Search results for: Network services.

Authors: Wernhuar Tarng, Weichian Tsai

Abstract:

The major purpose of this study is to use network and multimedia technologies to build a game-based learning system for junior high school students to apply in learning “World Geography" through the “role-playing" game approaches. This study first investigated the motivation and habits of junior high school students to use the Internet and online games, and then designed a game-based learning system according to situated and game-based learning theories. A teaching experiment was conducted to analyze the learning effectiveness of students on the game-based learning system and the major factors affecting their learning. A questionnaire survey was used to understand the students- attitudes towards game-based learning. The results showed that the game-based learning system can enhance students- learning, but the gender of students and their habits in using the Internet have no significant impact on learning. Game experience has a significant impact on students- learning, and the higher the experience value the better the effectiveness of their learning. The results of questionnaire survey also revealed that the system can increase students- motivation and interest in learning "World Geography".

Keywords: Game-based learning, situated learning, role playing, learning effectiveness, learning motivation.

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Authors: Shao Bo Cheng, Yong-Jin Han, Se Young Park, Seong-Bae Park

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Consumer-to-Consumer (C2C) E-commerce has been growing at a very high speed in recent years. Since identical or nearly-same kinds of products compete one another by relying on keyword search in C2C E-commerce, some sellers describe their products with spam keywords that are popular but are not related to their products. Though such products get more chances to be retrieved and selected by consumers than those without spam keywords, the spam keywords mislead the consumers and waste their time. This problem has been reported in many commercial services like ebay and taobao, but there have been little research to solve this problem. As a solution to this problem, this paper proposes a method to classify whether keywords of a product are spam or not. The proposed method assumes that a keyword for a given product is more reliable if the keyword is observed commonly in specifications of products which are the same or the same kind as the given product. This is because that a hierarchical category of a product in general determined precisely by a seller of the product and so is the specification of the product. Since higher layers of the hierarchical category represent more general kinds of products, a reliable degree is differently determined according to the layers. Hence, reliable degrees from different layers of a hierarchical category become features for keywords and they are used together with features only from specifications for classification of the keywords. Support Vector Machines are adopted as a basic classifier using the features, since it is powerful, and widely used in many classification tasks. In the experiments, the proposed method is evaluated with a golden standard dataset from Yi-han-wang, a Chinese C2C E-commerce, and is compared with a baseline method that does not consider the hierarchical category. The experimental results show that the proposed method outperforms the baseline in F1-measure, which proves that spam keywords are effectively identified by a hierarchical category in C2C E-commerce.

Keywords: Spam Keyword, E-commerce, keyword features, spam filtering.

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Authors: Shahab Kavehkar, Mohammad Ali Ghorbani, Valeriy Khokhlov, Afshin Ashrafzadeh, Sabereh Darbandi

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Water level forecasting using records of past time series is of importance in water resources engineering and management. For example, water level affects groundwater tables in low-lying coastal areas, as well as hydrological regimes of some coastal rivers. Then, a reliable prediction of sea-level variations is required in coastal engineering and hydrologic studies. During the past two decades, the approaches based on the Genetic Programming (GP) and Artificial Neural Networks (ANN) were developed. In the present study, the GP is used to forecast daily water level variations for a set of time intervals using observed water levels. The measurements from a single tide gauge at Urmia Lake, Northwest Iran, were used to train and validate the GP approach for the period from January 1997 to July 2008. Statistics, the root mean square error and correlation coefficient, are used to verify model by comparing with a corresponding outputs from Artificial Neural Network model. The results show that both these artificial intelligence methodologies are satisfactory and can be considered as alternatives to the conventional harmonic analysis.

Keywords: Water-Level variation, forecasting, artificial neural networks, genetic programming, comparative analysis.

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Authors: Meet Shah, Ankita Aditya, Dhruv Bindra, V. S. Omkar, Aashruti Seervi

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In today's world, we need documents everywhere for a smooth workflow in the identification process or any other security aspects. The current system and techniques which are used for identification need one thing, that is ‘proof of existence’, which involves valid documents, for example, educational, financial, etc. The main issue with the current identity access management system and digital identification process is that the system is centralized in their network, which makes it inefficient. The paper presents the system which resolves all these cited issues. It is based on ‘blockchain’ technology, which is a 'decentralized system'. It allows transactions in a decentralized and immutable manner. The primary notion of the model is to ‘have everything with nothing’. It involves inter-linking required documents of a person with a single identity card so that a person can go anywhere without having the required documents with him/her. The person just needs to be physically present at a place wherein documents are necessary, and using a fingerprint impression and an iris scan print, the rest of the verification will progress. Furthermore, some technical overheads and advancements are listed. This paper also aims to layout its far-vision scenario of blockchain and its impact on future trends.

