Search results for: Michael Henry

Authors: Mabel Usunobun Olanipekun, Henry Ogbemudia Omoregbee

Abstract:

Anomalies such as water pipeline and hydraulic or petrochemical pipeline network leakages and bursts have significant implications for economic conditions and the environment. In order to ensure pipeline systems are reliable, they must be efficiently controlled. Wireless Sensor Networks (WSNs) have become a powerful network with critical infrastructure monitoring systems for water, oil and gas pipelines. The loss of water, oil and gas is inevitable and is strongly linked to financial costs and environmental problems, and its avoidance often leads to saving of economic resources. Substantial repair costs and the loss of precious natural resources are part of the financial impact of leaking pipes. Pipeline systems experts have implemented various methodologies in recent decades to identify and locate leakages in water, oil and gas supply networks. These methodologies include, among others, the use of acoustic sensors, measurements, abrupt statistical analysis etc. The issue of leak quantification is to estimate, given some observations about that network, the size and location of one or more leaks in a water pipeline network. In detecting background leakage, however, there is a greater uncertainty in using these methodologies since their output is not so reliable. In this work, we are presenting a scalable concept and simulation where a pressure-driven model (PDM) was used to determine water pipeline leakage in a system network. These pressure data were collected with the use of acoustic sensors located at various node points after a predetermined distance apart. We were able to determine with the use of correlation difference to determine the leakage point locally introduced at a predetermined point between two consecutive nodes, causing a substantial pressure difference between in a pipeline network. After de-noising the signal from the sensors at the nodes, we successfully obtained the exact point where we introduced the local leakage using the correlation difference model we developed.

Keywords: leakage detection, acoustic signals, pipeline network, correlation, wireless sensor networks (WSNs)

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Authors: Riccardo Bonazzi, Michaël Poli, Abeba Nigussie Turi

Abstract:

This paper presents an applied research of a new module for the financial administration and management industry, Personalizable and Automated Checklists Integrator, Overseeing Legal Investigations (PACIOLI). It aims at designing the business model of the trust company of the future. By identifying the key stakeholders, we draw a general business process design of the industry. The business model focuses on disintermediating the traditional form of business through the new technological solutions of a software company based in Switzerland and hence creating a new interactive platform. The key stakeholders of this interactive platform are identified as IT experts, legal experts, and the New Edge Trust Company (NATC). The mechanism we design and propose has a great importance in improving the efficiency of the financial business administration and management industry, and it also helps to foster the provision of high value added services in the sector.

Keywords: new edge trust company, business model design, automated checklists, financial technology

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Authors: Hsiao-ting Lin

Abstract:

This paper analyzes the history of Taiwan’s secret program to develop its nuclear weapons during the Cold War. In July 1971, US President Richard Nixon shocked the world when he announced that his national security adviser Henry Kissinger had made a secret trip to China and that he himself had accepted an invitation to travel to Beijing. This huge breakthrough in the US-PRC relationship was followed by Taipei’s loss of political legitimacy and international credibility as a result of its UN debacle in the fall that year. Confronted with the Nixon White House’s opening to the PRC, leaders in Taiwan felt being betrayed and abandoned, and they were obliged to take countermeasures for the sake of national interest and regime survival. Taipei’s endeavor to create an effective nuclear program, including the possible development of nuclear weapons capabilities, fully demonstrates the government’s resolution to pursue its own national policy, even if such a policy was guaranteed to undermine its relations with the United States. With hindsight, Taiwan’s attempt to develop its own nuclear weapons did not succeed in sabotaging the warming of US-PRC relations. Worse, it was forced to come to a full stop when, in early 1988, the US government pressured Taipei to close related facilities and programs on the island. However, Taiwan’s abortive attempt to develop its nuclear capability did influence Washington’s and Beijing’s handling of their new relationship. There did develop recognition of a common American and PRC interest in avoiding a nuclearized Taiwan. From this perspective, Beijing’s interests would best be served by allowing the island to remain under loose and relatively benign American influence. As for the top leaders on Taiwan, such a policy choice demonstrated how they perceived the shifting dynamics of international politics in the 1960s and 1970s and how they struggled to break free and pursue their own independent national policy within the rigid framework of the US-Taiwan alliance during the Cold War.

