Search results for: methods of information culture of students

Authors: Jinhwan Yu, Jooyeon Yook

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After Apple's first introduction its smart phone, iPhone in the end of 2009 in Korea, the number of Korean smarphone users had been rapidly increasing so that the half of Korean population became smart phone users as of February, 2012. Currently, smart phones are positioned as a major digital media with powerful influences in Korea. And, now, Koreans are leaning new information, enjoying games and communicating other people every time and everywhere. As smart phone devices' performances increased, the number of usable services became more while adequate GUI developments are required to implement various functions with smart phones. The strategy to provide similar experiences on smart phones through familiar features based on employment of existing media's functions mostly contributed to smart phones' popularization in connection with smart phone devices' iconic GUIs. The spread of Smart phone increased mobile web accesses. Therefore, the attempts to implement PC's web in the smart phone's web are continuously made. The mobile web GUI provides familiar experiences to users through designs adequately utilizing the smart phone's GUIs. As the number of users familiarized to smart phones and mobile web GUIs, opposite to reversed remediation from many parts of PCs, PCs are starting to adapt smart phone GUIs. This study defines this phenomenon as the reversed remediation, and reviews the reversed remediation cases of Smart phone GUI' characteristics of PCs. For this purpose, the established study issues are as under: · what is the reversed remediation? · what are the smart phone GUI's characteristics? · what kind of interrelationship exist s between the smart phone and PC's web site? It is meaningful in the forecast of the future GUI's change by understanding of characteristics in the paradigm changes of PC and smart phone's GUI designs. This also will be helpful to establish strategies for digital devices' development and design.

Keywords: Graphic User Interface, Remediation, Smart Phone, South Korea, Web Site

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Authors: Selvam M, Natarajan. A M, Thangarajan R

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Parsing is important in Linguistics and Natural Language Processing to understand the syntax and semantics of a natural language grammar. Parsing natural language text is challenging because of the problems like ambiguity and inefficiency. Also the interpretation of natural language text depends on context based techniques. A probabilistic component is essential to resolve ambiguity in both syntax and semantics thereby increasing accuracy and efficiency of the parser. Tamil language has some inherent features which are more challenging. In order to obtain the solutions, lexicalized and statistical approach is to be applied in the parsing with the aid of a language model. Statistical models mainly focus on semantics of the language which are suitable for large vocabulary tasks where as structural methods focus on syntax which models small vocabulary tasks. A statistical language model based on Trigram for Tamil language with medium vocabulary of 5000 words has been built. Though statistical parsing gives better performance through tri-gram probabilities and large vocabulary size, it has some disadvantages like focus on semantics rather than syntax, lack of support in free ordering of words and long term relationship. To overcome the disadvantages a structural component is to be incorporated in statistical language models which leads to the implementation of hybrid language models. This paper has attempted to build phrase structured hybrid language model which resolves above mentioned disadvantages. In the development of hybrid language model, new part of speech tag set for Tamil language has been developed with more than 500 tags which have the wider coverage. A phrase structured Treebank has been developed with 326 Tamil sentences which covers more than 5000 words. A hybrid language model has been trained with the phrase structured Treebank using immediate head parsing technique. Lexicalized and statistical parser which employs this hybrid language model and immediate head parsing technique gives better results than pure grammar and trigram based model.

Keywords: Hybrid Language Model, Immediate Head Parsing, Lexicalized and Statistical Parsing, Natural Language Processing, Parts of Speech, Probabilistic Context Free Grammar, Tamil Language, Tree Bank.

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Authors: May Paing Paing Zaw, Su Myat Marlar Soe

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Network Management Systems have played a great important role in information systems. Management is very important and essential in any fields. There are many managements such as configuration management, fault management, performance management, security management, accounting management and etc. Among them, configuration, fault and security management is more important than others. Because these are essential and useful in any fields. Configuration management is to monitor and maintain the whole system or LAN. Fault management is to detect and troubleshoot the system. Security management is to control the whole system. This paper intends to increase the network management functionalities including configuration management, fault management and security management. In configuration management system, this paper specially can support the USB ports and devices to detect and read devices configuration and solve to detect hardware port and software ports. In security management system, this paper can provide the security feature for the user account setting and user management and proxy server feature. And all of the history of the security such as user account and proxy server history are kept in the java standard serializable file. So the user can view the history of the security and proxy server anytime. If the user uses this system, the user can ping the clients from the network and the user can view the result of the message in fault management system. And this system also provides to check the network card and can show the NIC card setting. This system is used RMI (Remote Method Invocation) and JNI (Java Native Interface) technology. This paper is to implement the client/server network management system using Java 2 Standard Edition (J2SE). This system can provide more than 10 clients. And then this paper intends to show data or message structure of client/server and how to work using TCP/IP protocol.