Keywords: Blockchain, decentralized system, fingerprint impression, identity management, iris scan.

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Authors: Amin Aghatabar Roodbary, Mohammad Hassan Bastani

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One of the defects of stepped frequency radar systems is their sensitivity to target motion. In such systems, target motion causes range cell shift, false peaks, Signal to Noise Ratio (SNR) reduction and range profile spreading because of power spectrum interference of each range cell in adjacent range cells which induces distortion in High Resolution Range Profile (HRRP) and disrupt target recognition process. Thus Target Motion Parameters (TMPs) effects compensation should be employed. In this paper, such a method for estimating TMPs (velocity and acceleration) and consequently eliminating or suppressing the unwanted effects on HRRP based on entropy minimization has been proposed. This method is carried out in two major steps: in the first step, a discrete search method has been utilized over the whole acceleration-velocity lattice network, in a specific interval seeking to find a less-accurate minimum point of the entropy function. Then in the second step, a 1-D search over velocity is done in locus of the minimum for several constant acceleration lines, in order to enhance the accuracy of the minimum point found in the first step. The provided simulation results demonstrate the effectiveness of the proposed method.

Keywords: ATR, HRRP, motion compensation, SFW, TMP.

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Authors: Benazeer Md. Shahzada, Verelst Jan, Van Grembergen Wim, Mannaert Herwig

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This article is an extension and a practical application approach of Wheeler-s NEBIC theory (Net Enabled Business Innovation Cycle). NEBIC theory is a new approach in IS research and can be used for dynamic environment related to new technology. Firms can follow the market changes rapidly with support of the IT resources. Flexible firms adapt their market strategies, and respond more quickly to customers changing behaviors. When every leading firm in an industry has access to the same IT resources, the way that these IT resources are managed will determine the competitive advantages or disadvantages of firm. From Dynamic Capabilities Perspective and from newly introduced NEBIC theory by Wheeler, we know that only IT resources cannot deliver customer value but good configuration of those resources can guarantee customer value by choosing the right emerging technology, grasping the economic opportunities through business innovation and growth. We found evidences in literature that SOA (Service Oriented Architecture) is a promising emerging technology which can deliver the desired economic opportunity through modularity, flexibility and loosecoupling. SOA can also help firms to connect in network which can open a new window of opportunity to collaborate in innovation and right kind of outsourcing

Keywords: Absorptive capacity, Dynamic Capability, Netenabled business innovation cycle, Service oriented architecture.

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Authors: Neeraj Nehra, R. B. Patel, V. K. Bhat

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Use of the Internet and the World-Wide-Web (WWW) has become widespread in recent years and mobile agent technology has proliferated at an equally rapid rate. In this scenario load balancing becomes important for P2P systems. Beside P2P systems can be highly heterogeneous, i.e., they may consists of peers that range from old desktops to powerful servers connected to internet through high-bandwidth lines. There are various loads balancing policies came into picture. Primitive one is Message Passing Interface (MPI). Its wide availability and portability make it an attractive choice; however the communication requirements are sometimes inefficient when implementing the primitives provided by MPI. In this scenario we use the concept of mobile agent because Mobile agent (MA) based approach have the merits of high flexibility, efficiency, low network traffic, less communication latency as well as highly asynchronous. In this study we present decentralized load balancing scheme using mobile agent technology in which when a node is overloaded, task migrates to less utilized nodes so as to share the workload. However, the decision of which nodes receive migrating task is made in real-time by defining certain load balancing policies. These policies are executed on PMADE (A Platform for Mobile Agent Distribution and Execution) in decentralized manner using JuxtaNet and various load balancing metrics are discussed.

Keywords: Mobile Agents, Agent host, Agent Submitter, PMADE.