Keywords: taiwan, richard nixon, nuclear program, chiang Kai-shek, chiang ching-kuo

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Authors: Tegan H. Emerson, Colin C. Olson, George Stantchev, Jason A. Edelberg, Michael Wilson

Abstract:

Detecting small targets at range is difficult because there is not enough spatial information present in an image sub-region containing the target to use correlation-based methods to differentiate it from dynamic confusers present in the scene. Moreover, this lack of spatial information also disqualifies the use of most state-of-the-art deep learning image-based classifiers. Here, we use characteristics of target tracks extracted from video sequences as data from which to derive distinguishing topological features that help robustly differentiate targets of interest from confusers. In particular, we calculate persistent homology from time-delayed embeddings of dynamic statistics calculated from motion tracks extracted from a wide field-of-view video stream. In short, we use topological methods to extract features related to target motion dynamics that are useful for classification and disambiguation and show that small targets can be detected at range with high probability.

Keywords: motion tracks, persistence images, time-delay embedding, topological data analysis

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Authors: Michael Koblischka, Anjela Koblischka-Veneva, XianLin Zeng, Essia Hannachi, Yassine Slimani

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Superconducting foams of YBa2Cu3O7 (abbreviated Y-123) were produced using the infiltration growth (IG) technique from Y2BaCuO5 (Y-211) foams. The samples were investigated by SEM (scanning electron microscopy) and electrical resistivity measurements. SEM observations indicated the specific microstructure of the foam struts with numerous tiny Y-211 particles (50-100 nm diameter) embedded in channel-like structures between the Y-123 grains. The investigation of the excess conductivity of different prepared composites was analyzed using Aslamazov-Larkin (AL) model. The investigated samples comprised of five distinct fluctuation regimes, namely short-wave (SWF), one-dimensional (1D), two-dimensional (2D), three-dimensional (3D), and critical (CR) fluctuations regimes. The coherence length along the c-axis at zero-temperature (ξc(0)), lower and upper critical magnetic fields (Bc1 and Bc2), critical current density (Jc) and numerous other superconducting parameters were estimated from the data. The analysis reveals that the presence of the tiny Y-211 particles alters the excess conductivity and the fluctuation behavior observed in standard YBCO samples.

Keywords: Excess conductivity, Foam, Microstructure, Superconductor YBa2Cu3Oy

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Authors: Farha Lakhani, Michael J. Pont

Abstract:

There are two main architectures used to develop software for modern embedded systems: these can be labelled as “event-triggered” (ET) and “time-triggered” (TT). The research presented in this paper is concerned with the issues involved in migration between these two architectures. Although TT architectures are widely used in safety-critical applications they are less familiar to developers of mainstream embedded systems. The research presented in this paper began from the premise that–for a broad class of systems that have been implemented using an ET architecture–migration to a TT architecture would improve reliability. It may be tempting to assume that conversion between ET and TT designs will simply involve converting all event-handling software routines into periodic activities. However, the required changes to the software architecture are, in many cases rather more profound. The main contribution of the work presented in this paper is to identify ways in which the significant effort involved in migrating between existing ET architectures and “equivalent” (and effective) TT architectures could be reduced. The research described in this paper has taken an innovative step in this regard by introducing the use of ‘Design patterns’ for this purpose for the first time.

Keywords: embedded applications, software architectures, reliability, pattern

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Authors: Daniel F. Bohorquez, Luis M. Agudelo, Henry H. León

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Heart rate variability (HRV) is defined as the temporary variation between heartbeats or RR intervals (distance between R waves in an electrocardiographic signal). This distance is currently a recognized biomarker. With the analysis of the distance, it is possible to assess the sympathetic and parasympathetic nervous systems. These systems are responsible for the regulation of the cardiac muscle. The analysis allows health specialists and researchers to diagnose various pathologies based on this variation. For the acquisition and analysis of HRV taken from a cardiac electrical signal, electronic equipment and analysis software that work independently are currently used. This complicates and delays the process of interpretation and diagnosis. With this delay, the health condition of patients can be put at greater risk. This can lead to an untimely treatment. This document presents a single portable device capable of acquiring electrocardiographic signals and calculating a total of 19 HRV metrics. This reduces the time required, resulting in a timelier intervention. The device has an electrocardiographic signal acquisition card attached to a microcontroller capable of transmitting the cardiac signal wirelessly to a mobile device. In addition, a mobile application was designed to analyze the cardiac waveform. The device calculates the RR and different metrics. The application allows a user to visualize in real-time the cardiac signal and the 19 metrics. The information is exported to a cloud database for remote analysis. The study was performed under controlled conditions in the simulated hospital of the Universidad de la Sabana, Colombia. A total of 60 signals were acquired and analyzed. The device was compared against two reference systems. The results show a strong level of correlation (r > 0.95, p < 0.05) between the 19 metrics compared. Therefore, the use of the portable system evaluated in clinical scenarios controlled by medical specialists and researchers is recommended for the evaluation of the condition of the cardiac system.