Keywords: TCP/ IP based client server application

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Authors: F. A. M. Safwan, H. N. N. Dilrukshi, P. U. S. Peiris

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Less availability of high quality green forages leads to low productivity of national dairy herd of Sri Lanka. Growing grass and fodder to suit the production system is an efficient and economical solution for this problem. CO-3 is placed in a higher category, especially on tillering capacity, green forage yield, regeneration capacity, leaf to stem ratio, high crude protein content, resistance to pests and diseases and free from adverse factors along with other fodder varieties grown within the country. An experiment was designed to determine the effect of organic sheep manure, inorganic fertilizers and liquid sheep manure on growth, yield and nutritive value of CO-3. The study was consisted with three treatments; sheep manure (T1), recommended inorganic fertilizers (T2) and liquid sheep manure (T3) which was prepared using bucket fermentation method and each treatment was consisted with three replicates and those were assigned randomly. First harvest was obtained after 40 days of plant establishment and number of leaves (NL), leaf area (LA), tillering capacity (TC), fresh weight (FW) and dry weight (DW) were recorded and second harvest was obtained after 30 days of first harvest and same set of data were recorded. SPSS 16 software was used for data analysis. For proximate analysis AOAC, 2000 standard methods were used. Results revealed that the plants treated with T1 recorded highest NL, LA, TC, FW and DW and were statistically significant at first and second harvest of CO-3 (p˂ 0.05) and it was found that T1 was statistically significant from T2 and T3. Although T3 was recorded higher than the T2 in almost all growth parameters; it was not statistically significant (p ˃0.05). In addition, the crude protein content was recorded highest in T1 with the value of 18.33±1.61 and was lowest in T2 with the value of 10.82±1.14 and was statistically significant (p˂ 0.05). Apart from this, other proximate composition crude fiber, crude fat, ash, moisture content and dry matter were not statistically significant between treatments (p ˃0.05). In accordance with the results, it was found that the organic fertilizer is the best fertilizer for CO-3 in terms of growth parameters and crude protein content.

Keywords: Fertilizer, growth parameters, Hybrid Napier CO-3, proximate composition.

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Authors: Gorazd Karer

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When performing a diagnostic procedure or surgery in general anesthesia (GA), a proper introduction and dosing of anesthetic agents is one of the main tasks of the anesthesiologist. That being said, depth of anesthesia (DoA) also seems to be a suitable process for closed-loop control implementation. To implement such a system, one must be able to acquire the relevant signals online and in real-time, as well as stream the calculated control signal to the infusion pump. However, during a procedure, patient monitors and infusion pumps are purposely unable to connect to an external (possibly medically unapproved) device for safety reasons, thus preventing closed-loop control. This paper proposes a conceptual solution to the aforementioned problem. First, it presents some important aspects of contemporary clinical practice. Next, it introduces the closed-loop-control-system structure and the relevant information flow. Focusing on transferring the data from the patient to the computer, it presents a non-invasive image-based system for signal acquisition from a patient monitor for online depth-of-anesthesia assessment. Furthermore, it introduces a User-Datagram-Protocol-based (UDP-based) communication method that can be used for transmitting the calculated anesthetic inflow to the infusion pump. The proposed system is independent of medical-device manufacturer and is implemented in MATLAB-Simulink, which can be conveniently used for DoA control implementation. The proposed scheme has been tested in a simulated GA setting and is ready to be evaluated in an operating theatre. However, the proposed system is only a step towards a proper closed-loop control system for DoA, which could routinely be used in clinical practice.

Keywords: Closed-loop control, Depth of Anesthesia, DoA, optical signal acquisition, Patient State index, PSi, UDP communication protocol.

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Authors: Ravneet Kaur, Joydeep Acharya, Sudhanshu Gaur

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Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

Keywords: Human machine interface, industrial internet of things, internet of things, optical character recognition, video analytic.

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Authors: A. Kospach, A. Mladek, M. Waltenberger, F. Schilling

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In this work, a coupled 1D/3D simulation approach for thermal protection and optimization of a trailer refrigeration power pack unit was developed. With the developed 1D/3D simulation approach thermal critical scenarios, such as summer, high-load scenarios are investigated. The 1D thermal model was built up consisting of the thermal network, which includes different point masses and associated heat transfers, the coolant and oil circuits, as well as the fan unit. The 3D computational fluid dynamics (CFD) model was developed to model the air flow through the power pack unit considering convective heat transfer effects. In the 1D thermal model the temperatures of the individual point masses were calculated, which served as input variables for the 3D CFD model. For the calculation of the point mass temperatures in the 1D thermal model, the convective heat transfer rates from the 3D CFD model were required as input variables. These two variables (point mass temperatures and convective heat transfer rates) were the main couple variables for the coupled 1D/3D simulation model. The coupled 1D/3D model was validated with measurements under normal operating conditions. Coupled simulations for summer high-load case were than performed and compared with a reference case under normal operation conditions. Hot temperature regions and components could be identified. Due to the detailed information about the flow field, temperatures and heat fluxes, it was possible to directly derive improvement suggestions for the cooling design of the transport refrigeration power pack unit.

Keywords: Coupled thermal simulation, thermal analysis, transport refrigeration unit, 3D computational fluid dynamics, 1D thermal modelling, thermal management systems.

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Authors: M. R. Kamandar, J. Massah

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The information of the impact cutting behavior of plants stalk plays an important role in the design and fabrication of plants cutting equipment. It is difficult to investigate a theoretical method for defining cutting properties of plants stalks because the cutting process is complex. Thus, it is necessary to set up an experimental approach to determine cutting parameters for a single stalk. To measure the shear force, shear energy and shear strength of plant stalk, a special impact cutting tester was fabricated. It was similar to an Izod impact cutting tester for metals but a cutting blade and data acquisition system were attached to the end of pendulum's arm. The apparatus was included four strain gages and a digital indicator to show the real-time cutting force of plant stalk. To measure the shear force and also testing the apparatus, two plants’ stalks, like buxus and privet, were selected. The samples (buxus and privet stalks) were cut under impact cutting process at four loading rates 1, 2, 3 and 4 m.s^-1 and three internodes fifth, tenth and fifteenth by the apparatus. At buxus cutting analysis: the minimum value of cutting energy was obtained at fifth internode and loading rate 4 m.s^-1 and the maximum value of shear energy was obtained at fifteenth internode and loading rate 1 m.s^-1. At privet cutting analysis: the minimum value of shear consumption energy was obtained at fifth internode and loading rate: 4 m.s^-1 and the maximum value of shear energy was obtained at fifteenth internode and loading rate: 1 m.s^-1. The statistical analysis at both plants showed that the increase of impact cutting speed would decrease the shear consumption energy and shear strength. In two scenarios, the results showed that with increase the cutting speed, shear force would decrease.