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Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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Authors: Emelia Noronha, Milind Malshe

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The phatic function of communication is a vital element of any conversation. This research paper looks into this function with respect to personal blogs maintained by Indian bloggers. This paper is a study into the phenomenon of phatic communication maintained by bloggers through their blogs. Based on a linguistic analysis of the posts of twenty eight Indian bloggers, writing in English, studied over a period of three years, the study indicates that though the blogging phenomenon is not conversational in the same manner as face-to-face communication, it does make ample provision for feedback that is conversational in nature. Ordinary day to day offline conversations use conventionalized phatic utterances; those on the social media are in a perpetual mode of innovation and experimentation in order to sustain contact with its readers. These innovative methods and means are the focus of this study. Though the personal blogger aims to chronicle his/her personal life through the blog, the socializing function is crucial to these bloggers. In comparison to the western personal blogs which focus on the presentation of the ‘bounded individual self’, we find Indian personal bloggers engage in the presentation of their ‘social selves’. These bloggers yearn to reach out to the readers on the internet and the phatic function serves to initiate, sustain and renew social ties on the blogosphere thereby consolidating the social network of readers and bloggers.

Keywords: Personal blogs, phatic, social-selves, blog readers.

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Authors: Oluseye A. Adeleke, Mohd. F. M. Salleh

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The performance of any cooperative communication system depends largely on the selection of a proper partner. Another important factor to consider is an efficient allocation of resource like power by the source node to help it in forwarding information to the destination. In this paper, we look at the concepts of partner selection and resource (power) allocation for a distributed communication network. A type of non-cooperative game referred to as Trade-Off game is employed so as to jointly consider the utilities of the source and relay nodes, where in this case, the source is the node that requires help with forwarding of its information while the partner is the node that is willing to help in forwarding the source node’s information, but at a price. The approach enables the source node to maximize its utility by selecting a partner node based on (i) the proximity of the partner node to the source and destination nodes, and (ii) the price the partner node will charge for the help being rendered. Our proposed scheme helps the source locate and select the relay nodes at ‘better’ locations and purchase power optimally from them. It also aids the contending relay nodes maximize their own utilities as well by asking proper prices. Our game scheme is seen to converge to unique equilibrium.

Keywords: Cooperative communication, game theory, node, power allocation, trade-off, utility.

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Authors: C. Sathiyakumar, K. Duraiswamy

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In MANET, mobile nodes communicate with each other using the wireless channel where transmission takes place with significant interference. The wireless medium used in MANET is a shared resource used by all the nodes available in MANET. Packet reserving is one important resource management scheme which controls the allocation of bandwidth among multiple flows through node cooperation in MANET. This paper proposes packet reserving and clogging control via Routing Aware Packet Reserving (RAPR) framework in MANET. It mainly focuses the end-to-end routing condition with maximal throughput. RAPR is complimentary system where the packet reserving utilizes local routing information available in each node. Path setup in RAPR estimates the security level of the system, and symbolizes the end-to-end routing by controlling the clogging. RAPR reaches the packet to the destination with high probability ratio and minimal delay count. The standard performance measures such as network security level, communication overhead, end-to-end throughput, resource utilization efficiency and delay measure are considered in this work. The results reveals that the proposed packet reservation and clogging control via Routing Aware Packet Reserving (RAPR) framework performs well for the above said performance measures compare to the existing methods.

Keywords: Packet reserving, Clogging control, Packet reservation in MANET, RAPR.

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Authors: Susmita Das, Kala Praveen Bagadi

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SDMA (Space-Division Multiple Access) is a MIMO (Multiple-Input and Multiple-Output) based wireless communication network architecture which has the potential to significantly increase the spectral efficiency and the system performance. The maximum likelihood (ML) detection provides the optimal performance, but its complexity increases exponentially with the constellation size of modulation and number of users. The QR decomposition (QRD) MUD can be a substitute to ML detection due its low complexity and near optimal performance. The minimum mean-squared-error (MMSE) multiuser detection (MUD) minimises the mean square error (MSE), which may not give guarantee that the BER of the system is also minimum. But the minimum bit error rate (MBER) MUD performs better than the classic MMSE MUD in term of minimum probability of error by directly minimising the BER cost function. Also the MBER MUD is able to support more users than the number of receiving antennas, whereas the rest of MUDs fail in this scenario. In this paper the performance of various MUD techniques is verified for the correlated MIMO channel models based on IEEE 802.16n standard.

