Search results for: complex adaptive systems

Authors: Manish Pal, Rumi Sutradhar

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Pavement surface unevenness plays a pivotal role on roughness index of road which affects on riding comfort ability. Comfort ability refers to the degree of protection offered to vehicle occupants from uneven elements in the road surface. So, it is preferable to have a lower roughness index value for a better riding quality of road users. Roughness is generally defined as an expression of irregularities in the pavement surface which can be measured using different equipments like MERLIN, Bump integrator, Profilometer etc. Among them Bump Integrator is quite simple and less time consuming in case of long road sections. A case study is conducted on low volume roads in West District in Tripura to determine roughness index (RI) using Bump Integrator at the standard speed of 32 km/h. But it becomes too tough to maintain the requisite standard speed throughout the road section. The speed of Bump Integrator (BI) has to lower or higher in some distinctive situations. So, it becomes necessary to convert these roughness index values of other speeds to the standard speed of 32 km/h. This paper highlights on that roughness index conversional model. Using SPSS (Statistical Package of Social Sciences) software a generalized equation is derived among the RI value at standard speed of 32 km/h and RI value at other speed conditions.

Keywords: Bump Integrator, Pavement Distresses, Roughness Index, SPSS.

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Authors: G. Venkata Rao, P. Kalpana, R. Srinivasa Rao

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Adequate and reliable estimates of aquifer parameters are of utmost importance for proper management of vital groundwater resources. At present scenario, the ground water is polluted because of industrial waste disposed over the land and the contaminants are transported in the aquifer from one area to another area, which is depending on the characteristics of the aquifer and contaminants. To know the contaminant transport, the accurate estimation of aquifer properties is highly needed. Conventionally, these properties are estimated through pumping tests carried out on water wells. The occurrence and movement of ground water in the aquifer are characteristically defined by the aquifer parameters. The pumping (aquifer) test is the standard technique for estimating various hydraulic properties of aquifer systems, viz., transmissivity (T), hydraulic conductivity (K), storage coefficient (S) etc., for which the graphical method is widely used. The study area for conducting pumping test is Pydibheemavaram Industrial area near the coastal belt of Srikulam, AP, India. The main objective of the present work is to estimate the aquifer properties for developing contaminant transport model for the study area.

Keywords: Aquifer, contaminant transport, hydraulic conductivity, industrial waste, pumping test.

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Authors: Tisciane Perpetuo e Oliveira, Dante Inga Narvaez, Marcelo Gradella Villalva

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Installations of solar photovoltaic systems have increased considerably in the last decade. Therefore, it has been noticed that monitoring of meteorological data (solar irradiance, air temperature, wind velocity, etc.) is important to predict the potential of a given geographical area in solar energy production. In this sense, the present work compares two computational tools that are capable of estimating the energy generation of a photovoltaic system through correlation analyzes of solar radiation data: PVsyst software and an algorithm based on the PVlib package implemented in MATLAB. In order to achieve the objective, it was necessary to obtain solar radiation data (measured and from a solarimetric database), analyze the decomposition of global solar irradiance in direct normal and horizontal diffuse components, as well as analyze the modeling of the devices of a photovoltaic system (solar modules and inverters) for energy production calculations. Simulated results were compared with experimental data in order to evaluate the performance of the studied methods. Errors in estimation of energy production were less than 30% for the MATLAB algorithm and less than 20% for the PVsyst software.

Keywords: Energy production, meteorological data, irradiance decomposition, solar photovoltaic system.