Keywords: biological signal análisis, heart rate variability (HRV), HRV metrics, mobile app, portable device.

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Authors: Sean Paulsen, Michael Casey

Abstract:

In this work we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

Keywords: transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training

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Authors: Barry Aifesehi Aiworo, Henry Oriakhi

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This paper, examines the analysis of access pattern to school and travel risks among school children in Benin City, Edo State, Nigeria. The risk includes accident, molestation (sexually) and kidnapping. The objective of this paper are to examine the various means (modes) of transport to school; determine the type and incidences of risk experienced by school children in the study area; examine the risk incidences and ages of school children in the study area. Hypothesis which states that the types of risks encountered by school children are independent of means of transport was tested using the chi-square test (X2). A sampling ratio of twelve percent (12%) was taken from 396 schools in Benin City. By implication, 49 schools were randomly selected in Benin City for this research. A total of 42,053 students in the 49 schools constitute the sample frame for the research. Two percent (2%), 841 students were taken as the sample size. The use of stratified sampling method was applied by stratifying the study area (Benin City) into local governments- Egor, Ikpoba-Okha and Oredo. Thereafter, the lists of schools in the various local governments were obtained from the Ministry of Education before the schools for research were randomly chosen from each local government area. The analysis revealed that 6.7% of the total students interviewed have been involved in road accidents. 1.04% of the total respondents said at one time or the other that they have been kidnapped. Finally, the research found that travel is comparatively safe and believes this may be partly attributable to safer route to schools and school children being more familiar with the school journey. The research indicates that children aged between eleven and fifteen are most at risk of hit or knocked down on Benin City’s roads. These findings may help in planning and targeting road safety initiative (education, campaigns) in Benin City.

Keywords: accident, molestation (sexually), kidnapping, pedophile, pedestrian

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Authors: Franky Michael Hamonangan Siagian, Affan Maulana, Himawan Tri Bayu Murti Petrus, Widi Astuti

Abstract:

In this study, the feasibility of the direct electrowinning method was used to produce zero-valent iron from red mud. The bauxite residue sample came from the Tayan mine, Indonesia, which contains high hematite (Fe₂O₃). Before electrolysis, the samples were characterized by various analytical techniques (ICP-AES, SEM, XRD) to determine their chemical composition and mineralogy. The direct electrowinning method of red mud suspended in NaOH was introduced at low temperatures ranging from 30 - 110 °C. Variations of current density, red mud: NaOH ratio and temperature were carried out to determine the optimum operation of the direct electrowinning process. Cathode deposits and residues in electrochemical cells were analyzed using XRD, XRF, and SEM to determine the chemical composition and current recovery. The low-temperature electrolysis current efficiency on Redmud can reach 20% recovery at a current density of 920,945 A/m². The moderate performance of the process was investigated with red mud, which was attributed to the troublesome adsorption of red mud particles on the cathode, making the reduction far less efficient than that with hematite.

Keywords: red mud, electrochemical reduction, Iron production, hematite

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Authors: Henry Pariaman, Iwa Garniwa, Isti Surjandari, Bambang Sugiarto