Keywords: Multiple input multiple output, multiuser detection, orthogonal frequency division multiplexing, space division multiple access, Bit error rate

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Authors: Cornelia-Eugenia Munteanu

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From a psychological perspective, psychopathology is the area of clinical psychology that has at its core psychological assessment and psychotherapy. In day-to-day clinical practice, psychodiagnosis and psychotherapy are used independently, according to their intended purpose and their specific methods of application. The paper explores how the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) and Mini Mental State Examination-2 (MMSE-2) psychological tools contribute to enhancing the effectiveness of cognitive behavioral psychotherapy (CBT). This combined approach, psychotherapy in conjunction with assessment of personality and cognitive functions, is illustrated by two cases, a severe depressive episode with psychotic symptoms and a mixed anxiety-depressive disorder. The order in which CBT, MMPI-2, and MMSE-2 were used in the diagnostic and therapeutic process was determined by the particularities of each case. In the first case, the sequence started with psychotherapy, followed by the administration of blue form MMSE-2, MMPI-2, and red form MMSE-2. In the second case, the cognitive screening with blue form MMSE-2 led to a personality assessment using MMPI-2, followed by red form MMSE-2; reapplication of the MMPI-2 due to the invalidation of the first profile, and finally, psychotherapy. The MMPI-2 protocols gathered useful information that directed the steps of therapeutic intervention: a detailed symptom picture of potentially self-destructive thoughts and behaviors otherwise undetected during the interview. The memory loss and poor concentration were confirmed by MMSE-2 cognitive screening. This combined approach, psychotherapy with psychological assessment, aligns with the trend of adaptation of the psychological services to the everyday life of contemporary man and paves the way for deepening and developing the field.

Keywords: Assessment, cognitive behavioral psychotherapy, MMPI-2, MMSE-2, psychopathology.

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Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

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To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: Building energy prediction, data mining, demand response, electricity market.

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Authors: Khaled Elbehiery, Hussam Elbehiery

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The success of education is dependent on evolution and adaptation, while the traditional system has worked before, one type of education evolved with the digital age is virtual education that has influenced efficiency in today’s learning environments. Virtual learning has indeed proved its efficiency to overcome the drawbacks of the physical environment such as time, facilities, location, etc., but despite what it had accomplished, the educational system over all is not adequate for being a productive system yet. Earning a degree is not anymore enough to obtain a career job; it is simply missing the skills and creativity. There are always two sides of a coin; a college degree or a specialized certificate, each has its own merits, but having both can put you on a successful IT career path. For many of job-seeking individuals across world to have a clear meaningful goal for work and education and positively contribute the community, a productive correlation and cooperation among employers, universities alongside with the individual technical skills is a must for generations to come. Fortunately, the proposed research “Entrepreneur Universal Education System” is an evolution to meet the needs of both employers and students, in addition to gaining vital and real-world experience in the chosen fields is easier than ever. The new vision is to empower the education to improve organizations’ needs which means improving the world as its primary goal, adopting universal skills of effective thinking, effective action, effective relationships, preparing the students through real-world accomplishment and encouraging them to better serve their organization and their communities faster and more efficiently.

Keywords: Virtual education, academic degree, certificates, internship, amazon web services, Microsoft Azure, Google cloud platform, hybrid models.

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Authors: Ahmed Ebian, Mona Shokair, Kamal Awadalla

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Mobile WiMAX is a broadband wireless solution that enables convergence of mobile and fixed broadband networks through a common wide area broadband radio access technology and flexible network architecture. It adopts Orthogonal Frequency Division Multiple Access (OFDMA) for improved multi-path performance in Non-Line-Of-Sight (NLOS) environments. Scalable OFDMA (SOFDMA) is introduced in the IEEE 802e[1]. WIMAX system uses one of different types of channel coding but The mandatory channel coding scheme is based on binary nonrecursive Convolutional Coding (CC). There are other several optional channel coding schemes such as block turbo codes, convolutional turbo codes, and low density parity check (LDPC). In this paper a comparison between the performance of WIMAX using turbo code and using convolutional product code (CPC) [2] is made. Also a combination between them had been done. The CPC gives good results at different SNR values compared to both the turbo system, and the combination between them. For example, at BER equal to 10-2 for 128 subcarriers, the amount of improvement in SNR equals approximately 3 dB higher than turbo code and equals approximately 2dB higher than the combination respectively. Several results are obtained at different modulating schemes (16QAM and 64QAM) and different numbers of sub-carriers (128 and 512).

Keywords: Turbo Code, Convolutional Product Code (CPC), Convolutional Product Code (CPC).