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Authors: S. B. Otieno, Were Fred, E. W. Kabiru, K. Waza

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Background: HIV/AIDS is leading to the loss of labor through sickness and subsequent death, this is leading to the neglect of farm and off-farm activities, with the subsequent loss of potential income and food security. The situation is sensitive to seasonal labour peaks in agriculture. This study was done to determine the impact of high HIV prevalence in farming systems and food security in Pala Bondo District, Kenya. Methods: In this study, 386 respondents were randomly chosen in Pala Sub-Location. The respondents and key informants were interviewed using structured questionnaire. The data were entered and analyzed using SPSS version 16. Results: It was established that majority of respondents (67%) were between 18 and 35 years {χ² = (1, N = 386) = 13.430, p = 0.000} (chimney effect). The study also established that 83.5% of respondents were married {χ² = (1, N= 370) = 166.277 p = 0.000} and predominant occupation being farming and fishing (61%), while 52.8% of farm labour was by hand, 26% by oxen, and 4.9% mechanized. 73.2% of respondents only farm 0.25 to 2 acres, 48% mentioned lack of labour in land preparation {χ² ((1,N = 321) = 113.146, p = 0.000), in planting {χ² (1, N = 321) = 29.28, p = 0.000}. Majority of respondents lack food from January to June, during which 93% buy food. Conclusion: The high HIV prevalence in Pala has affected the farm labour leading to food insecurity.

Keywords: Food security, HIV, AIDS, labour.

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Authors: G. Sevilla, S. Zapata, F. Giraldo, E. Torres, C. Collazos

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This work describes a framework for teaching of global software engineering (GSE) in university undergraduate programs. This framework proposes a method of teaching that incorporates adequate techniques of software requirements elicitation and validated tools of communication, critical aspects to global software development scenarios. The use of proposed framework allows teachers to simulate small software development companies formed by Latin American students, which build information systems. Students from three Latin American universities played the roles of engineers by applying an iterative development of a requirements specification in a global software project. The proposed framework involves the use of a specific purpose Wiki for asynchronous communication between the participants of the process. It is also a practice to improve the quality of software requirements that are formulated by the students. The additional motivation of students to participate in these practices, in conjunction with peers from other countries, is a significant additional factor that positively contributes to the learning process. The framework promotes skills for communication, negotiation, and other complementary competencies that are useful for working on GSE scenarios.

Keywords: Requirements analysis, distributed requirements engineering, practical experiences, collaborative support.

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Authors: Atanu K Samanta, Asim Ali Khan

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Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: Artificial neural network, ANN, brain tumor, computer-aided diagnostic, CAD system, gray-level co-occurrence matrix, GLCM, level set method, tumor segmentation.

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Authors: Münüre Tanur Erkoyuncu, Mustafa Yorgancılar

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Crop improvement through genetic engineering depends on effective and reproducible plant regeneration systems. Immature embryos are the most widely used explant source for in vitro regeneration in barley (Hordeum vulgare L.). However, immature embryos require the continuous growth of donor plants and the suitable stage for their culture is also certainly limited. On the other hand, mature embryos can be procured and stored easily; they can be studied throughout the year. In this study, an effective callus induction and plant regeneration were aimed to develop from mature embryos of different barley genotypes. The effect of medium (MS₁ and MS₂), auxin type (2,4-D, dicamba, picloram and 2,4,5-T) and concentrations (2, 4, 6 mg/l) on callus formation and effect of cytokinin type (TDZ, BAP) and concentrations (0.2, 0.5, 1.0 mg/l) on green plant regeneration were evaluated in mature embryo culture of barley. Callus and shoot formation was successful for all genotypes. By depending on genotype, MS₁ is the best medium, 4 mg/l dicamba is the best growth regulator in the callus induction and MS₁ is the best medium, 1 mg/l BAP is the best growth regulator in the shoot formation were determined.

Keywords: Barley, callus, embryo culture, mature embryo.

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Authors: T. Lantharthong, N. Rugthaicharoencheep

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This paper presents an efficient algorithm for optimization of radial distribution systems by a network reconfiguration to balance feeder loads and eliminate overload conditions. The system load-balancing index is used to determine the loading conditions of the system and maximum system loading capacity. The index value has to be minimum in the optimal network reconfiguration of load balancing. A method based on Tabu search algorithm, The Tabu search algorithm is employed to search for the optimal network reconfiguration. The basic idea behind the search is a move from a current solution to its neighborhood by effectively utilizing a memory to provide an efficient search for optimality. It presents low computational effort and is able to find good quality configurations. Simulation results for a radial 69-bus system with distributed generations and capacitors placement. The study results show that the optimal on/off patterns of the switches can be identified to give the best network reconfiguration involving balancing of feeder loads while respecting all the constraints.