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Availability of a complex system of thermal power plant is strongly influenced by the reliability of spare parts and maintenance management policies. A reliability-centered maintenance (RCM) technique is an established method of analysis and is the main reference for maintenance planning. This method considers the consequences of failure in its implementation, but does not deal with further risk of down time that associated with failures, loss of production or high maintenance costs. Risk-based maintenance (RBM) technique provides support strategies to minimize the risks posed by the failure to obtain maintenance task considering cost effectiveness. Meanwhile, condition-based maintenance (CBM) focuses on monitoring the application of the conditions that allow the planning and scheduling of maintenance or other action should be taken to avoid the risk of failure prior to the time-based maintenance. Implementation of RCM, RBM, CBM alone or combined RCM and RBM or RCM and CBM is a maintenance technique used in thermal power plants. Implementation of these three techniques in an integrated maintenance will increase the availability of thermal power plants compared to the use of maintenance techniques individually or in combination of two techniques. This study uses the reliability, risks and conditions-based maintenance in an integrated manner to increase the availability of thermal power plants. The method generates MPI (Priority Maintenance Index) is RPN (Risk Priority Number) are multiplied by RI (Risk Index) and FDT (Failure Defense Task) which can generate the task of monitoring and assessment of conditions other than maintenance tasks. Both MPI and FDT obtained from development of functional tree, failure mode effects analysis, fault-tree analysis, and risk analysis (risk assessment and risk evaluation) were then used to develop and implement a plan and schedule maintenance, monitoring and assessment of the condition and ultimately perform availability analysis. The results of this study indicate that the reliability, risks and conditions-based maintenance methods, in an integrated manner can increase the availability of thermal power plants.

Keywords: integrated maintenance techniques, availability, thermal power plant, MPI, FDT

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Authors: Zhaoxin Luo, Michael Zhu

Abstract:

In natural languages, there are always complex semantic hierarchies. Obtaining the feature representation based on these complex semantic hierarchies becomes the key to the success of the model. Several RNN models have recently been proposed to use latent indicators to obtain the hierarchical structure of documents. However, the model that only uses a single-layer latent indicator cannot achieve the true hierarchical structure of the language, especially a complex language like Chinese. In this paper, we propose a deep layered model that stacks arbitrarily many RNN layers equipped with latent indicators. After using EM and training it hierarchically, our model solves the computational problem of stacking RNN layers and makes it possible to stack arbitrarily many RNN layers. Our deep hierarchical model not only achieves comparable results to large pre-trained models on the Chinese short text classification problem but also achieves state of art results on the Chinese long text classification problem.

Keywords: nature language processing, recurrent neural network, hierarchical structure, document classification, Chinese

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Authors: Aviv Yaniv, Ron Ben Arosh, Nadav Gasner, Michael Konviser, Arbel Yaniv

Abstract:

This paper introduces two methods for the evaluation of Question Decomposition Meaning Representation (QDMR) as predicted by sequence-to-sequence model and COPYNET parser for natural language questions processing, motivated by the fact that previous evaluation metrics used for this task do not take into account some characteristics of the representation, such as partial ordering structure. To this end, several heuristics to extract such partial dependencies are formulated, followed by the hereby proposed evaluation methods denoted as Proportional Graph Matcher (PGM) and Conversion to Normal String Representation (Nor-Str), designed to better capture the accuracy level of QDMR predictions. Experiments are conducted to demonstrate the efficacy of the proposed evaluation methods and show the added value suggested by one of them- the Nor-Str, for better distinguishing between high and low-quality QDMR when predicted by models such as COPYNET. This work represents an important step forward in the development of better evaluation methods for QDMR predictions, which will be critical for improving the accuracy and reliability of natural language question-answering systems.

Keywords: NLP, question answering, question decomposition meaning representation, QDMR evaluation metrics

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Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

Abstract:

Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: convolution neural network, deep learning, malaria, thin blood smears

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Authors: Chu Chen, Giorgio Gotti, Tony Kang, Michael Wolfe

Abstract:

This study examines the role of codes of ethics in reducing the extent to which managers’ act opportunistically in reporting earnings. Corporate codes of ethics, by clarifying the boundaries of ethical corporate behaviors and making relevant social norms more salient, have the potential to deter managers from engaging in opportunistic financial reporting practices. In a sample of international companies, we find that the quality of corporate codes of ethics is associated with higher earnings quality, i.e., lower discretionary accruals. Our results are confirmed for a subsample of firms more likely to be engaging in opportunistic reporting behavior, i.e., firms that just meet or beat analysts’ forecasts. Further, codes of ethics play a greater role in reducing earnings management for firms in countries with weaker investor protection mechanisms. Our results suggest that corporate codes of ethics can be a viable alternative to country-level investor protection mechanisms in curbing aggressive reporting behaviors.