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Authors: Andreas Theissler, Ian Dear

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In the automotive industry test drives are being conducted during the development of new vehicle models or as a part of quality assurance of series-production vehicles. The communication on the in-vehicle network, data from external sensors, or internal data from the electronic control units is recorded by automotive data loggers during the test drives. The recordings are used for fault analysis. Since the resulting data volume is tremendous, manually analysing each recording in great detail is not feasible. This paper proposes to use machine learning to support domainexperts by preventing them from contemplating irrelevant data and rather pointing them to the relevant parts in the recordings. The underlying idea is to learn the normal behaviour from available recordings, i.e. a training set, and then to autonomously detect unexpected deviations and report them as anomalies. The one-class support vector machine “support vector data description” is utilised to calculate distances of feature vectors. SVDDSUBSEQ is proposed as a novel approach, allowing to classify subsequences in multivariate time series data. The approach allows to detect unexpected faults without modelling effort as is shown with experimental results on recordings from test drives.

Keywords: Anomaly detection, fault detection, test drive analysis, machine learning.

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Authors: Bassma Aldahlan, Zongming Fei

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Recently, there is a great interest in smart parking application. Theses applications are enhanced by a vehicular ad-hoc network, which helps drivers find and reserve satiable packing spaces for a period of time ahead of time. Named Data Networking (NDN) is a future Internet architecture that benefits vehicular ad-hoc networks because of its clean-slate design and pure communication model. In this paper, we proposed an NDN-based frame-work for smart parking that involved a fog computing architecture. The proposed application had two main directions: First, we allowed drivers to query the number of parking spaces in a particular parking lot. Second, we introduced a technique that enabled drivers to make intelligent reservations before their arrival time. We also introduced a “push-based” model supporting the NDN-based framework for smart parking applications. To evaluate the proposed solution’s performance, we analyzed the function for finding parking lots with available parking spaces and the function for reserving a parking space. Our system showed high performance results in terms of response time and push overhead. The proposed reservation application performed better than the baseline approach.

Keywords: Cloud Computing, Vehicular Named Data Networking, Smart Parking Applications, Fog Computing.

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Authors: Shih-Hsu Wang, Yuan-Yuan Cheng, Ming-Tsung Lee, Wei-Chih Wang

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Determining reasonable fees is the main objective of designing the cost estimation and payment systems for consultant contracts. However, project clients utilize different cost estimation and payment systems because of their varying views on the reasonableness of consultant fees. This study reviews the cost estimation and payment systems of consultant contracts for five countries, including the US (Washington State Department of Transportation), Japan (Ministry of Land, Infrastructure, Transport and Tourism), China (Engineering Design Charging Standard) and UK (Her Majesty's Treasure). Specifically, this work investigates the budgeting process, contractor selection method, contractual price negotiation process, cost review, and cost-control concept of the systems used in these countries. The main finding indicates that that project client-s view on whether the fee is high will affect the way he controls it. In the US, the fee is commonly considered to be high. As a result, stringent auditing system (low flexibility given to the consultant) is then applied. In the UK, the fee is viewed to be low by comparing it to the total life-cycle project cost. Thus, a system that has high flexibility in budgeting and cost reviewing is given to the consultant. In terms of the flexibility allowed for the consultant, the systems applied in Japan and China fall between those of the US and UK. Both the US and UK systems are helpful in determining a reasonable fee. However, in the US system, rigid auditing standards must be established and additional cost-audit manpower is required. In the UK system, sufficient historical cost data should be needed to evaluate the reasonableness of the consultant-s proposed fee

Keywords: Consultant Services, Cost Estimation and Payment System, Payment Flexibility, Cost-control Concept

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Authors: Sheena Christabel Pravin, M. Palanivelan

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Speech disfluencies are common in spontaneous speech. The primary purpose of this study was to distinguish linguistic disfluencies from stuttering disfluencies in bilingual Tamil–English (TE) speaking children. The secondary purpose was to determine whether their disfluencies are mediated by native language dominance and/or on an early onset of developmental stuttering at childhood. A detailed study was carried out to identify the prosodic and acoustic features that uniquely represent the disfluent regions of speech. This paper focuses on statistical modeling of repetitions, prolongations, pauses and interjections in the speech corpus encompassing bilingual spontaneous utterances from school going children – English and Tamil. Two classifiers including Hidden Markov Models (HMM) and the Multilayer Perceptron (MLP), which is a class of feed-forward artificial neural network, were compared in the classification of disfluencies. The results of the classifiers document the patterns of disfluency in spontaneous speech samples of school-aged children to distinguish between Children Who Stutter (CWS) and Children with Language Impairment CLI). The ability of the models in classifying the disfluencies was measured in terms of F-measure, Recall, and Precision.