Keywords: Buxus, privet, impact cutting, shear energy.

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Authors: Omid F. Valilai, Mahmoud Houshmand

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Nowadays companies strive to survive in a competitive global environment. To speed up product development/modifications, it is suggested to adopt a collaborative product development approach. However, despite the advantages of new IT improvements still many CAx systems work separately and locally. Collaborative design and manufacture requires a product information model that supports related CAx product data models. To solve this problem many solutions are proposed, which the most successful one is adopting the STEP standard as a product data model to develop a collaborative CAx platform. However, the improvement of the STEP-s Application Protocols (APs) over the time, huge number of STEP AP-s and cc-s, the high costs of implementation, costly process for conversion of older CAx software files to the STEP neutral file format; and lack of STEP knowledge, that usually slows down the implementation of the STEP standard in collaborative data exchange, management and integration should be considered. In this paper the requirements for a successful collaborative CAx system is discussed. The STEP standard capability for product data integration and its shortcomings as well as the dominant platforms for supporting CAx collaboration management and product data integration are reviewed. Finally a platform named LAYMOD to fulfil the requirements of CAx collaborative environment and integrating the product data is proposed. The platform is a layered platform to enable global collaboration among different CAx software packages/developers. It also adopts the STEP modular architecture and the XML data structures to enable collaboration between CAx software packages as well as overcoming the STEP standard limitations. The architecture and procedures of LAYMOD platform to manage collaboration and avoid contradicts in product data integration are introduced.

Keywords: CAx, Collaboration management, STEP applicationmodules, STEP standard, XML data structures

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Authors: Atousa Khodadadyan, Gabe Mythen, Hirbod Assa, Beverley Bishop

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Risk assessment and the knowledge provided through this process is a crucial part of any decision-making process in the management of risks and uncertainties. Failure in assessment of risks can cause inadequacy in the entire process of risk management, which in turn can lead to failure in achieving organisational objectives as well as having significant damaging consequences on populations affected by the potential risks being assessed. The choice of tools and techniques in risk assessment can influence the degree and scope of decision-making and subsequently the risk response strategy. There are various available qualitative and quantitative tools and techniques that are deployed within the broad process of risk assessment. The sheer diversity of tools and techniques available to practitioners makes it difficult for organisations to consistently employ the most appropriate methods. This tools and techniques adaptation is rendered more difficult in public risk regulation organisations due to the sensitive and complex nature of their activities. This is particularly the case in areas relating to the environment, food, and human health and safety, when organisational goals are tied up with societal, political and individuals’ goals at national and international levels. Hence, recognising, analysing and evaluating different decision support tools and techniques employed in assessing risks in public risk management organisations was considered. This research is part of a mixed method study which aimed to examine the perception of risk assessment and the extent to which organisations practise risk assessment’ tools and techniques. The study adopted a semi-structured questionnaire with qualitative and quantitative data analysis to include a range of public risk regulation organisations from the UK, Germany, France, Belgium and the Netherlands. The results indicated the public risk management organisations mainly use diverse tools and techniques in the risk assessment process. The primary hazard analysis; brainstorming; hazard analysis and critical control points were described as the most practiced risk identification techniques. Within qualitative and quantitative risk analysis, the participants named the expert judgement, risk probability and impact assessment, sensitivity analysis and data gathering and representation as the most practised techniques.

Keywords: Decision-making, public risk management organisations, risk assessment, tools and techniques.

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Authors: Mayowa A. Sofowora, Seraphim D. Eyono Obono

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The use of information and communication technologies such as computers, mobile phones and the Internet is becoming prevalent in today’s world; and it is facilitating access to a vast amount of data, services and applications for the improvement of people’s lives. However, this prevalence of ICTs is hampered by the problem of low income levels in developing countries to the point where people cannot timeously replace or repair their ICT devices when damaged or lost; and this problem serves as a motivation for this study whose aim is to examine the perceptions of teachers on the reliability of cellphones when used for teaching and learning purposes. The research objectives unfolding this aim are of two types: Objectives on the selection and design of theories and models, and objectives on the empirical testing of these theories and models. The first type of objectives is achieved using content analysis in an extensive literature survey: and the second type of objectives is achieved through a survey of high school teachers from the ILembe and UMgungundlovu districts in the KwaZulu-Natal province of South Africa. Data collected from this questionnaire based survey is analysed in SPSS using descriptive statistics and Pearson correlations after checking the reliability and validity of the questionnaires. The main hypothesis driving this study is that there is a relationship between the demographics and the attribution identity of teachers on one hand, and their perceptions on the reliability of cellphones on the other hand, as suggested by existing literature; except that attribution identities are considered in this study under three angles: intention, knowledge and ability, and action. The results of this study confirm that the perceptions of teachers on the reliability of cellphones for teaching and learning are affected by the school location of these teachers, and by their perceptions on learners’ cellphones usage intentions and actual use.