Keywords: corporate ethics policy, code of ethics, business ethics, earnings discretion, accruals

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Authors: Golnar Behzadi, Michael O'Sullivan, Tava Olsen, Abraham Zhang

Abstract:

By definition, increasing supply chain resilience improves the supply chain’s ability to return to normal, or to an even more desirable situation, quickly and efficiently after being hit by a disruption. This is especially critical in agribusiness supply chains where the products are perishable and have a short life-cycle. In this paper, we propose a resilience metric to capture and improve the recovery process in terms of both performance and time, of an agribusiness supply chain following either supply or demand-side disruption. We build a model that determines optimal supply chain recovery planning decisions and selects the best resilient strategies that minimize the loss of profit during the recovery time window. The model is formulated as a two-stage stochastic mixed-integer linear programming problem and solved with a branch-and-cut algorithm. The results show that the optimal recovery schedule is highly dependent on the duration of the time-window allowed for recovery. In addition, the profit loss during recovery is reduced by utilizing the proposed resilient actions.

Keywords: agribusiness supply chain, recovery, resilience metric, risk management

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Authors: Michael F. Mascolo

Abstract:

Western democratic traditions are being strained. Western nations are losing the common agonistic ground needed to engage in traditional forms of democracy – adversarial debate, voting, and the peaceful transfer of power. Political polarization among party elites has become commonplace. Because it seeks to resolve conflict through the integration of opposites, a dialectical approach to resolving partisan conflict offers the promise of helping political partisans bridge ideological divides. This paper contains an analysis of dialectical engagement as a collaborative alternative to adversarial politics. Dialectical engagement involves two broad phases: collaborative political problem-solving and dialectical problem-solving. The paper contains a description of an 18-month longitudinal study assessing the effectiveness of dialectical engagement as a method for bridging divides on contentious socio-political issues. The study shows how dialectical engagement produced dramatic consensus among a small group of individuals from different political orientations as they worked together to resolve the issue of capital punishment.

Keywords: collaborative democracy, dialectical thinking, capital punishment, partisan conflict

Procedia PDF Downloads 46

Authors: Franky Michael Hamonangan Siagian, Affan Maulana, Himawan Tri Bayu Murti Petrus, Panut Mulyono, Widi Astuti

Abstract:

In this study, the feasibility of the direct electrowinning method was used to produce zero-valent iron from red mud. The bauxite residue sample came from the Tayan mine, Indonesia, which contains high hematite (Fe₂O₃). Before electrolysis, the samples were characterized by various analytical techniques (ICP-AES, SEM, XRD) to determine their chemical composition and mineralogy. The direct electrowinning method of red mud suspended in NaOH was introduced at low temperatures ranging from 30 - 110 °C. Variations of current density, red mud: NaOH ratio and temperature were carried out to determine the optimum operation of the direct electrowinning process. Cathode deposits and residues in electrochemical cells were analyzed using XRD, XRF, and SEM to determine the chemical composition and current recovery. The low-temperature electrolysis current efficiency on Redmud can reach 20% recovery at a current density of 920,945 A/m². The moderate performance of the process was investigated with red mud, which was attributed to the troublesome adsorption of red mud particles on the cathode, making the reduction far less efficient than that with hematite.

Keywords: alumina, red mud, electrochemical reduction, iron production

Procedia PDF Downloads 48

Authors: Michael C. Nwaohia

Abstract:

Whereas anecdotal evidence supports the notion that increase in information technology (IT) know-how may enhance output of professionals in the accounting sector, this has not been systematically explored in the Nigerian context. Against this background, this paper examines the correlation between knowledgeability of IT and level of performance at everyday auditing and accounting tasks. It utilizes primary and secondary data from selected business organizations in Lagos, Nigeria. Accounting staff were administered structured questionnaires which, amongst other things, sought to examine knowledge and exposure to information technology prior to joining the firms and current level of performance based on self-reporting and supervisor comments. In addition, exposure to on-the-job IT training and current level of performance was examined. The statistical analysis of the data was done using the SPSS package. The results strongly suggest that prior exposure to IT skills enabled accounting professionals to better flexibly fit into the dynamic environment in which contemporary business takes place. Ultimately, the paper attempts to explicate some of the implications of these findings for individuals and business firms.