Keywords: Network reconfiguration, Distributed generation Capacitor placement, Load balancing, Optimization technique

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Authors: Mei Shan Ngan, Chee Wei Tan

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Due to the non-linear characteristics of photovoltaic (PV) array, PV systems typically are equipped with the capability of maximum power point tracking (MPPT) feature. Moreover, in the case of PV array under partially shaded conditions, hotspot problem will occur which could damage the PV cells. Partial shading causes multiple peaks in the P-V characteristic curves. This paper presents a hybrid algorithm of Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN) MPPT algorithm for the detection of global peak among the multiple peaks in order to extract the true maximum energy from PV panel. The PV system consists of PV array, dc-dc boost converter controlled by the proposed MPPT algorithm and a resistive load. The system was simulated using MATLAB/Simulink package. The simulation results show that the proposed algorithm performs well to detect the true global peak power. The results of the simulations are analyzed and discussed.

Keywords: Photovoltaic (PV), Partial Shading, Maximum Power Point Tracking (MPPT), Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN)

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Authors: Rachid.Dehini, Abdesselam.Bassou, Brahim.Ferdi

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Active Power Filters (APFs) are today the most widely used systems to eliminate harmonics compensate power factor and correct unbalanced problems in industrial power plants. We propose to improve the performances of conventional APFs by using artificial neural networks (ANNs) for harmonics estimation. This new method combines both the strategies for extracting the three-phase reference currents for active power filters and DC link voltage control method. The ANNs learning capabilities to adaptively choose the power system parameters for both to compute the reference currents and to recharge the capacitor value requested by VDC voltage in order to ensure suitable transit of powers to supply the inverter. To investigate the performance of this identification method, the study has been accomplished using simulation with the MATLAB Simulink Power System Toolbox. The simulation study results of the new (SAPF) identification technique compared to other similar methods are found quite satisfactory by assuring good filtering characteristics and high system stability.

Keywords: Artificial Neural Networks (ANN), p-q theory, (SAPF), Harmonics, Total Harmonic Distortion.

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Authors: Somayeh Timarchi, Keivan Navi

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Efficient modulo 2n+1 adders are important for several applications including residue number system, digital signal processors and cryptography algorithms. In this paper we present a novel modulo 2n+1 addition algorithm for a recently represented number system. The proposed approach is introduced for the reduction of the power dissipated. In a conventional modulo 2n+1 adder, all operands have (n+1)-bit length. To avoid using (n+1)-bit circuits, the diminished-1 and carry save diminished-1 number systems can be effectively used in applications. In the paper, we also derive two new architectures for designing modulo 2n+1 adder, based on n-bit ripple-carry adder. The first architecture is a faster design whereas the second one uses less hardware. In the proposed method, the special treatment required for zero operands in Diminished-1 number system is removed. In the fastest modulo 2n+1 adders in normal binary system, there are 3-operand adders. This problem is also resolved in this paper. The proposed architectures are compared with some efficient adders based on ripple-carry adder and highspeed adder. It is shown that the hardware overhead and power consumption will be reduced. As well as power reduction, in some cases, power-delay product will be also reduced.

Keywords: Modulo 2n+1 arithmetic, residue number system, low power, ripple-carry adders.

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Authors: Ezgi Dündar-Tekkaya, Nilgün Karatepe