Keywords: Attribution, Cellphones, E-learning, Reliability

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Authors: Tong-Hsien Chow

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Background: Plantar pressure measurement is an effective method for assessing plantar loading and can be applied to evaluating movement performance of the foot. The purpose of this study is to explore the sprint athletes’ plantar loading characteristics and pain profiles in static standing. Methods: Experiments were undertaken on 80 first-division college sprint athletes and 85 healthy non-sprinters. ‘JC Mat’, the optical plantar pressure measurement was applied to examining the differences between both groups in the arch index (AI), three regional and six distinct sub-regional plantar pressure distributions (PPD), and footprint characteristics. Pain assessment and self-reported health status in sprint athletes were examined for evaluating their common pain areas. Results: Findings from the control group, the males’ AI fell into the normal range. Yet, the females’ AI was classified as the high-arch type. AI values of the sprint group were found to be significantly lower than the control group. PPD were higher at the medial metatarsal bone of both feet and the lateral heel of the right foot in the sprint group, the males in particular, whereas lower at the medial and lateral longitudinal arches of both feet. Footprint characteristics tended to support the results of the AI and PPD, and this reflected the corresponding pressure profiles. For the sprint athletes, the lateral knee joint and biceps femoris were the most common musculoskeletal pains. Conclusions: The sprint athletes’ AI were generally classified as high arches, and that their PPD were categorized between the features of runners and high-arched runners. These findings also correspond to the profiles of patellofemoral pain syndrome (PFPS)-related plantar pressure. The pain profiles appeared to correspond to the symptoms of high-arched runners and PFPS. The findings reflected upon the possible link between high arches and PFPS. The correlation between high-arched runners and PFPS development is worth further studies.

Keywords: Sprint athletes, arch index, plantar pressure distributions, high arches, patellofemoral pain syndrome.

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Authors: K. Rajasekaran, Kannan Balasubramanian

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A sensory network consists of multiple detection locations called sensor nodes, each of which is tiny, featherweight and portable. A single path routing protocols in wireless sensor network can lead to holes in the network, since only the nodes present in the single path is used for the data transmission. Apart from the advantages like reduced computation, complexity and resource utilization, there are some drawbacks like throughput, increased traffic load and delay in data delivery. Therefore, multipath routing protocols are preferred for WSN. Distributing the traffic among multiple paths increases the network lifetime. We propose a scheme, for the data to be transmitted through a dominant path to save energy. In order to obtain a high delivery ratio, a basic route reconstruction protocol is utilized to reconstruct the path whenever a failure is detected. A basic reconstruction routing (BRR) algorithm is proposed, in which a node can leap over path failure by using the already existing routing information from its neighbourhood while the composed data is transmitted from the source to the sink. In order to save the energy and attain high data delivery ratio, data is transmitted along a multiple path, which is achieved by BRR algorithm whenever a failure is detected. Further, the analysis of how the proposed protocol overcomes the drawback of the existing protocols is presented. The performance of our protocol is compared to AOMDV and energy efficient node-disjoint multipath routing protocol (EENDMRP). The system is implemented using NS-2.34. The simulation results show that the proposed protocol has high delivery ratio with low energy consumption.

Keywords: Multipath routing, WSN, energy efficient routing, alternate route, assured data delivery.

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Authors: Brian A. Smith, Ronald W. McClendon, Gerrit Hoogenboom

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The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. Previous work established that the Ward-style artificial neural network (ANN) is a suitable tool for developing such models. The current research focused on developing ANN models with reduced average prediction error by increasing the number of distinct observations used in training, adding additional input terms that describe the date of an observation, increasing the duration of prior weather data included in each observation, and reexamining the number of hidden nodes used in the network. Models were created to predict air temperature at hourly intervals from one to 12 hours ahead. Each ANN model, consisting of a network architecture and set of associated parameters, was evaluated by instantiating and training 30 networks and calculating the mean absolute error (MAE) of the resulting networks for some set of input patterns. The inclusion of seasonal input terms, up to 24 hours of prior weather information, and a larger number of processing nodes were some of the improvements that reduced average prediction error compared to previous research across all horizons. For example, the four-hour MAE of 1.40°C was 0.20°C, or 12.5%, less than the previous model. Prediction MAEs eight and 12 hours ahead improved by 0.17°C and 0.16°C, respectively, improvements of 7.4% and 5.9% over the existing model at these horizons. Networks instantiating the same model but with different initial random weights often led to different prediction errors. These results strongly suggest that ANN model developers should consider instantiating and training multiple networks with different initial weights to establish preferred model parameters.