Keywords: accounting, firms, information technology, professional behavior

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Authors: D. A. Bruzon, G. Tapang, I. S. Martinez

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Global warming and climate change are significant environmental concerns, which require immediate global action in carbon emission mitigation. The capture, sequestration, and conversion of carbon dioxide to other products such as methane or ethanol are ways to control excessive emissions. Ionic liquids have shown great potential among the materials studied as carbon capture solvents and catalysts in the reduction of CO2. In this study, ionic liquids comprising of a methoxy (-OCH3) and cyano (-CN) functionalized imidazolium cation, [MOBMIM] and [CNBMIM] respectively, paired with tris(pentafluoroethyl)trifluorophosphate [FAP] anion were evaluated as effective capture solvents, and organocatalysts in the reduction of CO2. An in-situ electrochemical set-up, which can measure controlled amounts of CO2 both in the gas and in the ionic liquid phase, was used. Initially, reduction potentials of CO2 in the CO2-saturated ionic liquids containing the internal standard cobaltocene were determined using cyclic voltammetry. Chronoamperometric transients were obtained at potentials slightly less negative than the reduction potentials of CO2 in each ionic liquid. The time-dependent current response was measured under a controlled atmosphere. Reduction potentials of CO2 in methoxy and cyano-functionalized [FAP] ionic liquids were observed to occur at ca. -1.0 V (vs. Cc+/Cc), which was significantly lower compared to the non-functionalized analog [PMIM][FAP], with an observed reduction potential of CO2 at -1.6 V (vs. Cc+/Cc). This decrease in the potential required for CO2 reduction in the functionalized ionic liquids shows that the functional groups methoxy and cyano effectively decreased the free energy of formation of the radical anion CO2●⁻, suggesting that these electrolytes may be used as organocatalysts in the reduction of the greenhouse gas. However, upon analyzing the solubility of the gas in each ionic liquid, [PMIM][FAP] showed the highest absorption capacity, at 4.81 mM under saturated conditions, compared to [MOBMIM][FAP] at 1.86 mM, and [CNBMIM][FAP] at 0.76 mM. Also, calculated Henry’s constant determined from the concentration-pressure graph of each functionalized ionic liquid shows that the groups -OCH3 and -CN attached terminal to a C4 alkyl chain do not significantly improve CO2 solubility.

Keywords: carbon capture, CO2 reduction, electrochemistry, ionic liquids

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Authors: K. Adu Michael, K. Alese Boniface

Abstract:

Developing a reliable and sustainable software products is today a big challenge among up–coming software developers in Nigeria. The inability to develop a comprehensive problem statement needed to execute proper requirements engineering process is missing. The need to describe the ‘what’ of a system in one document, written in a natural language is a major step in the overall process of Software Engineering. Requirements Engineering is a process use to discover, analyze and validate system requirements. This process is needed in reducing software errors at the early stage of the development of software. The importance of each of the steps in Requirements Engineering is clearly explained in the context of using detailed problem statement from client/customer to get an overview of an existing system along with expectations from the new system. This paper elicits inadequate Requirements Engineering principle as the major cause of poor software development in developing nations using a case study of final year computer science students of a tertiary-education institution in Nigeria.

Keywords: client/customer, problem statement, requirements engineering, software developers

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Authors: Michael Okeke, Andrew Blyth

Abstract:

Supervisory Control And Data Acquisition (SCADA) as the state of the art Industrial Control Systems (ICS) are used in many different critical infrastructures, from smart home to energy systems and from locomotives train system to planes. Security of SCADA systems is vital since many lives depend on it for daily activities and deviation from normal operation could be disastrous to the environment as well as lives. This paper describes how No-Trust-Zone (NTZ) architecture could be incorporated into SCADA Systems in order to reduce the chances of malicious intent. The architecture is made up of two distinctive parts which are; the field devices such as; sensors, PLCs pumps, and actuators. The second part of the architecture is designed following lambda architecture, which is made up of a detection algorithm based on Particle Swarm Optimization (PSO) and Hadoop framework for data processing and storage. Apache Spark will be a part of the lambda architecture for real-time analysis of packets for anomalies detection.