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Carbon nanotubes (CNTs) with their high mechanical, electrical, thermal and chemical properties are regarded as promising materials for many different potential applications. Having unique properties they can be used in a wide range of fields such as electronic devices, electrodes, drug delivery systems, hydrogen storage, textile etc. Catalytic chemical vapor deposition (CCVD) is a common method for CNT production especially for mass production. Catalysts impregnated on a suitable substrate are important for production with chemical vapor deposition (CVD) method. Iron catalyst and MgO substrate is one of most common catalyst-substrate combination used for CNT. In this study, CNTs were produced by CCVD of acetylene (C2H2) on magnesium oxide (MgO) powder substrate impregnated by iron nitrate (Fe(NO3)3•9H2O) solution. The CNT synthesis conditions were as follows: at synthesis temperatures of 500 and 800°C multiwall and single wall CNTs were produced respectively. Iron (Fe) catalysts were prepared by with Fe:MgO ratio of 1:100, 5:100 and 10:100. The duration of syntheses were 30 and 60 minutes for all temperatures and catalyst percentages. The synthesized materials were characterized by thermal gravimetric analysis (TGA), transmission electron microscopy (TEM) and Raman spectroscopy.

Keywords: Carbon nanotube, catalyst, catalytic chemical vapordeposition, iron

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Authors: Ying Yu, Wen-Chi Kuo, Tung-Jung Sung

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The Product-Service System (PSS) has received widespread attention due to the increasing global competition in manufacturing and service markets. Today’s smart products and services are driven by Internet of things (IoT) technologies which will promote the transformation from traditional PSS to smart PSS. Although the smart PSS has some of technological achievements in businesses, it often ignores the real demands of target users when using products and services. Therefore, designers should know and learn the User Experience (UX) of smart products, services and systems. However, both of academia and industry still lack relevant development experience of smart PSS since it is an emerging field. In doing so, this is a case study of Xiaomi’s Chunmi, the largest IoT platform in the world, and addresses the two major issues: (1) why Chunmi should develop smart PSS strategies with UX; and (2) how Chunmi could successfully implement the strategic objectives of smart PSS through the design. The case study results indicated that: (1) the smart PSS can distinguish competitors by their unique UX which is difficult to duplicate; (2) early user engagement is crucial for the success of smart PSS; and (3) interaction, expectation, and enjoyment can be treated as a three-dimensional evaluation of UX design for smart PSS innovation. In conclusion, the smart PSS can gain competitive advantages through good UX design in the market.

Keywords: Design research, smart PSS, user experience, user engagement.

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Authors: Mojtaba Valinataj

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Reversible logic as a new favorable design domain can be used for various fields especially creating quantum computers because of its speed and intangible power consumption. However, its susceptibility to a variety of environmental effects may lead to yield the incorrect results. In this paper, because of the importance of multiplication operation in various computing systems, some novel reversible logic array multipliers are proposed with error detection capability by incorporating the parity-preserving gates. The new designs are presented for two main parts of array multipliers, partial product generation and multi-operand addition, by exploiting the new arrangements of existing gates, which results in two signed parity-preserving array multipliers. The experimental results reveal that the best proposed 4×4 multiplier in this paper reaches 12%, 24%, and 26% enhancements in the number of constant inputs, number of required gates, and quantum cost, respectively, compared to previous design. Moreover, the best proposed design is generalized for n×n multipliers with general formulations to estimate the main reversible logic criteria as the functions of the multiplier size.

Keywords: Array multipliers, Baugh-Wooley method, error detection, parity-preserving gates, quantum computers, reversible logic.

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Authors: Mat Syai'in, Adi Soeprijanto, Takashi Hiyama

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An optimal power flow (OPF) based on particle swarm optimization (PSO) was developed with more realistic generator security constraint using the capability curve instead of only Pmin/Pmax and Qmin/Qmax. Neural network (NN) was used in designing digital capability curve and the security check algorithm. The algorithm is very simple and flexible especially for representing non linear generation operation limit near steady state stability limit and under excitation operation area. In effort to avoid local optimal power flow solution, the particle swarm optimization was implemented with enough widespread initial population. The objective function used in the optimization process is electric production cost which is dominated by fuel cost. The proposed method was implemented at Java Bali 500 kV power systems contain of 7 generators and 20 buses. The simulation result shows that the combination of generator power output resulted from the proposed method was more economic compared with the result using conventional constraint but operated at more marginal operating point.