Keywords: Decision support systems, frost protection, fruit, time-series prediction, weather modeling

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Authors: K. C. Rajan, H. B. Rijal, Kazui Yoshida, Masanori Shukuya

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The electricity consumption in the Japanese household sector has increased with higher rate than that of other sectors. This may be because of aging and information oriented society that requires more electrical appliances to make the life better and easier, under this circumstances, energy saving is one of the essential necessity in Japanese society. To understand the way of energy use and demand response of the residential occupants, it is important to understand the structure of energy used. Home Energy Management System (HEMS) may be used for understanding the pattern and the structure of energy used. HEMS is a visualization system of the energy usage by connecting the electrical equipment in the home and thereby automatically control the energy use in each device, so that the energy saving is achieved. Therefore, the HEMS can provide with the easiest way to understand the structure of energy use. The HEMS has entered the mainstream of the Japanese market. The objective of this study is to understand the pattern of energy saving and cost saving in different regions including Japan during HEMS use. To observe thermal comfort level of HEMS managed residential buildings in Japan, the field survey was made and altogether, 1534 votes from 37 occupants related to thermal comfort, occupants’ behaviors and clothing insulation were collected and analyzed. According to the result obtained, approximately 17.9% energy saving and 8.9% cost saving is possible if HEMS is applied effectively. We found the thermal sensation and overall comfort level of the occupants is high in the studied buildings. The occupants residing in those HEMS buildings are satisfied with the thermal environment and they have accepted it. Our study concluded that the significant reduction in Japanese residential energy use can be achieved by the proper utilization of the HEMS. Better thermal comfort is also possible with the use of HEMS if energy use is managed in a rationally effective manner.

Keywords: Energy reduction, thermal comfort, HEMS market, thermal environment.

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Authors: Bi-Huei Tsai

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Prior research has not effectively investigated how the profitability of Chinese branches affect FDIs in China [1, 2], so this study for the first time incorporates realistic earnings information to systematically investigate effects of innovation, imitation, and profit factors of FDI diffusions from Taiwan to China. Our nonlinear least square (NLS) model, which incorporates earnings factors, forms a nonlinear ordinary differential equation (ODE) in numerical simulation programs. The model parameters are obtained through a genetic algorithms (GA) technique and then optimized with the collected data for the best accuracy. Particularly, Taiwanese regulatory FDI restrictions are also considered in our modified model to meet the realistic conditions. To validate the model-s effectiveness, this investigation compares the prediction accuracy of modified model with the conventional diffusion model, which does not take account of the profitability factors. The results clearly demonstrate the internal influence to be positive, as early FDI adopters- consistent praises of FDI attract potential firms to make the same move. The former erects a behavior model for the latter to imitate their foreign investment decision. Particularly, the results of modified diffusion models show that the earnings from Chinese branches are positively related to the internal influence. In general, the imitating tendency of potential consumers is substantially hindered by the losses in the Chinese branches, and these firms would invest less into China. The FDI inflow extension depends on earnings of Chinese branches, and companies will adjust their FDI strategies based on the returns. Since this research has proved that earning is an influential factor on FDI dynamics, our revised model explicitly performs superior in prediction ability than conventional diffusion model.

Keywords: diffusion model, genetic algorithms, nonlinear leastsquares (NLS) model, prediction error.

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Authors: Mahdiyeh Zafaranchi, Ethan S. Cantor, William T. Riddell, Jess W. Everett

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The New Jersey Department of Military and Veteran’s Affairs (NJ DMAVA) operates over 50 facilities throughout the state of New Jersey, US. NJ DMAVA is under a mandate to move toward decarbonization, which will eventually include eliminating the use of natural gas and other fossil fuels for heating. At the same time, the organization requires increased resiliency regarding electric grid disruption. These competing goals necessitate adopting the use of on-site renewables such as photovoltaic and geothermal power, as well as implementing power control strategies through microgrids. Planning for these changes requires a detailed understanding of current and future electricity use on yearly, monthly, and shorter time scales, as well as a breakdown of consumption by heating, ventilation, and air conditioning (HVAC) equipment. This paper discusses case studies of two buildings that were simulated using the QUick Energy Simulation Tool (eQUEST). Both buildings use electricity from the grid and photovoltaics. One building also uses natural gas. While electricity use data are available in hourly intervals and natural gas data are available in monthly intervals, the simulations were developed using monthly and yearly totals. This approach was chosen to reflect the information available for most NJ DMAVA facilities. Once completed, simulation results are compared to metrics recommended by several organizations to validate energy use simulations. In addition to yearly and monthly totals, the simulated peak demands are compared to actual monthly peak demand values. The simulations resulted in monthly peak demand values that were within 30% of the measured values. These benchmarks will help to assess future energy planning efforts for NJ DMAVA.

Keywords: Building Energy Modeling, eQUEST, peak demand, smart meters.

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Authors: Anastasiia Shuba, Tatiana Kuchmenko, Umarkhanov Ruslan, Bogdanova Ekaterina

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The development of new sensitive coatings for sensors is one of the key directions in the development of sensor technologies. Recently, there has been a trend towards the creation of multicomponent coatings for sensors, which make it possible to increase the sensitivity, and specificity, and improve the performance properties of sensors. When analyzing samples with a complex matrix of biological origin, the inclusion of micelles of bioactive substances (amino and nucleic acids, peptides, proteins) in the composition of the sensor coating can also increase useful analytical information. The purpose of this work is to evaluate the analytical characteristics of composite coatings of piezoelectric quartz sensors based on medium-molecular viscous sorbents with incorporated micellar casein concentrate during the sorption of vapors of volatile organic compounds. The sorption properties of the coatings were studied by piezoelectric quartz microbalance. Macromolecular compounds (dicyclohexyl-18-crown-6, triton X-100, lanolin, micellar casein concentrate) were used as sorbents. Highly volatile organic compounds of various classes (alcohols, acids, aldehydes, esters) and water were selected as test substances. It has been established that composite coatings of sensors with the inclusion of micellar casein are more stable and selective to vapors of highly volatile compounds than to water vapors. The method and technique of forming a composite coating using molecular viscous sorbents does not affect the kinetic features of VOC sorption. When casein micelles are used, the features of kinetic sorption depend on the matrix of the coating.