Keywords: industrial control system (ics, no-trust-zone (ntz), particle swarm optimisation (pso), supervisory control and data acquisition (scada), swarm intelligence (SI)

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Authors: Helen Pushkarskaya, Michael Smithson, Jane E. Joseph, Christine Corbly, Ifat Levy

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Studies of decision making under uncertainty generally focus on imprecise information about outcome probabilities (“ambiguity”). It is not clear, however, whether conflicting information about outcome probabilities affects decision making in the same manner as ambiguity does. Here we combine functional Magnetic Resonance Imaging (fMRI) and a simple gamble design to study this question. In this design, the levels of ambiguity and conflict are parametrically varied, and ambiguity and conflict gambles are matched on both expected value and variance. Behaviorally, participants avoided conflict more than ambiguity, and attitudes toward ambiguity and conflict did not correlate across subjects. Neurally, regional brain activation was differentially modulated by ambiguity level and aversion to ambiguity and by conflict level and aversion to conflict. Activation in the medial prefrontal cortex was correlated with the level of ambiguity and with ambiguity aversion, whereas activation in the ventral striatum was correlated with the level of conflict and with conflict aversion. This novel double dissociation indicates that decision makers process imprecise and conflicting information differently, a finding that has important implications for basic and clinical research.

Keywords: decision making, uncertainty, ambiguity, conflict, fMRI

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Authors: Abigail Rosenberg, Jennifer Duan, Michael Poteuck, Chunshui Yu

Abstract:

The Barry M. Goldwater Range, West in southwestern Arizona encompasses 2,808 square kilometers of Sonoran Desert. The hyper-arid range has an annual rainfall of less than 10 cm with an average high temperature of 41 degrees Celsius in July to an average low of 4 degrees Celsius in January. The range shares approximately 60 kilometers of the international border with Mexico. A majority of the range is open for recreational use, primarily off-highway vehicles. Because of its proximity to Mexico, the range is also heavily patrolled by U.S. Customs and Border Protection seeking to intercept and apprehend inadmissible people and illicit goods. Decades of off-roading and Border Patrol activities have negatively impacted this sensitive desert ecosystem. To assist the range program managers, this study is developing a model to identify erosion prone areas and calibrate the model’s parameters using the Automated Geospatial Watershed Assessment modeling tool.

Keywords: arid lands, automated geospatial watershed assessment, erosion modeling, sedimentation modeling, watershed modeling

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Authors: Thabelo Nelushi, Michael Scurrell, Tumelo Seadira

Abstract:

Global warming is one of the most important environmental issues which arise from occurrence of gases such as carbon dioxide (CO2) and methane (CH4) in the atmosphere. Exposure to these greenhouse gases results in health risk. Hydrogen is regarded as an alternative energy source which is a clean energy carrier for the future. There are different methods to produce hydrogen such as steam reforming, coal gasification etc., however the challenge with these processes is that they emit CO and CO2 gases and are costly. Photocatalytic reforming is a substitute process which is fascinating due to the combination of solar energy and renewable sources and the use of semiconductor materials such as catalysts. TiO2 is regarded as the most promising catalysts. TiO2 nanoparticles prepared by hydrothermal method and Ag/TiO2 are being investigated for photocatalytic production of hydrogen from butanol. The samples were characterized by raman spectroscopy, TEM/SEM, XRD, XPS, EDAX, DRS and BET surface area. 2 wt% Ag-doped TiO2 nanoparticle showed enhanced hydrogen production compared to a non-doped TiO2. The results of characterization and photoactivity shows that TiO2 nanoparticles play a very important role in producing high hydrogen by utilizing solar irradiation.

Keywords: butanol, hydrogen production, silver particles, TiO2 nanoparticles

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Authors: Ian A. McCulloh, Madelaine Zinser, Jesse Patsolic, Michael Ramos

Abstract:

Recommender systems are a common artificial intelligence (AI) application. For any given input, a search system will return a rank-ordered list of similar items. As users review returned items, they must decide when to halt the search and either revise search terms or conclude their requirement is novel with no similar items in the database. We present a statistically designed experiment that investigates the impact of similarity ratings on human judgement to conclude a search item is novel and halt the search. 450 participants were recruited from Amazon Mechanical Turk to render judgement across 12 decision tasks. We find the inclusion of ratings increases the human perception that items are novel. Percent similarity increases novelty discernment when compared with star-rated similarity or the absence of a rating. Ratings reduce the time to decide and improve decision confidence. This suggests the inclusion of similarity ratings can aid human decision-makers in knowledge search tasks.