Keywords: Optimal Power Flow, Generator Capability Curve, Particle Swarm Optimization, Neural Network

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Authors: Ruilian Zhao, Shukai Zhang, Yan Wang, Weiwei Wang

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Repairing broken test cases is an expensive and challenging task in evolving software systems. Although an automated repair technique with intent-preservation has been proposed, it does not take into account the association between test repairs and assertions, leading a large number of irrelevant candidates and decreasing the repair capability. This paper proposes a assertion-driven test repair approach. Furthermore, a intent-oriented priority criterion is raised to guide the repair candidate generation, making the repairs closer to the intent of the test. In more detail, repair targets are determined through post-dominance relations between assertions and the methods that directly cause compilation errors. Then, test repairs are generated from the target in a bottom-up way, guided by the the intent-oriented priority criteria. Finally, the generated repair candidates are prioritized to match the original test intent. The approach is implemented and evaluated on the benchmark of 4 open-source programs and 91 broken test cases. The result shows that the approach can fix 89% (81/91) broken test cases, which are more effective than the existing intent-preserved test repair approach, and our intent-oriented priority criteria work well.

Keywords: Test repair, test intent, software test, test case evolution.

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Authors: Bella Llego

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This research aims to study on “ASEAN Citizenship in the Internationalization of Thai Higher Education.” The purposes of this research are (1) to examine the Thai academics and scholars defined in the concept of internationalization of higher education, (2) to know how Thailand tries to fulfill its internationalization on education goal, (3) to find out the advantages and disadvantages of Thailand hub for higher education in Asia. Sequential mixed methods, qualitative and quantitative research methods were utilized to gather the data collected. By using a qualitative method (individual interviews from key Thai administrators and educators in the international higher education sector), a quantitative method (survey) was utilized to draw upon and to elaborate the recurring themes present during the interviews. The study found that many aspects of Thai international higher education programs received heavy influence from both the American and European higher education systems. Thailand’s role and leadership in the creation and launch of the ASEAN Economic Community (AEC) by 2015 gives its unique context for its internationalization efforts. English is being designated as the language of all Thai international programs; its influence further strengthened being the current language of academia, international business, and the internet, having global influence.

Keywords: ASEAN Citizenship, Internationalization, Thai Higher Education.

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Authors: Tarik Rashid, B. Q. Huang, M-T. Kechadi, B. Gleeson

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this paper presents an auto-regressive network called the Auto-Regressive Multi-Context Recurrent Neural Network (ARMCRN), which forecasts the daily peak load for two large power plant systems. The auto-regressive network is a combination of both recurrent and non-recurrent networks. Weather component variables are the key elements in forecasting because any change in these variables affects the demand of energy load. So the AR-MCRN is used to learn the relationship between past, previous, and future exogenous and endogenous variables. Experimental results show that using the change in weather components and the change that occurred in past load as inputs to the AR-MCRN, rather than the basic weather parameters and past load itself as inputs to the same network, produce higher accuracy of predicted load. Experimental results also show that using exogenous and endogenous variables as inputs is better than using only the exogenous variables as inputs to the network.

Keywords: Daily peak load forecasting, neural networks, recurrent neural networks, auto regressive multi-context neural network.

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Authors: M. P. Sebastian

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Health for all is considered as a sign of well-being and inclusive growth. New healthcare technologies are contributing to the quality of human lives by promoting health education and awareness, leading to the prevention, early diagnosis and treatment of the symptoms of diseases. Healthcare technologies have now migrated from the medical and institutionalized settings to the home and everyday life. This paper explores these new technologies and investigates how they contribute to health education and awareness, promoting the objective of high-value health system for all. The methodology used for the research is literature review. The paper also discusses the opportunities and challenges with futuristic healthcare technologies. The combined advances in genomics medicine, wearables and the IoT with enhanced data collection in electronic health record (EHR) systems, environmental sensors, and mobile device applications can contribute in a big way to high-value health system for all. The promise by these technologies includes reduced total cost of healthcare, reduced incidence of medical diagnosis errors, and reduced treatment variability. The major barriers to adoption include concerns with security, privacy, and integrity of healthcare data, regulation and compliance issues, service reliability, interoperability and portability of data, and user friendliness and convenience of these technologies.

