, however, be guided by the relevance of the observations.

Keywords: Engineering education, integrated curriculum, learning outcomes, performance measurement.

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Authors: T. Chaiechi, N. Stoeckl

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Scarcity of resources for biodiversity conservation gives rise to the need of strategic investment with priorities given to the cost of conservation. While the literature provides abundant methodological options for biodiversity conservation; estimating true cost of conservation remains abstract and simplistic, without recognising dynamic nature of the cost. Some recent works demonstrate the prominence of economic theory to inform biodiversity decisions, particularly on the costs and benefits of biodiversity however, the integration of the concept of true cost into biodiversity actions and planning are very slow to come by, and specially on a farm level. Conservation planning studies often use area as a proxy for costs neglecting different land values as well as protected areas. These literature consider only heterogeneous benefits while land costs are considered homogenous. Analysis with the assumption of cost homogeneity results in biased estimation; since not only it doesn’t address the true total cost of biodiversity actions and plans, but also it fails to screen out lands that are more (or less) expensive and/or difficult (or more suitable) for biodiversity conservation purposes, hindering validity and comparability of the results. Economies of scope” is one of the other most neglected aspects in conservation literature. The concept of economies of scope introduces the existence of cost complementarities within a multiple output production system and it suggests a lower cost during the concurrent production of multiple outputs by a given farm. If there are, indeed, economies of scope then simplistic representation of costs will tend to overestimate the true cost of conservation leading to suboptimal outcomes. The aim of this paper, therefore, is to provide first road review of the various theoretical ways in which economies of scope are likely to occur of how they might occur in conservation. Consequently, the paper addresses gaps that have to be filled in future analysis.

Keywords: Cost, biodiversity conservation, Multi-output production systems, Empirical techniques.

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Authors: Amjad Alsulami, Farah Albishri, Kholod Alzubidi, Lama Almehemadi, Salma Elhag

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Food allergy is a common and rising problem among children. Many students have their first allergic reaction at school, one of these is anaphylaxis, which can be fatal. This study discovered that several schools' processes lacked safety regulations and information on how to handle allergy issues and chronic diseases like diabetes where students were not supervised or monitored during the cafeteria purchasing process. Academic institutions have no obvious prevention or effort when purchasing food containing allergens or negatively impacting the health status of students who suffer from chronic diseases. The stability of students' health must be maintained because it greatly affects their performance and educational achievement. To address this issue, this paper uses a business reengineering process to propose the automation of the whole food-purchasing process, which will aid in detecting and avoiding allergic occurrences and preventing any side effects from eating foods that are conflicting with students' health. This may be achieved by designing a smart card with an embedded QR code that reveals which foods cause an allergic reaction in a student. A survey was distributed to determine and examine how the cafeteria will handle allergic children and whether any management or policy is applied in the school. Also, the survey findings indicate that the integration of QR technology into the food purchasing process would improve health condition detection. The family supported that the suggested solution would be advantageous because it ensured their children avoided eating not allowed food. Moreover, by analyzing and simulating the as-is process and the suggested process, the results demonstrate that there is an improvement in quality and time.

Keywords: QR code, smart card, food allergies, Business Process reengineering, health condition detection.

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