Keywords: Composite coating, piezoelectric quartz microbalance, sensor, volatile organic compounds.

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Authors: Oksana Razina, Shakeel Ahmad, Jessie Qun Ren, Olufemi Isiaq

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The modern life of businesses is categorically reliant on their established position online, where digital (and particularly website) content plays a significant role as the first point of information. Digital content, therefore, becomes essential – from making the first impression through to the building and development of client relationships. Despite a number of valuable papers suggesting a strategic approach when dealing with digital data, other sources often do not view or accept the approach to digital content as a holistic or continuous process. Associations are frequently made with merely a one-off marketing campaign or similar. The challenge is in establishing an agreed definition for the notion of Digital Content Strategy (DCS), which currently does not exist, as it is viewed from an excessive number of angles. A strategic approach to content, nonetheless, is required, both practically and contextually. We, therefore, aimed at attempting to identify the key content components, comprising a DCS, to ensure all the aspects were covered and strategically applied – from the company’s understanding of the content value to the ability to display flexibility of content and advances in technology. This conceptual project evaluated existing literature on the topic of DCS and related aspects, using PRISMA Systematic Review Method, Document Analysis, Inclusion and Exclusion Criteria, Scoping Review, Snow-Balling Technique and Thematic Analysis. The data were collected from academic and statistical sources, government and relevant trade publications. Based on the suggestions from academics and trading sources, related to the issues discussed, we revealed the key actions for content creation and attempted to define the notion of DCS. The major finding of the study presented Key Content Components of DCS and can be considered for implementation in a business retail setting.

Keywords: Digital content strategy, digital marketing strategy, key content components, websites.

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Authors: Oksana Razina, Shakeel Ahmad, Jessie Qun Ren, Olufemi Isiaq

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The modern life of businesses is categorically reliant on their established position online, where digital (and particularly website) content plays a significant role as the first point of information. Digital content, therefore, becomes essential – from making the first impression through to the building and development of client relationships. Despite a number of valuable papers suggesting a strategic approach when dealing with digital data, other sources often do not view or accept the approach to digital content as a holistic or continuous process. Associations are frequently made with merely a one-off marketing campaign or similar. The challenge is in establishing an agreed definition for the notion of Digital Content Strategy (DCS), which currently does not exist, as it is viewed from an excessive number of angles. A strategic approach to content, nonetheless, is required, both practically and contextually. We, therefore, aimed at attempting to identify the key content components, comprising a DCS, to ensure all the aspects were covered and strategically applied – from the company’s understanding of the content value to the ability to display flexibility of content and advances in technology. This conceptual project evaluated existing literature on the topic of DCS and related aspects, using PRISMA Systematic Review Method, Document Analysis, Inclusion and Exclusion Criteria, Scoping Review, Snow-Balling Technique and Thematic Analysis. The data were collected from academic and statistical sources, government and relevant trade publications. Based on the suggestions from academics and trading sources, related to the issues discussed, we revealed the key actions for content creation and attempted to define the notion of DCS. The major finding of the study presented Key Content Components of DCS and can be considered for implementation in a business retail setting.

Keywords: Digital content strategy, digital marketing strategy, key content components, websites.

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Authors: Marilena Ianculescu, Adriana Alexandru

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Internet of Health Things (IoHT) has already proved to be a persuasive means to support a proper assessment of the living conditions by collecting a huge variety of data. For a customized health management of a senior patient, IoHT provides the capacity to build a dynamic solution for sustaining the shift inside the patient-physician relationship by allowing a real-time and continuous remote monitoring of the health status, well-being, safety and activities of the senior, especially in a non-clinical environment. Thus, is created a win-win solution in which both the patient and the physician enhance their involvement and shared decision-making, with significant outcomes. Health monitoring systems in smart environments are becoming a viable alternative to traditional healthcare solutions. The ongoing “Non-invasive monitoring and health assessment of the elderly in a smart environment (RO-SmartAgeing)” project aims to demonstrate that the existence of complete and accurate information is critical for assessing the health condition of the seniors, improving wellbeing and quality of life in relation to health. The researches performed inside the project aim to highlight how the management of IoHT devices connected to the RO-SmartAgeing platform in a secure way by using a role-based access control system, can allow the physicians to provide health services at a high level of efficiency and accessibility, which were previously only available in hospitals. The project aims to identify deficient aspects in the provision of health services tailored to a senior patient’s specificity and to offer a more comprehensive perspective of proactive and preventive medical acts.

Keywords: Health management, Internet of Health Things, remote monitoring, senior patient.

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Authors: Stamatios A. Theocharis, George A. Tsihrintzis

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One of the most important factors for the success of e-government is training and preparing the workforce of the public sector. As changes and innovation in the public sector progress at a very slow pace and more slowly than in the private sector, issues related to human resources require special care. This is because the workforce will eventually seize the opportunities of the technological solutions used in e-Government. Thus, the central administration should provide employees with continuous and focused training not only on new technologies but also on a wide range of subjects and also improve interdepartmental interaction.