Keywords: Bilingual, children who stutter, children with language impairment, Hidden Markov Models, multi-layer perceptron, linguistic disfluencies, stuttering disfluencies.

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Authors: Om Prakash Verma, Rajesh Singla, Rajesh Kumar

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Conventional controller’s usually required a prior knowledge of mathematical modelling of the process. The inaccuracy of mathematical modelling degrades the performance of the process, especially for non-linear and complex control problem. The process used is Water-Bath system, which is most widely used and nonlinear to some extent. For Water-Bath system, it is necessary to attain desired temperature within a specified period of time to avoid the overshoot and absolute error, with better temperature tracking capability, else the process is disturbed.

To overcome above difficulties intelligent controllers, Fuzzy Logic (FL) and Adaptive Neuro-Fuzzy Inference System (ANFIS), are proposed in this paper. The Fuzzy controller is designed to work with knowledge in the form of linguistic control rules. But the translation of these linguistic rules into the framework of fuzzy set theory depends on the choice of certain parameters, for which no formal method is known. To design ANFIS, Fuzzy-Inference-System is combined with learning capability of Neural-Network.

It is analyzed that ANFIS is best suitable for adaptive temperature control of above system. As compared to PID and FLC, ANFIS produces a stable control signal. It has much better temperature tracking capability with almost zero overshoot and minimum absolute error.

Keywords: PID Controller, FLC, ANFIS, Non-Linear Control System, Water-Bath System, MATLAB-7.

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Authors: Valmir Baloshi, Fran Gjoka, Nehat Çollaku, Elvin Toromani

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As a sediment production mechanism, soil erosion is the main environmental threat to the Bovilla watershed, including the decline of water quality of the Bovilla reservoir that provides drinking water to Tirana city (the capital of Albania). Therefore, an experiment with 25 erosion plots for soil erosion monitoring has been set up since June 2017. The aim was to determine the soil loss on plot and watershed scale in Bovilla watershed (Tirana region) for implementation of soil and water protection measures or payments for ecosystem services (PES) programs. The results of erosion monitoring for the period June 2017 - May 2018 showed that the highest values of surface runoff were noted in bare land of 38829.91 liters on slope of 74% and the lowest values in forest land of 12840.6 liters on slope of 64% while the highest values of soil loss were found in bare land of 595.15 t/ha on slope of 62% and lowest values in forest land of 18.99 t/ha on slope of 64%. These values are much higher than the average rate of soil loss in the European Union (2.46 ton/ha/year). In the same sloping class, the soil loss was reduced from orchard or bare land to the forest land, and in the same category of land use, the soil loss increased with increasing land slope. It is necessary to conduct chemical analyses of sediments to determine the amount of chemical elements leached out of the soil and end up in the reservoir of Bovilla. It is concluded that PES programs should be implemented for rehabilitation of sub-watersheds Ranxe, Vilez and Zall-Bastar of the Bovilla watershed with valuable conservation practices.

Keywords: ANOVA, Bovilla, land cover, slope, soil loss, watershed management.

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Authors: Mohammad T. Uddin, Aurup R. Dhar

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The study was conducted to assess the impact of conservation agriculture practice on farmers’ socioeconomic condition and soil environmental quality in Bangladesh. A total of 450 (i.e., 50 focal, 150 proximal and 250 control) farmers from five districts were selected for this study. Descriptive statistics like sum, averages, percentages, etc. were calculated to evaluate the socioeconomic data. Using Enyedi’s crop productivity index, it was found that the crop productivity of focal, proximal and control farmers was increased by 0.9, 1.2 and 1.3 percent, respectively. The result of DID (Difference-in-difference) analysis indicated that the impact of conservation agriculture practice on farmers’ average annual income was significant. Multidimensional poverty index (MPI) indicates that poverty in terms of deprivation of health, education and living standards was decreased; and a remarkable improvement in farmers’ socioeconomic status was found after adopting conservation agriculture practice. Most of the focal and proximal farmers stated about increased soil environmental condition where majority of control farmers stated about constant environmental condition in this regard. The Probit model reveals that minimum tillage operation, permanent organic soil cover, and application of compost and vermicompost were found significant factors affecting soil environmental quality under conservation agriculture. Input support, motivation, training programmes and extension services are recommended to implement in order to raise the awareness and enrich the knowledge of the farmers on conservation agriculture practice.