Keywords: Bigdata, education, healthcare, ICT, patients, technologies.

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Authors: Gigih Supriyatno

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SQL injection is one of the most common types of attacks and has a very critical impact on web servers. In the worst case, an attacker can perform post-exploitation after a successful SQL injection attack. In the case of forensics web servers, web server analysis is closely related to log file analysis. But sometimes large file sizes and different log types make it difficult for investigators to look for traces of attackers on the server. The purpose of this paper is to help investigator take appropriate steps to investigate when the web server gets attacked. We use attack scenarios using SQL injection attacks including PHP backdoor injection as post-exploitation. We perform post-mortem analysis of web server logs based on Hypertext Transfer Protocol (HTTP) POST and HTTP GET method approaches that are characteristic of SQL injection attacks. In addition, we also propose structured analysis method between the web server application log file, database application, and other additional logs that exist on the webserver. This method makes the investigator more structured to analyze the log file so as to produce evidence of attack with acceptable time. There is also the possibility that other attack techniques can be detected with this method. On the other side, it can help web administrators to prepare their systems for the forensic readiness.

Keywords: Web forensic, SQL injection, web shell, investigation.

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Authors: S. Studente, S. Ellis, S. F. Garivaldis

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We report upon a study introducing a chatbot to develop learning communities at a London University, with a largely international student base. The focus of the chatbot was twofold; to ease the transition for students into their first year of university study, and to increase study engagement. Four learning communities were created using the chatbot; level 3 foundation, level 4 undergraduate, level 6 undergraduate and level 7 post-graduate. Students and programme leaders were provided with access to the chat bot via mobile app prior to their study induction and throughout the autumn term of 2019. At the end of the term, data were collected via questionnaires and focus groups with students and teaching staff to allow for identification of benefits and challenges. Findings indicated a positive correlation between study engagement and engagement with peers. Students reported that the chatbot enabled them to obtain support and connect to their programme leader. Both staff and students also made recommendation on how engagement could be further enhanced using the bot in terms of; clearly specified purpose, integration with existing university systems, leading by example and connectivity. Extending upon these recommendations, a second pilot study is planned for September 2020, for which the focus will be upon improving attendance rates, student satisfaction and module pass rates.

Keywords: Chatbot, e-learning, learning communities, student engagement.

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Authors: Azza. S. Naik, S. S. Lele

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Indian subcontinent has a plethora of traditional medicine systems that provide promising solutions to lifestyle disorders in an 'all natural way'. Spices and oilseeds hold prominence in Indian cuisine hence the focus of the current study was to evaluate the bioactive molecules from Linum usitatissinum (LU), Lepidium sativum (LS), Nigella sativa (NS) and Guizotia abyssinica (GA) seeds. The seeds were characterized for functional lipids like omega-3 fatty acid, antioxidant capacity, phenolic compounds, dietary fiber and anti-nutritional factors. Analysis of the seeds revealed LU and LS to be a rich source of α-linolenic acid (41.85 ± 0.33%, 26.71 ± 0.63%), an omega 3 fatty acid (using GCMS). While studying antioxidant potential NS seeds demonstrated highest antioxidant ability (61.68 ± 0.21 TEAC/ 100 gm DW) due to the presence of phenolics and terpenes as assayed by the Mass spectral analysis. When screened for anti-nutritional factor cyanogenic glycoside, LS seeds showed content as high as 1674 ± 54 mg HCN / kg. GA is a probable good source of a stable vegetable oil (SFA: PUFA 1:2.3). The seeds showed diversified bioactive profile and hence further studies to use different bio molecules in tandem for the development of a possible 'nutraceutical cocktail' have been initiated..