Keywords: ratings, rankings, crowdsourcing, empirical studies, user studies, similarity measures, human-centered computing, novelty in information retrieval

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Authors: Michael Miller, G. David Gearhart

Abstract:

The role of the American college presidency continues to evolve, increasingly incorporating varied elements of responsibility of institutional management. Once primarily focused on the academic operation of an institution, the role has changed to incorporate all of the business-related and public agency operations of an institution. This means that the modern college president must be capable of persuasively talking to legislators and donors, as well as students taking classes and the faculty who teach them. In addition to these dimensions, the contemporary college president must also be an expert on state and federal compliance issues, and must have the talent to steer marketing and public relations activities in a persuasive manner. This paper will report the findings of a spring 2020 survey of nearly 300 college presidents in the United States concerning their perceptions about the changing nature of the college presidency, with special consideration given to media relations, fundraising, business development, internationalization, and facility management.Survey results will be analyzed based on institutional type, gender, length of tenure in the presidential position, and career pathway to the presidency.

Keywords: college president, leadership, education management, neo-liberal higher education

Procedia PDF Downloads 91

Authors: Rich Osaretin Iyagbaye, Michael Osasele Omoigberale, Louis Aiwiegbenegbe Iyagbaye

Abstract:

Zooplankton communities of Ugbogui River at Ugbogui, Southwest Nigeria were investigated from August 2015 to April 2016. Four stations were studied from upstream to downstream with a distance of about 2 kilometres between each station. A total 10 species were identified; 5 copepods and 5 cladocerans in the following order of dominance: copepod > cladocera. A total zooplankton population of 272 individuals was recorded during the study period. Copepods and cladocera represented the predominant species (76.73% and 23.89% of the total zooplankton community respectively). Copepods and cladocera were dominated by both cycloid (77%) and bosmids (12.13%), respectively. The dominant copepod and Cladocera species were Tropocyclops prasinus and Bosmina longirostris representing 28.68% and 12.13% of the total zooplankton, respectively. The calculated diversity indices indicated that station 1 (1.992) was more diverse followed by station 4 (1.893), while zooplankton species in station 2 (1.4) were least diverse. Species richness was highest and lowest in stations 4 (2.015) and 2 (1.165) respectively. Community composition was similar at both stations 1 and 4, but varies seasonally across the four stations. Higher number and density was found during the wet season with a trend of declining proportion towards the dry months.

Keywords: abundance, diversity, population, species, Ugbogui river, zooplankton

Procedia PDF Downloads 153

Authors: M. Michael Gromiha, A. Mary Thangakani, Sandeep Kumar, D. Velmurugan

Abstract:

The main cause of several neurodegenerative diseases such as Alzhemier, Parkinson, and spongiform encephalopathies is formation of amyloid fibrils and plaques in proteins. We have analyzed different sets of proteins and peptides to understand the influence of sequence-based features on protein aggregation process. The comparison of 373 pairs of homologous mesophilic and thermophilic proteins showed that aggregation-prone regions (APRs) are present in both. But, the thermophilic protein monomers show greater ability to ‘stow away’ the APRs in their hydrophobic cores and protect them from solvent exposure. The comparison of amyloid forming and amorphous b-aggregating hexapeptides suggested distinct preferences for specific residues at the six positions as well as all possible combinations of nine residue pairs. The compositions of residues at different positions and residue pairs have been converted into energy potentials and utilized for distinguishing between amyloid forming and amorphous b-aggregating peptides. Our method could correctly identify the amyloid forming peptides at an accuracy of 95-100% in different datasets of peptides.

Keywords: aggregation, amyloids, thermophilic proteins, amino acid residues, machine learning techniques

Procedia PDF Downloads 583

Authors: Josef Wolfartsberger, Michael Heiml, Georg Schwarz, Sabrina Egger

Abstract:

Growing individualization and higher numbers of variants in industrial assembly products raise the complexity of manufacturing processes. Technical assistance systems considering both procedural and human factors allow for an increase in product quality and a decrease in required learning times by supporting workers with precise working instructions. Due to varying needs of workers, the presentation of working instructions leads to several challenges. This paper presents an approach for a multi-modal visualization application to support assembly work of complex parts. Our approach is integrated within an interconnected assistance system network and supports the presentation of cloud-streamed textual instructions, images, videos, 3D animations and audio files along with multi-modal user interaction, customizable UI, multi-platform support (e.g. tablet-PC, TV screen, smartphone or Augmented Reality devices), automated text translation and speech synthesis. The worker benefits from more accessible and up-to-date instructions presented in an easy-to-read way.

Keywords: assembly, assistive technologies, augmented reality, manufacturing, visualization

Procedia PDF Downloads 143