Keywords: Conservation agriculture, crop productivity, socioeconomic status, soil environment quality.

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Authors: H. Iranmanesh, M. R. Skandari, M. Allahverdiloo

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Project managers are the ultimate responsible for the overall characteristics of a project, i.e. they should deliver the project on time with minimum cost and with maximum quality. It is vital for any manager to decide a trade-off between these conflicting objectives and they will be benefited of any scientific decision support tool. Our work will try to determine optimal solutions (rather than a single optimal solution) from which the project manager will select his desirable choice to run the project. In this paper, the problem in project scheduling notated as (1,T|cpm,disc,mu|curve:quality,time,cost) will be studied. The problem is multi-objective and the purpose is finding the Pareto optimal front of time, cost and quality of a project (curve:quality,time,cost), whose activities belong to a start to finish activity relationship network (cpm) and they can be done in different possible modes (mu) which are non-continuous or discrete (disc), and each mode has a different cost, time and quality . The project is constrained to a non-renewable resource i.e. money (1,T). Because the problem is NP-Hard, to solve the problem, a meta-heuristic is developed based on a version of genetic algorithm specially adapted to solve multi-objective problems namely FastPGA. A sample project with 30 activities is generated and then solved by the proposed method.

Keywords: FastPGA, Multi-Execution Activity Mode, ParetoOptimality, Project Scheduling, Time-Cost-Quality Trade-Off.

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Authors: Priyanka Paliwal, N.P. Patidar

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Distributed Power generation has gained a lot of attention in recent times due to constraints associated with conventional power generation and new advancements in DG technologies .The need to operate the power system economically and with optimum levels of reliability has further led to an increase in interest in Distributed Generation. However it is important to place Distributed Generator on an optimum location so that the purpose of loss minimization and voltage regulation is dully served on the feeder. This paper investigates the impact of DG units installation on electric losses, reliability and voltage profile of distribution networks. In this paper, our aim would be to find optimal distributed generation allocation for loss reduction subjected to constraint of voltage regulation in distribution network. The system is further analyzed for increased levels of Reliability. Distributed Generator offers the additional advantage of increase in reliability levels as suggested by the improvements in various reliability indices such as SAIDI, CAIDI and AENS. Comparative studies are performed and related results are addressed. An analytical technique is used in order to find the optimal location of Distributed Generator. The suggested technique is programmed under MATLAB software. The results clearly indicate that DG can reduce the electrical line loss while simultaneously improving the reliability of the system.

Keywords: AENS, CAIDI, Distributed Generation, lossreduction, Reliability, SAIDI

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Authors: G. T. Balakayeva, K. K. Nurlybayeva, M. B. Zhanuzakov

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In the proposed work, we have developed software and designed a software architecture for the implementation of enterprise business processes. The proposed software has a multi-level architecture using a domain-specific tool. The developed architecture is a guarantor of the availability, reliability and security of the system and the implementation of business processes, which are the basis for effective enterprise management. Automating business processes, automating the algorithmic stages of an enterprise, developing optimal algorithms for managing activities, controlling and monitoring, reducing risks and improving results help organizations achieve strategic goals quickly and efficiently. The software described in this article can connect to the corporate information system via two methods: a desktop client and a web client. With an appeal to the application server, the desktop client program connects to the information system on the company's work PCs over a local network. Outside the organization, the user can interact with the information system via a web browser, which acts as a web client and connects to a web server. The developed software consists of several integrated modules that share resources and interact with each other through an API. The following technology stack was used during development: Node js, React js, MongoDB, Ngnix, Cloud Technologies, Python.

Keywords: Algorithms, document processing, automation, integrated modules, software architecture, software design, information system.