Keywords: antioxidants, bioactives, functional lipids and oilseeds

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Authors: M. Derakhshanfar, B. Minaei-Bidgoli

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Spatial trends are one of the valuable patterns in geo databases. They play an important role in data analysis and knowledge discovery from spatial data. A spatial trend is a regular change of one or more non spatial attributes when spatially moving away from a start object. Spatial trend detection is a graph search problem therefore heuristic methods can be good solution. Artificial immune system (AIS) is a special method for searching and optimizing. AIS is a novel evolutionary paradigm inspired by the biological immune system. The models based on immune system principles, such as the clonal selection theory, the immune network model or the negative selection algorithm, have been finding increasing applications in fields of science and engineering. In this paper, we develop a novel immunological algorithm based on clonal selection algorithm (CSA) for spatial trend detection. We are created neighborhood graph and neighborhood path, then select spatial trends that their affinity is high for antibody. In an evolutionary process with artificial immune algorithm, affinity of low trends is increased with mutation until stop condition is satisfied.

Keywords: Spatial Data Mining, Spatial Trend Detection, Heuristic Methods, Artificial Immune System, Clonal Selection Algorithm (CSA)

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Authors: Jia-Jang Wu

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This paper presents the scaling laws that provide the criteria of geometry and dynamic similitude between the full-size rotor-shaft system and its scale model, and can be used to predict the torsional vibration characteristics of the full-size rotor-shaft system by manipulating the corresponding data of its scale model. The scaling factors, which play fundamental roles in predicting the geometry and dynamic relationships between the full-size rotor-shaft system and its scale model, for torsional free vibration problems between scale and full-size rotor-shaft systems are firstly obtained from the equation of motion of torsional free vibration. Then, the scaling factor of external force (i.e., torque) required for the torsional forced vibration problems is determined based on the Newton’s second law. Numerical results show that the torsional free and forced vibration characteristics of a full-size rotor-shaft system can be accurately predicted from those of its scale models by using the foregoing scaling factors. For this reason, it is believed that the presented approach will be significant for investigating the relevant phenomenon in the scale model tests.

Keywords: Torsional vibration, full-size model, scale model, scaling laws.

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Authors: D. Danesh, M. J. Ryan, A. Abbasi

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Project Portfolio Management (PPM) is an essential component of an organisation’s strategic procedures, which requires attention of several factors to envisage a range of long-term outcomes to support strategic project portfolio decisions. To evaluate overall efficiency at the portfolio level, it is essential to identify the functionality of specific projects as well as to aggregate those findings in a mathematically meaningful manner that indicates the strategic significance of the associated projects at a number of levels of abstraction. PPM success is directly associated with the quality of decisions made and poor judgment increases portfolio costs. Hence, various Multi-Criteria Decision Making (MCDM) techniques have been designed and employed to support the decision-making functions. This paper reviews possible options to enhance the decision-making outcomes in organisational portfolio management processes using the Analytic Hierarchy Process (AHP) both from academic and practical perspectives and will examine the usability, certainty and quality of the technique. The results of the study will also provide insight into the technical risk associated with current decision-making model to underpin initiative tracking and strategic portfolio management.

Keywords: Analytic hierarchy process, decision support systems, multi-criteria decision-making, project portfolio management.

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Authors: Halil Snopce, Ilir Spahiu, Lavdrim Elmazi

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A lot of Scientific and Engineering problems require the solution of large systems of linear equations of the form bAx in an effective manner. LU-Decomposition offers good choices for solving this problem. Our approach is to find the lower bound of processing elements needed for this purpose. Here is used the so called Omega calculus, as a computational method for solving problems via their corresponding Diophantine relation. From the corresponding algorithm is formed a system of linear diophantine equalities using the domain of computation which is given by the set of lattice points inside the polyhedron. Then is run the Mathematica program DiophantineGF.m. This program calculates the generating function from which is possible to find the number of solutions to the system of Diophantine equalities, which in fact gives the lower bound for the number of processors needed for the corresponding algorithm. There is given a mathematical explanation of the problem as well. Keywordsgenerating function, lattice points in polyhedron, lower bound of processor elements, system of Diophantine equationsand : calculus.

Keywords: generating function, lattice points in polyhedron, lower bound of processor elements, system of Diophantine equations and calculus.