To achieve all this, new methods and training tools need to be implemented in addition to assessment of the employees. In this spirit, we propose the development of an educational platform with user personalization features. We propose the development of this platform using Moodle as the basic tool. Incorporating a personalization mechanism is very important since different employees have different backgrounds, education levels, computer skills, or different capability to develop further. Key features of the proposed platform include, besides typical e-learning tools, communities organized in order to exchange experiences and knowledge, groups of users based on certain criteria, automatic evaluation of users and potential self-education and self-assessment. In its fully developed form, this platform can be part of a more comprehensive knowledge management system for the public sector.

Keywords: e-Government, civil employees education, education technologies.

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Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: Deep neural models, natural language inference, recognizing textual entailment, sentence-to-sentence relation.

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Authors: Violina R. Angelova

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Comparative research has been conducted to allow us to determine the content of macro and microelements in the vegetative and reproductive organs of grass pea and the quality of grass pea seeds, as well as to identify the possibility of grass pea growth on soils contaminated by heavy metals. The experiment was conducted on an agricultural field subjected to contamination from the Non-Ferrous-Metal Works (MFMW) near Plovdiv, Bulgaria. The experimental plots were situated at different distances of 0.5 km and 8 km, respectively, from the source of pollution. On reaching commercial ripeness the grass pea plants were gathered. The composition of the macro and microelements in plant materials (roots, stems, leaves, seeds), and the dry matter content, sugars, proteins, fats and ash contained in the grass pea seeds were determined. Translocation factors (TF) and bioaccumulation factor (BCF) were also determined. The quantitative measurements were carried out through inductively-coupled plasma (ICP). The grass pea plant can successfully be grown on soils contaminated by heavy metals. Soil pollution with heavy metals does not affect the quality of the grass pea seeds. The seeds of the grass pea contain significant amounts of nutrients (K, P, Cu, Fe Mn, Zn) and protein (23.18-29.54%). The distribution of heavy metals in the organs of the grass pea has a selective character, which reduces in the following order: leaves > roots > stems > seeds. BCF and TF values were greater than one suggesting efficient accumulation in the above ground parts of grass pea plant. Grass pea is a plant that is tolerant to heavy metals and can be referred to the accumulator plants. The results provide valuable information about the chemical and nutritional composition of the seeds of the grass pea grown on contaminated soils in Bulgaria. The high content of macro and microelements and the low concentrations of toxic elements in the grass pea grown in contaminated soil make it possible to use the seeds of the grass pea as animal feed.

Keywords: Grass pea, heavy metals, micro and macroelements, polluted soils, quality.

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Authors: J. Ritonja

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Available commercial applications of power system stabilizers assure optimal damping of synchronous generator’s oscillations only in a small part of operating range. Parameters of the power system stabilizer are usually tuned for the selected operating point. Extensive variations of the synchronous generator’s operation result in changed dynamic characteristics. This is the reason that the power system stabilizer tuned for the nominal operating point does not satisfy preferred damping in the overall operation area. The small-signal stability and the transient stability of the synchronous generators have represented an attractive problem for testing different concepts of the modern control theory. Of all the methods, the adaptive control has proved to be the most suitable for the design of the power system stabilizers. The adaptive control has been used in order to assure the optimal damping through the entire synchronous generator’s operating range. The use of the adaptive control is possible because the loading variations and consequently the variations of the synchronous generator’s dynamic characteristics are, in most cases, essentially slower than the adaptation mechanism. The paper shows the development and the application of the self-tuning power system stabilizer based on recursive least square identification method and linear quadratic regulator. Identification method is used to calculate the parameters of the Heffron-Phillips model of the synchronous generator. On the basis of the calculated parameters of the synchronous generator’s mathematical model, the synthesis of the linear quadratic regulator is carried-out. The identification and the synthesis are implemented on-line. In this way, the self-tuning power system stabilizer adapts to the different operating conditions. A purpose of this paper is to contribute to development of the more effective power system stabilizers, which would replace currently used linear stabilizers. The presented self-tuning power system stabilizer makes the tuning of the controller parameters easier and assures damping improvement in the complete operating range. The results of simulations and experiments show essential improvement of the synchronous generator’s damping and power system stability.

Keywords: Adaptive control, linear quadratic regulator, power system stabilizer, recursive least square identification.

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Authors: Payman Davoodi-Nasab, Ahmad Rahbar-Kelishami, Jaber Safdari, Hossein Abolghasemi

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The high purity rare earth elements (REEs) have been vastly used in the field of chemical engineering, metallurgy, nuclear energy, optical, magnetic, luminescence and laser materials, superconductors, ceramics, alloys, catalysts, and etc. Neodymium is one of the most abundant rare earths. By development of a neodymium–iron–boron (Nd–Fe–B) permanent magnet, the importance of neodymium has dramatically increased. Solvent extraction processes have many operational limitations such as large inventory of extractants, loss of solvent due to the organic solubility in aqueous solutions, volatilization of diluents, etc. One of the promising methods of liquid membrane processes is emulsion liquid membrane (ELM) which offers an alternative method to the solvent extraction processes. In this work, a study on Nd extraction through multi-walled carbon nanotubes (MWCNTs) assisted ELM using response surface methodology (RSM) has been performed. The ELM composed of diisooctylphosphinic acid (CYANEX 272) as carrier, MWCNTs as nanoparticles, Span-85 (sorbitan triooleate) as surfactant, kerosene as organic diluent and nitric acid as internal phase. The effects of important operating variables namely, surfactant concentration, MWCNTs concentration, and treatment ratio were investigated. Results were optimized using a central composite design (CCD) and a regression model for extraction percentage was developed. The 3D response surfaces of Nd(III) extraction efficiency were achieved and significance of three important variables and their interactions on the Nd extraction efficiency were found out. Results indicated that introducing the MWCNTs to the ELM process led to increasing the Nd extraction due to higher stability of membrane and mass transfer enhancement. MWCNTs concentration of 407 ppm, Span-85 concentration of 2.1 (%v/v) and treatment ratio of 10 were achieved as the optimum conditions. At the optimum condition, the extraction of Nd(III) reached the maximum of 99.03%.