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Authors: Mohd Noah A. Rahman, Afzaal H. Seyal, Sharul T. Tajuddin, Hartiny Md Azmi

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Taking into consideration the real time situation specifically the higher academic institutions, small, medium to large companies, public to private sectors and the remaining sectors, do experience the inventory or asset shrinkages due to theft, loss or even inventory tracking errors. This happening is due to a zero or poor security systems and measures being taken and implemented in their organizations. Henceforth, implementing the Radio Frequency Identification (RFID) technology into any manual or existing web-based system or web application can simply deter and will eventually solve certain major issues to serve better data retrieval and data access. Having said, this manual or existing system can be enhanced into a mobile-based system or application. In addition to that, the availability of internet connections can aid better services of the system. Such involvement of various technologies resulting various privileges to individuals or organizations in terms of accessibility, availability, mobility, efficiency, effectiveness, real-time information and also security. This paper will look deeper into the integration of mobile devices with RFID technologies with the purpose of asset tracking and control. Next, it is to be followed by the development and utilization of MongoDB as the main database to store data and its association with RFID technology. Finally, the development of a web based system which can be viewed in a mobile based formation with the aid of Hypertext Preprocessor (PHP), MongoDB, Hyper-Text Markup Language 5 (HTML5), Android, JavaScript and AJAX programming language.

Keywords: RFID, asset tracking system, MongoDB, NoSQL.

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Authors: Shaukat Wasi, Zubair A. Shaikh, Sajid Qasmi, Hussain Sachwani, Rehman Lalani, Aamir Chagani

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Automatic Extraction of Event information from social text stream (emails, social network sites, blogs etc) is a vital requirement for many applications like Event Planning and Management systems and security applications. The key information components needed from Event related text are Event title, location, participants, date and time. Emails have very unique distinctions over other social text streams from the perspective of layout and format and conversation style and are the most commonly used communication channel for broadcasting and planning events. Therefore we have chosen emails as our dataset. In our work, we have employed two statistical NLP methods, named as Finite State Machines (FSM) and Hidden Markov Model (HMM) for the extraction of event related contextual information. An application has been developed providing a comparison among the two methods over the event extraction task. It comprises of two modules, one for each method, and works for both bulk as well as direct user input. The results are evaluated using Precision, Recall and F-Score. Experiments show that both methods produce high performance and accuracy, however HMM was good enough over Title extraction and FSM proved to be better for Venue, Date, and time.

Keywords: Emails, Event Extraction, Event Detection, Finite state machines, Hidden Markov Model.

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Authors: Erika Ann Schaub, Christian J Darken

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Sociological models (e.g., social network analysis, small-group dynamic and gang models) have historically been used to predict the behavior of terrorist groups. However, they may not be the most appropriate method for understanding the behavior of terrorist organizations because the models were not initially intended to incorporate violent behavior of its subjects. Rather, models that incorporate life and death competition between subjects, i.e., models utilized by scientists to examine the behavior of wildlife populations, may provide a more accurate analysis. This paper suggests the use of biological models to attain a more robust method for understanding the behavior of terrorist organizations as compared to traditional methods. This study also describes how a biological population model incorporating predator-prey behavior factors can predict terrorist organizational recruitment behavior for the purpose of understanding the factors that govern the growth and decline of terrorist organizations. The Lotka-Volterra, a biological model that is based on a predator-prey relationship, is applied to a highly suggestive case study, that of the Irish Republican Army. This case study illuminates how a biological model can be utilized to understand the actions of a terrorist organization.

Keywords: Biological Models, Lotka-Volterra Predator-Prey Model, Terrorist Organizational Behavior, Terrorist Recruitment.

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Authors: Jessica Lòpez Espejel, Mahaman Sanoussi Yahaya Alassan, Walid Dahhane, El Hassane Ettifouri

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Pretrained transformer-based models have shown high performance in natural language generation task. However, a new wave of interest has surged: automatic programming language generation. This task consists of translating natural language instructions to a programming code. Despite the fact that well-known pretrained models on language generation have achieved good performance in learning programming languages, effort is still needed in automatic code generation. In this paper, we introduce JaCoText, a model based on Transformers neural network. It aims to generate java source code from natural language text. JaCoText leverages advantages of both natural language and code generation models. More specifically, we study some findings from the state of the art and use them to (1) initialize our model from powerful pretrained models, (2) explore additional pretraining on our java dataset, (3) carry out experiments combining the unimodal and bimodal data in the training, and (4) scale the input and output length during the fine-tuning of the model. Conducted experiments on CONCODE dataset show that JaCoText achieves new state-of-the-art results.

Keywords: Java code generation, Natural Language Processing, Sequence-to-sequence Models, Transformers Neural Networks.

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