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Authors: R. Ashok Bakkiyaraj, N. Kumarappan

Abstract:

This paper investigates the suitability of Latin Hypercube sampling (LHS) for composite electric power system reliability analysis. Each sample generated in LHS is mapped into an equivalent system state and used for evaluating the annualized system and load point indices. DC loadflow based state evaluation model is solved for each sampled contingency state. The indices evaluated are loss of load probability, loss of load expectation, expected demand not served and expected energy not supplied. The application of the LHS is illustrated through case studies carried out using RBTS and IEEE-RTS test systems. Results obtained are compared with non-sequential Monte Carlo simulation and state enumeration analytical approaches. An error analysis is also carried out to check the LHS method’s ability to capture the distributions of the reliability indices. It is found that LHS approach estimates indices nearer to actual value and gives tighter bounds of indices than non-sequential Monte Carlo simulation.

Keywords: Composite power system, Latin Hypercube sampling, Monte Carlo simulation, Reliability evaluation, Variance analysis.

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Authors: Ashly Joseph

Abstract:

Modern businesses struggle significantly to secure and manage their data properly as the volume and complexity of their data both expand exponentially. Through the use of a multi-layered defense strategy, a centralized management platform, and cutting-edge technologies like AI, this research paper presents a comprehensive framework to integrate data security and management. The constraints of current data protection and management strategies, technological advancements, and the evolving threat landscape are all examined in this article. It suggests best practices for putting into practice integrated data security and governance models, placing an emphasis on ongoing adaptation. The advantages mentioned include a strengthened security posture, simpler procedures, lower costs, and reduced complexity. Additionally, issues including skill shortages, antiquated systems, and cultural obstacles are examined. Security executives and Chief Information Security Officers are given practical advice on how to evaluate, plan, and put into place strong data-centric security and management capabilities. The goal of the paper is to provide a thorough study of the data security and management landscape and to arm contemporary businesses with the knowledge they need to be proactive in protecting their data assets.

Keywords: Data security, security management, cloud computing, cybersecurity, data governance, security architecture, data management.

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Authors: Ihor Trots, Yuriy Tasinkevych, Andrzej Nowicki, Marcin Lewandowski

Abstract:

In the paper the study of synthetic transmit aperture method applying the Golay coded transmission for medical ultrasound imaging is presented. Longer coded excitation allows to increase the total energy of the transmitted signal without increasing the peak pressure. Moreover signal-to-noise ratio and penetration depth are improved while maintaining high ultrasound image resolution. In the work the 128-element linear transducer array with 0.3 mm inter-element spacing excited by one cycle and the 8 and 16- bit Golay coded sequences at nominal frequency 4 MHz was used. To generate a spherical wave covering the full image region a single element transmission aperture was used and all the elements received the echo signals. The comparison of 2D ultrasound images of the tissue mimicking phantom and in vitro measurements of the beef liver is presented to illustrate the benefits of the coded transmission. The results were obtained using the synthetic aperture algorithm with transmit and receive signals correction based on a single element directivity function.

Keywords: Golay coded sequences, radiation pattern, signal processing, synthetic aperture, ultrasound imaging.

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Authors: Jui P. Hung, Yuan L. Lai, Hui T. You

Abstract:

Chatter vibration has been a troublesome problem for a machine tool toward the high precision and high speed machining. Essentially, the machining performance is determined by the dynamic characteristics of the machine tool structure and dynamics of cutting process, which can further be identified in terms of the stability lobe diagram. Therefore, realization on the machine tool dynamic behavior can help to enhance the cutting stability. To assess the dynamic characteristics and machining stability of a vertical milling system under the influence of a linear guide, this study developed a finite element model integrated the modeling of linear components with the implementation of contact stiffness at the rolling interface. Both the finite element simulations and experimental measurements reveal that the linear guide with different preload greatly affects the vibration behavior and milling stability of the vertical column spindle head system, which also clearly indicate that the predictions of the machining stability agree well with the cutting tests. It is believed that the proposed model can be successfully applied to evaluate the dynamics performance of machine tool systems of various configurations.

Keywords: Machining stability, Vertical milling machine, Linearguide, Contact stiffness.

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