Keywords: Emulsion liquid membrane, extraction of neodymium, multi-walled carbon nanotubes, response surface method.

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Authors: Guadalupe Pérez, Jorge Islas, Mirna Guevara, Raúl Suárez

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Jatropha curcas is a perennial oleaginous plant that is currently considered an energy crop with high potential as an environmentally sustainable biofuel. During the last decades, research in biofuels has grown in tropical and subtropical regions in Latin America. However, as far we know, there are no reports on the growth and yield patterns of Jatropha curcas under the specific agro climatic scenarios of the State of Morelos, Mexico. This study presents the results of 52 months monitoring of 10 toxic and non-toxic ecotypes of Jatropha curcas (E1M, E2M, E3M, E4M, E5M, E6O, E7O, E8O, E9C, E10C) in an experimental plantation with minimum watering and fertilization resources. The main objective is to identify the ecotypes with the highest potential as biodiesel raw material in the select region, by developing experimental information. Specifically, we monitored biophysical and growth parameters, including plant survival and seed production (at the end of month 52), to study the performance of each ecotype and to establish differences among the variables of morphological growth, net seed oil content, and toxicity. To analyze the morphological growth, a statistical approach to the biophysical parameters was used; the net seed oil content -80 to 192 kg/ha- was estimated with the first harvest; and the toxicity was evaluated by examining the phorbol ester concentration (µg/L) in the oil extracted from the seeds. The comparison and selection of ecotypes was performed through a methodology developed based on the normalization of results. We identified four outstanding ecotypes (E1M, E2M, E3M, and E4M) that can be used to establish Jatropha curcas as energy crops in the state of Morelos for feasible agro-industrial production of biodiesel and other products related to the use of biomass.

Keywords: Biodiesel production, Jatropha curcas, morphologic growth, toxic and non-toxic ecotypes, seed oil content.

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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: Tulika Bhattacharyya, Suhita C. Chatterjee

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West Bengal, one of the most rapidly ageing states in India, has inadequate structure for elder care. Therefore, there is an urgent need to improve elder care which involves focusing on different care settings where the elderly exists, like - Homes, Hospitals and Long-Term Care facilities (e.g. - Old Age Homes, Hospices). The study explores various elder care settings, with the intention to develop an understanding about them, and thereby generate comprehensive information about the entire spectrum of elder care in Kolkata. Empirical data are collected from the elderly and their caregivers in different settings. The tools for data collection are narratives, in-depth interviews and focus group discussions, along with field observations. Mixed method design is adopted to analyze the complexities of elder care in different set ups. The major challenges of elder care in private Homes are: architecturally inadequate housing conditions, paucity of financial support and scarcity of skilled caregivers. While the key factors preventing the Hospital and Long-Term Care Facilities from providing elder care services are inadequate policies and set governmental standards for elder care for the hospitalized elderly in various departments of the Hospital and the elderly residing in different kinds of Long Term Care Facilities. The limitations in each care setting results in considerable neglect and abuse of the elderly. The major challenges in elder care in West Bengal are lack of continuum between different care settings/ peripheral location of private Homes within public health framework and inadequate state Palliative policy- including narcotic regulations. The study suggests remedial measures to improve the capacity to deliver elder care in different settings.

Keywords: Elder care settings, family caregiver, home care, geriatric hospital care, long term care facility.

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Authors: Marco Antonio Lara De la Calleja, María Catalina Ovando Chico, Eduardo Lopez Ruiz

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Community empowerment has been proved to be a key element in the solution of the food security problem. As a result of a conceptual analysis, it was found that agricultural production, economic development and governance, are the traditional basis of food security models. Although the literature points to social inclusion as an important factor for food security, no model has considered it as the basis of it. The aim of this research is to identify different dimensions that make an integral model for food security, with emphasis on community empowerment. A diagnosis was made in the study community (Tatoxcac, Zacapoaxtla, Puebla), to know the aspects that impact the level of food insecurity. With a statistical sample integrated by 200 families, the Latin American and Caribbean Food Security Scale (ELCSA) was applied, finding that: in households composed by adults and children, have moderated food insecurity, (ELCSA scale has three levels, low, moderated and high); that result is produced mainly by the economic income capacity and the diversity of the diet on its food. With that being said, a model was developed to promote food security through five dimensions: 1. Regional context of the community; 2. Structure and system of local food; 3. Health and nutrition; 4. Information and technology access; and 5. Self-awareness and empowerment. The specific actions on each axis of the model, allowed a systemic approach needed to attend food security in the community, through the empowerment of society. It is concluded that the self-awareness of local communities is an area of extreme importance, which must be taken into account for participatory schemes to improve food security. In the long term, the model requires the integrated participation of different actors, such as government, companies and universities, to solve something such vital as food security.

Keywords: Community empowerment, food security, model, systemic approach.

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